Rainfall Estimation Using Palarimetric Radar
使用参数雷达估算降雨量
基本信息
- 批准号:9907930
- 负责人:
- 金额:$ 29.39万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:1999
- 资助国家:美国
- 起止时间:1999-09-15 至 2003-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Under support from the U.S. Weather Research Program, the Principal Investigators will develop a new method to measure rainfall using polarimetric radar. Recent evidence obtained from polarimetric weather radars suggests that when existing polarimetric methods fail to adequately estimate rainfall, a significant cause is the variability in drop size distribution (DSD). Thus, understanding the impact of DSD on the performance of the polarimetric algorithms for rainfall estimation will be a major thrust of this research effort. The Principal Investigators will exploit this knowledge to develop a novel approach for rainfall estimation. The idea is to use polarimetric radar data to classify various rainfall regimes according to their DSD so that appropriate polarimetric relations can be continuously matched to each rain type. Characterization of a rainfall regime will be derived from various polarimetric variables. The corresponding DSD's will be measured by a state-of-the-art two-dimensional video-disdrometer. The disdrometer will be placed in a pit within an array of closely spaced rain gauges to eliminate wind effects and to acquire independent estimates of rainfall. Disdrometer data will be collected in all types of rainfall found in Oklahoma storms to develop the rain regime classification and to understand the differences among the various regimes.Verification of the "matched" polarimetric rainfall estimates will be done by comparison with rain gauge data from a micronetwork (42 gages at 5 km spacing, operated by the Agricultural Research Service, USDA) in south-central Oklahoma, the Oklahoma Mesonet (one or two gauges in each Oklahoma county), and the NOAA Cooperative Network. The latter two data sets will be employed primarily to assess range effects on the quality of radar rainfall estimation. At long distances non-uniform radar beam filling and vertical stratification of precipitation add to the uncertainty in rainfall estimates. The complement of network rain gauges, the Cimarron polarimetric radar just west of Oklahoma City, three operational WSR-88D radars in and around central Oklahoma, and a rain gauge comparison facility in Norman, provide a unique field laboratory to support the investigation. In addition, the Principal Investigators have a long history of radar - rain gauge comparisons.Improvement in radar rainfall estimation will have a positive impact on the quality of precipitation forecasts. Improved estimates will assist in mitigation of natural disasters due to flooding and lead to better management of water resources by government and commercial organizations.
在美国天气研究计划的支持下,主要研究人员将开发一种使用偏振雷达测量降雨的新方法。 最近从极化天气雷达获得的证据表明,当现有的极化方法无法充分估计降雨量时,一个重要原因是液滴尺寸分布(DSD)的变异性。 因此,了解DSD对降雨估计的极化算法的性能的影响将是这项研究工作的主要推动力。 主要研究人员将利用这些知识开发一种新的降雨估计方法。 我们的想法是使用极化雷达数据分类不同的降雨制度,根据其DSD,使适当的极化关系,可以连续匹配到每一种雨型。 降雨状况的特征将从各种极化变量中得出。 相应的DSD将由最先进的二维视频衍射仪测量。 降雨计将放置在一个坑内,坑内有一排间隔很近的雨量计,以消除风的影响,并获得独立的降雨量估计值。 将收集俄克拉荷马州风暴中所有类型降雨的散射计数据,以发展降雨状况分类,并了解各种状况之间的差异。将通过与来自微网络的雨量计数据进行比较,验证“匹配”的极化降雨估计值(42 gages at 5 km pitch,operated by the Agricultural Research Service,USDA)在俄克拉荷马州中南部,俄克拉荷马州Mesonet(每个俄克拉荷马州县有一个或两个测量仪)和NOAA合作网络。 后两组数据将主要用于评估距离对雷达降雨量估计质量的影响。在远距离上,不均匀的雷达波束填充和降水的垂直分层增加了降雨量估计的不确定性。网络雨量计的补充,俄克拉荷马州市以西的西马龙偏振雷达,俄克拉荷马州中部及其周围的三个运行WSR-88 D雷达,以及诺曼的雨量计比较设施,提供了一个独特的现场实验室来支持调查。 此外,首席调查员在雷达与雨量计比较方面有悠久的历史,雷达雨量估计的改善将对降水预测的质素有正面影响。 更好的估计将有助于减轻洪水造成的自然灾害,并使政府和商业组织更好地管理水资源。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
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Alexander Ryzhkov其他文献
Improvements in the Compression Filter and Calibration Factor of the Progressive Pulse Compression Technique
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2022 - 期刊:
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A technique proximate and ultimate analysis of solid fuels and coal tar
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10.1007/s10973-015-5134-7 - 发表时间:
2015-11-05 - 期刊:
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Alexander Ryzhkov的其他文献
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{{ truncateString('Alexander Ryzhkov', 18)}}的其他基金
Collaborative Research: Using Polarimetric Radar Observations, Cloud Modeling, and In Situ Aircraft Measurements for Large Hail Detection and Warning of Impending Hail
合作研究:利用偏振雷达观测、云建模和现场飞机测量来检测大冰雹并预警即将发生的冰雹
- 批准号:
2344259 - 财政年份:2024
- 资助金额:
$ 29.39万 - 项目类别:
Standard Grant
Collaborative Research: Studies of the Microphysical Processes in Ice and Mixed-Phase Clouds and Precipitation Using Multiparameter Radar Observations Combined with Cloud Modeling
合作研究:利用多参数雷达观测结合云模拟研究冰、混相云和降水的微物理过程
- 批准号:
1841246 - 财政年份:2019
- 资助金额:
$ 29.39万 - 项目类别:
Standard Grant
Winter Precipitation Microphysics with Polarimetric Radar and Explicit Modeling
利用偏振雷达和显式建模进行冬季降水微物理研究
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1143948 - 财政年份:2012
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Standard Grant
Tornadic Storms with Doppler Polarimetric Radar
使用多普勒偏振雷达观测龙卷风
- 批准号:
0532107 - 财政年份:2006
- 资助金额:
$ 29.39万 - 项目类别:
Continuing Grant
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