9414号热带气旋(DOUG)非对称结构和对降水影响的分析

ＤＯＵＧ热带气旋在靠近华东沿海大陆北上过程中，气旋西侧的降水强度显著减弱，主要是ＤＯＵＧ气旋的完全非对称结构造成的。本文从大尺度天气系统配置、卫星云图和中尺度数值模式计算结果分析了ＤＯＵＧ气旋内区和外区非对称结构的成因和演变。外区的非对称结构主要由环境场的大尺度天气系统的东高西低气压场配置造成的。气旋近中心中－β尺度的辐散下沉系统的发展是造成内区非对称结构的主要原因。二者的形成是相互独立的。但内区非对称结构的发展会促使外区非对称结构的加强。前者向后者逼近并结合造成了ＤＯＵＧ的完全非对称结构     

USE OF A STOCHASTIC WEATHER GENERATOR IN THE DEVELOPMENT OF CLIMATE CHANGE SCENARIOS

Climate change scenarios with a high spatial and temporal resolution are required in the evaluation of the effects of climate change on agricultural potential and agricultural risk. Such scenarios should reproduce changes in mean weather characteristics as well as incorporate the changes in climate variability indicated by the global climate model (GCM) used. Recent work on the sensitivity of crop models and climatic extremes has clearly demonstrated that changes in variability can have more profound effects on crop yield and on the probability of extreme weather events than simple changes in the mean values. The construction of climate change scenarios based on spatial regression downscaling and on the use of a local stochastic weather generator is described. Regression downscaling translated the coarse resolution GCM grid-box predictions of climate change to site-specific values. These values were then used to perturb the parameters of the stochastic weather generator in order to simulate site-specific daily weather data. This approach permits the incorporation of changes in the mean and variability of climate in a consistent and computationally inexpensive way. The stochastic weather generator used in this study, LARS-WG, has been validated across Europe and has been shown to perform well in the simulation of different weather statistics, including those climatic extremes relevant to agriculture. The importance of downscaling and the incorporation of climate variability are demonstrated at two European sites where climate change scenarios were constructed using the UK Met. Office high resolution GCM equilibrium and transient experiments.     

气候影响评价的两种统计学方法--论广州天气对死亡率的影响

通过最优二分割方法,找出杜会、经济或生物的某种指标(本文用广州死亡率)所敏感的气象变量和临界值,用达到临界值的样本建立指标和气象变量的回归方程,提出了最优二分割--逐步回归模式。还研究了一种最优化天气分型的应用。检验表明,评价天气对死亡率的影响,分割-回归模式比一般回归好,最优化天气分型又比分割-回归好。     

气象要素场概率分布特征的模拟

本文在气象要素区域概率分布模型－锯齿波模型的基础上，通过最小二乘法，拟合了该模型产生的区域气象要素概率分布曲线，并使用得到的拟合函数，模拟了实际气象要素场阈值的概率分布，验证了该模型的有效性，模拟结果表明：模拟值和实际统计值吻合较好，从而可以通过使用拟合函数，由某要素单站概率较方便，准确地得出该要素在区域范围的概率分布特征。     

2004年春季中国沙尘天气特征分析

利用全国681个站的沙尘天气观测资料分析得出,2004年春季中国北方的沙尘天气明显偏少、偏弱,主要表现在：（1）2004年春季681个站累计的沙尘天气日数2 080 d,相当于历史平均值的46.9%,是近四十余年中第三个偏少年份。沙尘暴的总面积约190万km2,仅为历史平均值的37.3%。（2）危害性较大的沙尘暴和强沙尘暴过程6次,不足2001年的一半。（3）4月和5月沙尘天气明显偏少导致整个春季显著偏少。沙尘天气出现时,PM10浓度相对增加,空气质量恶化,但与历史上较典型的强沙尘暴个例相比,PM10浓度增加的幅度不大。进一步分析表明,2004年春季沙尘天气偏少、偏弱的主要原因是大气动力条件不足,是比较特殊的一个年份。     

