模式探空的评估分析及其在强对流天气预报中的应用研究

分析华南地区强对流天气高发季节(4～5月)的模式探空与实际观测的比较结果.从模式探空的直接评估分析中发现,地面和较高层次的预报要素误差比较大,而中间层次误差比较小,在比较多个观测站和实时预报误差分析的基础上初步探讨其可能的原因.在不稳定度指数评估分析中发现,仅考虑中间层次要素的不稳定度指数性能比较稳定,而考虑地面要素的一些不稳定度指数则有可能比较敏感,在用地面观测订正后其质量有很大的提高.在强对流天气个例的应用研究中,认为逐时预报的模式探空有非常好的应用价值,以订正的对流有效位能指数为例进行了一些分析,表

Research on Assessment of Model-Generated Sounding and Application in Forecasting Strong Convective Weather

Because of the shortage of data density of conventional sounding data and the quality problems of some sounding data,it is so important to pay attention to the application of model-generated sounding.After analysed mode-generated sounding and observation data in detail during the high frequency convective weather season(April and May) in South China,the direct assessment of model-generated sounding data shows that the error amount of forecast element on surface and high levels is bigger than middle levels,for example,forecast element of temperature at 700-hPa level is the best,and the element forecast of surface temperature is very sensitive and difficult.Based on error analysis of multiple stations and real time forecast in long period,the possible reason is discussed.Assessment of instability indexes also shows that the performance of those instability indexes which is only considered the mid-level elements is relatively steady,but some indexes which is considered surface elements might be relatively sensitive,and their quality could be greatly improved by adding surface observation data.Case study shows that hourly model-generated sounding data are proved to be very useful in strong convective weather forecast,such as CAPE(Convective Available Potential Energy) index,it could be made good use of guiding to convective weather forecast.In the case study,hourly variation of four sounding stations data in South China is mainly analysed.The analysis shows that model-generated sounding data of the four stations(Lianping,Qingyuan,Yangjiang and Hong Kong) are very close to the corresponding observation value after added surface observation,and those model-generated sounding data of hourly forecast really enriches a lot of variation details which observation could not gave us,which details is consistent very well with the occurring of strong convective storm.Case study also shows that the fine features of afternoon storm and morning storm could be obtained by using model-generated sounding data,and these features are very important for forecasting severe storm in a few hours later.Field distribution analysis shows that the change of CAPE index could help us forecasting convective weather that takes place two or three hours later and some indexes only considered mid-level element such as K index and SI(Showalter Index) are very useful for very short range(212 hours) forecasting.There are a lot of cases that mesoscale convective systems derived from terrain-effect,which could be successfully simulated by a mesoscale numerical model, but for strong convective storms derived from large-scale weather systems,it would become very complicated,one reason might be that the initial data for mesoscale numerical model is not completely proper,another reason might be due to mesoscale numerical model,for example subgrid scale parameterization scheme is not perfect,so at present time,it might be the right way to forecast strong convective storm by combining model-generated sounding with conventional surface observation,radar echo and satellite image data.