LAPS同化GPS/PWV资料在暴雨预报中的应用研究

利用LAPS(Local Analysis and Prediction System)系统同化GPS(Global Positioning System)/PWV(Precipitable Water Vapor)资料,分析GPS/PWV资料对LAPS输出场的影响,并结合WRF模式,将LAPS输出场作为其初始场进行降水预报,进一步考察GPS/PWV资料对降水预报的作用。选取2009年6月28日湖北地区的一次强降水过程,设计三种方案进行试验。结果表明:同化GPS/PWV资料后对LAPS湿度场有显著的改善,而对高度场及风场的作用则不明显;GPS/PWV资料对区域平均可降水量的影响比雷达资料大一个量级;与此同时,利用多种评分方法对6 h累计降水做了检验,分析结果表明同化GPS/PWV资料能够有效地改进WRF模式的初始场,增加丰富的中小尺度信息,并对随后的确定性预报产生正影响。

Assimilation of GPS/PWV Data in LAPS and Its Application in Precipitation Forecasts

In order to evaluate the improvement of the GPS/PWV data assimilation to the initial humidity field and precipitation forecast field of numerical model, a series of assimilation experiments were performed using the LAPS (Local Analysis and Prediction System) and WRF (Weather Research and Forecasting) model. One heavy rainfall process in Hubei Area was taken as the experimental research object. The result shows that the assimilation of GPS/PWV is effective in reducing the error of PW in the LAPS humidity field, however its impact on potential height and wind fields is not so notable. The impacts of GPS/PWV are greater than radar data by comparing the total precipitable water analyzed by LAPS in different schemes. Different weather forecast scores show that the initial moisture field in WRF is significantly improved by using GPS/PWV data, and the improved moisture field in initial condition leads to positive effect on the forecast of rainfall.