广州S波段双偏振雷达数据质量初步分析

广东省已经通过新布设或对CINRAD\SA雷达的升级改造完成5部S波段双偏振雷达的业务运行。受目前双偏振雷达技术水平限制,双偏振雷达偏振量很不稳定,因此偏振雷达资料使用前需要对数据可用性、偏振量的系统偏差等进行初步分析,以保证偏振雷达后续产品的可靠性。使用广州S波段双偏振雷达稳定运行后的2016年7—8月连续观测资料,分析了噪声对零滞后相关系数ρ_HV(0)及差分反射率因子Z_DR的影响和订正效果。结果表明:当SNR小于20.0 dB时,偏振参量ρ_HV(0)和Z_DR的稳定性变差,数据不可用;噪声订正后,数据可用的SNR阈值减小为17.0 dB。进一步分析了经过噪声订正后的Z_DR和Z_H之间的关系,并与雨滴谱反演结果及理论值进行对比。结果表明:广州雷达Z_DR较雨滴谱反演值和理论值均偏小,Z_DR观测值存在系统偏差。结合广州的气候特征,对偏振量系统误差估计的微雨滴法的指数进行了调整,基于此方法分析了Z_DR、初始相位Φ_DP (0)的系统误差随方位角的变化。结果表明:Z_DR系统误差随方位角在-0.29~0.22 dB之间波动,剔除遮挡后的平均偏差为-0.09 dB,与实测Z_DR值和雨滴谱反演值及理论值对比偏小的结论一致,但偏差大小有区别;同时,Φ_DP (0)随方位角有4 °左右的波动。分析还发现Z_DR、Φ_DP (0)系统误差有随时间波动的特征。最后挑选个例对Z_DR进行噪声和系统误差订正后发现,订正后的Z_DR得到改善。这些初步分析和结果对S波段双偏振雷达数据的使用有一定的参考意义。      

用天气变量时间序列估计天气的可预报性

本文从非线性系统的吸引子概念出发,用单个气象时间序列重构维数较高的相空间并嵌入天气吸引子,根据相轨道上初始时刻紧邻的点随时间的演化来估计吸引子的维数和天气的可预报性。用500hPa亚洲环流指数和北京冬季气温的逐日资料计算表明,天气吸引子的维数分别为3.8和5.4;可预报时间尺度约6—14天,考虑相空间e指数膨胀因素后为4—9天。     

随机天气模型参数化方案的研究及其模拟能力评估

文中介绍了随机天气模型 WGEN的基本结构及其模拟原理 ,并针对其中随机过程的统计结构特征和 GCMs输出要素的不同时空尺度特点 ,利用动态数据的参数化分析方法等统计学技术 ,确定了该模型参数的估计方法。同时基于蒙特卡罗数值计算原理 ,给出了 WGEN的随机试验方法 ,并通过模拟基准气候 ,从时间分布和空间场两方面对模型在中国东北地区的模拟效果及其能力进行了评估。结果表明 ,模型对于最高气温、最低气温、降水和辐射等要素均具有较好的模拟效果 ,模拟序列与观测序列的取值分布有较一致的概率特性。由此可以结合 GCMs大尺度网格上输出的月和年要素值 ,通过调控随机过程的参数 ,生成具有不同气候变率的 2× CO2 逐日气候变化情景 ,实现气候预测模式与气候影响模式的嵌套 ,进一步研究气候变率变化的可能影响。     

