Evaluation of Mei-yu Heavy-Rainfall Quantitative Precipitation Forecasts in Taiwan by A Cloud-Resolving Model for Three Seasons of 2012–2014,Natural Hazards and Earth System Sciences

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Evaluation of Mei-yu Heavy-Rainfall Quantitative Precipitation Forecasts in Taiwan by A Cloud-Resolving Model for Three Seasons of 2012–2014
Natural Hazards and Earth System Sciences ( IF 4.2 ) Pub Date : 2021-02-22 , DOI: 10.5194/nhess-2020-397
Chung-Chieh Wang , Pi-Yu Chuang , Chih-Sheng Chang , Kazuhisa Tsuboki , Shin-Yi Huang , Guo-Chen Leu

Abstract. In this study, the performance of quantitative precipitation forecasts (QPFs) by the Cloud-Resolving Storm Simulator (CReSS) in real-time in Taiwan, at a horizontal grid spacing of 2.5 km and a domain size of 1500 x 1200 km², within a range of 72 h during three mei-yu seasons of 2012–2014 is evaluated using categorical statistics, with an emphasis on heavy events (≥ 100 mm per 24 h). The overall threat scores (TSs) of QPFs for all events on day 1 (0–24 h) are 0.18, 0.15, and 0.09 at the threshold of 100, 250, and 500 mm, respectively, and indicate considerable improvements compared to past results and 5-km models. Moreover, the TSs are shown to be higher and the model more skillful in predicting larger events, in agreement with earlier findings for typhoons. After classification based on observed rainfall, the TSs of day-1 QPFs for the largest 4 % of events by CReSS at 100, 250, and 500 mm (per 24 h) are 0.34, 0.24, and 0.16, respectively, and can reach 0.15 at 250 mm on day 2 (24–48 h) and 130 mm on day 3 (48–72 h). The larger events also exhibit higher probability of detection and lower false alarm ratio than weaker events almost without exception across all thresholds. The strength of the model lies mainly in the topographic rainfall in Taiwan rather than migratory events that are less predictable. Our results highlight the crucial importance of cloud-resolving capability and the size of fine mesh for heavy-rainfall QPFs in Taiwan.

更新日期：2021-02-22

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