肖艳姣,刘黎平,杨洪平. 2008. 基于天气雷达网三维拼图的混合反射率因子生成技术[J]. 气象学报, 66(3):470-473, doi:10.11676/qxxb2008.043
基于天气雷达网三维拼图的混合反射率因子生成技术
Technique for generating hybrid reflectivity field based on 3-D mosaicked reflectivityof weather radar network.
投稿时间:2007-01-31  
DOI:10.11676/qxxb2008.043
中文关键词:  波束阻挡,混合扫描仰角,等射束高度拼图,三维拼图,混合反射率因子
英文关键词:Beam occultation, Hybrid elevation angle, Mosaicked iso beam height map, 3-D mosaic, Hybrid reflectivity
基金项目:国家重大基础研究项目(2004CB418305)和武汉区域气象中心科技发展基金课题(QY-Z-200706)
作者单位
肖艳姣 中国气象局武汉暴雨研究所武汉 430074
中国气象科学研究院灾害天气国家重点实验室北京 100081 
刘黎平 中国气象科学研究院灾害天气国家重点实验室北京 100081 
杨洪平 中国气象局武汉暴雨研究所武汉 430074 
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中文摘要:
      首先基于1:25万的DEM(digital elevation model)数据、雷达站点信息、雷达波束高斯分布模式和标准大气情况下的波束传播路径计算了雷达的波束阻挡率,并把它与雷达 实测的反射率因子分布情况进行比较,发现两者具有很好的定性一致性和很强的定量相关性 ;其次根据设置的波束阻挡率阈值和波束下限(波束底部越过地形的高度)阈值得到不受地 形阻挡的最小扫描仰角在同一平面上的投影,即混合扫描仰角,这样计算出来的混合扫描仰角与雷达扫描方式无关,可用于不同扫描方式下的混合扫描反射率因子(没有波束阻挡的最低扫描仰角的反射率因子在同一平面上的投影)的获取;然后根据混合扫描仰角,利用标准大气情况下的雷达测高公式计算等射束高度,把来自雷达网中各雷达的等射束高度进行拼接得到等射束高度拼图,其中在各雷达重叠覆盖区,取最小的等射束高度;最后利用新一代天气雷达网三维拼图反射率因子数据以及等射束高度拼图数据得到天气雷达网的混合反射率因子,以便用于大范围降水估算算法中的降水率的计算。
英文摘要:
      Understanding the extent to which a radar view is blocked by surrounding obstacles plays an important role in the proper interpretation of reflectivity data, especially in the lowest antenna elevation angles, which provide the most useful information for rainfall rate estimation at ground level. A terrain based hybrid scan of lowest radar beams that are not significantly blocked by terrain is one of the most important approaches to improve the precision of rainfall estimates. The purpose is to generate hybrid reflectivity field used for precipitation rate calculation from 3-D mosaicked reflectivity field of radar network with high spatial and temporal resolutions. First of all, beam occultation, which is the percent of the radar beam power lost due to beam blockage, is calculated using an algorithm that uses high resolution DEM (digital elevation model) data, radar beam pattern or power density function (Gaussian beam approximation), and radar beam propagation path (assuming radar beams propagate under standard atmospheric refraction conditions). The algorithm begins by remapping Cartesian DEM data to a high resolution polar grid centered on a specified radar location. This high-resolution grid is user defined and used to perform beam occultation calculation. Here, a high grid resolution of 0.1°×250 m is the default setting. Comparison of model calculated beam occultation with radar observations indicates very good qualitative agreement and strongly quantitative correlation. Secondly, hybrid elevation angles are generated using thresholds for beam bottom clearance (default 150 m) and occultation (default 60%), which define the criteria for a hybrid elevation angle, which is the lowest angle satisfying both requirements. Beam bottom clearance is the height that a radar beam's bottom passes above the terrain. To compute the hybrid elevation angle, the elevation angle of a beam that clears the terrain by the beam bottom clearance threshold is calculated. The beam occultation is calculated using the elevation angle as a first guess. If the occultation is less than the threshold (60%) then the hybrid elevation has been found. Otherwise, the elevation angle is increased and the beam occultation calculation is performed again. The elevation angle will be adjusted unceasingly in an iterative process (at interval of 0.1°) until finding the hybrid elevation angle. The algorithm is independent of radar types and of radar scan strategies. According to hybrid elevation angle, operational hybrid elevation angle and hybrid scan reflectivity are obtained from volume scan radar data. Then, the standard refractive index beam heights (4/3 earth) are calculated for hybrid elevation angles for every radar in radar network, which are combined to produce a mosaicked beam height map. For the grid cell with multiple radar coverage, the minimum beam height is to be taken. Finally, the hybrid reflectivity field based on the mosaicked beam height field and 3-D mosaicked reflectivity field of radar network is obtained, which is used for rainfall rate estimation at ground level.
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