Publications

Abstract: During The Boreal Summer, Mesoscale Convective Systems Generated Over West Africa Propagate Westward And Interact With African Easterly Waves, And Dust Plumes Transported From The Sahel And Sahara By The African Easterly Jet. Once Off West Africa, The Vortices In The Wake Of These Mesoscale Convective Systems Evolve In A Complex Environment Sometimes Leading To The Development Of Tropical Storms And Hurricanes, Especially In September When Sea Surface Temperatures Are High. Numerical Weather Predictions Of Cyclogenesis Downstream Of West Africa Remains A Key Challenge Due To The Incomplete Understanding Of The Clouds-Atmospheric Dynamics-Dust Interactions That Limit Predictability. The Primary Objective Of The Clouds-Atmospheric Dynamics-Dust Interactions In West Africa (Caddiwa) Project Is To Improve Our Understanding Of The Relative Contributions Of The Direct, Semidirect, And Indirect Radiative Effects Of Dust On The Dynamics Of Tropical Waves As Well As The Intensification Of Vortices In The Wake Of Offshore Mesoscale Convective Systems And Their Evolution Into Tropical Storms Over The North Atlantic. Airborne Observations Relevant To The Assessment Of Such Interactions (Active Remote Sensing, In Situ Microphysics Probes, Among Others) Were Made From 8 To 21 September 2021 In The Tropical Environment Of Sal Island, Cape Verde. The Environments Of Several Tropical Cyclones, Including Tropical Storm Rose, Were Monitored And Probed. The Airborne Measurements Also Serve The Purpose Of Regional Model Evaluation And The Validation Of Spaceborne Wind, Aerosol And Cloud Products Pertaining To Satellite Missions Of The European Space Agency And Eumetsat (Including The Aeolus, Earthcare, And Iasi Missions).

Abstract: Three Convectively Active African Easterly Waves (Aews) That Propagated South Of The African Easterly Jet Were Observed Over The Northeast Atlantic Ocean In September 2021. Their Evolution Is Studied Using A Suite Of Theoretical Frameworks, As Well As The European Centre For Medium-Range Weather Forecast Reanalyses And Satellite-Derived Brightness Temperature Observations. The Environment Of These Aews Was Sampled During The Cloud-Atmospheric Dynamics-Dust Interactions In West Africa Campaign Near Cape Verde With The Goal To Assess Their Potential For Developing Into Tropical Cyclones. We Highlight The Processes That Inhibited The Development Of The First Aew (Which Evolved Into Tropical Disturbance Pierre-Henri) And That Played A Role In The Development Of The Later Two Into Tropical Storms Rose And Peter On September 19, 2021. The Three Aews Developed A So-Called “Marsupial Protective” Pouch. For Peter And Rose, The Pouch Was Associated With A Vertically Aligned Vortex At Low Levels And Efficiently Protected The Convective Systems Inside From Dry And Dusty Air Intrusion. The Development Of This Low-Level Vortex Is Associated With An Interaction With The Monsoon Trough For Rose And With A Vorticity Center Associated With A Wave Propagating North Of The African Easterly Jet (Aej) In The Case Of Peter. The Presence Of A Dust Flux Toward The Convective Core Near The Surface Is Highlighted For Rose And Peter In Spite Of The Presence Of The Protective Marsupial Pouch. On The Other Hand, Pierre-Henri Interacted Positively With Both The Monsoon Trough And An Aew North Of The Aej But Failed To Develop Into A Tropical Cyclone. The Wave North Of The Aej Brought Saharan Air Layer Air Masses Inside The Pouch That Led To A Drying Of The Circulation That May Explain The Decrease In Convective Activity. We Used Different Methods To Analyse The Processes That Helped Or Inhibited The Development Of Three African Easterly Waves (Aews) Into Tropical Cyclones. A Wave Pouch Structure That Protects A Convective System Moving With The Wave Is Observed In The Three Cases And Studied Within The Marsupial Paradigm Framework. The Development Of An Aligned Vortex At Low Levels, Either By Interaction With The Monsoon Trough Or Between Aews North And South Of The African Easterly Jet, Are Highlighted. In One Case, The Latter Interaction Caused The Intrusion Of Dry Air That Might Have Inhibited Cyclogenesis. Image

Abstract: Water And Disaster Risk Management Require Accurate Information About Hydrometeorological Extremes. However, Estimation Of Rare Events Using Extreme Value Analysis Is Hampered By Short Observational Records, With Large Resulting Uncertainties. Here, We Present A Surrogate World Setup That Makes Use Of Data Samples From Meteorological And Hydrological Seasonal Re-Forecasts To Explore Extremes For Long Return Periods. The Surrogate Timeseries Allow Us To Pool The Re-Forecasts Into 1000-Year-Long Timeseries. We Can Then Calculate Return Values Of Extremes And Explore How They Are Affected By The Size Of Sub-Samples As Method For Estimating The Uncertainty. The Approach Relies On The Fact That Probabilistic Seasonal Re-Forecasts, Initialized With Perturbed Initial Conditions, Have Limited Predictive Skill With Increasing Lead Time. At Long Lead Times Re-Forecasts Will Diverge Into Independent Samples. The Meteorological Seasonal Re-Forecasts Are Taken From The Seas5 System, And Hydrological Re-Forecasts Are Generated With The E-Hype Process-Based Model For The Pan-European Domain. Extreme Value Analysis Is Applied To Annual Maxima Of Precipitation And Streamflow For Return Periods Of 100 Years. The Analysis Clearly Demonstrates The Large Uncertainty In Long Return Period Estimates With Typical Available Samples Of Only Few Decades. The Uncertainty Is Somewhat Reduced For 100-Year Samples, But Several 100 Years Seem To Be Necessary To Have Robust Estimates. The Bootstrap With Replacement Approach Is Applied To Shorter Timeseries, And Is Shown To Well Reproduce The Uncertainty Range Of The Longer Samples. However, The Main Estimate Of The Return Value Can Be Significantly Offset. Although The Method Is Model Based, With The Associated Uncertainties And Bias Compared To The Real World, The Surrogate Approach Is Likely Useful To Explore Rare And Compounding Extremes. A Method To Generate 1000-Of-Years Long Surrogate Timeseries For Assessing Extreme Streamflow Using Seasonal Forecast Data Is Presented. Illustrative Cases Compare Conventional Bootstrap Method On Single Shorter Timeseries To The Surrogate Data, And Show A Rather Good Sampling Of The Uncertainty, But A Lack Of Precision For The Expected Value. Image

Abstract: The Accumulation Of Dust On The Surface Of Solar Panels Reduces The Amount Of Sunlight Reaching The Solar Cells And Results In A Decrease In Panel Performance. To Avoid This Loss Of Production And Thus, To Improve The Performance Capacity, Solar Panels Must Be Cleaned Frequently. The West African Region Is Well Known For Its High Solar Energy Potential. However, This Potential Can Be Reduced By The High Occurrence Of Dust Storms During The Year. This Article Aims To Provide A Contribution To The Construction Of A Meteorological Information Service For Solar Panel Cleaning Operations At Diass Solar Plant In Senegal (Western Sahel). It Is Based On A Full Year In Situ Experiment Comparing The Power Loss Due To Dust Between Solar Panels Cleaned At Different Frequencies And Those Not Cleaned. The Model To Determine The Cleaning Frequencies Is Based On The Deposition Rate Of Airborne Particles, The Concentration Of Airborne Particles, And The Density Of The Dust That Has A Major Impact On The Power Loss. Cleaning Frequencies Are Presented At Seasonal Scale Because In The Study Area, Dust Episodes Differ According To The Seasons. A Cost-Benefit Analysis Is Also Performed To Demonstrate The Advantage Of Using Weather Information Service To Support The Dust Cleaning Operations At Diass Plant. As Results, It Is Found That Cleaning Every 3 Weeks Is Required During The Dry Seasons, December-January-February And March-April-May. During The Rainy Season, Cleaning Every 5 Weeks Is Recommended In June-July-August, While In September-October-November Cleaning Every 4 Weeks Is Sufficient To Maintain An Optimal Performance Of The Solar Panel. The Total Costs Of Cleaning Operations Based On These Results Are Reduced Compared To The Current Costs Of Cleaning And The Benefits Are Much Higher Than Without Cleaning Action.

Abstract: Devastating Floods Have Plagued Many West African Cities In The Past Decades. In An Attempt To Reduce Flood Damage In Bamako (Mali), An Early Warning System (Ews) Demonstrator (Raincell App) Was Developed For Flash Floods. On 16 May 2019, While The Demonstrator Was Partially Operational, An Intense Rainfall Event Led To Devastating Floods. We Carried Out An Experience Feedback On This Flood Event By Comparing Ews Simulations To The Results Of A Field Survey. Given The Synoptic Situation And The Rapid Development Pattern Of The Storm, None Of The Global Forecasting Systems Were Able To Foresee Its Occurrence And Magnitude. The Hydrological Model Developed As Part Of The Demonstrator Correctly Identified Most Of The Locations Where Overbank Flow Occurred. In The Absence Of Data, The Predicted Discharge And Volume Values Could Not Be Validated. However, They Are Realistic Based On The Water Levels Reported In The Post-Disaster Needs Assessment Report. It Would Be Advisable To Couple It To A Two-Dimensional Hydraulic Model And Add Discharge And Water Level Monitoring To The Already Existing Rainfall Surveillance Scheme To Further Improve The System'S Performance. Increasing The Local Population'S Awareness Of The Dangers Of Clogged Waterways Is Also Mandatory.

Abstract: Analytical Multiplicative Random Cascades (Mrcs) Are Widely Used For The Temporal Disaggregation Of Coarse-Resolution Precipitation Time Series. This Class Of Models Applies Scaling Models To Represent The Dependence Of The Cascade Generator On The Temporal Scale And The Precipitation Intensity. Although Determinant, The Dependence On The External Precipitation Pattern Is Usually Disregarded In The Analytical Scaling Models. Our Work Presents A Unified Mrc Modelling Framework That Allows The Cascade Generator To Depend In A Continuous Way On The Temporal Scale, Precipitation Intensity And A So-Called Precipitation Asymmetry Index.Different Mrc Configurations Are Compared For 81 Locations In Switzerland With Contrasted Climates. The Added Value Of The Dependence Of The Mrc On The Temporal Scale Appears To Be Unclear, Unlike What Was Suggested In Previous Works. Introducing The Precipitation Asymmetry Dependence Into The Model Leads To A Drastic Improvement In Model Performance For All Statistics Related To Precipitation Temporal Persistence (Wet-Dry Transition Probabilities, Lag-N Autocorrelation Coefficients, Lengths Of Dry-Wet Spells). Accounting For Precipitation Asymmetry Seems To Solve This Important Limitation Of Previous Mrcs.The Model Configuration That Only Accounts For The Dependence On Precipitation Intensity And Asymmetry Is Highly Parsimonious, With Only Five Parameters, And Provides Adequate Performances For All Locations, Seasons And Temporal Resolutions. The Spatial Coherency Of The Parameter Estimates Indicates A Real Potential For Regionalisation And For Further Application To Any Location In Switzerland.

Abstract: Three Coupled Model Intercomparison Project 5 (Cmip5) Models That Simulated The G4 Experiment Of The Geoengineering Model Intercomparison Project (Geomip) Were Used To Investigate The Impact Of Stratospheric Aerosol Injection (Sai) On Combined Temperature And Precipitation Extremes In Africa That Can Have Greater Negative Impacts On Human And The Environment Than Individual Rainfall Or Temperature Extremes. The Examined Compound Extremes Included The Dry (R-Warm Vertical Bar Dry And R-Cold Vertical Bar Dry) And Wet (R-Warm Vertical Bar Wet And R-Cold Vertical Bar Wet) Modes Assessed During The Injection (Sai, 2050-2069) And Post-Injection (Postsai, 2070-2089) Periods Compared With The Historical Period (1986-2005). We Found A Significant Projected Change In The Occurrence Of Both Wet And Dry Modes During Sai And Postsai Related To The Historical Period. The Magnitude And Sign Of This Change Depend On The Season And The Geographical Location. During The Sai And Postsai, The Wet (R-Warm Vertical Bar Wet And R-Cold Vertical Bar Wet) Modes Are Projected To Be Significantly Lower While The Dry Modes Are Noted To Increase In A Large Part Of African Continent Depending On The Season And The Geographical Location And May Consequently Leads To An Increase Of The Droughts Prone Areas. The Termination Effect Is Noted To Reduce The Occurrence Of Dry Modes, Which May Reduce The Potential Negative Effects Of The Injection After Halting. As The Effect May Vary From One Region To Another And According To The Season, It Suggested Assessing The Key Sector Impacts Of Sai. Thus, This Change In Dry Modes Due To Sai Could Affect All Activities Which Depend On Water Resources Such As Water Supply, Agriculture And Food Production, Energy Demand, And Production With Adverse Effects On Health, Security, And Sustainable Development, But This Needs To Be Assessed And Quantified At Regional Scales.

Abstract: Hydrological Modelling To Support Hypotheses On Earth System Boundaries Or The Accelerating Water Crisis Is Nowadays Done At The Global Scale, With Difficulties Associated To Model Uncertainties. Here We Bring A Robustness Analysis Of Internal Model Variables As An Additional Tool For Model Evaluation Using Data From Six Earth Observation Products And The Global Catchment Model World-Wide Hype In A Comparative Study. The Assessment Shows That: (I) Variables Have High Agreement In Mid-Latitude Temperate Regions; (Ii) The Variables With Higher Agreement, And Associated With Good Model Performance In Streamflow, Were Actual Evapotranspiration, Fractional Snow Cover And Snow Water Equivalent; And (Iii) Changes In Total Water Storage Showed Very Poor Agreement, Probably Due To An Insufficient Number Of Aquifers In The Model Set-Up. We Propose This Procedure As A Standard Complementary Method In Global Hydrological Modelling, Highlighting The Importance Of Justifying Models Before Using Them For Scenario Analysis Or Water Accounting.

Abstract: A Rare Dataset Of In-Situ Be-10 From High-Resolution Depth Profiles, Soils, Rock Outcrops, And Stream Sediments Is Combined With Geochemical Analysis And Modelling Of Regolith Evolution To Understand The Variability Of Denudation Rates In A Mountain Watershed (Strengbach Critical Zone Observatory). High-Resolution Depth Profiles Are Key To Detect The Presence Of Mobile Regolith And To Highlight How It Affects The Critical Zone Evolution. The Modelling Of Regolith Evolution And Be-10 Concentrations Along Depth Profiles Allow Us To Estimate Both The Cosmic Ray Exposure Age (19 Kyr) And The Mean Denudation Rate (22 Mm Kyr(-1)) Of The Regolith Without Any Steady-State Assumption On Be-10 Concentrations. Comparison With Maximum Denudation Rates Inferred From Topsoil Samples Collected From The Surface Of The Depth Profiles And Calculated Using The Temporal Steady-State Assumption Of Be-10 Concentrations Highlights An Overestimation Of Denudation By A Factor Of Two. Maximum Spatially Averaged Denudation Rates Determined From Stream Sediment Samples Also Likely Overestimate Denudation Rates By A Factor Of Two. These Biases Are Significant For Investigating The Geomorphological Evolution And We Propose A Method To Correct Denudation Rates Using The Inherited Be-10 Concentrations And The Cosmic Ray Exposure Age Deduced From The High-Resolution Depth Profiles. A Key Result Is Also That A Steady State Of Be-10 Concentrations And A Steady State Of Regolith Thickness Are Two Different Equilibrium States That Do Not Necessarily Coincide. The Comparison Between Locally Corrected And Spatially Averaged Denudation Rates Indicates That The Watershed Geomorphology Is Not In A Topographic Steady State But Is Modulated By Regressive Fluvial Erosion. Nonetheless, Our Study Demonstrates That Even In A Watershed Where The Steady-State Assumption Of Be-10 Concentrations Is Not Verified, The Spatial Variations Of In-Situ Be-10 Concentrations In Sediments Still Carry Qualitatively Relevant Information On The Geomorphological Evolution Of Landscapes.

Abstract: Rainfall is a key driver of geomorphological processes ranging from impacting drops that lead to the small-scale dislodgement of soil particles to large-scale morphogenic floods and rainfall-induced hillslope processes. Although rainfall has been identified in seismic records, the associated power spectral density and its quantitative relation to the underlying physical processes have not yet been studied. Here, we analyze nearly 2 years of combined seismic and optical disdrometer measurements, where the latter enables the drop-based quantification of rainfall physical properties. Our measurements confirm the broadband observation of ground velocity power spectral density due to rainfall, allowing the seismic identification of rainfall at intensities as low as 1 mm/h. Seismic power, P, shows a power-law scaling with rainfall intensity, I, and kinetic energy, E: P proportional to I-2.1 and P proportional to E-1.6. The observed scaling relations are consistent between the three monitored sites although there are absolute differences in seismic power of about 1 order of magnitude, which are likely due to variability in landcover and subsurface seismic properties. With a physical model, we demonstrate that the observed power-law relations are set by an underlying linear relation between seismic power and rainfall impulse power, and that the associated exponent values of I and E are due to the covariance of the raindrop size distribution with the total number of drops. The largest raindrop fractions, whose relative contribution increases with rainfall intensity, dominate the seismic signal where, in our case, 90% of the seismic power is attributed to drops larger than 3 mm. Using our model, we estimate the contributing area of rainfall to seismic observations to be within a radial distance of -5-25 m. The spatially integrated nature of the seismic measurements and their sensitivity to large raindrops, which control the disaggregation and the mobilization of soil particles, make seismic records well-suited for the investigation of soil erosion processes. More generally, our work provides a basis for the temporally-resolved seismic quantification of rainfall that drives the dynamics of various hydro-geomorphological processes.

Abstract: In this letter we show the emergence of an agreement between the instruments of a rain-gauge network to point toward a positive trend in daily precipitation extremes since 1960 in the French Mediterranean Region. We identify for each gauge the time varying parameters of the generalized extreme value distribution of annual maximum precipitation over incremental time-windows. These distributions provide for each station of the network a trend assessment over a chosen period that can be interpreted for instance as a trend of the mean or as the trend of a chosen quantile. The incremental window, i.e. a window containing the series of data available at a given date, mimics the annual assessment of the trends that could have been made through time. Each year we thus have one trend per gauge that we can look in distribution through the network in order to assess the level of consensus among instruments. We show how the increasing size of the datasets used over a period of possible climate non-stationarity progressively leads from a dissensus anarchically pointing to no trend (before the 2000s) to a consensus where a majority of gauges points toward a positive trend (after the 2000s). The detected trend in this Mediterranean Region is quite substantial. For instance the 20 year return period precipitation in 1960 turns out to become a 8 year return period precipitation in 2020. Using a simulation basis we try to characterize the effect of decadal variability that is quite readable in the consensus evolution. The proposed metrics is thought to be a good candidate for the assessment of the local time and rate of emergence of climate change that has important implications in regards to adaptation of human and natural systems.

