A multi-model ensemble approach for assessment of climate change impact on surface winds in France

Statistical downscaling of 14 coupled atmosphere-ocean general circulation models (AOGCM) is presented to assess potential changes of the 10 m wind speeds in France. First, a statistical downscaling method is introduced to estimate daily mean 10 m wind speed at specific sites using general circulation model output. Daily 850 hPa wind field has been selected as the large scale circulation predictor. The method is based on a classification of the daily wind fields into a few synoptic weather types and multiple linear regressions. Years are divided into an extended winter season from October to March and an extended summer season from April to September, and the procedure is conducted separately for each season. ERA40 reanalysis and observed station data have been used to build and validate the downscaling algorithm over France for the period 1974–2002. The method is then applied to 14 AOGCMs of the coupled model intercomparison project phase 3 (CMIP3) multi-model dataset. Three time periods are focused on: a historical period (1971–2000) from the climate of the twentieth century experiment and two climate projection periods (2046–2065 and 2081–2100) from the IPCC SRES A1B experiment. Evolution of the 10 m wind speed in France and associated uncertainties are discussed. Significant changes are depicted, in particular a decrease of the wind speed in the Mediterranean area. Sources of those changes are investigated by quantifying the effects of changes in the weather type occurrences, and modifications of the distribution of the days within the weather types.     

中短期天气集合预报问题

集合预报从上个世纪九十年代兴起 ,目前已成为许多业务预报中心的重要业务之一 ,同时也成为研究的重要工具。系统介绍了全球模式中短期天气预报集合、有限区域模式短期天气预报集合以及集合预报在强风暴预报中的应用等 ,并对集合预报中应当注意的问题进行了阐述。     

Flood Forecasting and Warning at the River Basin and at the European Scale

Application of recent advances in numerical weather prediction (NWP) has the potential of allowing delivery of flood warning to extend well beyond the typical lead times of operational flood warning at the river basin scale. A prototype system, a European Flood Forecasting System (EFFS) developed to deliver such pre-warnings, aiming at providing a pre-warning at lead times of between 5 and 10 days is described. Considerable uncertainty in the weather forecast at these lead times, however, means that resulting forecasts must be treated probabilistically, and although probabilistic forecasts may be easy to disseminate, these are difficult to understand. This paper explores the structure of operational flood warning, and shows that integration in the flood warning process is required if the pre-warning is to fulfil its potential. A simple method of summarising the information in the pre-warning is presented, and the system in hindcast mode is shown to give clear indication of an upcoming major event in the Rhine basin up to 10 days before the actual event. Finally recommendations on the use of data assimilation to embed the EFFS system within an operational environment are given.     

误差订正在预报集成中的应用研究

根据误差的特性，即误差由系统误差和随机误差组成，对保山5月雨量的几种预报方法的预报结果进行分析，寻找系统误差的订正方法，降低系统误差的影响。将几种预报方法订正后的结果平均从而消除随机误差，其预报结果明显改善，平均误差和均方根误差明显降低，预报准确率明显提高，可以在业务预测中广泛推广应用。     

THE ENSEMBLE FORECASTING OF TROPICAL CYCLONE MOTION I：USING A PRIMITIVE EQUATION BAROTROPIC MODEL

1INTRODUCTIONErrorsofnumericalforecastingcomprisethoseintheinitialvalue,modelandcomputationandthefirstkindoferrorbecomesmoreandmoreoutstandingwiththeon-goingdevelopmentofcomputersandnumericalmodels.Subjecttoavailableobservationmeans,therealatmosphereisanythingbutapproximatelymeasured.Meanwhile,oneshouldpayattentiontothepossibility,assuggestedbyLorenz[1],thatanyslightdifferencesduringtheinitialstatemayleadtoresultsthatturnouttobetotallydissimilarfromwhatwouldbeexpectedotherwise,asfarasdefi…     

