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研究设计了基于生成对抗网络(Generative Adversarial Networks,GAN)的人工智能临近预报方法,并进行了业务试验。该方法利用广东12部S波段天气雷达2015—2017年海量雷达拼图资料进行人工智能学习来做临近预报。GAN方法从一系列雷达观测资料中,运用卷积法提取回波图像信息建立预报模型,并通过损失函数训练模型,得到基于人工智能技术的临近预报。对2018年发生在广东地区的4个天气过程的外推预报试验表明,GAN方法对对流天气过程的回波位置、形状及强度的临近预报多数情况下与实况基本一致,具有较好的预报效果。但是该方法预报的回波范围偏大,对层状云降水的预报效果较差。对西风带系统引起的降水,西南季风降水,东风系统引起的降水以及台风降水的18个个例1 h预报的3个级别的回波强度检验发现,GAN方法对中等强度回波的预报较好,但对强回波的预报效果仍有待提高。 相似文献
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A. Fernndez-Ferrero J. Senz G. Ibarra-Berastegi J. Fernndez 《Atmospheric Research》2009,94(3):448-461
The objective of this study is to compare several statistical downscaling methods for the development of an operational short-term forecast of precipitation in the area of Bilbao (Spain). The ability of statistical downscaling methods nested inside numerical simulations run by both coarse and regional model simulations is tested with several selections of predictors and domain sizes. The selection of predictors is performed both in terms of sound physical mechanisms and also by means of “blind” criteria, such as “give the statistical downscaling methods all the information they can process”.Results show that the use of statistical downscaling methods improves the ability of the mesoscale and coarse resolution models to provide quantitative precipitation forecasts. The selection of predictors in terms of sound physical principles does not necessarily improve the ability of the statistical downscaling method to select the most relevant inputs to feed the precipitation forecasting model, due to the fact that the numerical models do not always fulfil conservation laws or because precipitation events do not reflect simple phenomenological laws. Coarse resolution models are able to provide information usable in combination with a statistical downscaling method to achieve a quantitative precipitation forecast skill comparable to that obtained by other systems currently in use. 相似文献
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M. A. Novitskii Yu. B. Pavlyukov B. Ya. Shmerlin S. V. Makhnorylova N. I. Serebryannik S. A. Petrichenko L. A. Tereb O. V. Kalmykova 《Russian Meteorology and Hydrology》2016,41(10):683-690
The possibility of advance tornado warning is analyzed. The tornado observed in Bashkortostan on August 29, 2014 is considered as an example. To compute meteorological fields, the WRF model with high spatiotemporal resolution is used. Indices of convective instability are calculated. The analysis of variations in indices enabled forecasting the tornado generation with the lead time up to three days and with the accuracy up to several hours in time and 200 km in space. The possibility is demonstrated of registering and nowcasting tornados by using the available software for radar data processing. The polential is discussed of the joint use of such information for developing the syslem of monitoring and forecasting of severe weather events including tornados. 相似文献
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快速更新循环同化预报系统的汛期试验与分析 总被引：14，自引：6，他引：8
为了支持短时临近预报,利用新一代数值预报技术,结合高时空分辨的新一代探测所提供的观测信息,开发了基于快速更新循环同化的数值预报系统。基于GRAPES预报模式及其三维变分,开发了逐时循环同化,包括雷达、卫星、飞机、常规地面和探空等观测资料的同化模块,并采用nudging技术,引入雷达回波,订正模式的初始云水、雨水等信息,实现快速更新预报。多种测试和汛期连续试验表明,系统运行稳定可靠。逐时同化场合理,与实况基本一致。通过1个月的滚动预报综合分析和个例预报分析均表明,预报稳定有效,与观测分布基本一致,初步具备开展短时临近预报的能力。 相似文献
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为了提高人工增雨作业的作业水平和增雨效率,利用2010—2012年徐州市人工增雨作业中的多种观测资料,在分析徐州地区地形特征、增雨作业习惯的基础上,研究出适合本地区使用的人工增雨效果检验方法,建立人工增雨潜势分析模型,对未来12h的人工增雨潜势和临近增雨潜势进行逐步分级判断,将增雨潜势区分为两级:级别Ⅰ增雨潜势较小和级别Ⅱ增雨潜势较大,并指导人工增雨作业。2013年徐州人工增雨作业实践表明,人工增雨12h潜势预报模型和临近预报模型具有较高的准确率。以增雨潜势预报模型为基础,修改徐州地区人工增雨作业流程,提高指挥人员的工作效率,并提高人工增雨作业的效率。 相似文献
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强对流天气短时临近预报业务技术进展与挑战 总被引：20，自引：5，他引：15
强对流天气短时临近预报业务是国家防灾减灾、重大社会活动和精细化天气预报的迫切需要。虽然我国强对流天气短时临近预报业务已经取得了巨大进展,但与国外先进水平相比还有不少差距。本文总结了近年国内外强对流天气短时临近预报业务现状、技术进展、目前国内的技术支撑状况和所面临的挑战,并提出了相应的应对措施。目前强对流天气短时临近预报技术仍然主要是外推预报技术、数值预报技术和概念模型预报技术等,但快速更新循环的高时空分辨率数值模式预报和新一代静止气象卫星资料将在强对流天气短时临近预报中发挥重要作用。强对流天气监测、分析和机理研究是强对流天气短时临近预报的重要基础;先进的外推预报方法同快速更新循环的高时空分辨率数值模式预报以及二者的融合是未来强对流天气短时临近预报的重要发展方向。 相似文献