Abstract: This study aims to characterize the impacts of the Sahel-Sahara interface reforestation on compound extremes in the Sahel region during the West African monsoon season (June-July-August-September, JJAS). For this purpose, we performed a simulation with the standard version of the RegCM4 model, and another simulation with the altered version of the same model, taking into account the incorporated forest. Results show that reforestation may strongly influence the frequency of individual extreme events (dry and warm days) by decreasing them over and off the reforested zone. The reduction in these extreme dry and warm days may be due partly to the strengthening of the atmospheric moisture content over most parts of the West African domain and the weakening of the sensible heat flux south of 16 degrees N. The analysis also shows an increase in extreme wet days over and off the reforested zone, which could be associated partly with the strengthening of evapotranspiration over most parts of the West African domain, including the reforested area. The analysis of compound extremes shows a strong occurrence of the compound dry/warm mode over the northern Sahel for both runs, probably due to the weak precipitation recorded in this zone. Both experiments also simulated a strong compound wet/warm mode occurrence over the Sahel due to a high rainfall occurrence over this region. When comparing both runs, the impact of the reforestation was to decrease (increase) the compound extreme dry/warm (wet/warm) mode over the reforested zone. The dry/warm mode decrease is consistent with that of individual extreme dry and warm days, while the compound wet/warm mode increase may be driven by that of the extreme wet days. Finally, when considering the seasonal cycle, the dry/warm mode exhibits a more substantial decrease in the beginning (June-July, JJ) than during the peak of the West African summer monsoon season (August-September, AS). Moreover, reforestation similarly affects the compound wet/warm mode in JJ and AS by increasing it in the reforested region and decreasing it over the Southern Sahel (south of 15 degrees N). This work suggests that reforestation may be a good solution for West African policymakers to mitigate climate change over the region and to develop better strategies for water resource management.

Abstract: This paper deals with the identification of extreme multiscale flooding events in the Alpine conurbation of Grenoble, France. During such events, typically over one to several days, the organization in space and time of the generating hydrometeorological situation triggers the concurrent reaction of varied sets of torrents and main rivers and creates diverse socioeconomic damages and disruptions. Given the limits of instrumental data over the long run, in particular at the torrent scale, we explore the potential of a database of reported extreme flood events to study multiscale flooding over a Metropolitan domain. The definition of Metropolitan events is mainly based on the database built by the RTM (Restauration des Terrains de Montagne, a technical service of the French Forest Administration). Relying on expert reports, the RTM database covers the long lifetime of this French national service for the management of mountainous areas (1850-2019). It provides quantitative information about the time and place of inundation events as well as qualitative information about the generating phenomena and the consequent damages. The selection process to define Metropolitan events simply chronologically explores the RTM database and complements it with historical research data. It looks for concurrence between site events at the same date under a chosen set of criteria. All scales together, we selected 104 Metropolitan events between 1850 and 2019. Exploring the list of dates, we examine the homogeneity of the Metropolitan events over 1850-2019 and their space-time characteristics. We evidence the existence of multiscale flooding at the Metropolitan scale, and we discuss some implications for flood risk management.

Abstract: A climatic anomaly can potentially affect the hydrological behaviour of a catchment for several years. This article presents a new approach to quantifying this multi-year hydrological memory, using exclusively streamflow and climate data. Rather than providing a single value of catchment memory, we aim to describe how this memory fades over time. The precipitation-runoff relationship is analyzed through the concept of elasticity. Elasticity quantifies the change in one quantity caused by the change in another quantity. We analyze the elasticity of the relation between the annual anomalies of runoff yield and humidity index. We identify Catchment Forgetting Curves (CFC) to quantify multiyear catchment memory, considering not only the current year's humidity anomaly but also the anomalies of the preceding years. The variability of CFCs is investigated on a set of 158 Swedish and 527 French catchments. As expected, French catchments overlying large aquifers exhibit a long memory, i.e., with the impact of climate anomalies detected over several years. In Sweden, the expected effect of the lakes is less clear. For both countries, a relatively strong relationship between the humidity index and memory is identified, with drier regions exhibiting longer memory. Taking into account the multi-year memory has significantly improved the elasticity analysis for 15 % of the catchments. Our work thus underlines the need to account for catchment memory in order to produce meaningful and geographically coherent elasticity indices.

Abstract: This Study Aims To Characterize Changes In Compound Extremes Of Rainfall And Temperature Over West Africa. For This Purpose, Data From Chirps Observations, The Era5 Reanalysis, And Twenty-Four (24) Climate Models Involved In The Cmip5 Project Were Analyzed. First, Climate Models Were Evaluated In Terms Of Their Capacity To Simulate Summer Mean Climatology And Compound Extremes During The Historical Period (1981-2005), And Secondly, Changes In Compound Extremes Were Examined Under Rcp8.5 Emission Scenario Between The Near Future (2031-2055) And The Far Future (2071-2095) Relative To The Historical Period. Despite The Presence Of Some Biases, The Ensemble Mean Of The Models Well Reproduces The Compound Extremes Patterns Over West Africa At The Seasonal And Intraseasonal Timescales. The Analysis Over The Historical Period With Chirps/Era5 Dataset Shows A Strong Occurrence Of The Dry/Warm Mode Over The Northern Sahel During The June-July-August-September Period (Jjas; Main Rainy Season) And Over The Guinean Region During The February-March-April-May Season (Fmam; First And Main Rainy Season). These Strong Occurrences Are Due To A Weak And Highly Frequent Precipitation Recorded In These Zones. The Compound Wet/Warm Mode Is Frequent In Jjas Over The Sahel And The Sudanian Zone (Transition Area Between Sahel And Guinean Regions), While In Fmam, Its Occurrence Is Maximum Over The Guinean Region. The Study Also Shows That The Dry/Warm Mode Will Increase In The Whole Sahel (Western And Central) And In The Guinean Zone In The Near And Far Futures While The Compound Wet/Warm Mode Will Decrease In The Whole Region. This Study Suggests That The West Africa Region Will Be Prone To Drought Intensified By Warmer Temperatures And Calls For Climate Action And Adaptation Strategies To Mitigate The Risks On Rain-Fed Agriculture, Energy, And On Animals And Human Health.

Abstract: In this article, we compare the performance of three regionalization approaches in improving the at-site estimates of daily precipitation. The first method is built on the idea of conventional RFA (regional frequency analysis) but is based on a fast algorithm that defines distinct homogeneous regions relying on their upper-tail similarity. It uses only the precipitation data at hand without the need for any additional covariate. The second is based on the region-of-influence (ROI) approach in which neighborhoods, containing similar sites, are defined for each station. The third is a spatial method that adopts generalized additive model (GAM) forms for the model parameters. In line with our goal of modeling the whole range of positive precipitation, the chosen marginal distribution model is the extended generalized Pareto distribution (EGPD) to which we apply the three methods. We consider a dense network composed of 1176 daily stations located within Switzerland and in neighboring countries. We compute different criteria to assess the models' performance in the bulk of the distribution and the upper tail. The results show that all the regional methods offered improved robustness over the local EGPD model. While the GAM method is more robust and reliable in the upper tail, the ROI method is better in the bulk of the distribution.

Abstract: Hyperspectral imaging (HSI) isa non-destructive, high-resolution imaging technique that is currently under significant development for analyzing geological areas with remote devices or natural samples in a laboratory. In both cases, the hyperspectral image provides several sedimentary structures that must be separated to temporally and spatially de-scribe the sample. Sediment sequences are composed of successive deposits (strata, homogenite, flood) that are visible depending on sample properties. The classical methods to identify them are time-consuming, have a low spatial reso-lution (millimeters) and are generally based on naked-eye counting. In this study, we compare several supervised clas-sification algorithms to discriminate sedimentological structures in lake sediments. Instantaneous events in lake sediments are generally linked to extreme geodynamical events (e.g., floods, earthquakes), so their identification and counting are essential to understand long-term fluctuations and improve hazard assessments. Identification and counting are done by reconstructing a chronicle of event layer occurrence, including estimation of deposit thicknesses. Here, we applied two hyperspectral imaging sensors (Visible Near-Infrared, VNIR, 60 μm, 400-1000 nm; Short Wave Infrared, SWIR, 200 μm, 1000-2500 nm) on three sediment cores from different lake systems. We highlight that the SWIR sensor is the optimal one for creating robust classification models with discriminant analyses (prediction accu-racies of 0.87-0.98). Indeed, the VNIR sensor is impacted by the surface reliefs and structures that are not in the learn-ing set, which causes mis-classification. These observations are also valid for the combined sensor (VNIR-SWIR) and the RGB images. Several spatial and spectral pre-processing were also compared and enabled one to highlight discriminant information specific to a sample and a sensor. These works show that the combined use of hyperspectral imaging and machine learning improves the characterization of sedimentary structures compared to conventional methods.

Abstract: The influence of soil moisture initial conditions on the climate extreme indices over West Africa was investigated using the fourth generation of the International Centre for Theoretical Physics regional climate model (non-hydrostatic) coupled with version 4.5 of the Community Land Model (RegCM4-CLM4.5) at a 25 km spatial resolution. We initialized the control experiments with the reanalysis soil moisture data from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis of the 20th century (ERA-20C), while we initialized the dry and wet experiments with the maximum and minimum soil moisture values over the West Africa domain, respectively. For each experiment, an ensemble of five runs was performed for 5 years (2001-2005) with soil moisture initial conditions for the runs prescribed on 1 June and the simulations being performed over 4 months (122 d) from June to September. The performance of RegCM4-CLM4.5 with respect to simulating the 10 extreme rainfall and temperature indices used in this study is presented. The results are then discussed for the two idealized simulations that are most sensitive to the dry and wet soil moisture initial conditions in order to highlight the impacts beyond the limits of soil moisture internal forcing in the model. Over the Central Sahel, dry (wet) experiments lead to a decrease (increase) in precipitation extreme indices related to the number of events, but this was not seen for indices related to the intensity of the events. Soil moisture initial conditions unequally affect the daily minimum and maximum temperatures. The strongest impact is found on the maximum temperature: wet (dry) experiments decrease (increase) the maximum temperature over the whole region. Over the Central Sahel, wet (dry) experiments lead to a decrease (increase) in the maximum values of the minimum temperature.

Abstract: Climate change is projected to negatively affect water security which is already a challenge in many areas of Ghana including the Tano river basin (TRB). This study assessed the projections of rainfall and temperature and its impact on streamflow and actual evapotranspiration (ET) in the TRB of Ghana for 2021-2050 relative to the period 1986-2015. The impact assessment focused on how climate change under Representative Concentration Pathways (RCP 4.5 and RCP8.5) based on an ensemble mean of two regional climate models (RCMs) would affect streamflow and ET using the Soil and Water Assessment Tool (SWAT) model. Trend analysis and quantification for the streamflow and ET were analyzed using the Mann-Kendall's and Sen's slope estimators. The results show that the mean annual rainfall of 1401.9 mm would increase slightly by 0.5 % with a decreasing trend (1.22mm/yr) under the RCP4.5 scenario, but would decrease by 3.2% with a decreasing trend (0.3m mm/yr) under the RCP8.5 scenario. The mean annual temperature showed an increase (2.1 degrees C and 2.6 degrees C) with a statistically significant increasing trend of 0.07 and 0.09 degrees C/yr under RCP 4.5 and RCP8.5 respectively. An increase in ET with a non-significant increasing trend at a rate of 0.74 and 1.07 mm/year under RCP4.5 and RCP8.5 scenarios respectively is also projected. The mean annual streamflow is projected to decrease, with the decrease been more pronounced under the RCP8.5 (37.5%) scenario compared to the RCP4.5 scenario (19.9%). In general, the outcome of this study presents a useful perspective on the vulnerability of water resources to climate change and the need for better planning and management of the water resources in the basin. (C) 2021 The Author(s). Published by Elsevier B.V. on behalf of African Institute of Mathematical Sciences / Next Einstein Initiative.

Abstract: This study aims to review the existing literature on the past and future effects of climate, land use, and land cover changes on hydropower generation in West Africa (WA), based on listings in the Scopus and Google Scholar databases. This review shows that several African hydropower plants have experienced repeated power disruptions over the last three decades due to climate change and variability but it is less documented how increasing land use and land cover changes around the major dams have impacted the hydrological system and the hydropower generation. In the future, the risks of hydropower in WA may not be equally distributed within a country or region. Despite uncertainties in precipitation and on impacts on streamflow and water level in major basins, climate change is likely to reduce the available water over the range of 10%-20% (15%-40%) for the RCP4.5 (RCP8.5) scenario by 2050, which may considerably affect the water demand across all sectors, including hydropower. However, in the Kainji dam (Niger River basin), models project an increase in rainfall favorable to hydropower production for both RCP4.5 and RCP8.5. In contrast, within the Black Volta sub-basin, the intensification of land use is predicted to favor runoff and, consequently, an increase in the generation of Bui hydropower in the near future, even though models predict a rainfall decrease. This increase in land use for agriculture to feed a growing population has other adverse effects that need to be assessed, namely sedimentation and siltation, which are harmful to hydropower plants. Finally, the combined impact of climate and land use changes on the efficiency of hydroelectric infrastructure in WA is not well documented, while sustainable planning and investments in the hydropower sector require consideration of the nexus between climate, land use changes, and water.

Abstract: Climate change (CC) and variability impacts on hydroelectric generation have become critical for hydropower management. The trends of inflow, outflow, reservoir water level, and storage as well as hydraulicity indices of three main dams in Cote d'Ivoire, namely Kossou and Taabo in the Bandama basin and Buyo in the Sassandra basin were examined during 1981-2017 and their impacts on hydropower generation were analyzed. Moreover, the hydropower generation sensitivity to CC of these dams was assessed using statistical analysis. The results reveal that the inflow is highly dependent on rainfall while the water level is highly influenced by the outflow, which is a function of the inflow to the reservoirs and water management policy. Furthermore, the Mann Kendall test revealed that temperature and potential evapotranspiration have increased significantly in all three sub-basins while precipitation shows a significant upward trend only within the Taabo dam catchment area. Meanwhile, inflow to reservoir increased significantly and greatly than precipitation probably due to land use/cover change. Precipitation and inflow show a strong correlation as energy generation is significantly and strongly correlated to outflow (inflow) in all stations (except Kossou). Furthermore, the energy generation at Buyo and Taabo dams is more sensitive to reservoir inflow, while that of Kossou dam is more affected by water level. In addition, the power of a given year is also dependent on the total rainfall of that year and/or the previous year depending on the plant.

Abstract: Seismic Stations Are Increasingly Used To Monitor River Activity And To Quantify Sediment Transport During Flood Events. In Tropical Regions, Cyclone-Induced Floods Are Often Associated With Heavy Rain And Strong Wind Episodes, Generating Complex Seismic Records Involving The Simultaneous Signature Of Water, Sediment, Rainfall And Wind. Hence, Seismic Characterization Of Rain And Wind Is Then Required To Better Decipher Each Process And Improve Our Understanding Of The River Seismic Signature. In This Study, We Investigate Experimentally The Seismic Response Of Rain And Wind Using Data Recorded By Geophones Deployed In Various Soil Types And At Different Burial Depth (Bd), Co-Located With Various Meteorological Instruments. Our Results Show That The Power Spectral Density (Psd) Of The Seismic Noise Intensifies At A Frequency Between 60 And 500 Hz For Rain And 5 And 500 Hz For Wind, In The Presence Of Rain Precipitation As Low As 0.025 Mm/Min And/Or Wind Speed >= 3 M/S. Psd Analysis Indicates That The Seismic Signal Associated With Rain Decreases With The Bd With A Value Of Similar To 2-5 Db In A Depth Difference Of 10 Cm. We Also Observe That Each Soil Type Has Its Own Seismic Signature. The 4-Min Root Mean Square Correlation Between The Seismic Signal Amplitude And The Rain Precipitation Suggests That They Best Correlate With Pearson Coefficient >0.90 At Bd Of 30 Cm. The Transfer Function Between The Precipitation Rate (Or Kinetic Energy) And The Seismic Signal Amplitude Shows That The Signal Recorded By The Geophone Can Be Used As A Robust Proxy For These Parameters. Plain Language Summary In Addition To Recording Deep Earth Activity Such As Earthquakes Or Volcanic Eruptions, Seismic Sensors Can Measure Numbers Of Naturally-Induced Ground Vibrations Such As Those Generated By Rivers Activities. In Tropical Areas During Cyclonic Events, Heavy Rain (And Strong Wind) Leads To The Presence Of Severe Flooding, During Which Several Activities In And On The River (E.G., Sediment Transport, Wind, Water, And Rain) Generate Ground Vibration, Making The Overall Signals Recorded By Seismic Sensors Complex To Interpret. To Better Decipher The River Seismic Signature, Investigating The Wind And Rain Signatures Are Then Essential. In This Study, We Investigate Experimentally The Seismic Response Of Rain And Wind From Data Recorded By Geophones And Complemented By Different Meteorological Sensors. The Obtained Results Show That (A) The Strength Of The Seismic Noise Intensifies With Frequency For Rain And Wind; (B) The Seismic Signal Associated With Rain Decreases With The Burying Depth Of The Sensor; (C) The Amplitude Of The Seismic Signal Correlates With Rain Precipitation When The Sensor Is Well Buried And (D) The Signal Recorded By The Geophone Can Be Used As A Robust Proxy For Rain Precipitation.

Abstract: Flooding is a pervasive natural hazard-costly in both human and economic terms-and climate change will probably exacerbate risks around the world. Mountainous areas, such as the densely populated European Alps, are of particular concern as topography and atmospheric conditions can result in large and sudden floods. In addition, the Alps are experiencing a high warming rate, which is probably leading to more heavy rainfall events. Here, we compile palaeoflood records to test the still uncertain impact these climatic trends might have on flood frequency and magnitude in the European Alps. We demonstrate that a warming of 0.5-1.2 degrees C, whether naturally or anthropogenically forced, led to a 25-50% decrease in the frequency of large (>= 10 yr return period) floods. This decreasing trend is not conclusive in records covering less than 200 years but persistent in those ranging from 200 to 9,000 years. By contrast, extreme (>100 yr) floods may increase with a similar degree of warming in certain small alpine catchments impacted by local intensification of extreme rainfall. Our results show how long, continuous palaeoflood records can be used to disentangle complex climate-flooding relationships and assist in improving risk assessment and management at a regional scale. Moderate flooding in the European Alps declined during past warmer periods, whereas extreme floods both increased and decreased, according to an analysis of palaeoflood records.

Abstract: Changes in snow cover associated with the warming of the French Alps greatly influence social-ecological systems through their impact on water resources, mountain ecosystems, economic activities, and glacier mass balance. In this study, we investigated trends in snow cover and temperature over the twentieth century using climate model and reanalysis data. The evolution of temperature, precipitation and snow cover in the European Alps has been simulated with the Modele Atmospherique Regional (MAR) applied with a 7-km horizontal resolution and driven by ERA-20C (1902-2010) and ERA5 (1981-2018) reanalyses data. Snow cover duration and snow water equivalent (SWE) simulated with MAR are compared to the SAFRAN – SURFEX-ISBA-Crocus – MEPRA meteorological and snow cover reanalysis (S2M) data across the French Alps (1958-2018) and in situ glacier mass balance measurements. MAR outputs provide a realistic distribution of SWE and snow cover duration as a function of elevation in the French Alps. Large disagreements are found between the datasets in terms of absolute warming trends over the second part of the twentieth century. MAR and S2M trends are in relatively good agreement for the decrease in snow cover duration, with higher decreases at low elevation (similar to 5-10%/decade). Consistent with other studies, the highest warming rates in MAR occur at low elevations (< 1000 m a.s.l) in winter, whereas they are found at high elevations (> 2000 m a.s.l) in summer. In spring, warming trends show a maximum at intermediate elevations (1500 to 1800 m). Our results suggest that higher warming at these elevations is mostly linked to the snow-albedo feedback in spring and summer caused by the disappearance of snow cover at higher elevation during these seasons. This work has evidenced that depending on the season and the period considered, enhanced warming at higher elevations may or may not be found. Additional analysis in a physically comprehensive way and more high-quality dataset, especially at high elevations, are still required to better constrain and quantify climate change impacts in the Alps and its relation to elevation.

