复杂地形局地环流的数值模拟研究

采用一个三维中尺度动力学诊断模式,对重庆地区气象场进行了实例模拟,研究了复杂地形和不同下垫面型对流场的动力和热力作用,揭示了中尺度局地环流（山谷风、河陆风）的基本特征和变化规律,模拟结果与实测资料有好的一致性,表明该模式能够成功地模拟复杂地形局地环流。     

金塔绿洲大气边界层特征的数值模拟研究

利用美国NCAR中心的天气研究与预报模式WRF(weather Research and Forecast Model),对金塔绿洲的环流场、温度场及湿度场结构及其日变化进行了较为全面细致的模拟研究,WRF模式很好地模拟出了绿洲一沙漠环流的日变化特征和这种局地热力环流的空间结构,模拟再现了绿洲“冷岛效应”和邻近绿洲的沙漠“逆湿”等边界层特征．模拟还发州了白天绿洲湿度场“凹型槽,,式分布的特征。     

济南市城市热岛和山谷风环流的模拟研究

基于区域大气模拟系统(RAMS),采用水平网格嵌套等方法,实现了使用同一模式对区域尺度和城市尺度气象场的同步模拟.作者重点模拟和分析了济南地区两种典型的中尺度局地环流--城市热岛环流和山谷风环流.在考虑复杂地形条件和非均匀下垫面型对中尺度天气系统的动力过程和热力过程的影响下,结合考虑长短波辐射、湍流扩散和积云对流等多类重要物理过程,揭示了影响济南地区这两种中尺度局地环流的基本特征及其形成、演变规律.       

一个变网格大气环流模式对中国东部春季的区域气候模拟

将法国动力气象实验室发展的变网格全球大气环流模式LMDZ4在东亚地区进行加密,并使用ERA-40再分析资料进行环流强迫,对1958—2000年每年春季开展区域气候模拟,将模拟的4—5月气候平均态、年际和年代际变率与观测进行了对比。模式能够较为真实地模拟出4—5月东亚地区气候平均大气环流、降水和气温的空间分布,对对流层中、高层环流的模拟比对低层环流的模拟更接近于观测;模式对中国东部地区地面气候的模拟偏差主要表现为:中国中东部和华南地区偏暖偏湿,而华北则为偏冷偏湿。中东部地区的降水量比观测偏多约1.6mm/d;模拟的地表气温在华北偏低约1.4℃,在中东部和华南均偏高超过0.5℃。模式对降水的模拟偏差与其模拟的低层南支西南气流和北部西北气流均偏强有关。模式对中国东部对流层,尤其是对流层中上层大气环流的年际变化具有很好的再现能力,各物理量与观测值的相关系数都在0.6以上。模式也能很好地模拟出中国东部降水和气温的年际变率,在华北、中东部和华南,观测和模拟值在1958—2000年的相关系数均在0.7以上。模式还能够模拟出20世纪70年代末出现的中东部干旱和东北地区降水增多的年代际变化特征,也能够再现黄淮流域年代际增温的现...     

非静力、完全弹性二维中尺度模式的建立及数值试验研究

建立了一个非静力、安全弹性的二维中～β(γ)尺度数值模式。该模式对海风环流的模拟,验证了此模式对中尺度环流的模拟能力。利用该模式模拟了重庆地区复杂下垫面边界层气象要素场,探讨了地形、水陆分布、城市热岛及其相互作用,对边界层气象要素场分布的影响。     

北极海冰数值预报的初步研究——基于海冰—海洋耦合模式MITgcm的模拟试验

利用最近发展的MITgcm(麻省理工学院通用环流模式)海冰-海洋耦合模式,以NCEP(美国国家环境预测中心)再分析资料为大气强迫场进行了1992年1月至2009年12月北极海冰数值模拟.结果表明,此模式能很好地模拟卫星观测的北极海冰季节和年际变化,具备很好的北极海冰数值模拟能力.以此为基础,对2009年7月和10月北极...     

