Collaborative Research: Dual-Polarimetric Radar Data Assimilation Research for Enhanced Initialization of Moist Convective Systems

合作研究：湿对流系统增强初始化的双极化雷达数据同化研究

• 批准号: 1005354
• 负责人: John Mecikalski
• 金额: $ 44.41万
• 依托单位: University of Alabama in Huntsville
• 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: 2011-04-01 至 2015-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1005354&HistoricalAwards=false
• 关键词: Collaborative; Research; Dual; Polarimetric; Radar

The goals of this research are to improve the initialization of convective storms in high-resolution (1 ~ 4 km) numerical models by assimilating dual-polarimetric Doppler ("dual-pol") radar observations, and likewise to improve understanding of the evolution of convective storms using numerical models and data assimilation. The objectives of this research include:1) to develop a Doppler radar data assimilation methodology for ice-phase microphysical processes included in the "radar forward model", and to understand the general role of microphysics processes in convective storms and the storm related precipitation, using actual (i.e. as observed by ARMOR) case studies;2) to understand the information content of dual-polarimetric radar observations and their relationship to model physics uncertainty;3) to develop a technique to assimilate observations uniquely from the dual-polarimetric Doppler radar, investigate effective strategies for performing radar data assimilation, and evaluate the impacts of each dual-polarimetric variable in the model's [the Weather Research and Forecasting (WRF) model] initial condition and numerical prediction.Intellectual MeritsThe research activities will improve skill in Doppler radar data assimilation with ice-phase forward model, a better understanding of uncertainty in model microphysical parameters and dual-polarimetric radar observations, and subsequently significant advances in dual-polarimetric Doppler radar data assimilation techniques. The research will take advantage of the availability of the ground-based C-band Advanced Radar for Meteorological and Operational Research (ARMOR) dual-polarimetric Doppler observations, as well as the unique suite of in-situ and remote sensing observational instruments currently operating in the University of Alabama in Huntsville (UAHuntsville)/National Space Science and Technology center (NSSTC; in particular, an X-band mobile Doppler radar). Dual-polarimetric measurements collected by the ARMOR radar will be assimilated into the WRF with ice-phase microphysical processes embedded into the data assimilation package. These data will also be used to examine and constrain the uncertainties in the WRF model's microphysical parameterization. Observations from the NSSTC instruments, high-resolution numerical simulations, and data assimilation results for select case events of convective storms will be used to conduct the aforementioned research activities. This research will be one of the first of its kind using dual-polarimetric Doppler radar observations with the WRF model and the 3DVAR data assimilation system for real case studies.Broader ImpactThe research has the potential to improve operational forecasts of convective weather. In particular, the researchers will contribute to improving understanding of the evolution of convective storms and how to enhance short-term forecasts of convective precipitation via the assimilation of Doppler radar observations. The data assimilation techniques developed herein will be readily transferable to other research institutes, as well as the operational community, for improvements in the current prediction of convective storms. Given the upgrade of the WSR-88D radar network that is currently underway, research on the assimilation of dual-polarimetric radar data needs to move to the forefront so that new insights on the optimal methods for utilizing these data may be developed. The new findings will be communicated through conference presentations, peer-reviewed journal articles, and in educational materials for enhancing course curriculum. Collaboration with other university scientists and graduate students will further extend this research to the larger academic and educational community.

本研究的目的是通过同化双极化多普勒雷达观测资料来改进高分辨率（1 ~ 4 km）数值模式中对流风暴的初始化，同时利用数值模式和资料同化来提高对对流风暴演变的认识。本研究的主要目的是：1）发展一种用于雷达正演模式中冰相微物理过程的多普勒雷达资料同化方法，并利用实际资料，了解微物理过程在对流风暴和风暴相关降水中的一般作用。（如ARMOR观测）案例研究;2）了解双极化雷达观测的信息内容及其与模型物理不确定性的关系;（3）发展一种独特的同化双极化多普勒雷达观测资料的技术，研究进行雷达资料同化的有效策略，并评估每一个双极化变量在模式[天气研究与预报模式]初始条件和数值预报中的影响。学术价值研究活动将提高多普勒雷达资料同化冰相前向模式的技能，更好地了解模式微物理参数和双极化雷达观测的不确定性，并随后在双极化多普勒雷达数据同化技术方面取得重大进展。 这项研究将利用现有的地面C波段气象和业务研究高级雷达（ARMOR）双极化多普勒观测，以及亨茨维尔的亚拉巴马大学/国家空间科学和技术中心（NSSTC;特别是X波段移动的多普勒雷达）目前正在使用的一套独特的现场和遥感观测仪器。 ARMOR雷达收集的双极化测量数据将被同化到WRF中，冰相微物理过程嵌入到数据同化包中。 这些数据也将用于检查和限制WRF模式的微物理参数化的不确定性。上述研究活动将利用NSSTC仪器的观测结果、高分辨率数值模拟和选定对流风暴个例的数据同化结果。这项研究将是第一个使用双偏振多普勒雷达观测与WRF模式和3DVAR数据同化系统的真实的个例study.Broader ImpactThe研究有可能提高业务预报的对流天气。 特别是，研究人员将有助于提高对对流风暴演变的理解，以及如何通过同化多普勒雷达观测来加强对流降水的短期预报。 本文开发的数据同化技术将很容易转移到其他研究机构，以及业务界，在目前的对流风暴预报的改进。鉴于WSR-88 D雷达网络目前正在进行升级，关于双极化雷达数据同化的研究需要走到最前沿，以便开发关于利用这些数据的最佳方法的新见解。 新的研究结果将通过会议报告，同行评议的期刊文章，并在教育材料，以加强课程进行沟通。与其他大学科学家和研究生的合作将进一步将这项研究扩展到更大的学术和教育界。