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

使用雷达偏振测量和多普勒频谱 (CORSIPP) 描述受地形影响的雾化和次生冰生成及其对降水率的影响

• 批准号: 408008112
• 负责人: Dr. Heike Kalesse-Los
• 金额: --
• 依托单位: Institut für Meteorologie
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/408008112?language=en
• 关键词: Characterization; orography; influenced; riming; secondary

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.

降水是水文循环的主要组成部分。要了解气候变暖时水收支如何变化，就必须全面了解降水形成过程。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途径还不清楚。这是特别真实的雾凇和二次冰生产（SIP）的过程，可能与最大的不确定性定量降雪形成。填补我们对SIP和riming的理解的空白对于山区特别重要，因为山区特别容易受到降水和水预算变化的影响，例如降雨和降雪之间的比例。在这里，我们提出了一个研究项目，致力于了解riming和SIP过程中的复杂地形。为此，我们将在科罗拉多落基山的整个冬季运行一个创新的连续发射连续接收（STSR）扫描W波段云雷达和一个新颖的原位降雪相机。这些仪器将是大气辐射测量（ARM）地面大气综合现场实验室（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，我们将确定riming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）与额外的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。结合起来，拟议的项目将提高我们的理解，在复杂的地形和SIP过程。