JpGU-AGU Joint Meeting 2020

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-GI33] Data assimilation: A fundamental approach in geosciences

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)、三好 建正(理化学研究所)、宮崎 真一(京都大学理学研究科)

[MGI33-P03] Non-Gaussian statistics in global atmospheric dynamics with a 10240-member ensemble Kalman filter experiment using an intermediate AGCM

★Invited Papers

*近藤 圭一1,2三好 建正2 (1.気象研究所、2.理化学研究所 計算科学研究センター)

キーワード:アンサンブルデータ同化、非ガウス確率密度関数

In our previous work, we performed local ensemble transform Kalman filter (LETKF) experiments with 10240 ensemble members using an intermediate atmospheric general circulation model (AGCM) known as the SPEEDY (T30/L7) model. The previous study reported that the improvement in the tropics was relatively small by increasing the ensemble size up to 10240. We hypothesize that these small improvements be related to convectively dominated tropical dynamics. In this study, we found that the non-Gaussian probability density functions (PDFs) appeared in the regions with large analysis error, mainly in the tropics and storm track regions. The non-Gaussian PDFs are mainly generated by convective parametrization in the tropics and by the instability associated with advection in the storm track regions.

Acknowledgements: This study was partly supported by JST CREST (JPMJCR1312), JST AIP (JPMJCR19U2), JSPS KAKENHI (JP16K17806), and Post-K priority issue 4 of Japan Agency for Marine-Earth Science and Technology, which was promoted by the Ministry of Education, Culture, Sports, Science and Technology, Japan. Part of the results was obtained using the K computer at the RIKEN R-CCS through proposal numbers ra000015 and hp150019.