title: Evaluation of high-resolution precipitation estimates from satellites during July 2012 Beijing flood event using dense rain gauge observations.
abstract: Satellite-based precipitation estimates products, CMORPH and PERSIANN-CCS, were evaluated with a dense rain gauge network over Beijing and adjacent regions for an extremely heavy precipitation event on July 21 2012. CMORPH and PEERSIANN-CSS misplaced the region of greatest rainfall accumulation, and failed to capture the spatial pattern of precipitation, evidenced by a low spatial correlation coefficient (CC). CMORPH overestimated the daily accumulated rainfall by 22.84% while PERSIANN-CCS underestimated by 72.75%. In the rainfall center, both CMORPH and PERSIANN-CCS failed to capture the temporal variation of the rainfall, and underestimated rainfall amounts by 43.43% and 87.26%, respectively. Based on our results, caution should be exercised when using CMORPH and PERSIANN-CCS as input for monitoring and forecasting floods in Beijing urban areas, and the potential for landslides in the mountainous zones west and north of Beijing.
authors.affiliation: School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, Oklahoma, United States of America; Advanced Radar Research Center, National Weather Center, Norman, Oklahoma, United States of America.
authors.forename: Sheng
authors.initials: S
authors.lastname: Chen
authors.affiliation: Anhui Weather Modification Office, Hefei, China.
authors.forename: Huijuan
authors.initials: H
authors.lastname: Liu
authors.affiliation: Departments of Earth, Ocean, and Atmospheric Science, Florida State University, Tallahassee, Florida, United States of America.
authors.forename: Yalei
authors.initials: Y
authors.lastname: You
authors.affiliation: Cooperative Institutes for Mesoscale Meteorological Studies, University of Oklahoma, Norman, Oklahoma, United States of America; School of Meteorology, University of Oklahoma, Norman, Oklahoma, United States of America.
authors.forename: Esther
authors.initials: E
authors.lastname: Mullens
authors.affiliation: School of Computer Science, University of Oklahoma, Norman, Oklahoma, United States of America.
authors.forename: Junjun
authors.initials: J
authors.lastname: Hu
authors.affiliation: Anhui Weather Modification Office, Hefei, China.
authors.forename: Ye
authors.initials: Y
authors.lastname: Yuan
authors.affiliation: Beijing Weather Modification Office, Beijing, China.
authors.forename: Mengyu
authors.initials: M
authors.lastname: Huang
authors.affiliation: Remote Sensing Application Test Base of National Satellite Center, Gaugnxi, China; Disaster Mitigation Institute of the Guangxi Meteorological Bureau, Nanning, Gaugnxi, China.
authors.forename: Li
authors.initials: L
authors.lastname: He
authors.affiliation: Remote Sensing Application Test Base of National Satellite Center, Gaugnxi, China; Disaster Mitigation Institute of the Guangxi Meteorological Bureau, Nanning, Gaugnxi, China.
authors.forename: Yongming
authors.initials: Y
authors.lastname: Luo
authors.affiliation: Meteorological Information Center of the Guangxi Meteorological Bureau, Nanning, Gaugnxi, China.
authors.forename: Xingji
authors.initials: X
authors.lastname: Zeng
authors.affiliation: Department of Hydraulic Engineering, Tsinghua University, Beijing, China.
authors.forename: Guoqiang
authors.initials: G
authors.lastname: Tang
authors.affiliation: School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, Oklahoma, United States of America; Advanced Radar Research Center, National Weather Center, Norman, Oklahoma, United States of America.
authors.forename: Yang
authors.initials: Y
authors.lastname: Hong
mesh_terms: D000068476:Beijing; D055868:Floods; D005843:Geography; D011336:Probability; D011891:Rain; D017215:Satellite Communications; D062206:Spatial Analysis; D013997:Time Factors