基于WebGIS的精细化格点预报可视化设计与实现

为了满足天气预报服务和人们日益增长的需求,精细化格点预报成为天气预报数字化的发展趋势。采用B/S结构,借助WebGIS的可视化技术,基于ArcGIS API for JavaScript轻量级方法构建了精细化格点预报可视化系统。本文分析了气象格点数据的特征及格点数据的可视化表达方式,侧重于多种气象要素格点数据的可视化显示、格点交互编辑订正和基于格点位置的中期天气预报查询,为格点预报可视化提供更好的服务。     

基于GIS的格点精细化预报插值方法的研究

在格点间隔为9 km的气象预报基础上,本文运用双线性插值方法进行局部格点加密与数据的平滑,实现局部地区的3 km格点预报。通过使用距离倒数插值、克里金插值、自然邻域插值和样条函数插值,将局部3 km格点间隔数据与其余9 km格点间隔数据整体进行插值,并使用交叉验证法比较整体插值结果,发现克里金插值方法插值精度最好,最终选择使用克里金插值方法进行精细化格点插值预报,作为气象预报人员进行精细化天气预报的参考依据。     

道路交通气象服务系统的设计与应用

通过建立更快速的道路交通气象预警发布系统,开展基于位置的道路交通气象服务,将灾害天气情况直接发送给行驶中货车运输的司机,从而尽可能减少因恶劣天气带来的交通事故,保障人民群众生命财产安全.利用中国区域5 km分辨率智能网格天气实况数据和12379全国灾害预警发布平台实时获取全国3240个县市灾害预警信息,通过建立电子围栏...     

基于ANUSPLIN的小兴安岭地区降水格点数据空间插值

在全球变化研究中,高分辨率、网格化的气候数据作为环境因子是地学模型和气模型等相关研究的重要参数.本文以黑龙江省小兴安岭地区为研究对象,采用ANUSPLIN空间插值方法,利用该区域69个地面降水月值0.5°×0.5°格点和1 km空间分辨率DEM,对逐月降水进行了空间插值,使用广义交叉验证方法和多个评估指标进行了误差分析和精度评价,进一步分析了2020年小兴安岭地区降水月值的时空特征.结果表明:TVTPS4模型具有最优插值精度和区域适用性;降水具有阶段性和季节性,以及地域分布差异特征.本研究成果可为复杂地形地貌的气象要素精细化研究,以及区域可持续发展科学决策提供参考.     

基于MFC单文档和OpenGL的激光扫描数据可视化与编辑的研究

基于实测的点云数据,根据目前建筑点云显示方面的需求,需要通过平台展示点云成果.本文应用MFC单文档和OpenGL可实现点云数据的显示、缩放、压缩等效果,数据采用嘉荫县恐龙模型点云数据,经实验表明,采用MFC单文档和OpenGL在点云显示编辑方面具有较强大的功能,可作为成果展示的途径.     

地基GPS大气水汽监测及在气象业务应用中的关键技术

通过对地基GPS大气水汽监测及在气象业务应用中的关键技术研究,建立地基GPS资料处理、传输和业务应用平台,并对GPS水汽产品进行了检验对比,揭示地基GPS水汽资料在降水、暴雨等灾害性天气预报中的预报预警指标。     

基于IGS超级跟踪站的近实时GPS气象研究及应用

目前国内许多城市开始将CORS综合应用网服务于气象部门,为给地基GPS气象研究人员提供一个真实的研究环境,本文基于IGS超级跟踪站网络搭建了一个近实时GPS气象系统,并结合实测数据验证了该系统的有效性。基于该平台可以系统地研究GPS遥感水汽、层析水汽三维分布、数值天气预报同化GPS水汽以及利用电离层分布进行空间天气预报等理论。     

基于WebGIS的气象数据实时可视化研究

以ArcGIS平台为基础实现降雨数据的实时可视化,研究Micaps4与NetCDF转为通用GIS数据的方法。Micaps4采用先转ASCⅡ再转为通用GIS栅格数据,NetCDF直接采用ArcGIS工具箱转为通用GIS栅格数据。采用替换数据源的方式实时更新符合OGC标准的气象信息服务,实现降雨数据的实时共享发布。最终实现浙江省1 km格网Micaps4格式1 h、3 h、6 h降雨预报数据,5 km格网NetCDF格式1 h、24 h降雨预报数据的实时可视化,数据完全自动化更新,处理转换速度快、渲染效率高,且易于数据的共享和标准的建设,对于建设各级气象网络应用系统有十分重要的意义。     

