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1.
周康辉  郑永光  韩雷  董万胜 《气象》2021,47(3):274-289
近年来,机器学习理论和方法应用蓬勃发展,已在强对流天气监测和预报中广泛应用.各类机器学习算法,包括传统机器学习算法(如随机森林、决策树、支持向量机、神经网络等)和深度学习方法,已在强对流监测、短时临近预报、短期预报领域发挥了积极的重要作用,其应用效果往往明显优于依靠统计特征或者主观经验积累的传统方法.机器学习方法能够更...  相似文献   

2.
强对流天气监测预报预警技术进展   总被引:23,自引:8,他引:15       下载免费PDF全文
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。  相似文献   

3.
卫星风推导和应用综述   总被引:2,自引:3,他引:2       下载免费PDF全文
该文介绍了卫星风推导和应用的进展, 包括卫星风的算法, 卫星风在数值天气预报中的应用, 卫星风在天气分析和预报中的应用以及卫星风的研究工作动向。目前各个卫星数据处理中心卫星风的算法大体一致和稳定。风矢量的追踪用相关匹配法, 而风矢量的高度指定依靠双通道物理方法。卫星风的质量是从图像定位和定标开始的许多工作阶段的综合结果, 确保每个工作段的高质量对于风矢量的计算都十分重要。卫星风的高度指定仍然是最有挑战性的课题。因为物理定高方法进展不明显, 近期内尤其要重视几何定高技术的研究和使用。静止气象卫星的风对数值预报的影响在热带和南半球是正反馈; 由于在极地地区各种资料都十分匮乏, 极地卫星风对数值天气预报有非常明显的正反馈。卫星风与云图叠合显示, 在主要雨带、副热带高压、强对流和热带气旋的诊断、分布、预报中十分有用。  相似文献   

4.
The paper shows how much improvement can be achieved in weather forecasting by using NWP products. And for weather element forecasts, the types and number of NWP products highly impact on the quality of MOS forecasts and other utilities.  相似文献   

5.
After decades of research and development, the WSR-88 D(NEXRAD) network in the United States was upgraded with dual-polarization capability, providing polarimetric radar data(PRD) that have the potential to improve weather observations,quantification, forecasting, and warnings. The weather radar networks in China and other countries are also being upgraded with dual-polarization capability. Now, with radar polarimetry technology having matured, and PRD available both nationally and globally, it is important to understand the current status and future challenges and opportunities. The potential impact of PRD has been limited by their oftentimes subjective and empirical use. More importantly, the community has not begun to regularly derive from PRD the state parameters, such as water mixing ratios and number concentrations, used in numerical weather prediction(NWP) models.In this review, we summarize the current status of weather radar polarimetry, discuss the issues and limitations of PRD usage, and explore potential approaches to more efficiently use PRD for quantitative precipitation estimation and forecasting based on statistical retrieval with physical constraints where prior information is used and observation error is included. This approach aligns the observation-based retrievals favored by the radar meteorology community with the model-based analysis of the NWP community. We also examine the challenges and opportunities of polarimetric phased array radar research and development for future weather observation.  相似文献   

6.
崔玉玺 《气象》1987,13(6):3-6
介绍了我国数值预报格点资料及其在日常天气预报业务中的应用。简要说明了格点报资料的使用价值和分发形式的优点。指出随着数值天气预报和计算机技术的发展,格点资料对于天气预报业务的客观化和自动化,将越来越表现出重要作用。  相似文献   

7.
预报员在未来天气预报中的作用探讨   总被引:2,自引:0,他引:2  
章国材 《气象》2004,30(7):8-11
在没有数值天气预报的年代 ,天气预报是由预报员作出的 ,随着数值天气预报业务水平的不断提高 ,它首先取代了预报员的天气形势预报 ,目前正进入取代部分天气要素预报的时代。未来 1 0~ 2 0年中尺度数值天气预报和集合预报以及后处理技术将获得重大进展 ,客观预报有可能取代目前预报员的一些预报项目 ,但是预报员的作用仍然是不可缺少的 ,但需要按与时俱进的观点 ,认真分析客观预报与主观预报的最佳结合点 ,以不断提高天气预报水平  相似文献   

8.
A coupled atmospheric-hydrologic-hydraulic ensemble flood forecasting model,driven by The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) dat...  相似文献   

9.
重点围绕登陆热带气旋(LTC)降水预报研究进行了回顾和总结,指出针对LTC降水有三类预报技术:动力模式、统计方法和动力-统计结合的预报方法。以数值天气预报(NWP)模式为代表的预报技术对LTC降水的预报能力仍然非常有限。改进NWP模式预报误差的途径主要有两条:一是发展NWP模式;二是发展动力-统计结合的方法。分析表明,动力-统计相似预报是一项很有潜力的技术;针对现有研究中的不足,开展LTC降水动力-统计相似预报研究,探索减小数值模式LTC降水预报误差的有效方法,将是一个充满希望的研究领域和方向。  相似文献   

