卫星遥感地表植被及其在华南暴雨中尺度数值模拟中的应用试验

LAND VEGETATION RETRIVING FROM SATELLITE REMOTE SENSING AND APPLICATION TEST IN MESOSCALE SIMULATION FOR HEAVY RAINFALL OF SOUTH CHINA

  • 摘要: 将我国植被资料和NCAR资料分别用于非静力平衡中尺度模式MM5, 对1998年5月23~24日华南暴雨进行数值模拟试验, 比较其对降水量和动力热力场预报的影响, 结果表明, 当网格格距为45 km时, 二者差别很小, 当网格格距减小到5~15 km, 预报降水量最大值增加了12%~14%, 更接近观测值, 同时对低层大气热力动力结构也有一定影响。

     

    Abstract: The Land vegetation data set retrieved from NOAA satellite remote sensing data in the HUAMEX project during May and June 1998 is applied in the PSU/NCAR mesoscale model (MM5) to simulate a heavy rainfall case during 23-24 May 1998 and compared with the NCAR land-use data set. Results show that with our land vegetation data, the simulated 24 h accumulated rainfall increased about 12%-14% for a grid spacing of 5-15 km comparing with NCAR data. The dynamic and thermodynamic structures at the low levels are also affected. For lager grid spacing (45 km), the effects were not obvious.

     

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