Abstract: This article analyzes the large-scale circulations producing daily precipitation extremes in the Southwestern Alps and their trends from 1958 to 2017. We consider a high-resolution precipitation data set of 1 x 1 km(2) and the weather patterns associated to the precipitation seasonal maxima at each grid point. The high-resolution allows us to analyze in details the atmospheric influences triggering seasonal maxima. Four influences are considered-the Atlantic influence, the Mediterranean influence, the northeast circulation and the Anticyclonic situation. We show that influences on maxima are very well organized in space but their organization depends on the season. Maxima are very mainly triggered by two types of influences in the region-the Atlantic influence and the Mediterranean influence. Trends in weather patterns producing maxima are also organized in space, with opposite trends for the Atlantic and the Mediterranean influences. The Mediterranean influence retreated very significantly over the period in winter and spring, while the Atlantic influence significantly extended further south. In autumn the Mediterranean influence strengthened where it was already dominant.

Abstract: The aim of this study is to simulate the impact of mineral dust emissions from the Sahel-Saharan zone on temperature extremes over the Sahel. To achieve this goal, we performed two numerical simulations: one with the standard version of the regional climate model RegCM4 (no dust run) and another one with the same version of this model incorporating a dust module (dust run). The difference between both versions of the model allowed to isolate the impacts of mineral dust emissions on temperature extremes. The results show that the accumulation of mineral dust into the atmosphere leads to a decrease of the frequency of warm days, very warm days, and warm nights over the Sahel. This decrease is higher during the MAM (March-April-May) and JJA (June-July-August) periods especially in the northern and western parts of the Sahel. The impact of the mineral dust emissions is also manifested by a decrease of the frequency of tropical nights especially during MAM in the northern Sahel. When considering the warm spells, mineral particles tend to weaken them especially in MAM and JJA in the northern Sahel. To estimate the potential impacts of the mineral dust accumulation on heat stress, the heat index and the humidex are used. The analysis of the heat index shows that the dust impact is to reduce the health risks particularly in the northern Sahel during the MAM period, in the western Sahel during JJA, and in the southern and the northeastern parts of the Sahel during the SON (September-October-November) period. As for the humidex, it is characterized by a decrease especially in the northern Sahel for all seasons. This reduction of the occurrence of thermal extremes may have a positive effect on the energy demand for cooling and on global health. However, the accumulation of dust particles in the atmosphere may also increase the meningitis incidence and prevalence.

Abstract: Large multiscenario multimodel ensembles (MMEs) of regional climate model (RCM) experiments driven by global climate models (GCMs) are made available worldwide and aim at providing robust estimates of climate changes and associated uncertainties. Due to many missing combinations of emission scenarios and climate models leading to sparse scenario-GCM-RCM matrices, these large ensembles, however, are very unbalanced, which makes uncertainty analyses impossible with standard approaches. In this paper, the uncertainty assessment is carried out by applying an advanced statistical approach, called QUALYPSO, to a very large ensemble of 87 EURO-CORDEX climate projections, the largest MME based on regional climate models ever produced in Europe. This analysis provides a detailed description of this MME, including (i) balanced estimates of mean changes for near-surface temperature and precipitation in Europe, (ii) the total uncertainty of projections and its partition as a function of time, and (iii) the list of the most important contributors to the model uncertainty. For changes in total precipitation and mean temperature in winter (DJF) and summer (JJA), the uncertainty due to RCMs can be as large as the uncertainty due to GCMs at the end of the century (2071-2099). Both uncertainty sources are mainly due to a small number of individual models clearly identified. Due to the highly unbalanced character of the MME, mean estimated changes can drastically differ from standard average estimates based on the raw ensemble of opportunity. For the RCP4.5 emission scenario in central-eastern Europe for instance, the difference between balanced and direct estimates is up to 0.8 degrees C for summer temperature changes and up to 20 % for summer precipitation changes at the end of the century.

Abstract: In 2007, at the 2nd Africa-EU Summit, the development and implementation of earth observation based services to support sustainable development in Africa was agreed. A joint Africa-EU strategy created a framework for cooperation to this end called GMES & Africa. This cooperation aims to produce products and services relevant to the needs of Africans and implemented by African institutions. It is based in particular on the European Copernicus program. The themes covered by the cooperation include natural resource management, marine and coastal areas, water resource management, climate variability and change, disaster risk reduction and food security. Building on its early involvement in the previous projects, the Joint Research Centre has developed an operational and distributable open-source data processing tool, called eStation. One year before the end of the first phase of the project, a full survey of eStation users was conducted. The objective of the survey was to get a full overview of the use, strength, weakness and way to improve the eStation in an operational context. This study presents the main results of the survey. It identifies who are the users, what their operational tasks are and how they communicate the information to decision makers. In addition, the use of the station is described, its strengths and weaknesses are identified as well as the technical and thematic difficulties encountered. The survey underlines the importance of maintaining a constant dialogue between users and developers in order to offer technical and thematic supports to improve the efficiency of the use of the tools. This can be done by organising training and workshops and is essential for the proper use of the tools and products.

Abstract: The 20 km(2) Galabre catchment belongs to the French network of critical zone observatories (OZCAR; Gaillardet et al., Vadose Zone Journal, 2018, 17(1), 1-24). It is representative of the sedimentary lithology and meteorological forcing found in Mediterranean and mountainous areas. Due to the presence of highly erodible and sloping badlands on various lithologies, the site was instrumented in 2007 to understand the dynamics of suspended sediments (SS) in such areas. Two meteorological stations including measurements of air temperature, wind speed and direction, air moisture, rainfall intensity, raindrop size and velocity distribution were installed both in the upper and lower part of the catchment. At the catchment outlet, a gauging station records the water level, temperature and turbidity (10 min time-step). Stream water samples are collected automatically to estimate SS concentration-turbidity relationships, allowing quantification of SS fluxes with known uncertainty. The sediment samples are further characterized by measuring their particle size distributions and by applying a low-cost sediment fingerprinting approach using spectrocolorimetric tracers. Thus, the contributions of badlands located on different lithologies to total SS flux are quantified at a high temporal resolution, providing the opportunity to better analyse the links between meteorological forcing variability and watershed hydrosedimentary response. The set of measurements was extended to the dissolved phase in 2017. Both stream water electrical conductivity and major ion concentrations are measured each week and every 3 h during storm events. This extension of measurements to the dissolved phase will allow progress in understanding both the origin of the water during the events and the partitioning between particulate and dissolved fluxes of solutes in the critical zone. All data sets are available at .

Abstract: The availability of water resources in a reservoir for electricity generation is strongly linked to climate and weather conditions. Also, the use of these water resources is influenced by the population size as well as anthropogenic activities. This research attempts to assess the combined effects of (i) climate change (CC), (ii) land use/land cover change (LULCC), and (iii) development (Dev) conditions on water resources and hydropower generation (HPGen) using Regional Climate Models (RCMs) from Coordinated Regional Downscaling Experiment (CORDEX) under the Representative Concentrated Pathways (RCP): RCP4.5 and RCP8.5. The RCMs considered are: CanRCM, CCLM, and WRF being drived by CanESM2, CNRM-CERFACS, and NorESM1, respectively. The Water Evaluation and Planning model (WEAP) tool is used to simulate the water availability and HPGen in the Mono basin under present and future conditions. The ensemble mean of the three-climate dataset analysis reveals that the temperature is projected to increase significantly while the precipitation change is uncertain under both RCPs in the near (2020-2050) and the far (2070-2090) futures. These changes in climate variables consequently affected simulated water availability for different water consumption sectors especially the HPGen in the near and far futures. Moreover, the Dev was found to exacerbate the burden that constitutes the CC for water availability and HPGen. Nevertheless, LULCC associated with either CC or both CC and Dev were projected by all the RCMs and their ensemble mean to reduce this burden. However, its side effects namely reservoir siltation and sedimentation need to be deeply investigated.

Abstract: One way to use climate services in the case of sugarcane is to develop models that forecast yields to help the sector to be better prepared against climate risks. In this study, several models for forecasting sugarcane yields were developed and compared in the north of Ivory Coast (West Africa). These models were based on statistical methods, ranging from linear regression to machine learning algorithms such as the random forest method, fed by climate data (rainfall, temperature); satellite products (NDVI, EVI from MODIS Vegetation Index product) and information on cropping practices. The results show that the forecasting of sugarcane yield depended on the area considered. At the plot level, the noise due to cultivation practices can hide the effects of climate on yields and leads to poor forecasting performance. However, models using satellite variables are more efficient and those with EVI alone may explain 43% of yield variations. Moreover, taking into account cultural practices in the model improves the score and enables one to forecast 3 months before harvest in 50% and 69% of cases whether yields will be high or low, respectively, with errors of only 10% and 2%, respectively. These results on the predictive potential of sugarcane yields are useful for planning and climate risk management in this sector.

Abstract: The varved sediments of Lake Montcort`es (central pre-Pyrenees) have provided a continuous high-resolution record of the last ca. 3000 years. Previous chronological and sedimentological studies of this record have furnished detailed paleoenvironmental reconstructions. However, palynological studies are only available for the last millennium, when the landscape around the lake had already been transformed by humans. Therefore, the earlier vegetation of Montcortes and the history of its anthropogenic transformations remain unknown. This paper presents a palynological analysis of the interval between the Late Bronze Age and the Early Medieval period, aimed at recording preanthropic conditions, anthropization onset and the further landscape transformations. During the Late Bronze Age (ca. 1100 BCE to 770 BCE), the vegetation did not show any evidence of human impact. The decisive anthropogenic transformation of the Montcort`es catchment vegetation and landscape started at the beginning of the Iron Age (770 BCE) and continued during Roman and Medieval times in the form of recurrent burning, grazing, cultivation, silviculture and hemp retting. Some intervals of lower human pressure were recorded, but the original vegetation never returned. The anthropization that took place during the Iron Age did not cause notable changes in the sediment yield to the lake, but a significant limnological shift occurred, as manifested in the initiation of varve formation, a process that has been continuous until today. Climatic shifts seem to have played a secondary role in influencing vegetation and landscape changes. These results contrast with previous inferences of low anthropogenic impact until the Medieval Period, at a regional level. Similar studies may be developed on other mountain ranges to verify whether landscape anthropization occurred earlier than previously thought, and to verify the potential occurrence of elevational gradients in the anthropization of mountain landscapes.

Abstract: Stochastic rainfall generators aim to reproduce the main statistical features of rainfall at small spatial and temporal scales. The simulated synthetic rainfall series are recognized as suitable for use with impact analysis in water, agricultural, and ecological management. Convection-driven precipitation, dominant in certain regions of the world such as the intertropical belt regions, presents properties that require specific consideration when modeling: (i) strong rainfall intermittency, (ii) high variability of intensities within storms, (iii) strong spatiotemporal correlation of intensities, and (iv) marked seasonality of storm properties. In this article, improvements for an existing stochastic generator of rainfall fields that models convective storms are presented. Notable novelties include (i) the ability to model precipitation event timing, (ii) an improved temporal disaggregation scheme representing the rainfall distribution at subevent scales, and (iii) using covariates to reflect seasonal changes in precipitation occurrence and marginal distribution parameters. Extreme values are explicitly considered in the distribution of storm event intensities. The simulator is calibrated and validated using 28 years of 5-min precipitation data from the 30-rain-gauge AMMA-CATCH network in the Sahelian region of southwest Niger. Both large propagative systems and smaller local convective precipitation are generated. Results show that simulator improvements coherently represent the local climatology. The simulator can generate scenarios for impact studies with accurate representation of convective precipitation characteristics.

Abstract: This study characterizes the future changes in extreme rainfall and air temperature in the Mono river basin where the main economic activity is weather dependent and local populations are highly vulnerable to natural hazards, including flood inundations. Daily precipitation and temperature from observational datasets and Regional Climate Models (RCMs) output from REMO, RegCM, HadRM3, and RCA were used to analyze climatic variations in space and time, and fit a GEV model to investigate the extreme rainfalls and their return periods. The results indicate that the realism of the simulated climate in this domain is mainly controlled by the choice of the RCMs. These RCMs projected a 1 to 1.5 degrees C temperature increase by 2050 while the projected trends for cumulated precipitation are null or very moderate and diverge among models. Contrasting results were obtained for the intense rainfall events, with RegCM and HadRM3 pointing to a significant increase in the intensity of extreme rainfall events. The GEV model is well suited for the prediction of heavy rainfall events although there are uncertainties beyond the 90th percentile. The annual maxima of daily precipitation will also increase by 2050 and could be of benefit to the ecosystem services and socioeconomic activities in the Mono river basin but could also be a threat.

Abstract: Over the past decades, large variations of precipitation were observed in Africa, which often led to dramatic consequences for local society and economy. To avoid such disasters in the future, it is crucial to better anticipate the expected changes, especially in the current context of climate change and population growth. To this date, however, projections of precipitation over Africa are still associated with very large uncertainties. To better understand how this uncertainty can be reduced, this study uses an advanced Bayesian analysis of variance (ANOVA) method to characterize, for the first time in the regional climate projections of CORDEX-AFRICA, the different sources of uncertainty associated with the projections of precipitation over Africa. By 2090, the ensemble mean precipitation is projected to increase over the Horn of Africa from September to May and over the eastern Sahel and Guinea Coast from June to November. It is projected to decrease over the northern coast and southern Africa all year long, over western Sahel from March to August, and over the Sahel and Guinea Coast from March to May. Most of these projections however are not robust, i.e., the magnitude of change is smaller than the associated uncertainty. Over time, the relative contribution of internal variability (excluding interannual variability) to total uncertainty is moderate and quickly falls below 10%. By 2090, it is found that over the Horn of Africa, northern coast, southern Africa, and Sahel, most of the uncertainty results from a large dispersion across the driving Global Climate Models (in particular MIROC, CSIRO, CCCma, and IPSL), whereas over the tropics and parts of eastern Africa, most of the uncertainty results from a large dispersion across Regional Climate Models (in particular CLMcom).

Abstract: This article proposes a statistical framework for assessing the multiscale severity of a given storm at a given location. By severity we refer to the rareness of the storm event, as measured by the return period. Rather than focusing on predetermined spatiotemporal scales, we consider a model assessing the return period of a storm event observed across the continuum of durations and areas around a focus location. We develop a Bayesian intensity-duration-area-frequency model based on extreme value distribution and space-time scale invariance hypotheses. The model allows us to derive an analytical expression of the return period for any duration and area, while the Bayesian framework allows us by construction to assess the related uncertainties. We apply this framework to high-resolution radar-rain gauge reanalysis data covering a mountainous region of southern France during the autumns 2008-15 and comprising 50 rain events. We estimate the model at two grid points located a few kilometers apart on either side of the mountain crest, considering spatiotemporal scales ranging over 3-48 h and 1-2025 km(2). We show that at all scales and for all significant events, the return period uncertainties are skewed to the right, evidencing the need of considering uncertainty to avoid systematic risk underestimation. We also reveal the large variability of the storm severity both at short distance and across scales, due to both the natural variability of rainfall and the mask effect induced by the mountain crest.

Abstract: In West Africa (WA), interest in solar energy development has risen in recent years with many planned and ongoing projects currently in the region. However, a major drawback to this development in the region is the intense cloud cover that reduces the incoming solar radiation when present and causes fluctuations in solar power production. Therefore, understanding the occurrence of clouds and their link to the surface solar radiation in the region is important for making plans to manage future solar energy production. In this study, we use the state-of-the-art European Centre for Medium-range Weather Forecasts ReAnalysis (ERA5) dataset to examine the occurrence and persistence of cloudy and clear-sky conditions in the region. Then, we investigate the effects of cloud cover on the quantity and variability of the incoming solar radiation. The cloud shortwave radiation attenuation (CRASW down arrow) is used to quantify the amount of incoming solar radiation that is lost due to clouds. The results showed that the attenuation of incoming solar radiation is stronger in all months over the southern part of WA near the Guinea Coast. Across the whole region, the maximum attenuation occurs in August, with a meanCRASW down arrow of about 55% over southern WA and between 20% and 35% in the Sahelian region. Southern WA is characterized by a higher occurrence of persistent cloudy conditions, while the Sahel region and northern WA are associated with frequent clear-sky conditions. Nonetheless, continuous periods with extremely low surface solar radiation were found to be few over the whole region. The analysis also showed that the surface solar radiation received from November to April only varies marginally from one year to the other. However, there is a higher uncertainty during the core of the monsoon season (June to October) with regard to the quantity of incoming solar radiation. The results obtained show the need for robust management plans to ensure the long-term success of solar energy projects in the region.

Abstract: The RadAlp experiment aims at developing advanced methods for rainfall and snowfall estimation using weather radar remote sensing techniques in high mountain regions for improved water resource assessment and hydrological risk mitigation. A unique observation system has been deployed since 2016 in the Grenoble region of France. It is composed of an X-band radar operated by Meteo-France on top of the Moucherotte mountain (1901m above sea level; hereinafter MOUC radar). In the Grenoble valley (220m above sea level; hereinafter a.s.l.), we operate a research X-band radar called XPORT and in situ sensors (weather station, rain gauge and disdrometer). In this paper we present a methodology for studying the relationship between the differential phase shift due to propagation in precipitation (Phi(dp)) and path-integrated attenuation (PIA) at X band. This relationship is critical for quantitative precipitation estimation (QPE) based on polarimetry due to severe attenuation effects in rain at the considered frequency. Furthermore, this relationship is still poorly documented in the melting layer (ML) due to the complexity of the hydrometeors' distributions in terms of size, shape and density. The available observation system offers promising features to improve this understanding and to subsequently better process the radar observations in the ML. We use the mountain reference technique (MRT) for direct PIA estimations associated with the decrease in returns from mountain targets during precipitation events. The polarimetric PIA estimations are based on the regularization of the profiles of the total differential phase shift (Psi(dp)) from which the profiles of the specific differential phase shift on propagation (K-dp) are derived. This is followed by the application of relationships between the specific attenuation (k) and the specific differential phase shift. Such k-K-dp relationships are estimated for rain by using drop size distribution (DSD) measurements available at ground level. Two sets of precipitation events are considered in this preliminary study, namely (i) nine convective cases with high rain rates which allow us to study the phi(dp)-PIA relationship in rain, and (ii) a stratiform case with moderate rain rates, for which the melting layer (ML) rose up from about 1000 up to 2500ma.s.l., where we were able to perform a horizontal scanning of the ML with the MOUC radar and a detailed analysis of the phi(dp)-PIA relationship in the various layers of the ML. A common methodology was developed for the two configurations with some specific parameterizations. The various sources of error affecting the two PIA estimators are discussed, namely the stability of the dry weather mountain reference targets, radome attenuation, noise of the total differential phase shift profiles, contamination due to the differential phase shift on backscatter and relevance of the k-K-dp relationship derived from DSD measurements, etc. In the end, the rain case study indicates that the relationship between MRT-derived PIAs and polarimetry-derived PIAs presents an overall coherence but quite a considerable dispersion (explained variance of 0.77). Interestingly, the nonlinear k-K-dp relationship derived from independent DSD measurements yields almost unbiased PIA estimates. For the stratiform case, clear signatures of the MRT-derived PIAs, the corresponding phi(dp) value and their ratio are evidenced within the ML. In particular, the averaged PIA/phi(dp) ratio, a proxy for the slope of a linear k-K-dp relationship in the ML, peaks at the level of the copolar correlation coefficient (rho(hv)) peak, just below the reflectivity peak, with a value of about 0.42 dB per degree. Its value in rain below the ML is 0.33 dB per degree, which is in rather good agreement with the slope of the linear k-K-dp relationship derived from DSD measurements at ground level. The PIA/phi(dp) ratio remains quite high in the upper part of the ML, between 0.32 and 0.38 dB per degree, before tending towards 0 above the ML.

