Laurent Bertino

Job Position: 
Research Leader
Research Group: 
E-mail: 
Phone: 
+47 934 56 215
Laurent Bertino Staff Picture

Research interests

My aim is to improve the stochastic framework for performing data assimilation, other interests include numerical ocean modelling (especially in the hybrid coordinates ocean model HYCOM) and statistics applied to environmental problems. My PhD has borrowed the method of "Gaussian anamorphosis" from the weaponry of geostatistics for further applications of sequential data assimilation into coupled physical-ecosystem models.

2001: PhD in geostatistics from the Ecole des Mines de Paris.

2002: Post-doc at NERSC

2003: Group leader for the Modeling and Data Assimilation group.

2004: Co-director of the Mohn-Sverdrup Center.

2010: Research Director at NERSC.

CV

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cv-laurent_bertino_2p_2018.pdf90.59 KB

Project leader of the following projects

  1. ARC MFC: Copernicus Arctic Marine Services
  2. SWARP: Ships and Waves Reaching Polar Regions
  3. ES-PhD: Ensemble Smoother - Patrick Raanes

NERSC Principal Investigator of the following projects

  1. EVA: Earth system modelling of climate Variations in the Anthropocene
  2. SANGOMA: Stochastic Assimilation for the Next Generation Ocean Model Applications
  3. SeaFINE: Eddy-resolving South China Sea reanalysis
  4. CarboChange: Changes in carbon uptake and emissions by oceans in a changing climate

Project deputy leader of the following projects

  1. EmblA: Ensemble-based data assimilation for environmental monitoring and prediction
  2. OC-CCI: The ESA Ocean Colour Climate Change Initiative
  3. MyOcean: Development and Pre-operational validation of GMES Marine Core Services
  4. eVITA-EnKF: Forecasting non-linear systems using the ensemble Kalman filter and related methods
  5. MERSEA: Marine Environment and Security for the European Area

Publications

My Publications in CRIStin

Peer Review Publications and Books

97 total publications.

2019

  1. Smith GC, Allard R, Babin M, Bertino L, Chevallier M, Corlett G, et al. Polar Ocean Observations: A critical gap in the observing system and its effect on environmental predictions from hours to a season. Frontiers in Marine Science. 2019;
  2. Shah A. Stochastic data assimilation of observations with a detection limit. 2019.
  3. Bocquet M, Brajard J, Carrassi A, Bertino L. Data assimilation as a learning tool to infer ordinary differential equation representations of dynamical models. Nonlinear processes in geophysics. 2019;26(3).
  4. Xie J, Raj RP, Bertino L, Samuelsen A, Wakamatsu T. Evaluation of Arctic Ocean surface salinities from the Soil Moisture and Ocean Salinity (SMOS) mission against a regional reanalysis and in situ data. Ocean Science. 2019;15(5).
  5. Blyverket J, Hamer PD, Bertino L, Albergel C, Fairbairn D, Lahoz WA. An Evaluation of the EnKF vs. EnOI and the Assimilation of SMAP, SMOS and ESA CCI Soil Moisture Data over the Contiguous US. Remote Sensing. 2019;11(5).
  6. Moore AM, Martin MJ, Santha A, Arango HG, Balmaseda M, Bertino L, et al. Synthesis of ocean observations using data assimilation for operational, real-time and reanalysis systems: a more complete picture of the state of the ocean. Frontiers in Marine Science. 2019;6.
  7. Ali A, Christensen KH, Breivik Ø, Bertino L, Malila MP, Raj RP, et al. A comparison of Langmuir turbulence parameterizations and key wave effects in a numerical model of the North Atlantic and Arctic Oceans. Ocean Modelling. 2019;137.
  8. Bertino L, Traon P-YL. From Observation to Information and Users: The Copernicus Marine Service Perspective. Frontiers in Marine Science. 2019;
  9. Fujii Y, Remy E, Hao Z, Oke P, Halliwell G, Gasparin F, et al. Observing System Evaluation Based on Ocean Data Assimilation and Prediction Systems: On-Going Challenges and a Future Vision for Designing and Supporting Ocean Observational Networks. Frontiers in Marine Science. 2019;

