Here, we firstly demonstrate the potential of an advanced flow dependent data assimilation method for performing seasonal-to-decadal prediction and secondly, reassess the use of sea surface temperature (SST) for initialisation of these forecasts. We use the Norwegian Climate Prediction Model (NorCPM), which is based on the Norwegian Earth System Model (NorESM) and uses the deterministic ensemble Kalman filter to assimilate observations. NorESM is a fully coupled system based on the Community Earth System Model version 1, which includes an ocean, an atmosphere, a sea ice and a land model. A numerically efficient coarse resolution version of NorESM is used. We employ a twin experiment methodology to provide an upper estimate of predictability...
A data assimilation method capable of constraining the sea ice of an Earth system model in a dynamic...
International audienceHydrographic profiles are crucial observational datasets for constraining ocea...
Ocean biogeochemical (BGC) models utilise a large number of poorly-constrained global parameters to ...
Here, we firstly demonstrate the potential of an advanced flow dependent data assimilation method fo...
This study demonstrates that assimilating SST with an advanced data assimilation method yields predi...
The Norwegian Climate Prediction Model (NorCPM) is aiming at providing prediction from seasonal-to-d...
The 5th assessment of the IPCC, scheduled for 2014, will partly be dedicated to evaluating the feasi...
This study demonstrates that assimilating SST with an advanced data assimilation method yields predi...
There is a growing demand for skillful prediction systems in the Arctic. Using the Norwegian Climate...
We develop a data assimilation scheme with the Icosahedral Non-hydrostatic Earth System Model (ICON-...
The Norwegian Climate Prediction Model (NorCPM) is developed at the Bjerknes Center for Climate Rese...
Three 10 year ensemble decadal forecast experiments have been performed with the European Centre for...
Decadal predictions by Earth system models aim to capture the state and phase of the climate several...
A data assimilation method capable of constraining the sea ice of an Earth system model in a dynamic...
International audienceHydrographic profiles are crucial observational datasets for constraining ocea...
A data assimilation method capable of constraining the sea ice of an Earth system model in a dynamic...
International audienceHydrographic profiles are crucial observational datasets for constraining ocea...
Ocean biogeochemical (BGC) models utilise a large number of poorly-constrained global parameters to ...
Here, we firstly demonstrate the potential of an advanced flow dependent data assimilation method fo...
This study demonstrates that assimilating SST with an advanced data assimilation method yields predi...
The Norwegian Climate Prediction Model (NorCPM) is aiming at providing prediction from seasonal-to-d...
The 5th assessment of the IPCC, scheduled for 2014, will partly be dedicated to evaluating the feasi...
This study demonstrates that assimilating SST with an advanced data assimilation method yields predi...
There is a growing demand for skillful prediction systems in the Arctic. Using the Norwegian Climate...
We develop a data assimilation scheme with the Icosahedral Non-hydrostatic Earth System Model (ICON-...
The Norwegian Climate Prediction Model (NorCPM) is developed at the Bjerknes Center for Climate Rese...
Three 10 year ensemble decadal forecast experiments have been performed with the European Centre for...
Decadal predictions by Earth system models aim to capture the state and phase of the climate several...
A data assimilation method capable of constraining the sea ice of an Earth system model in a dynamic...
International audienceHydrographic profiles are crucial observational datasets for constraining ocea...
A data assimilation method capable of constraining the sea ice of an Earth system model in a dynamic...
International audienceHydrographic profiles are crucial observational datasets for constraining ocea...
Ocean biogeochemical (BGC) models utilise a large number of poorly-constrained global parameters to ...