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A strong tornado hit seven cities of northern France in the late evening of Sunday, 3 August 2008, causing severe damage along its 19 km path from Pont-sur-Sambre to Boussois. Three people were killed in the collapse of their house and 18 were injured. More than 1000 houses were damaged and several thousand trees were uprooted or fallen down.The authors led a damage survey in the hours that followed the disaster, then investigated this case, in order to determine the characteristics of this tornado precisely and to better understand the conditions that led to its formation. Weather radar analysis shows that the convective cell that gave rise to the tornado took on a fairly pronounced S-shaped structure, with a persistent mesocyclone in the central part of the convective system. The synoptic and mesoscale pattern associated with this severe storm was very dynamic, and characterized by a coupling between a low-level jet and a highly divergent jet-stream. The authors have reconstructed a vertical profile for this case study, in order to describe the tornadic environment precisely. The reconstructed profile reveals two main elements, namely an environment having a very modest vertical instability on one hand, and the presence of intense wind shear, notably in the lowest layers of the atmosphere on the other hand. This conclusion is supported by the analysis of many instability and shear parameters. 相似文献
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强对流天气短时临近预报系统（Severe Weather Automatic Nowcasting,SWAN）是面向短时临近监测、分析、预报、预警制作等功能为一体的业务平台。SWAN2.0基于MICAPS4（Meteorological Information Comprehensive Analysis and Processing System Version 4.0,人机交互气象信息处理和天气预报制作系统）二次开发框架,采用C/S架构,服务器部署在省级,负责收集数据,运算SWAN产品;客户端部署在气象台站,实现具体的预报业务,并形成算法二次开发接口。SWAN2.0新增了三维变分风场反演、基于分雨团技术的雷达降水估测、冰雹识别等方法,实现了算法管理、产品生成、分析处理、资料检索显示、实时监控报警、预警产品制作等功能。SWAN2.0业务系统已在全国试用,在强对流天气监测、分析和短时临近预报预警中发挥了重要作用。 相似文献
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采用2004年Casati提出的强度-尺度检验技术,选取2008年汛期代表不同类型降水(对流云降水、层状云降水、混合云降水)的4个降水过程,从尺度分解角度入手,对"世界气象组织天气研究计划——北京奥运会预报示范项目"(WWRP B08FDP)项目中4个I临近预报参加系统(BJANC,GRAPES-SWIFT,STEPS,CARDS)的1h定量降水预报进行时空尺度分解检验,研究降水预报技巧与降水时空尺度和强度之间的关系。结果表明:尽管目前国际先进的临近预报系统的水平分辨率已高达1～2km,但其有技巧的临近预报能力主要集中于空间尺度大于32km、时间尺度大于1h的降水系统,而对小于这些尺度的降水系统预报能力仍非常有限;在不同时空尺度的临近预报降水误差中,60%以上的误差来自于空间尺度小于8km的降水,85%以上的误差来自于时间尺度小于1h的降水,传统的外推技术不能满足这些较小时空尺度降水预报的需求,要发展有效的预报方法来提高较小时空尺度降水的预报能力。将基于外推的临近预报和基于稠密观测资料、快速更新的数值预报的潜势预报相结合可能是一条有效的解决途径。 相似文献
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四川省防雷中心自主研发了多因子融合雷电短临预警系统,并投入业务试运行.协助中国气象科学院研制开发了CAMS_LNWS雷电临近预警系统,并进行本地化处理和业务试用.对两个系统进行了简要介绍,并就应用情况进行了比较分析.结果表明：两个系统均具有较强的雷电预警能力,对19次雷电天气过程预警的TS评分,平均超过0.75.在实际应用中发现：CAMS_LNWS系统对未来新生雷电活动有更强的预警能力,而多因子融合短临预警系统则对已经出现雷电的移动路径和未来发展趋势有更好的预警效果,两者之间的结合应用为四川省雷电短临预警提供了技术支撑. 相似文献
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Lu YANG Cong-Lan CHENG Yu XIA Min CHEN Ming-Xuan CHEN Han-Bin ZHANG Xiang-Yu HUANG 《大气科学进展》2023,40(5):937-951
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... 相似文献
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短临降水预报是一项重要且具有挑战性的世界性难题.研究人员曾尝试使用各种技术预报降水,但是由于降水本身具有高度非线性、随机性和复杂性的特性,使得降水预测精确度并不高.近年来,随着人工智能技术的迅猛发展,其日渐渗透到人们生活的方方面面,气象领域也因此得益.人工神经网络能够对非线性系统进行建模,因此相比于传统方法,如数值天气预报法和光流法等,人工智能方法使得降水预报的准确率大大提高.本文介绍了传统降水预报的方法,着重总结概括了用于短临降水预报的各种最新人工智能方法,并对各研究方向进行归纳分析,为各类研究人员研究提供有益参考和借鉴. 相似文献
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Sounding-derived indices for neural network based short-term thunderstorm and rainfall forecasts 总被引：1，自引：0，他引：1
