Accurate Characterization of Winter Precipitation Using Multi-Angle Snowflake Camera, Visual Hull, Advanced Scattering Methods, and Polarimetric Radar

这项奖励将建立一种新的方法来表征冬季降水并对相关的极化雷达观测值进行建模，其长期目标是在更强、更危险的冬季事件中显著改进基于雷达的定量降水估计。主要的实现技术是(I)多角度雪花相机(MASC)，(Ii)重建3D水流星形状的视觉外壳(VH)几何方法，(Iii)快速准确的高级计算电磁(CEM)散射法，以及(Iv)来自先进CSU-CHILL雷达的全极化数据。这项研究的主要目标和使用的方法是：-使用MASC对冰粒进行微观物理和逼真的三维几何表征--结合坠落速度和颗粒几何来估计密度--“尺寸”幂定律、雪率--计算“逐颗粒”散射矩阵和偏振雷达观测值--雷达可测量物体模拟中散射模型各种参数的敏感性研究--CSU-CHILL和MASC/VH/CEM冬季降水事件数据的分析和交叉验证--针对先前分类的颗粒类型，推导和验证基于雷达的雪率关系。总体而言，它协同使用了新的研究仪器(MASC)，结合准确、高效、通用和强大的CEM散射方法，以及最先进的极化雷达(具有极高的极化纯度)，以显著提高雷达观测数据建模和冬季降水特征的准确性。这是首次使用真实(测量的)雪花图像进行高精度和高效的真实散射计算，以获得雷达可测量的参数，这将通过高精度的极化雷达进行验证。这将是关于散射矩阵的第一组高质量多年数据，以及构成冬季降水的基于MASC的分类粒子类型的全套雷达观测数据。基于高阶矩方法(MOM)的大气粒子散射全波CEM模拟方法将能够克服T矩阵和DDA方法的所有缺点。基于三张MASC照片的VH方法重建雪花三维形状比任何其他可用的雪花形状重建实例都要准确得多。从长远来看，这项研究将通过首先对降水类型进行分类，然后进行量化，显著改进基于雷达的对更强、更危险的冬季事件近地表液体当量降雪率的估计。使用MASC和OTT-PLOVIO雪量计联合进行的冬季降水研究将影响高级云解析模式中使用的微物理参数。由MASC/VH/CEM方法获得的冰水流星在3-150 GHz多个雷达/辐射传感器频率下的综合散射特性“查询表”应该是该领域的许多研究人员感兴趣和使用的。基于雷达的雪率关系将直接适用于WSR-88D网络对冬季降水的改进量化。本研究还旨在建立和推广全波CEM模拟方法和高阶MOM方法，作为未来大气颗粒散射分析研究的使能资源和技术。应用可扩展到辐射云/雪探测和毫米波雷达。有可能改变冬季降水的特征；这项研究的性质是变革性的。教育和宣传活动包括培训两名博士生，开设关于降水粒子散布的新课程，为科罗拉多前线范围内的研究生、教员和科学家举办一系列关于该项目主题的研讨会/讲座的高级讲习班，以及为高中生举办的关于雪花研究的K-12外联讲习班。

This award will establish a novel approach to characterization of winter precipitation and modeling of associated polarimetric radar observables, with a longer-term goal to significantly improve the radar-based quantitative precipitation estimation in stronger, more hazardous, winter events. The principal enabling technologies are (i) multi-angle snowflake camera (MASC), (ii) visual hull (VH) geometrical method for reconstruction of 3D hydrometeor shapes, (iii) fast and accurate advanced higher order computational electromagnetics (CEM) scattering methods, and (iv) fully polarimetric data from the advanced CSU-CHILL radar. The main objectives of this research and methods to be employed are:- Microphysical and realistic 3D-geometrical characterization of ice particles using MASC- Combining fall speed and particle geometry to estimate density-"size" power laws, snow rates- Calculations of "particle-by-particle" scattering matrices and polarimetric radar observables- Sensitivity studies of various parameters of scattering models in simulations of radar measurables- Analysis and cross-validation of CSU-CHILL and MASC/VH/CEM data for winter precipitation events- Derivation and validation of radar-based snow rate relations for previously classified particle types Intellectual merit is contained in and warranted by the research objectives described above. Overall, it is in the synergistic use of new research instrumentation (MASC) coupled with accurate, efficient, versatile, and robust CEM scattering methods as well as state-of-the-art polarimetric radar (with exceptional polarization purity) to substantially increase the accuracy of modeling of radar observables and characterization of winter precipitation. This is the first time real (measured) snowflake images will be used with highly accurate and efficient realistic scattering calculations, to obtain radar measurable parameters, which will be validated by a highly precise polarimetric radar. This will be the first set of high-quality multi-year data for scattering matrices and the full set of radar observables for MASC-based classified particle types constituting winter precipitation. The full-wave CEM modeling approach to atmospheric particle scattering based primarily on the higher order method of moments (MoM) will be able to overcome all shortcomings of both the T-matrix and the DDA methods. Snowflake 3D shape reconstruction by the VH method based on three MASC photographs is much more accurate than any other available snowflake shape reconstruction examples.This research will significantly improve, in a longer term, the radar-based estimation of liquid equivalent snow rates near the surface in stronger, more hazardous, winter events by first classification of precipitation type followed by quantification. Winter precipitation studies using the combined MASC and OTT-Pluvio snow gauge will impact microphysical parameterizations used in advanced cloud resolving models. "Look-up tables" with comprehensive scattering properties of ice hydrometeors, obtained by MASC/VH/CEM-methods, at multiple radar/radiometric sensor frequencies from 3-150 GHz, should be of interest and use for many researchers in the field. Radar-based snow rate relations will be directly applicable to improved quantification of winter precipitation by the WSR-88D network. This research is also aimed at establishing and promoting the full-wave CEM modeling approach and the higher order MoM as an enabling resource and technology for future research in atmospheric particle scattering analysis. Applications may be extended to radiometric cloud/snow detection and mm-wave radars. Having potential to change the way characterization of winter precipitation is done; this research is transformative in its nature. Educational and outreach activities include training of two Ph.D. students, a new course on scattering by precipitation particles, advanced workshops with a series of seminars/lectures on the topics of the project for graduate students, faculty, and scientists within the Colorado Front Range, and K-12 outreach workshops on Snowflake Research for high school students.