Publications

Peer reviewed papers

  1. Brankart, J.-M. and Brasseur, P. (1996). Optimal analysis of in situ data in the Western Mediterranean using statistics and cross-validation. Journal of Atmospheric and Oceanic Technology, 16(2), 477-491. [doi]
  2. Brasseur, P., Beckers, J.-M., Brankart, J.-M., and Schoenauen, R. (1996). Seasonal temperature and salinity fields in the Mediterranean Sea: Climatological analyses of an historical data set. Deep-Sea Research, 43(2),159-192. [doi]
  3. Uu, D.-V. and Brankart, J.-M. (1997). Seasonal variation of temperature and salinity fields and water masses in the Bieng Dong (South China) Sea. Mathematical and Computer Modelling, 26(12), 97-113. [doi]
  4. Brankart, J.-M. and Brasseur, P. (1998). The general circulation in the Mediterranean Sea: a climatological approach. Journal of Marine Systems, 18, 41-70. [doi]
  5. Rixen, M., Beckers, J.-M., Brankart, J.-M., and Brasseur, P. (2000). A numerically efficient data analysis method with error map generation. Ocean Modelling, 2, 45-60. [doi]
  6. Brankart, J.-M. and Pinardi, N. (2001). Abrupt cooling of the Mediterranean Levantine Intermediate Water at the beginning of the 1980s: observational evidence and model simulation. Journal of Physical Oceanography, 31(8), 2307-2320. [doi]
  7. Carmillet, V., Brankart, J.-M., Brasseur, P., Drange, H., Evensen, G., and Verron, J. (2001). A singular evolutive extended Kalman filter to assimilate ocean color data in a coupled physical-biochemical model of the North Atlantic. Ocean Modelling, 3,167-192. [doi]
  8. Beckers J.M., Rixen M., Brasseur P., Brankart J.M., Elmoussaoui A., Crépon M., Herbaut C., Martel F., Van den Berghe F., Mortier L., Lascaratos A., Drakopoulos P., Korres G., Nittis K., Pinardi N., Masetti E., Castellari S., Carini P., Tintore J., Alvarez A., Monserrat S., Parilla D., Vautard R., Speich S. (2002). Model intercomparison in the Mediterranean: MEDMEX simulations of the seasonal cycle. Journal of Marine Systems, 33-34, 215-251. [doi]
  9. Brankart, J.-M., Testut, C.-E., Brasseur, P., and Verron, J. (2003). Implementation of a multivariate data assimilation scheme for isopycnic coordinate ocean models: Application to a 1993-96 hindcast of the North Atlantic Ocean circulation. Journal of Geophysical Research, 108(C3), 19(1-20). [doi]
  10. Brusdal, K., Brankart, J.-M., Halberstadt, G., Evensen, G., Brasseur, P., van Leeuwen, P.-J., Dombrowsky, E., and Verron, J. (2003). A demonstration of ensemble-based assimilation methods with a layered OGCM from the perspective of operational ocean forecasting systems. Journal of Marine Systems, 40-41, 253-289. [doi]
  11. Parent, L., Testut, C.-E., Brankart, J.-M., Verron, J., Brasseur, P., and Gourdeau, L. (2003). Comparative assimilation of Topex/Poseidon and ERS altimeter data and of TAO temperature data in the Tropical Pacific Ocean during 1994-1998, and the mean sea-surface height issue. Journal of Marine Systems, 40-41, 381-401. [doi]
  12. Testut, C.-E., Brasseur, P., Brankart, J.-M., and Verron, J. (2003). Assimilation of sea-surface temperature and altimetric observations during 1992-1993 into an eddy permitting primitive equation model of the North Atlantic Ocean. Journal of Marine Systems, 40-41, 291-316. [doi]
  13. Birol, F., Brankart, J.M., Castruccio, F., Brasseur, P. and Verron, J. (2004). Impact of ocean mean dynamic topography on satellite data assimilation. Marine Geodesy, 27, 59-78. [doi]
