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。需要对降水形成过程有全面的了解，才能了解气候变暖情况下水收支的变化。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，但冰、液态水、云动力学、地形强迫和气溶胶粒子在冰、雪和雨形成过程中相互作用的确切路径尚不清楚。对于可能与定量降雪形成的最大不确定性相关的结冰和二次制冰(SIP)过程而言，情况尤其如此。对于特别容易受到降水和水收支变化(如雨雪比)影响的山区来说，填补我们对SIP和Riming的理解上的空白尤其重要。在这里，我们提出了一个致力于了解复杂地形中的Riming和SIP流程的研究项目。为此，我们将在科罗拉多州落基山脉的整个冬季使用一台创新的simultaneous-transmission-simultaneous-reception扫描W波段云雷达和一台新型的就地降雪相机。这些仪器将是大气辐射测量(ARM)地面大气综合野战实验室(SAIL)行动的一部分，将在该行动中部署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以及经验和贝叶斯机器学习恢复技术，我们将识别Riming和SIP事件，并量化它们对降雪率的影响。为了实现这一目标，需要在被动和主动微波辐射传输模型(PAMTRA)中添加额外的偏振变量和最新的散射能力。最后，使用广泛配置的SAIL测量将使我们能够将观测到的过程速率与环境条件(如温度、湿度、液态水路径以及云动态)联系起来。此外，我们还将特别关注地形条件下频繁出现的垂直空气运动的影响。总而言之，拟议的项目将加强我们对复杂地形中的Riming和SIP流程的了解。

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.