Biblio
Filters: Author is Counillon, Francois [Clear All Filters]
Propagation of Thermohaline Anomalies and Their Predictive Potential along the Atlantic Water Pathway. Journal of Climate 35, (2021).
Twenty-One Years of Phytoplankton Bloom Phenology in the Barents, Norwegian, and North Seas. Frontiers in Marine Science 8, (2021).
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
Impact of assimilating altimeter data on eddy characteristics in the South China Sea. Ocean Modelling 155, (2020).
Ocean Biogeochemical Predictions—Initialization and Limits of Predictability. Frontiers in Marine Science (2020).doi:10.3389/fmars.2020.00386
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
Assimilation of semi-qualitative sea ice thickness data with the EnKF-SQ: a twin experiment. Tellus A: Dynamic Meteorology and Oceanography 72, (2019). Abstract
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
Observational needs for improving ocean and coupled reanalysis, S2S Prediction, and decadal prediction. Frontiers in Marine Science 6:391, (2019).
Seasonal predictions initialised by assimilating sea surface temperature observations with the EnKF. Climate Dynamics 19, (2019).
Impact of assimilating a merged sea-ice thickness from CryoSat-2 and SMOS in the Arctic reanalysis. The Cryosphere 12, (2018). Abstract
Optimising assimilation of sea ice concentration in an Earth system model with a multicategory sea ice model. Tellus. Series A, Dynamic meteorology and oceanography 70:1435945, (2018).
Causes of the large warm bias in the Angola–Benguela Frontal Zone in the Norwegian Earth System Model. Climate Dynamics (2017).doi:10.1007/s00382-017-3896-2
Optimising assimilation of hydrographic profiles into isopycnal ocean models with ensemble data assimilation. Ocean Modelling 114, (2017).
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).
Alleviating the bias induced by the linear analysis update with an isopycnal ocean model. Quarterly Journal of the Royal Meteorological Society 142, (2016). Abstract
An assessment of the added value from data assimilation on modelled Nordic Seas hydrography and ocean transports. Ocean Modelling 99, (2016).
