日本地球惑星科学連合2018年大会

講演情報

[EE] ポスター発表

セッション記号 A (大気水圏科学) » A-AS 大気科学・気象学・大気環境

[A-AS01] 高性能スーパーコンピュータを用いた最新の大気科学

2018年5月20日(日) 10:45 〜 12:15 ポスター会場 (幕張メッセ国際展示場 7ホール)

コンビーナ:瀬古 弘(気象研究所)、小玉 知央(独立行政法人海洋研究開発機構)、滝川 雅之(独立行政法人海洋研究開発機構、共同)、三好 建正(理化学研究所計算科学研究機構)

[AAS01-P06] The computational aspect of the SCLAE-LETKF data assimilation system for rapid-update-cycle, high-resolution radar data assimilation

★Invited Papers

*Guo-Yuan Lien1Seiya Nishizawa1Ryuji Yoshida1Hisashi Yashiro1Tatiana Martsinkevich1Takumi Honda1Shigenori Otsuka1Takemasa Miyoshi1Hirofumi Tomita1Yutaka Ishikawa1 (1.RIKEN Advanced Institute for Computational Science)

キーワード:SCALE-LETKF, Radar data assimilation

We have developed the SCALE-LETKF system, utilizing the Scalable Computing for Advanced Library and Environment-Regional Model (SCALE-RM) model and the Local Ensemble Transform Kalman Filter (LETKF). The initial purpose is to use this system for the rapid-update-cycle, high-resolution assimilation of the Phased Array Weather Radar (PAWR) data. An ultimate goal of real-time PAWR assimilation with 100 ensemble members, at 100-m model resolution, and with a 30-second update cycle, using the full capacity of the K computer, has been set for this development. This requires very careful design in every part of the code, including computation and I/O, to achieve high parallelization efficiency to meet the goal. Memory space needs to be thriftily used in single processes to allow processing the big observational data. Besides, separate execution of many small programs, which is typical in ensemble data assimilation systems, needs to be avoid; instead, only two MPI programs, the model and the data assimilation programs, are executed for the entire data assimilation cycles. In the past three some years, we have made remarkable progress of the code development towards this goal, although the actual real-time operation has not been achieved yet. Meanwhile, we believe that the SCALE-LEKTF system has become a useful tool for broad mesoscale data assimilation studies. This presentation will summarize our achievement so far with the SCALE-LETKF system in the computational aspect.