  14. Birol, F., Brankart, J.M., Lemoine, J.M., Brasseur, P. and Verron, J. (2005). Assimilation of satellite altimetry referenced to the new GRACE geoid estimate. Geophysical Research Letters, 32(6), doi10.1029/2004GL021329. [doi]
  15. Brasseur, P., Bahurel, P., Bertino, L., Birol, F., Brankart, J.-M., Ferry, N., Losa, S., Remy, E., Schröter, J., Skachko, S., Testut, C.-E., Tranchant, B., van Leeuwen, P.J., and Verron, J. (2005). Data assimilation for marine monitoring and prediction : the MERCATOR operational assimilation systems and the MERSEA developments. Quarterly Journal of the Royal Meteorological Society, 131, 3561-3582. [doi]
  16. Castruccio F., Verron, J., Gourdeau, L., Brankart, J.M., and Brasseur, P. (2006). On the role of the GRACE mission in the joint assimilation of altimetric and TAO data in a Tropical Pacific Ocean model. Geophysical Research Letters, 33, L14616. [doi]
  17. Ourmières, Y., Brankart, J.M., Berline, L., Brasseur, P., and Verron, J. (2006). Incremental Analysis Update implementation into a sequential data assimilation system. Journal of Atmospheric and Oceanic technology, 23(12), 1729-1744. [doi]
  18. Berline L., Brankart, J.M., Brasseur, P., Ourmières, Y., et Verron, J. (2007). Improving the physics of a coupled physical-biogeochemical model of the North Atlantic through data assimilation: impact on the ecosystem, Journal of Marine Systems, 64(1-4), 153-172. [doi]
  19. Raick, C., Alvera-Azcarate, A., Barth, A., Brankart, J.M., Soetart, K. and Grégoire, M. (2007). Application of a SEEK filter to a 1D biogeochemical model of the Ligurian Sea: twin experiments and real in situ data assimilation, Journal of Marine Systems, 65(1-4), 561-583. [doi]
  20. Rozier, D., Birol, F., Cosme, E., Brasseur, P., Brankart, J.M. and Verron, J. (2007). A reduced order Kalman filter for data assimilation in physical oceanography. SIAM Rev., 49(3), 449-465. [doi]
  21. Broquet, G., Brasseur, P., Rozier, D., Brankart, J.M. and Verron, J. (2008). Estimation of model errors generated by atmospheric forcings for ocean data assimilation: experiments in a regional model of the Bay of Biscay. Ocean dynamics, 58(1), 1-17. [doi]
  22. Castruccio, F., Verron, J., Gourdeau, L., Brankart, J.M. and Brasseur, P. (2008). Joint altimetric and in-situ data assimilation using the GRACE mean dynamic topography: a 1993-1998 hindcast experiment in the Tropical Pacific Ocean. Ocean dynamics, 58(1), 43-63. [doi]
  23. Ourmières, Y., Brasseur, P., Levy, M., Brankart, J.M. and Verron, J. (2009). On the key role of nutrient data to constrain a coupled physicalbiogeochemical assimilative model of the North Atlantic Ocean. Journal of Marine Systems, 75(1-2), 100-115. [doi]
  24. Lauvernet C., Brankart J.M., Castruccio F., Broquet G., Brasseur P., Verron J. (2009). A truncated Gaussian filter for data assimilation with inequality constraints: application to the hydrostatic stability condition in ocean models. Ocean Modelling, 27, 1-17. [doi]
  25. Skachko S., Brankart J.-M., Castruccio F., Brasseur P., Verron J. (2009). Improved turbulent air-sea flux bulk parameters for the control of the ocean mixed layer: a sequential data assimilation approach. Journal of Atmospheric and Oceanic Technologies. 26(3), 538-555. [doi]
  26. Ubelmann C., Verron J., Brankart J.M., Cosme E., Brasseur P. (2009). Impact of upcoming altimetric missions on the prediction of the three-dimensional circulation in the tropical Atlantic ocean. Journal of Operational Oceanography, 2(1), 3-14. [online]
