Characterization of orography-influenced riming and secondary ice production and their effects on precipitation rates using radar polarimetry and Doppler spectra (CORSIPP)

降水是水文循环的主要组成部分。要了解在气候变暖的情况下水收支是如何变化的，就需要对降水形成过程有一个全面的了解。在中纬度地区，大多数降水是通过混合相云中的冰相产生的，但是冰、液态水、云动力学、地形强迫和气溶胶颗粒在冰、雪和雨形成过程中相互作用的确切途径尚不清楚。对于可能与定量降雪形成方面的最大不确定性相关的轮冻和次生冰生成（SIP）过程尤其如此。填补我们对SIP和rimming的理解空白对于特别容易受到降水和水收支变化（如雨雪比）影响的山区尤为重要。在这里，我们提出了一个研究项目，致力于了解在复杂地形的边缘和SIP过程。为此，我们将在科罗拉多落基山运行一个创新的同步传输-同步接收（STSR）扫描w波段云雷达和一个新颖的原位降雪相机，用于整个冬季。这些仪器将成为大气辐射测量（ARM）地面大气综合野外实验室（SAIL）活动的一部分，其中将部署ka波段和x波段雷达。结合光谱偏振和多频多普勒雷达观测与经验和贝叶斯机器学习检索技术，我们将识别轮辋和SIP事件，并量化它们对降雪率的影响。这一目标需要扩展被动和主动微波辐射传输模型（PAMTRA），增加极化变量和最先进的散射能力。最后，使用SAIL的广泛并置测量将使我们能够将观察到的过程速率与环境条件（如温度，湿度和液态水路径以及云动力学）联系起来。此外，我们将特别关注在地形条件下经常出现的垂直空气运动的影响。综合起来，拟议的项目将加强我们对复杂地形中的轮动和SIP过程的理解。

Precipitation is a major component of the hydrological cycle. A comprehensive understanding of the precipitation formation processes is required to understand how the water budget is changing in a warming climate. In mid-latitudes, most precipitation is generated through the ice phase in mixed-phase clouds, but the exact pathways through which ice, liquid water, cloud dynamics, orographic forcing, and aerosol particles are interacting during ice, snow and rain formation are not well understood. This is particularly true for riming and secondary ice production (SIP) processes that are likely related to the largest uncertainties with respect to quantitative snowfall formation. Filling the gaps in our understanding of SIP and riming is especially crucial for mountainous regions that are particularly vulnerable to changes in precipitation and the water budget such as the ratio between rain and snowfall. Here, we propose a research project dedicated to understanding riming and SIP processes in complex terrain. For this, we will operate an innovative simultaneous-transmission-simultaneous-reception (STSR) scanning W-band cloud radar together with a novel in situ snowfall camera for one entire winter season in the Colorado Rocky Mountain. The instruments will be part of the Atmospheric Radiation Measurement (ARM) Surface Atmosphere Integrated Field Laboratory (SAIL) campaign where a Ka-band and a X-band radar will be deployed. Combining spectral polarimetric and multi frequency Doppler radar observations with empirical and Bayesian machine learning retrieval techniques, we will identify riming and SIP events and quantify their impact on snowfall rates. This goal requires extending the Passive and Active Microwave radiative TRAnsfer model (PAMTRA) with additional polarimetric variables and state of the art scattering capabilities. Finally, using the extensive collocated measurements of SAIL will allow us to relate the observed process rates to environmental conditions such as temperature, humidity and liquid water path as well as cloud dynamics. In addition, we will put a special focus on the impact of vertical air motions that appear frequently in orographic conditions. Combined, the proposed project will enhance our understanding of riming and SIP processes in complex terrain.