PRELIMINARY STUDY OF BAROTROPIC STOCHASTIC DIFFERENCE MODEL APPLIED TO WEATHER PREDICTION

In order to consider both the deterministic and the stochastic property of atmospheric motion simul-taneously,in this paper,the weather prediction is proposed as the problem of the evolution of meteorologicalfield.The historical viewpoint of atmospheric motion is emphasized here.Based on time series analysis te-chnique,a stochastic-dynamical model with multiple initial fields is derived.Thus,weather forecasting is sum-meal up as a problem of solving a set of stochastic difference equations.For the barotropic atmosphere,thenumerical solutions of the equations are obtained by using the method of empirical orthogonal functions(EOF),and examples of medium-range weather prediction are given here.Meanwhile,selecting the order oftime series,i.e.,determining the number of initial fields properly,is also discussed.     

A TECHNIQUE TO RECOGNIZE AND ESTIMATE SEVERE STORM BY USING SINGLE DOPPLER WEATHER RADAR

Using single Doppler weather radar echo information, this paper presents a technique for recognizing two-di-mensional flow field structure of the severe storm and estimating the divergence, the vorticity, and the intensityof wind shear line, and gives some examples.     

局地强风暴云团与中尺度锋面波动

本文分析了1982—1988年2—5月份的41例与中尺度锋面波动相关联的局地强风暴云团的活动和演变特征，给出了其强盛期天气系统配置模式及其在天气尺度云系演变中的表现型式，最后对其移动做了一般性讨论。     

参考大气在中期天气预报和气候模拟中的应用

本文概述了根据应用参考大气概念提出的参考大气谱模式计算格式（或称静力扣除法）在国内外一些气象机构的中期天气预报、后处理和四维同化、以及气候模拟中的应用。计算表明，这种参考大气谱模式计算格式，能有效的减少截谱误差，明显地改进中期天气预报和气候模拟。     

梧州市森林火险气象预报

使用１９８０－１９９１年森林火灾及相应的气象资料，分析了森林火灾与有关气象要素的相关性。在此基础上，计算了森林火险天气预报指标，建立了预报模式，开展了森林火险天气等级预报。经试用效果较好。     

1993年北半球环流特征及其对我国天气气候的影响

１９９３年北半球主要环流特征表现为：５００ｈＰａ副产持续加强西伸，位置偏南；亚洲中纬度春，夏经向环流发展，东亚太平洋遥相关型稳定；西藏高原５００ｈＰａ位势高度持续偏高，印缅槽持续偏弱；１００ｈＰａ位势高度场低纬持续偏高，中，高纬持续偏低，夏季南亚高压位置异常偏高。热带海洋出现明显异常，一次新的厄尔尼诺现象发生。热带海洋和北半球大气环流的异常对我国天气气候产生明显影响。     

人工神经网络在天气预报中的应用研究

介绍了将人工神经元网络用于灾害性天气（暴雨）预报研究的情况，分析了天气预报问题的数学提法及困难所在，神经元网络用于天气预报的原理，暴雨预报的特点及我们对网络模型的改进。结果表明，神经风格确可通过学习从原始数据中提取足够的分类信息，达到较好的预报准确率，值得进一步研究。     

CHARACTERISTICS OF TURBULENCE SPECTRA IN DIFFERENT WEATHER PROCESSES UNDER UNSTABLE CONDITIONS*

In this paper,the data chosen from measurements by supersonic anemometers in Tongxian County of Beijing in 1990 are used to study characteristics of turbulence spectra in precipitation weather.Some turbulence parameters such as turbulence intensity,heat and momentum fluxes,friction velocity,M-O length and stability parameter are calculated and their dependence on turbulence spectra in different stability conditions are analyzed.Some encouraging results are obtained and compared with others' results.     

Development of Artificial Intelligence Technology in Weather Forecast

Numerical weather prediction, which is the major basis of current weather forecast, has some shortcomings, such as the understanding of the law of atmospheric motion, the assimilation and application of observation data, the expression of model physics, etc., leading to the forecast error of weather. The rapid development of artificial intelligence technology in recent years provides a new possibility for the advancement and innovation of weather forecast. In this paper, the background of the development of artificial intelligence, the current situation of the application of artificial intelligence technology to weather forecast and the future development trend are mainly described to account for this possibility. After that, the idea for development of weather forecast technology based on the integration of artificial intelligence and numerical forecast is put forward. Particularly, this study stresses that, in order to advance the AI algorithm of weather forecast in the future, it is requested to focus on the nonlinear and chaotic characteristics of atmospheric motion leading to the uncertainty of forecast. Starting from the essence of mathematics and physics, we need to realize the hybrid modeling of mathematics and physics, not only to establish the framework of input-output mapping, but also to provide solutions to the bottleneck problems of weather forecast.