The Development of a Nonhydrostatic Global Spectral Model

With the development of numerical weather prediction technology,the traditional global hydrostatic models used in many countries of the world for operational weather forecasting and numerical simulations of general circulation have become more and more unfit for high-impact weather prediction.To address this,it is important to invest in the development of global nonhydrostatic models.Few existing nonhydrostatic global models use consistently the grid finite difference scheme for the primitive equations of dynamical cores,which can subsequently degrade the accuracy of the calculations.A new nonhydrostatic global spectral model,which utilizes the Eulerian spectral method,is developed here from NCAR Community Atmosphere Model 3.0(CAM3.0).Using Janjic's hydrostatic/nonhydrostatic method,a global nonhydrostatic spectral method for the primitive equations has been formulated and developed.In order to retain the integrity of the nonhydrostatic equations,the atmospheric curvature correction and eccentricity correction are considered. In this paper,the Held-Suarez idealized test and an idealized baroclinic wave test are first carried out,which shows that the nonhydrostatic global spectral model has similar climate states to the results of many other global models for long-term idealized integration,as well as better simulation ability for short-term idealized integration.Then,a real case experiment is conducted using the new dynamical core with the full physical parameterizations of subgrid-scale physical processes.The 10-day numerical integration indicates a decrease in systematic error and a better simulation of zonal wind,temperature,and 500-hPa height.     

Meso-gamma scale forecasts using the nonhydrostatic model LM

Summary ?The nonhydrostatic model LM was developed for small scale operational predictions. Advances in computer development will give the possibility of operational models of a rather fine scale, which will cover the meso-gamma scale. The LM is currently applied at a scale of 7 km and an increase of the operational resolution to 2.5 km is planned for the next few years. Predictions of such high resolution require to abandon the hydrostatic assumption, which is used with most current operational weather prediction models. The LM was designed to cover all resolutions from 50 m to 50 km with an efficiency making it suitable for operational use. It is a fully elastic model, using second order centred finite differences. The time integration is done using the Klemp–Wilhelmson method, treating the slow modes by a larger time step than the fast modes. The vertical propagation of the fast waves is done implicitly. After describing the design of the LM, this paper gives examples of model predictions at the meso-γ scale. Some results of the current operational application at the resolution 7 km are presented. Deficiencies in the localisation of model generated precipitation are investigated using an idealised bell shaped mountain and applying different resolutions. In this way the convergence to the correct solution can be investigated. From these results it is concluded, that orographic filtering is necessary and the effect of such filtering on precipitation forecasts is investigated. Finally, the prediction of a squall line over northern Germany is shown in order to demonstrate the potential of the model in forecasting the meso-γ scale. Received May 15, 2001; revised September 21, 2001     

Application of numerical weather prediction techniques in the operational routine of the hydrometeorological service of the USSR

The purpose of the present paper is to review the application of numerical weather prediction techniques in the daily operational routine of the Hydrometeorological Service of the USSR. The theoretical aspects of numerical weather prediction models used have been discussed by the authors in original papers and will not, therefore, be repeated here.     

高性能计算技术在气象领域的应用

高性能计算通过应用超级计算机与并行处理技术解决复杂的计算问题,是信息技术发展比较迅猛的领域之一。气象应用始终是高性能计算的重要领域,高性能计算技术有效地解决了高分辨率、高精度气象数值预报模式发展限制,在气象预报预测业务中发挥着核心支撑作用。数十年以来,由于数值天气模式研究和业务运行对计算资源的强烈需求,国内外气象领域高性能计算机及应用迅速发展起来。气象领域对高性能计算能力及系统的可靠性需求日益提升。高性能计算技术将与气象预报应用日益融合,相互影响促进,不断创新发展。为满足气象预报预测业务和科研工作需求,中国气象部门将进一步提升高性能计算能力,并致力于优化集约高性能计算系统布局,高效管理计算资源,发挥最大效益。     

数值天气预报———另类途径的必要性和可行性

通过讨论省 (甚至地、市) 气象部门要不要开展数值天气预报工作的问题, 认为不是所有的地方都要开展, 只是那些希望搞科研型业务、迫切要求提高当地高影响天气的预报准确率的地方要开展。对于如何开展的问题, 提出不是去重复类似于主流途径的做法, 而是开辟另类途径, 并阐述了另类途径的内容、方法和意义。强调开展另类途径无需构建模式 (这是非常困难的工作), 只需运转现成的模式, 借助所关心的现象的历史数据来改造现成模式, 使之本地化, 是完全可行的。     

Evaluating the impact of lightning data assimilation on mesoscale model simulations of a flash flood inducing storm

