The impact of horizontal resolution on moist processes in the ECMWF model

Summer and winter climates simulated with the ECMWF (cycle 33) model at spectral scales T21, T42, T63 and T106 are analyzed to determine the impact of changes in horizontal resolution on atmospheric water vapor, clouds, convection, and precipitation. Qualitative changes in many moist processes occur in the transition from T21 to T42, especially in the tropics; at higher resolutions mostly incremental variations from patterns established at T42 result. Large-scale tropical moist processes are simulated more realistically at T21 than at finer resolutions, possibly reflecting a mismatch between the finer-scale dynamics and the scales at which the underlying assumptions of the physical parameterizations apply. Global precipitation increases monotonically with resolution, as a consequence of increasing convection. Global cloud cover, however, decreases in the transition from T21 to T42 due to drying of the tropics, but then increases slightly at finer resolutions. These small global increases are an outcome of compensating changes in different regions: decreases in cloud cover due to drying of the atmosphere at low latitudes are offset by high-latitude increases resulting from enhanced relative humidity associated with an intensifying atmospheric cold bias at finer resolutions.     

Review of numerical methods for nonhydrostatic weather prediction models

Summary ?Currently available computer power allows to run operational numerical weather prediction models at resolutions higher than 10 km. The aim of such high resolution modeling is the prediction of local weather, including orographically induced winds and local precipitation patterns. In this range the hydrostatic approximation is no longer valid and nonhydrostatic models have to be used instead. For several decades these models have been developed for research purposes only, but operational application is now reality. In this paper, the numerical methods used in current nonhydrostatic forecast models will be reviewed and some promising techniques in this field will be discussed. Special attention is given to aspects such as the choice of the vertical coordinate, the efficiency of algebraic solvers for semi-implicit time discretizations, and accurate and non-oscillatory advection schemes. Received July 6, 2001; revision October 12, 2001     

中国数值天气预报的自主创新发展

数值天气预报是天气预报业务和防灾、减灾的核心科技。中国数值天气预报研究和业务应用一直受到高度重视,在理论、方法和数值模式研究方面取得了有广泛国际影响的研究成果。在回顾新中国数值天气预报自主创新研究成果的基础上,重点对GRAPES(Global Regional Assimilation and PrEdiction System)半隐式半拉格朗日格点模式与物理过程的研发和业务应用的状况以及所取得的重要科学进展进行了综述。近年来,通过自主研发建立了中国数值天气预报业务体系—GRAPES体系。首次以自主技术实现了从区域3—10 km到全球25—50 km分辨率的确定性预报和集合预报系统,并在模式动力框架、四维变分同化和卫星资料同化技术等方面有所突破,建立了大气化学数值天气预报、台风数值预报和海浪预报等系统。自主研发的数值天气预报体系的建立是长期坚持既定科学技术方向以及研究和业务紧密结合、经验不断积累的结果,是中国自主发展数值天气预报技术的重要起点。     

地形跟随坐标下的中尺度模式气压梯度力计算误差分析及其改进方案

GRAPES_Meso模式预报存在南风偏大、虚假降水偏多等问题,且在大地形下游地区异常明显。平缓-混合坐标可以有效减小气压梯度力计算误差以及平流输送误差,而这两种误差与风场和水汽场预报密切相关。基于GRAPES_Meso模式选择四种平缓-混合坐标对一次典型的高原东部准静止锋降水过程进行模拟分析。模拟结果表明,较弱的天气形势演变下,平缓-混合坐标的改进效果比较明显,可以有效缓解风场预报偏差、虚假降水、虚假天气系统等问题,个例模拟的结果与实况更接近。

     