  27. Brankart J.M., Ubelmann C., Testut C.E., Cosme E., Brasseur P. and Verron J. (2009). Efficient parameterization of the observation error covariance matrix for square root or ensemble Kalman filters: application to ocean altimetry. Monthly Weather Review, 137(6), 1908-1927. [doi]
  28. Skandrani C., Brankart J.-M., Ferry N., Verron J., Brasseur P. and Barnier B. (2009). Controlling atmospheric forcing parameters of global ocean models: sequential assimilation of sea surface Mercator-Ocean reanalysis data. Ocean Science, 5, 403-419. [online]
  29. Béal D., Brasseur P., Brankart J.-M., Ourmières Y. and Verron J. (2010). Characterization of mixing errors in a coupled physical biogeochemical model of the North Atlantic: implications for nonlinear estimation using Gaussian anamorphosis. Ocean Science, 6, 247-262. [online]
  30. Cosme E., Brankart J.-M., Verron J., Brasseur P. and Krysta M. (2010). Implementation of a reduced-rank, square-root smoother for high resolution ocean data assimilation. Ocean Modelling, 33, 87-100. [doi]
  31. Brankart J.-M., Cosme E., Testut C.-E., Brasseur P. and Verron J. (2010). Efficient adaptive error parameterizations for square root or ensemble Kalman filters: application to the control of ocean mesoscale signals. Monthly Weather Review, 138(3), 932-950. [doi]
  32. Brankart J.-M., Cosme E., Testut C.-E., Brasseur P. and Verron J. (2011). Efficient local error parameterizations for square root or ensemble Kalman filters: application to a basin-scale ocean turbulent flow. Monthly Weather Review, 139(2), 474-493. [doi]
  33. Srinivasan A., Chassignet E.P., Bertino L., Brankart J.-M., Brasseur P., Chin M., Counillon F., Cummings J.A., Mariano A.J., Smedstad O.M. and Thacker W.C. (2011). A comparison of sequential assimilation schemes for ocean prediction with the HYbrid Coordinate Ocean Model (HYCOM): Twin Experiments with static forecast error covariances. Ocean Modeling, 37(3-4), 85-111. [doi]
  34. Doron M., Brasseur P. and Brankart J.-M. (2011). Stochastic estimation of biogeochemical parameters of a 3D ocean coupled physical-biogeochemical model: twin experiments. Journal of Marine Systems, 87, 194-207. [doi]
  35. Titaud O., Brankart J.-M., and Verron J. (2011). On the use of Finite-Time Lyapunov Exponents and Vectors for direct assimilation of images in ocean models. Tellus A, 63(5), 1038-1051. [doi]
  36. Melet A., Verron J. and Brankart J.-M. (2012). Potential outcomes of glider data assimilation in the Solomon sea: control of the water mass properties and parameter estimation. Journal of Marine Systems, 94, 232-246. [doi]
  37. Brankart J.-M., Testut C.-E., Béal D., Doron M., Fontana C., Meinvielle M., Brasseur P. and Verron J. (2012). Towards an improved description of ocean uncertainties: effect of local anamorphic transformations on spatial correlations. Ocean Science, 8, 121-142. [doi]
  38. Juza M., Penduff T., Brankart J.-M. and Barnier B. (2012). Estimating the distortion of mixed layer porperty distributions by the ARGO sampling. Journal of Operational Oceanography, 5(1), 45-58. [online]
  39. Ubelmann C., Verron J., Brankart J.-M., Brasseur P., and Cosme E. (2012). Assimilating altimetric data from multi-satellite scenarios to control Atlantic tropical instability waves: an observing system simulation experiments study. Ocean Dynamics, 62(6), 867-880. [doi]