Abstract: In West Africa, as in many other estuaries, enormous volumes of marine water are entering the continent. Fresh water discharge is very low, and it is commonly strongly linked to rainfall level. Some of these estuaries are inverse estuaries. During the Great Sahelian Drought (1968-1993), their hyperhaline feature was exacerbated. This paper aims to describe the evolution of the two main West African inverse estuaries, those of the Saloum River and the Casamance River, since the end of the drought. Water salinity measurements were carried out over three to five years according to the sites in order to document this evolution and to compare data with the historical ones collected during the long dry period at the end of 20th century. The results show that in both estuaries, the mean water salinity values have markedly decreased since the end of the drought. However, the Saloum estuary remains a totally inverse estuary, while for the Casamance River, the estuarine turbidity maximum (ETM) is the location of the salinity maximum, and it moves according to the seasons from a location 1-10 km downwards from the upstream estuary entry, during the dry season, to a location 40-70 km downwards from this point, during the rainy season. These observations fit with the functioning of the mangrove, the West African mangrove being among the few in the world that are markedly increasing since the beginning of the 1990s and the end of the dry period, as mangrove growth is favored by the relative salinity reduction. Finally, one of the inverse estuary behavior factors is the low fresh water incoming from the continent. The small area of the Casamance and Saloum basins (20,150 and 26,500 km(2) respectively) is to be compared with the basins of their two main neighbor basins, the Gambia River and the Senegal River, which provide significant fresh water discharge to their estuary.

Abstract: This study aims to provide improved knowledge and evidence on current (1986-2015) climate variation based on six rainfall indices over five West African countries (Senegal, Niger, Burkina Faso, Ivory Coast, and Benin) using the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) dataset. On average, precipitation has increased over the central Sahel and the western Sahel. This increase is associated with increase in the number of rainy days, longer wet spells and shorter dry spells. Over the Guinea Coast, the slight increase in precipitation is associated with an increase in the intensity of rainfall with a shorter duration of wet spells. However, these mean changes in precipitation are not all statistically significant and uniform within a country. While previous studies are focused on regional and sub-regional scales, this study contributes to deliver a climate information at a country level that is more relevant for decision making and for policy makers, and to document climate-related risks within a country to feed impact studies in key sectors of the development, such as agriculture and water resources.

Abstract: High densities of local-scale daily precipitation series across relatively large domains are of special interest for a wide range of applications (e.g., hydrological modeling, agriculture). The focus of the present study is to post-process gridded precipitation from a single reanalysis to correct bias and scale mismatch with observations, and to extend the same post-processing at sites without historical data. A Stochastic Model Output Statistical approach combined with meta-Gaussian spatiotemporal random fields, calibrated at sites, is employed to post-process the Climate Forecast System Reanalysis (CFSR) precipitation. The post-processed data, characterized by local parameters, is then mapped across the Great Lakes region (Canada) using two different approaches: (1) kriging, and (2) Vector Generalized Additive Model (VGAM) with spatial covariates. The kriging enables the interpolation of these parameters, while the spatial VGAM helps to spatially post-process CFSR precipitation using a single model. Thek-fold cross-validation procedure is employed to assess the ability of the two approaches to predict selected characteristics and climate indices. The kriging and spatial VGAM approaches modeled effectively the distribution of the precipitation process to similar extents (e.g., mean daily precipitation, variability and the number of wet days). The kriging approach produces slightly better estimates of climate indices than the spatial VGAM models. Both approaches demonstrate significant improvement of the metric estimation compared to those of CFSR without post-processing.

Abstract: This paper describes the assessment of the performance of a method for providing early warnings of unusually wet and dry precipitation conditions globally. The indicator that is used for forecasting these conditions is computed from forecasted standardized precipitation index (SPI) values for accumulation periods of 1, 3, and 6 months. The SPI forecasts are derived from forecasted precipitation produced by the latest probabilistic seasonal forecast of ECMWF. Early warnings of unusual precipitation periods are shown only when and where the forecast is considered robust (i.e., with at least 40% of ensemble members associated with intense forecasts), and corresponding with significant SPI values (i.e., below 21 for dry, or above 11 for wet conditions). The intensity of the forecasted events is derived based on the extreme forecast index and associated shift of tails products developed by ECMWF. Different warning levels are then assessed, depending on the return period of the forecast intensity, and the coherence of the ensemble forecast members. The assessment of the indicators performance is based on the 25-member ensemble forecast system that is carried out everymonth during the 36 years of the hindcast period (1981-2016). The results showthat significant information is provided even for the longest lead time, albeit with a large variability across the globe with the highest scores over central Russia, SoutheastAsia, and the northern part of SouthAmerica orAustralia. Because of the loss of predictability, each SPI is based on the first lead time. Asensitivity test highlights the influence on the robustness of the forecasts of the warning levels used, as well as the effects of prior conditions and of seasonality.

Abstract: Changes in precipitation over the European Alps are investigated with the regional climate model MAR (Modele Atmospherique Regional) applied with a 7 km resolution over the period 1903-2010 using the reanalysis ERA-20C as forcing. A comparison with several observational datasets demonstrates that the model is able to reproduce the climatology as well as both the interannual variability and the seasonal cycle of precipitation over the European Alps. The relatively high resolution allows us to estimate precipitation at high elevations. The vertical gradient of precipitation simulated by MAR over the European Alps reaches 33% km(-1) (1.21mm d(-1) km(-1)) in summer and 38% km(-1) (1.15 mm d(-1) km(-1)) in winter, on average, over 1971-2008 and shows a large spatial variability. A significant (p value < 0.05) increase in mean winter precipitation is simulated in the northwestern Alps over 1903-2010, with changes typically reaching 20% to 40% per century. This increase is mainly explained by a stronger simple daily intensity index (SDII) and is associated with less-frequent but longer wet spells. A general drying is found in summer over the same period, exceeding 20% to 30% per century in the western plains and 40% to 50% per century in the southern plains surrounding the Alps but remaining much smaller (< 10 %) and not significant above 1500 ma.s.l. Below this level, the summer drying is explained by a reduction in the number of wet days, reaching 20% per century over the northwestern part of the Alps and 30% to 50% per century in the southern part of the Alps. It is associated with shorter but more-frequent wet spells. The centennial trends are modulated over the last decades, with the drying occurring in the plains in winter also affecting high-altitude areas during this season and with a positive trend of autumn precipitation occurring only over the last decades all over the Alps. Maximum daily precipitation index (Rx1day) takes its highest values in autumn in both the western and the eastern parts of the southern Alps, locally reaching 50 to 70 mm d(-1) on average over 1903-2010. Centennial maxima up to 250 to 300 mm d(-1) are simulated in the southern Alps, in France and Italy, as well as in the Ticino valley in Switzerland. Over 1903-2010, seasonal Rx1day shows a general and significant increase at the annual timescale and also during the four seasons, reaching local values between 20% and 40% per century over large parts of the Alps and the Apennines. Trends of Rx1day are significant (p value < 0.05) only when considering long time series, typically 50 to 80 years depending on the area considered. Some of these trends are nonetheless significant when computed over 1970-2010, suggesting a recent acceleration of the increase in extreme precipitation, whereas earlier periods with strong precipitation also occurred, in particular during the 1950s and 1960s.

Abstract: Long-term changes in flood activity have often been reconstructed to understand their relationships to climate changes. This requires identification of flood layers according to certain characteristics (e.g., texture, geochemical composition, grain-size) and then to count them using naked-eye observation. This method is, however, time-consuming, and intrinsically characterized by a low resolution that may lead to bias and misidentification. To overcome this limitation, high-resolution analytical approaches can be used, such as X-ray fluorescence spectroscopy (XRF), X-ray computed tomography, or hyperspectral imaging (HSI). When coupled with discriminant algorithms, HSI allows for automatic identification of event layers. Here, we propose a new method of flood layers identification and counting based on the combination of both HSI and XRF core scanner analyses, applied to a Lake Bourget (French Alps) sediment sequence. We use a hyperspectral sensor from the short wave-infrared spectral range to create a discrimination model between event layers and continuous sedimentation. This first step allows the estimation of a classification map, with a prediction accuracy of 0.96, and then the automatic reconstruction of a reliable chronicle of event layers (induding their occurrence and deposit thicknesses). XRF signals are then used to discriminate flood layers among all identified event layers based on site-specific geochemical elements (in the case of Lake Bourget: Mn and Ti). This results in an automatically generated flood chronide. Changes in flood occurrence and event thickness through time reconstructed from the automatically generated floods chronicle are in good agreement with the naked-eye-generated chronicle. In detail, differences rely on a larger number of detected flood events (i.e., increase of 9% of the number of layers detected) and a more precise layer thickness estimation, thanks to a higher resolution. Therefore, the developed methodology opens a promising avenue to increase both the efficiency (time-saving) and robustness ( higher accuracy) of paleoflood reconstructions from lake sediments. Also, this methodology can be applied to identify any specific layers (e.g., varve, tephra, mass-movement turbidite, tsunami) and, thereby, it has a direct implication in paleolimnology. paleoflood hydrology and paleoseismology from sediment archives. (C) 2020 Elsevier B.V. All rights reserved.

Abstract: Precipitation amounts at daily or hourly scales are skewed to the right, and heavy rainfall is poorly modeled by a simple gamma distribution. An important yet challenging topic in hydrometeorology is to find a probability distribution that is able to model well low, moderate, and heavy rainfall. To address this issue, we present a semiparametric distribution suitable for modeling the entire range of rainfall amount. This model is based on a recent parametric statistical model called the class of extended generalized Pareto distributions (EGPDs). The EGPD family is in compliance with extreme value theory for both small and large values, while it keeps a smooth transition between these tails and bypasses the hurdle of selecting thresholds to define extremes. In particular, return levels beyond the largest observation can be inferred. To add flexibility to this EGPD class, we propose to model the transition function in a nonparametric fashion. A fast and efficient nonparametric scheme based on Bernstein polynomial approximations is investigated. We perform simulation studies to assess the performance of our approach. It is compared to two parametric models: a parametric EGPD and the classical generalized Pareto distribution (GPD), the latter being only fitted to excesses above a high threshold. We also apply our semiparametric version of EGPD to a large network of 180 precipitation time series over France.

Abstract: In Quaternary paleosciences, the rationale behind analogical inference presupposes that former processes can be explained by causes operating now, although their intensity and rates can vary through time. In this paper we synthesised the results of different modern analogue studies performed in a varved lake. We discuss their potential value to obtain best results from high resolution past records. Different biogeochemical contemporary processes revealed seasonality and year-to-year variability, e.g., calcite precipitation, lake oxygenation, production and deposition of pollen and phytoplankton growth. Fingerprints of the first two of these processes were clearly evidenced in the varve-sublayers and allow understanding related to past events. Pollen studies suggested the possibility of identifying and characterizing seasonal layers even in the absence of varves. Marker pigments in the water column were tightly associated with phytoplankton groups living today; most of them were identified in the sediment record as well. We observed that 50% of these marker pigments were destroyed between deposition and permanent burying. In another study, seasonality in the production/distribution of branched glycerol dialkyl glycerol tetraethers (brGDGTs) and derived temperature estimates were investigated in catchment soils and particles settling in the lake. The signatures of brGDGTs in depositional environments mainly were representative of stable conditions of soils in the catchment that last over decades; no brGDGTs seemed to be produced within the lake. The main contribution of this review is to show the advantages and limitations of a multiproxy modern-analogue approach in Lake Montcortes as a case study and proposing new working hypotheses for future research.

Abstract: This modeling study is conducted to examine the potential impact of the reforestation (greenbelt) location (either in Sahel or in Guinean region) on West Africansummer climate system. To this end, three simulations using the regional climate model RegCM4 driven by ERA-Interim reanalysis were performed at 50km horizontal resolution over a West African domain for the period 2000-2011. The first experiment, namely the control (CTRL), uses the standard vegetation cover, while the two others incorporate throughout the model integration, a zonal reforestation band of evergreen broadleaf over different locations: (i) over a 13 degrees N-17 degrees N band latitudes in a Sahel-Sahara region (experiment hereafter referred to as GB15N) and (ii) between 8.5 degrees N-11.5 degrees N in the Guinea Coast region (experiment hereafter referred to as GB10N). A comparison of the CTRL experiment with observation reveals a faithful reproduction of the mean boreal and summer seasonal precipitation pattern, though substantial dry/wet biases remain, especially in the Atlantic Ocean. In addition, the seasonal cycle over sub-regions matches satisfactory the observed pattern. The GB15N reforestation leads to a precipitation increase in the range of 2-4mm/day over the forested areas, whereas in the GB10N reforestation, precipitation increase is weaker and not necessarily located in the forested areas. Temperature cooling is observed over the reforested area and may be explained by a decrease of ground heat flux related to a reduction of the surface albedo.

Abstract: We propose an objective framework for selecting rainfall hazard mapping models in a region starting from rain gauge data. Our methodology is based on the evaluation of several goodness-of-fit scores at regional scale in a cross-validation framework, allowing us to assess the goodness-of- fit of the rainfall cumulative distribution functions within the region but with a particular focus on their tail. Cross-validation is applied both to select the most appropriate statistical distribution at station locations and to validate the mapping of these distributions. To illustrate the framework, we consider daily rainfall in the Ardeche catchment in the south of France, a 2260 km(2) catchment with strong inhomogeneity in rainfall distribution. We compare several classical marginal distributions that are possibly mixed over seasons and weather patterns to account for the variety of climato-logical processes triggering precipitation, and several classical mapping methods. Among those tested, results show a preference for a mixture of Gamma distribution over seasons and weather patterns, with parameters interpolated with thin plate spline across the region.

Abstract: Floods often affect not only a single location, but also a whole region. Flood frequency analysis should therefore be undertaken at a regional scale which requires the considerations of the dependence of events at different locations. This dependence is often neglected even though its consideration is essential to derive reliable flood estimates. A model used in regional multivariate frequency analysis should ideally consider the dependence of events at multiple sites which might show dependence in the lower and/or upper tail of the distribution. We here seek to propose a simple model that on the one hand considers this dependence with respect to the network structure of the region and on the other hand allows for the simulation of stochastic event sets at both gauged and ungauged locations. The new Fisher copula model is used for representing the spatial dependence of flood events in the nested Thur catchment in Switzerland. Flood event samples generated for the gauged stations using the Fisher copula are compared to samples generated by other dependence models allowing for modeling of multivariate data including elliptical copulas, R-vine copulas, and max-stable models. The comparison of the dependence structures of the generated samples shows that the Fisher copula is a suitable model for capturing the spatial dependence in the data. We therefore use the copula in a way such that it can be used in an interpolation context to simulate event sets comprising gauged and ungauged locations. The spatial event sets generated using the Fisher copula well capture the general dependence structure in the data and the upper tail dependence, which is of particular interest when looking at extreme flood events and when extrapolating to higher return periods. The Fisher copula was for a medium-sized catchment found to be a suit-able model for the stochastic simulation of flood event sets at multiple gauged and ungauged locations.

Abstract: Chronologies of lake-sediment records covering the last centuries to millennia are usually based on both short-lived radionuclides and radiocarbon dating. However, beyond the range of short-lived radionuclides, age model accuracy often suffers from large radiocarbon uncertainties. For high-altitude records, this issue is even more prominent as terrestrial plant fragments for radiocarbon dating are often lacking due to the sparse vegetation in such environments. In this study, we evaluate the potential of the geomagnetic field secular variations as a complementary tool to establish more robust age-depth relationships. Our palaeomagnetic study, applied to five high-altitude lakes from the western European Alps, first shows that recent unconsolidated sediments can carry stable remanent magnetization. The analysis of the magnetic parameters indicates that low-coercivity pseudo-single domain magnetite grains carry the natural magnetization. Nevertheless, the quality of palaeomagnetic secular variation records varies from one lake to another. This quality can be illustrated through the calculation of the declination/inclination maximum angular variations and their comparison to the expected value. Compared with available models, the declination variations are usually too large and the inclination too high. We discuss the validity of palaeosecular variation (PSV) of the Earth's magnetic field regarding rock magnetism, magnetization processes and possible deformation during coring. From a magnetic point of view, the quality of data is variable, but the characteristic remanent magnetization direction is consistent at site level between neighbouring lakes and with the reference curve, suggesting that geomagnetic field secular variations are approximately recorded. Finally, we attempt to correlate the declination/inclination variations of the characteristic remanent magnetization measured in the five records to the reference geomagnetic model to provide additional chronological markers for age-depth modelling. These stratigraphic chrono-markers appear in systematic agreement with our previous chronological data and enable a reduction of dating uncertainties up to 30% when including these chrono-markers in the age-depth modelling. This agreement supports the interpretation that PSV may have been recorded more or less accurately depending on the studied lake. Therefore, coupled with a comprehensive understanding through other analysis (sedimentology, dating, geochemistry), PSV can be used to improve the age models in the more favourable cases.

Abstract: Over the last years, several stationarity tests have been proposed. One of these methods uses time-frequency representations and stationarized replicas of the signal (known as surrogates) for testing wide-sense stationarity. In this letter, we propose a procedure to improve the original surrogate test. The proposed methodology can be seen as a guideline on how the surrogate test can be improved. We show mathematically that the modified test should exhibit improved classification performance. Numerical simulations on synthetic and real-world signals are carried out to evaluate the modified test against competing ones.

Abstract: The great success of the Tropical Rainfall Measuring Mission (TRMM) and its successor Global Precipitation Measurement (GPM) has accelerated the development of global high-resolution satellite-based precipitation products (SPP). However, the quantitative accuracy of SPPs has to be evaluated before using these datasets in water resource applications. This study evaluates the following GPM-era and TRMM-era SPPs based on two years (2014-2015) of reference daily precipitation data from rain gauge networks in ten mountainous regions: Integrated Multi-SatellitE Retrievals for GPM (IMERG, version 05B and version 06B), National Oceanic and Atmospheric Administration (NOAA)/Climate Prediction Center Morphing Method (CMORPH), Global Satellite Mapping of Precipitation (GSMaP), and Multi-Source Weighted-Ensemble Precipitation (MSWEP), which represents a global precipitation data-blending product. The evaluation is performed at daily and annual temporal scales, and at 0.1 deg grid resolution. It is shown that GSMaPV07 surpass the performance of IMERGV06B Final for almost all regions in terms of systematic and random error metrics. The new orographic rainfall classification in the GSMaPV07 algorithm is able to improve the detection of orographic rainfall, the rainfall amounts, and error metrics. Moreover, IMERGV05B showed significantly better performance, capturing the lighter and heavier precipitation values compared to IMERGV06B for almost all regions due to changes conducted to the morphing, where motion vectors are derived using total column water vapor for IMERGV06B.

Abstract: Precipitation over Antarctica is the main term in the surface mass balance of the Antarctic ice sheet, which is crucial for the future evolution of the sea level worldwide. Precipitation, however, remains poorly documented and understood mainly because of a lack of observations in this extreme environment. Two observatories dedicated to precipitation have been set up at the Belgian station Princess Elisabeth (PE) and at the French station Dumont d'Urville (DDU) in East Antarctica. Among other instruments, both sites have a vertically pointing micro rain radar (MRR) working at the K band. Measurements have been continuously collected at DDU since the austral summer of 2015-2016, while they have been collected mostly during summer seasons at PE since 2010, with a full year of observation during 2012. In this study, the statistics of the vertical profiles of reflectivity, vertical velocity, and spectral width are analyzed for all seasons. Vertical profiles were separated into surface precipitation and virga to evaluate the impact of virga on the structure of the vertical profiles. The climatology of the study area plays an important role in the structure of the precipitation: warmer and moister atmospheric conditions at DDU favor the occurrence of more intense precipitation compared with PE, with a difference of 8 dBZ between both stations. The strong katabatic winds blowing at DDU induce a decrease in reflectivity close to the ground due to the sublimation of the snowfall particles. The vertical profiles of precipitation velocity show significant differences between the two stations. In general, at DDU the vertical velocity increases as the height decreases, while at PE the vertical velocity decreases as the height decreases. These features of the vertical profiles of reflectivity and vertical velocity could be explained by the more frequent occurrence of aggregation and riming at DDU compared to PE because of the lower temperature and relative humidity at the latter, located further in the interior. Robust and reliable statistics about the vertical profile of precipitation in Antarctica, as derived from MRRs for instance, are necessary and valuable for the evaluation of precipitation estimates derived from satellite measurements and from numerical atmospheric models.

