Extreme precipitation events identified using detrended fluctuation analysis (DFA) in Anhui,China

Extreme weather events include unusual, severe or unseasonal weather, and weather at the extremes of the historical distribution. They have become more frequent and intense under global warming, especially in mid-latitude areas. They bring about great agricultural and economic losses. It is important to define the threshold of extreme weather event because it is the starting point of extreme weather event research, though it has been of seldom concern. Taking extreme precipitation events in Anhui, China as an example, the detrended fluctuation analysis (DFA) method is introduced to define the threshold of extreme weather events. Based on it, the spatial and temporal distributions of extreme precipitation events are analyzed. Compared to the traditional percentile method, DFA is based on the long-term correlation of time series. Thresholds calculated by DFA are much higher than the 99th percentile and the values are higher in the south and lower in the north. This spatial pattern is similar to the annual precipitation spatial pattern. There is an obvious increasing trend in the number of days with extreme precipitation, especially after the 1980s. This observation supports the point that more extreme events happen under global warming.     

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.     

Atmospheric Water Vapor Pressure over Land Surfaces: A Generic Algorithm with Data Input Limited to Air Temperature, Precipitation and Geographic Location

Summary A lack of information for surface water vapor pressure (WVP) represents a major impediment to model-assisted ecosystem analysis for understanding plant-environment interactions or for projecting biospheric responses to global climate change. This paper reports on a generic algorithm that captures global variation in monthly WVP. The algorithm solves WVP in terms of reduction from saturation WVP as a negative exponential function of potential evapotranspiration; the reduction rate per unit potential evapotranspiration in turn varies with monthly precipitation and a series of variables that distinguish local climate regimes. Data input to the algorithm is limited to monthly air temperature and precipitation, plus latitude, longitude and elevation. The algorithm is specified through regression fitting to monthly climate normal data from 852 stations around the world. It accounts for 96% of the variance in the WVP data, with a root mean square error of 0.17 kPa, or 12% of the data mean. The algorithm closely reproduces five-year sequential monthly WVP data for each of five selected United States locations representitative of diverse climate regimes: the average error generally falls within ±12% of the data mean, and the absolute error within ±0.2 kPa. Its projections also compare favorably against the WVP output from the General Circulation Models for temperature and precipitation conditions under the scenario of a doubled atmospheric carbon-dioxide concentration: the two fall within ±10% of each other for 75% of a total 264 data cases, or within ±20% for 94% of the cases. These statistics suggest that the spatially-based algorithm is useful for projecting temporal variation in WVP, and for extrapolative applications beyond the fluctuation range of present climate. Received March 4, 1999     

基于RAMS/CFORS Ⅱ模式一次低空核试验放射性烟云扩散的数值模拟

采用RAMS／CFORS Ⅱ模式模拟了一次低空核试验烟云的传输和沉降过程。CFORS Ⅱ模式是在RAMS／CFORS模式的基础上开发的,可用于对核试验放射性烟云长距离输送和沉降过程的模拟研究。模拟表明：对流层中低层的低压槽系统对本次低空核试验烟云的水平传输和垂直扩散起着重要的影响作用;烟云的长距离传输速度呈现出随高度递减而减小的趋势,在6000m以上,烟云在爆后48h即东移入海,6000m以下,烟云在中国大陆的扩散和沉降维持了5d以上;爆后2天内以大粒子沉降为主,其后以小粒子沉降为主,小粒子的放射性远小于大粒子,在爆后第4天,放射性沉降就减小了3个量级,而小粒子的沉降范围是大粒子的5倍以上。通过模拟和观测对比表明,模拟结果基本符合实际烟云的传输和沉降态势。     

对流和层状云系电活动,对流及降水特性的相关分析

通过对６次不同云系电特性、回波、对流及降水特性的综合分析，探讨了它们之间的相关性。结果表明：除不稳定能量外，－１０℃层和０℃层高度以及他们之间的高度差、０℃层与云顶的高度差也是表征雷暴动力和电特性的重要参量；雷暴云起电过程对冰相作用有较强的依赖性；雷暴中的电活动与对流活动成正相关，闪电多发生在３０ｄＢｚ强回波高度大于－１０℃层高度时段内，强烈的电活动与强降雨有很好的对应关系，而与一般性降雨对应关系较差；在雷暴消散期，闪电可能会影响雷暴的特性     

一种等压面上流场的可视化方法

结合等压面上高度场及其气象要素矢量场数据的空间分布特征，设计了一种能客观反映大气在等压面上的运行规律的可视化方法－表面场线映射，它在气象上有较好的实用价值。     

DLP大屏幕投影墙显示系统在山西气象业务工作中的应用

DLP（Digital Light Processor）大屏幕投影墙显示系统是集多种信息接收处理显示、多功能平台综合鼹示与控制于一体的全数字多用途高科技显示系统,在气象部门天气预报会商和会议系统中已普遍使用？奉文拟对DLP的技术特点和优势进行分析,结合山西省气象台业务现状和发展需求,对DLP大屏幕显示系统在业务一体化会商室业务平台中的设计方案及应用情况进行探讨,对应用DLP大屏幕显示系统后的远景功用和效益进行分析,旨在为气象DLP大屏幕项目建设提供前期研究支持。     

星载GPS地球静止轨道卫星自主定轨的新算法

针对地球静止轨道卫星的特点,提出了一种自主定轨的新算法--积分滤波算法,即利用Kalman滤波进行动力学模型数值积分与GPS定轨的有效融合.讨论了该算法的基本过程及其中Kalman滤波的数学模型和重要参数.最后给出了仿真实验过程和结果,证明了该算法的可行性.     

中心城区地表温度空间分布及地物降温效应——以南京市为例

基于TM图像,采用灰度图像分割算法,自动提取南京市中心城区的不透水面、植被及水体;并用单窗算法反演了地表温度;依据离市中心的距离将中心城区分为45级缓冲区,依次统计分析每一级缓冲区内的平均温度、不透水面温度、植被温度、水体温度及各类地物的面积比例等;建立了地表温度与不透水面比例、植被比例、水体比例之间的关系模型.研究结果表明:随离市中心距离的增大,地表温度降低;植被、水体具有降温效应,水体的降温效应是植被的2.43倍;地表温度与不透水面比例、植被比例、水体比例的综合关系模型模拟效果较好.     

小白洋淀水-沉积物系统多环芳烃的分布、来源与生态风险

以端村小白洋淀为研究对象,利用GC-MS测定了6个样点水、悬浮物和沉积物中15种优控多环芳烃(PAHs)的含量,分析了其组成与来源特征,探讨了不同多环芳烃单体的生态风险,结果表明:(1)15种优控多环芳烃的总含量(PAH15),水相为40.1-74.0ng/L,算术均值51.0ng/L;悬浮物为2438.0-5927.0ng/g,算术均值4528ng/g;沉积物为466.9-1366.4ng/g,算术均值为755.6ng/g;与国内外有关研究相比,污染较轻,(2)三相中均以2、3环PAHs为主,其比例均高于80%;并且,从水相、悬浮物相到沉积物相,2环PAHs依次降低,3环、4环依次升高,高环检出率和含量也依次升高,(3)沉积物中多环芳烃的来源以生物质燃料(秸秆、薪材)和煤的燃烧为主,以液体化石燃料(汽油、柴油和原油)的燃烧为辅,(4)沉积物中的芴(FLO)、菲(PHE)含量在潜在生态风险效应区间低值(ERL)与中值(ERM)之间,其生态风险几率介于10%-50%之间;其他PAHs单体的含量均低于ERL,其生态风险几率均低于10%.