天气预报效益定量评估方法的应用

根据历史上某种天气出现的概率及预报情况,分别应用随机决策期望值准则,概率统计及统计决策理论建立距阵评价模型三种方法,计算天气预报的潜在经济效益,并以实例进行详细说明。用户可以根据对天气的不同需求及防护费,损失费等情况,参考不同的经济效益评价方法,合理安排生产活动,使得经济上收益最大,损失尽可能减小。并为专业气象服务的效益评估提供了重要参考。     

县局天气预报思路浅探

县局天气预报思路浅探连木山（沁县气象局０４６４００）气象部门从它诞生的第一天起，就是要为社会服务。换句话说，就是社会经济的发展，需要有气象部门，需要气象部门的服务。因此气象服务是气象工作的出发点和归宿。县气象局是气象部门的基层单位，也是基层服务单位。...     

以提高天气预报准确率为核心的地市天气预报预测系统建设的思考

地市天气预报业务主要是针对政府决策及社会需求而展开的,是基层气象部门服务社会的重要窗口和拳头产品,随着国民经济的快速发展,天气预报准确与否对社会经济的影响越来越大,事关政府决策的大局和百姓生活,事关气象部门声誉及地位。以提高预报准确率为核心的地市天气预报预测系统建设,已成为支撑地市天气预报业务的基石,是气象工作的核心和重点。     

概率及天气概率预报

本文通过分析数学意义上的概率,以及气象业务实践中的概率预报,阐明了概率预报在天气预报中的应用价值。特别是对于数值预报产品开发应用,实行天气预报逐级指导,具有一定的参考意义。     

我省电视天气预报附加值开发的思考

近年,电视天气预报附加值开发工作日益受到各地气象部门的关注和积极开拓.取得明显的进展,促进了天气预报工作更加准确、及时地开展.于是引发了对我省电视天气预报附加值开发的思考.1 电视天气预报附加值开发是气象科学发展的需要气象科学是门尚待深入研究的科学,特别是天气预报涉及的因素很多很复杂,因此其预报能力和技术水平很难取得突破性进展,需要加大投入,促进探索研究,以提高监测、预报能力和技术水平.解放以来,特别是十一届三中全会以来,党和人民政府十分重视气象科学发展,每年从有限的财力中安排一定的资金发展气象事业,缩短了我国气象技术与世界气象技术水平的差距.但是,我国实际财力又决定     

绵阳电视天气预报制作系统简介

绵阳电视天气预报制作系统简介赫晓玲，蒲明，陈平（绵阳地区气象局邮码６２１０００）电视气象服务是气象服务的重要窗口之一，利用电视媒介发布灾害性天气预报和警报，是气象服务的重要手段之一。从１９９５年ｉｃ月１日起，一套别开生面的天气预报节目在绵阳电视台播出...     

探讨青海气象影视中心电视天气预报节目制作系统

利用电视媒介发布天气预报是气象部门对外服务的重要手段,公众通过天气预报了解当地乃至全国的天气情况,可以合理地安排工作和生活,政府各级领导也可以通过电视天气预报了解信息,有效进行防灾、抗灾的决策。因此,搞好电视天气预报节目,可以大大提高气象服务的社会经济效益,扩大气象部门的知名度。本文对青海气象影视中心电视天气预报、节目制作系统的现状进行了分析,由此提出了新一代电视天气预报节目制作系统的机构和连接方式,对节目的运行和维持提出几点粗浅的认识。     

天气概率预报的科学性及其应用前景

介绍了天气概率预报的科学性、对象、方法及应用前景，指出天然概率预报是我国天气预报技术的发展，它是适应社会需求，提高天气预报效益的重要手段。     

浅谈电视天气预报节目经营策略

从气象影视的内在经营和外部经营两个方面，阐述了基层气象台站提高电视天气预报节目制作水平的思路和经营策略，为搞好气象科技服务与产业，提高效益提供建议。     

中期天气预报自动化业务系统

本中期天气预报自动化业务系统，是以现代微机技术为依托，针对中期天气预报的特点，结合现行中期预报业务实际工作来进行建设的本ＭＦＳ采用模块结构，具有气象要求诊断分析，天气过程预报，灾害天气预报和气象信息情报服务等功能，完全可以代替气象台站的现行中期预报业务中的大量人工劳动。     