2018

  1. Aalstad K, Westermann S, Schuler T, Boike J, Bertino L. Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites. The Cryosphere. 2018;12(1).
  2. Raj RP, Nilsen JEØ, Johannessen JA, Furevik T, Andersen OB, Bertino L. Quantifying Atlantic Water transport to the Nordic Seas by remote sensing. Remote Sensing of Environment. 2018;216.
  3. Nakanowatari T, Inoue J, Sato K, Bertino L, Xie J, Matsueda M, et al. Medium-range predictability of early summer sea ice thickness distribution in the East Siberian Sea based on the TOPAZ4 ice–ocean data assimilation system. The Cryosphere. 2018;12(6).
  4. Ardhuin F, Aksenov Y, Benetazzo A, Bertino L, Brandt P, Caubet E, et al. Measuring currents, ice drift, and waves from space: the Sea Surface KInematics Multiscale monitoring (SKIM) concept. Ocean Science. 2018;14(3).
  5. Carrassi A, Bocquet M, Bertino L, Evensen G. Data assimilation in the geosciences - An overview of methods, issues and perspectives. WIREs Climate Change. 2018;
  6. Yu LQ, Fennel K, Bertino L, Gharamti ME, Thompson KR. Insights on multivariate updates of physical and biogeochemical ocean variables using an Ensemble Kalman Filter and an idealized model of upwelling. Ocean Modelling. 2018;126.
  7. Balibrea-Iniesta F, Xie J, Garcia-Garrido V, Bertino L, Mancho AM, Wiggins S. Lagrangian transport across the upper Arctic waters in the Canadian Basin. Quarterly Journal of the Royal Meteorological Society. 2018;145(718).
  8. Rabatel M, Rampal P, Carrassi A, Bertino L, Jones CKRT. Impact of rheology on probabilistic forecasts of sea ice trajectories: Application for search and rescue operations in the Arctic. The Cryosphere. 2018;12(3).
  9. Chatterjee S, Raj RP, Bertino L, Skagseth Ø, Ravichandran M, Johannessen OM. Role of Greenland sea gyre circulation on Atlantic water temperature variability in the Fram Strait. Geophysical Research Letters. 2018;45(16).
  10. Shah A, Gharamti ME, Bertino L. Assimilation of semi-qualitative observations with a stochasticensemble Kalman filter. Quarterly Journal of the Royal Meteorological Society. 2018;144(715).
  11. Xie J, Counillon F, Bertino L. Impact of assimilating a merged sea-ice thickness from CryoSat-2 and SMOS in the Arctic reanalysis. The Cryosphere. 2018;12(11).

Other Publications

2014

  1. Renkl C, Counillon F, Bertino L. Validation of the 20-year TOPAZ4 Reanalysis. 2014.

2013

  1. Finck N, Counillon F, Bertino L, Bouillon S, Rampal P. Validation of sea ice quantities of TOPAZ for the period 1990-2010. 2013.

2012

  1. Simon E, Samuelsen A, Bertino L. Report on error quantified hindcast with data assimilation (GreenSeas). 2012.
  2. Demchev D, Aleksandrov V, Volkov V, Wehde H, Zakhvatkina N, Bertino L, et al. Quality Information Document MyOcean V1 System WP05– ARC-MFC Reanalysis [Internet]. 2012. Available from: ftp://ftp.nersc.no/pub/Laurent/MyOcean/MYO_QUID-ARC-MFC-RA_NERSC_TechRep_final.pdf

2011

  1. Bertino L, Evensen G, Sakov P, Counillon F, Simon E, Bojarova J, et al. Forecasting non-linear systems with the Ensemble Kalman Filter and related data assimilation methods (eVITA-EnKF). 2011.
  2. Bertino L. Challenges and capabilities of data assimilation. Nansen-Tutu Centre Scientific Opening Symposium. 2011;
  3. Keghouche I, Bertino L, Johannessen OM. Ocean weather and ecosystem. 2011.
  4. Bertino L, Sakova I, Samuelsen A. Ocean weather and ecosystem, progress report. 2011.

2010

  1. Counillon F, Bentsen M, Bertino L. Implementing the EnKF into NorESM. 2010.
  2. Simon E, Bertino L. Joint state-parameter estimation in a 3-D coupled physical-ecosystem model of the North Atlantic: assimilation of SeaWiFS data with a non-Gaussian extension of an ESRF [Internet]. ESA Living Planet Symposium. 2010;Available from: http://www.esa.int/SPECIALS/Living_Planet_Symposium_2010/index.html
  3. Sagen H, Sandven S, Skarsoulis E, Worcester PF, Beszczynska-Möller A, Bertino L, et al. The fram Strait tomography system for ocean model validation, assimilation, and inversion. IPY - Oslo Science Conference. 2010;
  4. Haugen SA, Sagen H, Sandven S, Bertino L, Sakov P, Counillon F. Use of acoustic Travel Times for ocean model validation, and assimilation. 2010;
  5. Bertino L. Assimilation of ice and ocean observations for the operational forecast and reanalysis with TOPAZ. 2010;
  6. Nondal G. A study of the high and mid latitude biogeochemistry in the Atlantic Ocean: The influence of surface processes. 2010.
  7. Seiler A. Reservoir structural model updating using the Ensemble Kalman Filter. 2010.
  8. Keghouche I. Modeling the dynamics and drift of icebergs in the Barents Sea. 2010.
  9. Backeberg B. Modelling the mesoscale variability in the greater Agulhas Current System using a Hybrid Coordinate Ocean Model. 2010.
  10. Bertino L. TOPAZ: the MyOcean Arctic forecasting system [Internet]. World Climate Research Programme workshop on seasonal to multi-decadal predictability of polar climate. 2010;Available from: http://www.atmosp.physics.utoronto.ca/SPARC/PolarWorkshop/main.html
  11. Bertino L, Counillon F. Ocean
 assimilation 
and
 forecasting [Internet]. World Climate Research Programme workshop on seasonal to multi-decadal predictability of polar climate. 2010;Available from: http://www.atmosp.physics.utoronto.ca/SPARC/PolarWorkshop/main.html
  12. Milutinovic S, Bertino L. Assessment and Propagation of Uncertainties in Input Terms through the Vertically Generalized Productivity Model. COCOS Workshop on Combining Water Column Data with Sediment Trap and Satellite Observations for Improved Marine Carbon Export Estimates. 2010;
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