http://www.scar.ac.cn Sciences in Cold and Arid Regions 2013, 5(1): 0006–0015 DOI: 10.3724/SP.J.1226.2013.00006 G-WADI PERSIANN-CCS GeoServer for extreme precipitation event monitoring Kuolin Hsu * , Scott Sellars, Phu Nguyen, Dan Braithwaite, Wei Chu Department of Civil and Environmental Engineering and Center for Hydrometeorology and Remote Sensing, University of Cali- fornia-Irvine, Irvine, CA 92697-2175, USA *Correspondence to: Dr. Kuolin Hsu, Civil and Environmental Engineering and Center for Hydrometeorology and Remote Sensing, University of California-Irvine, E/4130 Engineering Gateway, Irvine, CA 92697-2175, USA. Tel: (949)8268826; E-mail: kuolinh@uci.edu Received: October 30, 2012 Accepted: January 20, 2013 ABSTRACT The Center for Hydrometeorology and Remote Sensing at the University of California, Irvine (CHRS) has been collaborating with UNESCO’s International Hydrological Program (IHP) to build a facility for forecasting and mitigating hydrological disasters. This collaboration has resulted in the development of the Water and Development Information for Arid Lands–– a Global Network (G-WADI) PERSIANN-CCS GeoServer, a near real-time global precipitation visualization and data service. This GeoServer pro- vides to end-users the tools and precipitation data needed to support operational decision making, research and sound water man- agement. This manuscript introduces and demonstrates the practicality of the G-WADI PERSIANN-CCS GeoServer for monitor- ing extreme precipitation events even over regions where ground measurements are sparse. Two extreme events are analyzed. The first event shows an extreme precipitation event causing widespread flooding in Beijing, China and surrounding districts on July 21, 2012. The second event shows tropical storm Nock-Ten that occurred in late July of 2011 causing widespread flooding in Thailand. Evaluation of PERSIANN-CCS precipitation over Thailand using a rain gauge network is also conducted and discussed. Keywords: G-WADI; remote sensing precipitation data; extreme flood event monitoring; PERSIANN-CCS; CHRS 1 Introduction Society understands that one of the most important as- pects of human survival is the ability to observe, monitor and adapt to extreme and/or catastrophic events. Meteoro- logical phenomena causing extreme weather events continue to directly impact society with heavy precipitation poten- tially causing infrastructure damage, flash floods and re- gional flooding. Anticipating and understanding these ex- treme weather events and their impacts on society using state-of-the-art tools, models and visualization products give emergency managers and planners the information they need to alert the public of an occurring extreme weather event and potential impacts. Having been developed under the collabo- ration of the Center for Hydrometeorology and Remote Sens- ing (CHRS) and the UNESCO International Hydrological Program (IHP)-Water and Development Information for Arid Lands—a Global Network (G-WADI) program, the G-WADI Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks—Cloud Classification Sys- tem (PERSIANN-CCS) GeoServer (G-WADI GeoServer) is a state-of-the-art tool that harnesses remotely sensed infor- mation to observe, monitor and analyze extreme weather events as they occur. The G-WADI GeoServer can display near real-time global coverage (60°N to 60°S) high-resolution precipitation, even in remote areas and over oceans where observations are limited (http://hydis.eng.uci.edu/gwadi/). Remotely sensed data provides us with an excellent window into global precipitation. Ground based observa- tions lack the spatial and temporal uniformity that character- izes the true nature of precipitation events. Satellites have emerged as a solution to limited aerial coverage and lower temporal resolution of ground based observations. High spatial and temporal resolutions of satellite estimates and ob-