WRF模式与Topmodel模型在洪水预报中的耦合预报试验研究

基于空间分辨率90 m×90 m的湖北荆门漳河水库数字高程模型（DEM）地形数据,并从2012-2015年选取了20场洪水过程（其中16场用于模拟,4场用于检验）,将华中区域数值天气预报业务模式WRF提供的三重嵌套空间分辨率3 km×3 km、9 km×9 km和27 km×27 km预报降雨与集总式新安江模型以及半分布式水文模型Topmodel耦合进行洪水预报试验。通过对比试验得到以下结论：当流域降雨的时、空分布比较均匀时,集总式新安江模型可以较准确地预报出洪峰流量和峰现时间,而当降雨时、空分布差异较大时,预报误差也会随之增大。基于DEM数据建立的Topmodel模型可以反映不同降雨时、空分布下洪水预报结果的差异,试验结果表明,3 km×3 km和9 km×9 km洪水预报的输出结果比较接近,且在确定性系数和洪峰相对误差上要优于27 km×27 km的洪水预报结果,而在峰现时差的预报上,则是27 km×27 km的洪水预报结果与实测较吻合。通过研究还发现,虽然当流域降雨的时、空分布存在一定差异时,3种空间分辨率的WRF预报降雨均无法预报出与实测一致的降雨分布,但是在某些情况下,当降雨的时间分布误差和空间分布误差相抵消时,仍然可以得到较为准确的洪水预报结果。因此,高时、空分辨率的模式预报降雨并不一定就能对洪水预报结果产生正贡献,需要通过反复尝试寻找水文模型和数值模式耦合的最佳时、空分辨率。     

一种局地非线性气候动力统计模型及其预报试验

根据反演建模理论，在引入一次样条函数的基础上，设计了一种局地非线性气候动力统计模型及其一整套反演方案。其实质是用逐段线性化的研究局地气候演化的非线性特征。作为初步试验，利用云南省18个测站1956年1月－1990年12月逐月温度距平和逐月雨量距平率的时间序列，反演得到一组近似描述云南省局地气候系统的非线性动力统计方程，应用反演获得的此非线性动力统计方程进行了云南省18个测站1991年1月－1994年12月逐月温度距平和逐月雨量距平率的预报试验。试验结果表明，温度距平和雨量距平率的拟合准确率分别约为78％和64％；温度距平和雨量距平率的外推预报准确率分别为75％和63％。表明此模型具有一定的拟合和预报能力，同时具有良好的稳定性。     

Tropical Stratospheric Circulation and Monsoon Rainfall

Interannual variability of both SW monsoon (June-September) and NE monsoon (October-December) rainfall over subdivisions of Coastal Andhra Pradesh, Rayalaseema and Tamil Nadu have been examined in relation to monthly zonal wind anomaly for 10 hPa, 30 hPa and 50 hPa at Balboa (9°N, 80°W) for the 29 year period (1958-1986). Correlations of zonal wind anomalies to SW monsoon rainfall (r = 0.57, significant at 1% level) is highest with the longer lead time (August of the previous year) at 10 hPa level suggesting some predictive value for Coastal Andhra Pradesh. The probabilities estimated from the contingency table reveal non-occurrence of flood during easterly wind anomalies and near non-occurrence of drought during westerly anomalies for August of the previous year at 10 hPa which provides information for forecasting of performance of SW monsoon over Coastal Andhra Pradesh. However, NE monsoon has a weak relationship with zonal wind anomalies of 10 hPa, 30 hPa and 50 hPa for Coastal Andhra Pradesh, Raya     

一个降水预报的时间序列线性平稳预测模型

本文利用兰州１９４４～１９９７年的月平均降水资料,建立了线性平稳序列的降水预测模型,该模型使用了功谱密度函数中的最大熵法（或叫全极模型）,并将特征多项式模大于１的根反射到单位圆内,再返回修正后的线性预测的系数。并对１９８６～１９９７年１１年的月降水做了预测试验,试验结果表明,该模型具有一定的预报能力,其中取１５阶预报效果较好。此方法在短期气候预测业务中,可作为台站月、季、年降水预测走向客观化、定量化方法的一种初步尝试     

