期刊
JOURNAL OF DISASTER RESEARCH
卷 12, 期 5, 页码 967-979出版社
FUJI TECHNOLOGY PRESS LTD
DOI: 10.20965/jdr.2017.p0967
关键词
meso-gamma-scale extreme heavy rainfall; numerical weather prediction; extrapolation-based nowcast; blending; predictability
资金
- Council for Science, Technology and Innovation (CSTI)
- Cross-ministerial Strategic Innovation Promotion Program (SIP)
- Enhancement of societal resiliency against natural disasters (Funding agency: JST)
The forecast accuracy of a numerical weather prediction (NWP) model for a very short time range (<= 1 h) for a meso-gamma-scale (2-20 km) extremely heavy rainfall (M gamma ExHR) event that caused flooding at the Shibuya railway station in Tokyo, Japan on 24 July 2015 was compared with that of an extrapolation-based nowcast (EXT). The NWP model used CReSS with 0.7 km horizontal grid spacing, and storm-scale data from dense observation networks (radars, lidars, and microwave radiometers) were assimilated using CReSS3DVAR. The forecast accuracy of the heavy rainfall area (>= 20 mm h(-1)), as a function of forecast time (FT), was investigated for the NWP model and EXT predictions using the fractions skill score (FSS) for various spatial scales of displacement error (L). These predictions were started 30 minutes before the onset of extremely heavy rainfall at Shibuya station. The FSS for L=1 km, i.e., grid-scale verification, showed NWP accuracy was lower than that of EXT before FT=40 min; however, NWP accuracy surpassed that of EXT from FT=45 to 60 min. This suggests the possibility of seamless, high-accuracy forecasts of heavy rainfall (>= 20mm h(-1)) associated with M gamma ExHR events within a very short time range (<= 1 h) by blending EXT and NWP outputs. The factors behind the fact that the NWP model predicted heavy rainfall area within the very short time range of <= 1 h more correctly than did EXT are also discussed. To enable this discussion of the factors, additional sensitivity experiments with a different assimilation method of radar reflectivity were performed. It was found that a moisture adjustment above the lifting condensation level using radar reflectivity was critical to the forecasting of heavy rainfall near Shibuya station after 25 min.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据