Abstract: The quantification of uncertainty sources in ensembles of climate projections obtained from combinations of different scenarios and climate and impact models is a key issue in climate impact studies. The small size of the ensembles of simulation chains and their incomplete sampling of scenario and climate model combinations makes the analysis difficult. In the popular single-time ANOVA approach for instance, a precise estimate of internal variability requires multiple members for each simulation chain (e.g., each emission scenario-climate model combination), but multiple members are typically available for a few chains only. In most ensembles also, a precise partition of model uncertainty components is not possible because the matrix of available scenario/models combinations is incomplete (i.e., projections are missing for many scenario-model combinations). The method we present here, based on data augmentation and Bayesian techniques, overcomes such limitations and makes the statistical analysis possible for single-member and incomplete ensembles. It provides unbiased estimates of climate change responses of all simulation chains and of all uncertainty variables. It additionally propagates uncertainty due to missing information in the estimates. This approach is illustrated for projections of regional precipitation and temperature for four mountain massifs in France. It is applicable for any kind of ensemble of climate projections, including those produced from ad hoc impact models.

Abstract: In the French Alps the quality of the radar Quantitative Precipitation Estimation (QPE) is limited by the topography and the vertical structure of precipitation. A previous study realized in all the French Alps, has shown a general bias between values of the national radar QPE composite and the rain gauge measurements: a radar QPE over-estimation at low altitude (+20% at 200 m a.s.l.), and an increasing underestimation at high altitudes (until -40% at 2100 m a.s.l.). This trend has been linked to altitudinal gradients of precipitation observed at ground level. This paper analyzes relative altitudinal gradients of precipitation estimated with rain gauges measurements in 2016 for three massifs around Grenoble, and for different temporal accumulations (yearly, seasonal, monthly, daily). Comparisons of radar and rain gauge accumulations confirm the bias previously observed. The parts of the current radar data processing affecting the bias value are pointed out. The analysis shows a coherency between the relative gradient values estimated at the different temporal accumulations. Vertical profiles of precipitation detected by a research radar installed at the bottom of the valley also show how the wide horizontal variability of precipitation inside the valley can affect the gradient estimation.

Abstract: Quantifying model uncertainty and internal variability components in climate projections has been paid a great attention in the recent years. For multiple synthetic ensembles of climate projections, we compare the precision of uncertainty component estimates obtained respectively with the two Analysis of Variance (ANOVA) approaches mostly used in recent works: the popular Single Time approach (STANOVA), based on the data available for the considered projection lead time and a time series based approach (QEANOVA), which assumes quasi-ergodicity of climate outputs over the available simulation period. We show that the precision of all uncertainty estimates is higher when more members are used, when internal variability is smaller and/or the response-to-uncertainty ratio is higher. QEANOVA estimates are much more precise than STANOVA ones: QEANOVA simulated confidence intervals are roughly 3-5 times smaller than STANOVA ones. Except for STANOVA when less than three members is available, the precision is rather high for total uncertainty and moderate for internal variability estimates. For model uncertainty or response-to-uncertainty ratio estimates, the precision is low for QEANOVA to very low for STANOVA. In the most unfavorable configurations (small number of members, large internal variability), large over- or underestimation of uncertainty components is thus very likely. In a number of cases, the uncertainty analysis should thus be preferentially carried out with a time series approach or with a local-time series approach, applied to all predictions available in the temporal neighborhood of the target prediction lead time.

Abstract: The RadAlp experiment aims at developing advanced methods for rain and snow estimation using weather radar remote sensing techniques in high mountain regions for improved water resource assessment and hydrological risk mitigation. A unique observation system has been deployed in the French Alps, Grenoble region. It is composed of a Meteo-France operated X-band MOUC radar (volumetric, Doppler and polarimetric) on top of the Mt Moucherotte (1920 m ASL), the X-band XPORT research radar (volumetric, Doppler, polarimetric), a K-band micro rain radar (MRR, Doppler, vertically pointing) and in situ sensors (rain gauges, disdrometers), latter three operated on the Grenoble campus (220 m ASL). Based on the observation that the precipitation phase changes at/below the elevation of mountain-top MOUC radar for more than 60% of the significant events, an algorithm for ML identification has been developed using valley-based radar systems: it uses the quasi vertical profiles of XPORT polarimetric measurements (horizontal and vertical reflectivity, differential reflectivity, cross-polar correlation coefficient) and the MRR vertical profiles of apparent falling velocity spectra. The algorithm produces time series of the altitudes and values of peaks and inflection points of the different radar observables. A literature review allows us to link the micro-physical processes at play during the melting process with the available polarimetric and Doppler signatures, e.g., (i) regarding the altitude differences between the peaks of reflectivity, cross-polar correlation coefficient and differential reflectivity, as well as (ii) regarding the co-variation of the profiles of Doppler velocity spectra and cross-polar correlation coefficient. A statistical analysis of the ML based on 42 rain events (98 h of XPORT data) is then proposed. Among other results, this study indicates that (i) the mean value of the ML width in Grenoble is 610 m with a standard deviation of 160 m; (ii) the mean altitude difference between the horizontal reflectivity and the rho HV peaks is 90 m and the mean altitude difference between the rho HV and Zdr peaks is 30 m; (iii) even for the limited rainrate range in the dataset (0-8.5 mm h-1), the “intensity effect” is clear on the reflectivity profile and the ML width, as well as on polarimetric variables such as rho HV peak value and the Zdr enhancement in the upper part of the profile. On the contrary, the study of both the “density effect” and the influence of the 0 degrees C isotherm altitude did not yield significant results with the considered dataset; (iv) a principal component analysis on one hand shows the richness of the dataset since the first 2 PCs explain only 50% of the total variance and on the other hand the added-value of the polarimetric variables since they rank high in a ranking of the total variance explained by individual variables.

Abstract: Heat and cold waves may have considerable human and economic impacts in Europe. Recent events, like the heat waves observed in France in 2003 and Russia in 2010, illustrated the major consequences to be expected. Reliable Early Warning Systems for extreme temperatures would, therefore, be of high value for decision makers. However, they require a clear definition and robust forecasts of these events. This study analyzes the predictability of heat and cold waves over Europe, defined as at least three consecutive days of Tmin and Tmax above the quantile Q90 (under Q10), using the extended ensemble system of ECMWF. The results show significant predictability for events within a 2-week lead time, but with a strong decrease of the predictability during the first week of forecasts (from 80 to 40% of observed events correctly forecasted). The scores show a higher predictive skill for the cold waves (in winter) than for the heat waves (in summer). The uncertainties and the sensitivities of the predictability are discussed on the basis of tests conducted with different spatial and temporal resolutions. Results demonstrate the negligible effect of the temporal resolution (very few errors due to bad timing of the forecasts), and a better predictability of large-scale events. The onset and the end of the waves are slightly less predictable with an average of about 35% (30%) of observed heat (cold) waves onsets or ends correctly forecasted with a 5-day lead time. Finally, the forecasted intensities show a correlation of about 0.65 with those observed, revealing the challenge to predict this important characteristic.

Abstract: We propose in this article a regional study of intensity-duration-area-frequency (IDAF) relationships of annual rainfall maxima in southern France. For this we develop a regional extreme value IDAF model based on space-time scale invariance hypotheses. The model allows us to link the statistical distributions of rainfall maxima over any duration and area. It provides in particular an analytical expression of the areal reduction factor, which expresses how the statistical distribution of rainfall maxima changes as the area increases, for any fixed duration. It also provides an analytical expression of areal return level for the continuum of area and duration. The model is applied to radar reanalysis data covering a 13,000-km(2) region of southern France featuring contrasted rainfall regimes (2008-2015). We estimate the IDAF relationships centered on any radar pixel of the region in the range 3-48 hr and 1-2,025 km(2). We obtain in particular a spatial distribution of the areal reduction factor, which allows us to distinguish different rainfall regimes in the region. The overall IDAF model provides also a regional quantification of areal rainfall risk by allowing the computation of rainfall return level maps for any area and duration in the applicable range. Despite inevitable sampling issues due to the shortness of the data sample, we highlight important differences in the spatial distribution of areal rainfall risk depending on the area and duration, illustrating that a comprehensive storm risk evaluation should consider the continuum of area and duration rather than arbitrarily predefined ones.

Abstract: Risk management in mountainous regions requires a precise assessment of snow extremes. We adopt the framework of max-stable processes, which connect extreme value statistics and geostatistics, to investigate the spatial dependence of winter maxima of 3-day snowfall and snow depths in the French Alps. Two important issues are broached: model selection and temporal non-stationarity. First, we introduce a cross-validation procedure which is used to assess the predictive ability of several max-stable processes to capture the spatial dependence structure of snowfall maxima. Then, we highlight a decrease in spatial dependence of extreme snowfall during the last decades. Lastly, we show a way to model temporal trends in a spatial dependence of extremes through the example of snow depth maxima. For both extreme snowfall and extreme snow depths, we find that the spatial dependence is strongly impacted by climate change, at first by the effect of the increase in temperature on the snow rain partitioning, also by the decrease in winter cumulated snowfall.

Abstract: In many regions worldwide, the electrification of rural areas is expected to be partly achieved through micro power grids. Compliance with the COP21 conference requires that such systems mainly build on renewable energy sources. To deliver a high power and quality service may be difficult to be achieved, especially when micro-grids are based on variable renewable sources. We here explore the multiscale temporal variability of the local solar resource in Africa and its implication for the development of 100% solar systems. Using high resolution satellite data of global horizontal irradiance (GHI) for a 21-year period (1995-2015), we characterize the seasonality and temporal variability of the local resource. We focus on its low percentile values which give a first guess on the size of the solar panels surface required for the micro-grid to achieve a given quality service. We assess the characteristics and especially persistence of the low resource situations, for which the local demand would not be satisfied. We finally assess how the ability of electricity consumers for some day-to-day flexibility (e.g. via the postponement of part of one day as demand to the next), would help to achieve the design level of service quality with a smaller microgrid system. (C) 2018 Elsevier Ltd. All rights reserved.

Abstract: Antarctica is among the most important regions when it comes to observing the effects of climate change. One important part of the variability of the land surface temperature (LST) observed on this continent is related to the sea surface temperature of the Tropical Pacific Ocean, which is associated with El Nino-Southern Oscillation (ENSO). This large-scale phenomenon is called tele-connection. In this study, we investigate the recent trends of LST in Antarctica over the last few decades and its relationship with one of the most intense El Nino events in 2015-2016. LST anomalies derived from satellite data (MODIS) and skin temperature from re-analysis (ERA-5 and ERA-Interim) were used, in addition to the Oceanic Nino Index (ONI) and Southern Annular Mode (SAM) time series. A non-parametric time series analysis was carried out to estimate LST trends over different zones of Antarctica. The results show a warming trend obtained from ERA-5 of about 0.9 K/decade in the interior of Antarctica, while MODIS showed the lowest temperature trends of similar to 1 K/decade in East Antarctica. The analysis between LST and the SAM index shows a negative relationship in the extreme periods of ENSO 2015-2016, showing colder autumns and warmer springs than in previous years. These results aide in understanding the effects of extreme phases of ENSO on Antarctica, which are of great importance given the projection of more intense phases over the next century as foreseen in future scenarios of climate change.

Abstract: This article focuses on conceptual and methodological developments allowing the integration of physical and social dynamics leading to model forecasts of circumstance-specific human losses during a flash flood. To reach this objective, a random forest classifier is applied to assess the likelihood of fatality occurrence for a given circumstance as a function of representative indicators. Here, vehicle-related circumstance is chosen as the literature indicates that most fatalities from flash flooding fall in this category. A database of flash flood events, with and without human losses from 2001 to 2011 in the United States, is supplemented with other variables describing the storm event, the spatial distribution of the sensitive characteristics of the exposed population, and built environment at the county level. The catastrophic flash floods of May 2015 in the states of Texas and Oklahoma are used as a case study to map the dynamics of the estimated probabilistic human risk on a daily scale. The results indicate the importance of time- and space-dependent human vulnerability and risk assessment for short-fuse flood events. The need for more systematic human impact data collection is also highlighted to advance impact-based predictive models for flash flood casualties using machine-learning approaches in the future.

Abstract: River flooding is among the most destructive of natural hazards globally, causing widespread loss of life, damage to infrastructure and economic deprivation. Societies are currently under increasing threat from such floods, predominantly from increasing exposure of people and assets in flood-prone areas, but also as a result of changes in flood magnitude, frequency, and timing. Accurate flood hazard and risk assessment are therefore crucial for the sustainable development of societies worldwide. With a paucity of hydrological measurements, evidence from the field offers the only insight into truly extreme events and their variability in space and time. Historical, botanical, and geological archives have increasingly been recognized as valuable sources of extreme flood event information. These different archives are here reviewed with a particular focus on the recording mechanisms of flood information, the historical development of the methodological approaches and the type of information that those archives can provide. These studies provide a wealthy dataset of hundreds of historical and palaeoflood series, whose analysis reveals a noticeable dominance of records in Europe. After describing the diversity of flood information provided by this dataset, we identify how these records have improved and could further improve flood hazard assessments and, thereby, flood management and mitigation plans. This article is categorized under: Science of Water > Water Quality Engineering Water > Planning Water Science of Water > Methods

Abstract: The region of Valencia in Spain has historically been affected by heavy precipitation events (HPEs). These HPEs are known to be modulated by the sea surface temperature (SST) of the Balearic Sea. Using an atmosphere-ocean regional climate model, we show that more than 70 % of the HPEs in the region of Valencia present a SST cooling larger than the monthly trend in the Northwestern Mediterranean before the HPEs. This is linked to the breaking of a Rossby wave preceding the HPEs: a ridge-trough pattern at mid-levels centered over western France associated with a low-level depression in the Gulf of Genoa precedes the generation of a cut-off low over southern Spain with a surface depression over the Alboran Sea in the lee of the Atlas. This latter situation is favourable to the advection of warm and moist air towards the Mediterranean Spanish coast, possibly leading to HPEs. The depression in the Gulf of Genoa generates intense northerly (Mistral) to northwesterly (Tramontane/Cierzo) winds. In most cases, these intense winds trigger entrainment at the bottom of the oceanic mixed layer which is a mechanism explaining part of the SST cooling in most cases. Our study suggests that the SST cooling due to this strong wind regime then persists until the HPEs and reduces the precipitation intensity.

Abstract: Over the twentieth century, Sahel rainfall has undergone extreme variations on a decadal timescale. This study investigated the recent precipitation changes in West African Sahel using a high-resolution Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) product over the period 1981-2014. We found that the recent increase in precipitation results principally from an increase in the number of wet days (+10 d compared to the normal) over the entire West African Sahel band, along with an increase in the precipitation intensity over the central part of the West African Sahel (+ 3 mm d(-1)). However, this overall increase in precipitation is associated with dry spells that are becoming more frequent but on average shorter over the entire West African Sahel band (on average by 30%), and with precipitation intensity that is decreasing (around 3 mm d(-1) during the study period) in the western part of the West African Sahel (Senegal). Such reorganization (i.e. weaker but more frequent precipitation) is expected to be beneficial for agriculture and society, reducing the likelihood of both flooding and droughts.

Abstract: This paper makes a regional evaluation of trend in yearly maxima of daily rainfall in southern France, both at point and spatial scales on a regular grid of 8 x 8 km(2). In order to filter out the high variability of rainfall maxima, the current analysis is based on a non-stationary GEV modeling in which the location parameter is allowed to vary with time. Three non-stationary models are considered for each series of maxima by constraining the location parameter to vary either linearly, linearly after a given date or linearly up to a final date. Statistical criteria are used to compare these models and select the best starting or final point of putative trends. The analysis shows that, at regional scale, the best distribution of maxima involves a linear trend starting in year 1985 and that this trend is significant in half the region, including most of the mountain ranges and part of the Rhne valley. Increases in yearly maxima are considerable since they reach up more than 60 mm/day in 20 years, which is more than 40 % of the average maximum in this area.

Abstract: Design flood estimates for a given return period are required in both gauged and ungauged catchments for hydraulic design and risk assessments. Contrary to classical design estimates, synthetic design hydrographs provide not only information on the peak magnitude of events but also on the corresponding hydrograph volumes together with the hydrograph shapes. In this study, we tested different regionalization approaches to transfer parameters of synthetic design hydrographs from gauged to ungauged catchments. These approaches include classical regionalization methods such as linear regression techniques, spatial methods, and methods based on the formation of homogeneous regions. In addition to these classical approaches, we tested nonlinear regression models not commonly used in hydrological regionalization studies, such as random forest, bagging, and boosting. We found that parameters related to the magnitude of the design event can be regionalized well using both linear and nonlinear regression techniques using catchment area, length of the main channel, maximum precipitation intensity, and relief energy as explanatory variables. The hydrograph shape, however, was found to be more difficult to regionalize due to its high variability within a catchment. Such variability might be better represented by looking at flood-type specific synthetic design hydrographs.

Abstract: Design hydrographs described by peak discharge, hydrograph volume, and hydrograph shape are essential for engineering tasks involving storage. Such design hydrographs are inherently uncertain as are classical flood estimates focusing on peak discharge only. Various sources of uncertainty contribute to the total uncertainty of synthetic design hydrographs for gauged and ungauged catchments. These comprise model uncertainties, sampling uncertainty, and uncertainty due to the choice of a regionalization method. A quantification of the uncertainties associated with flood estimates is essential for reliable decision making and allows for the identification of important uncertainty sources. We therefore propose an uncertainty assessment framework for the quantification of the uncertainty associated with synthetic design hydrographs. The framework is based on bootstrap simulations and consists of three levels of complexity. On the first level, we assess the uncertainty due to individual uncertainty sources. On the second level, we quantify the total uncertainty of design hydrographs for gauged catchments and the total uncertainty of regionalizing them to ungauged catchments but independently from the construction uncertainty. On the third level, we assess the coupled uncertainty of synthetic design hydrographs in ungauged catchments, jointly considering construction and regionalization uncertainty. We find that the most important sources of uncertainty in design hydrograph construction are the record length and the choice of the flood sampling strategy. The total uncertainty of design hydrographs in ungauged catchments depends on the catchment properties and is not negligible in our case.

Abstract: Flood hydrograph shapes contain valuable information on the flood-generation mechanisms of a catchment. To make good use of this information, we express flood hydrograph shapes as continuous functions using a functional data approach. We propose a clustering approach based on functional data for flood hydrograph shapes to identify a set of representative hydrograph shapes on a catchment scale and use these catchment-specific sets of representative hydrographs to establish regions of catchments with similar flood reactivity on a regional scale. We applied this approach to flood samples of 163 medium-size Swiss catchments. The results indicate that three representative hydrograph shapes sufficiently describe the hydrograph shape variability within a catchment and therefore can be used as a proxy for the flood behavior of a catchment. These catchment-specific sets of three hydrographs were used to group the catchments into three reactivity regions of similar flood behavior. These regions were not only characterized by similar hydrograph shapes and reactivity but also by event magnitudes and triggering event conditions. We envision these regions to be useful in regionalization studies, regional flood frequency analyses, and to allow for the construction of synthetic design hydrographs in ungauged catchments. The clustering approach based on functional data which establish these regions is very flexible and has the potential to be extended to other geographical regions or toward the use in climate impact studies.

