基于重组降水集合预报的洪水概率预报

采用条件亚正态模型方法,生成了具有包含不同可能性的降水集合预报。为了保持各子流域降水集合预报变量之间的空间相关性,采用集合预报重组方法对降水集合预报进行重新排列。使用重组后的降水集合预报驱动水文模型,实现了淮河上游大坡岭-息县、淮河上游息县-王家坝和汝河-洪河上游3个子流域的12次洪水过程的洪水概率预报,并对1988年9月7日和1991年7月31日两次洪水概率预报进行个例分析。结果表明:相对于单一确定性预报,通过条件亚正态分布模型生成降水集合预报后,再经过Schaake洗牌法空间相关性重新组合的降水集合预报,捕捉洪峰出现时间和流量的能力更强。对洪水概率预报来说,降水概率预报更能达到对未来的水文事件进行最大可能估计的目的,并尽可能综合了降水预报不确定性因素,同时也说明维持变量原有的空间相关特征对于降水概率预报具有重要意义。     

降水和温度MOS预报方法探讨

文中分析了庆阳地区春季降水气候特征和环流形势 ,用 1995～ 1998年 3～ 5月T10 6资料建立了该区 8县 (市 )春季降水、温度MOS预报方程 ,进行了回代检验和试报 ,并提出了模式更换后的处理方法     

Methods of long-range forecasting of dates of the spring flood beginning and peak flow in the estuary sections of the Ob and Yenisei rivers

Multi-year characteristics of the beginning of spring floods and their peak flow observed at the stream gauges located in the estuary sections of the Ob and Yenisei rivers in the period from 1936 to 2003 were obtained in this work. For most of stream gauges, significant correlation between these characteristic dates and dates when the accumulated positive temperatures (observed at the meteorological stations located in the middle parts of the catchments) reached 30 and 40°C was revealed. A great percentage of successful forecasts issued by using the multiple regression equations (78–86%) allow recommending using the obtained relationships for long-range forecasting of dates of the spring flood beginning and its peaks in the estuary sections of the Ob and Yenisei rivers with a 20–24-days lead time.     

Seasonal forecasting of air temperature anomalies using the time analog method

Proposed is a method of forecasting the monthly mean air temperature anomalies for three months of the moving season based on the statistical analysis of the array of analogous processes of temperature variations specially selected for the initial season using the operational forecast for the first ten-day period of prognostic period being available by the beginning of the forecast. The array of analogous processes is used for revealing the most frequently observed values of temperature anomalies in the future. The overall station-by-station analysis gives a field of anomaly forecast for the CIS territory for three forthcoming months and for a season. Presented is the assessment of forecasts issued from January 2007 to December 2010 using the real ten-day period forecasts. The estimates of forecasts based on the model using the normals for 1979?C2007 are also considered.     

逐步带逼近法在热带所旋路径预报中的应用

通过对逐步逼近法１９９５年试验情况与国内外预报台的综合预报以及与国内一些客观预报方法的比较分析，总结出该方法对移动路径明显转折的热带气旋有较好的预报能力，４８小时平均误差达到３００ｋｍ以内，特别是当热带气旋的移速发生明显变化时，该方法较之其它客观方法有明显的优越性。     

逐步带逼近法在热带所旋路径预报中的应用

通过对逐步逼近法１９９５年试验与国内外预报台的综合预报以及与国内一些客观预报方法的比较分析，总结出该方法对移动路径明显转折的热带气旋有较好的预报能力，４８小时平均误差达到３００ｋｍ以内，特别是当热带所旋的移速发生明显变化时，该方法较之其它客观方法有明显的优越性     

Medium-range forecasting of the extent of forest fire hazard from meteorological conditions

A new method of medium-range forecasting of a class of fire hazard is developed based on more precise accounting of accumulated moisture deficiency that is reflected by the Nesterov standard index. A physico-statistical interpretation of hydrodynamic forecasts of fields of meteorological variables is used for finding of prognostic values of the elements of the fire hazard index, using forecasts of maximum air temperature and precipitation in the Novosibirsk region from the earlier developed scheme. The initial set of variables contains data on the isobaric surface geopotential at 500 hPa, surface pressure, temperature at 850 hPa at the regular grid points at 2.5° × 2.5° resolution and their derivatives. For formulation of forecasting equations, the algorithm of model self-organization is used with external criteria. The input of initial information, forecast issuance, displaying results and their delivery to customers based on GIS-technologies are totally automated.     

Statistical forecast of surface ozone concentration in Moscow

Two synoptic-statistical methods for forecasting daily maximum surface ozone concentrations are proposed based on the relations between surface ozone and meteorological variables in the Moscow region. The methods use current ozone measurements and forecasts of meteorological variables and of synoptic situation. Statistically, the methods provide better forecast results than climatic and persistence methods. Compared with the persistence forecast, the above methods reduce the variance of the forecast error from 1.5 to 2 times. The most significant predictors for forecasting daily maximum surface ozone concentration with lead times of one to three days for Moscow are the forecast time (Julian day of the year), prognostic temperature, relative humidity, indices of the meteorological pollution potential of the atmosphere (MPP), and surface ozone concentration observed on the previous day. The forecast efficiency is demonstrated using the 2006 observational data from the stations of the Institute of Atmospheric Physics of the Russian Academy of Sciences-Moscow State University and Mosecomonitoring State Nature Protection Organization.     