数值天气预报业务模式现状与展望

动力统计结合是提高天气、气候预报水平的重要途径之一,关键问题是如何将数值模式与历史资料进行有效结合;相似预报这一传统方法与动力统计的结合是未来提高天气、气候预报水平的一个重要方向,尽管其原理目前仍停留在相似假设基础上且缺乏坚实的物理基础。文中从准确模式的初值问题出发,提出准确模式初值扰动概念,进而发展了动力统计相似集合预报（Dynamical Statistical Analog Ensemble Forecast,DSAEF）理论。DSAEF理论不仅回答了为什么可以进行相似预报,同时还指出了如何进行相似预报,即其原理是利用准确模式来做预报,并采用集合预报的方式实现预报。基于 DSAEF 理论,建立了登陆台风降水动力统计相似集合预报DSAEF_LTP （Landfalling Typhoon Precipitation,LTP）模型,该模型包括4个步骤：台风路径预报、广义初值构建、初值相似性判别和台风降水集合,其中广义初值由影响台风降水的物理因子构成。DSAEF_LTP模型具有可持续发展特性—可通过引入新因子或改善模型参数来改进模型的性能;目前该模型发布了广义初值包含台风路径、登陆季节和台风强度3个物理因子的1.0版和在此基础上改进了“相似区域”和“集合方案”的1.1版。该模型的性能提升很快,已完成的最新版本（1.1版）3次大样本预报试验均显示,与ECMWF、CMA-GFS、NCEP-GFS和SMS-WARMS （上海区域模式）对比,对≥100 mm和≥250 mm台风过程降水预报的TS评分,DSAEF_LTP模型（V1.1）排名第1。今后,围绕广义初值不断改善,研究引入更多影响登陆台风降水的物理因子,DSAEF_LTP 模型的发展前景广阔。     

The effect of horizontal resolution on ocean surface heat fluxes in the ECMWF model

Annual mean ocean surface heat fluxes have been studied as a function of horizontal resolution in the ECMWF model (cycle 33) and compared with Oberhuber's COADS (1959–1979) based empirical estimates. The model has been run at resolutions of T21, T42, T63 and T106 for 15 months with prescribed monthly varying climatological SST and sea ice. The T42 simulation was extended to 2 years, which enabled us to determine that many differences between the resolution runs were significant and could not be explained by the fact that individual realizations of an ensemble of years can be expected to give different estimates of the annual mean climate state. In addition to systematic differences between the modeled and the observed fluxes, the simulated fields of surface shortwave and longwave radiation showed much more spatial variability than the observed estimates. In the case of the longwave radiation this may be attributable more to deficiencies in the observations than to errors in the model. The modeled latent and sensible heat fields were in better agreement with observations. The primary conclusion concerning the dependence of ocean surface fluxes on resolution is that the T21 simulation differed significantly from the higher resolution runs, especially in the tropics. Although the differences among the three higher resolution simulations were generally small over most of the world ocean, there were local areas with large differences. It appears, therefore, that in relation to ocean surface heat fluxes, a resolution greater than T42 may not be justified for climate model simulations, although the locally large differences found between the higher resolution runs suggest that convergence has not been achieved everywhere even at T106.     

基于三种机器学习方法的降水相态高分辨率格点预报模型的构建及对比分析

冬季降水相态及其转变时间的精细化客观预报对提高气象预报和服务质量具有重要的现实意义。利用京津冀地区国家级自动气象站观测资料及网格化快速更新精细集成产品,统计分析了京津冀地区复杂地形下各类降水相态温度和湿球温度平均气候概率的分布差异及不同降水相态时网格化快速更新精细集成产品中可能影响降水相态判断的特征信息。然后将地面观测天气现象资料、复杂地形下降水相态气候特征及高分辨率模式输出产品作为特征向量,分别基于梯度提升（XGBoost）、支持向量机（SVM）、深度神经网络（DNN）3种机器学习方法建立了降水相态的高分辨率客观分类模型,并对同样条件下3种机器学习方法对雨、雨夹雪和雪3种京津冀主要降水相态的预报效果进行了对比检验,进一步提升了雨夹雪复杂降水相态的客观分类预报技巧。      

The impact of observation systems on medium-range weather forecasting in a global forecast system

To investigate the impact of various types of data on medium-range forecasts, observing system experiments are performed using an assimilation algorithm based on the National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) reanalysis system. Data-denial experiments for radiosonde, satellite, aircraft, and sea surface observations, and selected data experiments for radiosonde and surface data, are conducted for the boreal summer of 1997 and the boreal winter of 1997/1998. The data assimilation system used in this study is remarkably dependent on radiosonde data, which provides information about the three-dimensional structure of the atmosphere. As expected, the impact of radiosonde observations on medium-range forecasts is strongly positive over the Northern Hemisphere and tropics, whereas the satellite system is most beneficial over the Southern Hemisphere. These results are also found in experiments simulating historical changes in observation systems. Over the tropics, assimilation without radiosonde observations generates unbalanced analyses resulting in unrealistic forecasts that must be corrected by the forecast model. Forecasts based on analysis from the observation data before the era of radiosonde observation are found to be less meaningful. In addition, the impacts on forecasts are closely related to the geographical distribution of observation data. The memory of observation data embedded in the analysis tends to persist throughout forecasts. However, cases exist where the effect of forecast error growth is more dominant than that of analysis error, e.g., over East Asia in summer, and where the deficiency in observations is supplemented or the imbalance in analysis is adjusted by the forecast model during the period of forecasts. Forecast error growth may be related to the synoptic correction performed by the data assimilation system. Over data-rich areas, analysis fields are corrected to a greater extent by the data assimilation system than are those over data-poor areas, which can cause the forecast model to produce more forecast errors in medium-range forecasts. It is found that even one month per season is sufficient for forecast skill verification in data impact experiments. Additionally, the use of upper-air observations is found to benefit areas that are downstream of observation data-rich areas.     

