和预报员谈数值预报

用尽可能非专业的词语,向预报员介绍数值预报的成就、问题与应用。在简单回顾数值预报发展历史的基础上,重点分析了近十几年来数值预报的主要技术进步与有待解决的问题,对比了数值预报与主观经验预报的各自优势与不足,提出了优势互补对于提高业务预报的重要性。还分析了数值预报的技术进步对于数值预报产品释用的影响,以及预报员参与数值预报发展的可能性与必要性。     

Comparison of prediction performance using statistical postprocessing methods

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.     

上海区域数值预报模式集合预报系统的建立与试验

以目前运行的上海区域业务数值预报模式为基础,从预报模式的不确定性出发构造8个预报成员,建立了上海区域数值预报模式集合预报系统的初步模型,并对2004年夏季进行了逐日48 h预报试验。结果表明:集合平均对华东地区城市降水、温度、海平面气压等气象要素的总体预报能力与分辨率高3倍的业务模式相当,其中对雨量较大降水、最低温度、海平面气压(0~24 h)的预报效果好于业务模式;集合预报还能提供客观化、定量化的降水概率预报,对降水的发生、尤其是特大降水的发生有着很好的提示作用。     

GRAPES-GEPS环流集合预报的分类释用方法研究与检验

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。      

台风暴雨天气预报的现状和展望

将我国天气预报业务中台风暴雨的预报方法归纳为４种类型,它们是天气概念模型、数值预报产品动力释用、相似法和应用卫星、雷达探测资料等方法。以典型实例说明了每种方法的基本思路和大概情况。由此分析了我国在预报业务中所具有的优势和存在着的薄弱环节。依照近期的计划和动向对我国天气预报业务发展作了展望     

扩散系数反演及其差分格式研究

空气污染预报属于正问题，而从污染物浓度来求解扩散系数则属于反问题。正问题和反问题有着本质的不同，在解的定义和求解方法上也有很大的区别。从最优控制的角度定义了大气边界层中垂直扩散系数反演问题的解，用伴随模式方法得到目标函数的梯度并求解反问题。研究中发现，反演的结果与模式差分格式的选取有关，与测试源的设置也有直接的关系。在经过多次数值试验后，对于误差的来源进行了理论分析，发现了反演结果与差分格式及测试源之间的联系，得到了满意的反演结果，并为实验测定扩散系数提供了依据。     

集合数值预报在洪水预报中的应用进展

水文集合预报是近几年正在形成和发展的水文预报分支,其发展大致可分为两个阶段:第1阶段是1970年至20世纪末进行的长期径流预报,第2阶段从21世纪开始,主要学习气象数值预报中集合预报的概念在短期水文集合预报中的应用。目前,除了单一预报中心的集合预报系统在水文集合预报中应用外,多个预报中心的集合预报大集合也逐渐被应用于流域水文预报,甚至一些小流域的洪水预报。如利用TIGGE(THORPEX Interactive Grand Global Ensemble)集合预报驱动形成的大气-水文-水力的串联系统进行早期的洪水预警研究,将全球集合预报作为洪水模型输入的有限区域模式的初始条件和侧边界条件的研究。这些均表明,基于水文集合预报的洪水预报增加了预报附加值,并能够延长预警提前时间。以欧洲中期天气预报中心的欧洲洪水预警系统(EFAS)和美国NOAA的先进水文预报系统(AHPS)为代表,实现了集合预报在洪水中的实时业务预报,但仍存在数据处理和计算量大,以及如何基于集合水文预报做决策等问题。对于水文集合预报的前处理和后处理的各种技术已处于探索和验证阶段,如何更好地理解基于概率预报的洪水预警决策仍存在许多困难和挑战。     

