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Evaluation of CMPA Precipitation Estimate in the Evolution of Typhoon

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Evaluation of CMPA Precipitation Estimate in the Evolution of Typhoon 1055 © 2016 The Authors Journal of Hydroinformatics | 18.6 | 2016 Evaluation of CMPA precipitation estimate in the evolution of typhoon-related storm rainfall in Guangdong, China Dashan Wang, Xianwei Wang, Lin Liu, Dagang Wang, Huabing Huang and Cuilin Pan ABSTRACT The merged precipitation data of Climate Prediction Center Morphing Technique and gauge Dashan Wang Xianwei Wang observations (CMPA) generated for continental China has relatively high spatial and temporal Lin Liu Dagang Wang W resolution (hourly and 0.1 ), while few studies have applied it to investigate the typhoon-related Huabing Huang Cuilin Pan extreme rainfall. This study evaluates the CMPA estimate in quantifying the typhoon-related extreme Center of Integrated Geographic Information rainfall using a dense rain gauge network in Guangdong Province, China. The results show that the Analysis, School of Geography and Planning, and Guangdong Key Laboratory for event-total precipitation from CMPA is generally in agreement with gauges by relative bias (RB) of Urbanization and Geo-simulation, Sun Yat-sen University, 2.62, 10.74 and 0.63% and correlation coefficients (CCs) of 0.76, 0.86 and 0.91 for typhoon Utor, Guangzhou, China Usagi and Linfa events, respectively. At the hourly scale, CMPA underestimates the occurrence of < > Lin Liu (corresponding author) light rain ( 1 mm/h) and heavy rain ( 16 mm/h), while overestimates the occurrence of moderate Department of Geography, rain. CMPA shows high probability of detection (POD ¼ 0.93), relatively large false alarm ratio (FAR ¼ University of Cincinnati, Cincinnati, 0.22) and small missing ratio (0.07). CMPA captures the spatial patterns of typhoon-related rain OH, USA depth, and is in agreement with the spatiotemporal evolution of hourly gauge observations by CC E-mail: [email protected] from 0.93 to 0.99. In addition, cautiousness should be taken when applying it in hydrologic modeling for flooding forecasting since CMPA underestimates heavy rain (>16 mm/h). Key words | CMPA, evaluation, extreme rainfall, typhoon INTRODUCTION Extreme precipitation often causes or induces flooding, et al. d). All brought huge amounts of rainfall and landslides, and mudslides (Hong et al. ; Wu et al. caused heavy casualties and serious economic losses. ). Heavy rainfall driven by tropical cyclones (also Accurate measurement of precipitation with fine resol- called typhoons) frequently cause casualties and enormous ution and reasonable accuracy is essential but challenging property losses in coastal areas (Negri et al. ). For (Li et al. ). Automatic rain gauge networks can provide example, Katrina struck the Gulf Coast of Florida, Alabama, near-real time measurements, while the representativeness Mississippi and Louisiana on August 2005 (Knabb et al. of a sparse and uneven distribution of gauges is worthy of con- ), Morakot hit Taiwan and Fujian Provinces of China sideration (Li & Shao ). Weather radar is capable of on August 2009 (Van Nguyen & Chen ), and Yasi hit monitoring local precipitation under fine spatial resolution the Queensland coast of Australia on February 2011 (Chen and reliable quality, although it is affected by atmospheric conditions and high terrain in mountainous areas (Zhang This is an Open Access article distributed under the terms of the Creative et al. a). With the development of satellite precipitation Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited retrievals, high resolution and multi-sensor precipitation pro- (http://creativecommons.org/licenses/by/4.0/). ducts come out in succession and are available in near-real doi: 10.2166/hydro.2016.241 Downloaded from https://iwaponline.com/jh/article-pdf/18/6/1055/390671/jh0181055.pdf by guest on 30 December 2018 1056 D. Wang et al. | Evaluation of CMPA estimates in typhoon rainfall of Guangdong China Journal of Hydroinformatics | 18.6 | 2016 time, such as PERSIANN (hourly and 0.04W ; Sorooshian et al. of heavy rain over land according to the assessment study ), the US NOAA CPC Morphing Technique (CMORPH) using PACRIAN rain gauges over low-lying atolls and coastal (30 minutes and 8 km; Joyce et al. ), Naval Research Lab- islands in the tropical Pacificbasins(Chen et al. e). Mean- oratory (NRL)-Blend (3 hours and 0.25W ; Turk & Miller ), while, Habib et al. () highlight the potential of TMPA the Tropical Rainfall Measuring Mission (TRMM) Multi- products and demonstrate the significant improvement from satellite Precipitation Analysis (TMPA, 3 hours and 0.25W ; the real-time version to the research version in a study using Huffman et al. ), and the Global Precipitation Measure- six tropical-related heavy rainfall