A neural network-based scheme to do a multivariate analysis for forecasting the occurrence and intensity of a meteo event is presented. Many sounding-derived indices are combined together to build a short-term forecast of thunderstorm and rainfall events, in the plain of the Friuli Venezia Giulia region (hereafter FVG, NE Italy).For thunderstorm forecasting, sounding, lightning strikes and mesonet station data (rain and wind) from April to November of the years 1995–2002 have been used to train and validate the artificial neural network (hereafter ANN), while the 2003 and 2004 data have been used as an independent test sample. Two kind of ANNs have been developed: the first is a “classification model” ANN and is built for forecasting the thunderstorm occurrence. If this first ANN predicts convective activity, then a second ANN, built as a “regression model”, is used for forecasting the thunderstorm intensity, as defined in a previous article.The classification performances are evaluated with the ROC diagram and some indices derived from the Table of Contingency (like KSS, FAR, Odds Ratio). The regression performances are evaluated using the Mean Square Error and the linear cross correlation coefficient R.A similar approach is applied to the problem of 6 h rainfall forecast in the Friuli Venezia Giulia plain, but in this second case the data cover the period from 1992 to 2004. Also the forecasts of binary events (defined as the occurrence of 5, 20 or 40 mm of maximum rain), made by classification and regression ANN, were compared. Particular emphasis is given to the sounding-derived indices which are chosen in the first places by the predictor forward selection algorithm. 相似文献
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The EU accession countries have a high potential for low cost greenhouse gas emission reduction. As they cannot join the “bubble” agreement for the first commitment period of the Kyoto Protocol, project-based Joint Implementation (JI) could be a powerful strategy to integrate them into the EU climate policy strategy. An important question is whether the acquis communautaire will be used to define the baseline for the calculation of emission reductions from JI projects. A problem is that the grace periods for several environmental sectors differ considerably among countries. The EU should help accession countries to establish a predictable legal framework for JI preventing in this way the current legal uncertainty regarding JI procedures. 相似文献
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门可佩 《南京气象学院学报》2014,6(2):175-181
根据1827年以来的统计资料进行分析,长江流域大洪水展示出极为显著的有序性.运用翁文波信息预测理论,构建长江大洪水二维平面和三维立体信息有序网络结构并进行综合分析和预测,结果表明：2014、2020、2030、2036、2051与2058年前后的汛期,长江流域将有可能发生大洪水. 相似文献
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THE INFLUENCE OF CLOUD PARAMETERIZATION ADJUSTMENT USING REFLECTIVITY OF DOPPLER ON NOWCASTING WITH GRAPES MODEL 总被引：1，自引：0，他引：1
In this study, we attempted to improve the nowcasting of GRAPES model by adjusting the model initial field through modifying the cloud water, rain water and vapor as well as revising vapor-following rain water. The results show that the model nowcasting is improved when only the cloud water and rain water are adjusted or all of the cloud water, rain water and vapor are adjusted in the initial field. The forecasting of the former （latter） approach during 0-3 （0-6） hours is significantly improved. Furthermore, for the forecast for 0-3 hours, the latter approach is better than the former. Compared with the forecasting results for which the vapor of the model initial field is adjusted by the background vapor with those by the revised vapor, the nowcasting of the revised vapor is much better than that of background vapor. Analysis of the reasons indicated that when the vapor is adjusted in the model initial field, especially when the saturated vapor is considered, the forecasting of the vapor field is significantly affected. The changed vapor field influences the circulation, which in turn improves the model forecasting of radar reflectivity and rainfall. 相似文献
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由于能见度具有局地性和复杂的非线性变化特征,一直是精细化预报的难点。人工神经网络对复杂变化过程的模拟能力较高,为解决这一难题提供了可能性。本文采用循环神经网络,利用福州气象观测站地面观测数据,建立了福州单站能见度短临预报模型,并就预报能力进行了评估。随机检验结果表明,在1 h、3 h、6 h时效上,循环神经网络的预报与观测的变化趋势一致性较好;均方根误差比基于实况的预报分别减小15.75%、31.66%、41.26%,说明具备较好的预报能力;平均绝对值误差比传统BP神经网络分别减小12.90%、24.45%、 38.99%,表明循环神经网络对能见度预报具有优势,为能见度的精细化短临预报提供了新途径。 相似文献