Evaluation and Improvement of a SVD-Based Empirical Atmospheric Model

An empirical atmospheric model(EAM) based on the singular value decomposition(SVD) method is evaluated using the composite El Ni(?)o/Southern Oscillation(ENSO) patterns of sea surface temperature (SST) and wind anomalies as the target scenario.Two versions of the SVD-based EAM were presented for comparisons.The first version estimates the wind anomalies in response to SST variations based on modes that were calculated from a pair of global wind and SST fields(i.e.,conventional EAM or CEAM).The second version utilizes the same model design but is based on modes that were calculated in a region-wise manner by separating the tropical domain from the remaining extratropical regions(i.e.,region-wise EAM or REAM). Our study shows that,while CEAM has shown successful model performance over some tropical areas, such as the equatorial eastern Pacific(EEP),the western North Pacific(WNP),and the tropical Indian Ocean(TIO),its performance over the North Pacific(NP) seems poor.When REAM is used to estimate the wind anomalies instead of CEAM,a marked improvement over NP readily emerges.Analyses of coupled modes indicate that such an improvement can be attributed to a much stronger coupled variability captured by the first region-wise SVD mode at higher latitudes compared with that captured by the conventional one. The newly proposed way of constructing the EAM(i.e.,REAM) can be very useful in the coupled studies because it gives the model a wider application beyond the commonly accepted tropical domain.     

用改良的面积重叠法自动跟踪中尺度对流系统的试验研究

中尺度对流系统(Mesoscale Convective Systems, MCSs)的活动和演变,是造成致洪暴雨灾害性天气的主要因素之一.多年来,许多学者加大了对中尺度对流系统研究的力度.但是,中尺度对流系统的活动及其移动和传播的研究进展一直受到计算机自动识别和跟踪问题的制约.首先介绍了一种基于面积重叠法的MCSs自动跟踪技术,然后针对它存在的问题进行了改良,并应用改良后的面积重叠法对1998年6月至8月的青藏高原上空MCSs进行了识别与跟踪实验.实验结果表明,改良后的面积重叠法的跟踪准确率可达80%,比改良前提高了10%以上.     

Long-range forecasting of forest fire danger based on the SLAV model seasonal ensemble forecasts

Developed is a scheme of the long-range forest fire danger (FD) forecasting based on the computation of the Nesterov??s index and on hydrodynamic forecasts of air temperature and precipitation of the SLAV model. The satellite information on the climatic distribution of the snow cover was taken into account for the forecast issuance. It is proposed to express the FD index not using traditional classes of fire danger but in ??above the norm,?? ??norm,?? and ??below the norm?? gradations. Presented are the results of author??s trials of the method based on the retrospective model data for six years. Discussed are the approaches to the improvement of the method of long-range fire danger forecasting.     

风能模式预报的相似误差订正

采用一种基于相似误差的模式后处理方法,对2011年10月18日—2012年1月5日WRF模式24 h预报的陕西延长风电场风速进行误差订正。该方法通过寻找与当前预报相似的历史预报来进行误差订正,克服了一般基于时间顺序的误差订正方法的不足,即不能处理由于天气系统的剧烈转变引起的预报误差的快速变化。相似误差订正方法减小了预报的均方根误差和中心均方根误差,相对原始预报分别减小9%和10%左右。该方法不仅可以减小系统误差,还可以减小随机误差,从而提高预报准确率。同时,订正结果相对原始预报具有更好的Taylor图模态相关。相似误差订正方法对风能预报敏感区的订正效果更为显著,均方根误差和中心均方根误差分别减小了12%和22%左右。该方法尤其适用于基于风能模式预报的风速误差订正,同时该方法对其他的预测系统和预报变量也有很好的应用潜力。     

