Satellite data of both physical properties as well as ocean colour can be assimilated into coupled ocean-biogeochemical models with the aim to improve the model state. The physical observations like sea surface temperature usually have smaller errors than ocean colour, but it is unclear how far they can also constrain the biogeochemical model variables. Here, the effect of assimilating satellite sea surface temperature into the coastal ocean-biogeochemical model HBM-ERGOM with nested model grids in the North and Baltic Seas is investigated. A weakly and strongly coupled assimilation is performed with an ensemble Kalman filter. For the weakly coupled assimilation, the assimilation only directly influences the physical variables, while the bi...
An ensemble-based data assimilation framework for a coupled ocean–atmosphere model is applied to inv...
An ensemble-based data assimilation framework for a coupled ocean–atmosphere model is applied to inv...
The correct specification of all sources of uncertainty is critical to the success of data assimilat...
The effect of the assimilation of satellite sea surface temperature onto the forecast quality of the...
The effect of satellite sea surface temperature assimilation on the forecast quality of the coastal ...
A biogeochemical forecasting system of the North and Baltic Seas is developed based on the HIROMB-BO...
Coupled ocean-biogeochemical models simulate the ocean circulation in combination with a biogeochemi...
The impact of assimilating temperature, salinity, oxygen, phosphate and nitrate observations on mari...
Data assimilation combines observational data with numerical simulation models. The methodology allo...
In this paper we evaluate whether the assimilation of remotely-sensed optical data into a marine eco...
International audienceAn advanced multivariate sequential data assimilation system has been implemen...
© 2006 Dr. Matthew Robert John TurnerThis thesis has investigated the improvement of forecasting tem...
Ocean biogeochemical (BGC) models utilise a large number of poorly-constrained global parameters to ...
The HIROMB-BOOS Model (HBM) has been coupled with the Parallel Data Assimilation Framework PDAF (htt...
Within the European DIADEM project, a data assimilation system for coupled ocean circulation and mar...
An ensemble-based data assimilation framework for a coupled ocean–atmosphere model is applied to inv...
An ensemble-based data assimilation framework for a coupled ocean–atmosphere model is applied to inv...
The correct specification of all sources of uncertainty is critical to the success of data assimilat...
The effect of the assimilation of satellite sea surface temperature onto the forecast quality of the...
The effect of satellite sea surface temperature assimilation on the forecast quality of the coastal ...
A biogeochemical forecasting system of the North and Baltic Seas is developed based on the HIROMB-BO...
Coupled ocean-biogeochemical models simulate the ocean circulation in combination with a biogeochemi...
The impact of assimilating temperature, salinity, oxygen, phosphate and nitrate observations on mari...
Data assimilation combines observational data with numerical simulation models. The methodology allo...
In this paper we evaluate whether the assimilation of remotely-sensed optical data into a marine eco...
International audienceAn advanced multivariate sequential data assimilation system has been implemen...
© 2006 Dr. Matthew Robert John TurnerThis thesis has investigated the improvement of forecasting tem...
Ocean biogeochemical (BGC) models utilise a large number of poorly-constrained global parameters to ...
The HIROMB-BOOS Model (HBM) has been coupled with the Parallel Data Assimilation Framework PDAF (htt...
Within the European DIADEM project, a data assimilation system for coupled ocean circulation and mar...
An ensemble-based data assimilation framework for a coupled ocean–atmosphere model is applied to inv...
An ensemble-based data assimilation framework for a coupled ocean–atmosphere model is applied to inv...
The correct specification of all sources of uncertainty is critical to the success of data assimilat...