Exploiting Synergies between Remote Sensing and in Situ Measurements during ICE-T to Better Understand Ice Generation in Tropical Clouds

利用 ICE-T 期间遥感和现场测量之间的协同作用,更好地了解热带云中的冰生成

基本信息

  • 批准号:
    1034858
  • 负责人:
  • 金额:
    $ 53.81万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2011
  • 资助国家:
    美国
  • 起止时间:
    2011-01-01 至 2014-12-31
  • 项目状态:
    已结题

项目摘要

Despite longstanding recognition of the importance of ice nucleation and multiplication processes in clouds, both for precipitation processes as well as for the radiative impact of clouds on global climate, our understanding of heterogeneous ice nucleation mechanisms and the relevance of ice multiplication processes remains limited. The gaps in our understanding of ice formation processes hinder parameterization of ice initiation processes in numerical simulations of clouds, thus leading to uncertainties in cloud radiative properties and precipitation simulated in numerical models.The Ice in Clouds Experiments (ICE) are a series of field campaigns investigating ice nucleation in clouds in a range of different conditions, taking advantage of improvements in observational capabilities including improved in situ probes and airborne Doppler radar and lidar. ICE-Tropical (ICE-T), will investigate ice formation in shallow, convective clouds over the eastern Caribbean.Intellectual merits. The Wyoming Cloud Radar (WCR), together with upward- anddownward-looking versions of the Wyoming Cloud Lidar (WCL) will be flown on the NSF (National Science Foundation)/NCAR (National Center for Atmospheric Research)C-130 aircraft during ICE-T and will be used to observe ice occurrence within cloud.This research will help understanding the relationship between cloud-dynamics andmicrophysical processes. Lidar backscatter and depolarization measurements will be used in conjunction with the PCASP (Passive Cavity Aerosol Spectrometer Probe) and FSSP-300 (Forward Scattering Spectrometer Probe) measurements to identify aerosol distributions and dust layers. The effect of dust on ice formation in clouds will be examined by contrasting ice formation and development in clouds under dusty vs. non-dusty conditions.The dual-Doppler capability of the WCR will be used to investigate how ice is transported inside cloud, and explore the link between cloud dynamics and iceinitiation/multiplication. The combination of WCR and WCL will allow the reflectivity and velocity fields observed by the radar to be unambiguously linked to the boundaries ofthe mixed-phase region.Broader impacts. Radar, lidar, and in situ aerosol data collected during thisinvestigation will facilitate analyses conducted by other ICE-T investigators. A graduatestudent will participate in the ICE-T field campaign and data analysis phase. Data dissemination and other broader outreach efforts will also be carried out through various phases of this project. Finally, an improved understanding of ice nucleation andmultiplication mechanisms in the atmosphere will lead to improved parameterizations ofice processes in numerical models, in turn lead to a better cloud simulations in globalclimate models.
尽管长期以来认识到冰核和云中乘法过程的重要性,但对于降水过程以及云对云对全球气候的辐射影响,我们对异质冰核机制的理解以及冰乘过程的相关性仍然有限。我们对冰形成过程的理解的差距阻碍了云的数值模拟中冰开始过程的参数化,从而导致云辐射性能的不确定性和数值模型中模拟的云层模拟。云实验中的冰(ICE)是一系列在范围内的云层型在范围内的领域,这些领域是一系列领域的范围,该领域的范围是在范围内的范围,利用了范围的范围。多普勒雷达和激光雷达。冰 - 热带(ICE-T)将调查在加勒比东部的浅色云层中的冰形成。怀俄明州的云雷达(WCR)以及怀俄明州云激光雷达(WCL)的向上和下去的版本将在NSF(国家科学基金会)/NCAR(国家大气研究中心)C-130飞机中飞行,并将在ICE-T期间使用,并将在云中观察到ICE的研究。 LIDAR的反向散射和去极化测量将与PCASP(被动腔气雾剂光谱仪探针)和FSSP-300(正向散射光谱仪探针)测量一起使用,以识别气溶胶分布和防尘层。将通过将灰尘形成和在尘土飞扬的条件下与云层的形成和云中的发育进行对比,将检查灰尘对云中的冰形成的影响。WCR的双多普勒能力将用于研究如何在云中运输冰,并探索云动力学和冰融合/乘法/乘法之间的链接。 WCR和WCL的组合将允许雷达观察到的反射率和速度场与混合相区域的边界明确链接。在此期间收集的雷达,激光雷达和原位气溶胶数据将有助于其他ICE-T研究者进行的分析。毕业生将参加ICE-T现场活动和数据分析阶段。数据传播和其他更广泛的推广工作也将通过该项目的各个阶段进行。最后,对大气中的冰核和发光机制的了解将导致数值模型中的质疑过程的参数化改善,进而导致在全球气候模型中获得更好的云模拟。

