Evaluating quantitative precipitation forecasts using the 2.5 km cress model for typhoons in taiwan: An update through the 2015 season

Chung Chieh Wang, Chih Sheng Chang*, Yi Wen Wang, Chien Chang Huang, Shih Chieh Wang, Yi Shin Chen, Kazuhisa Tsuboki, Shin Yi Huang, Shin Hau Chen, Pi Yu Chuang, Hsun Chiu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


In this study, 24 h quantitative precipitation forecasts (QPFs) by a cloud-resolving model (with a grid spacing of 2.5 km) on days 1–3 for 29 typhoons in six seasons of 2010–2015 in Taiwan were examined using categorical scores and rain gauge data. The study represents an update from a previous study for 2010–2012, in order to produce more stable and robust statistics toward the high thresholds (typically with fewer sample points), which is our main focus of interest. This is important to better understand the model’s ability to predict such high-impact typhoon rainfall events. The overall threat scores (TS, defined as the fraction among all verification points that are correctly predicted to reach a given threshold to all points that are either observed or predicted to reach that threshold, or both) were 0.28 and 0.18 on day 1 (0–24 h) QPFs, 0.25 and 0.16 on day 2 (24–48 h) QPFs, and 0.15 and 0.08 on day 3 (48–72 h) QPFs at 350 mm and 500 mm, respectively, showing improvements over 5 km models. Moreover, as found previously, a strong dependence of higher TSs for larger rainfall events also existed, and the corresponding TSs at 350 and 500 mm for the top 5% of events were 0.39 and 0.25 on day 1, 0.38 and 0.21 on day 2, and 0.25 and 0.12 on day 3. Thus, for the top typhoon rainfall events that have the highest potential for hazards, the model exhibits an even higher ability for QPFs based on categorical scores. Furthermore, it is shown that the model has little tendency to overpredict or underpredict rainfall for all groups of events with different rainfall magnitude across all thresholds, except for some tendency to under-forecast for the largest event group on day 3. Some issues associated with categorical statistics to be aware of are also demonstrated and discussed.

Original languageEnglish
Article number1501
Issue number11
Publication statusPublished - 2021 Nov


  • Categorical skill scores
  • Cloud-resolving model
  • Quantitative precipitation forecast
  • Taiwan
  • Typhoon

ASJC Scopus subject areas

  • Environmental Science (miscellaneous)


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