三维GIS建筑物和道路实体模型与地形模型匹配方法

以建筑物和道路实体模型为例,对其与地形模型的匹配方法进行研究与试验。结果表明,顾及建筑物与道路实体模型特征的地形模型匹配结果更符合实际建模要求,为构建逼真的三维数字环境提供了基础。     

Effects of the low-frequency zonal wind variation on the high frequency atmospheric variability over the tropics

Recently, there is increasing evidence on the interaction of atmospheric high-frequency (HF) variability with climatic low-frequency (LF) variability. In this study, we examine this relationship of HF variability with large scale circulation using idealized experiments with an aqua-planet Atmospheric GCM (with zonally uniform SST), run in different zonal momentum forcing scenarios. The effect of large scale circulation changes to the HF variability is demonstrated here. The HF atmospheric variability is enhanced over the westerly forced region, through easterly vertical shear. Our study also manifests that apart from the vertical wind shear, strong low-level convergence and horizontal zonal wind shear are also important for enhancing the HF variance. This is clearly seen in the eastern part of the forcing, where the HF activity shows relatively maximum increase, in spite of similar vertical shear over the forced regions. The possible implications for multi-scale interaction (e.g. MJO–ENSO interaction) are also discussed.     

Advance and prospectus of seasonal prediction: assessment of the APCC/CliPAS 14-model ensemble retrospective seasonal prediction (1980–2004)

We assessed current status of multi-model ensemble (MME) deterministic and probabilistic seasonal prediction based on 25-year (1980–2004) retrospective forecasts performed by 14 climate model systems (7 one-tier and 7 two-tier systems) that participate in the Climate Prediction and its Application to Society (CliPAS) project sponsored by the Asian-Pacific Economic Cooperation Climate Center (APCC). We also evaluated seven DEMETER models’ MME for the period of 1981–2001 for comparison. Based on the assessment, future direction for improvement of seasonal prediction is discussed. We found that two measures of probabilistic forecast skill, the Brier Skill Score (BSS) and Area under the Relative Operating Characteristic curve (AROC), display similar spatial patterns as those represented by temporal correlation coefficient (TCC) score of deterministic MME forecast. A TCC score of 0.6 corresponds approximately to a BSS of 0.1 and an AROC of 0.7 and beyond these critical threshold values, they are almost linearly correlated. The MME method is demonstrated to be a valuable approach for reducing errors and quantifying forecast uncertainty due to model formulation. The MME prediction skill is substantially better than the averaged skill of all individual models. For instance, the TCC score of CliPAS one-tier MME forecast of Niño 3.4 index at a 6-month lead initiated from 1 May is 0.77, which is significantly higher than the corresponding averaged skill of seven individual coupled models (0.63). The MME made by using 14 coupled models from both DEMETER and CliPAS shows an even higher TCC score of 0.87. Effectiveness of MME depends on the averaged skill of individual models and their mutual independency. For probabilistic forecast the CliPAS MME gains considerable skill from increased forecast reliability as the number of model being used increases; the forecast resolution also increases for 2 m temperature but slightly decreases for precipitation. Equatorial Sea Surface Temperature (SST) anomalies are primary sources of atmospheric climate variability worldwide. The MME 1-month lead hindcast can predict, with high fidelity, the spatial–temporal structures of the first two leading empirical orthogonal modes of the equatorial SST anomalies for both boreal summer (JJA) and winter (DJF), which account for about 80–90% of the total variance. The major bias is a westward shift of SST anomaly between the dateline and 120°E, which may potentially degrade global teleconnection associated with it. The TCC score for SST predictions over the equatorial eastern Indian Ocean reaches about 0.68 with a 6-month lead forecast. However, the TCC score for Indian Ocean Dipole (IOD) index drops below 0.40 at a 3-month lead for both the May and November initial conditions due to the prediction barriers across July, and January, respectively. The MME prediction skills are well correlated with the amplitude of Niño 3.4 SST variation. The forecasts for 2 m air temperature are better in El Niño years than in La Niña years. The precipitation and circulation are predicted better in ENSO-decaying JJA than in ENSO-developing JJA. There is virtually no skill in ENSO-neutral years. Continuing improvement of the one-tier climate model’s slow coupled dynamics in reproducing realistic amplitude, spatial patterns, and temporal evolution of ENSO cycle is a key for long-lead seasonal forecast. Forecast of monsoon precipitation remains a major challenge. The seasonal rainfall predictions over land and during local summer have little skill, especially over tropical Africa. The differences in forecast skills over land areas between the CliPAS and DEMETER MMEs indicate potentials for further improvement of prediction over land. There is an urgent need to assess impacts of land surface initialization on the skill of seasonal and monthly forecast using a multi-model framework.     

基于BP神经网络的地质灾害细网格预报模型

地质灾害成因复杂,其中以气象因素、地质地貌因素引发的地质灾害最为常见.以金华地区为例,通过对金华市地质地貌条件及其对地质灾害点的调查,将全区划分为4个地质灾害隐患风险等级的网格区域.在此基础上利用金华中尺度气象资料,采用BP神经网络模型,建立地质灾害细网格预报模型,对该模型进行模拟和预报试验.结果表明,合理的隐患风险等级分区能使预报模型更符合科学规律,而采用分布较细的中尺度资料作为预报因子能进一步提高预报精度.模型的预报结果达到一定的可信度,为防灾减灾工作提供了科学依据.     