三维非静力二阶闭合PBL模式的初步研究

采用二阶距湍流闭合方案，建立了一个复杂地形下的三维非静力边界层预报模式。通过该模式，细致了模拟了北京地区的风、温时空变化和湍流场变化。结合地面、探空和气象塔的实测资料，进一步研究了该方案在三维空间上对平均场和湍流场的预报模拟效能。结果表明该模式能较好地进行平均量和湍流量的模拟和预报。     

广州地区局地环流的数值模拟

利用中国科学院大气物理研究所的Eta模式和中-β气象预报模式,选择广州地区不同季节的47天,得到47例(包括夏季和冬季)24h环流的数值模拟结果,经过认真分析。得到影响广州地区的主要局地环流型有三种,即辐合气流型、辐散气流型、热岛环流型。从模拟的统计结果来看,辐合气流型、辐散气流型、热岛环流型分别为28％、26％、36％,为广州市空气污染数值预报提供了典型的气象场资料。     

中β尺度系统造成的大暴雨过程数值模拟与诊断分析

利用T106资料和MM5V3．5中尺度非静力模式对2002年6月8—9日发生在陕西和四川东北部的一次突发大暴雨过程进行了数值模拟与诊断分析。模拟结果表明：在有利的大尺度环流形势下，中α尺度切变激发的中β尺度系统是本次暴雨的直接引导系统。进一步诊断分析揭示了中β尺度系统的动力场和热力场之间具有一种强耦舍机制：中β尺度系统是在低空急流带上发展起来的，垂直上升运动与近饱和湿空气柱及涡散柱互耦，低空对流不稳定层结的发展触发了强烈的垂直上升运动。模拟结果表明模式能很好地模拟中尺度对流系统的整个发展过程和降水雨带，细网格模拟的降水量与实况比较接近，分析结果可为中尺度暴雨预报提供参考依据．     

台湾地形对海棠台风影响的数值模拟研究

应用美国国家大气研究中心(NCAR)研发的WRF(Weather Research and Forecasting)气象模式,研究海棠台风(2005)接近并登陆台湾岛的过程中的强度、结构的演变,以及地形强迫作用对台风的影响.对模拟结果的评估表明,在整个海棠台风(2005)模拟实验期间,WRF模式很好地抓住了台风海棠强风,低中心气压的高强度特征.对引起台风降水的中尺度系统的分析表明,一方面台风环流与中央山脉地形共同作用激发出垂直次级环流在降水区域产生强烈的上升运动;另一方面,水平风场源源不断给该地区输送暖湿空气,为对流发展提供充足的水汽.分析结果表明中央山脉地形与台风环流场之间的配置形势对台风降水有着重要的影响.     

Monte Carlo多源模式在广东核电站大气环境评价中的应用

发展了ＭｏｎｔｅＣａｒｌｏ多源模式并用于模拟广东核电站排放的放射性污染物浓度分布和干湿沉积量。数值实验和六氟化硫（ＳＦ６）示踪实验表明,模式能很好地反映复杂地形和生态下垫面对污染物的输送、扩散和干湿沉积的影响;与观测值相比,浓度计算值的准确率大于等于５０％的概率为５８４％。     

Autoregressive logistic regression applied to atmospheric circulation patterns

Autoregressive logistic regression models have been successfully applied in medical and pharmacology research fields, and in simple models to analyze weather types. The main purpose of this paper is to introduce a general framework to study atmospheric circulation patterns capable of dealing simultaneously with: seasonality, interannual variability, long-term trends, and autocorrelation of different orders. To show its effectiveness on modeling performance, daily atmospheric circulation patterns identified from observed sea level pressure fields over the Northeastern Atlantic, have been analyzed using this framework. Model predictions are compared with probabilities from the historical database, showing very good fitting diagnostics. In addition, the fitted model is used to simulate the evolution over time of atmospheric circulation patterns using Monte Carlo method. Simulation results are statistically consistent with respect to the historical sequence in terms of (1) probability of occurrence of the different weather types, (2) transition probabilities and (3) persistence. The proposed model constitutes an easy-to-use and powerful tool for a better understanding of the climate system.     

中国北方沙尘天气气象场的数值模拟

利用PSU/NCAR的非静力中尺度气象预报模式MM5对北方地区气象场进行模拟,通过对2001年3月21日发生并影响北京地区的沙尘过程的数值实验表明,该模式能够较好地模拟和预测北方沙尘天气的时空演变特征。低值系统以及其低层辐合、高层辐散的垂直结构,可以产生很强的上升气流,形成地面起沙和沙尘上扬,而强风是沙尘输送的动力条件。利用轨迹模式对空气质点轨迹进行了模拟研究,可以较好地反映沙尘的发生源区和输送路径,与卫星监测和天气系统分析是一致的。并编写软件用于演示气象场的动态效果。     

合成风场的统计检验和蒙特卡洛检验

提出了二维风场的F检验及二维风场的蒙特卡洛检验方法.将方法用于长江流域夏季降水与印度夏季风的研究中,表明方法是有效的.     