基于频率匹配法的江西省ECMWF降水预报订正研究

利用2016—2019年ECMWF（European Centre for Medium-Range Weather Forecasts）降水预报资料和江西省93个国家气象站降水资料,基于频率匹配法进行降水偏差订正,采用4种方法统计降水频率对降水预报进行订正试验（不分区试验）,根据江西省汛期暴雨气候特征对汛期降水进行分区订正试验,并对典型强降水个例进行分析。结果表明: 频率匹配法降低了模式预报小雨的空报率和大雨、暴雨的漏报率,预报技巧改进明显。在4种降水频率统计方法中,准对称滑动平均法效果最好。分区试验对强降水的订正效果优于不分区试验,该试验对模式预报正技巧暴雨过程的订正能力大于无技巧过程。对于模式预报效果差（TS=0）、一般（0 < TS < 0.2）、好（TS≥0.2）的暴雨过程,分区试验改善的概率分别为40.8%、89.1%和65.3%。频率匹配分区订正后强降水面积更加接近实况,但强降水落区不能得到明显的改善。订正方法对模式预报强降水形态、位置与实况较接近的过程,效果较好。     

雷达热动力反演资料的高分辨率同化模拟试验

目前,北京地区的天气预报系统对局地对流性定量降水预报能力较弱,远不能满足人们生产、生活和防灾、减灾工作的需要。针对北京地区对提高0-12 h短时临近天气,尤其是夏季局地对流性降水预报能力的需求,基于中国气象局北京城市气象研究所变分多普勒雷达分析系统（VDRAS）的雷达热动力反演资料,建立了WRF模式初始化模块,采用四维资料同化（FDDA）方法,将VDRAS系统高时空分辨率三维热动力结构分析场资料同化到WRF模式中,实现了北京地区VDRAS分析场资料在WRF中尺度模式系统中的应用。通过降水个例的高分辨率同化模拟试验分析了雷达热动力反演资料同化对模式预报结果的影响。研究结果表明:雷达热动力反演资料的同化能够提高模式系统对近地面温、湿、风大气要素和降水过程的模拟能力,改善2 m比湿、降水落区、降水量级、降水时间的预报效果,减少降水漏报的现象。温度和比湿的同化比风的同化对模拟降水结果的改善更重要。虽然研究表明雷达热动力反演资料在WRF模式中的同化能够明显改善模式对选取降水个例的模拟效果,但其对模式尤其是数值业务模式系统预报效果的影响需要进一步更全面、更系统的检验,为业务化应用奠定更坚实的基础。      

几种统计预测方法对1998年南京降水的跨季节预测试验及分析

对1998年南京降水分别设计并开展了求和自回归滑动平均（Auto-Regressive Integrated Moving Average,ARIMA）模型预测、经验模态分解（Empirical Mode Decomposition,EMD）预测和基于Hilbert变换（HilbertTransformation,HT）的幅频分离预测等3种跨季节统计预测试验。结果表明：ARIMA模型预测结果存在明显的系统性误差且对夏季的降水突变现象预测困难;EMD分解预测的结果虽在降水演变趋势上有明显提高,但仍未能预测出夏季的强降水突变现象,究其原因可能是对高频分量预测效果不好所致;而基于Hilbert变换的幅频分离预测方法能够对各模态分量的瞬时频率和瞬时振幅实施隔离预测,消除两者的相互影响,显著改善高频模态的预测效果,使得最终预测结果最为理想,不仅具有最高的趋势相关性和最小的偏差,而且还较好地预测出了夏季两次强降水过程。不仅如此,在对2003年的降水预测验证中,基于Hilbert变换的幅频分离预测方法同样具有最好的预测效果,表明该方法预测效果较为稳定,为改进跨季节短期气候统计预测技术提供了一个新思路。     

基于空间梯度信息的质量控制方法在红外高光谱AIRS资料同化中的应用研究

本文利用中尺度非静力WRF(Weather Research Forecast, Version 3.4)模式, 针对1013号“鲇鱼”台风个例, 通过对红外高光谱AIRS(Atmospheric Infrared Sounder)资料经过基于空间梯度信息的质量控制之后同化进入模式, 来评估新的质量控制方法对同化效果的影响以及对台风数值模拟的改善情况。研究结果发现, 如果仅仅基于WRFDA(WRF Data Assimilation system, Version 3.4)模式自带的质量控制系统, 将会有部分梯度距平值明显较大超过阈值的资料被同化进入模式, 而这些可能受到“污染”且误差较大的资料同化进入模式必将会导致同化结果有较大误差, 影响分析结果的质量。而对AIRS资料经过基于空间梯度信息质量控制之后再同化进入模式, 确实可将梯度距平值大于阈值的“坏点”剔除掉, 从而使初始场的描述更加准确, 台风路径的模拟精度在一定程度上得到提高。综上可知, 基于空间梯度信息的质量控制方法整体上对改善同化效果有较好的正效应, 对台风的数值模拟也起到一定的促进作用。     

