Geoscience Reference
In-Depth Information
Chapter 21
Observing-System Research and Ensemble Data
Assimilation at JAMSTEC
Takeshi Enomoto, Takemasa Miyoshi, Qoosaku Moteki, Jun Inoue,
Miki Hattori, Akira Kuwano-Yoshida, Nobumasa Komori, and Shozo Yamane
Abstract Recent activities on ensemble data assimilation and its application to
observing-system research at the Japan Agency for Marine-Earth Science and
Technology are reviewed. A revised version of an ensemble-based data assimilation
system for global atmospheric data has been developed on the second-generation
Earth Simulator. This system assimilates conventional atmospheric observations and
satellite-based wind data into an atmospheric general circulation model using the
local ensemble transform Kalman filter (LETKF), a deterministic ensemble Kalman
filter algorithm that is extremely efficient with parallel computer architecture. The
updated system incorporates improvements to the previous system in the forecast
model, data assimilation algorithm and input data. Using the LETKF system,
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