Collaborative Research: Observing and Understanding Planetary Boundary Layer (PBL) Heterogeneities and Their Impacts on Tornadic Storms during VORTEX-SE 2018 Field Experiment

合作研究:在 VORTEX-SE 2018 现场实验期间观察和理解行星边界层 (PBL) 异质性及其对龙卷风暴的影响

基本信息

  • 批准号:
    1917701
  • 负责人:
  • 金额:
    $ 52.41万
  • 依托单位:
  • 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:
    2019-08-01 至 2024-07-31
  • 项目状态:
    已结题

项目摘要

High-impact weather phenomena such as high winds, hail, and heavy rainfall have huge socio-economic impacts. However, forecast for severe high-impact weather events, especially tornadoes, remains challenging. Historically, tornado research has been concentrated in the Great Plains while the Southeastern U.S. commonly experiences devastating tornadoes as well. Significant differences in environmental conditions over the two regions and frequent occurrence of tornadoes at night in the Southeast (SE) pose challenges to observing and understanding the formation and development of tornadoes in the SE. The Verification of the Origins of Rotation in Tornadoes Experiment - Southeast (VORTEX-SE) is a research program designed to understand how environments in the SE affect the formation, intensity, structure, and path of tornadoes in this region. During the VORTEX-SE field campaign in 2018, unprecedented advanced measurements from an airplane flying around tornadoes have been collected. Such observations cannot be done easily on the ground with hilly forest terrain. The study will utilize the unique observations and advanced computer models to understand airflow structures of tornadic storms and special environments for their formation. New knowledge gained from the research will contribute to improvement of tornado forecasting across the U.S. This project will provide support and training to graduate students in atmospheric measurement technologies, data analysis, and computer modeling and prepare them to become future scientists in severe weather research and prediction.The research team will conduct observational data analysis and advanced data assimilation that integrate observations and atmospheric prediction models. The unprecedented observation includes an advanced downward-pointing Compact Raman Lidar (CRL), a horizontally scanning lower fuselage (LF) radar, and dual Tail Doppler Radars (TDRs) onboard of a NOAA P-3 aircraft. The CRL is capable of measuring high-spatial and temporal resolution of water vapor, temperature, and aerosol profiles in the atmospheric boundary layer upstream of moving storms. Together with the P-3's in-situ measurements and the LF and TDR radar observations, unprecedented characterization of tornadic environments is expected. In addition, tornado-resolving numerical simulations will be performed, and variational, and ensemble-based data analysis and assimilation techniques will be applied. The primary goals of the project include: (1) characterization of spatial heterogeneities and temporal evolution of the PBL around convective storms in the VORTEX-SE domain with CRL measurements; (2) analysis and understanding of the impact of PBL heterogeneities on tornadic storms by synthesizing P-3 and other available observations; (3) identification and understanding of key physical processes involved in the tornadic storms through model simulations with advanced data assimilation methods. The synergy of airborne radar and lidar data with high-resolution model simulations will help pave the way for potentially transformative future process-oriented field experiments.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.
大风、冰雹和暴雨等高影响天气现象具有巨大的社会经济影响。然而,对严重的高影响天气事件,特别是龙卷风的预测仍然具有挑战性。从历史上看,龙卷风的研究一直集中在大平原,而美国东南部通常也会经历毁灭性的龙卷风。两个地区的环境条件存在显着差异,东南部(SE)夜间龙卷风频繁发生,这对观察和了解东南部龙卷风的形成和发展构成了挑战。东南部龙卷风实验中旋转起源的验证(VORTEX-SE)是一项研究计划,旨在了解东南部的环境如何影响该地区龙卷风的形成,强度,结构和路径。在2018年的VORTEX-SE现场活动中,从一架在龙卷风周围飞行的飞机上收集了前所未有的先进测量数据。在丘陵森林地形的地面上进行这种观测是不容易的。这项研究将利用独特的观测和先进的计算机模型来了解龙卷风风暴的气流结构及其形成的特殊环境。从研究中获得的新知识将有助于改善美国各地的龙卷风预报。该项目将为研究生提供大气测量技术,数据分析,和计算机建模,并准备他们成为未来的科学家在恶劣天气的研究和预测。研究小组将进行观测数据分析和先进的数据同化,结合观测和大气预测模型这一前所未有的观测包括NOAA P-3飞机机载的先进下指向紧凑型拉曼激光雷达(CRL)、水平扫描下机身(LF)雷达和双尾部多普勒雷达(TDRs)。CRL能够测量移动风暴上游大气边界层中的水汽、温度和气溶胶廓线的高空间和时间分辨率。加上P-3的现场测量和LF和TDR雷达观测,预计将对龙卷风环境进行前所未有的表征。此外,将进行解决龙卷风的数值模拟,并将应用变分和基于集合的数据分析和同化技术。该计划的主要目标是:(1)用CRL观测资料描述涡东南区对流风暴周围边界层的空间不均匀性和时间演变特征:(2)综合P-3和其他现有观测资料,分析和理解边界层不均匀性对龙卷风风暴的影响;(3)利用先进的资料同化方法,透过模式模拟,识别和了解龙卷风的主要物理过程。机载雷达和激光雷达数据与高分辨率模型模拟的协同作用将有助于为未来潜在的变革性面向过程的现场实验铺平道路。该奖项反映了NSF的法定使命,并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,被认为值得支持。