Hydrological Evaluation of the Canadian Meteorological Ensemble Reforecast Product

This paper evaluates the quality of the ensemble hydrological reforecasts obtained using the 18-year ensemble meteorological reforecast dataset available from the Canadian Centre for Meteorological and Environmental Prediction (CCMEP). This study focuses on four large watersheds in the province of Quebec. A distribution-based scaling (DBS) post-processing method is used to correct the 18-year ensemble precipitation reforecasts. An Ensemble Kalman Filter (EnKF) assimilation technique is also assessed to improve the initial conditions of the hydrologic model. There is a slight improvement in performance and reliability after applying the DBS approach to precipitation reforecasts, but this technique induces a reduction in the spread. The impact of the integration of the post-processed precipitation into the hydrologic model is also quite marginal. However, the addition of an EnKF provides better ensemble hydrological reforecasts with high performance, reliability, and skill, especially in the first reforecast horizons. The best results are, however, generally obtained when using DBS and an EnKF together. Combining DBS and an EnKF, hydrological forecasts for the next two weeks are obtained using the CCMEP reforecast and also the second generation Global Ensemble Forecast System (GEFS v2) reforecast, which is considered a reference. Forecasts of comparable skill and spread are obtained, with CCMEP-based forecasts showing better spread during the first week, and GEFS v2–based reforecasts showing better skill and spread during the second week. Finally, it is shown that the two meteorological reforecast products assessed in this study have similar economic value for hydrological forecasting applications based on the cost–loss model.     

气象预报的方法与不确定性

根据历史上有关气象的文字记载,结合大气科学发展的历史和现状,以深入浅出的方式回顾了气象预报制作方法的变更与发展.概述了当前业务预报的水平和相关研究的主要进展.针对数值预报,讨论了导致气象预报结果不确定性的主要原因.并通过介绍集合预报,对公众应当如何理解和使用预报产品提出了看法.     

On the Application of a Genetic Algorithm to the Predictability Problems Involving "On-Off" Switches

The lower bound of maximum predictable time can be formulated into a constrained nonlinear opti- mization problem, and the traditional solutions to this problem are the filtering method and the conditional nonlinear optimal perturbation (CNOP) method. Usually, the CNOP method is implemented with the help of a gradient descent algorithm based on the adjoint method, which is named the ADJ-CNOP. However, with the increasing improvement of actual prediction models, more and more physical processes are taken into consideration in models in the form of parameterization, thus giving rise to the on-off switch problem, which tremendously affects the effectiveness of the conventional gradient descent algorithm based on the ad- joint method. In this study, we attempted to apply a genetic algorithm (GA) to the CNOP method, named GA-CNOP, to solve the predictability problems involving on-off switches. As the precision of the filtering method depends uniquely on the division of the constraint region, its results were taken as benchmarks, and a series of comparisons between the ADJ-CNOP and the GA-CNOP were performed for the modified Lorenz equation. Results show that the GA-CNOP can always determine the accurate lower bound of maximum predictable time, even in non-smooth cases, while the ADJ-CNOP, owing to the effect of on-off switches, often yields the incorrect lower bound of maximum predictable time. Therefore, in non-smooth cases, using GAs to solve predictability problems is more effective than using the conventional optimization algorithm based on gradients, as long as genetic operators in GAs are properly configured.     

