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JDR Vol.12 No.5 pp. 956-966
doi: 10.20965/jdr.2017.p0956
(2017)

Paper:

Analysis of the 6 September 2015 Tornadic Storm Around the Tokyo Metropolitan Area Using Coupled 3DVAR and Incremental Analysis Updates

Ken-ichi Shimose, Shingo Shimizu, Ryohei Kato, and Koyuru Iwanami

Storm, Flood and Landslide Research Division,
National Research Institute for Earth Science and Disaster Resilience (NIED)
3-1 Tennodai, Tsukuba, Ibaraki 305-0006, Japan

Corresponding author

Received:
April 3, 2017
Accepted:
July 23, 2017
Online released:
September 27, 2017
Published:
October 1, 2017
Keywords:
surface wind analysis, data assimilation, 3DVAR, incremental analysis updating
Abstract

This study reports preliminary results from the three-dimensional variational method (3DVAR) with incremental analysis updates (IAU) of the surface wind field, which is suitable for real-time processing. In this study, 3DVAR with IAU was calculated for the case of a tornadic storm using 500-m horizontal grid spacing with updates every 10 min, for 6 h. Radial velocity observations by eight X-band multi-parameter Doppler radars and three Doppler lidars around the Tokyo Metropolitan area, Japan, were used for the analysis. In this study, three types of analyses were performed between 1800 to 2400 LST (local standard time: UTC + 9 h) 6 September 2015. The first used only 3DVAR (3DVAR), the second used 3DVAR with IAU (3DVAR+IAU), and the third analysis did not use data assimilation (CNTL). 3DVAR+IAU showed the best accuracy of the three analyses, and 3DVAR alone showed the worst accuracy, even though the background was updated every 10 min. Sharp spike signals were observed in the time series of wind speed at 10 m AGL, analyzed by 3DVAR, strongly suggesting that a “shock” was caused by dynamic imbalance due to the instantaneous addition of analysis increments to the background wind components. The spike signal was not shown in 3DVAR+IAU analysis, therefore, we suggest that the IAU method reduces the shock caused by the addition of analysis increments. This study provides useful information on the most suitable DA method for the real-time analysis of surface wind fields.

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Last updated on Oct. 20, 2017