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世界各国和各地区的环境预报中心的主要任务是向本国、本地区和全球公众发布科学的环境预报,包括天气、水、气候和空间天气的预报。气象学家与其他科学家合作,一起制作可靠、及时、准确的分析结果、指导意见、预报及预警,以确保人们的生命和财产安全,促进全球经济的发展,以满足人们日益增长的对环境信息的需求。为了更准确地制作预报、更好地服务大众以及最大限度地减少生命和财产损失,这里提出了"预报科学"思想。预报科学包括现代观测系统的资料收集、观测与预报信息的实时交流、各种科学技术的发展、无缝隙预报以及公共服务等。预报科学可以概括为三个相互独立的部分,即科学性、工程性和艺术性,且三者存在相互作用。总之,天气预报是大气与环境服务的重要组成部分;预报科学的科学性、工程性和艺术性均服务于天气预报、服务于人民。 相似文献
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美国国家天气局宣布，其制作15天天气预报的天气与气候模式有重大改进。2005年9月，美国国家天气局环境模拟中心开始提供更精细的大气信息，这些信息能帮助预报员提高预报准确度。随后，美国国家天气局对其全球预报系统（GFS：Global Forecast System）进行了升级，该系统是其用来预报全球天气形势的主要模式。美国国家天气局的各种天气预报均使用该模式，例如飓风预报、暴雨预报、干旱预报、雪暴预报、冰况预报以及航空预报。 相似文献
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随着计算机技术的飞速发展和人们对大气运动过程的深入了解,特别是随着近年来中尺度数值天气预报的业务化,高分辨率的包含复杂物理过程的中尺度业务预报模式已成为1990年以来数值天气预报发展的方向.预报员在实际业务工作中可参考的指导产品不仅有大尺度的天气形势信息,还包括各种中尺度及地面气象要素在内的大气运动的物理参数,从而以数值天气预报产品为基础的数值天气预报释用水平也得以提高.这不仅使得预报员能更方便地利用数值天气预报产品制作当地的各种天气及要素预报,而且使得气象服务更加准确及时.该文对武汉气象中心数值天气预报释用系统(以下简称系统)的开发环境、特点、技术方法和应用情况作了介绍. 相似文献
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（一）WEATHEAROFFICE（CA－NADAINAWEATHER）加拿大天气。这是由加拿大环境部主办的天气网站。网站分为加拿大天气、美国天气和世界天气三大版块,每个版块都包括该地区中大多数城市的天气预报、天气图形图表等多种信息。此外,该网站还设立了公众天气警报、天气产品商店（Weatherstore）等栏目。公众天气警报提供详实的灾害性天气的追踪实况观测和预报信息,同时提供付费的电话预报服务。“天气商店”是一个非常有意思的栏目,它包括广告服务、常规天气产品、专业转项预报、气候服务、水文服务、冰况分析服务、电话咨询等多… 相似文献
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天气研究与预报预警业务系统利用9210工程等现代化建设成果,发挥计算机技术优势和MICAPS平台的功能和作用,充分挖掘天气预报信息资源提高天气分析、研究和预报能力,推进天气预报由人工向计算机智能化方向发展以及天气预报的精细化制作与显示等方面积极探索,为开展天气预报研究和预报业务提供了有益的工具,对于提高气象预报服务水平具有积极作用。 相似文献
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近10年中国现代天气预报的发展与应用 总被引：5，自引：1，他引：4
近10年来,随着数值预报技术的进步,探测手段的日臻完善和丰富,以及高性能计算机快速发展和应用,现代天气预报技术取得了显著的进步,其中快速更新同化分析和预报、集合预报、概率预报以及数字化预报等新技术的应用,促进了中国天气预报业务水平的提高,在中国防灾减灾、保障社会经济发展和人民安康福祉的气象服务中发挥了重要作用。回顾和介绍了近10年中国现代天气预报新技术,主要包括基于中尺度模式的多源资料快速更新同化预报技术,提供灾害性、极端性天气预报的不确定性信息的集合预报和概率预报技术及高时空分辨率气象要素的数字化预报技术,展望未来发展趋势,以期能够对未来天气预报技术发展提供借鉴和参考。 相似文献
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In this study, the statistical post-processing methods that include bias-corrected and probabilistic forecasts of wind speed measured in PyeongChang, which is scheduled to host the 2018 Winter Olympics, are compared and analyzed to provide more accurate weather information. The six post-processing methods used in this study are as follows: mean bias-corrected forecast, mean and variance bias-corrected forecast, decaying averaging forecast, mean absolute bias-corrected forecast, and the alternative implementations of ensemble model output statistics (EMOS) and Bayesian model averaging (BMA) models, which are EMOS and BMA exchangeable models by assuming exchangeable ensemble members and simplified version of EMOS and BMA models. Observations for wind speed were obtained from the 26 stations in PyeongChang and 51 ensemble member forecasts derived from the European Centre for Medium-Range Weather Forecasts (ECMWF Directorate, 2012) that were obtained between 1 May 2013 and 18 March 2016. Prior to applying the post-processing methods, reliability