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?

Author:

Zhang Yu1,Hong Yang1,Wang Xuguang2,Gourley Jonathan J.3,Xue Xianwu4,Saharia Manabendra4,Ni Guangheng5,Wang Gaili6,Huang Yong7,Chen Sheng4,Tang Guoqiang5

Affiliation:

1. School of Civil Engineering and Environmental Science, and Advanced Radar Research Center, and Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma

2. School of Meteorology, and Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma

3. NOAA/National Severe Storms Laboratory, National Weather Center, Norman, Oklahoma

4. School of Civil Engineering and Environmental Science, and Advanced Radar Research Center, University of Oklahoma, Norman, Oklahoma

5. Department of Hydraulic Engineering, Tsinghua University, Beijing, China

6. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Science, Beijing, China

7. Anhui Meteorological Bureau, Hefei, China

Abstract

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 system and predictable by the GHPS 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 streamflow forecasts 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.

Publisher

American Meteorological Society

Subject

Atmospheric Science

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3