Parametrization and influence of subgridscale orography in general circulation and numerical weather prediction models

Summary The problem of representing the drag due to subgridscale orography is examined. Results from model simulations are used to illustrate clear deficiencies in the global angular momentum budgets and possible ways of correcting for these deficiencies are considered. It is argued that a formulation for the stress due to subgridscale gravity waves is required, as was first recognized by Boer et al. (1984a, b), and the impact of a scheme based on Palmer et al. (1986) is presented. The scheme is improved by using directionally-dependent subgridscale orographic variances. Results from 90-day integrations using the ECMWF and UKMO models with similar resolutions are very much in accord both with and without a wave drag parametrization scheme; showing much improved wintertime circulations.The relationship between the wave drag and the model orography is examined with the use of idealized stress profiles whereby the wave drag is limited to either near the surface or in the stratosphere. A combination of parametrized wave drag with an envelope orography performs best at this stage of development.Results are presented from a substantial series of ten-day forecast experiments with the ECMWF operational model using mean and (1 ) envelope orographies, these show significant improvements in forecast skill.With 26 Figures     

基于ECMWF和华东区域中尺度模式的暴雨预报特征研究北大核心

为探讨ECMWF、华东区域中尺度模式(简称为CMA-SH9模式)多个时效对夏季(2019年6—8月)暴雨预报特征,采用目标对象检验方法对不同类型影响系统下模式预报的强降水落区面积、位置、形状等进行评价,并对预报难度较大的受西风槽和西太平洋副热带高压(以下简称副高)边缘切变线影响的高空要素场及环流形势场进行了研究。结果表明:ECMWF和CMA-SH9模式对夏季暴雨预报偏小3个量级次数最多,CMA-SH9模式各时效对暴雨及以上降水预报的准确率大多高于ECMWF;ECMWF和CMA-SH9模式对热带气旋与中纬度系统相互作用的暴雨预报最好,其次是冷涡影响,预报较差的是受西风槽及副高边缘切变线影响的暴雨过程;西风槽及副高边缘切变线影响时ECMWF的位势高度场预报略好于CMA-SH9模式,温度的预报500 hPa以上CMA-SH9模式略好于ECMWF,500 hPa以下二者相差不大,相对湿度的预报CMA-SH9模式误差小于ECMWF,且CMA-SH9模式850 hPa的36 h和60 h时效预报误差最小;受西风槽及副高边缘切变线影响的一次暴雨过程中,相对湿度90%及以上落区的预报ECMWF与实况10 mm·h^(-1)降水落区几乎无交集,CMA-SH9模式的预报包含了10 mm降水落区。     

ECMWF细网格数值预报产品在乌鲁木齐东南大风 预报中的释用

利用ECMWF细网格数值预报产品和区域自动站、风廓线雷达等常规观测资料,对乌鲁木齐2013年春季南郊发生的一次东南大风过程进行诊断分析和预报释用,揭示了乌鲁木齐东南大风发生和维持的物理机制,发现细网格资料在预报时空分辨率和预报性能等方面均有提高,对东南大风预报具有指示意义,提高了预报的准确性。分析表明：达坂城至南郊一带东南风频发是由于春季地面蒙古高压部分南掉,形成东西间气压梯度力同乌鲁木齐南郊地形狭管方向一致时,并在“慢坡”重力下滑的共同作用下所形成的回流型东南大风;细网格850hPa风矢量、10m高度上的风、海平面气压场、2m高度上的温度等要素预报,对乌鲁木齐南郊东南大风的起止时间、风速量级及落区的预报有较好指示意义。     

