Publications

Abstract: The Great Whirl (Gw) Is A Quasi-Permanent Anticyclonic Eddy That Appears Every Summer Monsoon Offshore Of The Somalia Upwelling. The Annual Cycle Of The Gw Is Well Described, But Deviations From Its Mean Seasonal Cycle (Hereafter Non-Seasonal Variability) Have Been Less Explored. Satellite Observations Reveal That The Leading Mode Of Summer Non-Seasonal Sea-Level Variability In This Region Is Associated With Similar To 100-Km Northward Or Southward Gw Shifts From Its Climatological Position. Northward Shifts Are Associated With A Stronger Gw, And Two Cold, Productive Coastal Upwelling Wedges At 5 Degrees N And 10 Degrees N. Southward Shifts Are Associated With A Weaker Gw, No Wedge At 5 Degrees N And A Single Stronger-Than-Usual Cold And Productive Wedge At 10 Degrees N. An Eddy-Permitting (25-Km Resolution) 50-Member Ensemble Ocean Simulation Reproduces This Gw Variability Well. It Indicates That The Non-Seasonal Gw Variability Has A Short Similar To 20 Days Timescale Intrinsic Component, Associated With The Gw Interaction With Mesoscale Eddies, And A Lower-Frequency, Similar To 100 Days Externally Forced Component. Intrinsic Variability Dominates At Both Subseasonal (Two Thirds Of The Variance) And Interannual Timescales (57% Of The Variance). The Externally Forced Signal Results From Shifts In The Probability Distribution Of The Subseasonal Gw Position (E.G., More Likely Northward Than Southward Shifted Instantaneous Gw Positions Over A Season). The Mechanism For This External Forcing Is Not Entirely Clear, But It Appears To Be Related To The Rossby Wave Response To Offshore Wind Stress Curl Forcing, Which Evolves Into A North-South Dipole That Projects Onto The Gw Variability Pattern. The Great Whirl (Gw) Is A Similar To 500-Km Diameter Oceanic Eddy That Forms Each Summer Off The Somalia Coast. The Gw Influences The Temperature And Biological Productivity Of The Somalia Coastal Upwelling. The Gw Seasonal Cycle, Including Its Northward Movement At The End Of The Monsoon, Is Known. Here, We Study Deviations From This Mean Seasonal Cycle. The Gw Exhibits Fast (Typically 20 Days Long), Similar To 100-Km Northward Or Southward Displacements. These Displacements Result From Interactions With Smaller Neighboring Oceanic Eddies, And Are Hence The Consequence Of An Intrinsic Ocean Dynamics, Rather Than Atmospheric Forcing. The Gw Is More Pronounced When Displaced Northward, And The Somalia Coastal Upwelling Has Two Clear “Wedges” Of Cold, Plankton-Rich Water At 5 Degrees And 10 Degrees N. When Displaced Southward, The Gw Is Less Pronounced, And There Is A Single, Stronger-Than-Usual Wedge Of Cold Water At 10 Degrees N. We Also Show That Atmospheric Forcing Can Induce Seasonal Gw Displacements, By Making, For Example, Northward Events More Likely Than The Southward. Thus, The Seasonal Mean Gw Position Has Both A Predictable (Due To Atmospheric Forcing) And Slightly Larger Unpredictable (Due To Interactions With Eddies) Component. We Propose That The Atmospheric Forcing Influences The Fast Oscillations Of The Gw Through Slow Oceanic Adjustment To Wind Variations Further East. The Great Whirl (Gw) Non-Seasonal Variability Is Dominated By Similar To 100-Km Northward Or Southward Shifts Relative To Its Climatological Position Those Shifts Induce Sea Level, Surface Temperature And Chlorophyll Signals Those Gw Displacements Have A Fast (Similar To 20 Days) Intrinsic Variability Component And A Slower, Seasonal Forced Component

Abstract: This Study Evaluates The Impact Of Increasing Resolution On Arctic Ocean Simulations Using Five Pairs Of Matched Low- And High-Resolution Models Within The Omip-2 (Ocean Model Intercomparison Project Phase 2) Framework. The Primary Objective Is To Assess Whether A Higher Resolution Can Mitigate Typical Biases In Low-Resolution Models And Improve The Representation Of Key Climate-Relevant Variables. We Reveal That Increasing The Horizontal Resolution Contributes To A Reduction In Biases In Mean Temperature And Salinity And Improves The Simulation Of The Atlantic Water Layer And Its Decadal Warming Events. A Higher Resolution Also Leads To Better Agreement With Observed Surface Mixed-Layer Depth, Cold Halocline Base Depth And Arctic Gateway Transports In The Fram And Davis Straits. However, The Simulation Of The Mean State And Temporal Changes In Arctic Freshwater Content Does Not Show Improvement With Increased Resolution. Not All Models Achieve Improvements For All Analyzed Ocean Variables When Spatial Resolution Is Increased So It Is Crucial To Recognize That Model Numerics And Parameterizations Also Play An Important Role In Faithful Simulations. Overall, A Higher Resolution Shows Promise In Improving The Simulation Of Key Arctic Ocean Features And Processes, But Efforts In Model Development Are Required To Achieve More Accurate Representations Across All Climate-Relevant Variables.

Abstract: Melt Rates At The Base Of Antarctic Ice Shelves Are Needed To Drive Projections Of The Antarctic Ice Sheet Mass Loss. Current Basal Melt Parameterizations Struggle To Link Open Ocean Properties To Ice-Shelf Basal Melt Rates For The Range Of Current Sub-Shelf Cavity Geometries Around Antarctica. We Present A Proof Of Concept Exploring The Potential Of Simple Deep Learning Techniques To Parameterize Basal Melt. We Train A Simple Feedforward Neural Network, Or Multilayer Perceptron, Acting On Each Grid Cell Separately, To Emulate The Behavior Of Circum-Antarctic Cavity-Resolving Ocean Simulations. We Find That This Kind Of Emulator Produces Reasonable Basal Melt Rates For Our Training Ensemble, At Least As Close As Or Closer To The Reference Than Traditional Parameterizations. On An Independent Ensemble Of Simulations That Was Produced With The Same Ocean Model But With Different Model Parameters, Cavity Geometries And Forcing, The Neural Network Yields Similar Results To Traditional Parameterizations On Present Conditions. In Much Warmer Conditions, Both Traditional Parameterizations And Neural Network Struggle, But The Neural Network Tends To Produce Basal Melt Rates Closer To The Reference Than A Majority Of Traditional Parameterizations. While This Shows That Such A Neural Network Is At Least As Suitable For Century-Scale Antarctic Ice-Sheet Projections As Traditional Parameterizations, It Also Highlights That Tuning Any Parameterization On Present-Like Conditions Can Introduce Biases And Should Be Used With Care. Nevertheless, This Proof Of Concept Is Promising And Provides A Basis For Further Development Of A Deep Learning Basal Melt Parameterization. A Warmer Ocean Around Antarctica Leads To Higher Melting Of The Floating Ice Shelves, Which Influence The Ice Loss From The Antarctic Ice Sheet And Therefore Sea-Level Rise. In Computer Simulations Of The Ocean, These Ice Shelves Are Often Not Represented. For Simulations Of The Ice Sheet, So-Called Parameterizations Are Used To Link The Oceanic Properties In Front Of The Shelf And The Melt At Their Base. We Show That This Link Can Be Emulated With A Simple Neural Network, Which Performs At Least As Well As Traditional Physical Parameterizations Both For Present And Much Warmer Conditions. This Study Also Proposes Several Potential Ways Of Further Improving The Use Of Deep Learning To Parameterize Basal Melt. We Show That Simple Neural Networks Produce Reasonable Basal Melt Rates By Emulating Circum-Antarctic Cavity-Resolving Ocean Simulationspredicted Melt Rates For Present And Warmer Conditions Are Similar Or Closer To The Reference Simulation Than Traditional Parameterizationswe Show That Neural Networks Are Suited To Be Used As Basal Melt Parameterizations For Century-Scale Ice-Sheet Projections

Abstract: Parameterization Of Mesoscale Eddies In Coarse Resolution Ocean Models Is Necessary To Include The Effect Of Eddies On The Large-Scale Oceanic Circulation. We Propose To Use A Multiple-Scale Quasi-Geostrophic (Msqg) Model To Capture The Eddy Dynamics That Develop In Response To A Prescribed Large-Scale Flow. The Msqg Model Consists In Extending The Traditional Quasi Geostrophic (Qg) Dynamics To Include The Effects Of A Variable Coriolis Parameter And Variable Background Stratification. Solutions To This Msqg Equation Are Computed Numerically And Compared To A Full Primitive Equation Model. The Large-Scale Flow Field Permits Baroclinically Unstable Qg Waves To Grow. These Instabilities Saturate Due To Non-Linearities And A Filtering Method Is Applied To Remove Large-Scale Structures That Develop Due To The Upscale Cascade. The Resulting Eddy Field Represents A Dynamically Consistent Response To The Prescribed Background Flow, And Can Be Used To Rectify The Large-Scale Dynamics. Comparisons Between Gent-Mcwilliams Eddy Parameterization And The Present Solutions Show Large Regions Of Agreement, While Also Indicating Areas Where The Eddies Feed Back Onto The Large Scale In A Manner That The Gent-Mcwilliams Parameterization Cannot Capture. Also Of Interest Is The Time Variability Of The Eddy Feedback Which Can Be Used To Build Stochastic Eddy Parameterizations.

Abstract: A Theory For Flow Over Gentle Hills Using A Mixing-Length Turbulence Closure Is Developed To Describe The Transition From Turbulent Orographic Form Drag To Gravity Wave Drag. It Confirms That The First Is Associated With Downstream Sheltering, And The Second With Upstream Blocking And Strong Downslope Winds. It Shows That The Altitude At Which The Incident Flow Needs To Be Taken To Calculate The Drag Is The Inner Layer Scale At Which Dissipation Equilibrates Disturbance Advection. It Also Shows That The Parameter That Controls The Transition, Here A Richardson Number, Compares The Mountain Length With The Altitude Of The Turning Points Above Which The Upward-Propagating Gravity Waves Become Evanescent. Our Solutions Are Also Used To Show That The Downslope Winds Penetrate Well Into The Inner Layer And That A Good Fraction Of The Drag Is Deposited In The Inner Layer: All Of It In The Neutral Case, A Large Fraction In The Intermediate Cases When There Are Trapped Lee Waves, And Even In Stable Situations Without Trapping Part Of The Gravity Wave Drag Is Eroded In The Inner Layer. Some Discussion On How To Combine Neutral And Stratified Effects In The Parametrization Of Subgrid Scale Orography In Large-Scale Models Is Given. A Theory For The Interaction Between A Boundary Layer And A Low Mountain Is Derived. The Incident Wind Considered (U0$$ {U}_0 $$, Left Panel) Presents A Logarithmic Profile Near The Surface. The Theory Describes The Transition From Neutral To Stratified Flows, And The Systems Of Mountain Waves (Upward Propagating And Trapped, See Right Panel) That Develop During The Transition. The Theory Also Reproduces The Transition From Downstream Sheltering To Downslope Winds (Zoom) As Stratification Increases. The Mountain Drag And Reynolds Stress Profiles Are Also Discussed.Image

Abstract: The Don River Is Among The Largest Rivers In The Eastern Europe And Is Heavily Polluted. This River Inflows Into Small And Semi-Isolated Sea Of Azov, Which Is Connected With The Black Sea By A Narrow Strait. Generally, The Sea Of Azov Is A Large Choked Lagoon, Which Serves As A Barrier For River-Borne Constituents. Using Numerical Modeling, We Reveal That Presence Of The Choked Lagoon Significantly Slows Down The Estuary-Seawater Flux Of Dissolved Pollutants And Slackens Its Discharge-Induced Seasonal Variability. In Particular, The Sea Of Azov Delays The 5 % And 95 % Of The Total Flux Of Riverine Pollution To The Black Sea By 9 And 36 Months, Respectively. The Obtained Results Are Important For Assessment The Influence Of Background And Emergency Pollution Accidents At The Don River On Water Quality In The Study Region. Moreover, These Results Could Be Applied To Many Other Chocked Lagoons In The World Ocean.

Abstract: The Ocean Mixed Layer Is The Interface Between The Ocean Interior And The Atmosphere Or Sea Ice And Plays A Key Role In Climate Variability. It Is Thus Critical That Numerical Models Used In Climate Studies Are Capable Of A Good Representation Of The Mixed Layer, Especially Its Depth. Here We Evaluate The Mixed-Layer Depth (Mld) In Six Pairs Of Non Eddying (1 Degrees Grid Spacing) And Eddy-Rich (Up To 1/16 Degrees) Models From The Ocean Model Intercomparison Project (Omip), Forced By A Common Atmospheric State. For Model Evaluation, We Use An Updated Mld Dataset Computed From Observations Using The Omip Protocol (A Constant Density Threshold). In Winter, Low-Resolution Models Exhibit Large Biases In The Deep-Water Formation Regions. These Biases Are Reduced In Eddy-Rich Models But Not Uniformly Across Models And Regions. The Improvement Is Most Noticeable In The Mode Water Formation Regions Of The Northern Hemisphere. Results In The Southern Ocean Are More Contrasted, With Biases Of Either Sign Remaining At High Resolution. In Eddy-Rich Models, Mesoscale Eddies Control The Spatial Variability In Mld In Winter. Contrary To A Hypothesis That The Deepening Of The Mixed Layer In Anticyclones Would Make The Mld Larger Globally, Eddy-Rich Models Tend To Have A Shallower Mixed Layer At Most Latitudes Than Coarser Models Do. In Addition, Our Study Highlights The Sensitivity Of The Mld Computation To The Choice Of A Reference Level And The Spatio-Temporal Sampling, Which Motivates New Recommendations For Mld Computation In Future Model Intercomparison Projects.

Abstract: Intrinsic Processes Such As Mesoscale Turbulence Have Recently Been Proved As Important As Atmospheric Variability In Causing Variations In Ocean Bottom Pressure (P(B)). Intrinsic Processes Are Also Known To Generate Random Variability On Scales Larger Than The Mesoscale Through Inverse Energy Cascades Or Large-Scale Baroclinic Instability. Here, Model Analyses Reveal A Truly Global-Scale, Intrinsic P(B) Mode Of Variability At Monthly Time Scales That Relies On A Different Mechanism. The Intrinsic Mode Has Largest Amplitudes Around Drake Passage And Opposite Polarity Between The Southern Ocean And Atlantic/Arctic Oceans. Its Signature Is Consistent With Localized Eddy-Driven P(B) Anomalies Of Opposite Sign Near Drake Passage That Then Adjust Freely In The Rest Of The Ocean Via Barotropic Wave Processes. This Intrinsic Mode Seems Consistent With Observed P(B) Variability.