基于单多普勒天气雷达产品的强对流天气预报预警方法

本文对发生在常德新一代天气雷达探测区内的强对流天气(雷雨大风、冰雹、龙卷)在雷达回波强度场及速度场上的表现特征进行了归类分析,既用实例证实了美国强对流天气在多普勒天气雷达产品上的表现特征同样适用于中国,又对其表现特征进行了完善。在此基础上建立了适用于当地的基于单多普勒天气雷达产品的强对流天气预报方法,并根据雷达实时体扫资料对强对流天气进行语音、文字自动报警以及对风暴移向、移速进行预报作了实用性的探讨。在多普勒天气雷达产品应用还处在探索、起步阶段的我国,该方法为制作强对流天气预报提供了较系统的预报思路。     

城市气象保障技术的探讨

本文论述了城市气象服务和保障有关的实施技术,包括城市气象服务和保障中的实时气象资料的采集处理和检索、气候资料的查询分析、城市气象保障产品的制作、城市气象灾害的预报、服务信息的通信传输、应用软件和用户界面的设计等方面的技术,总结了在城市气象保障工作中,特别是大型活动中气象服务工作的相关技术经验。     

TYPICAL WEATHER CHARACTERISTICS ASSOCIATED WITH AIR POLLUTION IN HONG KONG AREA

With the hourly data of Air Pollution Index (API) by Hong Kong Environmental Protection Department (HKEPD) during the 6 years of 2000 - 2005 and NCEP / NCAR reanalysis data of 2.5° × 2.5° wind and pressure fields, the characteristics of API in Hong Kong area and the impacts of typical weather characteristics on the air pollution in Hong Kong have been studied. The results are shown as follows. (1) The API exhibits obvious seasonal variability as the number of air pollution days increases by the year. For most of the local monitoring stations, it is the most from January to March, a little less from July to September and the least from April to June. (2) There are four typical types of weather situations that are responsible for the air pollution in Hong Kong: tropical cyclones, continental cold highs, transformed highs that have moved out to sea and low pressure troughs.     

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.     

Projections of uncertainties in climate change scenarios into expected winter wheat yields

Summary The crop model CERES-Wheat in combination with the stochastic weather generator were used to quantify the effect of uncertainties in selected climate change scenarios on the yields of winter wheat, which is the most important European cereal crop. Seven experimental sites with the high quality experimental data were selected in order to evaluate the crop model and to carry out the climate change impact analysis. The analysis was based on the multi-year crop model simulations run with the daily weather series prepared by the stochastic weather generator. Seven global circulation models (GCMs) were used to derive the climate change scenarios. In addition, seven GCM-based scenarios were averaged in order to derive the average scenario (AVG). The scenarios were constructed for three time periods (2025, 2050 and 2100) and two SRES emission scenarios (A2 and B1). The simulated results showed that: (1) Wheat yields tend to increase (40 out of 42 applied scenarios) in most locations in the range of 7.5–25.3% in all three time periods. In case of the CCSR scenario that predicts the most severe increase of air temperature, the yields would be reduced by 9.6% in 2050 and by 25.8% in 2100 if the A2 emission scenario would become reality. Differences between individual scenarios are large and statistically significant. Particularly for the time periods 2050 and 2100 there are doubts about the trend of the yield shifts. (2) The site effect was caused by the site-specific soil and climatic conditions. Importance of the site influence increases with increasing severity of imposed climatic changes and culminates for the emission scenario A2 and the time period 2100. The sustained tendency benefiting two warmest sites has been found as well as more positive response to the changed climatic conditions of the sites with deeper soil profiles. (3) Temperature variability proved to be an important factor and influenced both mean and standard deviation of the yields. Change of temperature variability by more than 25% leads to statistically significant changes in yield distribution. The effect of temperature variability decreases with increased values of mean temperature. (4) The study proved that the application of the AVG scenarios – despite possible objections of physical inconsistency – might be justifiable and convenient in some cases. It might bring results comparable to those derived from averaging outputs based on number of scenarios and provide more robust estimate than the application of only one selected GCM scenario.     