机载LiDAR在河南省重点水库库区高精度DEM建立中的应用

本文以河南省7个重点水库为研究对象,以免像控方式获取库区机载LiDAR点云数据与正射影像数据,共飞行47个架次,获取数据总面积达950 km²,制作库区保护范围线2442 km、管理范围线1886 km;从设备选择、航飞参数设置、设备检校、点云数据滤波、点云精修、精度检查等几个关键环节进行论述,验证了该方法的可行性。研究结果表明,该方法在节省人力、物力、财力的同时,能获取库区高精度DEM成果,为库区管理范围与保护范围界限的划定及库区精细化管理提供了一种数据获取方法。     

海量点云通用图形处理器缓存机制与并行编辑方法

针对现有海量点云数据组织常采用树索引结构，不支持被通用图形处理器(GPGPU)并行计算，无法实现处理结果与可视化的实时共享，难以满足实时点云编辑应用等问题，该文提出了海量点云GPGPU缓存组织与并行编辑方法，设计了一种基于GPU顶点缓存的海量点云数据组织方法，基于计算着色器技术实现了可视化数据与点云属性的直接共享与并行处理，满足实时点云选择、删除、查询、属性修改等编辑应用，同时采用操作栈的数据结构支持编辑操作的高效回退。实验结果表明，对于亿级大规模点云，该文方法相比传统基于空间索引结构的方法，在点云编辑效率上具有较明显的优势。     

A Case Study on Forewarning of Yellow Rust Affected Areas on Wheat Crop Using Satellite Data

Objective of this study was to identify stripe rust affected areas of wheat crop as well as evaluation of remote sensing (RS) derived indices. Moderately low temperature and high humidity favour the growth of yellow rust. Most affected areas of Punjab are the foothill districts such as Gurdaspur, Hoshiarpur and Ropar. Occurrence of yellow rust is possible when maximum temperature for day is below 15 °C and Temperature difference of day’s maximum and minimum temperature is less than 5 °C during the early growth of wheat. Forecast of the infestation was done using 3 days forecast of weather data obtained from Weather Research and Forecasting (WRF) model at 5 km resolution. Weather forecast used was obtained from Meteorological and Oceanographic Satellite Data Archival System (MOSDAC) site and post infestation, identification of specific locations were done using multi-date IRS AWiFS data. It is an attempt for early detection through 3 days advance forewarning of weather which will be handy tool for planners to expedite relief measures in case of epidemic with a more focused zones of infestation as well as for crop insurers to know the location and extent of damage affected areas.     

Study of cloud liquid water path and total precipitable water from irs-p4/msmr and numerical weather prediction model output

A global weather analysis-forecast system is used to produce six hourly analysis of meteorological fields at roughly 150 km × 150 km resolution at the National Center for Medium Range Weather Forecast (NCMRWF). In this paper, we have studied the Total Precipitable Water Content (TPWC) and Cloud Liquid Water Path (CLWP) derived from the Indian Remote Sensing (IRS-P4) Satellite over the Indian Ocean region in relation to operational numerical weather prediction (NWP) model analysis and short-range forecasts. An objective analysis was carried out by introducing the observations of CLWP, TPWC and their values (six hour forecasts) from the T80 model as the first guess, for a 20 days period of August 1999 using the standard Cressman’s technique. The reanalysis could capture the signature of TPWC and CLWP data from IRS-P4 satellite. In general the observed values of TPWC and CLWP from IRS-P4 have a positive bias compared to NCMRWF analysis over the region where the satellite passed. The CLWP values have been compared with Special Sensor Microwave/Imager (SSM/I) products from the Defense Meteorological Satellite Program (DMSP) satellites. Results indicate that the model derived CLWP values were within acceptable limits, whereas the observations from the Multi-channel Scanning Microwave Radiometer (MSMR) showed slightly larger values.     

基于超快速星历反演大气可降水量的精度分析

水汽是预报某些灾害性天气的重要依据,因此及时获得高分辨率的水汽产品对精准预报天气具有至关重要的意义．针对最终精密星历更新速度较慢、时延较长,无法满足实时反演大气可降水量的要求,提出一种利用超快速星历代替最终精密星历反演大气可降水量的方法:基于地基GNSS反演大气可降水量的原理,利用GAMIT软件,根据国际GNSS服务(IGS)网站提供的不同精度的星历产品获得大气可降水量,并与气象探空站所获得的大气可降水量对比分析．研究结果表明,利用超快速星历所获得的大气可将水量与最终精密星历一致,二者平均差值优于0.1 mm,且与探空站测得的大气可降水量值非常一致,其精度可以满足天气预报的需求．      

