Biblio
Filters: Author is Counillon, Francois [Clear All Filters]
Flow-dependent assimilation of sea surface temperature in isopycnal coordinates with the Norwegian climate prediction model. Tellus A: Dynamic Meteorology and Oceanography 68:32437, (2016). Download: 32437-219959-1-PB.pdf (2.62 MB)
High-resolution ensemble forecasting for the Gulf of Mexico eddies and fronts. Ocean Dynamics 59, 83-95 (2009). Abstract
Download: ODYN-D-08-00015-2.pdf (4.53 MB); fulltext-21.pdf (5.4 MB)
Hindcast Study Of Winds, Waves, and Currents In Northern Gulf Of Mexico In Hurricane Ivan (2004). Offshore Technology ConferenceOffshore Technology Conference (2005).doi:10.4043/17736-MS
Impact of assimilating a merged sea-ice thickness from CryoSat-2 and SMOS in the Arctic reanalysis. The Cryosphere 12, (2018). Abstract
Impact of assimilating altimeter data on eddy characteristics in the South China Sea. Ocean Modelling 155, (2020).
Impact of ocean and sea ice initialisation on seasonal prediction skill in the Arctic. Journal of Advances in Modeling Earth Systems 11, (2019). Abstract
Impact of snow initialization in subseasonal-to-seasonal winter forecasts with the Norwegian Climate Prediction Model. Journal of Geophysical Research (JGR): Atmospheres 124, (2019). Abstract
Modeling dynamics and thermodynamics of icebergs in the Barents Sea from 1987 to 2005. Journal of Geophysical Research 115, 14 (2010). Abstract
Download: Modeling dynamics and thermodynamics of icebergs in the Barents Sea from 1987 to 2005.pdf (2.32 MB)
Monitoring the spreading of the Amazon freshwater plume by MODIS, SMOS, Aquarius, and TOPAZ. Journal of Geophysical Research (JGR): Oceans 120, (2015).
Observational needs for improving ocean and coupled reanalysis, S2S Prediction, and decadal prediction. Frontiers in Marine Science 6:391, (2019).
Ocean Biogeochemical Predictions—Initialization and Limits of Predictability. Frontiers in Marine Science (2020).doi:10.3389/fmars.2020.00386
Optimising assimilation of hydrographic profiles into isopycnal ocean models with ensemble data assimilation. Ocean Modelling 114, (2017).
Optimising assimilation of sea ice concentration in an Earth system model with a multicategory sea ice model. Tellus A: Dynamic Meteorology and Oceanography 70:1435945, (2018).
Quality assessment of the TOPAZ4 reanalysis in the Arctic over the period 1991-2013. Ocean Science 13, (2017).
Seasonal predictability of Kiremt rainfall in coupled general circulation models. Environmental Research Letters 12, (2017).
Seasonal predictions initialised by assimilating sea surface temperature observations with the EnKF. Climate Dynamics 19, (2019).
Seasonal to decadal predictions of regional Arctic sea ice by assimilating sea surface temperature in the Norwegian Climate Prediction Model. Climate Dynamics (2020).doi:10.1007/s00382-020-05196-4
Seasonal-to-decadal predictions with the ensemble kalman filter and the Norwegian earth System Model: A twin experiment. Tellus A: Dynamic Meteorology and Oceanography 66:21074, (2014).
TOPAZ4: an ocean-sea ice data assimilation system for the North Atlantic and Arctic. Ocean Science 8, (2012). Abstract
Toward Improved Estimation of the Dynamic Topography and Ocean Circulation in the High Latitude and Arctic Ocean: The Importance of GOCE. Surveys in geophysics 35, (2014). Abstract
Download: johannesen_j.a._etal_2014_toward_improved_estimation_of_the_dynamic_topography_and_ocean_circulation_in_the_high_latitude_and.pdf (5.43 MB)
Spaceborne investigation of the long-term variability of primary productivity in the Arctic Basin. The international conference ”Climate Changes in Polar and Subpolar Regions" (2011).
The TOPAZ monitoring and prediction system for the Atlantic. European Operational Oceanography: Present and Future, 4th EuroGOOS Conference, June 2005, Brest, France 456-459 (2005).
The Climate Model: An ARCPATH Tool to Understand and Predict Climate Change. Nordic Perspectives on the Responsible Development of the Arctic: Pathways to Action (2020).doi:10.1007/978-3-030-52324-4_8
