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在正常情况下, 由于天线仰角和地球曲率原因, 雷达波束位置在远距离处要比近距离处高。当雷达电磁波能量被部分阻挡时, 回波强度观测值低估; 被完全挡住时, 探测不到地物后的目标。该文利用高分辨率地形高程数据计算波束阻挡率, 确定组网拼图有效数据区域以及波束部分阻挡时的回波强度订正方法。根据业务观测模式VCP11及VCP12的14个仰角值, 在标准大气假定下, 对湖南、江西、浙江、福建、广东、广西和海南已建多普勒天气雷达组网的数据有效区域进行计算, 绘制出海拔1500 m, 3000 m和6000 m高度上有效区域图。分析结果表明:CAPPI数据有效范围比等射束高度图更能反映出多普勒天气雷达业务观测范围; 若采用VCP12模式观测, 与采用VCP11或VCP21模式观测相比, 不仅增加低层探测密度, 而且可扩大雷达实际探测距离, 其回波数据更适合于组网拼图。 相似文献
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《高原气象》2015,(6)
准确分析雷达的覆盖能力是应用新一代天气雷观测数据的重要基础,本文提出依据0℃层高度和雷达波束阻挡来分析雷达降水估算有效覆盖范围的方法,并以浙江为例,客观评估了新一代天气雷达针对降水估算的区域覆盖能力。分别评估雷达网当前业务中默认的降水估算混合扫描方法和考虑地形影响的混合扫描方法的覆盖效果,结果表明:相对SA雷达230 km的降水估算半径,本地主汛期内有17%的区域因波束太高而不适宜于降水估算;而在适宜高度范围内的有效覆盖与波束阻挡直接相关;无论哪种方法,因波束阻挡产生的盲区都较小;而业务默认方法由于未处理波束阻挡,导致35%的降水低估风险区,浙江大部分地区都存在低估风险;而考虑波束阻挡后有效覆盖区达82%以上,且对全年绝大部分降水的区域覆盖效果都相当好。鉴于浙江雷达网良好的覆盖能力,提出改进的雷达降水估算混合扫描方法,即在应用波束阻挡的同时,以本地0℃层为波束高度约束,从所有仰角中提取混合扫描数据。对比分析表明,该方法不仅满足区域覆盖的要求,而且估算的降水空间分布与地面观测实况的一致性最好。 相似文献
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区域雷达网同步观测对比分析 总被引：5，自引：0，他引：5
利用长江中游的合肥、宜昌、武汉、常德和长沙雷达周围的1:25万的地形高度数据得到各雷达的混合扫描仰角和等射束高度拼图。选用2004年7月17—19日5部雷达同步观测的雷达体扫资料,分析了各雷达的最低扫描仰角;在尽量排除地物杂波、波束阻挡、距离衰减和波束展宽等因素影响的情况下,对比分析了5部雷达构成的有重叠覆盖区的7个雷达对的反射率因子差异。结果表明:(1)对雷达最低扫描仰角进行分析可以检查雷达的仰角标定,武汉和合肥雷达平均最低观测仰角比VCP21扫描方式规定的要低;(2)用雷达对等距离线上的反射率垂直剖面可以分析雷达对同步观测的回波空间位置和强度差异,常德雷达和其周围雷达同步观测的回波高度明显偏低;(3)用雷达对等距离线上某高度的反射率因子曲线变化的一致程度可以分析雷达的方位标定,这5部雷达没有明显的方位定标偏差;(4)用雷达对等距离线上某高度的平均反射率因子差可以分析雷达对同步观测的系统观测差,宜昌雷达和其周围的雷达相比,观测的回波强度偏强,而武汉和其周围的雷达相比,观测的回波强度偏弱;(5)反射率因子差的时间平均值随着反射率因子的大小变化而变化,当观测的反射率因子越大时雷达对的反射率因子差的时间平均值也越大。 相似文献
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基于高分辨率高程数据统计分析新一代天气雷达组网的地形遮挡影响 总被引：1，自引：0，他引：1
新一代天气雷达由于受到地形限制产生波束遮挡导致波束能量衰减,从而造成雷达探测回波强度偏弱、雷达定量估测降水结果失真,因此对于雷达波束遮挡情况的统计和分析是一项重要的基础研究工作。利用SRTM （Shuttle Radar Topography Mission）数字高程数据对中国目前业务运行的212部新一代天气雷达波束遮挡情况进行模拟计算分析。计算结果包括雷达单站遮蔽角、VCP21模式0.5°、1.5°、2.4°、3.4°、4.3°仰角波束遮挡率、混合扫描及分区混合扫描波束遮挡率、雷达单站探测范围覆盖情况;计算并绘制全国天气雷达组网遮挡率拼图,统计全国天气雷达组网遮挡情况;利用2019年8月广东省11部天气雷达基数据对比验证单站及组网遮挡计算结果。结果表明雷达组网探测面积覆盖率超过70%,整体覆盖效果较好,遮挡计算结果与实际数据对比验证结果高度一致,对雷达数据订正、降水估测等产品具有正贡献。 相似文献
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地基天气雷达低仰角观测时雷达波束就有可能碰到山体或地表,使波束传播路径上该观测点及其后的观测点数据失真,波束受地形阻挡计算时要考虑到入射阻挡和入射前阻挡两种情况。在探讨雷达波束传播路径精确定位方法的基础上,基于微积分原理,从数学上推导了地形对雷达波束阻挡率及其计算公式。根据武汉周围3秒分辨率的地理高程栅格数据计算了武汉天气雷达在球面分层大气近似下的波束阻挡率。 相似文献
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地形的起伏使雷达波束受到严重的遮挡,使回波数据质量受到很大干扰。本文使用SRTM任务的DEM数据和谷歌公司的DEM数据分别计算了位于北京南郊的S波段雷达低仰角的波束遮挡率,建立了部分遮挡区域的回波反射率订正关系,并在2018年5月19日北京一次大范围层状云降水过程中,对波束遮挡订正前后的雷达定量估测雨量与地面3个雨量计观测结果进行了定性与定量化对比分析。结果表明:①波束遮挡订正有助于改善反射率因子的空间连续性。波束遮挡订正后的仰角0.5°的反射率与1.5°的反射率之间的差值整体呈现缩小特征,符合层状云降水垂直廓线特点。②09:00—11:00,相比波束遮挡订正前的雷达定量估测雨量(QPE),波束订正后的QPE准确性得到改善,使用分级标准误差与归一化平均偏差评价波束遮挡订正前后QPE与雨量计实测值之间的误差,波束订正后的反射率估测雨量与雨量计实测雨量一致性更好。 相似文献
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新一代天气雷达网资料的三维格点化及拼图方法研究 总被引：31，自引：6，他引：31
文中研究了几种把球坐标系下的雷达网反射率体扫资料插值到统一的笛卡尔坐标系下的经纬度网格上以及用多个雷达的反射率网格资料进行三维拼图的方法,并对多个雷达同步观测的反射率因子的空间一致性、系统误差以及雷达等距离线上回波的水平和垂直结构进行了分析。结果发现:在雷达资料格点化过程中,径向和方位上的最近邻居法和垂直方向的线性内插法的结合(NVI方法)是一种有效的雷达资料分析方法,它既能得到空间比较连续的反射率分析场,同时也较好地保留了体扫资料中原有的反射率结构特征;广州雷达和梅州雷达同步观测的空间一致性比较好;在多个雷达资料合成拼图的过程中,距离指数权重平均法能提供空间连续的三维反射率拼图数据,拼图也减轻了由雷达波束几何学引起的各种问题。 相似文献
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J. Rakovec 《Theoretical and Applied Climatology》1997,57(1-2):35-47
