自忆数值模式及其应用

取一个现成的数值模式作为动力核，根据自忆性数学原理，将该数值模式变换为一个自忆数值模式。该模式能包容若干个初始场的信息，这就为提高天气预报和气候预测准确率提供了一种可能和机会，藉此要衍生聘种新的预报途径。文中叙述了自忆数值模式的建模原理，给出了制作全球月温度场预报的实例。     

一种动态数据的新建模法及其预报应用

文章提出了一种新的动态数据建模法, 利用观测的数据序列, 先用双向差分原理反导出一个非线性常微分方程。 以此作为微分动力核, 然后运用自忆性原理建立预报模式, 我们称之为数据机理自记忆模式(Data-based Mechanism Self-memory Model), 简称为数忆模式, 缩写为 DAMSM。 多个实例计算表明, 数忆模式的预报准确率是比较令人满意的, 给出了长江三角洲夏季降水年际预报的实例。     

自忆谱模式制作中期天气预报的试验

基于大气自忆性观点, 引进记忆函数, 可构造一个差分-积分方程; 称之为自忆性方程; 给出了此方程的球谐表达式及其离散计算公式.以T42L9谱模式为动力核, 建立了一个全球自忆T42谱模式 (SMT42).用实际资料进行了逐日至15天积分试验计算, 表明对于500 hPa中期数值天气预报, SMT42比T42的均方根误差小得多, 同时SMT42对距平相关系数也有所提高, 这为中期数值天气预报提供了一种有潜力的新途径.     

北半球春季大气臭变化特征及其对大气温度和环流场的影响

基于大气自忆性观点 ,引进记忆函数 ,可构造一个差分 -积分方程 ;称之为自忆性方程 ;给出了此方程的球谐表达式及其离散计算公式 .以 T42 L9谱模式为动力核 ,建立了一个全球自忆 T42谱模式 (SMT42 ) .用实际资料进行了逐日至 1 5天积分试验计算 ,表明对于 50 0 h Pa中期数值天气预报 ,SMT42比 T42的均方根误差小得多 ,同时 SMT42对距平相关系数也有所提高 ,这为中期数值天气预报提供了一种有潜力的新途径     

区域气候预报自忆模式的研究与计算

从一个区域气候预报自忆模式出发,运用１９５１￣１９９７年江苏省月温度,降水和区域５００ｈＰａ高度场格点资料,确定了自忆函数的具体形式,研究了它的周期性,试作了江苏省１９８７￣１９９７年汛期降水和温度预报。     

自忆预报模式中记忆特性的探讨

运用有限振幅斜压波的截谱方程对自忆模式中的的记忆性进行了理论探讨。推导了相应的自忆性方程,在给定记忆函数呈线性和指数衰减型时求出了它的解析解,并讨论了这些解的物理意义和预报含意;证明了零解自忆性方程与记忆函数形式无关。通过计算遗忘因子,对动力可预报性和回溯阶等问题进行了讨论,并指出可将其统一纳入大气记忆理论的框架中。     

有限区分析预报系统及其业务应用

中国国家气象中心在新开发的有限区多元最优插值分析技术及１５层球面网格原始方程模式的基础上建立了一个新的有限区分析预报系统。１９９１年投入业务使用，主要用于２４－４８ｈ降水预报。这个系统是依附于全球同化预报系统的一个分支系统。亦即使用全球谱模式６ｈ预报作为初估值进行有限区细网格分析及使用其１２—６０ｈ预报作为侧边界值进行非同步嵌套预报。作为一个升级模式系统，它的进步表现在：较充分使用了卫星测湿资料及地面资料的细网格多元最优插值分析；同时使用同场及质量场初值，成功地实现了有限区非线性正规模初始化处理；采用位涡拟能守恒差分格式，包含较真实地形的球面坐标原始方程模式；实现了具有不同模式地形的差分模式与谱模式的嵌套及设计了分级降水客观检验系统。     

中尺度自忆模式在强降水预报中的应用

根据大气自忆性原理提出的回溯时间积分格式应用于中尺度格点模式MM5,构建了中尺度自忆模式SMM5并做了短期强降水预报的实验.结果表明,SMM5模式与MM5模式相比,由于使用了多个时刻的场资料,预报精度有了明显的提高, SMM5预报的最大雨区的中心位置与降水量也比MM5更接近实际观测场.     

