Cloud-resolving typhoon rainfall ensemble forecasts for Taiwan with large domain and extended range through time-lagged approach

Chung-Chieh Wang, Shin Yi Huang, Shin Hau Chen, Chih Sheng Chang, Kazuhisa Tsuboki

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

In this study, the performance of a new ensemble quantitative precipitation forecast (QPF) system for Taiwan, with a cloud-resolving grid spacing of 2.5 km, a large domain of 1860 km × 1360 km, and an extended range of 8 days, is evaluated for six typhoons during 2012-13. Obtaining the probability (ensemble) information through a time-lagged approach, this system combines the strengths of high resolution (for QPF) and longer lead time (for hazard preparation) in an innovative way. For the six typhoons, in addition to short ranges (≤3 days), the system produced a decent QPF at a longest range up to days 8, 4, 6, 3, 6, and 7, providing greatly extended lead times, especially for slow-moving storms that pose higher threats. Moreover, since forecast uncertainty (reflected in the spread) is reduced with lead time, this system can provide a wide range of rainfall scenarios across Taiwan with longer lead times, each highly realistic for the associated track, allowing for advanced preparation for worst-case scenarios. Then, as the typhoon approaches and the predicted tracks converge, the government agencies can make adjustments toward the scenario of increasing likelihood. This strategy fits well with the conventional wisdom of "hoping for the best, but preparing for the worst" when facing natural hazards. Overall, the system presented herein compares favorably in usefulness to a typical 24-member ensemble (5-km grid size, 750 km × 900 km, 3-day forecasts) currently in operation using similar computational resources. Requiring about 1500 cores to execute four 8-day runs per day, it is not only powerful but also affordable and feasible.

Original languageEnglish
Pages (from-to)151-172
Number of pages22
JournalWeather and Forecasting
Volume31
Issue number1
DOIs
Publication statusPublished - 2016 Jan 1

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Keywords

  • Atm/ocean structure/phenomena
  • Cloud resolving models
  • Ensembles
  • Forecasting
  • Hurricanes/typhoons
  • Models and modeling
  • Numerical weather prediction/forecasting
  • Precipitation
  • Rainfall

ASJC Scopus subject areas

  • Atmospheric Science

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