Advanced Study of Precipitation Microphysics with Multi-Frequency Polarimetric Radar Observations and Data Assimilation
多频极化雷达观测与数据同化的降水微物理高级研究
基本信息
- 批准号:1046171
- 负责人:
- 金额:$ 63.77万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2011
- 资助国家:美国
- 起止时间:2011-06-01 至 2015-05-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Progress toward more accurate short-range quantitative precipitation forecasts (QPF) depends on optimal use of high-resolution observations within cloud-resolving numerical weather prediction (NWP) models. Among available candidate observations, those from the U.S. network of operational S-band WSR-88D radars (which are soon to be upgraded with dual-polarization capabilities) are among the richest datasets available for ingest by both operational- and research-quality models. Prior efforts by this group of investigators advanced the characterization and retrieval of microphysical precipitation particle type and size distributions using both polarimetric-radar and ground-based disdrometer data, and supported development of forward operators and ensemble-Kalman filter based assimilation capabilities for a storm-scale NWP model. Efforts under the current project will extend to include data from multi-wavelength data (including high-resolution C-band and X-band polarimetric observations) to seek further improvements of QPF and potential for severe weather threatening life and property.The intellectual merit of this effort centers on overcoming and correcting for non-Rayleigh scattering effects present at shorter wavelengths to allow full exploitation of these additional moment data in driving more accurate NWP simulations and (ultimately) short-term forecasts.Broader impacts of this research will occur through graduate student and postdoc training and capitalization upon an ongoing large NOAA investment in adding dual-polarization capability to the existing operational WSR-88D radar network. Direct collaboration with staff at NOAA's Radar Operations Center will facilitate integration of developed algorithms and codes into a testbed (and perhaps ultimately operational) setting, and should aid utilization of quantitative (vs. presently more qualitative) information on storm microphysical properties to the maximum extent possible.
更准确的短期定量降水预报(QPF)的进展取决于云解析数值天气预报(NWP)模式中高分辨率观测的最佳使用。 在可用的候选观测数据中,来自美国S波段WSR-88 D雷达网络(即将升级为双极化能力)的观测数据是可供作战和研究质量模型摄取的最丰富的数据集之一。 这组研究人员先前的努力,先进的表征和检索的微物理降水粒子类型和粒度分布,使用偏振雷达和地面disdrometer数据,并支持发展的前向运营商和集成卡尔曼滤波器为基础的同化能力的风暴尺度数值预报模式。 目前项目下的工作将扩大到包括多波长数据(包括高分辨率C波段和X波段偏振观测),以寻求进一步改进QPF和潜在的威胁生命和财产的恶劣天气。这项工作的智力价值集中在克服和纠正非瑞利散射效应存在于较短的波长,允许充分利用这些额外的矩数据,以驱动更准确的数值预报模拟,这项研究的更广泛的影响将发生通过研究生和博士后培训和资本化后,正在进行的大型NOAA投资,增加双极化能力,现有的业务WSR-88 D雷达网络。 与美国国家海洋和大气管理局雷达操作中心的工作人员直接合作,将促进开发的算法和代码集成到一个试验台(也许最终操作)设置,并应有助于利用定量(与目前更多的定性)信息风暴微物理特性的最大可能。
项目成果
期刊论文数量(0)
专著数量(0)
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会议论文数量(0)
专利数量(0)
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Guifu Zhang其他文献
Comparison of spaced‐antenna baseline wind estimators: Theoretical and simulated results
间隔天线基线风估计器的比较:理论和模拟结果
- DOI:
10.1029/2003rs002931 - 发表时间:
2004 - 期刊:
- 影响因子:1.6
- 作者:
R. Doviak;Guifu Zhang;S. Cohn;W. Brown - 通讯作者:
W. Brown
Assimilation of Polarimetric Radar Data in Simulation of a Supercell Storm with a Variational Approach and the WRF Model
- DOI:
https://doi.org/10.3390/rs13163060 - 发表时间:
2021 - 期刊:
- 影响因子:5
- 作者:
Muyun Du;Jidong Gao;Guifu Zhang;Yunheng Wang;Pamela L. Heiselman;Chunguang Cui - 通讯作者:
Chunguang Cui
Weather Radar Education at the University of Oklahoma--An Integrated Interdisciplinary Approach
俄克拉荷马大学的气象雷达教育——综合跨学科方法
- DOI:
- 发表时间:
2007 - 期刊:
- 影响因子:0
- 作者:
R. Palmer;M. Yeary;M. Biggerstaff;P. Chilson;J. Crain;K. Droegemeier;Y. Hong;A. Ryzhkov;T. Schuur;S. Torres;Tian;Guifu Zhang;Yan Zhang - 通讯作者:
Yan Zhang
Angular and range interferometry to refine weather radar resolution
角度和距离干涉测量法可提高气象雷达分辨率
- DOI:
10.1029/2004rs003125 - 发表时间:
2005 - 期刊:
- 影响因子:1.6
- 作者:
Guifu Zhang;Tian;R. Doviak - 通讯作者:
R. Doviak
Implementation and research on indoor mobile robot mapping and navigation based on RTAB-Map
基于RTAB-Map的室内移动机器人建图导航的实现与研究
- DOI:
10.1109/m2vip55626.2022.10041090 - 发表时间:
2022 - 期刊:
- 影响因子:0
- 作者:
Guifu Zhang;Zhisheng Zhang;Zhijie Xia;Min Dai;Peng Meng;Jiahuan Cen - 通讯作者:
Jiahuan Cen
Guifu Zhang的其他文献
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{{ truncateString('Guifu Zhang', 18)}}的其他基金
Hybrid Ensemble Variational Analysis of Polarimetric Radar Data to Improve Microphysical Parameterization and Short-term Weather Prediction
偏振雷达数据的混合集成变分分析,以改进微物理参数化和短期天气预报
- 批准号:
2136161 - 财政年份:2021
- 资助金额:
$ 63.77万 - 项目类别:
Continuing Grant
Improving Microphysics Parameterizations and Quantitative Precipitation Forecast through Optimal Use of Video Disdrometer, Profiler and Polarimetric Radar Observations
通过优化使用视频测距仪、剖面仪和偏振雷达观测来改进微物理参数化和定量降水预报
- 批准号:
0608168 - 财政年份:2006
- 资助金额:
$ 63.77万 - 项目类别:
Continuing Grant
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