项目成果

期刊论文数量(4)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Time-dependent freezing rate parcel model
  • DOI:
    10.5194/acp-15-2071-2015
  • 发表时间:
    2014-11
  • 期刊:
  • 影响因子:
    6.3
  • 作者:
    G. Vali;J. Snider
  • 通讯作者:
    G. Vali;J. Snider
Integrating laboratory and field data to quantify the immersion freezing ice nucleation activity of mineral dust particles
  • DOI:
    10.5194/acp-15-393-2015
  • 发表时间:
    2015-01-01
  • 期刊:
  • 影响因子:
    6.3
  • 作者:
    DeMott, P. J.;Prenni, A. J.;Kreidenweis, S. M.
  • 通讯作者:
    Kreidenweis, S. M.
Calibration of the passive cavity aerosol spectrometer probe for airborne determination of the size distribution
  • DOI:
    10.5194/amt-6-2349-2013
  • 发表时间:
    2013-01-01
  • 期刊:
  • 影响因子:
    3.8
  • 作者:
    Cai, Y.;Snider, J. R.;Wechsler, P.
  • 通讯作者:
    Wechsler, P.
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Zhien Wang其他文献

Anvil Productivities of Tropical Deep Convective Clusters and Their Regional Differences
热带深对流星团的砧生产力及其区域差异
LIDAR and RADAR Observations
激光雷达和雷达观测
  • DOI:
  • 发表时间:
    2013
  • 期刊:
  • 影响因子:
    0
  • 作者:
    J. Pelon;G. Vali;G. Ancellet;G. Ehret;P. Flamant;S. Haimov;G. Heymsfield;D. Leon;J. Mead;A. Pazmany;A. Protat;Zhien Wang;M. Wolde
  • 通讯作者:
    M. Wolde
Association of Antarctic polar stratospheric cloud formation on tropospheric cloud systems
南极极地平流层云形成与对流层云系统的关联
  • DOI:
  • 发表时间:
    2008
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Zhien Wang;G. Stephens;T. Deshler;C. Trepte;T. Parish;D. Vane;D. Winker;Dong Liu;L. Adhikari
  • 通讯作者:
    L. Adhikari
Improved tropical deep convective cloud detection using MODIS observations with an active sensor trained machine learning algorithm
使用 MODIS 观测和主动传感器训练的机器学习算法改进热带深对流云检测
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    13.5
  • 作者:
    Kang Yang;Zhien Wang;M. Deng;Brennan Dettmann
  • 通讯作者:
    Brennan Dettmann
Intercomparison of model simulations of mixed‐phase clouds observed during the ARM Mixed‐Phase Arctic Cloud Experiment. II: Multilayer cloud
ARM 混合相北极云实验 II:多层云期间观测到的混合相云模型模拟的相互比较。
  • DOI:
    10.1002/qj.415
  • 发表时间:
    2008
  • 期刊:
  • 影响因子:
    8.9
  • 作者:
    H. Morrison;R. McCoy;S. Klein;S. Xie;Yali Luo;A. Avramov;Mingxuan Chen;J. Cole;M. Falk;M. Foster;A. D. Del Genio;J. Harrington;C. Hoose;M. Khairoutdinov;V. Larson;Xiaohong Liu;G. McFarquhar;M. Poellot;K. von Salzen;B. Shipway;M. Shupe;Y. Sud;D. Turner;D. Veron;G. Walker;Zhien Wang;Audrey B. Wolf;Kuan Xu;Fanglin Yang;Gong Zhang
  • 通讯作者:
    Gong Zhang

Zhien Wang的其他文献

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{{ truncateString('Zhien Wang', 18)}}的其他基金

CAESAR: Characterizing and Understanding Atmospheric Boundary Layer Fluxes, Structure and Cloud Property Evolution in Arctic Cold Air Outbreaks
CAESAR:描述和理解北极冷空气爆发时的大气边界层通量、结构和云特性演化
  • 批准号:
    2151075
  • 财政年份:
    2023
  • 资助金额:
    $ 53.81万
  • 项目类别:
    Continuing Grant
Collaborative Research: Sundowner Winds EXperiment (SWEX) in Santa Barbara, California
合作研究:加利福尼亚州圣巴巴拉的日落风实验 (SWEX)
  • 批准号:
    1921596
  • 财政年份:
    2020
  • 资助金额:
    $ 53.81万
  • 项目类别:
    Standard Grant
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
  • 批准号:
    1917693
  • 财政年份:
    2019
  • 资助金额:
    $ 53.81万
  • 项目类别:
    Standard Grant
MRI: Development of a Multi-function Airborne Raman Lidar for Atmospheric Process Studies
MRI:开发用于大气过程研究的多功能机载拉曼激光雷达
  • 批准号:
    1337599
  • 财政年份:
    2013
  • 资助金额:
    $ 53.81万
  • 项目类别:
    Standard Grant
Collaborative Research: Colorado Airborne Multi-Phase Cloud Study (CAMPS)
合作研究:科罗拉多机载多相云研究 (CAMPS)
  • 批准号:
    0964184
  • 财政年份:
    2010
  • 资助金额:
    $ 53.81万
  • 项目类别:
    Continuing Grant
CAREER: Developing New Airborne Cloud, Aerosol and Water Vapor Observation Capabilities by Synergizing Remote Sensors and in Situ Probes on the University of Wyoming King Air
职业:通过协同怀俄明大学国王航空的远程传感器和原位探测器开发新的机载云、气溶胶和水蒸气观测能力
  • 批准号:
    0645644
  • 财政年份:
    2007
  • 资助金额:
    $ 53.81万
  • 项目类别:
    Continuing Grant

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