Monthly prediction of rainfall over India and its homogeneous zones during monsoon season: a supervised principal component regression approach on general circulation model products

A supervised principal component regression (SPCR) technique has been employed on general circulation model (GCM) products for developing a monthly scale deterministic forecast of summer monsoon rainfall (June–July–August–September) for different homogeneous zones and India as a whole. The time series of the monthly observed rainfall as the predictand variable has been used from India Meteorological Department gridded (1°?×?1°) rainfall data. Lead 0 (forecast initialized in the same month) monthly products from GCMs are used as predictors. The sources of these GCMs are International Research Institute for Climate and Society, Columbia University, National Center for Environmental Prediction, and Japan Agency for Marine Earth Science and Technology. The performance of SPCR technique is judged against simple ensemble mean of GCMs (EM) and it is found that over almost all the zones the SPCR model gives better skill than EM in June, August, and September months of monsoon. The SPCR technique is able to capture the year to year observed rainfall variability in terms of sign as well as the magnitude. The independent forecasts of 2007 and 2008 are also analyzed for different monsoon months (Jun–Sep) in homogeneous zones and country. Here, 1982–2006 have been considered as development year or training period. Results of the study suggest that the SPCR model is able to catch the observational rainfall over India as a whole in June, August, and September in 2007 and June, July, and August in 2008.     

Application of Artificial Neural Networks to Rainfall Forecasting in Queensland, Australia

In this study,the application of artificial intelligence to monthly and seasonal rainfall forecasting in Queensland,Australia,was assessed by inputting recognized climate indices,monthly historical rainfall data,and atmospheric temperatures into a prototype stand-alone,dynamic,recurrent,time-delay,artificial neural network.Outputs,as monthly rainfall forecasts 3 months in advance for the period 1993 to 2009,were compared with observed rainfall data using time-series plots,root mean squared error(RMSE),and Pearson correlation coefficients.A comparison of RMSE values with forecasts generated by the Australian Bureau of Meteorology’s Predictive Ocean Atmosphere Model for Australia(POAMA)-1.5 general circulation model(GCM) indicated that the prototype achieved a lower RMSE for 16 of the 17 sites compared.The application of artificial neural networks to rainfall forecasting was reviewed.The prototype design is considered preliminary,with potential for significant improvement such as inclusion of output from GCMs and experimentation with other input attributes.     

北半球环状模和东北冷涡与我国东北夏季降水关系分析

利用国家气象信息中心提供的1951～2004年全国160个测站月平均降水资料和欧洲中心提供的ERA-40再分析资料,对近50多年东北地区夏季降水、东北冷涡与前期北半球环状模和海温的关系进行了统计分析,定义了一个夏季(6～8月)东北冷涡强度指数(NECVI)。结果表明:NECVI能够较好表征东北低涡的气候效应;夏季东北冷涡强度与降水存在显著的正相关,东北冷涡强年,降水偏多,前期2月北半球环状模(NAM)偏弱;东北冷涡偏弱年,降水偏少,前期2月NAM偏强。此外,夏季东北冷涡与前期的中国近海海温存在显著的负相关,前期NAM和中国近海海温的异常可以作为夏季东北冷涡异常的一个前兆信号,进而为东北地区夏季降水异常的预测提供参考依据。     

我国5月降水的气候特点和长期变化

从月尺度降水长期预报业务的需要出发，根据中央气象台长期科１６０站月降水资料，分析了中国５月份降水的基本气候特点和长期变化，进一步明确了５月份降水预报业务的工作重点，揭示出某些对５月份降水预报业务有价值的气候现象，其中５月份南北方降水长期变化的阶段性及其反位相振荡现象（ＳＮ现象）对５月份降水长期预报业务具有重要实践意义。     

