冬季高海拔复杂地形下GRAPES Meso要素预报的检验评估

利用GRAPES(Globe/Regional Assimilation and Prediction System)对2010年温哥华奥运会6个场馆气温、相对湿度、风及降水量的预报结果,采用预报准确率、平均误差、平均绝对误差、Alpha Index、TS和ETS评分等统计量对其进行了较详细的评估。结果表明:GRAPESMeso预报相对湿度的准确率最高,且随预报时效的增加,其变化趋于稳定。起初模式对相对湿度的预报偏干,之后逐渐变为预报偏湿;气温预报偏低;风速预报偏大。逐日各要素预报检验结果表明,气温的变化幅度最小;各级降水检验发现,晴雨预报的TS评分最高,且随降水增大,ETS评分逐渐接近TS。与其他模式预报结果对比发现,GRAPES-Meso对复杂地形下要素预报还存在一定的不足。本研究还发现,模式存在一定的系统误差,若能有效订正其误差,将有助于改进模式预报。

A Study of the GRAPES Meso Prediction Verification for High Altitude and Complex Terrain During Winter Time

Using the output from the run of GRAPES Meso for the six venues during the Vancouver 2010 Winter Olympic and Paralympic Games, its capability to forecast the 2 m temperature, relative humidity, 10 m wind speed and wind direction is evaluated in terms of the forecast accuracy, mean error, mean absolute error and Alpha Index. And also statistics TS, EH, PO, NH, B and ETS are used for the verification of precipitation. The results show that the forecast accuracy of relative humidity is the highest and the forecast performance tends to be steady with the increasing leading time. The model exhibits a cold bias for temperature forecast. As for relative humidity, the forecast experiences a gradual transition from dry bias to wet bias, while wind speed forecast is always larger than observation. Among all the classification for the precipitation, the forecasts of GRAPES Meso for rain or shine have the highest mean TS. And with the increase of precipitation, ETS is gradually close to the TS. At last compared with the other models we found that there are some deficiencies in GRAPES Meso. Through the verification it is found that there is a certain systematic error in the forecasts, and if the error can be effectively reduced then the numerical weather prediction will have a greater improvement.