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。      

Methods of agrometeorological grain crop forecasts for the districts,farms, and fields

The methods are presented of agrometeorological forecasting of winter and spring grain crops for the district, all types of farm units, and field taking account of the regional crop forecast, weather conditions, cereal cropping technologies, and soil cultivation level. The additional yields of winter and spring wheat and spring barley and oat are developed depending on the soil cultivation level, summertime soil moistening, and doses of mineral fertilizers. The method tested on the basis of independent data demonstrated that the accuracy of such forecasts is 83–99% for the fields with intensive cultivation technology and 80% for the farm units.     

Analysis of the surface temperature and wind forecast errors of the NCAR-AirDat operational CONUS 4-km WRF forecasting system

Investigating the characteristics of model-forecast errors using various statistical and object-oriented methods is necessary for providing useful guidance to end-users and model developers as well. To this end, the random and systematic errors (i.e., biases) of the 2-m temperature and 10-m wind predictions of the NCAR-AirDat weather research and forecasting (WRF)-based real-time four-dimensional data assimilation (RTFDDA) and forecasting system are analyzed. This system has been running operationally over a contiguous United States (CONUS) domain at a 4-km grid spacing with four forecast cycles daily from June 2009 to September 2010. In the result an exceptionally useful forecast dataset was generated and used for studying the error properties of the model forecasts, in terms of both a longer time period and a broader coverage of geographic regions than previously studied. Spatiotemporal characteristics of the errors are investigated based on the 24-h forecasts between June 2009 and April 2010, and the 72-h forecasts between May and September 2010. It was found that the biases of both wind and temperature forecasts vary greatly seasonally and diurnally, with dependency on the forecast length, station elevation, geographical location, and meteorological conditions. The temperature showed systematic cold biases during the daytime at all station elevations and warm biases during the nighttime above 1,000 m above sea level (ASL), while below 600 m ASL cold biases occurred during the nighttime. The forecasts of surface wind speed exhibited strong positive biases during the nighttime, while the negative biases were observed in the spring and summer afternoons. The surface wind speed was mostly over-predicted except for the stations located between 1,000 and 2,100 m ASL, for which negative biases were identified for most forecast cycles. The highest wind-speed errors were found over the high terrain and near sea-level stations. The wind-direction errors were relatively large at the high-terrain elevation in the Rocky and Appalachian mountain ranges and the western coastal areas and the error structure exhibited notable diurnal variability.     

南宁各种下垫面温度特征及预报方法探讨

介绍下垫面温度观测的原理,并用南宁2002年12月至2003年11月资料,分析了沥青、水泥、泥土温度的特征,包括这3种下垫面的日平均温度、日最高温度、日最低温度、温度日较差特征以及它们与气温的差值。指出气温是影响各种下垫面温度的最主要因素,云对下垫面日最高温度影响显著,大气环流变换对各种下垫面温度的波动有明显影响。对各种下垫面日最高温度的预报方法进行了初步探讨。建立了基于日最高气温预报之上的各种下垫面日最高温度预报模型,并对预报与实况值进行了对比分析,指出提高次日最高气温的预报准确率和预报是否出现阴天有中到大雨天气的预报准确率,可显著改善各种下垫面日最高温度的预报效果。     

春季中国日最高气温延伸期预报误差分析及订正

数值模式直接输出和经模式后处理得到的预报误差比较,是延伸期逐日要素预报应用基础。针对中国2 583个站点在2020年春季11~30天的日最高温度预报,根据欧洲数值中心的集合预报输出,首先,使用BP-SM（Back-Propagation - Self memory）法和回归法,进行确定性预报订正效果比较;结果表明BP-SM法和回归法都明显降低了预报绝对误差;在11~14天预报中,BP-SM法得到的平均绝对误差为3.3~3.6 ℃,预报准确率超过35%,订正效果更优。其次,基于模式直接输出和BP-SM法获得的概率预报,使用CRPSS (continuous ranked probability skill score)进行了可预报性分析。结果表明,在地形复杂地区,经过订正,预报准确率明显改善。对于延伸期逐日要素预报,合理的模式后处理方法是降低预报误差和提高预报能力的重要环节。      

“CMA北京模式”中三种不同阵风诊断方案在北京地区大风预报中的评估

数值模式预报是阵风预报的重要途径之一,对“中国气象局北京快速更新循环数值预报系统（简称CMA北京模式）”中AFWA、UPP、IUM三种阵风诊断方案在北京地区大风预报中的性能进行了分析评估。两次大风过程的分析以及各季节大风预报的批量试验检验结果显示:三种方案的阵风预报存在明显差异,IUM方案的阵风预报能力优势明显。IUM方案对冷空气大风和雷暴大风预警都有较好的指示意义。其对2020年3月18日冷空气大风过程中大风起始时间、大风区位置和演变以及过程极大风速均有较好的预报效果,对2020年8月2日雷暴大风过程中大风区范围预报偏大且位置存在偏差,但对大风预警的指示意义最强。IUM方案的阵风风速预报整体偏强,但对各个季节达到或超过5级阵风的等级预报较为准确。总体而言,IUM方案对北京地区大风预报性能较好,基于该方案制作的阵风预报产品可为大风预报提供有力支撑。      