Abstract: We Describe A Form Of Atlantic Meridional Overturning Circulation (Amoc) Variability That We Believe Has Not Previously Appeared In Observations Or Models. It Is Found In An Ensemble Of Eddy-Resolving North Atlantic Simulations That The Amoc Frequently Reverses In Sign At Similar To 35 Degrees N With Gyre-Wide Anomalies In Size And That Reach Throughout The Water Column. The Duration Of Each Reversal Is Roughly 1 Month. The Reversals Are Part Of The Annual Amoc Cycle Occurring In Boreal Winter, Although Not All Years Feature An Actual Reversal In Sign. The Occurrence Of The Reversals Appears In Our Ensemble Mean, Suggesting It Is A Forced Feature Of The Circulation. A Partial Explanation Is Found In An Ekman Response To Wind Stress Anomalies. Model Ensemble Simulations Run With Different Combinations Of Climatological And Realistic Forcings Argue That It Is The Atmospheric Forcing Specifically That Results In The Reversals, Despite The Signals Extending Into The Deep Ocean.

Abstract: The ocean is suggested to play a major role in the ongoing winter decay of the sea ice cover in the western Eurasian Basin. Using a high-resolution sea ice-ocean model, we investigate the processes influencing the ice-ocean interactions in winter in the waters north of Svalbard, with a particular focus on those contributing to sea ice melt events of large amplitude. These short term events, lasting 5-10 days, are associated with locally large melt rates mostly found along the pathway of the Atlantic Water. The sum of all these events over the simulation period is found to contribute 40% of the total winter melt. Episodes of strong surface winds, occasionally associated with enhanced velocity shear at the mixed layer base, can trigger enhanced entrainment of Atlantic Water through the relatively shallow upper thermocline in the Atlantic Water boundary current, leading to substantial ocean heat transfer to the sea ice. In some cases, strengthening of the boundary current also contributes to fueling the heat transfer to the ice. Another type of large melt event, not linked to increased ocean vertical heat flux but due to ice being advected over warm surface waters, is also identified, sometimes associated with episodes of ice close-up. Sea ice budget calculations show that, overall, large melt events contribute significantly to the eastward retreat of the winter marginal ice zone on the upper slope east of Svalbard while episodes of northward advection of ice largely dominate the ice edge retreat over the shelf north of Svalbard.

Abstract: Circulation in the Southern Ocean is unique. The strong wind stress forcing and buoyancy fluxes, in concert with the lack of continental boundaries, conspire to drive the Antarctic Circumpolar Current replete with an intense eddy field. The effect of Southern Ocean eddies on the ocean circulation is significant-they modulate the momentum balance of the zonal flow, and the meridional transport of tracers and mass. The strength of the eddy field is controlled by a combination of forcing (primarily thought to be wind stress) and intrinsic, chaotic, variability associated with the turbulent flow field itself. Here, we present results from an eddy-permitting ensemble of ocean model simulations to investigate the relative contribution of forced and intrinsic processes in governing the variability of Southern Ocean eddy kinetic energy. We find that variations of the eddy field are mostly random, even on longer (interannual) timescales. Where correlations between the wind stress forcing and the eddy field exist, these interactions are dominated by two distinct timescales-a fast baroclinic instability response; and a multi-year process owing to feedback between bathymetry and the mean flow. These results suggest that understanding Southern Ocean eddy dynamics and its larger-scale impacts requires an ensemble approach to eliminate intrinsic variability, and therefore may not yield robust conclusions from observations alone.

Abstract: Antarctic Ice Sheet Projections Show The Highest Sensitivity To Increased Basal Melting In The Amundsen Sea. However, Little Is Known About The Processes That Control Future Increase In Melt Rates. We Build An Ensemble Of Three Ocean-Sea-Ice-Ice-Shelf Simulations For Both The Recent Decades And The Late 21St Century, Constrained By Regional Atmosphere Simulations And The Multi-Model Mean Climate Change Of The Fifth Climate Model Intercomparison Project Under The Rcp8.5 Scenario. The Ice-Shelf Melt Rates Are Typically Multiplied By 1.4-2.2 From Present Day To Future, For A Total Basal Mass Loss Increased By 346 Gt Yr(-1) On Average. This Is Equally Explained By Advection Of Warmer Water From Remote Locations And Regional Changes In Ekman Downwelling And In The Ice-Shelf Melt-Induced Circulation, While Increased Iceberg Melt Plays No Significant Role. Our Simulations Suggest That High-End Melt Projections Previously Used To Constrain Recent Sea Level Projections May Have Been Significantly Overestimated.

Abstract: We Investigate The Predictability Properties Of The Ocean Dynamics Using An Ensemble Of Short-Term Numerical Regional Ocean Simulations Forced By Prescribed Atmospheric Conditions. In That Purpose, We Developed A Kilometric-Scale, Regional Model For The Western Mediterranean Sea (Med-West60, At 1/60 Degrees Horizontal Resolution). A Probabilistic Approach Is Then Followed, Where A Stochastic Parameterization Of Model Uncertainties Is Introduced In This Setup To Initialize Ensemble Predictability Experiments. A Set Of Three Ensemble Experiments (20 Members And 2 Months) Are Performed, One With The Deterministic Model Initiated With Perturbed Initial Conditions And Two With The Stochastic Model, For Two Different Amplitudes Of Stochastic Model Perturbations. In All Three Experiments, The Spread Of The Ensemble Is Shown To Emerge From The Smallest Scales (Kilometric Scale) And Progressively Upscales To The Largest Structures. After 2 Months, The Ensemble Variance Saturates Over Most Of The Spectrum, And The Small Scales (< 100 Km) Have Become Fully Decorrelated Across The Ensemble Members. These Ensemble Simulations Can Provide A Statistical Description Of The Dependence Between Initial Accuracy And Forecast Accuracy For Time Lags Between 1 And 20 D. The Predictability Properties Are Assessed Using A Cross-Validation Algorithm (I.E., Using Alternatively Each Ensemble Member As The Reference Truth And The Remaining 19 Members As The Ensemble Forecast) Together With A Given Statistical Score To Characterize The Initial And Forecast Accuracy. From The Joint Distribution Of Initial And Final Scores, It Is Then Possible To Quantify The Probability Distribution Of The Forecast Score Given The Initial Score Or Reciprocally To Derive Conditions On The Initial Accuracy To Obtain A Target Forecast Accuracy. The Misfit Between Ensemble Members Is Quantified In Terms Of Overall Accuracy (Crps Score), Geographical Position Of The Ocean Structures (Location Score) And Spatial Spectral Decorrelation Of The Sea Surface Height 2-D Fields (Decorrelation Score). With This Approach, We Estimate For Example That, In The Region And Period Of Interest, The Initial Location Accuracy Required (Necessary Condition) With A Perfect Model (No Model Uncertainty) To Obtain A Location Accuracy Of The Forecast Of 10 Km With A 95 % Confidence Is About 8 Km For A 1 D Forecast, 4 Km Fora 5 D Forecast And 1.5 Km Fora 10 D Forecast, And This Requirement Cannot Be Met With A 15 D Or Longer Forecast.

Abstract: The global ocean is warming and has absorbed 90% of the Earth Energy Imbalance over 2010-2018 leading to global mean sea level rise. Both ocean heat content (OHC) and sea level trends show large regional deviations from their global means. Both quantities have been estimated from in-situ observations for years. However, in-situ profile coverage is spatially uneven, leading to uncertainties when assessing both OHC and sea level trends, especially at regional scale. Recently, a new possible driver of regional sea level and OHC trends has been highlighted using eddy-permitting ensemble ocean simulations over multiple decades: non-linear ocean processes produce chaotic fluctuations, which yield random contributions to regional decadal OHC and sea level trends. In-situ measurements capture a combination of the atmospherically-forced response and this intrinsic ocean variability. It is therefore important to understand the imprint of the chaotic ocean variability recorded by the in-situ measurement sampling in order to assess its impact and associated uncertainty on regional budgets. A possible approach to investigate this problem is to use a set of synthetic in-situ-like profiles extracted from an ensemble of forced ocean simulations started from different states and integrated with the same atmospheric forcing. Comparisons between the original ensemble outputs and the remapped, subsampled, in-situ-like profiles elucidate the contribution of chaotic ocean variability to OHC and regional sea level trends. Our results show that intrinsic variability may be large in eddy-active regions in the gridded model outputs, and remains substantial when using the in-situ sampling-based estimates. Using the latter, the same result is also found on large scales, for which atmospheric forcing has been identified as the main driver. Our results suggest accounting for this intrinsic ocean variability when assessing regional OHC and sea level trend budgets on decadal time scales.

Abstract: Y AltiKa, first ever high frequency Ka-band altimeter on board SARAL (Satellite with ARgos and ALtiKa) has gone through different phases of operations, viz. Exact Repeat Mission, (ERM, March 2013 – July 2016), Drifting phase, (DP, July 2016 – January 2018) and then to Mispointing phase, (MP, February 2018 – till date). A detailed assessment of Sea level anomaly (SLA), Significant Wave Height (SWH) and Ocean Surface Wind Speed (WS) has been carried out during these different phases with a focus on the North Indian Ocean. Crossover analysis using the Jason series of satellites available during various phases of SARAL suggest high quality of SARAL/AltiKa data during the ERM and DP with root mean square differences of the order of 0.080 m, 0.25 m and 1 m/s for SLA, SWH and WS respectively. These differences are more during MP, being 0.095 m, 0.45 m and 1.72 m/s for SLA, SWH and WS respectively. Wavenumber Power spectrum computed from the along-track AltiKa SLA reveals that slopes in the mesoscale band (70-250 km) in different phases of operations are not very different. Errors in gridded SARAL/AltiKa SLA with respect to standard AVISO product remains unchanged during DP, but degrade by nearly 9.3% in the MP as compared to ERM. To assess the effect of assimilating along track SWH and SLA from different phases, two set of wave and circulation model simulations, with and without SARAL AltiKa data assimilation, were performed. Assimilation of SWH improved the wave height simulation by similar to 12.8% during the DP and similar to 8% during ERM and MP. As regards to circulation modeling, no significant difference of assimilating SLA from different phases was observed in the mesoscale range. These results indicate the usefulness of SLA from SARAL AltiKa during DP and MP for studying the mesoscale dynamics. (C) 2021 COSPAR. Published by Elsevier B.V. All rights reserved.

Abstract: Wind Waves Play An Important Role In The Climate System, Modulating The Energy Exchange Between The Ocean And The Atmosphere And Effecting Ocean Mixing. However, Existing Ship-Based Observational Networks Of Wind Waves Are Still Sparse, Limiting Therefore The Possibilities Of Validating Satellite Missions And Model Simulations. In This Paper We Present Data Collected On Three Research Cruises In The North Atlantic And Arctic In 2020 And 2021 And The Seavision System For Measuring Wind Wave Characteristics Over The Open Ocean With A Standard Marine Navigation X-Band Radar. Simultaneously With The Seavision Wind Wave Characteristic Measurements, We Also Collected Data From The Spotter Wave Buoy At The Same Locations, And We Ran The Wavewatch Iii Model In A Very High-Resolution Configuration Over The Observational Domain Seavision Measurements Were Validated Against Co-Located Spotter Wave Buoy Data And Intercompared With The Output Of Wavewatch Iii Simulations. Observations Of The Wind Waves With The Navigation X-Band Radar Were Found To Be In Good Agreement With Buoy Data And Model Simulations With The Best Match For The Wave Propagation Directions. Supporting Datasets Consist Of Significant Wave Heights, Wave Directions, Wave Periods And Wave Energy Frequency Spectra Derived From Both Seavision And The Spotter Buoy. All Supporting Data Are Available Through The Pangaea Repository – Https://Doi.Org/10.1594/Pangaea.939620 (Gavrikov Et Al., 2021). The Dataset Can Be Further Used For Validation Of Satellite Missions And Regional Wave Model Experiments. Our Study Shows The Potential Of Ship Navigation X-Band Radars (When Assembled With Seavision Or Similar Systems) For The Development Of A New Near-Global Observational Network Providing A Much Larger Number Of Wind Wave Observations Compared To E.G. Voluntary Observing Ship (Vos) Data And Research Vessel Campaigns.

Abstract: The thickness-weighted average (TWA) framework, which treats the residual-mean flow as the prognostic variable, provides a clear theoretical formulation of the eddy feedback onto the residual-mean flow. The averaging operator involved in the TWA framework, although in theory being an ensemble mean, in practice has often been approximated by a temporal mean. Here, we analyze an ensemble of North Atlantic simulations at mesoscale-permitting resolution (1/12 degrees). We therefore recognize means and eddies in terms of ensemble means and fluctuations about those means. The ensemble dimension being orthogonal to the temporal and spatial dimensions negates the necessity for an arbitrary temporal or spatial scale in defining the eddies. Eddy-mean flow feedbacks are encapsulated in the Eliassen-Palm (E-P) flux tensor and its convergence indicates that eddy momentum fluxes dominate in the separated Gulf Stream. The eddies can be interpreted to contribute to the zonal meandering of the Gulf Stream and a northward migration of it in the meridional direction. Downstream of the separated Gulf Stream in the North Atlantic Current region, the interfacial form stress convergence becomes leading order in the E-P flux convergence.

Abstract: The “eddying” ocean, recognized for several decades, has been the focus of much observational and theoretical research. We here describe a generalization for the analysis of eddy energy, based on the use of ensembles, that addresses two key related issues: the definition of an “eddy” and the general computation of energy spectra. An ensemble identifies eddies as the unpredictable component of the flow, and permits the scale decomposition of their energy in inhomogeneous and non-stationary settings. We present two distinct, but equally valid, spectral estimates: one is similar to classical Fourier spectra, the other reminiscent of classical empirical orthogonal function analysis. Both satisfy Parseval's equality and thus can be interpreted as length-scale dependent energy decompositions. The issue of “tapering” or “windowing” of the data, used in traditional approaches, is also discussed. We apply the analyses to a mesoscale “resolving” (1/12 degrees) ensemble of the separated North Atlantic Gulf Stream. Our results reveal highly anisotropic spectra in the Gulf Stream and zones of both agreement and disagreement with theoretically expected spectral shapes. In general, we find spectral slopes that fall off faster than the steepest slope expected from quasi-geostrophic theory.