大降雨型滑坡临界雨量及潜势预报模型研究

通过对湖北省1975～2002年发生的194次滑坡个例进行分析发现：滑坡时间主要发生在5-8月,占全年总次数的80％左右,与多年月平均雨量分布比较一致;滑坡区域主要位于湖北西部山地,高频中心在三峡库区;滑坡与前期降雨尤其是大降雨关系非常密切,大降雨型滑坡占滑坡总次数的63．1％。利用实效雨量计算方法,确定了大降雨型滑坡临界雨量,以此为依据建立了潜势预报模型。     

Predicting June Mean Rainfall in the Middle/Lower Yangtze River Basin

We demonstrate that there is significant skill in the GloSea5 operational seasonal forecasting system for predicting June mean rainfall in the middle/lower Yangtze River basin up to four months in advance.Much of the rainfall in this region during June is contributed by the mei-yu rain band.We find that similar skill exists for predicting the East Asian summer monsoon index(EASMI)on monthly time scales,and that the latter could be used as a proxy to predict the regional rainfall.However,there appears to be little to be gained from using the predicted EASMI as a proxy for regional rainfall on monthly time scales compared with predicting the rainfall directly.Although interannual variability of the June mean rainfall is affected by synoptic and intraseasonal variations,which may be inherently unpredictable on the seasonal forecasting time scale,the major influence of equatorial Pacific sea surface temperatures from the preceding winter on the June mean rainfall is captured by the model through their influence on the western North Pacific subtropical high.The ability to predict the June mean rainfall in the middle and lower Yangtze River basin at a lead time of up to 4 months suggests the potential for providing early information to contingency planners on the availability of water during the summer season.     

Simulation of the annual and diurnal cycles of rainfall over South Africa by a regional climate model

The capability of a current state-of-the-art regional climate model for simulating the diurnal and annual cycles of rainfall over a complex subtropical region is documented here. Hourly rainfall is simulated over Southern Africa for 1998–2006 by the non-hydrostatic model weather research and forecasting (WRF), and compared to a network of 103 stations covering South Africa. We used five simulations, four of which consist of different parameterizations for atmospheric convection at a 0.5 × 0.5° resolution, performed to test the physic-dependency of the results. The fifth experiment uses explicit convection over tropical South Africa at a 1/30° resolution. WRF simulates realistic mean rainfall fields, albeit wet biases over tropical Africa. The model mean biases are strongly modulated by the convective scheme used for the simulations. The annual cycle of rainfall is well simulated over South Africa, mostly influenced by tropical summer rainfall except in the Western Cape region experiencing winter rainfall. The diurnal cycle shows a timing bias, with atmospheric convection occurring too early in the afternoon, and causing too abundant rainfall. This result, particularly true in summer over the northeastern part of the country, is weakly physic-dependent. Cloud-resolving simulations do not clearly reduce the diurnal cycle biases. In the end, the rainfall overestimations appear to be mostly imputable to the afternoon hours of the austral summer rainy season, i.e., the periods during which convective activity is intense over the region.     

一种基于可预报性的暴雨预报评分新方法Ⅱ:暴雨检验评分模型及评估试验

针对当前暴雨预报检验采用二分类事件检验方法存在较严重的“空报”“漏报”双重惩罚,没有考虑暴雨时空分布不均和预报评分可比性不够等问题,在分析预报员对暴雨预报评分期望值基础上,设计了一种基于可预报性的暴雨预报检验评分新方法和计算模型,分析了理想评分,并对2015-2016年4-10月中国中央气象台5 km×5 km定量降水格点预报和降水落区等级暴雨预报进行评分试验,获得了以下结果和结论:（1）预报员对暴雨预报评分期望值呈现梯级下降特征,与传统的TS评分存在显著差异;（2）设计了一种基于可预报性的暴雨预报检验新方法,通过引入e指数函数构建暴雨预报评分基函数,进而构建暴雨评分模型,该模型可以较好地拟合预报员对暴雨预报评分的期望值,同时改善了评分在不同量级阈值处的断崖式突变情况;（3）提出了预报与观测的邻域匹配方法,即一个预报点与所定义邻域中的一组观测相匹配,并利用距离加权最大值法确定暴雨评分值权重系数,预报与观测距离越近,距离权重系数越大,评分值权重越大,提高了评分的合理性,避免了距离较远的匹配站点得高分不利于鼓励预报员提高预报精度的问题;（4）对中国中央气象台逐日5 km×5 km水平分辨率的定量降水格点预报产品和中央气象台定量降水落区等级预报产品进行了评分试验,暴雨预报准确率全国平均值大于60分。基于可预报性的暴雨预报检验新评分与传统暴雨预报TS评分逐日演变特征相似,但可以较好地解析TS为0的预报评分,解析后的新评分与预报员和公众的心理预期更为接近。      