亚高斯贝叶斯预报处理器及其初步试验

为用户提供概率天气预报信息是公共气象服务的发展趋势,概率天气预报技术的不断改进实现了概率天气预报信息的不断优化。在众多概率天气预报技术方法中,贝叶斯预报处理器是一种新近出现的、基于贝叶斯统计理论的概率预报技术;贝叶斯预报处理器可以根据一个确定性预报系统的预报值与观测值之间代表着这个系统预报性能的统计关系,借助于贝叶斯统计理论,把一个确定性预报转化为一个概率预报,从而实现对预报不确定性的定量化。由于亚高斯似然模型可以适用于多种单调似然比随机依赖结构,故采用该似然模型的亚高斯贝叶斯预报处理器,它在气象、水文等领域具有较强的适用性。在简要介绍了连续型二维随机变量情形下的贝叶斯定理及正态-线性贝叶斯预报处理器之后,详细论述了采用单一预报因子的连续型预报量亚高斯贝叶斯预报处理器,并以长沙站和武汉站2008年1月每日00时(世界时)地面气温(T2m)的中国国家气象中心、欧洲中期天气预报中心、美国国家环境预测中心集合预报中的控制预报资料(预报时效选为96h)作为确定性预报样本,对亚高斯贝叶斯预报处理器进行了初步试验。结果表明,亚高斯贝叶斯预报处理器可以将T2m各集合预报中的控制预报转化为能定量地表达各控制预报不确定性的T2...     

The Meta-Gaussian Bayesian Processor of Forecasts and Associated Preliminary Experiments

Public weather services are trending toward providing users with probabilistic weather forecasts, in place of traditional deterministic forecasts. Probabilistic forecasting techniques are continually being improved to optimize available forecasting information. The Bayesian Processor of Forecast (BPF), a new statistical method for probabilistic forecast, can transform a deterministic forecast into a probabilistic forecast according to the historical statistical relationship between observations and forecasts generated by that forecasting system. This technique accounts for the typical forecasting performance of a deterministic forecasting system in quantifying the forecast uncertainty. The meta-Gaussian likelihood model is suitable for a variety of stochastic dependence structures with monotone likelihood ratios. The meta-Gaussian BPF adopting this kind of likelihood model can therefore be applied across many fields, including meteorology and hydrology. The Bayes theorem with two continuous random variables and the normal-linear BPF are briefly introduced. The meta-Gaussian BPF for a continuous predictand using a single predictor is then presented and discussed. The performance of the meta-Gaussian BPF is tested in a preliminary experiment. Control forecasts of daily surface temperature at 0000 UTC at Changsha and Wuhan stations are used as the deterministic forecast data. These control forecasts are taken from ensemble predictions with a 96-h lead time generated by the National Meteorological Center of the China Meteorological Administration, the European Centre for Medium-Range Weather Forecasts, and the US National Centers for Environmental Prediction during January 2008. The results of the experiment show that the meta-Gaussian BPF can transform a deterministic control forecast of surface temperature from any one of the three ensemble predictions into a useful probabilistic forecast of surface temperature. These probabilistic forecasts quantify the uncertainty of the control forecast; accordingly, the performance of the probabilistic forecasts differs based on the source of the underlying deterministic control forecasts.     

Long-term ensemble forecast of snowmelt runoff with the help of the physics-based models of runoff generation

Applicability of the physically based models of runoff generation has been shown for the long-term ensemble forecasts of snowmelt runoff volumes and peak discharges. For the deterministic forecast, the ensembles of runoff hydrographs have been modeled by different combinations of measured and calculated indices of the basin conditions on the date of the forecast issue and by the mean weather for the lead time of the forecast. For the probabilistic forecast, the ensembles of runoff hydrographs have been modeled either by the ensembles of weather, which were observed for the lead-time periods of different years, or by the ensembles of weather generated by the Monte Carlo method with the help of a stochastic weather generator. The criteria have been suggested to compare the effectiveness of the probabilistic forecasts of snowmelt runoff characteristics and peak discharges and the different forecasting approaches have been compared. The study has been carried out for the Seim and Sosna river basins.     

集合预报的现状和前景

综合论述了近年来已在国际上引起高度重视的新一代动力随机预报方法 ——— 集合预报。 随着计算机技术的迅猛发展和由于大气初值和数值模式中物理过程存在着不确定性的事实, 这一方法无疑代表了数值天气预报未来演变发展的方向。 未来的天气预报产品预计将从“决定论”的预报转变为“随机论”的预报来正确地表达气象科学中这一所谓“可预报性问题”, 以便更好地为用户服务。 文中扼要地叙述了集合预报的概念、基本问题及其最新的研究动态和发展, 包括(1)如何建立和评估一个集合预报系统;(2)如何正确地表征大气初值和模式物理过程的不确定性与随机性;(3)如何从集合预报中提炼有用的预报信息和合理地解释、检验集合预报的产品, 特别是概率预报。 除了直接在天气预报上的应用, 还提到集合预报在气象观测和资料同化方面应用的动态, 以引起有关研究人员的注意。     

