日本地球惑星科学連合2019年大会

講演情報

[E] ポスター発表

セッション記号 M (領域外・複数領域) » M-GI 地球科学一般・情報地球科学

[M-GI30] Data assimilation: A fundamental approach in geosciences

2019年5月29日(水) 17:15 〜 18:30 ポスター会場 (幕張メッセ国際展示場 8ホール)

コンビーナ:中野 慎也(情報・システム研究機構 統計数理研究所)、藤井 陽介(気象庁気象研究所)、宮崎 真一(京都大学理学研究科)、三好 建正(理化学研究所)

[MGI30-P01] Superposition of atmospheric states using information redundancy for Numerical Weather Prediction

*石橋 俊之1 (1.気象庁気象研究所)

Atmospheric state analysis is a difficult scientific problem due to our limited ability in computation and observation, and analysed atmospheric states are fluctuating around the true state. The purpose of this paper is to analyse atmospheric state as a superposition of possible atmospheric states using information redundancy, and evaluate its accuracy in the context of numerical weather prediction (NWP). This atmospheric state analysis approach has two novel aspects. First, it uses only real atmospheric information, and no-artificial perturbations unlike existing ensemble based methods. Second, it does not require specific error structures of our knowledge of the atmosphere. We performed this method on a global numerical weather prediction system of Japan Meteorological Agency. The experimental results show the method can clearly reduce forecast root means square errors about 3-5% in average within 2 day forecast compared to existing methods (CNTL). Furthermore, forecast RMSEs of ensemble means of ensemble forecasts using only a few members generated by this method are significantly smaller than CNTL from the forecast initial time.