Summary Radar reflectivity from hydrometeors is used for the estimation of the precipitation rate at ground level. If the vertical reflectivity profile is taken into account, the estimate can be improved considerably. In the first part of the article some theoretical explanations are given for the two most pronounced characteristic of the vertical radar reflectivity profile from clouds. In general, the observed values decrease with height in the upper part of the radar echo due to the growth of precipitation particles by collision and coalescence. The effect of the bright band, especially in more stratiform types of precipitation, adds a significant strong peak to the profile, at the approximate height of the 0 °C isotherm. These explanations, although being simplified, also provide a quantitative explanation of the two characteristics mentioned previously. Averaged seasonal characteristics of vertical profiles in Slovenia are used as the climatological basis for the construction of an idealised profile for correcting the precipitation estimate. For individual cases, and also after averaging, a maximum in the profiles can clearly be detected. This maximum is much sharper if the profiles are normalised. When looking at time changes, it is shown that most of the changes in radar reflectivity, on average, occur during a roughly 6-hour time-lag between the two measurements. With greater time-lags, the differences are smaller on average. This is caused by the local natural evolution of the precipitation field and indicates that a 6-hour to 12-hour accumulating and averaging of data could diminish much of the error due to the time variation in radar estimated precipitation.With 5 Figures 相似文献
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降水粒子对云的生消和演化有非常重要的影响。毫米波雷达适合观测非降水云和弱降水云。利用毫米波雷达数据判断云内降水粒子生成与否有很高的实用价值。本文利用飞机观测的云滴谱数据计算云的反射率因子。将其与雷达探测值进行比对,发现两者有较好的一致性。因此利用滴谱计算的降水粒子反射率因子阈值可以作为雷达判断降水粒子生成的指标。通过分析滴谱计算云滴和降水粒子的反射率因子的概率密度函数可以得到用于区分云滴和降水粒子的反射率因子阈值。通常,云滴的反射率因子不超过-5dBz,降水粒子的反射率因子高于-20dBz,-15~-12dBz可作为判断降水粒子出现的阈值。 相似文献
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R. Bechini E. Gorgucci G. Scarchilli S. Dietrich 《Meteorology and Atmospheric Physics》2002,79(3-4):275-284
Summary The error structure of radar measurements should be accurately known in order to provide reliable estimates for a number
of quantitative meteorological applications, from rainfall rate estimation to cloud microphysics. The aim of this paper is
to give a detailed characterization of Z
H
and Z
DR
measurements obtained by the weather radar of Fossalon di Grado (Gorizia, Italy). Vertical-looking observations are used
to determine the system bias on differential reflectivity and to estimate the measurement error on both Z
H
and Z
DR
in the rain medium. It is estimated that no bias is affecting Z
DR
and the accuracy of Z
H
and Z
DR
is 0.8 and 0.1 dB, respectively. A similar evaluation is done in the rain medium at larger ranges with the antenna pointing
at low elevation angles. The long time stability of the absolute reflectivity calibration is also established by radar-rain
gage inter-comparison over almost 200 hours of precipitation data collected during nearly two years.