华东地区地面和高空风场的多模式集成精细化预报研究

基于欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts, ECMWF)、中国国家气象中心业务运行的中尺度数值预报系统(Global/Regional Assimilation and Prediction Enhanced System Meso, GRAPES-Meso)、美国国家环境预报中心(National Centers for Environmental Prediction, NCEP)的全球预报系统(Global Forecast System, GFS)、GRAPES全球预报系统(GRAPES-GFS)4个模式风场预报资料,利用双线性、反距离加权、三次样条、克里格等插值方法对华东及周边地区(110°～130°E,20°～40°N)2020年1—4月逐日地面和高空风0～72 h集合预报资料进行降尺度处理,得到满足机场及终端区气象保障的精细化风场预报。此外,还对精细化风场预报做多模式集成。结果表明,对于风场的精细化格点预报,反距离加权插值方法误差最小,为最优水平插值方法。基于扩展复卡尔曼滤波的多模式集成...     

SVD在识别江苏气旋类暴雨过程敏感区信号中的应用

利用ECMWF集合预报资料,采取连续SVD的方法作为敏感性分析的工具,对同受江淮气旋影响的江苏省沿江苏南和淮北地区两次不同暴雨过程中海平面气压场的敏感区进行诊断分析。结果表明:1)敏感信号最早可提前2 d左右被锁定,存在明显地东传特征,也有位相之间转换。2)沿江苏南的降水过程中信号最早出现在江西北部和湖南西北部,主要沿着长江一线向下游传播;正负信号的转换对应有雨带位置向南调整,而一致的负信号可引起降水整体偏多,反之亦然。3)淮北暴雨预报的不确定性始于江苏中东部沿海,它的正扰动和湖北北部的负扰动都可使异常雨带呈东北-西南向正-负形式的分布,而以鄂西为中心的正扰动则可使得区域降水整体偏弱,反之也都亦然;但这些信号主要沿着鄂-豫-皖-苏一线传播。4)两次过程前两模态的敏感区在覆盖离散度的大值区域上有一定的互补性。     

MCC降水过程集合预报不同物理过程扰动方案的对比试验研究

利用WRF模式,从模式的不确定性角度来构造中尺度的集合预报,重点对比分析了不同物理参数化方案、物理过程随机扰动方案、积云对流参数化敏感参数扰动方案对中尺度对流复合体降水集合预报的影响。试验结果表明:3种物理过程扰动方法都可以反映中尺度对流复合体降水预报的不确定性特征,其预报效果比控制预报好。物理过程随机扰动方案集合平均的降水落区及强度最接近实况,并且其降水的ETS评分要高于其他2种方案。从均方根误差与离散度的角度来看,3种方案中物理过程随机扰动的均方根误差要小于其他2种方案,而其离散度要大于其他2种方案,物理过程随机扰动方案要优于其他2种方案。     

集合预报中动态调整的增长模繁殖及其对自由繁殖的改进

用增长模繁殖（BGM）法产生集合预报初始扰动的过程中,对增长模适时的进行调整是有必要的。介绍了动态调整的方法,利用T63L9全球谱模式,通过数值试验考察了在繁殖过程中采用动态调整时增长模的增长和饱和情况,并与自由繁殖试验作了相应的比较。结果表明:动态调整情况下,各层扰动的增长率可以达到一个比较大的数值;在形态饱和方面,动态调整能在很大程度上克服自由繁殖时低层扰动饱和时间滞后的缺陷;综合考虑,动态调整下扰动饱和时间可比自由繁殖缩短1天以上,且饱和特征更加明显。     

基于EEMD的太阳绕太阳系质心运动和太阳活动Hallstatt周期分析

基于行星会合指数运动学方程,推演出太阳质心到太阳系质心距离变化的计算公式,并利用该公式重建太阳质心相对于太阳系质心的距离变化时间序列,作为太阳轨道运动的替代性指标,使用聚合经验模态分解(Ensemble empirical mode decomposition,EEMD)方法分析0～25.0 ka BP太阳质心到太阳系...