基于LAPS分析的WRF模式逐时气温精细化预报释用

为了满足湖北电力和华中电力系统对逐时气温预报的需求,开展气温精细化预报服务,基于局地分析预报系统(LAPS)分析融合的WRF模式精细化数值预报产品,对2011年4月1日至7月20日湖北省内及周边区域站点的逐时气温进行精细化预报释用.比较几种模式释用方案,结果表明:WRF模式预报趋势较好,预报准确率评分50％左右,日间08-20时预报误差小于夜间,最高气温(Tmax)评分54％,最低气温(Tmin)评分为44％.通过模式释用,提高了预报准确率,可使预报评分提高到60％～70％,对Tmax评分达到57％,对Tmin评分最高达到74％.分时刻建立MOS方程能够有效降低夜间20-07时的预报误差.将实况最高气温引入Kalman滤波方程能进一步提高预报准确率.

Product Interpretation of Refined Hourly Temperature Based on the Assimilation of WRF Model in LAPS

Based on the assimilation of refined WRF model products in Local Analysis and Prediction System (LAPS), in order to meet the needs of the power system temperature forecast, several product interpretation forecast methods of hourly temperature were designed in Hubei Province and surrounding stations from 1 April to 20 July 2011. Compared with other several forecast models, results show that the WRF model has a good simulation of temperature trend, the temperature forecast accuracy score is around 50%, the forecast error in the daytime of 08-20 BT is less than that in the nighttimes, the accuracy score of maximum temperature is 54% and the accuracy score of minimum temperature is 44%. The forecast accuracy can be further improved through product interpretation of model output, so that the accuracy score reached to 60%-70%, that of maximum temperature got 57% and that of minimum temperature reached 74%. In addition, the MOS equation established hourly time can effectively reduce the forecast errors in nighttime of 20-07 BT. Furthermore, bringing maximum temperature factor into Kalman system equations can be further improved forecast accuracy.