Abstract: Satellite altimetry data have revealed a global mean sea level rise of 3.1 mm/yr since 1993 with large regional sea level variability. These remote data highlight complex structures especially in strongly eddying regions. A recent study showed that over 38% of the global ocean area, the chaotic variability may hinder the attribution to the atmospheric forcing of regional sea level trends from 1993 to 2015. This study aims to complement this work by focusing on the atmospherically forced and chaotic interannual variability of regional sea level and its components. At interannual time scales, variability can hamper the detection of regional sea level trends. A global 1/4 degrees ocean/sea-ice 50-member ensemble simulation is analyzed to disentangle the imprints of the atmospheric forcing and of the chaotic ocean variability on the interannual variability of regional sea level and of its steric and manometric components over 1993-2015. The atmospherically forced and chaotic interannual variabilities of sea level mainly have a steric origin, except in coastal areas. The chaotic part of the interannual variability of sea level and its components is stronger in the Pacific and Atlantic Oceans than in the Indian Ocean. The chaotic part of the interannual variance of sea level and of its steric component exceeds 20% over 48% of the global ocean area; this fractional area reduces to 26% for the manometric component. These results confirm the substantial imprint of the chaotic interannual variability on sea level components, questioning in several regions the attribution of their observed evolution to atmospheric causes. Plain Language Summary Since the early 1990s, satellite altimetry has become the main observing system for continuously measuring the sea level variations with a near global coverage. It has revealed a global mean sea level rise of 3.1 mm/yr since 1993 with large regional sea level variability that differs from the mean estimate. These measurements highlight complex structures especially for the western boundary currents (Gulf Stream or Kuroshio) or the Antarctic Circumpolar Current. Recent studies based on numerical modeling showed that the ocean spontaneously generates a chaotic intrinsic variability that substantially impacts the sea level interannual-to-decadal variability and its long-term trends. It is important to note that sea level observations simultaneously record these chaotic variations in the ocean but also the response to the atmospheric forcings. Here, we use a 50-member ensemble ocean simulation to disentangle the atmospherically forced and chaotic parts of the interannual variability of sea level and of its steric and manometric components. We found that, in several regions, the chaotic interannual variability has a large imprint on sea level components. While these results do not question the anthropic origin of global mean sea level rise, they give new insights into the oceanic vs. nonoceanic origin of regional interannual variability.

Abstract: The southwestern Pacific Ocean sits at a bifurcation where southern subtropical waters are redistributed equatorward and poleward by different ocean currents. The processes governing the interannual variability of these currents are not completely understood. This issue is investigated using a probabilistic modeling strategy that allows disentangling the atmospherically forced deterministic ocean variability and the chaotic intrinsic ocean variability. A large ensemble of 50 simulations performed with the same ocean general circulation model (OGCM) driven by the same realistic atmospheric forcing and only differing by a small initial perturbation is analyzed over 1980-2015. Our results show that, in the southwestern Pacific, the interannual variability of the transports is strongly dominated by chaotic ocean variability south of 20 degrees S. In the tropics, while the interannual variability of transports and eddy kinetic energy modulation are largely deterministic and explained by the El Nino-Southern Oscillation (ENSO), ocean nonlinear processes still explain 10% to 20% of their interannual variance at large scale. Regions of strong chaotic variance generally coincide with regions of high mesoscale activity, suggesting that a spontaneous inverse cascade is at work from the mesoscale toward lower frequencies and larger scales. The spatiotemporal features of the low-frequency oceanic chaotic variability are complex but spatially coherent within certain regions. In the Subtropical Countercurrent area, they appear as interannually varying, zonally elongated alternating current structures, while in the EAC (East Australian Current) region, they are eddy-shaped. Given this strong imprint of large-scale chaotic oceanic fluctuations, our results question the attribution of interannual variability to the atmospheric forcing in the region from pointwise observations and one-member simulations.

Abstract: The flow of energy in the wind-driven circulation is examined in a combined theoretical and numerical study. Based on a multiple-scale analysis, we find the mesoscale field in the ocean interior is strongly affected by, but does not feed back onto, the ventilated thermocline. In the western boundary region, the associated currents first appear as coastal jets, conserving mean energy, and later as separated jet extensions where the mesoscale is energized by the mean field. It is in the separated jet zone where the primary loss of general circulation energy to the mesoscale occurs. These ideas are tested by an analysis of a regional 1/12 degrees primitive equation numerical model of the North Atlantic. The predictions of the theory are generally supported by the numerical results. The one exception is that topographic irregularities in the coastal jet spawn eddies, although these eddies contribute modestly to the energy budget. We therefore conclude the primary sink of wind input into the mean circulation is in the separated jet, and not the interior. The analysis also shows wind energy input to be much smaller than the interior energy fluxes; thus, the general circulation largely recirculates energy.

Abstract: The quasigeostrophic and the generalized omega equations are the most widely used methods to reconstruct vertical velocity w from in situ data. As observational networks with much higher spatial and temporal resolutions are being designed, the question arises of identifying the approximations and scales at which an accurate estimation of w through the omega equation can be achieved and what critical scales and observables are needed. In this paper we test different adiabatic omega reconstructions of w over several regions representative of main oceanic regimes of the global ocean in a fully eddy-resolving numerical simulation with a 1/60 degrees horizontal resolution. We find that the best reconstructions are observed in conditions characterized by energetic turbulence and/or weak stratification where near-surface frontal processes are felt deep into the ocean interior. The quasigeostrophic omega equation gives satisfactory results for scales larger than similar to 10 km horizontally while the improvements using a generalized formulation are substantial only in conditions where frontal turbulent processes are important (providing improvements with satisfactory reconstruction skill down to similar to 5 km in scale). The main sources of uncertainties that could be identified are related to processes responsible for ocean thermal wind imbalance (TWI), which is particularly difficult to account for (especially in observation-based studies) and to the deep flow that is generally improperly accounted for in omega reconstructions through the bottom boundary condition. Nevertheless, the reconstruction of mesoscale vertical velocities may be sufficient to estimate vertical fluxes of oceanic properties in many cases of practical interest.

Abstract: Variations in ocean bottom pressure are important for understanding ocean circulation and climate. While most studies have focused on atmospherically driven variability, here we use eddy-permitting large ensemble simulation output from the OceaniC Chaos-ImPacts, strUcture, predicTability (OCCIPUT) project to isolate chaotic intrinsic variability generated by nonlinear oceanic processes. Analyzing separately the mean seasonal cycle and remainder variability in intra-annual (60-365 days) and subseasonal (2-60 days) bands, we find intrinsic variations larger than atmospherically driven ones over eddy-active regions across all timescales, particularly in the intra-annual range, where intrinsic variations dominate in almost 25% of the oceans. At scales larger than mesoscale, intrinsic variability is still considerable, supporting the process of energy inverse cascade toward lower frequency and larger scales. Results highlight the importance of intrinsic variability over a range of spatiotemporal scales and provide new insights on the interpretation of GRACE-like observations and their de-aliasing procedures.

Abstract: The persistence in the strength and direction of western boundary great ocean currents suggests that flow-driven turbines implemented in these currents have great potential for energy exploitation. However, technological developments in the design and installation of power-generating plants in the ocean are tied to our capacity to accurately identify the most favourable sites and provide practical assessments of the potentially recoverable energy. Here we use a global eddy-resolving ocean model to demonstrate that large ocean power plants may exert feedback on oceanic circulation that results in highly unpredictable changes in ocean currents. Regionally, these changes can drastically modify the path of the current. In extreme cases this corresponds to a decrease in the available power by more than 80% from initial expectations. Ocean currents offer a potential source of power, but identification of the best sites requires a detailed understanding of their variability. Barnier et al. undertake global eddy-resolving ocean modelling to gain insight into the feedback from ocean power plants on currents and the changes they can induce.

Abstract: The ocean surface boundary layer is a critical interface across which momentum, heat, and trace gases are exchanged between the oceans and atmosphere. Surface processes (winds, waves, and buoyancy forcing) are known to contribute significantly to fluxes within this layer. Recently, studies have suggested that submesoscale processes, which occur at small scales (0.1-10 km, hours to days) and therefore are not yet represented in most ocean models, may play critical roles in these turbulent exchanges. While observational support for such phenomena has been demonstrated in the vicinity of strong current systems and littoral regions, relatively few observations exist in the open-ocean environment to warrant representation in Earth system models. We use novel observations and simulations to quantify the contributions of surface and submesoscale processes to turbulent kinetic energy (TKE) dissipation in the open-ocean surface boundary layer. Our observations are derived from moorings in the North Atlantic, December 2012 to April 2013, and are complemented by atmospheric reanalysis. We develop a conceptual framework for dissipation rates due to surface and submesoscale processes. Using this framework and comparing with observed dissipation rates, we find that surface processes dominate TKE dissipation. A parameterization for symmetric instability is consistent with this result. We next employ simulations from an ocean front-resolving model to reestablish that dissipation due to surface processes exceeds that of submesoscale processes by 1-2 orders of magnitude. Together, these results suggest submesoscale processes do not dramatically modify vertical TKE budgets, though such dynamics may be climatically important owing to their ability to remove energy from the ocean.

Abstract: Uncertainties of snowpack models and of their meteorological forcings limit their use by avalanche hazard forecasters, or for glaciological and hydrological studies. The spatialized simulations currently available for avalanche hazard forecasting are only assimilating sparse meteorological observations. As suggested by recent studies, their forecasting skills could be significantly improved by assimilating satellite data such as snow reflectances from satellites in the visible and the near-infrared spectra. Indeed, these data can help constrain the microstructural properties of surface snow and light absorbing impurities content, which in turn affect the surface energy and mass budgets. This paper investigates the prerequisites of satellite data assimilation into a detailed snowpack model. An ensemble version of Meteo-France operational snowpack forecasting system (named S2M) was built for this study. This operational system runs on topographic classes instead of grid points, so-called 'semi-distributed' approach. Each class corresponds to one of the 23 mountain massifs of the French Alps (about 1000 km(2) each), an altitudinal range (by step of 300 m) and aspect (by step of 45 degrees). We assess the feasability of satellite data assimilation in such a semi-distributed geometry. Ensemble simulations are compared with satellite observations from MODIS and Sentinel-2, and with in-situ reflectance observations. The study focuses on the 2013-2014 and 2016-2017 winters in the Grandes-Rousses massif. Substantial Pearson R-2 correlations (0.75-0.90) of MODIS observations with simulations are found over the domain. This suggests that assimilating it could have an impact on the spatialized snowpack forecasting system. However, observations contain significant biases (0.1-0.2 in reflectance) which prevent their direct assimilation. MODIS spectral band ratios seem to be much less biased. This may open the way to an operational assimilation of MODIS reflectances into the Meteo-France snowpack modelling system.

Abstract: We present in this paper the results of the Russian Academy of Sciences North Atlantic Atmospheric Downscaling (RAS-NAAD) project, which provides a 40-yr 3D hindcast of the North Atlantic (10 degrees-80 degrees N) atmosphere at 14-km spatial resolution with 50 levels in the vertical direction (up to 50 hPa), performed with a regional setting of theWRF-ARW3.8.1model for the period 1979-2018 and forced by ERA-Interim as a lateral boundary condition. The dataset provides a variety of surface and free-atmosphere parameters at sigma model levels and meets many demands of meteorologists, climate scientists, and oceanographers working in both research and operational domains. Three-dimensional model output at 3-hourly time resolution is freely available to the users. Our evaluation demonstrates a realistic representation of most characteristics in both datasets and also identifies biases mostly in the ice-covered regions. High-resolution and nonhydrostatic model settings in NAAD resolve mesoscale dynamics first of all in the subpolar latitudes. NAAD also provides a new view of the North Atlantic extratropical cyclone activity with a much larger number of cyclones as compared with most reanalyses. It also effectively captures highly localized mechanisms of atmospheric moisture transports. Applications of NAAD to ocean circulation and wave modeling are demonstrated.

Abstract: In the near future, the Surface Water Ocean Topography (SWOT) mission will provide images of altimetric data at kilometric resolution. This unprecedented 2-dimensional data structure will allow the estimation of geostrophy-related quantities that are essential for studying the ocean surface dynamics and for data assimilation uses. To estimate these quantities, i.e., to compute spatial derivatives of the Sea Surface Height (SSH) measurements, the uncorrelated, small-scale noise and errors expected to affect the SWOT data must be smoothed out while minimizing the loss of relevant, physical SSH information. This paper introduces a new technique for de-noising the future SWOT SSH images. The de-noising model is formulated as a regularized least-square problem with a Tikhonov regularization based on the first-, second-, and third-order derivatives of SSH. The method is implemented and compared to other, convolution-based filtering methods with boxcar and Gaussian kernels. This is performed using a large set of pseudo-SWOT data generated in the western Mediterranean Sea from a 1/60 simulation and the SWOT simulator. Based on root mean square error and spectral diagnostics, our de-noising method shows a better performance than the convolution-based methods. We find the optimal parametrization to be when only the second-order SSH derivative is penalized. This de-noising reduces the spatial scale resolved by SWOT by a factor of 2, and at 10 km wavelengths, the noise level is reduced by factors of for summer and winter, respectively. This is encouraging for the processing of the future SWOT data.

Abstract: An important characteristic of geophysically turbulent flows is the transfer of energy between scales. Balanced flows pass energy from smaller to larger scales as part of the well-known upscale cascade, while submesoscale and smaller scale flows can transfer energy eventually to smaller, dissipative scales. Much effort has been put into quantifying these transfers, but a complicating factor in realistic settings is that the underlying flows are often strongly spatially heterogeneous and anisotropic. Furthermore, the flows may be embedded in irregularly shaped domains that can be multiply connected. As a result, straightforward approaches like computing Fourier spatial spectra of nonlinear terms suffer from a number of conceptual issues. In this paper, we develop a method to compute cross-scale energy transfers in general settings, allowing for arbitrary flow structure, anisotropy, and inhomogeneity. We employ Green's function approach to the kinetic energy equation to relate kinetic energy at a point to its Lagrangian history. A spatial filtering of the resulting equation naturally decomposes kinetic energy into length-scale-dependent contributions and describes how the transfer of energy between those scalestakes place. The method is applied to a doubly periodic simulation of vortex merger, resulting in the demonstration of the expected upscale energy cascade. Somewhat novel results are that the energy transfers are dominated by pressure work, rather than kinetic energy exchange, and dissipation is a noticeable influence on the larger scale energy budgets. We also describe, but do not employ here, a technique for developing filters to use in complex domains.

