Laurent Bertino

Job Position: 
Group 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

84 total publications.

2018

  1. 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.
  2. Xie J, Bertino L, Cardellach E, Semmling M, Wickert J. An OSSE evaluation of the GNSS-R altimetry data for the GEROS-ISS mission as a complement to the existing observational networks. Remote Sensing of Environment. 2018;209.
  3. 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.
  4. 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;In Press, Corrected Proof.
  5. 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. 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.
  7. Carrassi A, Bocquet M, Bertino L, Evensen G. Data assimilation in the geosciences - An overview of methods, issues and perspectives. WIREs Climate Change. 2018;In press.

2017

  1. Buehner M, Bertino L, Caya A, Heimbach P, Smith G. Sea ice data assimilation. 2017.
  2. Carrieres T, Caya A, Posey P, Metzger JE, Bertino L, Melsom A, et al. Automated Sea Ice Prediction Systems [Internet]. 2017. Available from: http://www.cambridge.org/gb/academic/subjects/earth-and-environmental-science/oceanography-and-marine-science/sea-ice-analysis-and-forecasting-towards-increased-reliance-automated-prediction-systems?f
  3. 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 Discussions (OSD). 2017;
  4. Aksenov Y, Popova EE, Yool A, Nurser GAJ, Williams T, Bertino L, et al. On the future navigability of Arctic sea routes: High-resolution projections of the Arctic Ocean and sea ice. Marine Policy. 2017;75.
  5. Gharamti ME, Samuelsen A, Bertino L, Simon E, Korosov A, Daewel U. Online tuning of ocean biogeochemical model parameters using ensemble estimation techniques: Application to a one-dimensional model in the North Atlantic. Journal of Marine Systems. 2017;168.
  6. George MS, Joseph PV, Joseph KA, Bertino L, Johannessen OM. The cold pool of the Bay of Bengal and its association with the break phase of the Indian summer monsoon. Atmospheric and Oceanic Science Letters. 2017;10(3).
  7. Gharamti ME, Tjiputra J, Bethke I, Samuelsen A, Skjelvan I, Bentsen M, et al. Ensemble data assimilation for ocean biogeochemical state and parameter estimation at different sites. Ocean Modelling. 2017;112.
  8. Xie J, Bertino L, Lisæter KA, Counillon F, Sakov P. Quality assessment of the TOPAZ4 reanalysis in the Arctic over the period 1991-2013. Ocean Science. 2017;13(1).

2016

  1. Wang Y, Counillon F, Bertino L. Alleviating the bias induced by the linear analysis update with an isopycnal ocean model. Quarterly Journal of the Royal Meteorological Society. 2016;142(695).
  2. Lien VS, Hjøllo SS, Skogen MD, Svendsen E, Wehde H, Bertino L, et al. An assessment of the added value from data assimilation on modelled Nordic Seas hydrography and ocean transports. Ocean Modelling. 2016;99.
  3. Raanes P. Improvements to Ensemble Methods for Data Assimilation in the Geosciences [Internet]. 2016. Available from: https://ora.ox.ac.uk/objects/uuid:9f9961f0-6906-4147-a8a9-ca9f2d0e4a12
  4. Xie J, Counillon F, Bertino L, Tian-Kunze X, Kaleschke L. Benefits of assimilating thin sea ice thickness from SMOS into the TOPAZ system. The Cryosphere. 2016;10(6).
  5. Wickert J, Cardellach E, Martín-Neira M, Bandeiras J, Bertino L, Andersen OB, et al. GEROS-ISS: GNSS REflectometry, Radio Occultation, and Scatterometry Onboard the International Space Station. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2016;9(10).

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. Haugen SA, Sagen H, Sandven S, Bertino L, Sakov P, Counillon F. Use of acoustic Travel Times for ocean model validation, and assimilation. 2010;
  4. Bertino L. Assimilation of ice and ocean observations for the operational forecast and reanalysis with TOPAZ. 2010;
  5. 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;
  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, 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
  11. 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;
  12. 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
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Nansen-Bangladesh International Centre for Coastal, Ocean and Climate Studies
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Nansen-Tutu Centre for Marine Environmental Research
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