The Near-Real-Time SCALE-LETKF System: A Case of the September 2015 Kanto-Tohoku Heavy Rainfall

DOI 機関リポジトリ (HANDLE) Web Site 被引用文献16件 参考文献39件 オープンアクセス
  • Lien Guo-Yuan
    RIKEN Advanced Institute for Computational Science
  • Miyoshi Takemasa
    RIKEN Advanced Institute for Computational Science Department of Atmospheric and Oceanic Science, University of Maryland Japan Agency for Marine-Earth Science and Technology (JAMSTEC)
  • Nishizawa Seiya
    RIKEN Advanced Institute for Computational Science
  • Yoshida Ryuji
    RIKEN Advanced Institute for Computational Science Research Center for Urban Safety and Security, Kobe University
  • Yashiro Hisashi
    RIKEN Advanced Institute for Computational Science
  • Adachi Sachiho A.
    RIKEN Advanced Institute for Computational Science
  • Yamaura Tsuyoshi
    RIKEN Advanced Institute for Computational Science
  • Tomita Hirofumi
    RIKEN Advanced Institute for Computational Science

書誌事項

公開日
2017
資源種別
journal article
DOI
  • 10.2151/sola.2017-001
公開者
公益社団法人 日本気象学会

説明

<p>With a goal of real-time, high-resolution, short-term prediction of heavy rainfall systems, the SCALE-LETKF was developed implementing the local ensemble transform Kalman filter with the Scalable Computing for Advanced Library and Environment-Regional Model (SCALE-RM). The system has been running in near real time experimentally since May 2015, configured for weather analyses and forecasts at 18-km resolution for a 5760 × 4320 km area around Japan. Among the data for more than one year, the near-real-time forecasts and the 3-km resolution downscaling simulations are demonstrated for a selected case of the September 2015 Kanto-Tohoku heavy rainfall associated with Typhoon Etau (2015). The typhoon track was successfully analyzed and predicted by the system, and the line-shaped rainband producing heavy rainfall can be reasonably forecasted by the downscaling simulation from the near-real-time data.</p>

収録刊行物

  • SOLA

    SOLA 13 (0), 1-6, 2017

    公益社団法人 日本気象学会

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参考文献 (39)*注記

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