Flash floods are associated with highly localized convective storms producing heavy rainfall. Quantitative precipitation forecasting of such storms will potentially benefit from explicit representations of deep moist convection in numerical weather prediction models. However, explicit representation of moist convection is still not viable in operational mesoscale models, which rely on convective parameterizations for issuing short to medium-range forecasts. In this study we evaluate a technique that uses regional Cloud-to-Ground (CG) lightning observations to define areas of deep moist convection in thunderstorms and adjust the model-generated precipitation fields in those regions. The study focuses on a major flash flood inducing storm in central Europe (23 August 2005) that was simulated with the aid of an operational weather forecasting system (POSEIDON system based on Eta/NCEP model). The performance of the technique is assessed using as reference distributed rainfall estimates from a network of radar observations. The results indicate that CG lightning data can offer sufficient information to increase the mesoscale model skill in reproducing local convective precipitation that leads to flash floods. The model error correction is shown to be proportional to the density of lightning occurrence, making the technique potentially suitable for operational forecasting of flash flood inducing thunderstorms.     

Climatology of cyclones over the southwest Pacific: 1992–2001

Summary The Australian east coast is subject to a range of synoptic/mesoscale weather systems ranging from low-pressure troughs, small explosive low-pressure systems near the Australian east coast, to synoptic scale maritime low-pressure systems, and both tropical and extra-tropical cyclones. These systems vary dynamically in intensity and structure across a spectrum that includes both weak and intense cold-cored systems, to warm-cored tropical cyclones and “hybrid” systems. A preliminary 10 year climatology, from 1992 to 2001, is presented that concentrates on those cyclones in open waters that threaten life and property as a result of heavy coastal rain or the combined effects of wind, sea state and swell, including both long fetch and storm surges. There are 28 systems in the 10-year climatology. In terms of their development, the most numerous were the 50% of storms that occurred as systems within an easterly trough, followed by 21% that occurred as circulations on decaying Tasman Sea cold fronts. In addition, a numerical weather prediction (NWP) modelling case study of the ‘hybrid’ sub-tropical cyclone system of March 2001 was carried out using archived real-time data. Operational numerical weather prediction (NWP) model forecasts of this system, which was not named in accordance with Australian classification policy, were all poor except for the US MRF model, which provided marginally useful guidance. None of the operational global and regional models available to forecasters predicted an intense cyclone, and only the US MRF model predicted landfall. A high-resolution forecast using all available data produced significantly improved predictions over the operational models up to four days before landfall.     

Synoptic and mesoscale study of a severe convective outbreak with the nonhydrostatic Global Environmental Multiscale (GEM) model

Summary ?A nonhydrostatic 4-km version of the Global Environmental Multiscale (GEM) model, with detailed microphysics included, was used to forecast the initiation, development, and structure of a tornado-producing supercell storm that occurred near Pine Lake (Alberta, Canada) on 15 July 2000. Examination of observations and comparison with conceptual models indicate that this storm is a good example of supercell storms that regularly produce summertime severe weather over Alberta. It was found that the high-resolution model was able to reproduce the early initiation of convective activity along the Rocky Mountains foothills, as well as the rapid northeastward propagation towards the Pine Lake area and the subsequent intensification into a supercell storm. The general structures of the forecasted convective system correspond well with conceptual representations of such events. Overall, this high-resolution forecast of the Pine Lake supercell storm was a significant improvement over the current operational version of the GEM model (24 km), which was not able to intensify the foothills’ convection into a supercell storm. Finally, it was found that the nonhydrostatic version of the model produces better trajectory and propagation speed of the convective system, as compared with the hydrostatic one. Received March 20, 2001; revised August 24, 2001     

人工智能技术在数值天气预报中的应用

当前,人工智能迎来第3次发展浪潮并在多个领域大数据分析中取得巨大成功,这为人工智能技术与数值天气预报结合提供了契机.已有大量研究尝试将人工智能技术用于数值天气预报的初值生成、预报和产品应用过程中,涉及观测资料预处理、资料同化、模式积分、后处理以及高性能计算,通过误差估计、参数估计和局部代理等手段使预报结果,得到改进且计...     