Abstract: This paper develops a new nonparametric method that is suitable for detecting slowly-varying nonstationarities that can be seen as trends in the time marginal of the time-varying spectrum of the signal. The rationale behind the proposed method is to measure the importance of the trend in the time marginal by using a proper test statistic, and further compare this measurement with the ones that are likely to be found in stationary references. It is shown that the distribution of the test statistic under stationarity can be modeled fairly well by a Generalized Extreme Value (GEV) pdf, from which a threshold can be derived for testing stationarity by means of a hypothesis test. Finally, the new method is compared with other ones found in the literature. (C) 2017 Published by Elsevier B.V.

Abstract: We used the Abdu Salam International Centre for Theoretical Physics (ICTP) Regional Climate Model version 4.5 (RegCM4.5), to investigate the potential impacts of land cover change of the Sahel-Sahara interface on the West African climate over an interannual timescale from 1990 to 2009. A simulation at 50 km grid spacing is performed with the standard version of the RegCM4.5 model (control run), followed by three vegetation change experiments at the Sahel-Sahara interface (15 degrees N and 20 degrees N): forest, tall grass, and short grass savanna. The impacts of land cover change are assessed by analyzing the difference between the altered runs and the control one in different sub-domains (western Sahel, central Sahel, eastern Sahel, and Guinea). Results show that the presence of forest, tall grass, and short grass savanna at the Sahel-Sahara interface tends to decrease the mean summer surface temperature in the whole domain. Nevertheless, this decrease is more pronounced over the Central Sahel when considering the forest experiment. This temperature decrease is associated with a weakening (strengthening) of the sensible (latent) heat flux in the whole domain. An analysis of the radiation field is performed to better explain the changes noted in the latent heat flux, the sensible heat flux, and the surface temperature. When considering the rainfall signal, the analysis shows that the afforestation options tend to alter the precipitation in the considered sub-domains substantially by increasing it in the whole Sahel region, with strong interannual variability. This rainfall increase is associated with an increase of the atmospheric moisture. Finally, we investigated the impacts of the afforestation options on some features of the rainfall events, and on the atmospheric dynamics during wet and dry years. All afforestation options tend to increase the frequency of the number of rainy days in regions located south of 18 degrees N during both periods. Nevertheless, this increase is stronger over the Central and Eastern Sahel during wet years in the forest case. All afforestation experiments induce an increase (decrease) of the low-levels monsoon flux in the Eastern Sahel (western Sahel) during both periods. At the mid-levels, the three afforestation options tend to move northward and to decrease the intensity of the African Easterly Jet (AEJ) south of 13 degrees N during wet and dry years.The intensity of the AEJ is weaker during the wet period. The vegetation change experiments also affect the Tropical Easterly Jet (TEJ), especially during wet years, by increasing its intensity over the southern Sahel. The analysis of the activity of African Easterly Waves (AEWs) patterns exhibits a decrease of the intensity of these disturbances over the Sahel during both periods. This may be due to the weakening of the meridional temperature contrast between the continent and the Gulf of Guinea due to the Sahel-Sahara surface temperature cooling induced by the afforestation. In summary, this study shows that during both periods, the increase of the atmospheric moisture due to the afforestation is associated with favorable AEJ/TEJ configurations (weaker and northward position of the AEJ; stronger TEJ) which in turn may create a stronger convection and then, an increase in the Sahel rainfall. This Sahel rainfall increase is associated with a strengthening of the intense and heavy rainfall events which may impact diversely local populations.

Abstract: Traffic source emission inventories for the rapidly growing West African urban cities are necessary for better characterization of local vehicle emissions released into the atmosphere of these cities. This study is based on local field measurements in Yopougon (Abidjan, Cote d'Ivoire) in 2016; a site representative of anthropogenic activities in West African cities. The measurements provided data on vehicle type and age, traveling time, fuel type, and estimated amount of fuel consumption. The data revealed high traffic flow of personal cars on highways, boulevards, and backstreets, whereas high flows of intra-communal sedan taxis were observed on main and secondary roads. In addition, the highest daily fuel consumption value of 56 L.day(-1) was recorded for heavy vehicles, while the lowest value of 15 L.day(-1) was recorded for personal cars using gasoline. This study is important for the improvement of uncertainties related to the different databases used to estimate emissions either in national or international reports. This work provides useful information for future studies on urban air quality, climate, and health impact assessments in African cities. It may also be useful for policy makers to support implementation of emission reduction policies in West African cities.

Abstract: We present a multi-site stochastic model for the generation of average daily temperature, which includes a flexible parametric distribution and a multivariate autoregressive process. Different versions of this model are applied to a set of 26 stations located in Switzerland. The importance of specific statistical characteristics of the model (seasonality, marginal distributions of standardized temperature, spatial and temporal dependence) is discussed. In particular, the proposed marginal distribution is shown to improve the reproduction of extreme temperatures (minima and maxima). We also demonstrate that the frequency and duration of cold spells and heat waves are dramatically underestimated when the autocorrelation of temperature is not taken into account in the model. An adequate representation of these characteristics can be crucial depending on the field of application, and we discuss potential implications in different contexts (agriculture, forestry, hydrology, human health).

Abstract: Moving towards energy systems with high variable renewable energy shares requires a good understanding of the impacts of climate change on the energy penetration. To do so, most prior impact studies have considered climate projections available from Global Circulation Models (GCMs). Other studies apply sensitivity analyses on the climate variables that drive the system behavior to inform how much the system changes due to climate change. In the present work, we apply the Decision Scaling approach, a framework merging these two approaches, for analyzing a renewables-only scenario for the electric system of Northern Italy where the main renewable sources are solar and hydropower. Decision Scaling explores the system sensibility to a range of future plausible climate states. GCM projections are considered to estimate probabilities of the future climate states. We focus on the likely future energy mix within the region (25% of solar photovoltaic and 75% of hydropower). We also carry out a sensitivity analysis according to the storage capacity. The results show that run-of-the river power generation from this Alpine area is expected to increase although the average inflow decreases under climate change. They also show that the penetration rate is expected to increase for systems with storage capacity less than one month of average load and inversely for higher storage capacity.

Abstract: The French critical zone initiative, called OZCAR (Observatoires de la Zone Critique-Application et Recherche or Critical Zone Observatories-Application and Research) is a National Research Infrastructure (RI). OZCAR-RI is a network of instrumented sites, bringing together 21 pre-existing research observatories monitoring different compartments of the zone situated between “the rock and the sky,” the Earth's skin or critical zone (CZ), over the long term. These observatories are regionally based and have specific initial scientific questions, monitoring strategies, databases, and modeling activities. The diversity of OZCAR-RI observatories and sites is well representative of the heterogeneity of the CZ and of the scientific communities studying it. Despite this diversity, all OZCAR-RI sites share a main overarching mandate, which is to monitor, understand, and predict (“earthcast”) the fluxes of water and matter of the Earth's near surface and how they will change in response to the “new climatic regime.” The vision for OZCAR strategic development aims at designing an open infrastructure, building a national CZ community able to share a systemic representation of the CZ, and educating a new generation of scientists more apt to tackle the wicked problem of the Anthropocene. OZCAR articulates around: (i) a set of common scientific questions and cross-cutting scientific activities using the wealth of OZCAR-RI observatories, (ii) an ambitious instrumental development program, and (iii) a better interaction between data and models to integrate the different time and spatial scales. Internationally, OZCAR-RI aims at strengthening the CZ community by providing a model of organization for pre-existing observatories and by offering CZ instrumented sites. OZCAR is one of two French mirrors of the European Strategy Forum on Research Infrastructure (eLTER-ESFRI) project.

Abstract: Compared to the other continents and lands, Antarctica suffers from a severe shortage of in situ observations of precipitation. APRES3 (Antarctic Precipitation, Remote Sensing from Surface and Space) is a program dedicated to improving the observation of Antarctic precipitation, both from the surface and from space, to assess climatologies and evaluate and ameliorate meteorological and climate models. A field measurement campaign was deployed at Dumont d'Urville station at the coast of Adelie Land in Antarctica, with an intensive observation period from November 2015 to February 2016 using X-band and K-band radars, a snow gauge, snowflake cameras and a disdrometer, followed by continuous radar monitoring through 2016 and beyond. Among other results, the observations show that a significant fraction of precipitation sublimates in a dry surface katabatic layer before it reaches and accumulates at the surface, a result derived from profiling radar measurements. While the bulk of the data analyses and scientific results are published in specialized journals, this paper provides a compact description of the dataset now archived in the PANGAEA data repository (https://www.pangaea.de, https://doi.org/10.1594/PANGAEA.883562) and made open to the scientific community to further its exploitation for Antarctic meteorology and climate research purposes.

Abstract: We analyzed helium and neon in 24 samples from between 3,607 and 3,767m (i.e., down to 2m above the lake-ice interface) of the accreted ice frozen to the ceiling of Lake Vostok. Within uncertainties, the neon budget of the lake is balanced, the neon supplied to the lake by the melting of glacier ice being compensated by the neon exported by lake ice. The helium concentration in the lake is about 12 times more than in the glacier ice, with a measured He-3/He-4 ratio of 0.120.01R(a). This shows that Lake Vostok's waters are enriched by a terrigenic helium source. The He-3/He-4 isotope ratio of this helium source was determined. Its radiogenic value (0.057xR(a)) is typical of an old continental province, ruling out any magmatic activity associated with the tectonic structure of the lake. It corresponds to a low geothermal heat flow estimated at 51mW/m(2). Plain Language Summary Extending over 15,000km(2) in a deep trough north of Vostok station, Lake Vostok is the largest and the deepest among the many subglacial lakes to have been discovered in Antarctica. Its ice ceiling is tilted, with an ice thickness of 3,750m in the south and 4,300m in the north. As the melting point is pressure dependent, the base of the glacier melts on the thick side (northern region) whereas lake water refreezes in the south, where the Vostok station is located. Unlike most gases, helium and neon can be incorporated into the crystal structure of ice during freezing. This property makes helium and neon isotopes in the accreted ice a valuable source of information on the concentration and isotope composition of both gases in the lake water itself. Between 2006 and 2012, we collected 24 samples from between 3,607 and 3,767m (i.e., down to 2m above the lake-ice interface) of the accreted ice frozen to the ceiling of Lake Vostok (lake ice) for analyzing helium and neon. Within uncertainties, the neon concentration measured in the lake ice is equal to that in the glacier ice. This indicates that the neon budget of the lake is balanced, the neon supply to the lake by the melting of glacier ice being compensated by the Ne export by lake ice. This confirms earlier suggestions from radar data and GPS measurements of surface ice velocity that the water added to the lake by the melting of glacier ice is balanced by the lake ice, which is exported by the glacier's movement out of the lake. Helium isotopes (He-3 and He-4) are sensitive indicators of tectonic-magmatic activity. In continental areas of recent tectonic-magmatic activity such as geothermal areas, the ratio He-3/He-4 is at its highest, accompanied by excess heat flow. On the contrary, in stable continental areas, low He-3/He-4 ratios are found. The low He-3/He-4 ratio in Lake Vostok clearly demonstrates the absence of volcanic and/or magmatic activity associated with the tectonic structure of the lake, in agreement with the absence of magnetic anomaly. The helium concentration in the lake is about 12 times the concentration measured in the glacier ice. This shows that the Lake Vostok's waters are enriched from beneath by a flux of helium typical of an old stable continental province. Helium isotopes points to a low geothermal heat flow beneath the lake. We estimate this heat flow at 51mW/m(2). This value is fully consistent with the heat flow map for Antarctica inferred from satellite magnetic data and corresponds to the baseline heat fl

Abstract: Reanalyses, based on numerical weather prediction methods assimilating past observations, provide continuous precipitation datasets and represent interesting options for assessing the climatology of regions with sparse station networks (e.g., northern Canada). However, reanalysis series cannot be used directly because of possible biases and mismatch between their spatial and temporal resolutions with that needed for local applications. To address these issues, a Stochastic Model Output Statistics (SMOS) approach was selected to post-process precipitation series simulated by the Climate Forecast System Reanalysis (CFSR) across Canada. This approach uses CFSR precipitation as a covariate and is based on two regression models: the first one is a logistic regression that deals with precipitation occurrence, and the second is a vector generalized linear model for precipitation intensity. At-site post-processed daily precipitation series are randomly generated using the SMOS approach, and selected climate indicators from the Expert Team on Climate Change Detection and Indices, which is jointly sponsored by the Commission for Climatology of the World Meteorological Organization's (WMO) World Climate Data and Monitoring Programme, the Climate Variability and Predictability Programme of the World Climate Research Programme, and the Joint WMO-IOC Technical Commission for Oceanography and Marine Meteorology (CCI/CLIVAR/JCOMM) are estimated and compared with corresponding observed and CFSR values. The two models in the SMOS approach, in addition to adequately correcting systematic biases, produced better predictions than the climatology of the wet and dry and intensity sequences. Additionally, the SMOS generally yields consistent climate indices when compared with those from CFSR without post-processing, though there is still room for improvement for specific indices (e.g., annual maximum of cumulative wet days).

Abstract: The Canadian Sea Ice and Snow Evolution (CanSISE) Network is a climate research network focused on developing and applying state-of-the-art observational data to advance dynamical prediction, projections, and understanding of seasonal snow cover and sea ice in Canada and the circumpolar Arctic. This study presents an assessment from the CanSISE Network of the ability of the second-generation Canadian Earth System Model (CanESM2) and the Canadian Seasonal to Interannual Prediction System (CanSIPS) to simulate and predict snow and sea ice from seasonal to multi-decadal timescales, with a focus on the Canadian sector. To account for observational uncertainty, model structural uncertainty, and internal climate variability, the analysis uses multi-source observations, multiple Earth system models (ESMs) in Phase 5 of the Coupled Model Intercomparison Project (CMIP5), and large initial-condition ensembles of CanESM2 and other models. It is found that the ability of the CanESM2 simulation to capture snow-related climate parameters, such as cold-region surface temperature and precipitation, lies within the range of currently available international models. Accounting for the considerable disagreement among satellite-era observational datasets on the distribution of snow water equivalent, CanESM2 has too much springtime snow mass over Canada, reflecting a broader northern hemispheric positive bias. Biases in seasonal snow cover extent are generally less pronounced. CanESM2 also exhibits retreat of springtime snow generally greater than observational estimates, after accounting for observational uncertainty and internal variability. Sea ice is biased low in the Canadian Arctic, which makes it difficult to assess the realism of long-term sea ice trends there. The strengths and weaknesses of the modelling system need to be understood as a practical tradeoff: the Canadian models are relatively inexpensive computationally because of their moderate resolution, thus enabling their use in operational seasonal prediction and for generating large ensembles of multidecadal simulations. Improvements in climate-prediction systems like CanSIPS rely not just on simulation quality but also on using novel observational constraints and the ready transfer of research to an operational setting. Improvements in seasonal forecasting practice arising from recent research include accurate initialization of snow and frozen soil, accounting for observational uncertainty in forecast verification, and sea ice thickness initialization using statist
ical predictors available in real time.

Abstract: An early warning system for drought events can provide valuable information for decision makers dealing with water resources management and international aid. However, predicting such extreme events is still a big challenge. In this study, we compare two approaches for drought predictions based on forecasted precipitation derived from the Ensemble extended forecast model (ENS) of the ECMWF, and on forecasted monthly occurrence anomalies of weather regimes (MOAWRs), also derived from the ECMWF model. Results show that the MOAWRs approach outperforms the one based on forecasted precipitation in winter in the north-eastern parts of the European continent, where more than 65 % of droughts are detected 1 month in advance. The approach based on forecasted precipitation achieves better performance in predicting drought events in central and eastern Europe in both spring and summer, when the local at mospheric forcing could be the key driver of the precipitation. Sensitivity tests also reveal the challenges in predicting small-scale droughts and drought onsets at longer lead times. Finally, the results show that the ENS model of the ECMWF successfully represents most of the observed linkages between large-scale atmospheric patterns, depicted by the weather regimes and drought events over Europe.

Abstract: Dust generation and transportation from North Africa are thought to modulate the West African Monsoon (WAM) features. In this study, we investigated the relationship between the Saharan Air Layer located above Atlantic Ocean (OSAL) and WAM features, including Monsoon flow, African Easterly Jet (AEJ) and Tropical Easterly Jet (TEJ) over West Africa using the RegCM4 regional model at 30 km grid resolution. Two sets of experiments with and without dust load were performed between 2007 and 2013 over the simulation domain, encompassing the whole of West Africa and a large part of the adjacent Atlantic Ocean. An intercomparison of the two simulations shows that dust load into the atmosphere greatly influences both the wind and temperature structure at different levels, resulting in the observed changes in the main features of the WAM system during summer. These changes lead to a westward shift with a slight strengthening of AEJ core over tropical Atlantic and weakening of both TEJ and monsoon flux penetration over land. In addition, despite running the RegCM4 with prescribed sea surface temperature, a correlation has been found between Aerosol Optical Depths in OSAL and WAM dynamics suggesting a mechanistic link between dust and WAM well reproduced by RegCM4.

Abstract: Modeling extreme snow depths in space is important for water storage, tourism industry, mountain ecosystems, collapse of buildings, and avalanche prevention. However, studies modeling the spatial dependence structure of extremes generally assume temporal stationarity which is clearly questionable in a climate change context. We model climatic trends within the spatial dependence structure of extremes, with application to a data set of snow depth winter maxima. From 82 stations spanning the 1970-2012 period in the French Alps, we infer a strong decrease in the range of spatial extremal dependence. This finding is related to a strong decrease in both the snow precipitation ratio and the winter cumulated snowfall, due to increasing temperatures. Hence, we demonstrate that the spatial dependence of extreme snow depths is impacted by climate change in a similar way as has been observed for extreme snowfalls. Furthermore, snow depths maxima are more spatially dependent than snowfalls. The space-time approach that we introduce may be very useful for assessing past and future evolutions under ongoing climate change in various hydrological quantities.

Abstract: Sequences of lake sediments often form long and continuous records that may be sensitive recorders of seismic shaking. A multi-proxy analysis of Lake Bohinj sediments associated with a well-constrained chronology was conducted to reconstruct Holocene seismic activity in the Julian Alps (Slovenia). A seismic reflection survey and sedimentological analyses identified 29 homogenite-type deposits related to mass-wasting deposits. The most recent homogenites can be linked to historical regional earthquakes (i.e. 1348ad, 1511ad and 1690ad) with strong epicentral intensity [greater than damaging' (VIII) on the Medvedev-Sponheuer-Karnik scale]. The correlation between the historical earthquake data set and the homogenites identified in a core isolated from local stream inputs, allows interpretation of all similar deposits as earthquake related. This work extends the earthquake chronicle of the last 6600years in this area with a total of 29 events recorded. The early Holocene sedimentary record is disturbed by a seismic event (6617 +/- 94calyrbp) that reworked previously deposited sediment and led to a thick sediment deposit identified in the seismic survey. The period between 3500calyrbp and 2000calyrbp is characterized by a major destabilization in the watershed by human activities that led to increases in erosion and sedimentation rates. This change increased the lake's sensitivity to recording an earthquake (earthquake-sensitivity threshold index) with the occurrence of 72 turbidite-type deposits over this period. The high turbidite frequency identified could be the consequence of this change in lake earthquake sensitivity and thus these turbidites could be triggered by earthquake shaking, as other origins are discarded. This study illustrates why it is not acceptable to propose a return period for seismic activity recorded in lake sediment if the sedimentation rate varies significantly.

