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暴雨灾害  2021, Vol. 40 Issue (5): 549-557    DOI: 10.3969/j.issn.1004-9045.2021.05.012
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基于CMPAS的临海市超强台风洪涝淹没个例模拟及检验
高大伟1, 吴利红1, 马浩1, 姚益平1, 方贺1, 朱占云2, 魏爽3
1. 浙江省气候中心, 杭州 310017;
2. 浙江省气象服务中心, 杭州 310017;
3. 浙江省气象信息网络中心, 杭州 310017
Simulation and verification of a flood inundation event in Linhai induced by super severe typhoon based on CMPAS data
GAO Dawei1, WU Lihong1, MA Hao1, YAO Yiping1, FANG He1, ZHU Zhanyun2, WEI Shuang3
1. Zhejiang Climate Center, Hangzhou 310017;
2. Zhejiang Meteorological Service Center, Hangzhou 310017;
3. Zhejiang Meteorological Information and Network Center, Hangzhou 310017
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摘要 以2019年09号超强台风“利奇马”引发的浙江省台州临海市受淹为例,利用浙江省水文站和气象站降水量观测资料对国家级地面-卫星-雷达三源融合实况格点降水数据(CMPAS-5km,CMA Multisource Precipitation Analysis System)进行检验评估;然后,基于CMPAS-5km计算的面雨量和降水分布权重栅格驱动FloodArea二维水动力淹没模型,在“暴雨情景”下进行洪涝模拟,并借助哨兵1号合成孔径雷达卫星(Sentinel-1 SAR)资料和地面验证点开展模拟受淹验证。结果表明:CMPAS-5km降水与站点降水的时空一致性较好,与水文站、“水文站+气象站”两套资料的过程降水量相关系数均达0.89,与水文站逐小时平均降水的相关系数为0.79、均方根误差为1.7 mm·h-1;在台州受淹模拟区,CMPAS-5km、水文站及气象站三者的小时面雨量变化趋势较为一致,过程累积面雨量分别为305.5 mm、304.1 mm和283.7 mm; CMPAS-5km在数据稳定性、时效性、精细度及数据接口上较其他两套资料有优势;在SAR影像中新增水体明显区域与FloodArea模拟结果匹配较好,模拟水深与4个验证点的实际水深的误差均在±22%以内。
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高大伟
吴利红
马浩
姚益平
方贺
朱占云
魏爽
关键词台风暴雨   三源融合实况格点降水   洪涝淹没模拟   哨兵1号数据   临海     
Abstract: Taking the flood inundation event in Linhai, Taizhou, Zhejiang Province caused by the super severe typhoon (1909) Lekima for example, we have verified and evaluated the 5km real-time data (CMPAS-5km) from the CMA Multi-source Precipitation Analysis System by using the precipitation data obtained by hydrological and meteorological stations over Zhejiang Province. In addition, we haveconductedflood simulations under the rainstorm scenarios based on the spatial distribution with weighted grid of area precipitation and accumulated precipitation calculated by CMPAS-5km to drive the FloodArea two-dimensional hydrodynamic inundation model, and performed verification of the simulated flooding by using Sentinel-1 SAR images and representative flooded points. The results show that the precipitation from CMPAS-5km and that from the stations have good temporal and spatial consistency, and the correlation coefficient (R) ofprecipitation from CMPAS-5km with those from hydrological stations and“hydrological + meteorological”stations are both 0.89. Rand root mean square error (RSME) of precipitation from CMPAS-5km with the hourly averaged precipitation from hydrological stations are 0.79 and 1.7 mm·h-1, respectively. The hourly area rainfall among CMPAS-5km, hydrological stations and meteorological stations have more consistent variation trend in Taizhou flooded simulation area, and the accumulated area rainfall in the whole simulation process is 305.5 mm, 304.1 mm and 283.7 mm, respectively. CMPAS-5km is superior to the other two sets of data from ground stations in stability, timeliness, precision and data interface. The newly-increased water area in SAR images matches the FloodArea simulation results well, and the relative bias between the maximum simulated water depth and the actual water depth at the four verification points is within ±22%.
Key wordstyphoon rainstorm   CMPAS-5km   flood inundation simulation   Sentinel-1 data   Linhai   
收稿日期: 2020-12-07;
基金资助:浙江省基础公益研究计划项目(LGF19D050001);华东区域气象科技协同创新基金合作项目(QYHZ201811);中国气象局预报员专项(CMAYBY2019-048);浙江省气象局科技计划项目(2019YB02)
通讯作者: 吴利红,主要从事气象灾害评估。E-mail:txhwlh678@sina.com   
作者简介: 高大伟,主要从事气候监测及灾害风险评估。E-mail:davidgao82@163.com
引用本文:   
高大伟, 吴利红, 马浩,等 .2021. 基于CMPAS的临海市超强台风洪涝淹没个例模拟及检验[J]. 暴雨灾害, 40(5): 549-557.
GAO Dawei, WU Lihong, MA Hao, et al .2021. Simulation and verification of a flood inundation event in Linhai induced by super severe typhoon based on CMPAS data[J]. Torrential Rain and Disasters, 40(5): 549-557.
 
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