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

基本信息

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

项目摘要

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.

冬季风暴会导致运输，商业，电网和公共安全的重大干扰。该研究项目的目的是提供有关冬季风暴期间云和降水量的更好信息，以便可以更好地预测这些事件。研究人员将使用先进的雷达观测和技术来分析这些数据，以研究影响地表降水类型和降水量的各种过程。对暴风雪的更好预测对于地面和航空旅行尤为重要，这项工作与相关的运营预测机构有联系。此外，学生将接受雷达气象技术的培训，以确保下一代科学家的发展。研究团队将研究冷季风暴的微物理学，重点是使用多频，双极化雷达观察。现代天气雷达技术中最先进的工具与明确的微物理建模的独特组合将用于更好地理解冬季风暴中的微物理学，包括树突状增长，额定，聚集，高空聚集以及熔融层的过程。主要的观察工具将是Stony Brook University的雷达设施，由KA波段扫描雷达以及W-和KU波段分析雷达雷达强调。地面测量值将包括多角度雪花摄像头（MASC），调解仪以及社区协作铁路，冰雹和雪网（Cocorahs）观察。 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借助向前雷达操作员模拟雪形成的关键微物理过程，并提供了建议，以改善这些过程以大量和光谱箱模型改善这些过程。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的审查标准来通过评估来支持的。

项目成果

期刊论文数量（7）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

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

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.

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

DOI：
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.

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