  40. Troupin C., Barth A., Sirjacobs D., Ouberdous M., Brankart J.-M., Brasseur P., Rixen M., Alvera-Azcárate A., Belounis M., Capet A., Lenartz F., Toussaint M.-E., and Beckers J.-M. (2012). Generation of analysis and consistent error fields using the Data Interpolating Variational Analysis (Diva). Ocean Modelling, 52-53, 90-101. [doi]
  41. Freychet N., Cosme E., Brasseur P., Brankart J.-M. and Kpemlie E. (2012). Obstacles and benefits of the implementation of a reduced rank smoother with a high resolution model of the Atlantic ocean. Ocean Science, 8, 797-811. [doi]
  42. Duchez A., Verron J., Brankart J.-M., Ourmières Y. and Fraunié P. (2012). Monitoring the Northern Current in the Gulf of Lions with an observing system simulation experiment. Scientia Marina, 76(3), 441-453. [doi]
  43. Fontana C., Brasseur P., and Brankart J.-M. (2013). Toward a multivariate reanalysis of the North Atlantic ocean biogeochemistry during 1998-2006 based on the assimilation of SeaWiFS chlorophyll data. Ocean Science, 9, 37-56. [online]
  44. Doron M., Brasseur, P., Brankart J.-M., Losa S. N., and Melet A. (2013). Stochastic estimation of biogeochemical parameters from Globcolour ocean colour satellite data in a North Atlantic 3D ocean coupled physical-biogeochemical model. Journal of Marine Systems, 117-118, 81-95. [doi]
  45. Brankart J.-M. (2013). Impact of uncertainties in the horizontal density gradient upon low resolution global ocean modelling. Ocean Modelling, 66, 64-76. [doi]
  46. Gaultier L., Verron J., Brankart J.-M., Titaud O., and Brasseur P. (2013). On the inversion of submesoscale tracer fields to estimate the surface ocean circulation. Journal of Marine Systems, 126, 33-42. [doi]
  47. Meinvielle M., Brankart J.-M., Brasseur P., Barnier B., Dussin R., and Verron J. (2013). Optimal adjustment of the atmospheric forcing parameters of ocean models using sea surface temperature data assimilation. Ocean Science, 9, 867-883. [online]
  48. Gaultier L., Djath B., Verron J., Brankart J.-M., Brasseur P. and Melet A. (2014). Inversion of submesoscale patterns from a high-resolution Solomon Sea model: feasibility assessment. Journal of Geophysical Research, 119(7), 4520-4541. [doi]
  49. Brankart J.-M., Candille G., Garnier F., Calone C., Melet A., Bouttier P.-A., Brasseur P. and Verron, J. (2015). A generic approach to explicit simulation of uncertainty in the NEMO ocean model. Geoscientific Model Development, 8, 1285-1297. [doi]
  50. Candille G., Brankart J.-M., and Brasseur P. (2015). Assessment of an ensemble system that assimilates Jason-1/Envisat altimeter data in a probabilistic model of the North Atlantic ocean circulation. Ocean Science, 11, 425-438. [doi]
  51. Yan Y., Barth A., Beckers J.M., Candille G., Brankart J.M., Brasseur P. (2015). Ensemble assimilation of ARGO temperature profile, sea surface temperature and altimetric satellite data into an eddy permitting primitive equation model of the North Atlantic Ocean. Journal of Geophysical Research 120, 5134-5157. [doi]
  52. Garnier F., Brankart J.-M., Brasseur P. and Cosme E. (2016). Stochastic parameterizations of biogeochemical uncertainties in a 1/4° NEMO/PISCES model for probabilistic comparisons with ocean color data. Journal of Marine Systems, 155, 59-72. [doi]
  53. Abdelnur Ruggiero G., Cosme E., Brankart J.-M., Le Sommer J. and Ubelmann C. (2016). An efficient way to account for observation error correlations in the assimilation of data from the future SWOT high-resolution altimeter mission. Journal of Atmospheric and Oceanic Technology, 33, 2755-2768. [doi]
