Development of a cloud-resolving 4DVAR data assimilation system based on the JMA nonhydrostatic model

Takuya Kawabata; Hiromu Seko; Tohru Kuroda; Yasutaka Wakatsuki; Yuki Honda; Kyuichiro Tamiya; Kazumasa Aonashi; Yoshinori Shoji; Kazuo Saito; Tadashi Tsuyuki

doi:10.1117/12.578123

22 December 2004 Development of a cloud-resolving 4DVAR data assimilation system based on the JMA nonhydrostatic model

Takuya Kawabata, Hiromu Seko, Tohru Kuroda, Yasutaka Wakatsuki, Yuki Honda, Kyuichiro Tamiya, Kazumasa Aonashi, Yoshinori Shoji, Kazuo Saito, Tadashi Tsuyuki

Author Affiliations +

Proceedings Volume 5661, Remote Sensing Applications of the Global Positioning System; (2004) https://doi.org/10.1117/12.578123
Event: Fourth International Asia-Pacific Environmental Remote Sensing Symposium 2004: Remote Sensing of the Atmosphere, Ocean, Environment, and Space, 2004, Honolulu, Hawai'i, United States

Abstract

A cloud resolving 4-dimensional variational data assimilation system (4DVAR) based on the Japan Meteorological Agency nonhydrostatic model (JMA-NHM) is under development. One of the targets of this system is the analysis of mesoscale convective systems. Features of background error statistics for the model with a horizontal resolution of 2km (hereinafter abbreviated as 2km model) are much different from those with a 5km resolution (5km model). Thus, forecast error estimated by the scale-down method from that forecast error obtained from the 5km model was not applicable. To develop the cloud resolving system, background error statistics for the system with 2km horizontal intervals were calculated and a suitable set of control variables was designed. Using the new background error statistics and the new control variable set, a preliminary data assimilation experiment of the Global Positioning System (GPS)-derived precipitable water vapor (PWV) and radial wind observed by Doppler radars (RW) was performed. By assimilating GPS-PWV and RW, the convergence of horizontal wind was strengthened, and observed features of horizontal winds and PWV were reproduced in the analyzed field.

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Takuya Kawabata, Hiromu Seko, Tohru Kuroda, Yasutaka Wakatsuki, Yuki Honda, Kyuichiro Tamiya, Kazumasa Aonashi, Yoshinori Shoji, Kazuo Saito, and Tadashi Tsuyuki "Development of a cloud-resolving 4DVAR data assimilation system based on the JMA nonhydrostatic model", Proc. SPIE 5661, Remote Sensing Applications of the Global Positioning System, (22 December 2004); https://doi.org/10.1117/12.578123

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KEYWORDS

Error analysis

Data modeling

Clouds

Global Positioning System

Atmospheric modeling

Systems modeling

Statistical modeling

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