An assessment of European synoptic variability in Hadley Centre Global Environmental models based on an objective classification of weather regimes

The frequency of occurrence of persistent synoptic-scale weather patterns over the European and North-East Atlantic regions is examined in a hierarchy of climate model simulations and compared to observational re-analysed data. A new objective method, employing pattern correlation techniques, has been constructed for classifying daily-mean mean-sea-level pressure and 500 hPa geopotential height fields with respect to a set of 29 European weather regime types, based on the widely known subjective Grosswetterlagen (GWL) system of the German Weather Service. The objective method is described and applied initially to ERA40 and NCEP re-analysis data. While the resulting daily Objective-GWL catalogue shows some systematic differences with respect to the subjectively-derived original GWL series, the method is shown to be sufficiently robust for application to climate model output. Ensemble runs from the most recent development of the Hadley Centre’s Global Environmental model, HadGEM1, in atmosphere-only, coupled and climate change scenario modes are analysed with regards to European synoptic variability. All simulations successfully exhibit a wide spread of GWL occurrences across all regime types, but some systematic differences in mean GWL frequencies are seen in spite of significant levels of interdecadal variability. These differences provide a basis for estimating local anomalies of surface temperature and precipitation over Europe, which would result from circulation changes alone, in each climate simulation. Comparison to observational re-analyses shows a clear and significant improvement in the simulation of realistic European synoptic variability with the development and resolution of the atmosphere-only models.     

北京地区暴雨个例的观测敏感区研究

利用基于集合预报的相关方法对2009年7月23日发生在北京及周边地区的暴雨过程的观测敏感区进行了分析。通过WRF(Weather Research Forecast)三维变分方法对初始场进行随机扰动,形成30个初始集合样本,做了预报时效为12 h的集合预报。利用该方法分析检验区(北京及周边地区)累积降水[14:00(北京时间,下同)至20:00]相对于初始时刻(08:00)各基本要素的敏感性,确定感性要素及其对应的区域。研究发现初步确定的敏感性要素为水汽和温度,对应的敏感区分别位于北京的西南侧和北京的东北侧,且通过实况分析可知初步确定的敏感性要素和对应的敏感区具有明确的物理意义。还进一步通过观测系统模拟试验(OSSE)的资料同化验证所确定的敏感区,结果表明在水汽对应的敏感区内同化水汽对降水的预报结果有明显的改进;在温度对应的敏感区内同化温度,降水的预报准确率有了明显的提高,说明了初步确定的敏感性要素和敏感区的正确性。在水汽对应的敏感区内同化水汽的同时在温度对应的敏感区内同化温度,使降水预报的技巧有大幅度的提高,说明了温度和水汽的共同作用对提高降水预报准确率贡献最大。因此,通过基于集合预报的相关方法能够快速的确定敏感区。研究结果将为确定北京暴雨的观测敏感区提供参考。     

对流参数化与微物理过程的耦合及其对台风预报的影响研究

在SAS（Relaxed Arakawa-schubert Scheme）对流参数化方案中引入对流云和层状云的相互耦合机制,并通过一个台风个例对改进前后两种方案的预报效果进行了比较。试验结果表明：对于台风这种对流云和层状云相互作用非常强烈的天气系统,在对流参数化方案中引入对流云和层状云的耦合机制可以有效地提高模式对台风路径的预报水平,但是对于台风强度的预报效果不明显。考虑对流参数化和微物理过程耦合后模式的参数化降水变弱而格点降水增强,与NCEP再分析资料的对比发现,改进方案对于台风外围的大尺度温度场和湿度场的预报会有所改进,但仍然存在偏干偏冷的现象。对雨和雪的不同处理方式、不同云底条件以及是否考虑雨雪的卷入抬升三个方面进行了敏感性试验,发现72 h内模式预报结果对这些因素的差异不是很敏感。从多个个例的统计结果来看,新方案对台风路径预报的改进效果是比较稳定的。     

基于风向线性变化假定的单Doppler雷达风场IVAP反演技术

IVAP和扩展VAP技术是在常用的VAD和VAP技术基础上发展起来的单Doppler雷达风场反演技术.在IVAP和扩展VAP技术基础上,进一步改进IVAP技术,将IVAP技术反演假定从局地均匀扩展到局地风速均匀、风向随方位角线性变化,进而提高IVAP技术的反演能力.使用涡旋流场试验表明,改进后的IVAP技术对于风速稳定,而风向变化的风场的反演能力有明显提高.由于改进后的IVAP技术保持了IVAP技术反演时可不对原始资料进行平滑预处理,对于小尺度扰动具有滤波作用,其应用更为广泛.     