Received June 21, 2001 Revised November 13, 2001 相似文献
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35GHz云雷达反射率因子数据的质量控制 总被引：2，自引：2，他引：0
大气非云粒子(气溶胶、昆虫、悬浮物)以及雷达元器件固有噪声,是影响云雷达定量探测大气云层宏观以及微观产品的重要因素。为了剔除云雷达基数据中的散点噪声对数据质量的影响,本文利用新一代多普勒偏振8.6 mm云雷达资料,基于模糊逻辑识别地物的方法分析雷达散点噪声、气溶胶以及大气云粒子的反射率因子回波的统计特征,通过统计的特征值对反射率因子进行分类,保留正常回波数据。结果表明:该方法能较好区分云粒子回波和非云粒子回波,提高云雷达反射率因子的数据质量。 相似文献
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Future space-borne cloud profiling radars (CPR) will employ longer pulse lengths than ground-based systems. As a consequence, reflectivity profiles observed from space will be more strongly convoluted with the radar pulse shape. Here we describe a constrained linear inverse technique that reduces the effects of this convolution. We apply the technique to simulated data, based on actual observations from the ground, and show that significant improvements in the reflectivity profile can be obtained. Average Z errors (dBz) are halved, while cloud boundaries are substantially better retrieved. The results in this paper are relevant to space-borne missions like CloudSat and EarthCARE. 相似文献
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A systematic procedure for calibrating system gain bias (so-called “calibration error”) of radar reflectivity measurements from the Korea Meteorological Administration (KMA) operational radar network is presented. First, the RJNI radar located at Jindo Island is calibrated by comparing with radar reflectivities simulated theoretically by a scattering algorithm using drop spectra collected by a disdrometer from June 19 to 29, 2009. Once the RJNI radar is calibrated, the reflectivity measurements from nearby radars are compared with the RJNI radar reflectivities to determine existing gain biases of nearby radars. This radar-radar calibration procedure was repeated with the other radars within the network. For isolating a system gain bias, echoes affected by partial beam blockage due to ground clutter and by attenuation due to precipitation were removed. The system gain biases of the RJNI and RPSN radars were ?3 and ?4.2 dB, respectively, during the experimental period. The RBRI and RDNH radars revealed relatively large biases, above ?8 dB. The other radars (RKSN, RGSN, RSSP, RKWK, RGDK, RIIA, and RMYN) revealed biases from ?6 to ?7 dB. Thus, the reflectivity measurements from all of the KMA radars were severely biased. New R-Z relations of R = 3.350 × 10?2Z0.624 (Z = 231.1R 1.6) for stratiform and R=1.546 × 10?2 Z 0.714 (Z = 342.4R 1.4) for convective precipitations were derived using disdrometer data. Using these R-Z relations, the radar-derived total rainfall amounts from the reflectivity measurements without calibration produced significant underestimations, compared to gauge measurements at about 80 sites, with a normalized bias of about ?56%. On the other hand, after calibrating the above system biases, the radar-derived rainfall amounts corresponded well with the gauge measurements, with a normalized bias of about ?3%. In conclusions, the radar reflectivity measurements from the KMA radar network are severely biased and the procedure presented in this study can be used to resolve the system gain biases. 相似文献