Data Assimilation Research Team Events / Media

Dr. Jiping Xie (Nansen Environmental and Remote Sensing Center, Bergen, Norway / Bjerknes Center for Climate Research, Bergen, Norway)

Benefits from the Ensemble Kalman Filter in the Arctic marine environment forecast and reanalysis

The Arctic Ocean is experiencing sustained and significant changes, such as rising sea temperatures and rapidly decreasing sea ice cover. However, due to insufficient observation accumulation, the accuracy of high-resolution simulations is insufficient, blocking a comprehensive understanding of Arctic environmental changes.

In the past decade, more and more new observational products or methods have been developed and applied to overcome the problem of sparse Arctic observations and deepen the understanding of cross-circle interactions. Based on the Ensemble Kalman Filter (EnKF) method and the Hybrid Coordinate Ocean Model (HYCOM), the coupled ocean and sea ice assimilation system (TOPAZ) has been the main horse in the Arctic Monitoring and Forecasting Center (ARCMFC) of the Copernicus Marine Service. In this system, all accessible ocean and sea ice observations in the Arctic, both from in-situ and by remote sensing, are assimilated by EnKF with 100 model members. It benefits from the advantage that the direct and indirect linear correlations between observation variables and model state variables can be quantitatively represented through the large ensemble members. Relevant to the results from this system, the Arctic reanalysis product and the 10-days forecast about ocean and sea ice are accessible to the public through the Copernicus portal. The individual case studies of assimilating sea ice thickness and sea surface salinity again confirm the EnKF method's robustness.

In this talk, in addition to presenting the latest developments in the TOPAZ system, I will discuss new challenges and ongoing attempts to further improve Arctic marine environment forecasting skills.