Development of an Operational Hybrid Data Assimilation System at KIAPS

This study introduces the operational data assimilation (DA) system at the Korea Institute of Atmospheric Prediction Systems (KIAPS) to the numerical weather prediction community. Its development history and performance are addressed with experimental illustrations and the authors’ previously published studies. Milestones in skill improvements include the initial operational implementation of three-dimensional variational data assimilation (3DVar), the ingestion of additional satellite observations, and changing the DA scheme to a hybrid four-dimensional ensemble-variational DA using forecasts from an ensemble based on the local ensemble transform Kalman filter (LETKF). In the hybrid system, determining the relative contribution of the ensemble-based covariance to the resultant analysis is crucial, particularly for moisture variables including a variety of horizontal scale spectra. Modifications to the humidity control variable, partial rather than full recentering of the ensemble for humidity further improves moisture analysis, and the inclusion of more radiance observations with higher-level peaking channels have significant impacts on stratosphere temperature and wind performance. Recent update of the operational hybrid DA system relative to the previous 3DVar system is described for detailed improvements with interpretation.     

ConvLSTM Based Temperature Forecast Modification Model for North China

The correction of model forecast is an important step in evaluating weather forecast results. In recent years, post-processing models based on deep learning have become prominent. In this paper, a deep learning model named ED-ConvLSTM based on encoder-decoder structure and ConvLSTM is developed, which appears to be able to effectively correct numerical weather forecasts. Compared with traditional post-processing methods and convolutional neural networks, ED-ConvLSTM has strong collaborative extraction ability to effectively extract the temporal and spatial features of numerical weather forecasts and fit the complex nonlinear relationship between forecast field and observation field. In this paper, the post-processing method of ED-ConvLSTM for 2 m temperature prediction is tested using The International Grand Global Ensemble dataset and ERA5-Land data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Root mean square error and temperature prediction accuracy are used as evaluation indexes to compare ED-ConvLSTM with the method of model output statistics, convolutional neural network postprocessing methods, and the original prediction by the ECMWF. The results show that the correction effect of ED-ConvLSTM is better than that of the other two postprocessing methods in terms of the two indexes, especially in the long forecast time.     

我国现有短期气候业务预测方法综述

对我国短期气候业务预测方法的综合分析表明 :我国现有的短期气候业务预测经验和统计方法仍是主要的 ;物理因子和前兆强信号结合天气气候学分析的概念预测模型方法在业务预测中发挥重要作用 ;动力模式预测方法在业务预测中取得一定效果 .随着动力模式的进一步发展 ,短期气候业务预测将逐步走向以动力模式客观预报为指导预报的新阶段     

GNSS反演资料在GRAPES_Meso三维变分中的应用

为了进一步提高GRAPES_Meso的分析和预报效果,该文在GRAPES_Meso三维变分同化系统中建立了同化GNSS/RO反演的大气资料的观测算子,实现了对GNSS/RO反演的大气资料的同化应用,并通过2013年7月1个月的同化和预报试验分析了GNSS/RO反演大气资料对GRAPES_Meso模式系统分析和预报的影响。结果表明:增加了GNSS/RO反演大气资料的同化后,GRAPES_Meso位势高度场的分析误差明显减小,平均分析误差减小约8%,预报误差略有减小,平均预报误差减小约1%;湿度场的分析误差和预报误差变化不明显,常规观测资料稀少的青藏高原地区的降水预报技巧有所提高,小雨到大雨的ETS (equitable threat score) 评分提高约0.01,对全国及其他分区的降水预报技巧总体上有正效果。     

全球最优插值客观分析

主要叙述国家气象中心实时运行的全球资料同化系统中的客观分析方案，该方案采用最优插值统计方法，使用所有可以使用的各种类型有不同误差的观测资料和模式的６ｈ预报值，给出数值形式的全球分析值。在两年的业务运行中，为Ｔ４２中期数值预报谱模式提供了较好的初始场。     