analysis was conducted by using rank histograms to identify the statistical consistency of ensemble forecast and corresponding observations. Based on the results of our study, we found that the prediction skills of probabilistic forecasts of EMOS and BMA models were superior to the biascorrected forecasts in terms of deterministic prediction, whereas in probabilistic prediction, BMA models showed better prediction skill than EMOS. Even though the simplified version of BMA model exhibited best prediction skill among the mentioned six methods, the results showed that the differences of prediction skills between the versions of EMOS and BMA were negligible. 相似文献
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国家级强对流天气综合业务支撑体系建设 总被引：1，自引：2，他引：1
国家级强对流天气预报业务正在从以短期预报为主调整到短期和短时预报并重的业务格局。文章从强对流天气预报技术发展与服务需求的角度,重点介绍了国家级强对流天气综合业务支撑平台及其核心技术。该平台以气象数据组织和图形化表达两个核心要求为牵引,发展了数据分析处理系统、自动气象绘图系统和WEB检索与显示系统。数据分析处理系统基于多源观测资料、中尺度数值预报和全球数值预报,发展了集约、高效的强对流天气监测和临近预报、短时预报和短期预报等数据分析处理技术,是整个平台的核心;主要核心技术包括:从不稳定与能量、水汽、抬升与垂直风切变等条件出发,以归纳总结的分类强对流天气概念模型为基础的分类强对流短期预报分析技术;应用"配料法"发展的分类分等级的强对流天气客观概率预报技术;强对流短时预报技术包括高分辨率数值预报释用、多模式预报集成、对流尺度分析、实况和模式探空分析等多项技术,重点实现了从过去3 h实况到未来12 h预报的无缝隙衔接;强对流的监测和临近预报技术在基于多源资料的强对流天气实况与强对流系统监测技术基础上,发展了基于雷达特征量、强对流实况、各类强对流指数和预警信号等多源信息的报警技术。自动气象绘图系统实现了高效、便捷地接入多种数据、自动进行数据分析和制图等多项功能。在预报服务方面,基于WebGIS发展了县级分类强对流预警信号和国家级分类强对流预警预报产品共享技术,实现强对流短时预报业务的高交互性与上下互通的功能。 相似文献
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集合预报在数值天气预报体系中具有重要地位，因此如何有效提取集合样本信息以提高集合预报技巧一直是一个重要课题。基于中国全球集合预报业务系统（GRAPES-GEPS）的500 hPa高度场集合资料开展对环流集合预报的分类释用方法研究，并对集合聚类预报结果进行了检验分析。通过在传统Ward聚类法中引入动态聚类的“手肘法”方案，发展了环流集合预报分类释用方法。针对该方法的个例分析表明，对于中国中东部地区环流集合预报的聚类释用方法能够有效地划分出最有可能发生的环流形势类型并提供发生概率。确定性预报综合检验结果显示，集合预报聚类结果中发生概率最高的集合大类相对于集合平均的预报技巧有明显提升，并随着预报时效的延长提升更明显。总体来看，通过集合预报的分类释用方法划分环流形势类型可以为天气预报提供参考依据，具有实际应用价值。 相似文献
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Keunhee Han JunTae Choi Chansoo Kim 《Asia-Pacific Journal of Atmospheric Sciences》2016,52(5):495-507
As the 2018 Winter Olympics are to be held in Pyeongchang, both general weather information on Pyeongchang and specific weather information on this region, which can affect game operation and athletic performance, are required. An ensemble prediction system has been applied to provide more accurate weather information, but it has bias and dispersion due to the limitations and uncertainty of its model. In this study, homogeneous and nonhomogeneous regression models as well as Bayesian model averaging (BMA) were used to reduce the bias and dispersion existing in ensemble prediction and to provide probabilistic forecast. Prior to applying the prediction methods, reliability of the ensemble forecasts was tested by using a rank histogram and a residualquantile-quantile plot to identify the ensemble forecasts and the corresponding verifications. The ensemble forecasts had a consistent positive bias, indicating over-forecasting, and were under-dispersed. To correct such biases, statistical post-processing methods were applied using fixed and sliding windows. The prediction skills of methods were compared by using