摘要
卫星资料提供了大量关于云和雨的观测信息,在暴雨预报中可发挥巨大的作用,然而在数值模式资料同化中的应用水平仍然不高,特别是红外辐射资料的应用。由于有云环境下辐射传输过程的模拟难度很大,因此通常只同化晴空环境下的红外辐射资料。基于GRAPES-3DVAR(Global and Regional Assimilation and Prediction Enhanced System,全球/区域同化预报系统),根据RTTOV辐射传输模式(fast radiative transfer model for TOVS,快速辐射传输模式)的特点,增加云水含量、云冰水含量和云量作为同化系统控制变量,在改进辐射传输模式对红外资料模拟的同时,利用红外资料调整初始云参数和大气参数。针对2007年5月26日南海季风爆发后广东地区的一次暴雨过程,选取MODIS(Moderate Resolution Imaging Spectroradiometer,中分辨成像光谱仪)传感器水汽(第27)和云顶观测(第36)通道进行了同化试验,利用WRF(Weather Research and Forecasting Model,天气研究和预报模式)进行了数值模拟,结果表明同化MODIS资料,可以改进初始场水汽和温度分布,间接调整高空风场,调整趋势符合卫星观测,对短时降水预报有正面影响。
Satellite observations provide a great deal of information on clouds and precipitation, playing an important role in heavy rain forecasting. They are, however, insufficiently applied in the data assimilation of numerical weather predictions, especially with regard to the infrared radiances. Since it is difficult to simulate infrared radiances transmission under cloudy conditions, assimilating only the radiances with clear-sky conditions seems to be the usual practice. On the basis of the GRAPES-3DVAR （Global and Regional Assimilation and Prediction Enhanced System）, cloud liquid water, cloud ice water and cloud cover are added as the governing variables in the assimilation system. This scheme can not only improve the simulation of infrared radiances transmission by RTTOV （fast radiative transfer model for TOVS）, but also adjust the atmospheric parameters and cloud parameters using infrared radiance observations. In this paper, a case of heavy rain in Guangdong province on May 26, 2007 is selected, which was after the onset of the South China Sea Monsoon. For this case, the channels of MODIS （Moderate Resolution Imaging Spectroradiometer） for observing water vapor （ch.27） and cloud top （ch.36） are selected for assimilation and the process of heavy rain is simulated using the WRF （Weather Research and Forecasting Model）. The results show that the assimilated MODIS data can improve the distribution of water vapor and temperature in the first guess fields and adjust the upper-level wind field indirectly; the tendency of the adjustment conforms well to the satellite observations and the assimilation scheme has positive impacts on the short-range forecasting of rainstorms.
出处
《热带气象学报》
CSCD
北大核心
2010年第1期22-30,共9页
Journal of Tropical Meteorology
基金
国家重点基础研究发展计划资助(2009CB421500)
广东省自然科学基金项目(7035011)共同资助
关键词
MODIS亮温资料
同化
暴雨
MODIS brightness temperature data
assimilation
rainstorm
