诊断天气气候时间序列极值特征的一种新方法

将平稳过程的交叉理论用于天气气候极值分析,提出了一种诊断天气气候时间序列极值特征量的新方法,在正态假设下,推证出天气气候记录中,极值出现频数、持续时间和等待时间的估计公式,论证了极值出现频数与其频谱结构的对应关系及其相互推算方法.实例应用表明,其理论计算值与实测值相当一致,这种方法对于气候变化诊断与预测和天气预报具有很强的实用价值.     

日本气象研究所数值模拟现状调研及展望

文章介绍了日本气象研究所利用数值天气预报模式对中尺度天气、台风、气候和海洋变化等进行数值模拟的现状及其展望。     

高温天气的分析与预报

高温天气的分析与预报王正旺，庞转棠（长治市气象局０４６０００）１引言高温是一种灾害性天气。高温能影响作物开花授粉，造成空壳猛增，可加速植株蒸腾，破坏水分代谢活动而发生萎谢。在作物生长后期使作物逼热而粒重减轻等。高温对人体健康也具有一定影响。当人体皮肤...     

北京地区强对流天气短时预报方法的研究

本文由两部分组成，第一部分分析了北京地区冰雹落区与中尺度天气系统、散度场、涡度场、地面总能量场及相对湿度分布的关系。在此基础上概括出冰雹落区的概念模式，为冰雹落区预报提供了一种依据。第二部分说明了利用北京０８时单站探空资料预报强对流天气有无及强度的判断树方法，为强对流天气的短时预报提供了有应用价值的思路和方法。     

一次转折性天气的预报

1 简 述 1992年绥化地区严重的干旱持续到初夏,6月上旬中受强冷空气侵袭,我区出现了5—7天的低温阴雨天气,降水明显偏多,发生了历史同期罕见的局地大雨和暴雨,本旬气温偏低4℃—5℃,出现了夏季冷害,对这次转折性天气,预报准确,取得很好的服务效果。     

气象台天气分析预报技术发展走向和对策研究--气象台天气分析预报技术走向研究之二

气象台预报位于天气预报服务第一线，加快发展气象台业务预报技术为当前急需。本文继时省地气象台预报技术现状的评估之后，利用新一代业务技术体制专题研究报告和国外考察报告作二次分析研究，试图理清气象台业务预报技术今后发展的环境、发展的前景和基本框架及某些发展规律，并就其中某些重要技术工作展开讨论。     

河南省强对流天气的特征与预报

选取１９９４￣１９９６年７１４ＣＤ雷达资料中较完整的７次河南省区域强对流天气过程,从大尺度环境场、稳定度参数、水汽条件、中尺度流场和７１４ＣＤ强度场、速度场等方面进行了详细分析,寻找其共性和差异,为做好河南省区域强对流天气的监测和预报提出了一些有实用价值的预报依据和指标。     

Non-Gaussian Lagrangian Stochastic Model for Wind Field Simulation in the Surface Layer

Wind field simulation in the surface layer is often used to manage natural resources in terms of air quality, gene flow(through pollen drift), and plant disease transmission(spore dispersion). Although Lagrangian stochastic(LS) models describe stochastic wind behaviors, such models assume that wind velocities follow Gaussian distributions. However,measured surface-layer wind velocities show a strong skewness and kurtosis. This paper presents an improved model, a non-Gaussian LS model, which inco...     

An Improved, Downscaled, Fine Model for Simulation of Daily Weather States

In this study,changes in daily weather states were treated as a complex Markov chain process,based on a continuous-time watershed model(soil water assessment tool,SWAT) developed by the Agricultural Research Service at the U.S.Department of Agriculture(USDA-ARS).A finer classification using total cloud amount for dry states was adopted,and dry days were classified into three states:clear,cloudy,and overcast(rain free).Multistate transition models for dry-and wet-day series were constructed to comprehensively downscale the simulation of regional daily climatic states.The results show that the finer,improved,downscaled model overcame the oversimplified treatment of a two-weather state model and is free of the shortcomings of a multistate model that neglects finer classification of dry days(i.e.,finer classification was applied only to wet days).As a result,overall simulation of weather states based on the SWAT greatly improved,and the improvement in simulating daily temperature and radiation was especially significant.     

克拉玛依特强大风的气候特征及天气分析与预报

分析1971—2006年克拉玛依11级以上特强大风天气的气候特征,总结了年代际变化及月、季分布特点。研究显示,在全球气候变暖造成极端天气事件明显增多的大气候背景下,克拉玛依特强大风天气呈明显减少趋势。在这种气候背景下,利用NCEP资料,分析了克拉玛依发生特强大风的主要天气形势特征,提出预报思路,给出预报经验指标,提高对特强大风的防范意识和预报能力     

Footprints in Homogeneously and Heterogeneously Driven Boundary Layers Derived from a Lagrangian Stochastic Particle Model Embedded into Large-Eddy Simulation

A Lagrangian stochastic (LS) model, which is embedded into a parallelised large-eddy simulation (LES) model, is used for dispersion and footprint evaluations. For the first time an online coupling between LES and LS models is applied. The new model reproduces concentration patterns, which were obtained in prior studies, provided that subgrid-scale turbulence is included in the LS model. Comparisons with prior studies show that the model evaluates footprints successfully. Streamwise dispersion leads to footprint maxima that are situated less far upstream than previously reported. Negative flux footprints are detected in the convective boundary layer (CBL). The wide range of applicability of the model is shown by applying it under neutral and stable stratification. It is pointed out that the turning of the wind direction with height leads to a considerable dependency of source areas on height. First results of an application to a heterogeneously heated CBL are presented, which emphasize that footprints are severely affected by the inhomogeneity.     