Operative Scheme for the Short-range Complex Forecasting of Surface Air Temperature and Humidity

The statistical scheme is proposed for the forecast of surface air temperature and humidity using operative weather forecasts with 3–5-day lead time from the best forecasting hydrodynamic models as well as the archives of forecasts of these models and observational data from 2800 weather stations of Russia, Eastern Europe, and Central Asia. The output of the scheme includes the forecasts of air temperature for the standard observation moments with the period of 6 hours and extreme temperatures with the lead times of 12–120 hours. The accuracy of temperature and humidity forecasts for the period from July 2014 till June 2017 is much higher than that for the forecasts of original hydrodynamic models. The skill scores for extreme temperature forecasts based on the proposed method are compared with the similar results of the Weather Element Computation (WEC) forecasting scheme and forecasts by weathermen.     

Forecasts in urban transportation planning: Uses,methods, and dilemmas

Legislation and regulation require cities to prepare forecasts of patronage and J. cost when they compete for federal funds with which to build urban rapid transit systems. Experience shows that these forecasts routinely overestimate patronage and underestimate costs. The explanation for this phenomenon is to be found not in technical shortcomings in the forecasting methods, but in the fact that the forecasts are critically dependent on assumptions of key parameters. Assumptions are chosen to produce forecasts which justify projects favored on the basis of local politics. In an environment in which competition for funds is vigorous, effective advocacy becomes more important than objectivity in the use of forecasting methods. This paper reviews forecasting models widely used by transportation consultants, and shows how the models are manipulated in order to promote systems which have been chosen on the basis of political criteria.     

强对流天气监测预报预警技术进展

强对流天气预报业务包括监测、分析、预报、预警和检验等方面。对流初生识别、对流系统强度识别和对流天气类型识别等监测技术取得新进展,综合多源资料的监测技术已应用于中国气象局中央气象台业务。对流系统的触发、发展和维持机制等获得了新认识,我国不同类型强对流天气及其环境条件统计气候特征、分析规范及相应业务产品等为业务预报提供了必要基础和技术支撑。光流法、多尺度追踪技术以及应用模糊逻辑方法的临近预报技术等有明显进展,融合短时预报技术得到广泛应用,对流可分辨高分辨率数值 (集合) 预报及其后处理产品预报试验取得了显著成效,基于数值 (集合) 预报应用模糊逻辑方法的分类强对流天气短期预报技术为业务预报提供了技术支撑。强对流天气综合监测和多尺度自适应临近预报技术、多尺度分析技术以及融合短时预报技术、发展并应用模糊逻辑等方法的、基于高分辨率数值 (集合) 模式的区分不同强度等级和极端性的分类强对流天气精细化 (概率) 预报技术等是未来发展的主要方向。     

滇西北旅游景区气象指数预报方法研究

依据云南省迪庆州3站40年的观测资料,利用统计检验结果,同时结合天气预报的时间和空间尺度理论,论证了迪庆州各旅游景点的气象指数预报。用最靠近景区的气象观测站所提供的天气预报资料和逐时观测资料作为预报景区指数的基础,同时根据景区的经纬度、海拔高度、植被状况进行订正,最终获取旅游景区的特种气象预报指数。旅游景区的特种气象预报软件开发应用天气学、数值方法等理论和业务技术方法,用Fortran语言和vB语言编程,研制了迪庆州各景区的紫外线指数、舒适指数、着装指数、火险等级、旅游气象指数系统。该系统软件已投入业务运行。     

NCEP集合预报系统在亚欧和北美区域的预报效果对比

使用NCEP集合预报系统（EPS）输出的500hPa位势高度场预报资料和相应的NCEP／NCAR再分析资料,针对集合平均预报和概率预报,采用多种预报效果检验评价方法,对该系统在亚欧和北美区域的预报效果进行全面的分析比较。总体而言,NCEP—EPS对亚欧区域的环流集合预报效果不亚于其对北关区域的预报效果。1）ACC检验表明,亚欧区域的集合平均预报效果在除冬季外的三个季节都明显优于北美区域,可用预报的时效相差达0．6～1d,且夏季的差别最大。RMSE检验表明,亚欧区域的预报效果在四个季节里均优于北美区域。2）集合概率预报可靠性的季节差别不明显,均为预报时效较短（长）时,北关（亚欧）区域的可靠性更好。系统对亚欧区域的事件识别范围相对较小,但其预报可靠性较高,北美区域则正好相反。3）夏季亚欧区域的集合概率预报效果明显优于北美区域,秋季和冬季北关区域的预报效果较好,春季在预报时效小于5d时北美区域占优,而其后则是亚欧区域的预报分辨能力更好。