动力延伸(月)预报的季节变化和误差分析

本文用中国科学院大气物理研究所的全球谱模式（T42L9）和国家气象中心提供的1994年3月到1995年2月36个例子（每月3个）的全球客观分析资料做了较系统的动力延伸（月）预报试验，检验了预报结果，分析了模式的气候漂移，并对预报结果进行了系统误差订正，结果表明预报评分有明显的季节变化，冬季较高，夏季较低，动力预报高度距平相关系数北半球各个季节的平均都明显高于持续性预报和气候预报。     

带随机初值和随机强迫的简单模式的集合预报试验

本文用简单的准地转正压涡度方程谱模式作为本文模式的动力框架,考虑到作为模式初始场的气象资料中存在着大量的随机误差,以及模式中物理过程的不完善(例如,没有考虑大气与下垫面的相互作用、辐射等),采用在模式中加入随机强迫项和使用随机初值的蒙特卡洛方法,建立了一个统计动力相结合的模式,并用此模式做了1983年1月500hPa月平均高度场的数值预报试验。试验结果表明:同时考虑随机强迫和随机初值的模式预报效果优于纯动力模式、随机初值模式和随机强迫模式的预报效果。     

数值预报误差订正技术中相似-动力方法的发展

Due to the increasing requirement for high-level weather and climate forecasting accuracy, it is necessary to exploit a strategy for model error correction while developing numerical modeling and data assimilation techniques. This study classifies the correction strategies according to the types of forecast errors, and reviews recent studies on these correction strategies. Among others, the analogue-dynamical method has been developed in China, which combines statistical methods with the dynamical model, corrects model errors based on analogue information, and effectively utilizes historical data in dynamical forecasts. In this study, the fundamental principles and technical solutions of the analogue-dynamical method and associated development history for forecasts on different timescales are introduced. It is shown that this method can effectively improve medium- and extended-range forecasts, monthly-average circulation forecast, and short-term climate prediction. As an innovative technique independently developed in China, the analogue- dynamical method plays an important role in both weather forecast and climate prediction, and has potential applications in wider fields.     

集合方法在月动力预报信息提取中的应用

本工作将集合方法应用于提取月动力预报有用信息。利用中国气象局国家气候中心Ｔ６３Ｌ１６全球谱模式的５００百帕高度场月集合预报产品（集合成员数为８个，初始场的选取采用滞后方法（ＬＡＦ），即相邻两天的００００，０６００，１２００和１８００ＧＭＴ的初始化资料），就１９９７年１月至５月共１５次预报，分析了集合预报成员间的离散度与预报评分（距平相关系数和均方根误差）的关系，研究了用集合各成员预报离散度作为各个成员逐日预报的权重对月预报效果的影响。结果表明集合预报成员的离散度与预报评分有显著的相关，是有效预报长度Ｎ的一个很好估计；用离散度作为权重平均的月预报高度距平相关系数明显高于算术平均和线性权重，此外个例分析表明月平均环流及其异常的预报得到明显的提高。     

T63模式月动力延伸预报高度场的改进实验

为克服T63模式月动力延伸预报中纬向平均环流的系统性误差较大的情形,文章利用NCEP/NCAR逐候再分析500 hPa高度场资料和非线性时空序列预测理论的局域近似法进行逐候纬向平均高度距平场预报.近30组个例的预报效果分析表明,就1～3旬总体而言,非线性时空序列预测方法对纬向平均高度距平场的预报优于持续性预报和模式动力延伸预报,体现了改善纬向平均高度场的能力.尤其是第3旬的预报,当持续性预报偏差与实况偏差明显增大、动力预报技巧相对于第1旬和第2旬降低时,相空间重构结果仍然保持一定的优势.     

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     

Intercomparison of the performance of MM5/WRF with and without satellite data assimilation in short-range forecast applications over the Indian region

The present study is conducted to verify the short-range forecasts from mesoscale model version5 (MM5)/weather research and forecasting (WRF) model over the Indian region and to examine the impact of assimilation of quick scatterometer (QSCAT) near surface winds, spectral sensor microwave imager (SSM/I) wind speed and total precipitable water (TPW) on the forecasts by these models using their three-dimensional variational (3D-Var) data assimilation scheme for a 1-month period during July 2006. The control (without satellite data assimilation) as well as 3D-Var sensitivity experiments (with assimilating satellite data) using MM5/WRF were made for 48 h starting daily at 0000 UTC July 2006. The control run is analyzed for the intercomparison of MM5/WRF short-range forecasts and is also used as a baseline for assessing the MM5/WRF 3D-Var satellite data sensitivity experiments. As compared to the observation, the MM5 (WRF) control simulations strengthened (weakened) the cross equatorial flow over southern Arabian sea near peninsular India. The forecasts from MM5 and WRF showed a warm and moist bias at lower and upper levels with a cold bias at the middle level, which shows that the convective schemes of these models may be too active during the simulation. The forecast errors in predicted wind, temperature and humidity at different levels are lesser in WRF as compared to MM5, except the temperature prediction at lower level. The rainfall pattern and prediction skill from day 1 and day 2 forecasts by WRF is superior to MM5. The spatial distribution of forecast impact for wind, temperature, and humidity from 1-month assimilation experiments during July 2006 demonstrated that on average, for 24 and 48-h forecasts, the satellite data improved the MM5/WRF initial condition, so that model errors in predicted meteorological fields got reduced. Among the experiments, MM5/WRF wind speed prediction is most benefited from QSCAT surface wind and SSM/I TPW assimilation while temperature and humidity prediction is mostly improved due to latter. The largest improvement in MM5/WRF rainfall prediction is due to the assimilation of SSM/I TPW. The assimilation of SSM/I wind speed alone in MM5/WRF degraded the humidity and rainfall prediction. In summary the assimilation of satellite data showed similar impact on MM5/WRF prediction; largest improvement due to SSM/I TPW and degradation due to SSM/I wind speed.     