项目成果

期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
A Comparison of Convective Storm Inflow Moisture Variability between the Great Plains and the Southeastern United States Using Multiplatform Field Campaign Observations
使用多平台现场观测比较大平原和美国东南部之间的对流风暴流入水分变化
  • DOI:
    10.1175/jtech-d-22-0037.1
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    2.2
  • 作者:
    Lin, Guo;Wang, Zhien;Ziegler, Conrad;Hu, Xiao-Ming;Xue, Ming;Geerts, Bart;Chu, Yufei
  • 通讯作者:
    Chu, Yufei
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Ming Xue其他文献

[Effect of asiaticoside on hyperoxia-induced bronchopulmonary dysplasia in neonatal rats and related mechanism].
积雪草苷对高氧诱导的新生大鼠支气管肺发育不良的影响及相关机制
The Socket Programming and Software Design for Communication Based on Client/Server
基于客户端/服务器通信的Socket编程及软件设计
Unusual presentation of esophageal tuberculosis: a case study
  • DOI:
    10.1186/s12879-024-10418-9
  • 发表时间:
    2025-01-02
  • 期刊:
  • 影响因子:
    3.000
  • 作者:
    Ming Xue;Yue-Can Zeng
  • 通讯作者:
    Yue-Can Zeng
Differentiation of Acquired Immune Deficiency Syndrome Related Primary Central Nervous System Lymphoma from Cerebral toxoplasmosis with Use of Susceptibility-Weighted Imaging and Contrast Enhanced 3D-T1WI
  • DOI:
    10.1016/j.ijid.2021.10.023
  • 发表时间:
    2021-12-01
  • 期刊:
  • 影响因子:
  • 作者:
    Jingjing Li;Ming Xue;Zhibin Lv;Chunshuang Guan;Shunxing Huang;Shuo Li;Bo Liang;Xingang Zhou;Budong Chen;Ruming Xie
  • 通讯作者:
    Ruming Xie
Incorporating Diagnosed Intercept Parameters and the Graupel Category within the ARPS Cloud Analysis System for the Initialization of Double-Moment Microphysics: Testing with a Squall Line over South China
将诊断的截距参数和霰粒类别纳入 ARPS 云分析系统中以初始化双力矩微物理:用华南飑线进行测试
  • DOI:
    10.1175/mwr-d-15-0008.1
  • 发表时间:
    2016-01
  • 期刊:
  • 影响因子:
    3.2
  • 作者:
    Yujie Pan;Ming Xue;Guoqing Ge
  • 通讯作者:
    Guoqing Ge

Ming Xue的其他文献

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{{ truncateString('Ming Xue', 18)}}的其他基金

The Severe Hail Analysis, Representation, and Prediction (SHARP) Project
严重冰雹分析、表示和预测 (SHARP) 项目
  • 批准号:
    1261776
  • 财政年份:
    2013
  • 资助金额:
    $ 52.41万
  • 项目类别:
    Continuing Grant
Collaborative Research: Enabling Petascale Ensemble-Based Data Assimilation for the Numerical Analysis and Prediction of High-Impact Weather
合作研究:实现基于千万亿次集合的数据同化,以进行高影响天气的数值分析和预测
  • 批准号:
    0905040
  • 财政年份:
    2009
  • 资助金额:
    $ 52.41万
  • 项目类别:
    Standard Grant
Collaborative Research: CDI-Type II--Integrated Weather and Wildfire Simulation and Optimization for Wildfire Management
合作研究:CDI-Type II——天气与野火综合模拟及野火管理优化
  • 批准号:
    0941491
  • 财政年份:
    2009
  • 资助金额:
    $ 52.41万
  • 项目类别:
    Standard Grant
VORTEX2: A Study of Tornado and Tornadic Thunderstorm Dynamics through High-Resolution Simulation, Advanced Data Assimilation and Prediction
VORTEX2:通过高分辨率模拟、高级数据同化和预测研究龙卷风和龙卷风雷暴动力学
  • 批准号:
    0802888
  • 财政年份:
    2008
  • 资助金额:
    $ 52.41万
  • 项目类别:
    Continuing Grant
Storm-Scale Quantitative Precipitation Forecasting Using Advanced Data Assimilation Techniques: Methods, Impacts and Sensitivities
使用先进数据同化技术的风暴规模定量降水预报:方法、影响和敏感性
  • 批准号:
    0530814
  • 财政年份:
    2005
  • 资助金额:
    $ 52.41万
  • 项目类别:
    Continuing Grant
Optimal Utilization and Impact of Water Vapor and Other High Resolution Observations in Storm-Scale Quantitative Precipitation Forecasts (QPF)
水蒸气和其他高分辨率观测在风暴规模定量降水预报 (QPF) 中的优化利用和影响
  • 批准号:
    0129892
  • 财政年份:
    2002
  • 资助金额:
    $ 52.41万
  • 项目类别:
    Continuing Grant
A New Joint Weather Research and Prediction (WRF) Model
新的联合天气研究和预测 (WRF) 模型
  • 批准号:
    9909007
  • 财政年份:
    2000
  • 资助金额:
    $ 52.41万
  • 项目类别:
    Standard Grant

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