Events / Media

Data Assimilation Seminar Series

Dr. Shunji Kotsuki (Dec. 25, 2015, 15:30-)

Affiliation RIKEN-AICS
Title Ensemble Data Assimilation of GSMaP precipitation into the nonhydrostatic global atmospheric model NICAM
Abstract Following Lien et al. (2015), this study aims to improve the numerical weather prediction (NWP) through assimilating satellite-derived precipitation data. It is generally difficult to assimilate precipitation data into numerical models mainly because of non-Gaussianity of precipitation variables and nonlinear precipitation processes. We use an ensemble Kalman filter (EnKF) approach to avoid explicit linearization of models. To deal with the non-Gaussianity, we apply an empirical Gaussian transformation to precipitation variables for both model background and observations. Lien et al. pioneered to show that using an EnKF and Gaussian transformation helps improve the forecasts by assimilating global precipitation data both in a simulated study using the SPEEDY model and in a real-world study using the NCEP GFS and TRMM Multi-satellite Precipitation Analysis (TMPA) data.
This study extends the previous study by Lien et al. and assimilates the JAXA’s Global Satellite Mapping of Precipitation (GSMaP) data into the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) at 112-km horizontal resolution. This presentation will include the most recent progress up to the time of the seminar.
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