10.
该系统与Micaps工作平台设置接口,利用新技术所提供的各种图表工具和信息,对数值预报(NWP)形势场进行逐日反查分析比较,归纳出一些与临汾地区出现好雨相关好的形势场。对这些(NWP)形势场与08时实时资料形势场对应分析,确定高空环流型、低层影响系统及各层预报指标;分析各层物理量场分布特征、卫星云图的不同种类云系结构演变规律等建立模型。系统投入业务运行以来效果良好,提高了转折性天气预报准确率。  相似文献   

11.
盛夏数值预报模式对副高预报性能检验及其释用   总被引:2,自引:1,他引:1  
利用1998年6~8月T106和ECMWF数值预报产品,对副高预报能力和产品质量进行了全面检验;通过对数值预报产品加工处理后获取的有关参数和特征量进行综合分析,在业务预报中对重大天气预报实例进行释用。结果表明,ECMWF对副高增衰进退的运动趋势预报能力较强,对中期重大天气过程和雨区预报有重要指导意义。T10696小时预报基本可信,120小时以后预报能力锐减,是模式改进的重点  相似文献   

12.
In this paper, the model output machine learning (MOML) method is proposed for simulating weather consultation, which can improve the forecast results of numerical weather prediction (NWP). During weather consultation, the forecasters obtain the final results by combining the observations with the NWP results and giving opinions based on their experience. It is obvious that using a suitable post-processing algorithm for simulating weather consultation is an interesting and important topic. MOML is a post-processing method based on machine learning, which matches NWP forecasts against observations through a regression function. By adopting different feature engineering of datasets and training periods, the observational and model data can be processed into the corresponding training set and test set. The MOML regression function uses an existing machine learning algorithm with the processed dataset to revise the output of NWP models combined with the observations, so as to improve the results of weather forecasts. To test the new approach for grid temperature forecasts, the 2-m surface air temperature in the Beijing area from the ECMWF model is used. MOML with different feature engineering is compared against the ECMWF model and modified model output statistics (MOS) method. MOML shows a better numerical performance than the ECMWF model and MOS, especially for winter. The results of MOML with a linear algorithm, running training period, and dataset using spatial interpolation ideas, are better than others when the forecast time is within a few days. The results of MOML with the Random Forest algorithm, year-round training period, and dataset containing surrounding gridpoint information, are better when the forecast time is longer.  相似文献   

13.
基于模式约束三维变分技术的连续循环同化试验研究   总被引:3,自引:1,他引:2  
梁旭东  王斌 《气象学报》2010,68(2):153-161
由于模式约束三维变分同化技术中考虑了模式的动力和物理过程,因此能保证各物理量间的平衡关系,从而滤除由于观测资料引入导致的高频波动,减小模式与初始场的协调时间.由于能在较短时间调整到稳定状态,采用模式约束三维变分同化进行连续循环同化可用较少的计算量达到同化多时次的多种观测资料的目的.该研究利用模式约束三维变分技术,针对2006年"桑美"台风个例,进行了连续循环同化卫星云导风、QuikSCAT海面风、Bogus海平面气压的试验.在台风数值预报中往往需要使用经验构造的台风信息(如Bogus海平面气压,Bogus风场等),该研究采用了模式约束三维变分同化技术同化Bogus海平面气压.由于模式约束三维变分同化技术充分考虑了各物理量间的约束,因此通过同化Bogus海平面气压也调整了初始场中相应的高度场、温度场、风场等变量,使得初始场中的台风涡旋具有较强的协调性,提高了对台风的模拟能力.采用AVN模式6小时间隔的分析场作为侧边界,2006年8月8日20时的分析场作为初估场,文中对8月8日20时到9日05时"桑美"台风的观测资料进行了连续循环同化.采用连续循环同化后台风路径的模拟精度得到了显著提高,对台风降水结构等的模拟也得到了改善.  相似文献   

14.
在三峡地区降水条件气候均匀区域划分的基础上,用Atlas一阶矩概率匹配法,分别在每一个区域建立了对流型、雷雨混合型、阵雨混合型3种雨型随测距变化的气候Z-R关系。这些关系能综合订正由波束平均作用、雨区对电磁波的衰减等因素所造成的雷达测量降水的误差  相似文献   

15.
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  
杨波  郑永光  蓝渝  周康辉  刘鑫华  毛旭 《气象》2017,43(7):845-855
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   

16.
国家气象中心针对强天气预报的特点开发了强天气模式诊断变量和概率预报产品,包括T639全球模式强天气诊断变量产品、基于GRAPES_RUC的中尺度精细化强天气诊断变量产品、基于WRF中尺度模式的区域中尺度集合概率预报产品,于2009年从无到有建立了一套完整的强天气数值预报产品库,提供确定性预报产品和不确定信息的概率产品,为强天气预报业务的开展打下了良好的基础。应用上述产品对"6.3"河南飑线天气的模式预报能力的分析表明,高分辨率模式对强对流天气的预报能力有了较大的提高,但对于强天气预报,15km分辨率仍然不足够高,且产品显示的时空分辨率都应在现有基础上提高,才能更好地展示数值预报产品对强对流过程发生发展和演变过程。  相似文献   