  54. Bessières L., Leroux S., Brankart J.-M., Molines J.-M., Moine M.-P., Bouttier P.-A., Penduff T., Terray L., Barnier B. and Sérazin G. (2017). Development of a probabilistic ocean modelling system based on NEMO 3.5: application at eddying resolution. Geoscientific Model Development, 10(3), 1091-1106. [doi]
  55. Durán Moro M., Brankart J.-M., Brasseur P. and Verron J. (2017). Exploring image data assimilation in the prospect of high-resolution satellite oceanic observations. Ocean Dynamics, 87(7), 875-895. [doi]
  56. Yan Y., Barth A., Beckers J.-M., Brankart J.-M., Brasseur P. and Candille G. (2017). Comparison of different incremental analysis update schemes in a realistic assimilation system with Ensemble Kalman Filter. Ocean Modelling, 115, 27-41. [doi]
  57. Leroux, S., T. Penduff, L. Bessières, J.-M. Molines, J.-M. Brankart, G. Sérazin, B. Barnier, and L. Terray (2018). Intrinsic and Atmospherically Forced Variability of the AMOC: Insights from a Large-Ensemble Ocean Hindcast. J. Climate, 31, 1183-1203. [doi]
  58. Tissier, A.-S., Brankart, J.-M., Testut, C.-E., Ruggiero, G., Cosme, E., and Brasseur, P. (2019). A multiscale ocean data assimilation approach combining spatial and spectral localisation, Ocean Science, 15, 443-457. [doi]
  59. Prieur C., Viry L., Blayo E., and Brankart J. M. (2019). A global sensitivity analysis approach for marine biogeochemical modeling, Ocean Modelling, 139, 101402. [doi]
  60. Metref S., Cosme E., Le Sommer J., Poel N., Brankart J.-M., Verron J. and Gomez Navarro L. (2019). Reduction of Spatially Structured Errors in Wide-Swath Altimetric Satellite Data Using Data Assimilation. Remote Sensing, 11(11), 1336. [doi]
  61. Zanna L., Brankart J.-M., Huber M., Leroux S., Penduff T. and Williams P. D. (2019), Uncertainty and Scale Interactions in Ocean Ensembles: From Seasonal Forecasts to Multi-Decadal Climate Predictions. Q J R Meteorol Soc. 145(1), 160-175. [doi]
  62. Germineaud, C., J.-M. Brankart, and P. Brasseur (2019). An Ensemble-Based Probabilistic Score Approach to Compare Observation Scenarios: An Application to Biogeochemical-Argo Deployments. J. Atmos. Oceanic Technol., 36, 2307-2326. [doi]
  63. Brankart J.-M. (2019). Implicitly Localized MCMC Sampler to Cope With Non-local/Non-linear Data Constraints in Large-Size Inverse Problems. Front. Appl. Math. Stat. 5:58. [doi]
  64. Metref, S., Cosme E., Le Guillou F., Le Sommer J., Brankart J.-M. and Verron J. (2020). Wide-Swath Altimetric Satellite Data Assimilation With Correlated-Error Reduction. Front. Mar. Sci. 6:822. [doi]
  65. Santana-Falcon Y., Brankart J.M. and Brasseur P. (2020). Towards a methodology for routinely assimilating colour data into a NEMO/PISCES ensemble simulation, Ocean Science, 16, 1297--1315. [doi]
  66. Leroux S., Brankart J.-M., Albert A., Brodeau L., Molines J.-M., Jamet Q., Le Sommer J., Penduff T., and Brasseur P. (2022). Ensemble quantification of short-term predictability of the ocean dynamics at a kilometric-scale resolution: a Western Mediterranean test case. Ocean Sci., 18, 1619-1644. [doi]
  67. Popov M., Brankart J.-M., Capet A., Cosme E., Brasseur P. (2023). Ensemble analysis and forecast of ecosystem indicators in the North Atlantic using ocean colour observations and prior statistics from a stochastic NEMO/PISCES simulator. Ocean Sci., 20, 155-180, [doi]