基于增长模繁殖法的暴雨集合预报

采用WRF模式对2010年9月发生在河南省附近的一次暴雨过程进行了集合预报试验。用增长模繁殖方法(BGM)制作了集合预报方案1;为了充分利用背景场信息,结合时间滞后法,制定了集合预报方案2:滚动繁殖法;考虑到暴雨过程中天气形势的特殊性,结合区域空间特征,制定了集合预报方案3:区域繁殖法。这3组试验均对变量U、V、T、Q进行了初值扰动,加上控制预报,均产生了9个集合成员。试验结果表明:几种集合预报方法在预报效果上相较于控制预报都具有明显的改善,滚动繁殖法及区域繁殖法对增长模繁殖法都具有一定的改进作用,其中区域繁殖法的预报效果更优,与实况更为接近。

Storm ensemble forecast based on the BGM method

Rainstorms frequently occur in China,resulting in significant loss of economic assets.For this reason,meteorologists throughout the country have performed great amounts of research regarding rainstorm prediction.Although the synoptic-scale evolution of the typical mid-latitude weather system is relatively well forecasted,numerical weather prediction models still face many difficulties in forecasting the storm-scale details.The storm-scale numerical weather predictions have significant limitations,e.g.the development process of medium-scale and micro-scale systems is sensitive to the physical and boundary layer processes,which are responsible for forecast uncertainty;and the chaotic characteristics and nonlinear action of the atmosphere result in predictability limitations.Considering both the problems described above and the successful application of an ensemble forecast technique for global medium-scale forecasts,it is reasonable to choose an ensemble forecast.In comparison with a single control forecast,an ensemble forecast can provide a more accurate estimate of the first moment of the probability density function of future atmospheric states,and can also provide higher-order moment estimations,such as the forecast error variance.How to obtain fast-growth errors,which is comparable to the actual forecast growth error,is an important problem involved in ensemble forecast.In order to obtain the actual fast-growth errors,the Breeding of Growth Mode (BGM) has been used in this paper.The method,proposed by Toth and Kalnay(1997),which has been used to generate perturbations for medium-scale ensemble forecast at NCEP,is a reasonable choice for capturing growing errors modes,especially with extreme weather.There are some problems to be solved when generating initial perturbation with BGM,such as the number of ensemble members,breeding cycles,and time span.It has been demonstrated that the number of BGM ensemble members should be no less than eight,thus in this paper nine was chosen as the number.The breeding cycles were designed for six hours,the forecasts ran four times per day,and the time span was designed for three days.In this paper I conducted some research,due to the uncertainty of the initial field.Based on the concept of breeding growth modes,I conducted some rainstorm ensemble prediction examples which had occurred around Henan Province(located in northern China) in September 2010,by using the Weather Research Forecast model(WRF),a non-hydrostatic medium-scale model with a full physics package.The model domain was centered at 33°N,119°E,and covered Henan.In this paper,three methods based on BGM have been made to improve the prediction results.Through the improvement of the breeding growth method,I conducted both the scroll breeding growth method and regional breeding growth method.The scroll breeding growth method combines the breeding growth and time lag methods.The purpose of this method is to take advantage of background fields,thereby making the prediction results more accurate.The regional breeding growth method takes both time and space factors into consideration.It enhances the strength of convection by multiplying different factors in different regions.From the three groups of experiments with different perturbation types,the following conclusions are obtained:(1) Both the scroll breeding growth method and regional breeding growth method have positive contributions to the storm-scale precipitation forecast.The accuracies of prediction of rain location and rain intensity are also improved.(2) The scroll breeding growth method and regional breeding growth method also make a significant improvement on the perspective of forecast error.Compared with BGM,they take the information of growing errors into account,and improve the defects of ensemble dispersion.(3) In terms of different intensities and different stages of rainstorms,the regional breeding growth method maintains a certain degree of stability from a variety of rates.