2013年汛期华中区域业务数值模式降水预报检验

为充分了解华中区域中尺度业务数值预报模式更新为WRF后的预报性能,对该模式2013年汛期24 h和48 h的累积降水预报产品,采用TS评分、预报正确率、漏报率、空报率、偏差及ETS评分等统计量对其进行了较详细的评估。结果表明：从日平均降水率分布来看,24 h预报的降水中心位置和强度与实况更接近,48 h的预报明显偏大、偏强;汛期总体降水检验表明,该模式的降水预报以偏大为主,随着降水量级的增大,TS和ETS评分逐渐减小,且ETS评分逐渐靠近TS;逐月降水检验结果发现,该区域汛期月晴雨预报正确率与雨日率呈正相关;通过梅雨期WRF与GRAPES_Meso的预报对比检验可见,两个模式都表现出了较好的预报性能。值得指出的是,随着降水量级的增大,WRF模式降水预报优势逐渐显现。总的来说,该模式的降水预报产品具有一定的参考价值。     

CAPPS1和CAPPS2数值预报模式对比分析

对CAPPS1模式和CAPPS2模式预报广西污染物进行了对比分析。主要对比了其污染扩散原理、气象预报模式、操作系统、运行时间、预报时效及预报效果。分析表明：CAPPS1和CAPPS2模式对各种污染物预报的相关系数均在0．44以上，两种模式预报广西空气污染都是可行的；两种模式均对SO2的预报效果最好，NO2次之，PM10相对最差；CAPPS2模式对各种污染物的预报值与实测值相关系数均比CAPPS1高，其中NO2的相关系数提高幅度最大；CAPPS2模式对NO2和PM10的预报准确率比CAPPS1偏高，而对SO2的预报准确率比CAPPS1偏低；CAPPS2预报首要污染物正确率比CAPPS1高出11个百分点，而预报首要污染物等级正确率则高出9个百分点。     

卫星资料循环同化应用对区域数值预报效果影响分析

为提高卫星资料在同化系统中的利用率及验证卫星微波资料对区域数值预报效果的影响,本文以2008年8月1-31日为研究时段,利用WRF模式及其WRF-3DVAR同化模块,设计并构建了卫星微波资料的快速循环同化方案,分析循环同化方案对数值预报的改进效果.结果表明,相比于单时次同化,循环同化方案使各预报要素的相关系数在一定程度上得到改善,均方差也呈现减小的趋势.此外,对研究时段内暴雨和台风个例的具体分析显示,循环同化方案能够有效改善降水和台风路径的预报.     

北京地区中尺度数值业务预报的客观检验

对北京地区中尺度数值天气预报客观检验系统的框架和方法进行了详细的介绍，分析了北京地区冬季（2001年11月1日~2002年2月28日）主要预报要素的客观检验结果，在此基础上给出北京地区冬季中尺度数值预报业务的误差特征，并根据检验结果定性地分析了模式预报系统性和非系统性误差的可能来源。结果表明，模式地形的强迫作用是地面和对流层低层预报系统性误差的重要来源；测站高空预报要素的非系统性误差显著，初始时刻存在的误差在积分过程中被进一步放大；对北京 (54511) 单站地面要素预报的检验结果发现，2-m温度预报冬季整体偏低。在系统性误差为主要误差分量时对模式的平均误差进行订正能有效地提高温度预报的准确率。     

确定数值预报模式中扩散系数的一个客观方法

当数值预报模式的分辨率得到提高时,模式中扩散系数的数值大小必然随之改变。通常情况下,一方面,扩散系数的数值应足够大（即有下限值）,以便过滤掉模式中不想要的小尺度噪音;另一方面,扩散系数的数值应尽量小（即有上限值）,以免出现计算不稳定。本文提出一种确定高分辨率模式中扩散系数数值大小的客观方法,即＂双试验＂（twin experiment）同化方法（初始低分辨率模式的预报结果作为＂观测资料＂,新的高分辨率模式作为同化模式）,从而通过伴随变分同化方法来确定控制变量（即扩散系数）的数值大小。本文采用一维浅水模式测试和描述上述试验方案。通过低分辨率模式预报结果和高分辨率模式预报结果的比较（高、低分辨率模式预报结果的比较在低分辨率模式格点上进行）,采用最小二乘法可客观求得适用于高分辨率模式的扩散系数的＂最优＂值。数值试验结果表明,采用这种方法得到的高分辨率模式的扩散系数,不仅能过滤掉模式中不想要的小尺度噪音,而且能够避免出现计算不稳定。研究还指出,当扩散系数的大小略微超过其上限值时（这种情况在极小化迭代中有可能会出现）,计算不稳定的出现将使目标函数的数值迅速增加,并导致极小化程序收敛的失败;时间步长的减小（约20%）可以显著地改进目标函数的条件数,从而可避免极小化程序收敛的失败。     

