Martin Canter

A new method of bias correction using an ensemble transform Kalman filter as data assimilation scheme is developed. The objective is to create a stochastic forcing term which will partially remove the bias from numerical models. The forcing term is considered as a parameter to be estimated through state vector augmentation and the assimilation of observations.

The theoretical formulation of this method is introduced in the general context of numerical modelling. A specially designed and… Show more

A new method of bias correction using an ensemble transform Kalman filter as data assimilation scheme is developed. The objective is to create a stochastic forcing term which will partially remove the bias from numerical models. The forcing term is considered as a parameter to be estimated through state vector augmentation and the assimilation of observations.

The theoretical formulation of this method is introduced in the general context of numerical modelling. A specially designed and modified Lorenz '96 model is studied, and provides a testing environment for this new bias correction method. Several different aspects are considered through both single and iterative assimilation in a twin experiment.

The method is then implemented on the global general circulation model of the ocean NEMO-LIM2. The forcing term generation is detailed to respect particular physical constraints. Again, a twin experiment allows to assess the efficiency of the method on a realistic model. The assimilation of sea surface height observations is performed, with sea surface salinity and temperature as control variable. Subsequently, a multivariate assimilation shows further improvement of the bias correction.

Finally, the method is confronted to real sea surface height observations from the CNES-CLS09 global mean dynamic topography. A thorough study of the NEMO-LIM2 model response to the bias correction forcing term is proposed, and specific results are highlighted. An iterative assimilation concludes the method investigation. Possible ideas and future developments are suggested. Show less

In this study, we aim at developing a new method of bias correction using data assimilation. This method is based on the stochastic forcing of a model to correct bias by directly adding an additional source term into the model equations. This method is presented and tested first with a
twin experiment on a fully controlled Lorenz ’96 model. It is then applied to the lower-resolution global circulation NEMO-LIM2 model, with both a twin experiment and a real case experiment. Sea surface height… Show more

In this study, we aim at developing a new method of bias correction using data assimilation. This method is based on the stochastic forcing of a model to correct bias by directly adding an additional source term into the model equations. This method is presented and tested first with a
twin experiment on a fully controlled Lorenz ’96 model. It is then applied to the lower-resolution global circulation NEMO-LIM2 model, with both a twin experiment and a real case experiment. Sea surface height observations are used to create a forcing to correct the poorly located and estimated currents. Validation is then performed throughout the use of other variables such as sea surface temperature and salinity. Results show that the method is able to consistently correct part of the model bias. The bias correction term is presented and is consistent with the limitations of the global circulation model causing bias on the oceanic currents. Show less

Current ocean models have relatively large errors and biases in the Southern Ocean. The aim of this study is to provide a reanalysis from 1985 to 2006 assimilating sea surface temperature, sea ice concentration and sea ice drift. In the following it is also shown how surface winds in the Southern Ocean can be improved using sea ice drift estimated from infrared radiometers. Such satellite observations are available since the late seventies and have the potential to improve the wind forcing… Show more

Current ocean models have relatively large errors and biases in the Southern Ocean. The aim of this study is to provide a reanalysis from 1985 to 2006 assimilating sea surface temperature, sea ice concentration and sea ice drift. In the following it is also shown how surface winds in the Southern Ocean can be improved using sea ice drift estimated from infrared radiometers. Such satellite observations are available since the late seventies and have the potential to improve the wind forcing before more direct measurements of winds over the ocean are available using scatterometry in the late nineties. The model results are compared to the assimilated data and to independent measurements (the World Ocean Database 2009 and the mean dynamic topography based on observations). The overall improvement of the assimilation is quantified, in particular the impact of the assimilation on the representation of the polar front is discussed. Finally a method to identify model errors in the Antarctic sea ice area is proposed based on Model Output Statistics techniques using a series of potential predictors. This approach provides new directions for model improvements. Show less

Despite the progresses achieved over the last decade, many gaps in our knowledge of the processes that rule the variability of the sea ice extent in the Southern Ocean are still remaining. In particular, the recent positive trend in sea ice extent appears puzzling in a global warming context associated with a large temperature increase over the last 30 years and a strong decrease of the extent and volume of the large majority of the components of the cryosphere (snow cover, glaciers, Arctic sea… Show more

Despite the progresses achieved over the last decade, many gaps in our knowledge of the processes that rule the variability of the sea ice extent in the Southern Ocean are still remaining. In particular, the recent positive trend in sea ice extent appears puzzling in a global warming context associated with a large temperature increase over the last 30 years and a strong decrease of the extent and volume of the large majority of the components of the cryosphere (snow cover, glaciers, Arctic sea ice, etc.). Several hypotheses have been proposed to explain this positive trend, partly attributing it to changes in the atmospheric circulation or in the oceanic stratification that would impact on the sea ice transport and the heat exchanges between the atmosphere, the ocean and sea ice. However, no clear conclusion has been obtained yet regarding the relative importance of various mechanisms.

The goal of this project is firstly to improve our understanding of the mechanisms responsible for the recent changes in the Antarctic sea ice cover. Secondly, based on this improved understanding, we will be able to perform more accurate predictions and projections of the sea ice changes. Both predictions for the next decades and the projections for the end of the 21st century will be investigated. Decadal-scale is the main theme of this project but our results will also bring some new light on the longer term projections. Show less