events in Louisiana, USA. ment products (4 km and 30 minutes; Sorooshian et al. Prat & Nelson () quantify the contribution of tropical- ). For continental China, version 1.0 of the merged precipi- related rainfall over land to the annual rainfall around the tation data of the Climate Prediction Center Morphing world using TMPA 3B42 V7 estimate, and this contribution Technique and gauge based precipitation (CMPA, 0.1W and 1 could be better quantified if the underestimate of peak rain hour) are available for recent years and demonstrate high rate of TMPA is adjusted. In addition, the emergence of agreements with ground observations (Shen et al. ). CMPA estimate has not received enough attention, although These products greatly improve hydrological simulation and it shows high agreements with ground observations (Shen flood prediction due to their large coverage and relatively et al. ) and is used in a few studies (Yu & Liu ; Chen high spatial resolution (Anagnostou ; Hossain & Letten- et al. , ). Moreover, few studies use the CMPA to quan- maier ; Behrangi et al. ; Jiang et al. ). titatively analyze the typhoon-related heavy rainfall in China. Satellite precipitation estimates have considerable Therefore, the primary objective of this study is to evalu- importance in many hydrological and meteorological appli- ate the performance of the hourly CMPA product on cations (Tian et al. ). The satellite-based precipitation typhoon-related storms using an independent, dense rain products usually need verification before being applied in gauge network in Guangdong Province, China. Seven hydrologic modeling (Turk et al. ). The comprehensive typhoon-related storm events were selected to compare the evaluation to satellite precipitation products has significant CMPA estimates with dense gauge recordings over 1,330 implications. On the one hand, the knowledge of error stations. This study intends to investigate the error charac- characteristics is beneficial to the improvement of retrieval teristics of the CMPA estimate on typhoon storms through algorithm (Dinku et al. ). On the other hand, the error comprehensive assessment, such as quantifying total rain characteristics offer suggestions on how the data are prop- depth, rainfall hyetograph, spatiotemporal pattern and erly used in hydrologic and climatic models since errors storm evolutions, and so on. may vary notably among different seasons and climate set- tings (Dai et al. ; Zhou et al. ; Stampoulis & Anagnostou ). Satellite precipitation estimates, after STUDY AREA AND DATA bias adjustment, can provide better performance in hydrolo- gical modeling (Su et al. ; Yong et al. ). Study area The current satellite rainfall estimates have limitations in detecting extreme rainfall but with great potential. For The study area is in the Guangdong Province of southern instance, the four products of TMPA 3B42 V6, 3B42 RT, PER- China, which contains 21 prefecture-level cities/regions and SIANN-CCS and CMORPH greatly underestimates the peak spans 20–26 W Ninlatitudeand109–118 W Einlongitude rain rate for the extreme rainfall brought by the Typhoon Mor- (Figure 1). It is in sub-tropic and tropic climate settings con- akot in Taiwan and Fujian Provinces, China (Chen et al. a). trolled mainly by the South China Sea Monsoon (Yang et al. Both TMPA 3B42 V6 and CMORPH considerably underesti- ). The annual mean air temperature and rain depth are mates the moderate and heavy rainfall and overestimates the 22 W C and 1,800 mm, respectively (Zeng et al. ). The wet light rainfall of typhoon-related precipitation over mainland season normally ranges from April to September. Typhoon- China (Yu et al. ). The TMPA 3B42 V7 performs better related heavy rain events occur in the late wet season from over ocean than over land, and underestimates the frequency July to September and even occasionally in October (Wang Downloaded from https://iwaponline.com/jh/article-pdf/18/6/1055/390671/jh0181055.pdf by guest on 30 December 2018 1057 D. Wang et al. | Evaluation of CMPA estimates in typhoon rainfall of Guangdong China Journal of Hydroinformatics | 18.6 | 2016 Figure 1 | Terrain of Guangdong Province, China, CMPA grids (grey squares), rain gauges (purple dots) and the tracks of three typhoon events (Utor, Usagi and Linfa). Please refer to the online version of this paper to see this figure in color: http://dx.doi.org/10.2166/hydro.2016.241 (open access). et al. ). On average, 2.8 typhoons have struck this area in rapidly growing population and dramatically flourishing econ- recent years and contributed 20–30% to the annual rain omics make this area more vulnerable to flooding events. depth (Ren et al. ). The low-lying coastal terrains and the mountainous areas are susceptible to typhoon-induced floods Typhoon events (Zhang et al. b). In addition, the permanent residents
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