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Application of Cloud Analysis System to Typhoon Molave Simulation
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摘要: 借鉴美国CAPS开发的中尺度ARPS模式的资料分析系统ADAS，设计了基于GRAPES_Meso的云分析系统，实现了地面云观测资料、卫星云图、多普勒雷达反射率资料在GRAPRS模式中的综合融合应用。通过对登陆台风莫拉菲 (0906) 数值模拟检验云分析系统的性能。结果表明：云分析系统通过地面云观测资料、卫星红外云图、可见光云图、多普勒雷达反射率的同化，能够反演出合理的三维云覆盖状况；在三维云覆盖的基础上结合云底云顶高度，进而反演出云水、云冰、雨水、雪、霰等云微物理量，并显著改善模式初始湿度场；在台风登陆过程的模拟中，虽然对台风路径的预报有所偏差，但对比控制试验，在台风登陆地点、台风强度、路径的预报中云分析发挥了正作用；通过对云分析后初始场反演的雷达回波进行检验，验证了云分析的可行性与正确性，对整体的降水预报效果也有明显改善。
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关键词:
- 云分析系统;
- 同化;
- 水成物;
- 台风莫拉菲 (0906)
Abstract: The moist physical processes (mutual transformation of water substance), cloud and rain formation, and corresponding dynamic and thermal effect on precipitation forecast is important for the meso-scale and micro-scale numerical weather prediction model. In order to improve the cloud microphysical parameterization of GRAPES_Meso model, the surface cloud observation data, satellite image and Doppler radar reflectivity are analyzed, and the GRAPES Cloud Analysis System is developed referring to ARPS model and ARPS Data Analysis System (ADAS).The progress and principle of cloud analysis in meso-scale numerical weather prediction model is described at first, and then the technical feasibility of leading cloud analysis into GRAPES_Meso model is analyzed, based on which the cloud analysis module is designed. There are several monomial sub-modules in the GCAS (GRAPES Cloud Analysis System) such as the observation pre-treatment sub-module, 3D cloud cover analysis sub-module, humidity and moisture contents filed analysis sub-module. The special pre-treatment process has been designed for domestic observation data. The GRAPES Cloud Analysis System is developed for the first time which is based on LAPS (Local Analysis and Prediction System) cloud analysis program and referring to ARPS model and ADAS. The adjustment of the 3D cloud cover and initial field and cloud water and hydrometeors is analyzed when surface cloud observation data, satellite image and Doppler radar reflectivity is assimilated in the GRAPES_Meso. The performance of the GRAPES Cloud Analysis System is inspected by the simulation of the landing Typhoon Molave (0906). First, the distribution of 3D cloud cover is retrieved from the cloud analysis system. Second, the cloud water and hydrometeors is produced quickly based on the 3D cloud cover and the height of cloud top and bottom, also, the initial field is adjusted. Third, the forecast of typhoon track in the simulation has a little error, however, the cloud analysis system has displayed positive effects on typhoon landing sites and typhoon track and intensity forecasting compared to the controlled experiment. Finally, the feasibility and correctness of cloud analysis is verified by analysing the radar reflectivity derived from cloud analysis system, indicating the performance of total precipitation forecast is improved obviously.The feasibility of Cloud Analysis System and the assimilating capability are discussed. The System is suitable for operational run for its low computation cost and hot-swap support. Further more, there are some questions which deserve to be more widely debated, for example, Cloud Analysis System should match with the model, region and resolution. The quality control of Doppler radar reflectivity factor data, coordination between initial moist thermal and dynamic field are also very important. -
图 1 台风莫拉菲2009年7月18日20：00—19日20：00路径图
Fig. 1 Typhoon Molave (0906) track from 2000 BT 18 Jul 2009 to 2000 BT 19 Jul 2009
图 3 2009年7月18日20：00 4 km高度雷达组合反射率因子
Fig. 3 Doppler radar reflectivity of 4 km height at 2000 BT 18 Jul 2009
图 4 云分析前后4 km高度云量场分布 (a) 初始云量，(b) 云分析后云量
Fig. 4 The increment of 4 km cloud cover with cloud analysis
(a) the initial cloud cover, (b) cloud cover with cloud analysis
图 5 云分析生成的水成物含量沿22°N垂直剖面 (单位:g·kg-1)
Fig. 5 The cross section of moisture contents along 22°N (unit:g·kg-1)
图 6 云分析对相对湿度场的调整 (单位：%) (a)11.5 km高度，(b)4 km高度
Fig. 6 The increment of relative humidity with cloud analysis (unit:%)
(a) the increment at 11.5 km height, (b) the increment at 4 km height
图 7 2009年7月18日20：00水成物反演的雷达组合反射率因子 (单位：dBZ)
Fig. 7 Radar composite reflectivity inversed from cloud analysis system at 2000 BT 18 Jul 2009(unit:dBZ)
图 8 台风路径 (间隔3 h) 与强度 (单位：hPa) 预报对比图
(a)2009年7月18日20：00—19日11：00控制试验，(b)2009年7月18日20：00—19日17：00云分析试验
Fig. 8 The comparison of typhoon track (3-hour interval) and intensity (unit:hPa) forecast
(a) control experiment from 2000 BT 18 Jul 2009 to 1100 BT 19 Jul 2009, (b) experment with cloud analysis from 2000 BT 18 Jul 2009 to 1700 BT 19 Jul 2009
图 9 2009年7月19日20：00 4 km高度雷达组合反射率因子图
Fig. 9 Doppler radar reflectivity of 4 km height at 2000 BT 19 Jul 2009
图 10 2009年7月19日20：00模式预报雷达组合反射率因子预报图 (单位：dBZ)
Fig. 10 The forecast of radar composite reflectivity at 2000 BT 19 Jul 2009(unit:dBZ)
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