Abstract: Heat and discomfort indices are applied to the multimodel ensemble mean of COordinated Regional climate Downscaling EXperiment-Africa regional climate model projections to investigate future changes in heat stress and the proportion of human population at risk under 1.5 degrees C and 2 degrees C global warming scenarios over West Africa. The results show that heat stress of category Extreme Caution is projected to extend spatially (up to 25%) over most of the Gulf of Guinea, Sahel, and Sahara desert areas, with different regional coverage during the various seasons. Similarly, the projected seasonal proportion of human population at discomfort substantially increases to more than 50% over most of the region. In particular, in June-August over the Sahel and the western Sahara desert, new areas (15% of West Africa) where most of the population is at risk emerge. This indicates that from 50% to almost everyone over most of the Sahel countries and part of the western Sahara desert is at risk of possible heat cramp, heat exhaustion, and heat stroke in future climate scenarios. These conditions become more frequent and are accompanied by the emergence of days with dangerous heat stress category during which everyone feels discomfort and is vulnerable to a likely heat cramp and heat exhaustion. In general, all the above features are more extended and more frequent in the 2 degrees C than in the 1.5 degrees C scenario. Protective measures are thus required for outdoor workers, occupational settings in hot environments, and people engaged in strenuous activities.

Abstract: The Cevennes-Vivarais region in southern France is prone to heavy rainfall that can lead to flash floods which are one of the most hazardous natural risks in Europe. The results of numerous studies show that besides rainfall and physical catchment characteristics the catchment's initial soil moisture also impacts the hydrological response to rain events. The aim of this paper is to analyze the relationship between catchment mean initial soil moisture (theta) over bar (ini) and the hydrological response that is quantified using the event-based runoff coefficient phi(ev) in the two nested catchments of the Gazel (3.4 km(2)) and the Claduegne (43 km(2)). Thus, the objectives are twofold: (1) obtaining meaningful estimates of soil moisture at catchment scale from a dense network of in situ measurements and (2) using this estimate of (theta) over bar (ini) to analyze its relation with phi(ev) calculated for many runoff events. A sampling setup including 45 permanently installed frequency domain reflectancy probes that continuously measure soil moisture at three depths is applied. Additionally, on-alert surface measurements at approximate to 10 locations in each one of 11 plots are conducted. Thus, catchment mean soil moisture can be confidently assessed with a standard error of the mean of <= 1.7 vol% over a wide range of soil moisture conditions. The phi(ev) is calculated from high-resolution discharge and precipitation data for several rain events with a cumulative precipitation P-cum ranging from less than 5mm to more than 80 mm. Because of the high uncertainty of phi(ev) associated with the hydrograph separation method, phi(ev) is calculated with several methods, including graphical methods, digital filters and a tracer-based method. The results indicate that the hydrological response depends on (theta) over bar (ini): during dry conditions phi(ev) is consistently below 0.1, even for events with high and intense precipitation. Above a threshold of (theta) over bar (ini) = 34 vol % phi(ev) can reach values up to 0.99 but there is a high scatter. Some variability can be explained with a weak correlation of phi(ev) with P-cum and rain intensity, but a considerable part of the variability remains unexplained. It is concluded that threshold-based methods can be helpful to prevent overestimation of the hydrological response during dry catchment conditions. The impact of soil moisture on the hydrological response during wet catchment conditions, however, is still insufficiently understood and cannot be generalized based on the present results.

Abstract: Assessments of present and future flood hazard are often limited by the scarcity and short time span of the instrumental time series. In pursuit of documenting the occurrence and magnitude of pre-instrumental flood events, the field of paleoflood hydrology emerged during the second half of the 20th century. Historically, this field has mainly been developed on the identification and dating of flood evidence in fluvial sedimentary archives. In the last two decades, paleoflood hydrology approaches have also been deployed to investigate past floods contained in other natural archives. This article reviews major methodological and technological advancements in the study of lake sediments with the aim to showcase new, robust and continuous paleoflood series. Methodological advancements of flood archives such as tree rings and speleothems are also addressed. The recent developments in these fields have resulted in a growing paleoflood community that opens for cross-disciplinary analysis and synthesis of large data sets to meet the pressing scientific challenges in understanding changes in flood frequency and magnitude.

Abstract: Rainfall is an important driver of erosion processes. The mean rainfall rate is often used to account for the erosive impact of a particular climate. However, for some erosion processes, erosion rate is a nonlinear function of rainfall, e.g., due to a threshold for erosion. When this is the case, it is important to take into account the full distribution of rainfall, instead of just the mean. In light of this, we have characterized the variability of daily rainfall over the Himalayan orogen using high spatial and temporal resolution rainfall data sets. We find significant variations in rainfall variability over the Himalayan orogen, with increasing rainfall variability to the west and north of the orogen. By taking into account variability of rainfall in addition to mean rainfall rate, we find a pattern of rainfall that, from a geomorphological perspective, is significantly different from mean rainfall rate alone. Using these findings, we argue that short-term rainfall variability may help explain observed short and long-term erosion rates in the Himalayan orogen. Plain Language Summary An important topic in earth science is understanding how climate and tectonic forces interact to shape the surface of the Earth. One of the main influences that climate has on the Earth's surface is to cause erosion by delivering water to landscapes as rain and snow. Wetter climates should, in general, cause more erosion than drier climates, which is why the mean annual rainfall has traditionally been used as a measure of the erosive strength of climate. However, field evidence seems to suggest that the effect of climate is more sophisticated than can be captured with the mean annual rainfall. There is a considerable body of theory demonstrating that the intensity of rainfall, or storminess, is an equally important aspect of how climate causes erosion. In light of this, we have characterized the storminess in the Himalayan mountain range, a place with high erosion rates driven by rainfall. We show that there is large variation in storminess from place to place in the Himalayas, and that this can help explain observed rates of erosion, which do not match mean annual rainfall rates.

Abstract: A major part of renewable electricity production is characterized by a large degree of intermittency driven by the natural variability of climate factors such as air temperature, wind velocity, solar radiation, precipitation, evaporation, and river runoff. The main strategies to handle this intermittency include energy-storage, -transport, -diversity and-information. The three first strategies smooth out the variability of production in time and space, whereas the last one aims a better balance between production and demand. This study presents a literature review on the space-time variability of climate variables driving the intermittency of wind-, solar and hydropower productions and their joint management in electricity systems. A vast body of studies pertains to this question bringing results covering the full spectrum of resolutions and extents, using a variety of data sources, but mostly dealing with a single source. Our synthesis highlights the consistency of these works, and, besides astronomic forcing, we identify three broad climatic regimes governing the variability of renewable production and load. At sub-daily time scales, the three considered renewables have drastically different pattern sizes in response to small scale atmospheric processes. At regional scales, large perturbation weather patterns consistently control wind and solar production, hydropower having a clearly distinct type of pattern. At continental scales, all renewable sources and load seem to display patterns of constant space characteristics and no indication of marked temporal trends.

Abstract: Using 17 years (1998-2014) of daily TRMM 3B42 rainfall data, we provide a climatological characterization of wet and dry spells in West Africa, which should serve to assess the ability of climate model to simulate these high impact events. The study focuses on four subregions (Western and Central Sahel, Sudanian zone and Guinea Coast). Defining wet (dry) spells as sequences of consecutive days with precipitation higher (lower) than 1 mm, we describe the space-time variability of wet and dry spell occurrence. This climatology stresses the influence of the relief on the number and duration of these spells. The spatio-temporal variability of the wet and dry spells also appears to be closely related to the spatio-temporal variability of the West African monsoon. The number of wet spells of all durations and of 2-3 day dry spells have similar features with a maximum occurrence during the local rainy seasons and a spatial pattern similar to the mean annual rainfall with a north-south gradient. In contrast, dry spells lasting more than four days show some singularities such as a low occurrence over the Sahelian band or high occurrence along the Guinea Coast mainly from Ivory Coast to Benin. Moreover, the seasonal cycle of these longer dry spells presents higher occurrences at the beginning and the end of the rainy seasons.

Abstract: Mediterranean regions are prone to heavy rainfall, flash floods, and erosion issues. Drop size distribution (DSD) is a key element for studying these phenomena through the hydrological variables which can be derived from it (rainfall rates and totals, kinetic energy fluxes). This paper proposes a five-year (2012-2016) DSD climatology, summarized by scaling parameters for concentration, size, and shape. The DSD network is composed of two longitudinal transects of three OTT Parsivel optical disdrometers each, across the Mediterranean Cevennes-Vivarais region. The influence of several factors are analysed: location (distance from the sea, orographic environment), season, daily synoptic weather situation (derived from geopotential heights, at 700 and 1000 hPa), rainfall type (analysed from 5 min radar data), as well as some combinations of these factors. It was found and/or confirmed that the orographic environment, season, weather patterns associated with the exposure to low level atmospheric flows, and rainfall types influenced the microphysical processes, leading to rainfall, measured at the ground. Consequently, the DSD characteristics, as well as the relationships between the rainfall rate and reflectivity factor, are influenced by these factors.

Abstract: The nature and timing of environmental changes throughout the last glacial-interglacial transition in the South Caucasus, and more widely in eastern Europe, are still not fully understood. According to certain pollen records, forest expansion occurred in many areas several millennia after what is considered worldwide as the onset of the Holocene. The current problem we face is that the time lag in forest expansion varies from one sequence to another, sometimes with no delay at all. Moreover, the potential forcing/controlling factors behind this complex pattern, contrary to the almost synchronous global Holocene warming, are still a matter for debate. Accordingly, we revisit the issue of forest expansion through vegetation history obtained in the South Caucasus using a new pollen record, retrieved from the Nariani paleolake (South Georgia). These data attest to a steppic phase, initially dominated by Amaranthaceae-Chenopodiaceae (12,700-10,500 cal yr BP), then by Poaceae (10,500-9000 cal yr BP), culminating with a more forested phase (9000-5000 cal yr BP). Although some palaeoclimatic regional reconstructions show a wet early Holocene, we interpret the delay in forest expansion recorded in Nariani (2500 years) as the result of reduced spring precipitation, which would have limited forest development at that time.

Abstract: A comprehensive hydrometeorological dataset is presented spanning the period 1 January 201131 December 2014 to improve the understanding of the hydrological processes leading to flash floods and the relation between rainfall, runoff, erosion and sediment transport in a mesoscale catchment (Auzon, 116 km(2)) of the Mediterranean region. Badlands are present in the Auzon catchment and well connected to high-gradient channels of bedrock rivers which promotes the transfer of suspended solids downstream. The number of observed variables, the various sensors involved (both in situ and remote) and the space-time resolution (similar to km(2), similar to min) of this comprehensive dataset make it a unique contribution to research communities focused on hydrometeorology, surface hydrology and erosion. Given that rainfall is highly variable in space and time in this region, the observation system enables assessment of the hydrological response to rainfall fields. Indeed, (i) rainfall data are provided by rain gauges (both a research network of 21 rain gauges with a 5 min time step and an operational network of 10 rain gauges with a 5 min or 1 h time step), S-band Doppler dual-polarization radars (1 km(2), 5 min resolution), disdrometers (16 sensors working at 30 s or 1 min time step) and Micro Rain Radars (5 sensors, 100m height resolution). Additionally, during the special observation period (SOP-1) of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, two X-band radars provided precipitation measurements at very fine spatial and temporal scales (1 ha, 5 min). (ii) Other meteorological data are taken from the operational surface weather observation stations of Meteo-France (including 2m air temperature, atmospheric pressure, 2 m relative humidity, 10m wind speed and direction, global radiation) at the hourly time resolution (six stations in the region of interest). (iii) The monitoring of surface hydrology and suspended sediment is multi-scale and based on nested catchments. Three hydrometric stations estimate water discharge at a 2-10 min time resolution. Two of these stations also measure additional physico-chemical variables (turbidity, temperature, conductivity) and water samples are collected automatically during floods, allowing further geochemical characterization of water and suspended solids. Two experimental plots monitor overland flow and erosion at 1 min time resolution on a hillslope with vineyard. A network of 11 sensors installed in the intermittent hydrographic network continuously me
asures water level and water temperature in headwater subcatchments (from 0.17 to 116 km(2)) at a time resolution of 2-5 min. A network of soil moisture sensors enables the continuous measurement of soil volumetric water content at 20 min time resolution at 9 sites. Additionally, concomitant observations (soil moisture measurements and stream gauging) were performed during floods between 2012 and 2014. Finally, this dataset is considered appropriate for understanding the rainfall variability in time and space at fine scales, improving areal rainfall estimations and progressing in distributed hydrological and erosion modelling.

Abstract: Great effort is made to address heat waves (HWs) in developed countries because of their devastating impacts on society, economy, and environment. However, HWs are still understudied over developing countries. This is particularly true in West Africa, and especially in the Sahel, where temperatures recurrently reach critical values, such as during the 2010 HW event in the western Sahel. This work aims at characterizing the Sahelian HWs during boreal spring seasons (April-May-June) and understanding the mechanisms associated with such extreme events. Over the last three decades, Sahelian HWs have been becoming more frequent, lasting longer, covering larger areas, and reaching higher intensities. The physical mechanisms associated with HWs are examined to assess the respective roles of atmospheric dynamics and radiative and turbulent fluxes by analyzing the surface energy budget. Results suggest that the greenhouse effect of water vapor is the main driver of HWs in the western Sahel, increasing minimum temperatures by enhanced downward longwave radiation. Atmospheric circulation plays an important role in sustaining these warm anomalies by advecting moisture from the Atlantic Ocean and the Guinean coasts into the Sahel. Maximum temperature anomalies are mostly explained by increased downward shortwave radiation due to a reduction in cloud cover. Interannual variability of HWs is affected by the delayed impact of El Nio-Southern Oscillation (ENSO), with anomalous temperature warming following warm ENSO events, resulting from an amplified water vapor feedback.

Abstract: This study compares the multivariate predictions of daily temperature, temperature range, precipitation, surface wind and solar radiation of a single-model analogue approach with an original multi-model analogy over 12 regions in Europe and Maghreb. Both approaches are based on two-level analogue models where atmospheric predictors are either dynamic or thermodynamic. In the multi-model approach, independent analogue models with predictand-specific predictors are used. In the single-model one, a unique analogue model and its associated set of predictors is applied to all predictands. Testing numerous large-scale predictors, we first identify the best predictor sets for each modelling strategy. Those obtained for the single-model approach are significantly different from those of the predictand-specific models. This is especially the case for local temperature and wind speed. Both methods perform similarly for precipitation, temperature range and radiation. We next assess the ability of both approaches to simulate physically coherent multivariate weather scenarios. With the single-model method, weather scenarios are obtained for each prediction day from observations sampled simultaneously on one analogue day. The physical consistency between variables is thus automatically fulfilled each day. This allows the single-model method to reproduce well the observed inter-predictand correlations, especially the significant correlations between radiation and precipitation and between radiation and temperature range. These results suggest a hybrid analogue model using a single-model for radiation, temperature range and precipitation, combined with a univariate approach for wind. Two options are proposed for temperature for which either the predictand-specific method or a single-model approach with an additional correction are conceivable. This hybrid approach leads to a possible compromise between reasonable univariate prediction skills and realistic inter-predictands correlations, both classically required for many impact studies.

Abstract: Recent flash flood impact studies highlight that road networks are often disrupted due to adverse weather and flash flood events. Road users are thus particularly exposed to road flooding during their daily mobility. Previous exposure studies, however, do not take into consideration population mobility. Recent advances in transportation research provide an appropriate framework for simulating individual travelactivity patterns using an activity-based approach. These activity-based mobility models enable the prediction of the sequence of activities performed by individuals and locating them with a high spatial-temporal resolution. This paper describes the development of the MobRISK microsimulation system: a model for assessing the exposure of road users to extreme hydrometeorological events. MobRISK aims at providing an accurate spatiotemporal exposure assessment by integrating travel-activity behaviors and mobility adaptation with respect to weather disruptions. The model is applied in a flash-flood-prone area in southern France to assess motorists' exposure to the September 2002 flash flood event. The results show that risk of flooding mainly occurs in principal road links with considerable traffic load. However, a lag time between the timing of the road submersion and persons crossing these roads contributes to reducing the potential vehicle-related fatal accidents. It is also found that sociodemographic variables have a significant effect on individual exposure. Thus, the proposed model demonstrates the benefits of considering spatiotemporal dynamics of population exposure to flash floods and presents an important improvement in exposure assessment methods. Such improved characterization of road user exposures can present valuable information for flood risk management services.

Abstract: Mediterranean Alpine populations are particularly exposed to natural hazards like floods and earthquakes because of both the close Mediterranean humidity source and the seismically active Alpine region. Knowledge of longterm variability in flood and earthquake occurrences is of high value since it can be useful to improve risk assessment and mitigation. In this context, we explore the potential of a lake-sediment sequence from Lago Inferiore de Laures in Valle d'Aosta (Northern Italy) as a long-term record of past floods and earthquakes. The high-resolution sedimentological study revealed 76 event layers over the last ca. 270 years; 8 are interpreted as most probably induced by earthquakes and 68 by flood events. Comparison to historical seismic data suggests that the recorded earthquakes are strong (epicentral Medvedev-Sponheuer-Karnik (MSK) intensity of VI-IX) and/or close to the lake (distance of 25-120 km). Compared to other lake-sediment sequences, Lago Inferiore de Laures sediments appear to be regionally the most sensitive to earthquake shaking, offering a great potential to reconstruct the past regional seismicity further back in time. Comparison to historical and palaeoflood records suggests that the flood signal reconstructed from Lago Inferiore de Laures sediments represents the regional and (multi-) decadal variability of summer-autumn floods well, in connection to Mediterranean mesoscale precipitation events. Overall, our results reveal the high potential of Lago Inferiore de Laures sediments to extend the regional earthquake and flood catalogues far back in time.

Abstract: We review the scientific efforts over the last decades to reconstruct erosion from continuous alpine lake sediment records. We focused both on methodological issues, showing the growing importance of non-destructive high resolution approaches (XRF core-scanner) as well as progresses in the understanding of processes leading to the creation of an “erosion signal” in lakes. We distinguish “continuous records” from “event-records”. Both provide complementary information but need to be studied with different approaches. Continuous regionally-relevant records proved to be particularly pertinent to document regional erosion patterns throughout the Holocene, in particular applying the source to sink approach. Event-based approaches demonstrated and took advantage of the strong non-linearity of sediment transport in high altitude catchment areas. This led to flood frequency and intensity reconstructions, highlighting the influence of climate change upon flood dynamics in the mountain. The combination of different record types, both in terms of location (high vs. low elevation), sedimentology (high vs. low terrigenous contribution) and significance (local vs. regional) is one of the main outputs of this paper. It allows the establishment of comprehensive histories of NW French Alps erosion, but also and consequently, soil dynamics and hydrological patterns throughout the Holocene. We also discuss the influence of glacier dynamics, one of the major agents of erosion in the Alps. A major feature is the growing human influence upon erosion at a local scale since at least the middle of the Bronze Age (3500 cal. BP). However and according to the regional record from Lake Bourget, only few periods of rising erosion at local scales generated a regional record that can be discriminated from wetter climatic periods. Among them, the period between 200 BCE and 400 AD appeared to be marked by a generalised rise in human-triggered erosion at local scales in the northern French Alps. This review highlights the importance of modern high-resolution and interdisciplinary studies of lake sediments, in order to better understand the complex relationships between humans, climate and the Earth system in general. We strongly argue that regional integration of data is now required to move a step further. Such an integration is easier with cost- and time-effective methods as well as after a better definition of approaches and their limits. This should lead to a stronger collaboration between paleo-data producers and modellers in the near future. (C) 2016 Elsevier Ltd. All rights reserved.