Abstract: The snow cover is a key component of land surface hydrology, especially in mountain areas where it governs the amount and timing of water availability in downstream areas. It is involved in relevant climate feedbacks and natural hazards such as avalanches and floods. Monitoring and forecasting snow cover characteristics is challenging. While snow cover extent is relatively easy to retrieve from satellite data, remote sensing retrievals of the snow water equivalent (SWE) is often inaccurate, particularly in complex mountainous terrain. Model-based snow cover estimates, driven by meteorological data, often bear significant uncertainties due to both input data and model errors. Data assimilation can combine both approaches to improve SWE estimates. In this paper, we review current state-of-the-art data assimilation methodologies used to optimally combine measurements with snow cover models in order to reduce uncertainties. The suitability of a given data assimilation method varies with the numerical complexity of snow models as well as the availability and the type of observations. This review describes the issues and challenges associated with data assimilation applied to the mountain snow cover, providing recommendations for existing and upcoming monitoring and prediction systems of snow hydrology in mountainous regions.

Abstract: Satellite-derived surface chlorophyll data are assimilated daily into a three-dimensional 24-member ensemble configuration of an online-coupled NEMO (Nucleus for European Modeling of the Ocean)-PISCES (Pelagic Interaction Scheme of Carbon and Ecosystem Stu dies) model for the North Atlantic Ocean. A 1-year multivariate assimilation experiment is performed to evaluate the impacts on analyses and forecast ensembles. Our results demonstrate that the integration of data improves surface analysis and forecast chlorophyll representation in a major part of the model domain, where the assimilated simulation outperforms the probabilistic skills of a non-assimilated analogous simulation. However, improvements are dependent on the reliability of the prior free ensemble. A regional diagnosis shows that surface chlorophyll is overestimated in the northern limit of the subtropical North Atlantic, where the prior ensemble spread does not cover the observation's variability. There, the system cannot deal with corrections that alter the equilibrium between the observed and unobserved state variables producing instabilities that propagate into the forecast. To alleviate these inconsistencies, a 1-month sensitivity experiment in which the assimilation process is only applied to model fluctuations is performed. Results suggest the use of this methodology may decrease the effect of corrections on the correlations between state vectors. Overall, the experiments presented here evidence the need of refining the description of model's uncertainties according to the biogeochemical characteristics of each oceanic region.

Abstract: Because of the irregular sampling pattern of raw altimeter data, many oceanographic applications rely on information from sea surface height (SSH) products gridded on regular grids where gaps have been filled with interpolation. Today, the operational SSH products are created using the simple, but robust, optimal interpolation (OI) method. If well tuned, the OI becomes computationally cheap and provides accurate results at low resolution. However, OI is not adapted to produce high-resolution and high-frequency maps of SSH. To improve the interpolation of SSH satellite observations, a data-driven approach (i.e., constructing a dynamical forecast model from the data) was recently proposed: analog data assimilation (AnDA). AnDA adaptively chooses analog situations from a catalog of SSH scenes-originating from numerical simulations or a large database of observations-which allow the temporal propagation of physical features at different scales, while each observation is assimilated. In this article, we review the AnDA and OI algorithms and compare their skills in numerical experiments. The experiments are observing system simulation experiments (OSSE) on the Lorenz-63 system and on an SSH reconstruction problem in the Gulf of Mexico. The results show that AnDA, with no necessary tuning, produces comparable reconstructions as does OI with tuned parameters. Moreover, AnDA manages to reconstruct the signals at higher frequencies than OI. Finally, an important additional feature for any interpolation method is to be able to assess the quality of its reconstruction. This study shows that the standard deviation estimated by AnDA is flow dependent, hence more informative on the reconstruction quality, than the one estimated by OI.

Abstract: Ocean ecosystems are subject to a multitude of stressors, including changes in ocean physics and biogeochemistry, and direct anthropogenic influences. Implementation of protective and adaptive measures for ocean ecosystems requires a combination of ocean observations with analysis and prediction tools. These can guide assessments of the current state of ocean ecosystems, elucidate ongoing trends and shifts, and anticipate impacts of climate change and management policies. Analysis and prediction tools are defined here as ocean circulation models that are coupled to biogeochemical or ecological models. The range of potential applications for these systems is broad, ranging from reanalyses for the assessment of past and current states, and short-term and seasonal forecasts, to scenario simulations including climate change projections. The objectives of this article are to illustrate current capabilities with regard to the three types of applications, and to discuss the challenges and opportunities. Representative examples of global and regional systems are described with particular emphasis on those in operational or pre-operational use. With regard to the benefits and challenges, similar considerations apply to biogeochemical and ecological prediction systems as do to physical systems. However, at present there are at least two major differences: (1) biogeochemical observation streams are much sparser than physical streams presenting a significant hinderance, and (2) biogeochemical and ecological models are largely unconstrained because of insufficient observations. Expansion of biogeochemical and ecological observation systems will allow for significant advances in the development and application of analysis and prediction tools for ocean biogeochemistry and ecosystems, with multiple societal benefits.

Abstract: This paper summarizes recent efforts on Observing System Evaluation (OS-Eval) by the Ocean Data Assimilation and Prediction (ODAP) communities such as GODAE OceanView and CLIVAR-GSOP. It provides some examples of existing OS-Eval methodologies, and attempts to discuss the potential and limitation of the existing approaches. Observing System Experiment (OSE) studies illustrate the impacts of the severe decrease in the number of TAO buoys during 2012-2014 and TRITON buoys since 2013 on ODAP system performance. Multi-system evaluation of the impacts of assimilating satellite sea surface salinity data based on OSEs has been performed to demonstrate the need to continue and enhance satellite salinity missions. Impacts of underwater gliders have been assessed using Observing System Simulation Experiments (OSSEs) to provide guidance on the effective coordination of the western North Atlantic observing system elements. OSSEs are also being performed under H2020 AtlantOS project with the goal to enhance and optimize the Atlantic in-situ networks. Potential of future satellite missions of wide-swath altimetry and surface ocean currents monitoring is explored through OSSEs and evaluation of Degrees of Freedomfor Signal (DFS). Forecast Sensitivity Observation Impacts (FSOI) are routinely evaluated for monitoring the ocean observation impacts in the US Navy's ODAP system. Perspectives on the extension of OS-Eval to coastal regions, the deep ocean, polar regions, coupled data assimilation, and biogeochemical applications are also presented. Based on the examples above, we identify the limitations of OS-Eval, indicating that the most significant limitation is reduction of robustness and reliability of the results due to their system-dependency. The difficulty of performing evaluation in near real time is also critical. A strategy to mitigate the limitation and to strengthen the impact of evaluations is discussed. In particular, we emphasize the importance of collaboration within the ODAP community for multi-system evaluation and of communication with ocean observational communities on the design of OS-Eval, required resources, and effective distribution of the results. Finally, we recommend further developing OS-Eval activities at international level with the support of the international ODAP (e.g., OceanPredict and CLIVAR-GSOP) and observational communities.

Abstract: Satellite observations and output from a high-resolution ocean model are used to investigate how the Loop Current in the Gulf of Mexico affects the Gulf Stream transport through the Florida Straits. We find that the expansion (contraction) of the Loop Current leads to lower (higher) transports through the Straits of Florida. The associated surface velocity anomalies are coherent from the southwestern tip of Florida to Cape Hatteras. A simple continuity-based argument can be used to explain the link between the Loop Current and the downstream Gulf Stream transport: as the Loop Current lengthens (shortens) its path in the Gulf of Mexico, the flow out of the Gulf decreases (increases). Anomalies in the surface velocity field are first seen to the southwest of Florida and within 4 weeks propagate through the Florida Straits up to Cape Hatteras and into the Gulf Stream Extension. In both the observations and the model this propagation can be seen as pulses in the surface velocities. We estimate that the Loop Current variability can be linked to a variability of several Sverdrups (1Sv = 10(6) m(3) s(-1)) through the Florida Straits. The exact timing of the Loop Current variability is largely unpredictable beyond a few weeks and its variability is therefore likely a major contributor to the chaotic/intrinsic variability of the Gulf Stream. However, the time lag between the Loop Current and the flow downstream of the Gulf of Mexico means that if a lengthening/shortening of the Loop Current is observed this introduces some predictability in the downstream flow for a few weeks.

Abstract: From the recent developments of data-driven methods as a means to better exploit large-scale observation, simulation and reanalysis datasets for solving inverse problems, this study addresses the improvement of the reconstruction of higher-resolution Sea Level Anomaly (SLA) fields using analog strategies. This reconstruction is stated as an analog data assimilation issue, where the analog models rely on patch-based and Empirical Orthogonal Functions (EOF)-based representations to circumvent the curse of dimensionality. We implement an Observation System Simulation Experiment (OSSE) in the South China Sea. The reported results show the relevance of the proposed framework with a significant gain in terms of Root Mean Square Error (RMSE) for scales below 100 km. We further discuss the usefulness of the proposed analog model as a means to exploit high-resolution model simulations for the processing and analysis of current and future satellite-derived altimetric data with regard to conventional interpolation schemes, especially optimal interpolation.

Abstract: The Surface Water and Ocean Topography (SWOT) mission is a next generation satellite mission expected to provide a 2 km-resolution observation of the sea surface height (SSH) on a two-dimensional swath. Processing SWOT data will be challenging because of the large amount of data, the mismatch between a high spatial resolution and a low temporal resolution, and the observation errors. The present paper focuses on the reduction of the spatially structured errors of SWOT SSH data. It investigates a new error reduction method and assesses its performance in an observing system simulation experiment. The proposed error-reduction method first projects the SWOT SSH onto a subspace spanned by the SWOT spatially structured errors. This projection is removed from the SWOT SSH to obtain a detrended SSH. The detrended SSH is then processed within an ensemble data assimilation analysis to retrieve a full SSH field. In the latter step, the detrending is applied to both the SWOT data and an ensemble of model-simulated SSH fields. Numerical experiments are performed with synthetic SWOT observations and an ensemble from a North Atlantic, 1/60 degrees simulation of the ocean circulation (NATL60). The data assimilation analysis is carried out with an ensemble Kalman filter. The results are assessed with root mean square errors, power spectrum density, and spatial coherence. They show that a significant part of the large scale SWOT errors is reduced. The filter analysis also reduces the small scale errors and allows for an accurate recovery of the energy of the signal down to 25 km scales. In addition, using the SWOT nadir data to adjust the SSH detrending further reduces the errors.

Abstract: The observation and simulation of the variability of coastal sea level are impacted by various uncertainties, such as measurement errors and sampling biases, unresolved processes, and model and forcing biases. Ocean model simulations suggest that another uncertainty should be taken into account for the attribution of sea-level changes. Global ocean simulations indeed show that resolving mesoscale turbulence (even partly) promotes the emergence of low-frequency (LF) chaotic intrinsic variability (CIV) which causes substantial random fluctuations of sea level up to multiple decades in eddy-active regions of the world ocean. This random LFCIV is superimposed on the atmospherically forced (or simply “forced”) fluctuations, which are directly controlled by the atmospheric variability. We show from a large ensemble of global oceanic hindcasts that this multi-decadal LFCIV leaves a substantial imprint on the long-term trends (1993-2015) of coastal sea level: over 17-20% of the global ocean coastal area, in particular along the coastlines of the northwestern Pacific and Indian Oceans, and around the Gulf of Mexico, random sea-level trends may blur their atmospherically forced counterpart, such that simulated (and potentially observed) coastal sea-level trends cannot be unambiguously attributed to atmospheric or anthropic causes. The steric and manometric sea-level change contributions of these uncertainties are discussed, suggesting that they mostly come from the manometric sea-level trends near the coasts.

Abstract: A major challenge for managing impacts and implementing effective mitigation measures and adaptation strategies for coastal zones affected by future sea level (SL) rise is our limited capacity to predict SL change at the coast on relevant spatial and temporal scales. Predicting coastal SL requires the ability to monitor and simulate a multitude of physical processes affecting SL, from local effects of wind waves and river runoff to remote influences of the large-scale ocean circulation on the coast. Here we assess our current understanding of the causes of coastal SL variability on monthly to multi-decadal timescales, including geodetic, oceanographic and atmospheric aspects of the problem, and review available observing systems informing on coastal SL. We also review the ability of existing models and data assimilation systems to estimate coastal SL variations and of atmosphere-ocean global coupled models and related regional downscaling efforts to project future SL changes. We discuss (1) observational gaps and uncertainties, and priorities for the development of an optimal and integrated coastal SL observing system, (2) strategies for advancing model capabilities in forecasting short-term processes and projecting long-term changes affecting coastal SL, and (3) possible future developments of sea level services enabling better connection of scientists and user communities and facilitating assessment and decision making for adaptation to future coastal SL change.

Abstract: This paper introduces the Sobol' indices approach for global sensitivity analysis (SA), in the context of marine biogeochemistry. Such an approach is particularly well suited for ocean biogeochemical models, which make use of numerous parameters within large sets of differential equations with complex dependencies. This SA allows for a detailed study of the relative influence of a large number of input parameters on output quantities of interest to be chosen. It is able to distinguish between direct effects of these parameters and effects due to interaction between two or more parameters. Although demanding in terms of computation, such a tool is now becoming affordable, thanks to the development of distributed computing environments. An applicative example is presented with the MODECOGeL biogeochemical model, and illustrates the advantages of this approach over standard local SA.

Abstract: Spatio-temporal variability of surface geostrophic mesoscale currents in the Balearic Sea (western Mediterranean) is characterized from satellite altimetry in combination with in-situ velocity measurements collected, among others, by drifting buoys, gliders and high-frequency radar. Here, we explore the use of tracking data from living organisms in the Balearic Sea as an alternative way to acquire in-situ velocity measurements. Specifically, we use GPS-tracks of resting Scopoli's shearwaters Calonectris diomedea, that act as passive drifters, and compare them with satellite-derived velocity patterns. Results suggest that animal-borne GPS data can be used to identify rafting behaviour outside of the breeding colonies and, furthermore, as a proxy to describe local sea surface currents. Four rafting patterns were identified according to the prevailing driving forces responsible for the observed trajectories. We find that 76% of the bird trajectories are associated with the combined effects of slippage and Ekman drift and/or surface drag; 59% are directly driven by the sea surface currents. Shearwaters are therefore likely to be passively transported by these driving forces while resting. The tracks are generally consistent with the mesoscale features observed in satellite data and identified with eddy-tracking software.

