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

该合同将建立一种描述冬季降水特征和相关极化雷达观测模型的新方法，其长期目标是在更强、更危险的冬季事件中显著改善基于雷达的定量降水估计。主要实现技术是(i)多角度雪花相机（MASC）， （ii）用于重建3D水流星形状的视觉船体（VH）几何方法，（iii）快速准确的先进高阶计算电磁（CEM）散射方法，以及（iv）来自先进CSU-CHILL雷达的全极化数据。本研究的主要目标和采用的方法是：-使用MASC对冰粒进行微观物理和逼真的3d几何表征-结合下落速度和颗粒几何来估计密度-“尺寸”幂律，降雪率。“逐粒子”散射矩阵和极化雷达观测值的计算。雷达可测量值模拟中散射模型各种参数的敏感性研究。冬季降水事件的CSU-CHILL和MASC/VH/CEM数据的分析和交叉验证。基于雷达的降雪率关系的推导和验证先前分类的粒子类型。上述研究目标包含并保证了知识价值。总的来说，它是在新的研究仪器（MASC）的协同使用，加上准确，高效，通用和强大的CEM散射方法，以及最先进的极化雷达（具有特殊的极化纯度），以大大提高雷达观测模型和冬季降水表征的准确性。这是第一次将真实（测量）雪花图像与高精度和高效的现实散射计算一起使用，以获得雷达可测量参数，这些参数将通过高精度极化雷达进行验证。这将是第一组关于散射矩阵的高质量多年数据，以及基于masc的构成冬季降水的分类粒子类型的全套雷达观测数据。基于高阶矩量法（MoM）的大气粒子散射全波CEM建模方法能够克服t矩阵和DDA方法的所有缺点。基于三张MASC照片的VH法雪花三维形状重建比其他任何可用的雪花形状重建实例都要准确得多。从长远来看，本研究将通过首先对降水类型进行分类，然后进行量化，显著改善基于雷达的在更强、更危险的冬季事件中近地表液体等效雪率的估计。使用MASC和OTT-Pluvio积雪计联合进行的冬季降水研究将影响高级云分辨模式中使用的微物理参数化。通过MASC/VH/ cem方法在3-150 GHz多个雷达/辐射传感器频率下获得的冰水气象物综合散射特性的“查找表”应该引起该领域许多研究人员的兴趣和使用。基于雷达的雪率关系将直接适用于WSR-88D网对冬季降水的改进量化。本研究还旨在建立和推广全波CEM建模方法和高阶MoM，为未来大气粒子散射分析的研究提供有利的资源和技术。应用范围可扩展到辐射云/雪探测和毫米波雷达。有可能改变冬季降水的表征方式；这项研究本质上是变革性的。教育和推广活动包括培训两名博士生，开设一门关于降水粒子散射的新课程，为科罗拉多前沿地区的研究生、教师和科学家举办一系列研讨会/讲座的高级讲习班，以及为高中学生举办的关于雪花研究的K-12推广讲习班。

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.