Abstract: We propose in this paper a regional formulation of Intensity-Duration-Frequency curves of point-rainfall maxima in a scale-invariant Generalized Extreme Value (GEV) framework. The two assumptions we make is that extreme daily rainfall is GEV-distributed – which is justified by Extreme Value Theory (EVT) – and that extremes of aggregated daily rainfall follow simple-scaling relationships. Following these assumptions, we develop in a unified way a GEV simple-scaling model for extremes of aggregated daily rainfall over the range of durations where scaling applies. Then we propose a way of correcting this model for measurement frequency, giving a new GEV-scaling model for extremes of aggregated hourly rainfall. This model deviates from the simple-scaling assumption. This framework is applied to the Mediterranean region of Cevennes-Vivarais, France. A network of about 300 daily raingage stations covering the last 50 years and accumulated to span the range 1 day-1 week is used to fit the scale invariant GEV-model locally. By means of spatial interpolation of the model parameters, and correction for measurement frequency, we are able to build a regional model with good performances down to 1 h duration, even though only one hourly station is used to build the model. Finally we produce mean and return level maps within the region in the range 1 h-1 week and comment on the potential rain storms leading to these maps. (C) 2016 Elsevier B.V. All rights reserved.

Abstract: The particle identification scheme developed by Dolan and Rutledge for X-band polarimetric radar is tested for the first time in Africa and compared with in situ measurements. The data were acquired during the Megha-Tropiques mission algorithm-validation campaign that occurred in Niger in 2010. The radar classification is compared with the in situ observations gathered by an instrumented aircraft for the 13 August 2010 squall-line case. An original approach has been developed for the radar-in situ comparison: it consists of simulating synthetic radar variables from the microphysical-probe information and comparing the two datasets in a common “radar space.” The consistency between the two types of observation is good considering the differences in sampling illustrated in the paper. The time evolution of the hydrometeor types and their relative proportion in the convective and stratiform regions are analyzed. The farther away from the convection one looks, the more aggregation dominates, riming diminishes, and hydrometeors are less dense. Particle identification based on the polarimetric radar will be applied to a 5-yr African dataset in the future.

Abstract: Flash floods are responsible for a majority of natural disaster fatalities in the USA and Europe and most of them are vehicle-related. If human exposure to flood is generally assessed through the number of inhabitants per buildings located in flood prone zone, it is clear that this number varies dramatically throughout the day as people move from place to place to follow their daily program of activities. Knowing the number of motorists exposed on flood prone road sections or the factors determining their exposure would allow providing a more realistic evaluation of the degree of exposure. In order to bridge this gap and provide emergency managers with methods to assess the risk level for motorists, this paper describes two methods, a simple rough-and-ready estimate and a traffic attribution method, and applies both of them on datasets of the Gard departement, an administrative region of Southern France with about 700000 inhabitants over 5875 km(2). The first method to obtain an overall estimation of motorists flood exposure is to combine (i) the regional density of roads and rivers to derive a count of potential road cuts and (ii) the average daily kilometers driven by commuters of the study area to derive the number of people passing these potential cuts. If useful as a first approximation, this method fails to capture the spatial heterogeneities introduced by the geometry of river and road networks and the distribution of commuters' itineraries. To address this point, this paper (i) uses a pre-established detailed identification of road cuts (Naulin et al., 2013) and (ii) applies a well-known traffic attribution method to existing and freely available census datasets. Both methods indicate that commuters' exposure is much larger than the number of commuters itself, illustrating the risk amplification effect of mobility. Comparing the results from both methods shows that (i) the road network geometry plays a significant role in reducing the risk of river-road dangerous intersections and (ii) not all commuters are equally exposed. Evidently commuters who have longer routes are more exposed, but residents of rural municipalities as well as professionals with highly qualified jobs are also more exposed. Finally, these exposure assessment methods applied to the Gard area allows locating road sections where commuters' exposure to flood is high. It also sets the first step toward the implementation of a modeling platform able to combine the estimation of daily travel patterns exposure and behavioral response of motorists to road flooding, a critical input for emergency services and services in charge of the management of road networks in flash flood prone areas. (C) 2016 Elsevier B.V. All rights reserved.

Abstract: Streamflow time series provide baseline data for many hydrological investigations. Errors in the data mainly occur through uncertainty in gauging (measurement uncertainty) and uncertainty in the determination of the stage-discharge relationship based on gaugings (rating curve uncertainty). As the velocity area method is the measurement technique typically used for gaugings, it is fundamental to estimate its level of uncertainty. Different methods are available in the literature (ISO 748, Q+, IVE), all with their own limitations and drawbacks. Among the terms forming the combined relative uncertainty in measured discharge, the uncertainty component relating to the limited number of verticals often includes a large part of the relative uncertainty. It should therefore be estimated carefully. In ISO 748 standard, proposed values of this uncertainty component only depend on the number of verticals without considering their distribution with respect to the depth and velocity cross-sectional profiles. The Q+ method is sensitive to a user-defined parameter while it is questionable whether the IVE method is applicable to stream-gaugings performed with a limited number of verticals. To address the limitations of existing methods, this paper presents a new methodology, called FLow Analog UnceRtainty Estimation (Fume), to estimate the uncertainty component relating to the limited number of verticals. High-resolution reference gaugings (with 31 and more verticals) are used to assess the uncertainty component through a statistical analysis. Instead of subsampling purely randomly the verticals of these reference stream-gaugings, a subsampling method is developed in a way that mimicks the behavior of a hydrometric technician. A sampling quality index (SQI) is suggested and appears to be a more explanatory variable than the number of verticals. This index takes into account the spacing between verticals and the variation of unit flow between two verticals. To compute the uncertainty component for any routine gauging, the four most similar gaugings among the reference stream-gaugings dataset are selected using an analog approach, where analogy includes both riverbed shape and flow distribution complexity. This new method was applied to 3185 stream-gaugings with various flow conditions and compared with the other methods (ISO 748, IVE, with a simple automated parametrization). Results show that FLAME is overall consistent with the Q+ method but not with ISO 748 and NE methods, which produce clearly overestimated uncertainties fo
r discharge measurements with less than 15 verticals. The FLAURE approach therefore appears to be a consistent method. An advantage is the explicit link made between the estimation of cross-sectional interpolation errors and the study of high-resolution reference gaugings. (C) 2015 Elsevier B.V. All rights reserved.

Abstract: When considering 100% renewable scenarios, backup generation is needed for stabilizing the network when Climate Related Energy (CRE) such as wind, solar or run-of-the river hydropower are not sufficient for supplying the load. Several studies show that, over relatively short time period (less than 10 years), backup generation needs are reduced by dissipating power densities either in space through grids or time through storage. This study looks at the impact of low time frequency variations of CRE with a specific focus on the time variability induced by the North Atlantic Oscillation (NAO) teleconnection pattern during winter season. A set of eleven regions in Europe and Tunisia is used for highlighting space variability of the winter NAO's impact. For each of these regions, we combine data from the Weather Research and Forecasting Model and the European Climate Assessment & Dataset for estimating solar power, wind-power, run-of-the-river hydro-power and the energy load over the 1980-2012 time period. Results show that NAO's impact on winter penetration rate depends on both the considered energy source and the location. They also highlight a non-linear relation between the NAO's impact on CRE penetration rates and the level of equipment used for harvesting the CRE sources. (C) 2016 Elsevier Ltd. All rights reserved.

Abstract: The penetration rate of Climate Related Energy sources like solar-power, wind-power and hydro-power source is potentially low as a result of the large space and time variability of their driving climatic variables. Increased penetration rates can be achieved with mixes of sources. Optimal mixes, i.e. obtained with the optimal share for each source, are being identified for a number of regions worldwide. However, they often consider wind and solar power only. Based on 33 years of daily data (1980-2012) for a set of 12 European regions, we re-estimate the optimal mix when wild run-of-the-river energy is included in the solar/wind mix. It is found to be highly region dependent but the highest shares are often obtained for run-of-the-river, ranging from 35% to 65% in Belarus and England. High solar shares (>40%) are found in southern countries but solar shares drop to less than 15% in northern countries. Wind shares range from 10 to 35% with the exception of Norway where it reaches 50%. These results put in perspective the optimal 60%-40% wind/solar mix currently used for Europe. For all regions, including run-of-the-river in the mix allows increasing the penetration rate of CREs (from 1 to 8% points). (C) 2015 Elsevier Ltd. All rights reserved.

Abstract: The French research community in the Mediterranean Sea modeling and the French operational ocean forecasting center Mercator Ocean have gathered their skill and expertise in physical oceanography, ocean modeling, atmospheric forcings and data assimilation to carry out a MEDiterranean sea ReanalYsiS (MEDRYS) at high resolution for the period 1992-2013. The ocean model used is NEMOMED12, a Mediterranean configuration of NEMO with a 1/12 degrees (similar to 7 km) horizontal resolution and 75 vertical z levels with partial steps. At the surface, it is forced by a new atmospheric-forcing data set (ALDERA), coming from a dynamical downscaling of the ERA-Interim atmospheric reanalysis by the regional climate model ALADIN-Climate with a 12 km horizontal and 3 h temporal resolutions. This configuration is used to carry a 34-year hindcast simulation over the period 1979-2013 (NM12-FREE), which is the initial state of the reanalysis in October 1992. MEDRYS uses the existing Mercator Ocean data assimilation system SAM2 that is based on a reduced-order Kalman filter with a threedimensional (3-D) multivariate modal decomposition of the forecast error. Altimeter data, satellite sea surface temperature (SST) and temperature and salinity vertical profiles are jointly assimilated. This paper describes the configuration we used to perform MEDRYS. We then validate the skills of the data assimilation system. It is shown that the data as-similation restores a good average temperature and salinity at intermediate layers compared to the hindcast. No particular biases are identified in the bottom layers. However, the reanalysis shows slight positive biases of 0.02 psu and 0.15 degrees C above 150 m depth. In the validation stage, it is also shown that the assimilation allows one to better reproduce water, heat and salt transports through the Strait of Gibraltar. Finally, the ability of the reanalysis to represent the sea surface high-frequency variability is shown.

Abstract: The Sicily Channel surface circulation is investigated by analyzing the outputs of a high-resolution ocean model MED12 forced during 46 years by the ARPERA atmospheric fields. Applying a neural network classifier, we show that the surface circulation in the Sicily Channel can be decomposed into 8 modes characterizing the major patterns of that circulation, particularly the Algerian Current separation at the entrance to the Sicily Channel, the features of the Atlantic Tunisian Current and of the Atlantic Ionian Stream. These modes reflect the variability of the circulation in space and time at seasonal and inter-annual scales. Some modes preferably occur in winter whilst others are characteristic of summer. The mode sequence presents an inter-annual variability in good agreement with observations. The topography of the Sicily Channel sill plays a major role in steering the circulation. In particular the summer upwelling along the southern coast of Sicily, which is present in several modes, could be explained by a large-scale density forcing. A combination of barotropic/baroclinic double Kelvin waves generated on both sides of the sill provides a mechanism for explaining the complexity of the surface circulation advecting the surface waters from the Western Mediterranean toward the Eastern Mediterranean, the most salient features of which are the Atlantic Tunisian Current, the Atlantic Ionian Stream and the Tyrrhenian Sicilian Current which is a new feature highlighted by the present study.

Abstract: While the application of uncertainty propagation methods to hydrometry is still challenging, in situ collaborative interlaboratory experiments are a valuable tool for empirically estimating the uncertainty of stream gauging techniques in given measurement conditions. The authors propose a simple procedure for organizing such experiments and processing the results according to the authoritative ISO standards related to interlaboratory experiments, which are of common practice in many metrological fields. Beyond the computation and interpretation of the results, some issues are discussed regarding the estimation of the stream gauging technique bias in the absence of accurate enough discharge references in rivers; the uncertainty of the uncertainty estimates, according to the number of participants and repeated measurements; the criteria related to error sources that are possibly meaningful for categorizing measurement conditions. The interest and limitations of the in situ collaborative interlaboratory experiments are exemplified by an application to the hydro-acoustic profiler (ADCP) stream gauging technique conducted in 2010 at two different sites downstream of Genissiat hydropower plant in the Rhone river, France. Typically, the expanded uncertainty (with a probability level of 95%) of the average discharge over six successive transects varied from +/- 5% at one site with favorable conditions to +/- 9% at the other site due to unstable flow conditions.

Abstract: Debris flow occurrence is generally forecasted by means of empirical rainfall depth-duration thresholds based on raingauge observations. Rainfall estimation errors related to the sparse nature of raingauge data are enhanced in case of convective rainfall events characterized by limited spatial extent. Such errors have been shown to cause underestimation of the rainfall thresholds and, thus, less efficient forecasts of debris flows occurrence. This work examines the spatial organization of debris flows-triggering rainfall around the debris flow initiation points using high-resolution, carefully corrected radar data for a set of short duration (<30 h) storm events occurred in the eastern Italian Alps. On average, triggering rainfall presents a local peak corresponding to the debris flow initiation point, with rain depth at 5 km (10 km) distance being on average around 70% (40%) of rain depth observed at the debris flow initiation points. The peak is consistently enhanced for events characterized by short durations and causes a systematic underestimation of the rainfall depth-duration thresholds when rainfall is measured away from the debris flow initiation points. We develop an analytical framework that exploits the general characteristics of the spatial rainfall organization to predict the systematic underestimation of the depth-duration thresholds when rainfall is sampled away from the initiation points. Predictions obtained based on this analytical framework are assessed using a Monte Carlo sampling technique. (C) 2015 Elsevier B.V. All rights reserved.

Abstract: Whereas changes in magnitude of geophysical extremes under climate change have received significant attention, potential concomitant changes in spatial dependence structures have remained unexplored so far. Here we provide first evidence of such an effect, highlighting a significant trend in the spatial dependence structure of snowfall extremes in the French Alps at decadal time scale. Specifically, we process a comprehensive data set of winter maximum snowfall from all over the French Alps collected in 90 stations from 1958 to 2012. We estimate extremal dependence over 20year moving estimation windows taking into account possible anisotropy potentially related to orographic effects and/or patterns in atmospheric flows. For each window, we derive a range representing the distance above which extremes are almost independent. We show that snowfall extremes tended to become less spatially dependent over time, with the dependence range reduced roughly by half during the study period. We demonstrate the connection between this trend and local and synoptic climatic variables associated with the current climate change context. In details, the decreasing pattern in extremal dependence is concomitant with a trend toward less harsh winter conditions. It is attributable at first to the increase in temperature and its major control on the snow/rain partitioning. Yet a magnitude effect, with less dependent extremes due to a decrease in intensity of precipitation, also exists. Finally, we show that our results are largely insensitive to the minimal modeling assumptions necessary to our data-based approach. This robustness makes it potentially suitable for various other studies in the field of geophysical extremes.

Abstract: In this study, a regional distributed hydrological model is used to perform long-term and flash-flood event simulations, over the Cevennes-Vivarais region (south of France). The objective is to improve our understanding on the role played by geology on the hydrological processes of catchments during two past flash-flood events. This modelling work is based on Vannier et al. (“Regional estimation of catchment-scale soil properties by means of streamflow recession analysis for use in distributed hydrological models”, Hydrological Processes, 2014), where streamflow recessions are analysed to estimate the thickness and hydraulic conductivity of weathered rock layers, depending on the geological nature of catchments. Weathered rock layers are thus implemented into the hydrological model CVN-p, and the contribution of these layers is assessed during flash-flood events simulations as well as during inter event periods. The model is used without any calibration, to test hypotheses on the active hydrological processes. The results point out two different hydrological behaviours, depending on the geology: on crystalline rocks (granite and gneiss), the addition of a weathered rock layer considerably improves the simulated discharges, during flash-flood events as well as during recession periods, and makes the model able to remarkably reproduce the observed streamflow dynamics. For other geologies (schists especially), the benefits are real, but not sufficient to properly simulate the observed streamflow dynamics. These results probably underline the existence of poorly known processes (flow paths, non-linear spilling process) associated with the planar structure of schisty rocks. On a methodological point of view, this study proposes a simple way to account for the additional storage associated with each geological entity, through the addition of a weathered porous rock layer situated below the traditionally considered upper soil horizons, and shows its applicability and benefits for the simulation of flash flood events at the regional scale. (C) 2016 Elsevier B.V. All rights reserved.

Abstract: Flash-floods are among the most devastating hazards in the Mediterranean. A major subset of damage and casualties caused by flooding is related to road submersion. Distributed hydrological nowcasting can be used for road flooding monitoring. This requires rainfall-runoff simulations at a high space and time resolution. Distributed hydrological models, such as the ISBA-TOP coupled system used in this study, are designed to simulate discharges for any cross-section of a river but they are generally calibrated for certain outlets and give deteriorated results for the sub-catchment outlets. The paper first analyses ISBA-TOP discharge simulations in the French Mediterranean region for target points different from the outlets used for calibration. The sensitivity of the model to its governing factors is examined to highlight the validity of results obtained for ungauged river sections compared with those obtained for the main gauged outlets. The use of improved model inputs is found beneficial for sub-catchments simulation. The calibration procedure however provides the parameters' values for the main outlets only and these choices influence the simulations for ungauged catchments or sub-catchments. As a result, a new version of ISBA-TOP system without any parameter to calibrate is used to produce diagnostics relevant for quantifying the risk of road submersion. A first diagnostic is the simulated runoff spatial distribution, it provides a useful information about areas with a high risk of submersion. Then an indicator of the flood severity is given by simulated discharges presented with respect to return periods. The latter has to be used together with information about the vulnerability of road-river cross-sections. (C) 2016 Elsevier B.V. All rights reserved.

Abstract: The long-term response of the flood activity to both Atlantic and Mediterranean climatic influences was explored by studying a lake sequence (Lake Foreant) of the Western European Alps. High-resolution sedimentological and geochemical analysis revealed 171 event layers, 168 of which result from past flood events over the last millennium. The layer thickness was used as a proxy of intensity of past floods. Because the Foreant palaeoflood record is in agreement with the documented variability of historical floods resulting from local and mesoscale, summer-to-autumn convective events, it is assumed to highlight changes in flood frequency and intensity related to such events typical of both Atlantic (local events) and Mediterranean (mesoscale events) climatic influences. Comparing the Foreant record with other Atlantic-influenced and Mediterranean-influenced regional flood records highlights a common feature in all flood patterns that is a higher flood frequency during the cold period of the Little Ice Age (LIA, AD 1300-1900). In contrast, high-intensity flood events are apparent during both the cold LIA and the warm Medieval Climate Anomaly (MCA, AD 9501250). However, there is a tendency towards higher frequencies of high-intensity flood events during the warm MCA. The MCA extremes could mean that under the global warming scenario, we might see an increase in intensity (not in frequency). However, the flood frequency and intensity in the course of the 20th century warming trend did not change significantly. Uncertainties in future evolution of flood intensity lie in the interpretation of the lack of 20th century extremes (transition or stable?) and the different climate forcing factors between the two periods (greenhouse gases vs. solar and/or volcanic eruptions).

Abstract: Simulation methods for design flood analyses require estimates of extreme precipitation for simulating maximum discharges. This article evaluates the multi-exponential weather pattern (MEWP) model, a compound model based on weather pattern classification, seasonal splitting and exponential distributions, for its suitability for use in Norway. The MEWP model is the probabilistic rainfall model used in the SCHADEX method for extreme flood estimation. Regional scores of evaluation are used in a split sample framework to compare the MEWP distribution with more general heavy-tailed distributions, in this case the Multi Generalized Pareto Weather Pattern (MGPWP) distribution. The analysis shows the clear benefit obtained from seasonal and weather pattern-based subsampling for extreme value estimation. The MEWP distribution is found to have an overall better performance as compared with the MGPWP, which tends to overfit the data and lacks robustness. Finally, we take advantage of the split sample framework to present evidence for an increase in extreme rainfall in the southwestern part of Norway during the period 1979-2009, relative to 1948-1978.