CCM3大气环流模式月-季尺度预报初步试验

以1991和1994年NCEP再分析格点资料作初始场, 用NCAR气候模式CCM3进行了48次月、季预报, 针对500 hPa高度和中国降水资料对其预测能力进行了检验.结果表明, CCM3对月尺度的高度场的预报有一定的能力.对中国160站的降水距平进行月尺度和季节预报, 其准确程度可以和目前经验预报的水平相当.比较使用实际海温和用外推法预测的海温两种下边界条件所作的预报结果发现, 两者的效果差异不大.     

Space-detailed climatic forecasting of air temperature and precipitation in Eastern Siberia on the basis of accounting for local features of the underlying surface

A physical-statistical approach is used for space specification of forecasting fields of air temperature and precipitation in the mid-21st century in Eastern Siberia. The initial data on the monthly mean values representing ensemble-averaged results of 12 general circulation models of the atmosphere and the ocean, with a 2° × 2° latitude-longitude grid are specified on a 12.5 × 12.5 km grid accounting for local features of surface topography and reflectivity. The most pronounced effect of increasing space resolution is found in the areas with complicated relief, especially in summer. This corresponds to physical properties of the processes affecting local features of precipitation and air temperature fields and demonstrates efficiency of the approach under use.     

基于ECMWF细网格模式产品的湿螺旋度在四川盆地强降水预报的应用试验

利用欧洲中期数值预报中心(ECMWF)高分辨率预报场(0.25°×0.25°)资料以及四川省加密自动站降水量资料对2011年汛期7—9月和2012年5—7月共计20例强降水个例进行湿螺旋度指标的统计分析,分别归纳总结出6和24 h内强降水发生发展及落区分布的判据指标。利用这些判据指标对2012年8月30日至9月1日及9月8日发生在四川盆地的两例强降水过程及2013年汛期6—8月暴雨个例进行检验并在汛期投入了业务预报工作。检验结果表明:低层700或850 hPa湿螺旋度正值区的分布对强降水落区分布指示较好;当强降水发生时,24 h时效预报的24~48 h 3 h间隔预报场湿螺旋度数量值超过了指标值并持续了2个时次以上,达到了强降水发生的要求;零场预报的0~24 h及12 h时效预报的12~36 h间隔3 h预报场任一时刻湿螺旋度数量值达到了6 h指标判据值,对其后6 h的暴雨落区有较好的指示作用,可作为短时临近预报的业务参考;湿螺旋度订正预报暴雨发生的TS评分远高于ECMWF模式,预报效果好。     

月平均降水量的二次规划最优组合预测方法研究

以逐步回归、均生函数和多层递阶作为月平均降水量的3种子预报方法，进一步采用二次规划计算方法，通过计算各子方法的最优非负权系数进行最优组合预测建模研究。实例计算结果表明，这种组合预测模型的预报精度优于各子方法，并具有较好的理论依据，可在实际业务预报中进行推广应用。     