The Effect of the MAPS Weather Model on GPS-Determined Ellipsoidal Heights

We investigated a current numerical weather model, known as MAPS (Mesoscale Analysis and Prediction System), to determine if it could precisely define the behavior of GPS signals in the tropospere, ultimately leading to improved GPS-determined ellipsoidal heights. MAPS is the research version of the Rapid Update Cycle (RUC2) generated by NOAA's Forecast System Laboratory. MAPS is generated on an hourly basis and provides coverage in the contiguous United States at a 40-km grid spacing. We processed numerous subsets of GPS data collected over a months-long period on 23 static baselines ranging in length from 62 to 304 km. The GPS data were processed in 1/2-hr, 1-hr, 2-hr, and 4-hr session lengths. The primary effort was to compare the precision of heights obtained using a commonly adopted seasonal weather model with the precision of heights obtained using the MAPS weather model. Our analysis shows that the current version of MAPS can lead to improvement in GPS height precision when session lengths are shorter than two hours. For sessions longer than two hours, comparably precise heights may be obtained using a less accurate seasonal model by introducing appropriate nuisance parameters into the height estimation process. ? 2001 John Wiley & Sons, Inc.     

气象卫星发展回顾与展望

回顾了国际气象卫星和中国风云气象卫星的发展,综述了气象卫星在图像解译、定量产品应用和数据同化方面的成就以及辐射校正技术的进步。围绕大气科学,特别是数值天气预报对天基观测的需求,展望了未来气象卫星的技术发展方向。     

Geodetic sensitivity to surface meteorological data: 24-h and 6-h observing sessions

Tests have been performed to assess the utility of surface meteorological measurements for improved geodetic performance. Three types of a priori met data are considered: a default global, seasonal model; local met measurements collected at a subset of the test network; output values from a NOAA Forecast Systems Lab assimilation model. A variety of configurations for handling tropospheric parameters in the geodetic solutions is also considered. We find no geodetic advantage in using the measured met data under any test scenario. Differences among the three types of a priori information are generally insignificant, although biases can be introduced when some troposphere parameters are not adjusted. Even when using only a relatively small network (<100 km) the differences remain minor. When observing sessions are reduced from 24 h to 6 h the increased error due to measurement noise obscures all other effects except for the shortest baselines where some advantage may be achieved by not adjusting troposphere parameters for very close station pairs.     

中国东南沿海地区大气反常结构遥感初探

对流层大气作为电波传播的主要媒介,其大气剖面参数直接影响无线电系统的作用距离和导航、定位精度,因此,研究大气剖面的微波遥感技术,尤其是大气反常结构,对分析评估无线电信息系统在复杂大气环境条件下工作性能和提供电波折射修正精度等具有重要的应用价值。中国东南沿海地区一直是研究的热点区域,本文选取青岛、射阳、厦门、海口4个站的气象探空仪观测数据,统计了这些地区大气波导的平均高度和厚度,对采用地基多通道微波辐射计的天顶和扫角亮温遥感其参数的算法进行了初步探索,提出了改进的组合神经网络算法来判别并遥感大气波导。同时,使用多年的探空数据对该算法进行了仿真验证,并用青岛气象站的实测数据验证了该算法的精度。结果表明该算法可用于遥感大气反常结构,并且与以往的算法相比更加实用、有效,可为雷达、通信、导航等系统设备提供环境信息保障。     

Methods for Mapping and Medium-Range Forecasting of Fire Danger in Forests on the Basis of Weather Conditions

Two Russian researchers outline a method whereby imagery from NOAA-series satellites is used to augment data derived from Russia's network of meteorological stations during extreme fire hazard situations. The focus more specifically is on developing a medium-range forecast of the fire hazard on the basis of repeated imaging and medium-range (10-day, 3-day) weather forecasts, for the purpose of compiling forecast maps of fire danger to support fire detection, prevention, firefighting measures, as well as the timely deployment of personnel and equipment. Translated by Edward Torrey, Alexandria, Virginia, from: Geografiya i prirodnyye resursy, 2002, No. 4, pp. 112-117.     

融机器学习与WRF大气模式的PM2.5预报方法

针对当前我国重污染天气实时的空气质量预报问题,该文提出了一种融合随机森林算法与WRF大气模式的PM2.5浓度实时预报方法。该方法结合了北京市地面空气质量监测数据和WRF气象数据进行分析,将高层大气状态(如逆温层高度等)融入了预报模型中,建立了0~72h的PM2.5浓度实时预报模型。实验证明,该模型能够对0~72h单站点的PM2.5浓度进行较高精度的实时预报,且在24~72h的长时预报结果上较基于地面空气污染物数据与地表气象站数据的预报方法精度有明显提升,即该方法可以更好地模拟大气物理化学状态,从而更为精准地进行长时PM2.5浓度预报。     

基于Google Earth的气象多参数综合显示系统

利用Google Earth平台,将天气过程中的雷电、红外云图、MICAPS高空图以及TMPA降水资料,通过编写KML/KMZ文件,建立了气象多参数综合显示系统。该系统平台的建立,可在三维空间中真实动态地再现天气的发生发展及演变过程。此平台将有利于灾害性天气成灾过程和物理机制的研究。