国外中期数值预报业务模式的性能及发展趋势

作者简单介绍了国内预报员较为熟悉的欧洲中期天气预报中心，美国国家气象中心和日本气象厅三个中期预报模式的性能及预报效果，包括近几年颇为流行的半拉格朗日时间积分方案，物理过程参数化方案的完善和改进，中期数值预报业务模式的发展趋势等。     

成乐高速公路大雾预报方法研究

本文重点分析成乐高速公路沿线大雾历年变化特征,分别用指标判断法和非线性统计支持向量机SVM方法,对成乐路沿线各站大雾的有无定性和能见度量级做出短期和短临客观预报模型,最后通过人为经验订正,对沿线各站大雾做出精细化客观预报;其次,作为新方法的探讨,用中尺度wrf模式对2008年一次典型连续强浓雾天气作了数值模拟试验,试验结果良好,但是该方法的业务化应用有一定难度,还有待进一步研究。      

Numerical Weather Prediction in China in the New Century ——Progress, Problems and Prospects

This paper summarizes the recent progress of numerical weather prediction(NWP)research since the last review was published.The new generation NWP system named GRAPES(the Global and Regional Assimila- tion and Prediction System),which consists of variational or sequential data assimilation and nonhydrostatic prediction model with options of configuration for either global or regional domains,is briefly introduced, with stress on their scientific design and preliminary results during pre-operational implementation.In ad- dition to the development of GRAPES,the achievements in new methodologies of data assimilation,new improvements of model physics such as parameterization of clouds and planetary boundary layer,mesoscale ensemble prediction system and numerical prediction of air quality are presented.The scientific issues which should be emphasized for the future are discussed finally.     

Numerical weather prediction over the Eastern Caribbean using Florida State University (FSU) global and regional spectral models and multi-model/multi-analysis super-ensemble

Summary A month-long short-range numerical weather prediction experiment using the Florida State University’s (FSU) global and regional models and the multi-model/multi-analysis super-ensemble over the Eastern Caribbean domain is presented in this paper. The paper also investigates weather prediction capabilities of FSU global and regional models by examining the root mean square errors (RMSE) for the wind and precipitation fields. Super-ensemble forecasting, a new statistical approach to weather forecasting, is used over this domain. Here, forecasts from a number of numerical models provide the input and statistical combinations of these forecasts produce the super-ensemble forecast. A similar approach is used for the precipitation field where one model using different rain rate algorithms is used to generate different model outputs. The results show that the super-ensemble method produces forecasts that are superior to those obtained from the ensemble members. Received May 29, 2000/Revised February 15, 2001     

Progress towards better weather forecasts for city dwellers: from short range to climate change

Summary The current resolution of operational weather forecast model is not sufficient in general to explicitly resolve even the major cities of the World. As a consequence, urban areas have traditionally been neglected in such models. The introduction of tiled land surface models has enabled sub-gridscale landuse to be modelled, and hence has provided the opportunity to model cities within weather forecast models. However, to date there has been little effort made within the operational weather forecast community. At present there is only one operational centre that explicitly resolves urban areas. This centre includes a simple urban scheme within its mesoscale and global models, which has been shown to have a positive impact on the forecast. However, with the recent developments within urban meteorology there are now a variety of urban schemes, which vary in their complexity and parameter requirements, that would be suitable for operational weather forecast models. So it is likely that more operational models, and in particular mesoscale models, will include urban areas in the near future. With the majority of the World‘s population living in cities, the resilience of these cities to the impacts of climate change is also becoming of increasing interest. This means that urban areas will have to be included within climate change simulations, as well as weather forecast simulations, in the future. At present, only one climate change model has included a parametrisation for urban areas. However, this is likely to increase if work in this area grows rapidly.     

数值预报AI气象大模型国际发展动态研究

数值预报是研究地球系统的重要工具,有助于加深科学家对大气、海洋、气候和环境等复杂系统之间相互作用和变化过程的理解,在防灾减灾、气候变化和环境治理等方面发挥着不可或缺的作用。随着模式复杂度和分辨率的提高,传统数值模式在气候变化研究和气候预测方面取得了迅速的进展,但也面临一些挑战,需要得到数据同化、集合耦合、高性能计算和不确定性分析等多方面的支持。而近年来,“AI+气象”的交叉研究在气象领域引起了广泛关注。基于多种深度学习架构的人工智能大模型,依托强大的计算资源和海量的数据进行训练,能够以新的科学范式进行高效数值预报。气象大模型不断涌现,一些科技公司如华为、英伟达、DeepMind、谷歌、微软等,以及国内外高校如清华大学、复旦大学、密歇根大学、莱斯大学等发布了多个涵盖临近预报、短时预报、中期预报和延伸期预报等不同领域的气象大模型。这标志着人工智能与气象领域的交叉融合已经达到新的高度。尽管气象大模型在现阶段取得了较大突破,但其发展仍然面临弱可解释性、泛化能力不足、极端事件预报强度偏低、智能预报结果过平滑、深度学习框架能力需要拓展等诸多挑战。     

Parallelization Load Balance Strategy for a Global Grid-Point Model

The Global/Regional Assimilation and PrEdiction System (GRAPES) is a new-generation operational numerical weather prediction (NWP) model developed by the China Meteorological Administration (CMA).It is a grid-point model with a code structure different from that of spectral models used in other operational NWP centers such as the European Centre for Medium-Range Weather Forecasts (ECMWF),National Centers for Environmental Prediction (NCEP),and Japan Meteorological Agency (JMA),especially in the context of p...     