基于MM5模式的站点暴雨预报方法研究

基于对MM5模式输出产品的解释应用,建立了站点定量的暴雨MOS预报方法。从临沂中尺度数值预报模式产品中挑选x1（模式预报降水）,…,x12（沙氏指数）等12个模式产品和物理诊断因子为基本可能预报因子,又添加它们自身的非线性型xi^2xi^3,xi^1/2,1nxi,e^xi（i=1,…,12）和各因子间非线性交互作xixj（i=1,…,11,j=i＋1,…,12）型的126个可能预报因子。用非线性逐步判别做晴、雨二级判别,然后对雨型样本做逐步回归,得到暴雨的MOS预报方法。检验结果表明：该模型对暴雨有较强的预报能力,可应用于实际预报业务中。     

North Sea – Caspian Pattern (NCP) – an upper level atmospheric teleconnection affecting the eastern Mediterranean – implications on the regional climate

Summary ?A calendar of the negative and positive phases of the North Sea – Caspian Pattern (NCP) for the period 1958–1998 was used to analyse the implication of the NCP upper level teleconnections on the regional climate of the eastern Mediterranean basin. Series of monthly mean air temperature and monthly total rainfall from 33 stations across Greece, Turkey and Israel, for the same period, were used. For each month, from October to April, averages of the monthly mean temperatures and the monthly rainfall totals as well as the standardized values of both parameters were calculated separately for the negative (NCP (−)) and the positive (NCP (+)) phases of the NCP. At all stations and in all months, temperature values were significantly higher during the NCP (−) as compared with the NCP (+). Furthermore, apart from very few exceptions, the absolute monthly mean maximum and monthly mean minimum values were obtained during the NCP (−) and the NCP (+) phases, respectively. The maximum impact of the NCP on mean air temperature was detected in the continental Anatolian Plateau, where the mean seasonal differences are around 3.5 °C. This influence decreases westwards and southwards. The influence on the rainfall regime is more complex. Regions exposed to the southern maritime trajectories, in Greece and in Turkey, receive more rainfall during the NCP (−) phase, whereas in the regions exposed to the northern maritime trajectories, such as Crete in Greece, the Black Sea region in Turkey, and in all regions of Israel, there is more rainfall during the NCP (+) phase. The accumulated rainfall differences between the two phases are over 50% of the seasonal average for some stations. A comparison of the capabilities of the NCP, the North Atlantic Oscillation (NAO) and the Southern Oscillation (SO) indices to differentiate between below and above normal temperatures was made. The results have placed the NCP, as the best by far of all three teleconnections in its ability to differentiate between below or above normal temperatures and as the main teleconnection affecting the climate of the Balkans, the Anatolian Peninsula and the Middle East. These results may serve to downscale General Circulation Model (GCM) scenarios to a regional scale and provide forecasts regarding eventual temperature and/or precipitation changes. Received June 25, 2001; revised February 25, 2002; accepted March 3, 2002     

车贝雪夫系数与我国温度、降水关系的初步探讨

本文用车贝雪夫多项式分解了15—65°N、75—155°E范围内,1954—1975年逐候500毫巴等压面位势场。求出车贝雪夫的一些主要系数,讨论了这些系数的物理意义及其与我国温度、降水的关系。主要结果有: 1.表示大气经、纬向环流的车贝雪夫系数A_(10)、A_(01)与我国温度等级十年滑动平均和各地月平均温度存在相关关系。此关系的存在为温度趋势预报提供了可能性。 2.表示平均高度的A_(00)系数冬季12月的值和A_(10)系数冬季1月的值,两者组合成的复相关表为长江中、下游汛期(5—8月)降水趋势预报提供了可能性。用复相关表的结果,有三年做过长江中、下游汛期降水趋势预报,其结果与实况基本一致。     

运用上月各气象要素的特征来预告下月雨量——(沈阳夏季各月雨量作例)

一个地方下月的雨量,能不能从当地上月天气演变的结果所记录下来的各种气象要素的数值来推测呢?现在这篇报告的目的就想解答这个问题。关於这方面的研究,以前早有人注意,例如竺可桢教授研究过冬天温度与夏季雨量的关系,