河南\

对1949年以来影响我国的台风暴雨及其预报研究的进展,从台风暴雨形成机理、专题研究、预报研究和研究新动向等四方面进行回顾总结。首先,从环境场、下垫面和内部条件三个角度对台风暴雨形成机理进行简要回顾,并从“75.8”特大暴雨、“莫拉克”极端暴雨、远距离暴雨、台风暴雨的诊断分析和气候特征等五个角度做了专题回顾。同时,简要回顾了台风暴雨预报研究进展,并就台风暴雨研究新动向给出了在云微物理、极端降水和预报方法三个方向上的初步判断。在此基础上,给出了小结与展望。

     

Toward the development of prediction models for the primary Caribbean dry season

Summary Two statistical models are created for the Caribbean during its dry season. Canonical correlation analysis (CCA) confirms that there is a robust El Ni?o Southern Oscillation (ENSO) signal in the region during the dry season and that the mode manifests itself as oppositely signed precipitation anomalies over the north and south Caribbean. The south-eastern Caribbean becomes dry in response to a warm event. The first statistical model consequently uses a rainfall index averaged over the south-eastern Caribbean as the predictand. A model which retains an ENSO proxy as one of two predictors shows reasonable skill with hindcast predictions for the region. A second model is created using a Jamaican rainfall index as predictand. Jamaica falls in the transition zone i.e. between the oppositely signed north-south precipitation anomalies characteristic of the ENSO dry season mode. In this case no ENSO related predictor is retained in the final model. Composite analysis of select atmospheric variables for anomalously high and low rainfall years (for the dry season) give an understanding of the dynamics of the Caribbean dry season during phases of the ENSO, particularly those which lead to the creation of the transition zone. Authors’ address: Tannecia S. Stephenson, A. Anthony Chen, Michael A. Taylor, Department of Physics, University of the West Indies, Mona, Jamaica.     

On the assimilation of satellite sounder data in cloudy skies in numerical weather prediction models

Satellite measurements are an important source of global observations in support of numerical weather prediction (NWP). The assimilation of satellite radiances under clear skies has greatly improved NWP forecast scores. However, the application of radiances in cloudy skies remains a significant challenge. In order to better assimilate radiances in cloudy skies, it is very important to detect any clear field-of-view (FOV) accurately and assimilate cloudy radiances appropriately. Research progress on both clear FOV detection methodologies and cloudy radiance assimilation techniques are reviewed in this paper. Overview on approaches being implemented in the operational centers and studied by the satellite data assimilation research community is presented. Challenges and future directions for satellite sounder radiance assimilation in cloudy skies in NWP models are also discussed.     

ECMWF seasonal forecast system 3 and its prediction of sea surface temperature

The latest operational version of the ECMWF seasonal forecasting system is described. It shows noticeably improved skill for sea surface temperature (SST) prediction compared with previous versions, particularly with respect to El Nino related variability. Substantial skill is shown for lead times up to 1?year, although at this range the spread in the ensemble forecast implies a loss of predictability large enough to account for most of the forecast error variance, suggesting only moderate scope for improving long range El Nino forecasts. At shorter ranges, particularly 3?C6?months, skill is still substantially below the model-estimated predictability limit. SST forecast skill is higher for more recent periods than earlier ones. Analysis shows that although various factors can affect scores in particular periods, the improvement from 1994 onwards seems to be robust, and is most plausibly due to improvements in the observing system made at that time. The improvement in forecast skill is most evident for 3-month forecasts starting in February, where predictions of NINO3.4 SST from 1994 to present have been almost without fault. It is argued that in situations where the impact of model error is small, the value of improved observational data can be seen most clearly. Significant skill is also shown in the equatorial Indian Ocean, although predictive skill in parts of the tropical Atlantic are relatively poor. SST forecast errors can be especially high in the Southern Ocean.     

A numerical research on the influences of the diurnal variation of solar radiation on the medium-range weather processes

In this paper, we use a spectral model for the medium-range numerical weather forecast to discuss the impact of the diurnal variation of solar radiation on the medium-range weather processes. Under the tests of two typical winter and summer cases, we find that the influences of the diurnal variation of solar radiation on summer weather are really important, especially on its rainfall, surface heat transport and 500 hPa height field. On winter weather, however, the influences are very weak.     

数值天气预报和气候预测的可预报性问题

考察由初始状态误差和模式中参数误差所引起的预报结果的不确定性。提出了数值天气预报与气候预测中三类可预报性问题，即，最大可预报时间，最大预报误差，初值与参数的最大允许误差。然后将这三类问题化成了对应的非线性优化问题，给出了处理此类非线性优化问题的思路，并且有数值方法对Lorenz模型研究了这三类问题。