中尺度地形对强对流天气的影响的数值诊断

许多重大天气灾害发生在特定地形条件下,例如山区的喇叭口地形容易有暴雨发生。山脉的阻碍以及造成的空气被迫抬升、绕流、穿谷流,地形的不同加热和摩擦效应产生的中尺度环流对局地强对流天气有明显作用。 大别山区和皖南山系对江淮地区的暴雨和强对流天气的影响也早已为该地区预报员们所重视,通过雷达、天气图和云图资料分析认识到山区热力对流、长江穿谷流和大别山背风坡低压是江淮地区剧烈天气发生的重要因素。 为了比较深入地了解中尺度地形对强对流天气的影响,除了从实测资料进行细致分析外,有必要从     

1971-2010 年重庆蔬菜气候生产潜力特征分析

利用重庆地区1971-2010年34个地面气象站日值数据集,结合周广胜气候生产潜力模型,采用线性回归、Mann-Kendal突变、经验正交函数（EOF）等方法分析重庆地区蔬菜气候生产潜力。结果表明：重庆地区年平均蔬菜生产力呈下降趋势,并存在明显的突变,主要是由于降水量的减少;全市蔬菜气候生产潜力空间分布呈现渝东南、渝东北偏西地区偏高的特点, 局地差异也比较明显。重庆气候处于暖湿型气候时对蔬菜的生长最为有利。     

北京风沙天气的气溶胶特征

利用常规气象观测资料、卫星云图以及1988、1990、1992、1993、1995、2000年等年北京风沙天气期间所采集的气溶胶样品的分析结果,研究了北京的风沙天气分布特征,风沙期间大气污染状况,产生风沙天气的主要原因及沙尘的来源等.初步得出北京的风沙天气主要出现在春季,是造成春季大气污染的重要原因之一;北京春季风沙天气是由沙尘暴、浮尘和扬沙造成,但以扬尘引起的频率为最高,占71.4%;风沙期间大气气溶胶与无风沙时气溶胶的物理化学特征有明显的差异;大气气溶胶的物理化学特征显示出,风沙期间的大气气溶胶主要来源于自然源,以局地尘源为主,人为排放的气溶胶作用相对减弱.     

天气数值预报中过去资料的使用问题

本文指出在天气数值预报中要解的天气方程组与我们能有的求解条件是不相配称的.因此需要研究如何把方程组化成最合适的形式而最充分地利用可能有的定解条件(特別是最可靠最完全的气象量测的分布)以使预报效果最好.在某些情形下,天气数值预报可以提成“演变”问题,从而可能使用过去的资料.作为某一气象量的初值问题,天气数值预报也可能使用一部分过去资料.而在以前的天气数值预报是并不使用过去天气资料的.本文最后讨论了这样提法的意义.     

一个制作长期天气预报的前后相关图解方法

本文提出一个利用相关散布图制作长期天气预报的方法,试验结果指出准确率甚高.     

面向Internet的农业气象产量动态预报

针对信息时代Internet网上用户对产量预报动态查询的需求 ,探讨了面向Inter net的农业气象产量预报的解决方案。试验结果表明 ,由于作物生长发育和产量形成是一个光、温、水、土条件长期、综合作用 ,生物量长期累积的过程 ,因此利用积分回归方法 ,考虑全生育期光、温、水气象因子的综合影响 ,根据已出现的天气实况 ,在假定后期天气条件正常的情况下 ,有可能预测出未来产量的趋势。随着天气实况的逐一出现 ,后期的预报结果可望逐步接近实际值。统计检验和试报结果误差均在允许范围内。     

新植白莲套种晚稻栽培技术与气象条件分析

根据新植白莲套种晚稻栽培技术试验示范观测,分析探讨了白莲套种晚稻栽培对气象条件的要求和可能存在的春季低温、夏季高温、寒露风等农业气象灾害影响,并提出科学的农业气象灾害防御对策.分析得出试验示范区气候条件能满足新植白莲套种晚稻种植的要求,为当地大面积推广新植白莲套种晚稻生产积累了经验和科学依据.