美国天气预报技术的发展

介绍了美国天气预报技术的发展现状。指出在大气探测技术、数值预报及可视化技术发展的推动下美国传统的天气预报向定量与定时方向发展。定量降水预报的实现是天气预报由定性走向定量的重要标志。在充分利用数值模式产品的基础上综合应用卫星与雷达资料建立客观预报工具在暴雨和强对流天气预报中取得较好效果;中尺度分析业务系统的不断改进使降水预报的技巧有明显提高。作者还介绍了美国数值预报产品释用及预报业务系统的概况。最后     

The ECMWF medium-range prediction models development of the numerical formulations and the impact of increased resolution

Summary An outline is given of the numerical formulations that have been utilized for medium-range prediction at the European Centre for Medium-Range Weather Forecasts. The sigma-coordinate grid-point model adopted for the first phase of operational forecasting, and the hybrid-coordinate spectral model which replaced it, are described. Particular emphasis is placed on aspects of the time-stepping employed in the spectral model. It is shown how a semi-implicit treatment of the zonal advection of vorticity and specific humidity, and selective use of enhanced horizontal diffusion, enables time-steps to be used which are well over 50% longer than would otherwise be possible in a spectral model with a classical semi-implicit treatment of gravity-wave terms, with negligible computational cost and negligible impact on forecast accuracy, at T 106 resolution at least. Some discussion of the stability of the semi-implicit gravity-wave scheme is also included.The experimental evidence which led to the operational change from the grid-point to the spectral model is summarized, and the sensitivity of forecasts to the horizontal resolution of the spectral model is illustrated. Both the change in method and increases in resolution result in systematic improvements in the details of cyclone development, and they occasionally have major beneficial impact on the evolution of the forecast in the medium range. Conventional objective verification indicates a much smaller mean improvement of T 106 resolution over T 63 than of T 63 over T 42, although the advantage of T 106 is nevertheless clear-cut. This advantage is more than confirmed by synoptic assessment. Scope for further improvement is indicated by first results from global forecasts with a resolution of T 159. Indications of sensitivity to the magnitude of horizontal diffusion and the resolution of the model orography are also given.The spectral model was initially used operationally with a 16-level vertical resolution, and the uppermost level at which prognostic variables were held was 25 mb. The results which justified a subsequent change to 19 levels, with increased stratospheric resolution and a 10 mb top level, are presented. In this case the principal medium-range forecast improvement came about because better initial analyses could be produced when the 19-level model was used in data assimilation.With 24 Figures     

北京地区中尺度非静力数值预报系统的开发与实时预报应用

国家气象中心与北京市气象局联合开发并将于1999年底建成“北京地区中尺度数值天气预报业务系统”。作为开发的第一阶段,以PSU/NCAR的MM5非静力中尺度模式为基础,在国家气象中心IBM/SP2机并行运算环境下与国家气象中心资料源连接并应用北京地区加密地面观测资料,初步建成了“北京地区中尺度数值天气预报试验系统”（以下简称BJ-MM5V.1）。模式设计为垂直23层,水平分辨率分别为45和15km的两重双向嵌套网格。在IBM/SP2计算机上用24个节点作36 h预报所需机时为2 h 20 min,满足实时业务预报需要。该系统于1997年夏季进行了实时运行试验,可提供北京地区每小时降水量预报每3 h多种气象要素预报,预报产品在北京市气象局试用。结果表明,系统有较强的稳定性和实用性,对降水时空分布的预报效果较好。