Abstract: Ocean data assimilation systems encompass a wide range of scales that are difficult to control simultaneously using partial observation networks. All scales are not observable by all observation systems, which is not easily taken into account in current ocean operational systems. The main reason for this difficulty is that the error covariance matrices are usually assumed to be local (e.g. using a localisation algorithm in ensemble data assimilation systems), so that the large-scale patterns are removed from the error statistics. To better exploit the observational information available for all scales in the assimilation systems of the Copernicus Marine Environment Monitoring Service, we investigate a new method to introduce scale separation in the assimilation scheme. The method is based on a spectral transformation of the assimilation problem and consists in carrying out the analysis with spectral localisation for the large scales and spatial localisation for the residual scales. The target is to improve the observational update of the large-scale components of the signal by an explicit observational constraint applied directly on the large scales and to restrict the use of spatial localisation to the small-scale components of the signal. To evaluate our method, twin experiments are carried out with synthetic altimetry observations (simulating the Jason tracks), assimilated in a 1/4 degrees model configuration of the North Atlantic and the Nordic Seas. Results show that the transformation to the spectral domain and the spectral localisation provides consistent ensemble estimates of the state of the system (in the spectral domain or after backward transformation to the spatial domain). Combined with spatial localisation for the residual scales, the new scheme is able to provide a reliable ensemble update for all scales, with improved accuracy for the large scale; and the performance of the system can be checked explicitly and separately for all scales in the assimilation system.

Abstract: The most common methodology used to detect and characterize mesoscale eddies in the global ocean is to analyze altimetry-based sea-level gridded products with an automatic eddy detection and tracking algorithm. However, a careful look at the location of altimetry tracks shows that their separation is often larger than the Rossby radius of deformation. This implies that gridded products based on the information obtained along track would potentially be unable to characterize the mesoscale variability and, in particular, the eddy field. In this study, we analyze up to what extent sea-level gridded products are able to characterize mesoscale eddies with a special focus on the North Atlantic Ocean and the Mediterranean Sea. In order to perform this task, we have generated synthetic sea level anomaly maps using along-track data extracted from realistic high-resolution ocean model simulations and applying an optimal interpolation procedure. Then, we have used an eddy detection and tracking algorithm to the gridded synthetic product and to the original model outputs and compared the characteristics of the resulting eddy fields. Our results suggest that gridded products largely underestimate the density of eddies, capturing only between 6% and 16% of the total number of eddies. The main reason is that the spatial resolution of the gridded products is not enough to capture the small-scale eddies that are the most abundant. Also, the unresolved structures are aliased into larger structures in the gridded products, so those products show an unrealistic number of large eddies with overestimated amplitudes. Mesoscale eddies are ocean vortexes that are found all across the global ocean. These structures can move water inside their interiors and stir the surrounding waters, resulting in a net transport of water properties, such as heat and salt. The most common way to study these eddies is by using satellite-based observations of the signature that most of eddies have on the sea surface. We show, by using a new generation of numerical models and mimicking the measuring process that satellites do, that the vast majority of the eddy field is missed because the available observations do not have enough resolution to resolve the smaller vortexes. Moreover, the mapping procedure used tends to merge several smaller eddies into a larger one, making the true detection of eddies with size enough to be correctly captured by satellite measurements not reliable.

Abstract: Calibration/Validation (C/V) studies using sites in the oceans have a long history and protocols are well established. Over lakes, C/V allows addressing problems such as the performance of the various retracking algorithms and evaluating the accuracy of the geophysical corrections for continental waters. This is achievable when measurements of specific and numerous field campaigns and a ground permanent network of level gauges and weather stations are processed. C/V consists of installation of permanent sites (weather stations, limnigraphs, and GPS reference points) and the organization of regular field campaigns. The lake Issykkul serves as permanent site of C/V, for a multi-mission purpose. The objective of this paper is to calculate the altimeter biases of Jason-3 and Sentinel-3A, both belonging to an operational satellite system which is used for the long-term monitoring of lake level variations. We have also determined the accuracy of the altimeters of these two satellites, through a comparison analysis with in situ data. In 2016 and 2017, three campaigns have been organized over this lake in order to estimate the absolute bias of the nadir altimeter onboard the Jason-3 and Sentinel-3A. The fieldwork consisted of measuring water height using a GPS system, carried on a boat, along the track of the altimeter satellite across the lake. It was performed at the time of the pass of the altimeter. Absolute altimeter biases were calculated by averaging the water height differences along the pass of the satellite (GPS from the boat system versus altimetry). Jason-3 operates in a Low Resolution Mode (LRM), while the Sentinel-3A operates in Synthetic Aperture Radar (SAR) mode. In this study we found that the absolute biases measured for Jason-3 were -28 +/- 40 mm with the Ocean retracker and 206 +/- 30 mm with the Ice-1 retracker. The biases for Sentinel-3A were -14 +/- 20 mm with the Samosa (Ocean like) retracker and 285 +/- 20 mm with the OCOG (Ice-1-like) retracker. We have also evaluated the accuracy of these two altimeters over Lake Issykkul which reached to 3 cm, for both the instruments, using the Ocean retracker.

Abstract: Several methods that reconstruct the three-dimensional ocean dynamics from sea level are presented and evaluated in the Gulf Stream region with a 1/60 degrees realistic numerical simulation. The use of sea level is motivated by its better correlation with interior pressure or quasi-geostrophic potential vorticity (PV) compared to sea surface temperature and sea surface salinity, and, by its observability via satellite altimetry. The simplest method of reconstruction relies on a linear estimation of pressure at depth from sea level. Another method consists in linearly estimating PV from sea level first and then performing a PV inversion. The last method considered, labeled SQG for surface quasi-geostrophy, relies on a PV inversion but assumes no PV anomalies. The first two methods show comparable skill at levels above -800 m. They moderately outperform SQG which emphasizes the difficulty of estimating interior PV from surface variables. Over the 250-1,000 m depth range, the three methods skillfully reconstruct pressure at wavelengths between 500 and 200 km whereas they exhibit a rapid loss of skill between 200 and 100 km wavelengths. Applicability to a real case scenario and leads for improvements are discussed.

Abstract: Over northeastern Canada, the amount of water stored in a snowpack, estimated by its snow water equivalent (SWE) amount, is a key variable for hydrological applications. The limited number of weather stations driving snowpack models over large and remote northern areas generates great uncertainty in SWE evolution. A data assimilation (DA) scheme was developed to improve SWE estimates by updating meteorological forcing data and snowpack states with passive microwave (PMW) satellite observations and without using any surface-based data. In this DA experiment, a particle filter with a Sequential Importance Resampling algorithm (SIR) was applied and an inflation technique of the observation error matrix was developed to avoid ensemble degeneracy. Advanced Microwave Scanning Radiometer 2 (AMSR-2) brightness temperature (T-B) observations were assimilated into a chain of models composed of the Crocus multilayer snowpack model and radiative transfer models. The microwave snow emission model (Dense Media Radiative Transfer – Multi-Layer model, DMRT-ML), the vegetation transmissivity model (omega-tau(opt)), and atmospheric and soil radiative transfer models were calibrated to simulate the contributions from the snowpack, the vegetation, and the soil, respectively, at the top of the atmosphere. DA experiments were performed for 12 stations where daily continuous SWE measurements were acquired over 4 winters (2012-2016). Best SWE estimates are obtained with the assimilation of the T-Bs at 11, 19, and 37 GHz in vertical polarizations. The overall SWE bias is reduced by 68% compared to the original SWE simulations, from 23.7 kg m(-2) without assimilation to 7.5 kg m(-2) with the assimilation of the three frequencies. The overall SWE relative percentage of error (RPE) is 14.1% (19% without assimilation) for sites with a fraction of forest cover below 75 %, which is in the range of accuracy needed for hydrological applications. This research opens the way for global applications to improve SWE estimates over large and remote areas, even when vegetation contributions are up to 50% of the PMW signal.

Abstract: A global 1/4 degrees ocean/sea-ice 50-member ensemble simulation is analyzed to disentangle the imprints of the atmospheric forcing and the chaotic ocean variability on regional sea level trends over the satellite altimetry period. We find that the chaotic ocean variability may mask atmospherically forced regional sea level trends over 38% of the global ocean area from 1993 to 2015, and over 47% of this area from 2005 to 2015. These regions are located in the western boundary currents, in the Southern Ocean and in the subtropical gyres. While these results do not question the anthropogenic origin of global mean sea level rise, they give new insights into the intrinsically oceanic versus atmospheric forcing of regional sea level trends and provide new constraints on the measurement time required to attribute regional sea level trends to the atmospheric forcing or to climate change. Plain Language Summary As a direct consequence of anthropogenic influences, global mean sea level rises in response to ocean warming and land ice melting. Since the early 1990s, satellite altimetry has revealed large regional contrasts in sea level trends, controlled by temperature and salinity changes, oceanic processes and atmospheric forcing. Using an ensemble of forced eddying ocean simulations, we show that regional sea level trends over the altimetric period are only partly determined by the atmospheric evolution (both natural and anthropogenic): nonlinear ocean processes produce additional sea level trends that are inherently random, which can compete in certain regions with the externally forced trends. These results do not question the existence of global and regional sea level trends, but suggest that sea level trends may not be unambiguously attributed to external causes in certain regions.

Abstract: Icebergs represent approximately half of Greenland's yearly mass loss, having important implications for biological productivity, freshwater fluxes in the ocean, and navigation. This study applies an iceberg model that uses integrated ocean fields (from surface to iceberg keel) to simulate the drift and decay of Greenland icebergs. This version of iceberg model (VERT) is compared with a more widely adopted version (SURF) which only uses surface ocean fields in its equations. We show that icebergs in VERT tend to drift along the shelf break, while in SURF they concentrate along the coastline. Additionally, we show that Greenland's southeast coast is the source of similar to 60% of the icebergs that cross the interior of the Labrador Seaa region that stages buoyancy-driven convection and is, therefore, sensitive to freshwater input. Plain Language Summary Thousands of icebergs break off from Greenland every year, threatening navigation along North America's east coast. Since it is difficult to monitor individual icebergs, computer simulations are useful to help us understand their common pathways and, potentially, to predict when and from where icebergs come from. In this study, we use an improved iceberg model (one that uses the variations of ocean currents and temperature with depth to interact with icebergs) to simulate Greenland icebergs' distribution and their persistence in different regions of the North Atlantic. We show that this improved version better reproduces iceberg pathways observed in the past. Moreover, we find that icebergs breaking off from the southeast part of Greenland compose most icebergs reaching the middle of the Labrador Seaa region where iceberg melt may affect ocean circulation and, consequently, heat distribution from tropics to poles. This means that an increasing volume of icebergs coming out of this particular region in a warmer world might have an effect back on the climate.

Abstract: Global ocean models that admit mesoscale turbulence spontaneously generate a substantial interannual-to-multidecadal chaotic intrinsic variability in the absence of atmospheric forcing variability at these timescales. This phenomenon is substantially weaker in non-turbulent ocean models but provides a marked stochastic flavor to the low-frequency variability in eddying ocean models, which are being coupled to the atmosphere for next-generation climate projections. In order to disentangle the atmospherically forced and intrinsic ocean variabilities, the OCCIPUT (OceaniC Chaos – ImPacts, strUcture, predicTability) project performed a long (1960-2015), large ensemble (50 members) of global ocean/sea ice 1/4 degrees simulations driven by the same atmospheric reanalysis, but with perturbed initial conditions. Subsequent ensemble statistics show that the ocean variability can be seen as a broadband “noise,” with characteristic scales reaching multiple decades and basin sizes, locally modulated by the atmospheric variability. In several mid-latitude regions, chaotic processes have more impact than atmospheric variability on both the low-frequency variability and the long-term trends of regional ocean heat content. Consequently, certain climate-relevant oceanic signals cannot be unambiguously attributed to atmospheric variability, raising new issues for the detection, attribution, and interpretation of oceanic heat variability and trends in the presence of mesoscale turbulence.

Abstract: A seasonally forced 1/12 degrees global ocean/sea ice simulation is used to characterize the spatiotemporal inverse cascade of kinetic energy (KE). Nonlinear scale interactions associated with relative vorticity advection are evaluated using cross-spectral analysis in the frequency-wavenumber domain from sea level anomaly (SLA) time series. This analysis is applied within four eddy-active midlatitude regions having large intrinsic variability spread over a wide range of scales. Over these four regions, mesoscale surface KE is shown to spontaneously cascade toward larger spatial scales-between the deformation scale and the Rhines scale- and longer time scales (possibly exceeding 10 years). Other nonlinear processes might have to be invoked to explain the longer time scales of intrinsic variability, which have a substantial surface imprint at midlatitudes. The analysis of a fully forced 1/12 degrees hindcast shows that low-frequency and synoptic atmospheric forcing barely affects this inverse KE cascade. The inverse cascade is also at work in a 1/4 degrees simulation, albeit with a weaker intensity, consistent with the weaker intrinsic variability found at this coarser resolution. In the midlatitude North Pacific, the spatiotemporal cascade transfers KE from high-frequency frontal Rossby waves (FRWs), probably generated by baroclinic instability, toward the lower-frequency, westward-propagating mesoscale eddy (WME) field. The WMEs provide local gradients of potential vorticity that support these short Doppler-shifted FRWs. FRWs have periods shorter than 2 months and might be subsampled by altimetric observations, perhaps explaining why the temporal inverse cascade deduced from high-resolution models and mapped altimeter products can be quite different. The nature of the nonlinear interactions between FRWs and WMEs remains unclear but might involve wave turbulence processes.

Abstract: We present a new surface-atmospheric dataset for driving ocean-sea-ice models based on Japanese 55-year atmospheric reanalysis (JRA-55), referred to here as JRA55-do. The JRA55-do dataset aims to replace the CORE interannual forcing version 2 (hereafter called the CORE dataset), which is currently used in the framework of the Coordinated Ocean-ice Reference Experiments (COREs) and the Ocean Model Intercomparison Project (OMIP). A major improvement in JRA55-do is the refined horizontal grid spacing (similar to 55 km) and temporal interval (3 hr). The data production method for JRA55-do essentially follows that of the CORE dataset, whereby the surface fields from an atmospheric reanalysis are adjusted relative to reference datasets. To improve the adjustment method, we use high-quality products derived from satellites and from several other atmospheric reanalysis projects, as well as feedback on the CORE dataset from the ocean modelling community. Notably, the surface air temperature and specific humidity are adjusted using multi-reanalysis ensemble means. In JRA55-do, the downwelling radiative fluxes and precipitation, which are affected by an ambiguous cloud parameterisation employed in the atmospheric model used for the reanalysis, are based on the reanalysis products. This approach represents a notable change from the CORE dataset, which imported independent observational products. Consequently, the JRA55-do dataset is more self-contained than the CORE dataset, and thus can be continually updated in near real-time. The JRA55-do dataset extends from 1958 to the present, with updates expected at least annually. This paper details the adjustments to the original JRA-55 fields, the scientific rationale for these adjustments, and the evaluation of JRA55-do. The adjustments successfully corrected the biases in the original JRA-55 fields. The globally averaged features are similar between the JRA55-do and CORE datasets, implying that JRA55-do can suitably replace the CORE dataset for use in driving global ocean-sea-ice models.

