Developing 2-way feedback nested-domain LETKF data assimilation system and application to high-resolution typhoon analyses and forecasts

开发2路反馈嵌套域LETKF资料同化系统及其在高分辨率台风分析和预报中的应用

• 批准号: 17K14396
• 负责人: Lien GuoYuan
• 金额: $ 2.08万
• 依托单位: Institute of Physical and Chemical Research
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Young Scientists (B)
• 财政年份: 2017
• 资助国家: 日本
• 起止时间: 2017-04-01 至 2019-03-31
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-17K14396/
• 关键词: データ同化; 台風; 気象学

This project ended in the middle of the second fiscal year because the principal investigator moved outside of Japan. During the one-year and four-month period of this project, the online nested-domain LETKF has been newly implemented in the SCALE-LETKF system. Combined with the existing online nested-domain function in the SCALE-RM model, the SCALE-LETKF has become capable of running both data assimilation cycles and extended ensemble forecasts with multiple nested domains in an online framework. The design is efficient in both the computational and human-effort aspects.The data assimilation experiments with the September 2015 Kanto-Tohoku Heavy Rainfall case were conducted using this new online nesting function. Compared with the old offline downscaling experiment in Lien et al. (2017, SOLA), the online nested-domain experiment led to improved forecast skill, due to further performing data assimilation in the inner high-resolution domain and frequent coupling of the two domains in the model forecast steps.The principal investigator also coauthored two papers by Honda et al. (2018a,b, MWR, JGR) for typhoon data assimilation studies using this SCALE-LETKF system.All source code developed in this project is publicly available at https://github.com/gylien/scale-letkf, with an MIT license.Due to early termination of this project, the 2-way feedback LETKF analysis with multiple nested domains is still under development. The principal investigator may be able to continue working on it and concluding the work in his next position.

该项目在第二个财政年度中期结束，因为主要研究员移居日本以外。在为期一年零四个月的项目期间，在线嵌套域LETKF已在SCALE-LETKF系统中新实现。结合SCALE-RM模式中现有的在线嵌套域功能，SCALE-LETKF已经能够在在线框架中运行多个嵌套域的数据同化循环和扩展集合预报。该设计在计算和人工方面都是有效的。使用这种新的在线嵌套功能对2015年9月关东东北暴雨个例进行了同化试验。与Lien等人的旧离线降尺度实验相比。（2017，SOLA），在线嵌套域实验导致改进的预报技巧，由于进一步执行内部高分辨率域的数据同化和模式预报步骤中两个域的频繁耦合。首席研究员还与本田等人合著了两篇论文。（2018 a，B，MWR，JGR）使用该SCALE-LETKF系统进行台风数据同化研究。该项目开发的所有源代码都可以在https：//github.com/gylien/scale-letkf上公开获得，并获得MIT许可。由于该项目提前终止，具有多个嵌套域的双向反馈LETKF分析仍在开发中。主要研究者可以在下一个职位上继续工作并完成工作。

项目成果

Assimilating All-Sky Himawari-8 Satellite Infrared Radiances: A Case of Typhoon Soudelor (2015)

• DOI: 10.1175/mwr-d-16-0357.1
• 发表时间: 2018-01
• 期刊: Monthly Weather Review
• 影响因子: 3.2
• 作者: T. Honda;T. Miyoshi;G. Lien;S. Nishizawa;Ryuji Yoshida;S. Adachi;K. Terasaki;K. Okamoto;H. Tomita

Issues regarding maintaining ensemble spreads, balance, and high-resolution information in rapid-update-cycle radar data assimilation with the LETKF

使用 LETKF 进行快速更新周期雷达数据同化时，有关维持集合分布、平衡和高分辨率信息的问题

• 发表时间: 2018
• 作者: Guo-Yuan Lien;and Takemasa Miyoshi
• 通讯作者: and Takemasa Miyoshi

Implicit thinning and localization of dense observation data in the LETKF: A case of phased array weather radar

LETKF中密集观测数据的隐式细化和定位：以相控阵天气雷达为例

• 发表时间: 2017
• 作者: Guo-Yuan Lien;and Takemasa Miyoshi
• 通讯作者: and Takemasa Miyoshi

SCALE-LETKF code repository on GitHub

GitHub 上的 SCALE-LETKF 代码存储库

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

用于快速更新周期、高分辨率雷达数据同化的 SCLAE-LETKF 数据同化系统的计算方面

• 发表时间: 2018
• 作者: Guo-Yuan Lien;Seiya Nishizawa;Ryuji Yoshida;Hisashi Yashiro;Tatiana Martsinkevich;Takumi Honda;Shigenori Otsuka;Takemasa Miyoshi;Hirofumi Tomita;and Yutaka Ishikawa
• 通讯作者: and Yutaka Ishikawa