Collaborative Research: Studies of the Microphysical Processes in Ice and Mixed-Phase Clouds and Precipitation Using Multiparameter Radar Observations Combined with Cloud Modeling

合作研究：利用多参数雷达观测结合云模拟研究冰、混相云和降水的微物理过程

• 批准号: 1841215
• 负责人: Pavlos Kollias
• 金额: $ 33.04万
• 依托单位: SUNY at Stony Brook
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-01 至 2024-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1841215&HistoricalAwards=false
• 关键词: Collaborative; Research; Studies; Microphysical; Processes

Winter storms cause major disruptions to transportation, commerce, the power grid and public safety. The goal of this research project is to provide better information on the properties of clouds and precipitation during winter storms so that these events can be better forecast. The researchers will use advanced radar observations, and techniques to analyze that data, to study a variety of processes in winter storms that affect the types and amount of precipitation that falls at the surface. Better predictions of snowstorms are especially important for ground and air travel and this work has connections to the relevant operational forecast agencies. In addition, students will be trained in radar meteorology techniques, ensuring the advancement of the next generation of scientists.The research team will investigate the microphysics of cold-season storms, with a focus on the use of multi-frequency, dual-polarimetric radar observations. A unique combination of state-of-the-art tools in modern weather radar technology and explicit microphysical modeling will be used to derive a better understanding of the microphysics in winter storms, including dendritic growth, riming, aggregation aloft, and processes in the melting layer. The main observational tools will be the radar facilities at Stony Brook University, which are highlighted by the Ka-band scanning radar and W- and Ku-band profiling radars. Ground measurements will include the Multi-Angle Snowflake Camera (MASC), disdrometers, and Community Collaborative Rail, Hail and Snow Network (CoCoRaHS) observations. The main objectives of the work are to: 1) Explore synergy among polarimetric, multi-frequency, and Doppler radar measurements using innovative techniques for processing and representing multi-parameter radar data to provide information about microphysical and kinematic processes in ice and mixed-phase clouds, 2) Investigate novel radar methods for quantification of ice hydrometers, and 3) Develop a 1D cloud spectral bin model combined with a forward radar operator to simulate key microphysical processes of snow formation and provide recommendations for improving the parameterization these processes in large bulk and spectral bin models.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

冬季风暴对交通、商业、电网和公共安全造成重大破坏。 该研究项目的目标是提供有关冬季风暴期间云和降水特性的更好信息，以便更好地预报这些事件。 研究人员将使用先进的雷达观测和技术来分析这些数据，以研究冬季风暴中影响地面福尔斯降水类型和数量的各种过程。 更好地预测暴风雪对地面和空中旅行特别重要，这项工作与相关的业务预报机构有关。 此外，学生将接受雷达气象学技术培训，确保下一代科学家的进步，研究小组将调查冷季风暴的微观物理学，重点是使用多频率、双极化雷达观测。 现代天气雷达技术和显式微物理建模的最先进工具的独特组合将用于更好地了解冬季风暴中的微物理学，包括树枝状生长，雾凇，高处聚集和融化层中的过程。 主要的观测工具将是斯托尼布鲁克大学的雷达设施，主要是Ka波段扫描雷达和W波段和Ku波段剖面雷达。 地面测量将包括多角度雪花相机（MASC），disdrometers和社区合作铁路，冰雹和雪网络（CoCoRaHS）观测。 这项工作的主要目标是：1）探索极化，多频和多普勒雷达测量之间的协同作用，使用创新技术处理和表示多参数雷达数据，以提供有关冰和混合相云中微物理和运动学过程的信息，2）研究新的雷达方法来量化冰比重计，和3）开发一个一维云光谱面元模型，结合前向雷达操作员，模拟雪形成的关键微物理过程，并为改进大体积和光谱面元模型中这些过程的参数化提供建议。该奖项反映了NSF的法定使命，并被认为值得支持通过使用基金会的知识价值和更广泛的影响审查标准进行评估。

项目成果

Snowflake Selfies: A Low-Cost, High-Impact Approach toward Student Engagement in Scientific Research (with Their Smartphones)

雪花自拍：一种低成本、高影响力的学生参与科学研究的方法（使用智能手机）

• DOI: 10.1175/bams-d-19-0096.1
• 发表时间: 2020
• 期刊: Bulletin of the American Meteorological Society
• 影响因子: 8
• 作者: Kumjian, Matthew R.;Bowley, Kevin A.;Markowski, Paul M.;Lombardo, Kelly;Lebo, Zachary J.;Kollias, Pavlos
• 通讯作者: Kollias, Pavlos

First Light Multi-Frequency Observations with a G-band radar

使用 G 波段雷达进行首次光多频率观测

• 发表时间: 2020
• 期刊: Atmospheric measurement techniques
• 影响因子: 3.8
• 作者: Lamer, K.;Oue, M.;Battaglia, A.;Roy, R. J.;Cooper, K. B.;Dhillon, R.;and Kollias, P.
• 通讯作者: and Kollias, P.

The Cloud-resolving model Radar SIMulator (CR-SIM) Version 3.3: description and applications of a virtual observatory

云解析模型雷达模拟器 (CR-SIM) 3.3 版：虚拟天文台的描述和应用

• DOI: 10.5194/gmd-13-1975-2020
• 发表时间: 2020
• 期刊: Geoscientific Model Development
• 影响因子: 5.1
• 作者: Oue, Mariko;Tatarevic, Aleksandra;Kollias, Pavlos;Wang, Dié;Yu, Kwangmin;Vogelmann, Andrew M.
• 通讯作者: Vogelmann, Andrew M.

Impacts of Vertical Nonuniform Beam Filling on the Observability of Secondary Ice Production due to Sublimation

垂直非均匀光束填充对升华产生的二次冰的可观测性的影响

• DOI: 10.1175/jtech-d-22-0076.1
• 发表时间: 2023
• 期刊: Journal of Atmospheric and Oceanic Technology
• 影响因子: 2.2
• 作者: Carlin, Jacob T.;Dunnavan, Edwin L.;Ryzhkov, Alexander V.;Oue, Mariko
• 通讯作者: Oue, Mariko

Microphysical Insights into Ice Pellet Formation Revealed by Fully Polarimetric Ka-Band Doppler Radar

全偏振 Ka 波段多普勒雷达揭示冰粒形成的微观物理见解

• DOI: 10.1175/jamc-d-20-0054.1
• 发表时间: 2020
• 期刊: Journal of Applied Meteorology and Climatology
• 影响因子: 3
• 作者: Kumjian, Matthew R.;Tobin, Dana M.;Oue, Mariko;Kollias, Pavlos
• 通讯作者: Kollias, Pavlos