Abstract: This paper compares several commonly used state-of-the-art ensemble-based data assimilation methods in a coherent mathematical notation. The study encompasses different methods that are applicable to high-dimensional geophysical systems, like ocean and atmosphere and provide an uncertainty estimate. Most variants of Ensemble Kalman Filters, Particle Filters and second-order exact methods are discussed, including Gaussian Mixture Filters, while methods that require an adjoint model or a tangent linear formulation of the model are excluded. The detailed description of all the methods in a mathematically coherent way provides both novices and experienced researchers with a unique overview and new insight in the workings and relative advantages of each method, theoretically and algorithmically, even leading to new filters. Furthermore, the practical implementation details of all ensemble and particle filter methods are discussed to show similarities and differences in the filters aiding the users in what to use when. Finally, pseudo-codes are provided for all of the methods presented in this paper.

Abstract: This paper presents the technical implementation of a new, probabilistic version of the NEMO ocean-sea-ice modelling system. Ensemble simulations with N members running simultaneously within a single executable, and interacting mutually if needed, are made possible through an enhanced message-passing interface (MPI) strategy including a double parallelization in the spatial and ensemble dimensions. An example application is then given to illustrate the implementation, performances, and potential use of this novel probabilistic modelling tool. A large ensemble of 50 global ocean-sea-ice hindcasts has been performed over the period 1960-2015 at eddy-permitting resolution (1/4 degrees) for the OCCIPUT (oceanic chaos – impacts, structure, predictability) project. This application aims to simultaneously simulate the intrinsic/chaotic and the atmospherically forced contributions to the ocean variability, from mesoscale turbulence to interannual-to-multidecadal timescales. Such an ensemble indeed provides a unique way to disentangle and study both contributions, as the forced variability may be estimated through the ensemble mean, and the intrinsic chaotic variability may be estimated through the ensemble spread.

Abstract: It has been suggested that the coastal Southern Ocean subsurface may warm over the 21st century in response to strengthening and poleward shifting winds, with potential adverse effects on West Antarctic glaciers. However, using a 1/12 degrees ocean regional model that includes ice-shelf cavities, we find a more complex response to changing winds in the Amundsen Sea. Simulated offshore subsurface waters get colder under strengthened and poleward shifted winds representative of the SAM projected trend. The buoyancy-driven circulation induced by ice-shelf melt transports this cold offshore anomaly onto the continental shelf, leading to cooling and decreased melt below 450 m. In the vicinity of ice-shelf fronts, Ekman pumping contributes to raise the isotherms in response to changing winds. This effect overwhelms the horizontal transport of colder offshore waters at intermediate depths (between 200 and 450 m), and therefore increases melt rates in the upper part of the ice-shelf cavities, which reinforces the buoyancy-driven circulation and further contributes to raise the isotherms. Then, prescribing an extreme grounding line retreat projected for 2100, the total melt rates simulated underneath Thwaites and Pine Island are multiplied by 2.5. Such increase is explained by a larger ocean/ice interface exposed to CDW, which is then amplified by a stronger melt-induced circulation along the ice draft. Our main conclusions are that (1) outputs from ocean models that do not represent ice shelf cavities (e.g., CMIP5 models) should not be directly used to predict the thermal forcing of future ice shelf cavities; (2) coupled ocean/ice sheet models with a velocity-dependent melt formulation are needed for future projections of glaciers experiencing a significant grounding line retreat.

Abstract: Satellite sensors increasingly provide high-resolution (HR) observations of the ocean. They supply observations of sea surface height (SSH) and of tracers of the dynamics such as sea surface salinity (SSS) and sea surface temperature (SST). In particular, the Surface Water Ocean Topography (SWOT) mission will provide measurements of the surface ocean topography at very high-resolution (HR) delivering unprecedented information on the meso-scale and submeso-scale dynamics. This study investigates the feasibility to use these measurements to reconstruct meso-scale features simulated by numerical models, in particular on the vertical dimension. A methodology to reconstruct three-dimensional (3D) multivariate meso-scale scenes is developed by using a HR numerical model of the Solomon Sea region. An inverse problem is defined in the framework of a twin experiment where synthetic observations are used. A true state is chosen among the 3D multivariate states which is considered as a reference state. In order to correct a first guess of this true state, a two-step analysis is carried out. A probability distribution of the first guess is defined and updated at each step of the analysis: (i) the first step applies the analysis scheme of a reduced-order Kalman filter to update the first guess probability distribution using SSH observation; (ii) the second step minimizes a cost function using observations of HR image structure and a new probability distribution is estimated. The analysis is extended to the vertical dimension using 3D multivariate empirical orthogonal functions (EOFs) and the probabilistic approach allows the update of the probability distribution through the two-step analysis. Experiments show that the proposed technique succeeds in correcting a multivariate state using meso-scale and submeso-scale information contained in HR SSH and image structure observations. It also demonstrates how the surface information can be used to reconstruct the ocean state below the surface.

Abstract: Mesoscale activity is an important component of the Solomon Sea circulation that interacts with the energetic low-latitude western boundary currents of the South Tropical Pacific Ocean carrying waters of subtropical origin before joining the equatorial Pacific. Mixing associated with mesoscale activity could explain water mass transformation observed in the Solomon Sea that likely impacts El Nino Southern Oscillation dynamics. This study makes synergetic use of glider data, altimetry, and high-resolution model for exploring mesoscale eddies, especially their vertical structures, and their role on the Solomon Sea circulation. The description of individual eddies observed by altimetry and gliders provides the first elements to characterize the 3-D structure of these tropical eddies, and confirms the usefulness of the model to access a more universal view of such eddies. Mesoscale eddies appear to have a vertical extension limited to the Surface Waters (SW) and the Upper Thermocline Water (UTW), i.e., the first 140-150 m depth. Most of the eddies are nonlinear, meaning that eddies can trap and transport water properties. But they weakly interact with the deep New Guinea Coastal Undercurrent that is a key piece of the equatorial circulation. Anticyclonic eddies are particularly efficient to advect salty and warm SW coming from the intrusion of equatorial Pacific waters at Solomon Strait, and to impact the characteristics of the New Guinea Coastal Current. Cyclonic eddies are particularly efficient to transport South Pacific Tropical Water (SPTW) anomalies from the North Vanuatu Jet and to erode by diapycnal mixing the high SPTW salinity.

Abstract: A 1/128 ocean model configuration of the Amundsen Sea sector is developed to better understand the circulation induced by ice-shelf melt and the impacts on the surrounding ocean and sea ice. Eighteen sensitivity experiments to drag and heat exchange coefficients at the ice shelf/ocean interface are performed. The total melt rate simulated in each cavity is function of the thermal Stanton number, and for a given thermal Stanton number, melt is slightly higher for lower values of the drag coefficient. Sub-ice-shelf melt induces a thermohaline circulation that pumps warm circumpolar deep water into the cavity. The related volume flux into a cavity is 100-500 times stronger than the melt volume flux itself. Ice-shelf melt also induces a coastal barotropic current that contributes 45612% of the total simulated coastal transport. Due to the presence of warm circumpolar deep waters, the melt-induced inflow typically brings 4-20 times more heat into the cavities than the latent heat required for melt. For currently observed melt rates, approximately 6-31% of the heat that enters a cavity with melting potential is actually used to melt ice shelves. For increasing sub-ice-shelf melt rates, the transport in the cavity becomes stronger, and more heat is pumped from the deep layers to the upper part of the cavity then advected toward the ocean surface in front of the ice shelf. Therefore, more ice-shelf melt induces less sea-ice volume near the ice sheet margins. Plain Language Summary The ice-shelf cavities of the Amundsen Sea, Antarctica, act as very powerful pumps that create strong inflows of warm water under the ice-shelves, as well as significant circulation changes in the entire region. Such warm inflows bring more heat than required to melt ice, so that a large part of that heat exits ice-shelf cavities without being used. Due to mixing between warm deep waters and melt freshwater, melt-induced flows are warm and buoyant when they leave cavities. Therefore, they reach the ocean surface near ice-shelf fronts and can melt significant amounts of sea ice. It is thus suggested that climatic trends in sub ice-shelf melt could partly explain sea ice trends near the ice-sheet margins in the Amundsen Sea region.

Abstract: Global rainfall information is useful for many applications. However, real-time versions of satellite-based rainfall products are known to contain errors. Recent studies have demonstrated how the information about rainfall intrinsically contained in soil moisture data can be utilised for improving rainfall estimates. That is, soil moisture dynamics are impacted for several days by the accumulated amount of rainfall following within a particular event. In this context, soil moisture data from the Soil Moisture Ocean Salinity (SMOS) satellite is used in this study to correct rainfall accumulation estimates provided by satellite-based real-time precipitation products such as CMORPH, TRMM-3B42RT or PERSIANN. An algorithm based on the SMOS measurements data assimilation is tested in two land-surface models of different complexity: a simple hydrological model (Antecedent Precipitation Index (API)) and a more sophisticated state-of-the-art land-surface model (SURFEX (Surface Extemalisee)). We show how the assimilation technique, based on a particle filter method, generally leads to a significant improvement in rainfall estimates, with slightly better results for the simpler (and less computationally demanding) API model. This methodology has been evaluated for six years at ten sites around the world with different land use and climatological features. The results also show the limitations of the methodology in regions highly affected by mountainous terrain, forest or intense radio-frequency interference (RFI), which can notably affect the quality of the retrievals. The satisfactory results shown here invite the future operational application of the methodology in near-real time on a global scale.

Abstract: Quantifying the effect of the seawater density changes on sea level variability is of crucial importance for climate change studies, as the sea level cumulative rise can be regarded as both an important climate change indicator and a possible danger for human activities in coastal areas. In this work, as part of the Ocean Reanalysis Intercomparison Project, the global and regional steric sea level changes are estimated and compared from an ensemble of 16 ocean reanalyses and 4 objective analyses. These estimates are initially compared with a satellite-derived (altimetry minus gravimetry) dataset for a short period (2003-2010). The ensemble mean exhibits a significant high correlation at both global and regional scale, and the ensemble of ocean reanalyses outperforms that of objective analyses, in particular in the Southern Ocean. The reanalysis ensemble mean thus represents a valuable tool for further analyses, although large uncertainties remain for the inter-annual trends. Within the extended intercomparison period that spans the altimetry era (1993-2010), we find that the ensemble of reanalyses and objective analyses are in good agreement, and both detect a trend of the global steric sea level of 1.0 and 1.1 ± 0.05 mm/year, respectively. However, the spread among the products of the halosteric component trend exceeds the mean trend itself, questioning the reliability of its estimate. This is related to the scarcity of salinity observations before the Argo era. Furthermore, the impact of deep ocean layers is non-negligible on the steric sea level variability (22 and 12 % for the layers below 700 and 1500 m of depth, respectively), although the small deep ocean trends are not significant with respect to the products spread.

Abstract: Light-absorbing impurities (LAIs) decrease snow albedo, increasing the amount of solar energy absorbed by the snowpack. Its most intuitive and direct impact is to accelerate snowmelt. Enhanced energy absorption in snow also modifies snow metamorphism, which can indirectly drive further variations of snow albedo in the near-infrared part of the solar spectrum because of the evolution of the near-surface snow microstructure. New capabilities have been implemented in the detailed snowpack model SURFEX/ISBACrocus (referred to as Crocus) to account for impurities' deposition and evolution within the snowpack and their direct and indirect impacts. Once deposited, the model computes impurities' mass evolution until snow melts out, accounting for scavenging by meltwater. Taking advantage of the recent inclusion of the spectral radiative transfer model TARTES (Two-stream Analytical Radiative TransfEr in Snow model) in Crocus, the model explicitly represents the radiative impacts of light-absorbing impurities in snow. The model was evaluated at the Col de Porte experimental site (French Alps) during the 2013-2014 snow season against in situ standard snow measurements and spectral albedo measurements. In situ meteorological measurements were used to drive the snowpack model, except for aerosol deposition fluxes. Black carbon (BC) and dust deposition fluxes used to drive the model were extracted from simulations of the atmospheric model ALADIN-Climate. The model simulates snowpack evolution reasonably, providing similar performances to our reference Crocus version in terms of snow depth, snow water equivalent (SWE), near-surface specific surface area (SSA) and shortwave albedo. Since the reference empirical albedo scheme was calibrated at the Col de Porte, improvements were not expected to be significant in this study. We show that the deposition fluxes from the ALADIN-Climate model provide a reasonable estimate of the amount of light-absorbing impurities deposited on the snowpack except for extreme deposition events which are greatly underestimated. For this particular season, the simulated melt-out date advances by 6 to 9 days due to the presence of light-absorbing impurities. The model makes it possible to apportion the relative importance of direct and indirect impacts of light-absorbing impurities on energy absorption in snow. For the snow season considered, the direct impact in the visible part of the solar spectrum accounts for 85% of the total impact, while the indirect impact related to accelerated snow metamorphi

Abstract: In this paper, three incremental analysis update schemes (IAU 0, IAU 50 and IAU 100) are compared in the same assimilation experiments with a realistic eddy permitting primitive equation model of the North Atlantic Ocean using the Ensemble Kalman Filter. The difference between the three IAU schemes lies on the position of the increment update window. The relevance of each IAU scheme is evaluated through analyses on both thermohaline and dynamical variables. The validation of the assimilation results is performed according to both deterministic and probabilistic metrics against different sources of observations. For deterministic validation, the ensemble mean and the ensemble spread are compared to the observations. For probabilistic validation, the continuous ranked probability score (CRPS) is used to evaluate the ensemble forecast system according to reliability and resolution. The reliability is further decomposed into bias and dispersion by the reduced centred random variable (RCRV) score. The obtained results show that 1) the IAU 50 scheme has the same performance as the IAU 100 scheme 2) the IAU 50/100 schemes outperform the IAU 0 scheme in error covariance propagation for thermohaline variables in relatively stable region, while the IAU 0 scheme outperforms the IAU 50/100 schemes in dynamical variables estimation in dynamically active region 3) in case with sufficient number of observations and good error specification, the impact of IAU schemes is negligible. The differences between the IAU 0 scheme and the IAU 50/100 schemes are mainly due to different model integration time and different instability (density inversion, large vertical velocity, etc.) induced by the increment update. The longer model integration time with the IAU 50/100 schemes, especially the free model integration, on one hand, allows for better re-establishment of the equilibrium model state, on the other hand, smooths the strong gradients in dynamically active region. (C) 2017 Elsevier Ltd. All rights reserved.