WAP Push在江西气象预警信息发布平台中的应用

阐述了WAP Push技术的体系结构、工作流程和WAP Push技术在气象预警信息发布中的优势;介绍了江西气象预警信息发布平台的整体框架,该平台采用了分布式的3层结构,分别为信息获取层、信息编辑/存储层和信息发布层,具有较强的安全性、稳定性和可维护性;重点介绍了WAP Push信息发布模块的工作流程和主要功能,该模块具有发送图文并茂的WAP Push消息或普通短信息,支持群发信息,返回信息发送状态等功能;最后探讨了WAP Push技术在气象业务中的应用及前景。     

十堰市气候干旱分析及预报指标

利用十堰市7个代表站1953-2006年的降水资料和气温资料,用降水距平百分率（R指标）这一传统的干旱等级划分方法,并考虑到气温引入了P指标对干旱等级进行了划分,揭示了该区域干旱发生的基本特征。结果表明：十堰是我国中部地区干旱频发地区之一,干旱存在自身的周期性和连续发生的规律,地理分布是北部重于南部。造成十堰干旱的主要天气系统是东亚大槽、副热带高压和青藏高压（大陆高压）。这3个系统交替影响并控制该市：春季主要是东亚大槽稳定;夏季副热带高压控制为主、大陆高压控制次之;秋季大陆高压控制为主、副热带高压控制次之。根据不同季节和不同类型的干旱,给出了具体的预报指标。     

近50年黄河中游三花区间降水特征分析

利用黄河中游三花区间(三门峡到花园口)近50 a(1955-2004年)气候资料,分析了三花区间降水量的时空分布特征,结果表明:区间汛期降水量的年代变化趋势与非汛期大多相反;不论区间还是分区,20世纪90年代降水量较常年偏少都十分显著.近期(1986-2004年)年降水量较常年偏少1成左右.其中,汛期降水量偏少1～2成;非汛期区间和伊洛河偏少,沁河和干流为正常或略偏多.     

山西离柳集团化肥厂雷击原因分析及防雷方案

离柳集团化肥厂几乎每年均遭受雷害侵袭造成较大损失。本文对雷击原因（特别是DCS系统雷击原因）进行了系统分析并提出综合防雷方案。该方案2007年实施后取得良好的防雷效果。     

初始场中尺度信息对暴雨预报的影响

由于观测资料分辨率与模式分辨率的不同,利用高分辨率模式对暴雨进行预报时,常规观测资料形成的初始场不能直接分辨出中尺度系统,这种中尺度系统特征的缺少可以认为是初始场的一种信息误差。利用中尺度天气分析的尺度分离方法可以提取这种中尺度信息。通过分析初始场中尺度信息的结构、演变特征及其对暴雨预报影响的机理,发现初始场中尺度信息的结构在主要雨带的对流敏感区具有明确的天气学意义,包含了有利暴雨产生的信息;其能量随时间也是增长的,特别是在积分12小时以后,能量迅速增长然后趋于稳定,超过了初始随机扰动的能量增长。利用减弱和增强初始场中中尺度信息的两种初始场作暴雨预报,其结果反映了初始场中尺度信息对暴雨预报的重要性,特别是对雨团位置和强度的预报,这些信息会直接影响暴雨的精细预报。     

基于SCIATRAN模型的二氧化氮DOAS 反演敏感性试验

气溶胶和地表反照率是影响星载SCIAMACHY仪器观测数据定量遥感NO2大气柱总量的2个主要因子.文中利用高光谱分辨率大气辐射传输模型SCIATRAN,在考虑分子吸收和气溶胶多次散射影响基础上,精确模拟了气溶胶、地表反照率和NO2气体浓度变化对差分处理前后卫星反射光谱的影响,并定义影响因子f,对3个模拟参数进行综合评价.结果表明:(1)通过剔除卫星反射光谱中慢变光谱变化成分,DOAS方法明显降低了气溶胶和地表反照率对卫星反射光谱的影响;(2)差分处理前,3个模拟参数的影响强弱依次为地表反照率、气溶胶和NO2浓度;而差分处理后,3个模拟参数的影响强弱依次为NO2浓度、地表反照率和气溶胶.在影响趋势上,气溶胶和地表反照率很相似,均体现为宽带效应,在440-450 nm内有水汽强吸收和多次散射复杂相互作用导致的较大峰值;NO2浓度变化对差分处理前后的光谱都呈现气体吸收结构的影响特性;(3)由于吸收和散射相互作用等因素的影响,在基于卫星观测的差分光谱中仍然残留有气溶胶和地表反照率的误差,地表反照率约占18.6%,气溶胶约占6.2%.因此,当前SCIAMACHY遥感的NO2产品在中国区域浓度偏高,需要对气溶胶和地表反照率进行二次精细化的订正.