支持向量机方法应用于理想时间序列的预测研究

简要介绍了基于统计学习理论的支持向量机方法的基本思想和原理,利用该方法对33模Lorenz系统的理想混沌时间序列建立预测模型,并对在此基础上产生的非平稳时间序列进行预测试验研究。结果表明,支持向量机方法不仅对平稳过程有较好的预报能力,也可以适用于非平稳过程,对实际序列的预测有一定的启发意义。     

A statistical model for spatial inventory data: a case study of N2O emissions in municipalities of southern Norway

In this paper we apply a linear regression with spatial random effect to model geographically distributed emission inventory data. The study presented is on N₂O emission assessments for municipalities of southern Norway and on activities related to emissions (proxy data). Taking advantage of the spatial dimension of the emission process, the method proposed is intended to improve inventory extension beyond its earlier coverage. For this, the proxy data are used. The conditional autoregressive model is used to account for spatial correlation between municipalities. Parameter estimation is based on the maximum likelihood method and the optimal predictor is developed. The results indicate that inclusion of a spatial dependence component lead to improvement in both representation of the observed data set and prediction.     

初值协调性对模式数值积分结果的影响

利用国家气候中心新一代全球大气环流模式BCC_AGCM2.0.1,考虑了初值协调性对模式数值积分结果的影响,进行了两组数值回报试验(简称S1,S2),对27年(1980～2006年)的夏季基本气候态进行了对比分析,并考察了该模式对夏季气候的回报技巧。使用交叉检验的方法,计算了对模式结果的评估参数值,包括时间和空间距平相关系数,对该模式性能进行了评估和检验。结果表明,BCC_AGCM2.0.1对季节尺度的大气环流场具有良好的模拟性能,模式基本上再现了观测位势高度场、温度场、流场的分布特征以及大尺度降水分布特征。500 hPa位势高度、温度空间距平相关系数对比表明,平均而言,500 hPa位势高度、温度的空间距平相关性,热带区域(30°S～30°N)高于东亚区域(0°～60°N,60°E～150°E)和全球区域。回报与观测的降水距平百分率相关系数分布对比表明,试验S2在我国江淮地区及南方地区的回报技巧要明显优于S1。     

我国现代气候业务现状及未来发展趋势

从气候监测诊断、气候预测、气候系统模式、气候评价与灾害风险管理、气候变化业务和气候业务平台等角度,系统概述了我国现代气候业务现状。提出了以气候监测和动力学诊断为基础,以提升气候服务、气候风险管理和应对气候变化能力为目标,以发展客观化气候预测技术和定量化气候评估方法为核心的现代气候业务概念。分析了国际气候业务发展趋势及我国气候业务的差距,明确了加强气候系统基本变量监测、提高气候系统模式分辨率和改进物理过程、发展第2代短期气候预测系统、研发气象灾害风险评估方法并建立中国气候服务系统 (CFCS) 等发展任务。     

A New Infrared Atmospheric Sounding Interferometer Channel Selection and Assessment of Its Impact on Met Office NWP Forecasts

A new set of Infrared Atmospheric Sounding Interferometer(IASI) channels was re-selected from 314 EUMETSAT channels.In selecting channels,we calculated the impact of the individually added channel on the improvement in the analysis outputs from a one-dimensional variational analysis(1D-Var) for the Unified Model(UM) data assimilation system at the Met Office,using the channel score index(CSI) as a figure of merit.Then,200 channels were selected in order by counting each individual channel's CSI contribution.Compared with the operationally used 183 channels for the UM at the Met Office,the new set shares 149 channels,while the other 51 channels are new.Also examined is the selection from the entropy reduction method with the same 1D-Var approach.Results suggest that channel selection can be made in a more objective fashion using the proposed CSI method.This is because the most important channels can be selected across the whole IASI observation spectrum.In the experimental trial runs using the UM global assimilation system,the new channels had an overall neutral impact in terms of improvement in forecasts,as compared with results from the operational channels.However,upper-tropospheric moist biases shown in the control run with operational channels were significantly reduced in the experimental trial with the newly selected channels.The reduction of moist biases was mainly due to the additional water vapor channels,which are sensitive to the upper-tropospheric water vapor.