Abstract: Three hindcast simulations of the global ocean circulation differing by resolution (1/4 or 1/12 degrees) or parametrization or atmospheric forcing are used to describe the interactions between the large anticyclonic eddies generated by the Somali Current system during the Southwest Monsoon. The present investigation of the Somalian coherent eddy structures allows us to identify the origin and the subsequent development of the cyclones flanked upon the Great Whirl (GW) previously identified by Beal and Donohue (2013) in satellite observations and to establish that similar cyclones are also flanked upon the Southern Gyre (SG). These cyclones are identified as potential actors in mixing water masses within the large eddies and offshore the coast of Somalia. All three simulations bring to light that during the period when the Southwest Monsoon is well established, the SG moves northward along the Somali coast and encounters the GW. The interaction between the SG and the GW is a collision without merging, in a way that has not been described in observations up to now. During the collision the GW is pushed to the east of Socotra Island, sheds several smaller patches of anticyclonic vorticity, and often reforms into the Socotra Eddy, thus proposing a formation mechanism for that eddy. During this process the GW gives up its place to the SG. This process is robust throughout the three simulations.

Abstract: The merger of two identical surface temperature vortices is studied in the surface quasi-geostrophic model. The motivation for this study is the observation of the merger of submesoscale vortices in the ocean. Firstly, the interaction between two point vortices, in the absence or in the presence of an external deformation field, is investigated. The rotation rate of the vortices, their stationary positions and the stability of these positions are determined. Then, a numerical model provides the steady states of two finite-area, constant-temperature, vortices. Such states are less deformed than their counterparts in two-dimensional incompressible flows. Finally, numerical simulations of the nonlinear surface quasi-geostrophic equations are used to investigate the finite-time evolution of initially identical and symmetric, constant temperature vortices. The critical merger distance is obtained and the deformation of the vortices before or after merger is determined. The addition of external deformation is shown to favor or to oppose merger depending on the orientation of the vortex pair with respect to the strain axes. An explanation for this observation is proposed. Conclusions are drawn towards an application of this study to oceanic vortices.

Abstract: Vortex merger is a phenomenon characterizing the whole class of geophysical vortices, from atmospheric storms and large oceanic eddies up to small scale turbulence. Here we focus on the merger of subsurface oceanic anticyclones in an idealized primitive equations model. This study has been motivated by past and recent observations of colliding lens-like anticyclones off of Gibraltar Strait. The critical conditions for merger (critical merger distance and time needed for merger) are determined. We will show that the predictions of classical two-dimensional merger are not verified for subsurface isolated vortices. For instance, critical merger distances will be reduced because of the vortex potential vorticity (PV) structure. The post-merger characteristics of the vortex (radius, extension and PV), are also determined. Merger-related effects, like production of peripheral filaments and small-scale eddies are also investigated and suggest the contribution of merger in both direct and inverse energy cascades.

Abstract: In studies of ocean mixing, it is generally assumed that small-scale turbulent overturns lose 15%-20% of their energy in eroding the background stratification. Accumulating evidence that this energy fraction, or mixing efficiency R-f, significantly varies depending on flow properties challenges this assumption, however. Here, the authors examine the implications of a varying mixing efficiency for ocean energetics and deep-water mass transformation. Combining current parameterizations of internal wave-driven mixing with a recent model expressing R-f as a function of a turbulence intensity parameter Re-b = epsilon(nu)/nu N-2, the ratio of dissipation epsilon(nu) to stratification N-2 and molecular viscosity nu, it is shown that accounting for reduced mixing efficiencies in regions of weak stratification or energetic turbulence (high Re-b) strongly limits the ability of breaking internal waves to supply oceanic potential energy and drive abyssal upwelling. Moving from a fixed R-f = 1/6 to a variable efficiency R-f(Re-b) causes Antarctic Bottom Water upwelling induced by locally dissipating internal tides and lee waves to fall from 9 to 4 Sverdrups (Sv; 1 Sv equivalent to 10(6) m(3) s(-1)) and the corresponding potential energy source to plunge from 97 to 44 GW. When adding the contribution of remotely dissipating internal tides under idealized distributions of energy dissipation, the total rate of Antarctic Bottom Water upwelling is reduced by about a factor of 2, reaching 5-15 Sv, compared to 10-33 Sv for a fixed efficiency. The results suggest that distributed mixing, overflow-related boundary processes, and geothermal heating are more effective in consuming abyssal waters than topographically enhanced mixing by breaking internal waves. These calculations also point to the importance of accurately constraining R-f (Re-b) and including the effect in ocean models.

Abstract: In spite of recent advances, biogeochemical models are still unable to represent the full complexity of natural ecosystems. Their formulations are mainly based on empirical laws involving many parameters. Improving biogeochemical models therefore requires to properly characterize model uncertainties and their consequences. Subsequently, this paper investigates the potential of using random processes to simulate some uncertainties of the 1/4 degrees coupled Physical-Biogeochemical NEMO/PISCES model of the North Atlantic ocean. Starting from a deterministic simulation performed with the original PISCES formulation, we propose a generic method based on AR(1) random processes to generate perturbations with temporal and spatial correlations. These perturbations are introduced into the model formulations to simulate 2 classes of uncertainties: the uncertainties on biogeochemical parameters and the uncertainties induced by unresolved scales in the presence of non-linear processes. Using these stochastic parameterizations, a probabilistic version of PISCES is designed and a 60-member ensemble simulation is performed. With respect to the simulation of chlorophyll, the relevance of the probabilistic configuration and the impacts of these stochastic parameterizations are assessed. In particular, it is shown that the ensemble simulation is in good agreement with the SeaWIFS ocean color data. Using these observations, the statistical consistency (reliability) of the ensemble is evaluated with rank histograms. Finally, the benefits expected from the probabilistic description of uncertainties (model error) are discussed in the context of future ocean color data assimilation. (C) 2015 Elsevier B.V. All rights reserved.

Abstract: This study compares the simulation of subseasonal tropical variability by a set of six state-of-the-art AGCMs in two experiments in aquaplanet configuration: a zonally symmetric experiment, and an experiment with a warm pool centered on the equator. In all six models, the presence of the warm pool generates zonal asymmetries in the simulated mean states in the form of a "Gill-type'' response, made more complex by feedbacks between moisture, convective heating and circulation. Noticeable differences appear from one model to another. Only half the models simulate mean low-level equatorial westerlies over the warm pool area. The presence of the warm pool can also favor the development of large-scale variability consistent with observed Madden-Julian Oscillation (MJO) characteristics, but this happens only in half the models. Our results do not support the idea that the presence of the warm pool and/or of mean low-level equatorial westerlies are sufficient conditions for MJO-like variability to arise in the models. Comparing spectral characteristics of the simulated Convectively Coupled Equatorial Waves (CCEWs) in the aquaplanet experiments and the corresponding coupled atmosphere-ocean (i. e., CMIP) and atmosphere-only (i. e., AMIP) simulations, we also show that there is more consistency for a given model across its configurations, than for a given configuration across the six models. Overall, our results confirm that the simulation of subseasonal variability by given model is significantly influenced by the parameterization of subgrid physical processes (most-likely cloud processes), both directly and through modulation of the mean state.

Abstract: Most data assimilation algorithms require the inverse of the covariance matrix of the observation errors. In practical applications, the cost of computing this inverse matrix with spatially correlated observation errors is prohibitive. Common practices are therefore to subsample or combine the observations so that the errors of the assimilated observations can be considered uncorrelated. As a consequence, a large fraction of the available observational information is not used in practical applications. In this study, a method is developed to account for the correlations of the errors that will be present in the wide-swath sea surface height measurements, for example, the Surface Water and Ocean Topography (SWOT) mission. It basically consists of the transformation of the observation vector so that the inverse of the corresponding covariance matrix can be replaced by a diagonal matrix, thus allowing to genuinely take into account errors that are spatially correlated in physical space. Numerical experiments of ensemble Kalman filter analysis of SWOT-like observations are conducted with three different observation error covariance matrices. Results suggest that the proposed method provides an effective way to account for error correlations in the assimilation of the future SWOT data. The transformation of the observation vector proposed herein yields both a significant reduction of the root-mean-square errors and a good consistency between the filter analysis error statistics and the true error statistics.

Abstract: A global eddy-permitting (1/4 degrees resolution) ocean general circulation model is shown to spontaneously generate intrinsic oceanic variability (IOV) up to multidecadal timescales (T > 20years) under a repeated seasonal atmospheric forcing. In eddy-active regions, the signature of this multidecadal eddy-driven IOV on sea level is substantial, weakly autocorrelated, and is comparable to (and may clearly exceed) the corresponding signature of internal climate variability (ICV) produced by current coupled climate modelswhose laminar ocean components may strongly underestimate IOV. Deriving sea level trends from finite-length time series in eddy-active regions yields uncertainties induced by this multidecadal IOV, which are of the same order of magnitude as those due to ICV. A white noise model is proposed to approximate the low-frequency tail of the IOV spectra and could be used to update ICV estimates from current climate simulations and projections.

Abstract: Uncertainty in ocean analysis methods and deficiencies in the observing system are major obstacles for the reliable reconstruction of the past ocean climate. The variety of existing ocean reanalyses is exploited in a multi-reanalysis ensemble to improve the ocean state estimation and to gauge uncertainty levels. The ensemble-based analysis of signal-to-noise ratio allows the identification of ocean characteristics for which the estimation is robust (such as tropical mixedlayer-depth, upper ocean heat content), and where large uncertainty exists (deep ocean, Southern Ocean, sea ice thickness, salinity), providing guidance for future enhancement of the observing and data assimilation systems.

Abstract: A realistic circulation model of the North Atlantic ocean at 0.25 degrees resolution (NATL025 NEMO configuration) has been adapted to explicitly simulate model uncertainties. This is achieved by introducing stochastic perturbations in the equation of state to represent the effect of unresolved scales on the model dynamics. The main motivation for this work is to develop ensemble data assimilation methods, assimilating altimetric data from past missions Jason-1 and Envisat. The assimilation experiment is designed to provide a description of the uncertainty associated with the Gulf Stream circulation for years 2005/2006, focusing on frontal regions which are predominantly affected by unresolved dynamical scales. An ensemble based on such stochastic perturbations is first produced and evaluated using along-track altimetry observations. Then each ensemble member is updated by a square root algorithm based on the SEEK (singular evolutive extended Kalman) filter (Brasseur and Verron, 2006). These three elements – stochastic parameterization, ensemble simulation and 4-D observation operator – are then used together to perform a 4-D analysis of along-track altimetry over 10-day windows. Finally, the results of this experiment are objectively evaluated using the standard probabilistic approach developed for meteorological applications (Toth et al., 2003; Candille et al., 2007). The results show that the free ensemble – before starting the assimilation process – correctly reproduces the statistical variability over the Gulf Stream area: the system is then pretty reliable but not informative (null probabilistic resolution). Updating the free ensemble with altimetric data leads to a better reliability with an information gain of around 30% (for 10-day forecasts of the SSH variable). Diagnoses on fully independent data (i.e. data that are not assimilated, like temperature and salinity profiles) provide more contrasted results when the free and updated ensembles are compared.

Abstract: With the advent of Argo floats, it now seems feasible to study the interannual variations of upper ocean hydrographic properties of the historically undersampled Southern Ocean. To do so, scattered hydrographic profiles often first need to be mapped. To investigate biases and errors associated both with the limited space-time distribution of the profiles and with the mapping methods, we colocate the mixed-layer depth (MLD) output from a state-of-the-art 1/12 degrees DRAKKAR simulation onto the latitude, longitude, and date of actual in situ profiles from 2005 to 2014. We compare the results obtained after remapping using a nearest neighbor (NN) interpolation and an objective analysis (OA) with different spatiotemporal grid resolutions and decorrelation scales. NN is improved with a coarser resolution. OA performs best with low decorrelation scales, avoiding too strong a smoothing, but returns values over larger areas with large decorrelation scales and low temporal resolution, as more points are available. For all resolutions OA represents better the annual extreme values than NN. Both methods underestimate the seasonal cycle in MLD. MLD biases are lower than 10 m on average but can exceed 250 m locally in winter. We argue that current Argo data should not be mapped to infer decadal trends in MLD, as all methods are unable to reproduce existing trends without creating unrealistic extra ones. We also show that regions of the subtropical Atlantic, Indian, and Pacific Oceans, and the whole ice-covered Southern Ocean, still cannot be mapped even by the best method because of the lack of observational data.

Abstract: An established iceberg module, ICB, is used interactively with the Nucleus for European Modelling of the Ocean (NEMO) ocean model in a new implementation, NEMO-ICB (v1.0). A 30-year hindcast (1976-2005) simulation with an eddy-permitting (0.25 degrees) global configuration of NEMO-ICB is undertaken to evaluate the influence of icebergs on sea ice, hydrography, mixed layer depths (MLDs), and ocean currents, through comparison with a control simulation in which the equivalent iceberg mass flux is applied as coastal runoff, a common forcing in ocean models. In the Southern Hemisphere (SH), drift and melting of icebergs are in balance after around 5 years, whereas the equilibration timescale for the Northern Hemisphere (NH) is 15-20 years. Iceberg drift patterns, and Southern Ocean iceberg mass, compare favourably with available observations. Freshwater forcing due to iceberg melting is most pronounced very locally, in the coastal zone around much of Antarctica, where it often exceeds in magnitude and opposes the negative freshwater fluxes associated with sea ice freezing. However, at most locations in the polar Southern Ocean, the annual-mean freshwater flux due to icebergs, if present, is typically an order of magnitude smaller than the contribution of sea ice melting and precipitation. A notable exception is the southwest Atlantic sector of the Southern Ocean, where iceberg melting reaches around 50% of net precipitation over a large area. Including icebergs in place of coastal runoff, sea ice concentration and thickness are notably decreased at most locations around Antarctica, by up to similar to 20% in the eastern Weddell Sea, with more limited increases, of up to similar to 10% in the Bellingshausen Sea. Antarctic sea ice mass decreases by 2.9 %, overall. As a consequence of changes in net freshwater forcing and sea ice, salinity and temperature distributions are also substantially altered. Surface salinity increases by similar to 0.1 psu around much of Antarctica, due to suppressed coastal runoff, with extensive freshening at depth, extending to the greatest depths in the polar Southern Ocean where discernible effects on both salinity and temperature reach 2500 m in the Weddell Sea by the last pentad of the simulation. Substantial physical and dynamical responses to icebergs, throughout the global ocean, are explained by rapid propagation of density anomalies from high-to-low latitudes. Complementary to the baseline model used here, three prototype modifications to NEMO-ICB are also introduced and discussed.