the mean absolute error, root mean square error, continuous ranked probability score, and continuous ranked probability skill score. Under the fixed window, BMA exhibited better prediction skill than the other methods in most observation station. Under the sliding window, on the other hand, homogeneous and non-homogeneous regression models with positive regression coefficients exhibited better prediction skill than BMA. In particular, the homogeneous regression model with positive regression coefficients exhibited the best prediction skill. 相似文献
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Lei HAN Mingxuan CHEN Kangkai CHEN Haonan CHEN Yanbiao ZHANG Bing LU Linye SONG Rui QIN 《大气科学进展》2021,38(9):1444-1459
Correcting the forecast bias of numerical weather prediction models is important for severe weather warnings. The refined grid forecast requires direct correction on gridded forecast products, as opposed to correcting forecast data only at individual weather stations. In this study, a deep learning method called CU-net is proposed to correct the gridded forecasts of four weather variables from the European Centre for Medium-Range Weather Forecast Integrated Forecasting System global model(ECMWF-IFS): 2-m temperature, 2-m relative humidity, 10-m wind speed, and 10-m wind direction, with a forecast lead time of 24 h to 240 h in North China. First, the forecast correction problem is transformed into an image-toimage translation problem in deep learning under the CU-net architecture, which is based on convolutional neural networks.Second, the ECMWF-IFS forecasts and ECMWF reanalysis data(ERA5) from 2005 to 2018 are used as training,validation, and testing datasets. The predictors and labels(ground truth) of the model are created using the ECMWF-IFS and ERA5, respectively. Finally, the correction performance of CU-net is compared with a conventional method, anomaly numerical correction with observations(ANO). Results show that forecasts from CU-net have lower root mean square error, bias, mean absolute error, and higher correlation coefficient than those from ANO for all forecast lead times from 24 h to 240 h. CU-net improves upon the ECMWF-IFS forecast for all four weather variables in terms of the above evaluation metrics, whereas ANO improves upon ECMWF-IFS performance only for 2-m temperature and relative humidity. For the correction of the 10-m wind direction forecast, which is often difficult to achieve, CU-net also improves the correction performance. 相似文献
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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. 相似文献
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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。 相似文献
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关于提高天气预报准确率的几个问题 总被引：10，自引：0，他引：10
提高天气预报准确率是气象业务的一项基础性、系统性的工作。作者从天气预报的业务技术体系着眼,借鉴发达国家的发展经验,分析了提高天气预报准确率的若干问题,提出了发展精细化的预报技术体系,将数值预报模式、天气学预报方法、动力诊断和统计释用及基于卫星和雷达等现代探测技术的短时临近预警技术相结合的预报技术路线;提出了有利于精细化预报的业务体系,即发展以定量降水预报、台风预报和灾害性天气短时临近预警为重点的专业化预报业务体系;指出专家型预报队伍的建设是提高预报业务水平的关键环节。 相似文献