2008—2018年我国人工影响天气技术及应用进展

在抗旱、防雹、生态环境保护和重大活动气象保障等国家和地方重大需求的推动下,2008—2018年我国人工影响天气技术和应用得到快速发展。在气溶胶粒子、云（雾）物理垂直结构和降水形成机理等方面,开展了大量科学试验研究,取得了重要成果,建立了国家级人工影响天气实时业务数值预报模式,提高了对作业云特征和演变过程的预报能力,对作业方案的科学设计具有重要作用。在机载云粒子谱仪与成像仪、多通道微波辐射计、X波段偏振雷达、雨（雾）滴谱仪、先进火箭作业系统等核心关键技术装备的国产化研发方面也取得重要进展,研制成功国产机载云粒子测量系统、地基多通道微波辐射计和立体播撒火箭作业系统,并应用于业务,提高了作业条件监测识别和地基作业能力。建立了空中国王、新舟60等型号的先进飞机探测和作业平台,大幅度提高了作业飞行高度、续航时间和空中作业能力。在电离、飞秒激光、声波等人工增雨新技术领域开展了理论和实验探索研究,在飞秒激光诱导降雪机理实验和数值模拟等方面取得了重要进展。     

下一代大气模式中的数值方法综述

数值预报是逐日天气预报、气候预测和气象防灾减灾的核心科技支撑。为进一步提高预报预测的准确度和延长预见期,甚高分辨率、多圈层耦合、多尺度嵌套、多尺度集合、数值地球系统模拟技术等是下一代数值预报的重要发展方向。异构众核高性能计算机和E级计算的高速发展为这一发展提供了契机,但也对现有业务数值预报中采用的数值方法提出了挑战。此文仅对国内外下一代大气模式涉及到的数值方法进行综述,着重于数值算法、准均匀球面网格和时间积分方案等3个方面,期望为相关研究者提供参考。     

数值天气预报和气候预测可预报性研究的若干动力学方法

简要回顾了数值天气预报和气候预测可预报性研究的若干动力学方法,包括用于研究第一类可预报性问题的线性奇异向量（LSV）和条件非线性最优初始扰动（CNOP-I）方法,以及Lyapunov指数和非线性局部Lyapunov指数方法。前两种方法用于研究预报或预测的预报误差问题,可以用于估计天气预报和气候预测的最大预报误差,而且根据导致最大预报误差的初始误差结构的信息,这两种方法可以用于确定预报或预测的初值敏感区。应该指出的是,LSV是基于线性化模式,对于描述非线性大气和海洋的运动具有局限性。因而,对于非线性模式,应该选择使用CNOP-I估计最大预报误差。Lyapunov指数和非线性局部Lyapunov指数可以用于研究第一类可预报性问题中的预报时限问题,前者是基于线性模式,不能解释非线性对预报时限的影响,而非线性局部Lyapunov指数方法则考虑了非线性的影响,能够较好地估计实际天气和气候的预报时限。第二类可预报性问题的研究方法相对较少,本文仅介绍了由我国科学家提出的关于模式参数扰动的条件非线性最优参数扰动（CNOP-P）方法,该方法可以用于寻找到对预报有最大影响的参数扰动,并可以进一步确定哪些参数最应该利用观测资料进行校准。另一方面,通过对比CNOP-I和CNOP-P对预报误差的影响,可以判断导致预报不确定性的主要误差因子,进而指导人们着力改进模式或者初始场。     

天气预报的业务技术进展

该文总结回顾了中央气象台近年来的天气预报业务技术进展。天气预报质量的历史演变显示了预报业务水平的提高, 这种业务能力的提高既反映了预报技术的发展, 也带来了天气预报业务的变化。对业务天气预报中各种预报技术应用进展的分析表明:数值预报在天气预报业务能力提高中发挥着重要的基础性作用; 同时, 基于对不同尺度天气影响系统发展演变过程深入认识的基础上, 天气学的预报方法依然是预报业务中的重要技术方法; 动力诊断预报已成为灾害性天气预报中的重要手段之一, 数值预报产品的解释应用是实现气象要素精细定量预报的技术途径。