17.
使用INCA(Integrated Nowcasting through Comprehensive Analysis)多源资料融合分析和短临外推预报系统的预报结果作为气象强迫场,驱动一路面温度理论预报模型(Model of the Environment and Temperature of Roads,METRo),开展江苏省高速公路夏季路面高温预报试验,并使用公路沿线逐小时的路面温度观测资料对预报结果进行检验。结果表明:该预报方法能够较好地预报出高速公路沿线日最高路面温度的逐日变化趋势,以及日最高路面温度的大范围空间分布特征。平均日最高路面温度预报绝对偏差为4.1℃,平均相对偏差为10.8%。其中,日最高路面温度预报绝对偏差在5℃以内的站次占总数的64.5%,相对偏差在15%以内的站次占总数的74.6%,比常规业务预报方法分别提高了23.1%和25.3%。但该预报方法对较小的温度波动以及局地性较强的极端温度分布特征的预报技巧还需进一步提高。  相似文献   

18.
This article describes a new general circulation model (GCM) developed jointly by The University of New South Wales (UNSW) and the University of Hamburg. The model is versatile in that it can be run as a medium-range (1 to 15 days) global numerical weather prediction (NWP) model; as an extended range (15 to 30 days) NWP model; and as a GCM for periods extending from seasons, through annual and decadal periods, and beyond. The model can be coupled with ocean models that vary in complexity from simple "swamp" oceans to complex ocean GCMs. The atmospheric GCM also has a number of novel features, particularly in the numerical integration scheme which is a high-order, mass-conserving, semi-implicit semi-Lagrangian scheme, thereby removing the stability restriction on the time-step and allowing efficient long-term integrations. The emphasis here will be on demonstrating that the new model performs effectively on the usual measures of skill (statistics such as mean errors, root-mean-square errors and anomaly correlations) in several standard applications upon which new models usually are assessed. These applications include medium range weather forecasts out to 10 days on a daily basis over a one year period; a limited 10-year simulation climatology, prediction of atmospheric anomalies using SST anomalies in an El Nino year; and an alternative two-way approach to regional modelling (the "down-scaling problem") made possible because the unconditional stability of the semi-implicit, semi-Lagrangian formulation permits large variations in grid spacing without changing the time step size. Finally, the model is run on a variety of parallel computing platforms and it is shown that near-linear speed-up can be attained. This is significant for both medium range NWP and very long-term GCM integrations. Received: 28 February 1996 / Accepted: 30 July 1996  相似文献   

19.
The Atmospheric Boundary Layer Over Baltic Sea Ice   总被引:4,自引:0,他引:4  
A new parametrization for the surface energy balance of urban areas is presented. It is shown that this new method can represent some of the important urban phenomena, such as an urban heat island and the occurrence of a near-neutral nocturnal boundary layer with associated positive turbulent heat fluxes, unlike the traditional method for representing urban areas within operational numerical weather prediction (NWP) models. The basis of the new parametrization is simple and can be applied easily within an operational NWP model. Also, it has no additional computational expense compared to the traditional scheme and is hence applicable for operational forecasting requirements. The results show that the errors for London within the Met Office operational mesoscale model have been significantly reduced since the new scheme was introduced. The bias and root-mean-square (rms) errors have been approximately halved, with the rms error now similar to the model as a whole. The results also show that a seasonal cycle still exists in the model errors, but it is suggested that this may be caused by anthropogenic heat sources that are neglected in the urban scheme.The British Crowns right to retain a non-exclusive royalty-free license in and to any copyright is acknowledged.  相似文献   

20.
基于聚类天气分型的KNN方法在风预报中的应用   总被引:5,自引:1,他引:4       下载免费PDF全文
以模式识别和相似预报思想为基础, 建立基于自组织神经网络 (SOM) 的聚类天气分型和交叉验证的K最近邻域非参数估计仿真模型 (KNN)。该模型首先以自组织神经网络技术对西北地区的高空流场和高度场进行聚类分型, 针对不同天气形势下的历史样本, 通过交叉检验, 分别寻求各类天气型下的最佳K组合。为了验证聚类天气分型对KNN方法的影响, 使用2003—2006年冬半年T213数值预报产品和宁夏日最大风速资料, 同时建立了宁夏冬半年日最大风速≥6 m/s天气分型和未分型的KNN预报模型, 并对2007年1—5月进行了预报试验, 预报评估结果表明:天气分型后的预报模型总体上降低了预报空报率, 提高了预报准确率, 特别是某些类天气型, 提高幅度更大, 为分类相似预报开拓了思路。  相似文献   

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