气象场相关分析及合成分析中蒙特卡洛检验方法及应用

指出了气象要素及气象要素场显著性检验中的问题，介绍了解决这种问题的蒙特卡洛模拟试验方法。若干要素及气象场相关场检验的蒙特卡洛试验表明，所得结果可以在实际工作中参考使用。     

Carbon Monoxide emission and concentration models for Chiang Mai urban area

An emission inventory containing emissions from traffic and other sources was complied. Based on the analysis, Carbon Monoxide （CO） emissions from traffic play a very important role in CO levels in Chiang Mai area. Analysis showed that CO emissions from traffic during rush hours contributed approximately 90% of total CO emissions. Regional Atmospheric Modeling System （RAMS） was applied to simulate wind fields and temperatures in the Chiang Mai area, and eight ca~es were selected to study annual variations in wind fields and temperatures. Model results can reflect major features of wind fields and diurnal variations in temperatures. For evaluating the model performance, model results were compared with observed wind speed, wind direction and temperature, which were monitored at a meteorological tower. Comparison showed that model results are in good agreement with observations, and the model captured many of the observed features. HYbrid Particle And Concentration Transport model （HYPACT） was used to simulate CO concentration in the Chiang Mai area. Model results generally agree well with observed CO concentrations at the air quality monitoring stations, and can explain observed CO diurnal variations.     

Downscaling of general circulation model outputs: simulation of the snow climatology of the French Alps and sensitivity to climate change

A downscaling method was developed to simulate the seasonal snow cover of the French Alps from general circulation model outputs under various scenarios. It consists of an analogue procedure, which associates a real meteorological situation to a model output. It is based on the comparison between simulated upper air fields and meteorological analyses from the European Centre for Medium-Range Weather Forecasts. The selection uses a nearest neighbour method at a daily time-step. In a second phase, the snow cover is simulated by the snow model CROCUS at several elevations and in the different regions of the French Alps by using data from the real meteorological situations. The method is tested with real data and applied to various ARPEGE/Climat simulations: the present climate and two climate change scenarios. Received: 26 September 1995 / Accepted: 7 August 1996     

北京交通环境污染诊断模拟初步研究

建立了能够用于评估大型城市交通环境污染与气象条件关系的数值模拟技术,即三维边界层光化学数值模式.其中,高分辨率的精细城市边界层气象场、细致的城市地理与环境参数、空气污染物输送扩散与大气化学模拟以及交通废气污染源的分布等诸多因子是实施模拟研究的几个重要环节.从模拟结果看出,各污染物在地面附近浓度相对高值区位于排放源附近和下风方.在边界层顶附近,污染物浓度分布较均匀,分布趋势和气流一致.虽然仅仅考虑了城区污染物本底浓度和主要交通干道机动车的排放,但交通排放对城区污染物浓度的贡献是较大的.     

Assessment of a stochastic downscaling methodology in generating an ensemble of hourly future climate time series

This study extends a stochastic downscaling methodology to generation of an ensemble of hourly time series of meteorological variables that express possible future climate conditions at a point-scale. The stochastic downscaling uses general circulation model (GCM) realizations and an hourly weather generator, the Advanced WEather GENerator (AWE-GEN). Marginal distributions of factors of change are computed for several climate statistics using a Bayesian methodology that can weight GCM realizations based on the model relative performance with respect to a historical climate and a degree of disagreement in projecting future conditions. A Monte Carlo technique is used to sample the factors of change from their respective marginal distributions. As a comparison with traditional approaches, factors of change are also estimated by averaging GCM realizations. With either approach, the derived factors of change are applied to the climate statistics inferred from historical observations to re-evaluate parameters of the weather generator. The re-parameterized generator yields hourly time series of meteorological variables that can be considered to be representative of future climate conditions. In this study, the time series are generated in an ensemble mode to fully reflect the uncertainty of GCM projections, climate stochasticity, as well as uncertainties of the downscaling procedure. Applications of the methodology in reproducing future climate conditions for the periods of 2000–2009, 2046–2065 and 2081–2100, using the period of 1962–1992 as the historical baseline are discussed for the location of Firenze (Italy). The inferences of the methodology for the period of 2000–2009 are tested against observations to assess reliability of the stochastic downscaling procedure in reproducing statistics of meteorological variables at different time scales.