A Large-Eddy Simulation and Lagrangian Stochastic Study of Heavy Particle Dispersion in the Convective Boundary Layer

Large-eddy simulation and Lagrangian stochastic dispersion models were used to study heavy particle dispersion in the convective boundary layer (CBL). The effects of various geostrophic winds, particle diameters, and subgrid-scale (SGS) turbulence were investigated. Results showed an obvious depression in the vertical dispersion of heavy particles in the CBL and major vertical stratification in the distribution of particle concentrations, relative to the passive dispersion. Stronger geostrophic winds tended to increase the dispersion of heavy particles in the lower CBL. The SGS turbulence, particularly near the surface, markedly influenced the dispersion of heavy particles in the CBL. For reference, simulations using passive particles were also conducted; these simulation results agreed well with results from previous convective tank experiments and numerical simulations.     

大气环流模式与春玉米生长模拟模式联接的影响评估模拟试验

根据春玉米田间试验资料和历史气候资料,对春玉米生长模拟模式进行了验证与灵敏性分析,在此基础上,运用逐步订正法将当前气候前景和大气环流模式输出资料结合历史气候资料生成的未来气候情景订正到１ｏ×１ｏ网格点上,与春玉米生长模拟模式相联接,就未来气候变化对我国东北地区春玉米生长、发育和最终产量的可能影响进行了网格化定量模拟,并对一些适应性对策的效果进行了定性或定量的分析。结果表明,在ＤＫＲＺＯＰＹＣ模拟的未来情景下,若保持当前作物品种和生产技术措施不变,研究区域除北部将平均增产７０％外,其余地区都将有不同程度的减产,幅度在－１０％～－５０％之间,而在ＮＣＡＲ模拟的情景下,中西部地区将增产,其它地区可维持当前产量水平。适应性对策将对开发利用未来可能的气候资源,减缓未来气候变化的负效应,充分发挥其正效应起到积极作用,进而绝大部分区域将受益于未来水热条件的改变。     

多层土壤温度模拟及其检验

对陆面过程模式(BATS)土壤温度模拟进行了改进,提出了一个利用气象站资料模拟土壤温度的模式。研究结果表明：采用热扩散方程模拟多层土壤温度,可与观测站的资料直接比较;模式能很好地模拟各层土壤温度的年变化、季变化、日变化。冬季下层土壤温度高于上层土壤温度,夏季上层土壤温度高于下层土壤温度,上下层温度的转换时间大约在3月份和10月份,这与实测土壤温度的年变化非常一致;模式较准确地模拟了各层土壤温度垂直方向变化的时滞效应。     

非正态分布的天气气候序列极值特征诊断方法研究

推广了非正态假设下的交叉理论,且将其用于极值特征的诊断,并从理论上导出了适用性更广的基于Gamma分布和负指数分布的极值特征量诊断公式及其样本估计式.以有关降水要素的时间序列为例,说明了这种方法在天气气候诊断与气候影响研究中的应用前景.     

High-resolution Simulation of an Extreme Heavy Rainfall Event in Shanghai Using the Weather Research and Forecasting Model: Sensitivity to Planetary Boundary Layer Parameterization

In this study,an extreme rainfall event that occurred on 25 May 2018 over Shanghai and its nearby area was simulated using the Weather Research and Forecasting model,with a focus on the effects of planetary boundary layer(PBL)physics using double nesting with large grid ratios(15:1 and 9:1).The sensitivity of the precipitation forecast was examined through three PBL schemes:the Yonsei University Scheme,the Mellor?Yamada?Nakanishi Niino Level 2.5(MYNN)scheme,and the Mellor?Yamada?Janjic scheme.The PBL effects on boundary layer structures,convective thermodynamic and large-scale forcings were investigated to explain the model differences in extreme rainfall distributions and hourly variations.The results indicated that in single coarser grids(15 km and 9 km),the extreme rainfall amount was largely underestimated with all three PBL schemes.In the inner 1-km grid,the underestimated intensity was improved;however,using the MYNN scheme for the 1-km grid domain with explicitly resolved convection and nested within the 9-km grid using the Kain?Fritsch cumulus scheme,significant advantages over the other PBL schemes are revealed in predicting the extreme rainfall distribution and the time of primary peak rainfall.MYNN,with the weakest vertical mixing,produced the shallowest and most humid inversion layer with the lowest lifting condensation level,but stronger wind fields and upward motions from the top of the boundary layer to upper levels.These factors all facilitate the development of deep convection and moisture transport for intense precipitation,and result in its most realistic prediction of the primary rainfall peak.