Hydrometeorological analysis and remote sensing of extremes: Was the july 2012 Beijing flood event detectable and predictable by global satellite observing and global weather modeling systems?

Yu Zhang, Yang Hong, Xuguang Wang, Jonathan J. Gourley, Xianwu Xue, Manabendra Saharia, Guangheng Ni, Gaili Wang, Yong Huang, Sheng Chen, Guoqiang Tang

Research output: Contribution to journalArticlepeer-review

46 Scopus citations

Abstract

Prediction, and thus preparedness, in advance of flood events is crucial for proactively reducing their impacts. In the summer of 2012, Beijing, China, experienced extreme rainfall and flooding that caused 79 fatalities and economic losses of $1.6 billion. Using rain gauge networks as a benchmark, this study investigated the detectability and predictability of the 2012 Beijing event via the Global Hydrological Prediction System (GHPS), forced by the NASA Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis at near-real time and by the deterministic and ensemble precipitation forecast products from the NOAA Global Forecast System (GFS) at several lead times. The results indicate that the disastrous flooding event was detectable by the satellite-based global precipitation observing systemand predictable by theGHPS forced by the GFS 4 days in advance. However, the GFS demonstrated inconsistencies from run to run, limiting the confidence in predicting the extreme event. The GFS ensemble precipitation forecast products from NOAA for streamflowforecasts provided additional information useful for estimating the probability of the extreme event. Given the global availability of satellite-based precipitation in near-real time and GFS precipitation forecast products at varying lead times, this study demonstrates the opportunities and challenges that exist for an integrated application of GHPS. This system is particularly useful for the vast ungauged regions of the globe.

Original languageEnglish
Pages (from-to)381-395
Number of pages15
JournalJournal of Hydrometeorology
Volume16
Issue number1
DOIs
StatePublished - 2015
Externally publishedYes

Keywords

  • Ensembles
  • Flood events
  • Forecasting
  • Hydrologic models
  • Probability forecasts/models/distribution
  • Short-range prediction

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