2013年华中区域中尺度业务数值预报的客观检验

利用经过质量控制的风廓线雷达组网资料（以下简称观测）对华中区域中尺度业务模式（WHMM）水平风场的预报能力进行检验评估，分别从总体、不同高度、不同风速以及单站等方面对全风速（wspd）、纬向风（u）、经向风（v）进行1个月（2013年5月）的统计分析。结果表明：（1）WHMM对风场具有较好的预报能力。其12 h和24 h的预报与观测的相关系数在0.6以上，通过α=0.01的显著性检验，12 h相关系数大于24 h的，预报风速整体存在负偏差，较观测偏小。随预报时效延长，风场的预报误差增大。u和wspd的预报能力好于v。（2）在垂直方向上，WHMM的wspd、u和v预报的均方根误差（RMSE）随高度先增加后减小，在1~2 km高度预报误差较大，4~5 km的预报误差较小。（3）按照风廓线雷达测风wspd间隔5 m·s^-1将模式预报分组，在30 m·s^-1以下不同速度分组中，WHMM 12 h预报的wspd、u和v与观测值的相关系数均大于24 h的，且通过α=0.01的显著性检验，12 h预报的RMSE大于24 h的，并随风速增加而增大。（4）从单站的风廓线来看，模式可以预报出站点上空风场随高度的变化趋势，广州站预报效果好于芜湖和秭归站。

Assimilation of Wind Profiler Data in the Canadian Meteorological Centre's Analysis Systems

In order to use quality-controled wind profiler network data (hereinafter referred to as observation) to evaluate the prediction ability of the horizontal wind in Wuhan Mesoscale Model (WHMM), comparison results of one month (May 2013) in the whole domain, and at different heights, speeds and single stations are analyzed, respectively, by calculating the correlation coefficient, bias, and root mean square error. Results show that (1) WHMM has a good performance for the horizontal wind forecasting. The correlation coefficients of 12 h and 24 h forecasts are larger than 0.6 and correspond to α=0.01 significant level. The correlation coefficients of 12 h forecast are greater than that of 24 h, and there are negative biases in the wind speed forecast, which is smaller than the observations.With the increase of the forecast range, the forecasting errors of the wind increase. The prediction of the U-component (u) and the wind speed (wspd) are better than that of V-component (v). (2) In the vertical distribution, the RMSEs of wspd, u and v of WHMM forecast increase first and then decrease with height. The RMSEs at the height of 1~2 km are largest. The RMSEs at the height of 4~5 km are smaller than that at other heights. (3) In groups of ≤ 5 m·s^-1, 5-10 m·s^-1, 10-15 m·s^-1, 15-20 m·s^-1 and 20-30 m·s^-1, the correlation coefficients between 12 h predictions and observations are larger than those at 24 h, and they all correspond to α=0.01 significant level test. The RMSEs of wspd, u and v of WHMM forecasts increase with the increasing wind speed under different wind speed groups. (4) From wind profiles at a single station, the model can predict the trend of wind field over the station with height. The forecasting skill at Guangzhou station is better than that at Wuhu and Zigui stations.