Downscaling of the global seasonal forecasts of hydrometcenter of Russia for North Eurasia

Proposed is a method of downscaling of the global ensemble seasonal forecasts of air temperature computed using the SLAV model of the Hydrometcenter of Russia. The method is based on the regression and suggests a probabilistic interpretation of forecasts based on the assessment of uncertainty associated with the regression and model forecast ensemble spread. The verification of the method for 70 weather stations of North Eurasia using the rank probability skill score RPSS showed a significant advantage of downscaled forecasts over the forecasts interpolated from the model grid points. It is concluded that the use of the downscaling method is reasonable for the long-range forecasting of the station air temperature for North Eurasia.     

Probabilistic temperature forecasting with statistical calibration in Hungary

Weather forecasting is based on the outputs of deterministic numerical weather forecasting models. Multiple runs of these models with different initial conditions result in forecast ensembles which are used for estimating the distribution of future atmospheric variables. However, these ensembles are usually under-dispersive and uncalibrated, so post-processing is required. In the present work, Bayesian model averaging (BMA) is applied for calibrating ensembles of temperature forecasts produced by the operational limited area model ensemble prediction system of the Hungarian Meteorological Service (HMS). We describe two possible BMA models for temperature data of the HMS and show that BMA post-processing significantly improves calibration and probabilistic forecasts although the accuracy of point forecasts is rather unchanged.     

Evaluation of the Added Value of Probabilistic Nowcasting Ensemble Forecasts on Regional Ensemble Forecasts

Ensemble forecasting systems have become an important tool for estimating the uncertainties in initial conditions and model formulations and they are receiving increased attention from various applications. The Regional Ensemble Prediction System(REPS), which has operated at the Beijing Meteorological Service(BMS) since 2017, allows for probabilistic forecasts. However, it still suffers from systematic deficiencies during the first couple of forecast hours. This paper presents an integrated prob...     

上海地区春季最高气温预报失败案例分析

本文分析了2015年3月17—18日上海地区连续两天发生最高气温预报失误的天气背景,并使用当日实况观测和业务预报使用的数值模式资料,剖析预报失败的原因,分析表明:对天空状况的误判是导致17日预报失败的主要原因,且东南风预报偏强更进一步增大了预报误差;冷空气影响时间的判断失误是导致18日预报失败的主要原因。从模式预报的实时检验、预报的跳跃性和不确定性角度分析了预报中存在的问题:预报员应重视本地和上游实况,从传统对单一确定性模式预报的依赖向多模式多起报时次及能提供概率预报和不确定性信息的业务集合预报的分析思路转型。此外,还需加强对集合预报的系统性检验、评估及数值预报释用产品的开发,增加包含不确定性信息的公众天气预报发布形式。     

A study of effectiveness of the ensemble long-term forecasts of spring floods issued with physically based models of the river runoff formation

In this paper, possible ways to increase effectiveness of the long-term ensemble spring floods forecasting and to assess their uncertainty based on the physical-mathematical model of the runoff formation (for the Vyatka River case study) are studied. It is shown that deterministic forecasts issued by using this approach are more accurate than those obtained from the traditional forecasting methods based on regression relationships. Probabilistic methods of forecasting of the spring flood volume and maximum discharge, which are issued by using various ways of the weather ensembles setting, are compared. Reliability of probabilistic forecasts of the volume and maximum discharge is estimated.     

Science and Prediction of Heavy Rainfall over China: Research Progress since the Reform and Opening-Up of New China

This paper reviews the major progress on development of the science and prediction of heavy rainfall over China since the beginning of the reform and opening-up of new China(roughly between 1980 and 2019). The progress of research on the physical mechanisms of heavy rainfall over China is summarized from three perspectives: 1) the relevant synoptic weather systems, 2) heavy rainfall in major sub-regions of China, and 3) heavy rainfall induced by typhoons. The development and application of forecasting techniques for heavy rainfall are summarized in terms of numerical weather prediction techniques and objective forecasting methods. Greatly aided by the rapid progress in meteorological observing technology and substantial improvement in electronic computing, studies of heavy rainfall in China have advanced to investigating the evolution of heavy-rain-producing storms and observational analysis of the cloud microphysical features. A deeper and more systematic understanding of the synoptic systems of importance to the production of heavy rainfall has also been developed. Operational forecast of heavy rainfall in China has changed from subjective weather event forecasts to a combination of both subjective and objective quantitative precipitation forecasts, and is now advancing toward probabilistic quantitative precipitation forecasts with the provision of forecast uncertainty information.