GMS-5反演湿度场的一维变分质量控制试验

应用一维变分方法对GMS5资料反演的相对湿度场进行了变分同化质量控制试验。首先具体分析了1998年6月12～29日的MM5模式12h预报湿度场、卫星反演湿度场和同化分析湿度场的误差统计量(误差平均值、误差自协方差矩阵、均方根误差等)。在此基础上,又应用一维变分方法对1998年7月20～30日的资料进行了同化试验,并以1998年7月21日00时(世界时)的结果为例,详细分析比较了3种湿度场。分析结果表明:MM5模式背景湿度场总体上低层偏湿,中上层偏干,各层面上的干湿区域区分明显;但往往湿区过湿,干区又偏干,均方根误差(RMSE)相对较大,各层面多在10以上,最高达到15.6。GMS5卫星反演湿度场总体与探空实测结果更接近,但整体平均看,各个层面基本上略偏湿,特别在中低层,RMSE为6.3～8.9。经过一维变分质量控制的湿度场基本接近卫星反演湿度场,但同化后的湿度场的RMSE在中低层要比卫星反演场的要小,RMSE下降了0.4～0.7,下降比率达到6%～9%;高层与卫星反演结果基本接近。对模式向前12h预报场而言,同化了卫星反演湿度场后,均方根误差值下降了1.4～9.0,下降比率达到17%～59%,同化后的湿度场与实际大气大大接近。

QUALITY CONTROL EXPERIMENT OF GMS-5 RETRIEVAL OF RH FIELD BY USING 1-DVAR TECHNIQUE

A quality control experiment was performed for relative humidity (RH) fields retrieved from multi-spectral GMS-5 imagery by using an one-dimensional variational (1-DVAR) analysis technique. First, the MM5 12-h forecast, satellite retrieval and assimilation analysis of RH fields were given respectively, from June 12 to June 29 in 1998, and then their error statistics (with respect to radiosondes) were analyzed in detail, including mean error, error covariance and RSME. Based on the result, the GMS-5 retrievals of RH field were assimilated from July 20 to July 30 1998, and an example of assimilation for 00:00Z 21 July 1998 was performed to compare the three types of moisture fields. The result indicates, as a whole, that the MM5 12-h forecasts of RH are mainly wetter than the radiosondes observation in the lower troposphere (925-700 hPa) and drier in the upper/middle levels of the troposphere (above 500 hPa). At each level, the wet area and dry area are distinguished distinctly, but the dry area is mostly too dry and wet area too moist, so that the RMSE is more than 10 and the maximum 15.6. Though the retrievals of RH are generally rather close to the radiosondes, there is some wet in the dry area and some dry in the wet area. The satellite-retrieved fields are, on the whole, a little too wet, especially at the middle and low levels. The RMSE is between 6.3 and 8.9. The RMSE of the assimilation of humidity field that closes to the satellite retrievals is smaller than that of the GMS-5 retrievals of RH at the middle and low levels. The RMSE of the assimilation of moisture fields falls by 0.4 to 0.7, which is a reduction of 6% to 9% at the middle/low levels and is close to that of the GMS-5 retrievals at the upper levels. As for the 12-h forecasts of RH, the reduction of RMSE when assimilating GMS-5 RH is between 1.4 and 9.0, which is a reduction of 17% to 59%. It is shown that the analyzed fields approach further to the actual atmospheric moisture fields.