Abstract: Through two numerical experiments, a 1-D vertical model called NEMO1D was used to investigate physical and numerical turbulent-mixing behaviour. The results show that all the turbulent closures tested (k + l from Blanke and Delecluse, 1993, and two equation models: generic length scale closures from Umlauf and Burchard, 2003) are able to correctly reproduce the classical test of Kato and Phillips (1969) under favourable numerical conditions while some solutions may diverge depending on the degradation of the spatial and time discretization. The performances of turbulence models were then compared with data measured over a 1-year period (mid-2010 to mid-2011) at the PAPA station, located in the North Pacific Ocean. The modelled temperature and salinity were in good agreement with the observations, with a maximum temperature error between 2 and 2 degrees C during the stratified period (June to October). However, the results also depend on the numerical conditions. The vertical RMSE varied, for different turbulent closures, from 0.1 to 0.3 degrees C during the stratified period and from 0.03 to 0.15 degrees C during the homogeneous period. This 1-D configuration at the PAPA station (called PAPA1D) is now available in NEMO as a reference configuration including the input files and atmospheric forcing set described in this paper. Thus, all the results described can be recovered by downloading and launching PAPA1D. The configuration is described on the NEMO site (http://www.nemo-ocean.eu/Using-NEMO/Configurations/C1D_PAPA). This package is a good starting point for further investigation of vertical processes.

Abstract: The marine environment plays an increasingly important role in shaping economies and infrastructures, and touches upon many aspects of our lives, including food supplies, energy resources, national security and recreational activities. Global Ocean Data Assimilation Experiment (GODAE) and GODAE OceanView have provided platforms for international collaboration that significantly contribute to the scientific development and increasing uptake of ocean forecasting products by end users who address societal issues such as those listed above. Many scientific challenges and opportunities remain to be tackled in the ever-changing field of operational oceanography, from the observing system to modelling, data assimilation and product dissemination. This paper provides a brief overview of past achievements in GODAE OceanView, but subsequently concentrates on the future scientific foci of GODAE OceanView and its Task Teams, and provides a vision for the future of ocean forecasting.

Abstract: The anisotropy of eddy variability in the global ocean is examined in geostrophic surface velocities derived from satellite observations and in the horizontal velocities of a 1/12 degrees global ocean model. Eddy anisotropy is of oceanographic interest as it is through anisotropic velocity fluctuations that the eddy and mean-flow fields interact dynamically. This study is timely because improved observational estimates of eddy anisotropy will soon be available with Surface Water and Ocean Topography (SWOT) altimetry data. We find there to be good agreement between the characteristics and distributions of eddy anisotropy from the present satellite observations and model ocean surface. In the model, eddy anisotropy is found to have significant vertical structure and is largest close to the ocean bottom, where the anisotropy aligns with the underlying isobaths. The highly anisotropic bottom signal is almost entirely contained in the barotropic variability. Upper-ocean variability is predominantly baroclinic and the alignment is less sensitive to the underlying bathymetry. These findings offer guidance for introducing a parameterization of eddy feedbacks, based on the eddy kinetic energy and underlying bathymetry, to operate on the barotropic flow and better account for the effects of barotropic Reynolds stresses unresolved in coarse-resolution ocean models. (C) 2015 Elsevier Ltd. All rights reserved.

Abstract: Tangent linear and adjoint models (TAMs) are efficient tools to analyse and to control dynamical systems such as NEMO. They can be involved in a large range of applications such as sensitivity analysis, parameter estimation or the computation of characteristic vectors. A TAM is also required by the 4D-Var algorithm, which is one of the major methods in data assimilation. This paper describes the development and the validation of the tangent linear and adjoint model for the NEMO ocean modelling platform (NEMOTAM). The diagnostic tools that are available alongside NEMOTAM are detailed and discussed, and several applications are also presented.

Abstract: Sea surface height, sea surface temperature, and temperature profiles at depth collected between January and December 2005 are assimilated into a realistic eddy permitting primitive equation model of the North Atlantic Ocean using the Ensemble Kalman Filter. Sixty ensemble members are generated by adding realistic noise to the forcing parameters related to the temperature. The ensemble is diagnosed and validated by comparison between the ensemble spread and the model/ observation difference, as well as by rank histogram before the assimilation experiments. An incremental analysis update scheme is applied in order to reduce spurious oscillations due to the model state correction. The results of the assimilation are assessed according to both deterministic and probabilistic metrics with independent/semiindependent observations. For deterministic validation, the ensemble means, together with the ensemble spreads are compared to the observations, in order to diagnose the ensemble distribution properties in a deterministic way. For probabilistic validation, the continuous ranked probability score (CRPS) is used to evaluate the ensemble forecast system according to reliability and resolution. The reliability is further decomposed into bias and dispersion by the reduced centered random variable (RCRV) score in order to investigate the reliability properties of the ensemble forecast system. The improvement of the assimilation is demonstrated using these validation metrics. Finally, the deterministic validation and the probabilistic validation are analyzed jointly. The consistency and complementarity between both validations are highlighted.

Abstract: The implementation of a regional 1/36 degrees numerical model of a key sub region of the southwestern Pacific Ocean: the Solomon Sea is discussed.This model is two-way embedded into a 1/12 degrees resolution basin-scale model, itself one-way nested in a global 1/12 degrees resolution ocean model.The three main questions discussed in this study concern (i) the bathymetry, (ii) the setting up of adequate forcing functions, especially regarding the wind stress parameterization, and (iii) the strategy used to embed and conned the model configurations together Such a system, exemplified here for the Solomon Sea, represents a prototype of embedded model systems that are considered in operational oceanography.

Abstract: The Southwest Pacific Ocean Circulation and Climate Experiment (SPICE) is an international research program under the auspices of CLIVAR. The key objectives are to understand the Southwest Pacific Ocean circulation and the South Pacific Convergence Zone (SPCZ) dynamics, as well as their influence on regional and basin-scale climate patterns. South Pacific thermocline waters are transported in the westward flowing South Equatorial Current (SEC) toward Australia and Papua-New Guinea. On its way, the SEC encounters the numerous islands and straits of the Southwest Pacific and forms boundary currents and jets that eventually redistribute water to the equator and high latitudes. The transit in the Coral, Solomon, and Tasman Seas is of great importance to the climate system because changes in either the temperature or the amount of water arriving at the equator have the capability to modulate the El Nino-Southern Oscillation, while the southward transports influence the climate and biodiversity in the Tasman Sea. After 7 years of substantial in situ oceanic observational and modeling efforts, our understanding of the region has much improved. We have a refined description of the SPCZ behavior, boundary currents, pathways, and water mass transformation, including the previously undocumented Solomon Sea. The transports are large and vary substantially in a counter-intuitive way, with asymmetries and gating effects that depend on time scales. This paper provides a review of recent advancements and discusses our current knowledge gaps and important emerging research directions. Key Points <list id=“jgrc20950-list-0001” list-type=“bulleted”> <list-item id=“jgrc20950-li-0001”>Southwest Pacific WBCs transport large volumes toward the equator and the pole <list-item id=“jgrc20950-li-0002”>Pathways are complex; water properties tend to erode during the transit <list-item id=“jgrc20950-li-0003”>Variations due to seasons, ENSO and the SPCZ modulate the relative WBC strengths

Abstract: The Solomon Sea is an area of high level of eddy kinetic energy (EKE), and represents a transit area for the low-latitude western boundary currents (LLWBCs) connecting the subtropics to the equatorial Pacific and playing a major role in ENSO dynamics. This study aims at documenting the surface mesoscale activity in the Solomon Sea for the first time. Our analysis is based on the joint analysis of altimetric data and outputs from a 1/12 degrees model simulation. The highest surface EKE is observed in the northern part of the basin and extends southward to the central basin. An eddy tracking algorithm is used to document the characteristics and trajectories of coherent mesoscale vortices. Cyclonic eddies, generated in the south basin, are advected to the north by the LLWBCs before merging with stationary mesoscale structures present in the mean circulation. Anticyclonic eddies are less numerous. They are generated in the southeastern basin, propagate westward, reach the LLWBCs, and dissipate. The seasonal and interannual modulations of the mesoscale activity are well marked. At seasonal time scale, maximum (minimum) activity is in May-June (September). At interannual time scale, the mesoscale activity is particularly enhanced during La Nina conditions. If instabilities of the regional circulations seem to explain the generation of mesoscale features, the modulation of the mesoscale activity seems to be rather related with the intrusion at Solomon Strait of the surface South Equatorial Current, rather than to the LLWBCs, by modulating the horizontal and vertical shears suitable for instabilities. Key Points <list id=“jgrc20632-list-0001” list-type=“bulleted”> <list-item id=“jgrc20632-li-0001”>A first analysis of the surface mesoscale activity in the Solomon Sea <list-item id=“jgrc20632-li-0002”>Mesoscale is related with the SEC inflow at Solomon Strait rather than to LLWBC <list-item id=“jgrc20632-li-0003”>Maximum activity is in May-June, it is enhanced during La Nina conditions

Abstract: In this paper, we first evaluate the ability of the European Centre for Medium Range Forecast operational analysis and the ERA-Interim reanalysis to capture the surface wind signature of tropical cyclones (TCs). In those products, the error on the TC position is typically similar to 150 km, cyclones are too big (similar to 250 km in ERA-Interim and >100 km in the operational analysis against similar to 50 km in observations) and the maximum wind speed is on average underestimated by 15-27 m.s(-1) for strong TCs. These biases are generally reduced with the increase of horizontal resolution in the operational analysis, but remain significant at T1279 (similar to 16 km). We then assess the TCs oceanic temperature signature in two global eddy-permitting ocean reanalyses (GLORYS1 and GLORYS2) forced by the above atmospheric products. The resulting cold wake is on average underestimated by similar to 50% in the two oceanic reanalyses. This bias is largely linked to the underestimated TCs strength in the surface forcing, and the resulting underestimated vertical mixing. The overestimated TC radius also tends to overemphasize the Ekman pumping response to the cyclone. Underestimating vertical mixing without underestimating Ekman pumping results in the absence of the observed subsurface warming away from the TC tracks in the two reanalyses. Data assimilation only marginally contributes to reducing these errors, partly because cyclone signatures are not well resolved by the ocean observing system. Based on these results, we propose some assimilation and forcing strategies in order to improve the restitution of TC signatures in oceanic reanalyses. Crown Copyright (C) 2013 Published by Elsevier Ltd. All rights reserved.

Abstract: From September 2002 to October 2010, the Envisat radar altimeter surveyed Greenland and Antarctica ice sheets on a 35 day repeat orbit, providing a unique data set for ice sheet mass balance studies. Up to 85 repeat cycles are available and the whole Envisat data set may be along-track processed in order to provide height variability and trend with a good spatial resolution for the objectives of ice sheet survey. Soon, a joint Centre National d'Etudes Spatiales/Indian Space Research Organisation mission, SARAL (Satellite with Argos and AltiKa), with the AltiKa payload on board, will be launched on exactly the same orbit (less than 1 km of the nomimal orbit in the across-track direction). This will allow an extension of previous European Remote Sensing (ERS) satellite, ERS-1 and ERS-2, and Envisat missions of the European Space Agency (ESA), in particular from the point of view of ice altimetry. However, AltiKa operates in the Ka band (36.8 GHz), a higher frequency than the classical Ku band (13.6 GHz), leading to important modifications and potential improvements in the interactions between radar wave and snow-pack. In this paper, a synthesis is presented of all available information relevant to ice altimetry scientific purposes as derived from the Envisat mission: mean and temporal derivatives of the height -but also of the backscatter and of the two waveform parameters -snow-pack change corrections, across-track surface slope at 1 km scale, etc. The spatial and temporal variability of ice sheet surface elevation is investigated with the help of the high-resolution Envisat along-track observations. We show that at least 50 repeat cycles are needed to reach the required accuracy for the elevation trend. It is thus advocated as potentially highly beneficial for SARAL/AltiKa as a follow-on mission. Moreover, the novel characteristics of SARAL/AltiKa are promising in improving our understanding of snow penetration impact.

Abstract: The meridional transport of salt is computed in a global eddy-resolving numerical model (1/12 degrees resolution) in order to improve our understanding of the ocean salinity budget. A methodology is proposed that allows a global analysis of the salinity balance in relation to surface water fluxes, without defining a “freshwater anomaly” based on an arbitrary reference salinity. The method consists of a decomposition of the meridional transport into (i) the transport by the time-longitude-depth mean velocity, (ii) time-mean velocity recirculations and (iii) transient eddy perturbations. Water is added (rainfall and rivers) or removed (evaporation) at the ocean surface at different latitudes, which creates convergences and divergences of mass transport with maximum and minimum values close to +/- 1 Sv. The resulting meridional velocity effects a net transport of salt at each latitude (+/- 30 Sv PSU), which is balanced by the time-mean recirculations and by the net effect of eddy salinity-velocity correlations. This balance ensures that the total meridional transport of salt is close to zero, a necessary condition for maintaining a quasi-stationary salinity distribution. Our model confirms that the eddy salt transport cannot be neglected: it is comparable to the transport by the time-mean recirculation (up to 15 Sv PSU) at the poleward and equatorial boundaries of the subtropical gyres. Two different mechanisms are found: eddy contributions are localized in intense currents such as the Kuroshio at the poleward boundary of the subtropical gyres, while they are distributed across the basins at the equatorward boundaries. Closer to the Equator, salinity-velocity correlations are mainly due to the seasonal cycle and large-scale perturbations such as tropical instability waves.