A Global Spectral Model and Test of Its Performance

A brief introduction is given of a global spectral model, its dynamical framework and diabatic physical processes involved. A number of real forecasts are shown to illustrate the forecasting capability of the model for various weather processes. It can even manage to predict some of those typical weather processes in summer which used to be difficult to forecasters.     

Progress in Predictability Studies in China （2003-2006）

Since the last International Union of Geodesy and Geophysics General Assembly(2003),predictability studies in China have made significant progress.For dynamic forecasts,two novel approaches of conditional nonlinear optimal perturbation and nonlinear local Lyapunov exponents were proposed to cope with the predictability problems of weather and climate,which are superior to the corresponding linear theory.A possible mechanism for the"spring predictability barrier"phenomenon for the El Ni(?)o-Southern Oscillation (ENSO)was provided based on a theoretical model.To improve the forecast skill of an intermediate coupled ENSO model,a new initialization scheme was developed,and its applicability was illustrated by hindcast experiments.Using the reconstruction phase space theory and the spatio-temporal series predictive method, Chinese scientists also proposed a new approach to improve dynamical extended range(monthly)prediction and successfully applied it to the monthly-scale predictability of short-term climate variations.In statistical forecasts,it was found that the effects of sea surface temperature on precipitation in China have obvious spatial and temporal distribution features,and that summer precipitation patterns over east China are closely related to the northern atmospheric circulation.For ensemble forecasts,a new initial perturbation method was used to forecast heavy rain in Guangdong and Fujian Provinces on 8 June 1998.Additionally, the ensemble forecast approach was also used for the prediction of a tropical typhoons.A new downscaling model consisting of dynamical and statistical methods was provided to improve the prediction of the monthly mean precipitation.This new downsealing model showed a relatively higher score than the issued operational forecast.     

Multiscale Global Atmosphere Model SL-AV: the Results of Medium-range Weather Forecasts

Development of the multiscale version of the global atmosphere model SL-AV required many improvements in the dynamical core, replacement or refinement of parameterization algorithms and complex tuning of the model. These modifications were initially tested with the experiments on modern climate simulation and then incorporated into the model configuration for medium-range numerical weather prediction. The impact of these model improvements on forecast quality is studied in this paper. The increase in accuracy of model climate characteristics has led to the reduction of forecast errors. The comparison of quality for numerical forecasts starting from the initial data of Hydrometcenter of Russia and ECMWF is carried out. The effect of replacing the initial data turned out to be comparable to the effect of multi-year works on model development. This shows the importance and necessity of development and improvement of the Hydrometcenter of Russia data assimilation system.     

不同海温强迫的月动力延伸集合预报试验

利用全球谱模式T106L19和增长模繁殖法（BGM）建立了月动力延伸集合预报系统,基于气候海表面温度（SST）和预测海表面温度,设计了三组集合预报试验,一组为气候SST作为模式下边界条件的集合预报试验（CSST试验）,另一组为预测SST作为模式的下边界条件的集合预报试验（FSST试验）,第三组为前两组试验的集合预报结果之和（AVE30试验）,对两种海温强迫分别进行了48个月的试验,并对预报结果进行了检验和分析。结果表明：相对于单一的控制预报,不管是CSST试验还是FSST试验,利用BGM方法制作的初值集合预报能显著提高月平均环流的预报技巧,集合预报对PNA区域的预报技巧改进显著,特别是预测SST强迫有正的贡献;同时考虑初值和边值不确定性影响的集合预报试验（AVE30试验）,其全球预报技巧不仅高于控制预报,也分别高于FSST试验和CSST试验,这说明要提高月延伸预报技巧,必须同时考虑初值和边值的影响;大气对SST强迫的响应在模式积分10天开始显著,SST对第二旬和第三旬的作用直接影响月平均环流的预报效果,而SST对第二旬和第三旬预报的影响不仅与SST本身变化有关,还与初值有关,不同的初值其作用不同;集合预报对我国夏季月平均温度分布具有较强预报能力,采用预报海温强迫的预报结果,总体上优于气候海温强迫的结果。