第194回 第2部

Various ocean reanalysis datasets have been released with the development of ocean data assimilation systems since the 2000s when global ocean interior observations by Argo profiling floats started. Geostationary satellites such as Himawari-8 recently have observed sea surface temperatures at much higher temporal and spatial resolutions than before (10 mins. and 2km, respectively). To construct three-dimensional ocean fields by extracting the most from both sparse in-situ data and dense satellite data, we have developed an ensemble Kalman filter system for ocean data assimilation. We have faced two major challenges: (i) exceedingly underdispersive ensemble because of atmospheric forcing without uncertainties considered and (ii) dynamical imbalance causing initial shocks. This presentation provides an overview of ocean data assimilation and presents our research about how to tackle the challenges.