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

本研究的目标是通过同化双极化多普勒（“dual-pol”）雷达观测来改进高分辨率（1 ~ 4 km）数值模型中对流风暴的初始化，并同样利用数值模型和数据同化来提高对对流风暴演化的理解。本研究的目标包括：1）开发“雷达前向模型”中包含的冰相微物理过程的多普勒雷达数据同化方法，并使用实际（即ARMOR观测到的）案例研究来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；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）开发一种独特的同化观测的技术从双极化多普勒雷达，研究执行雷达数据同化的有效策略，并评估模型[天气研究和预报（WRF）模型]初始条件和数值预测中每个双极化变量的影响。智力优点研究活动将提高使用冰相前向模型进行多普勒雷达数据同化的技能，更好地理解模型微物理参数和双极化雷达观测的不确定性，以及随后双极化的重大进展多普勒雷达数据同化技术。 该研究将利用用于气象和业务研究的地面C波段先进雷达（ARMOR）双极化多普勒观测，以及目前在亨茨维尔阿拉巴马大学（UAHuntsville）/国家空间科学技术中心（NSSTC；特别是X波段移动多普勒雷达）运行的独特的现场和遥感观测仪器套件。 ARMOR 雷达收集的双极化测量结果将被同化到 WRF 中，并将冰相微物理过程嵌入到数据同化包中。 这些数据还将用于检查和约束 WRF 模型的微物理参数化中的不确定性。 NSSTC仪器的观测、高分辨率数值模拟以及对流风暴选定案例事件的数据同化结果将用于开展上述研究活动。这项研究将是同类研究中首次使用双偏振多普勒雷达观测与 WRF 模型和 3DVAR 数据同化系统进行实际案例研究。更广泛的影响该研究有可能改善对流天气的业务预报。 特别是，研究人员将有助于提高对对流风暴演变的理解，以及如何通过多普勒雷达观测的同化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，以改进当前对流风暴的预测。鉴于目前正在进行的WSR-88D雷达网络的升级，双极化雷达数据同化的研究需要走向前沿，以便可以开发出利用这些数据的最佳方法的新见解。 新的发现将通过会议演讲、同行评审的期刊文章以及用于加强课程的教育材料来传达。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。

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.