The Colorado State University Convective CLoud Outflows and UpDrafts Experiment (C³LOUD-Ex)
The intensity of deep convective storms is driven in part by the strength of their updrafts and cold pools. In spite of the importance of these storm features, they can be poorly represented within numerical models. This has been attributed to model parameterizations, grid resolution, and the lack o...
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| Published in: | Bulletin of the American Meteorological Society 2021-07, Vol.102 (7), p.E1283-E1305 |
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The Colorado State University Convective CLoud Outflows and UpDrafts Experiment (C³LOUD-Ex) |
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van den Heever, Susan C. Grant, Leah D. Freeman, Sean W. Marinescu, Peter J. Barnum, Julie Bukowski, Jennie Casas, Eleanor Drager, Aryeh J. Fuchs, Brody Herman, Gregory R. Hitchcock, Stacey M. Kennedy, Patrick C. Nielsen, Erik R. Park, J. Minnie Rasmussen, Kristen Razin, Muhammad Naufal Riesenberg, Ryan Dellaripa, Emily Riley Slocum, Christopher J. Toms, Benjamin A. van den Heever, Adrian |
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Cold Cold pools Convective clouds Convective storms Drone aircraft Environmental conditions Evaluation Mathematical models Modelling Numerical models Outflow Pools Precipitation Radar Radiosondes Resolution Spatial variations Storms Thunderstorms Updraft Velocity Wind shear |
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Bulletin of the American Meteorological Society, 2021-07, Vol.102 (7), p.E1283-E1305 |
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The intensity of deep convective storms is driven in part by the strength of their updrafts and cold pools. In spite of the importance of these storm features, they can be poorly represented within numerical models. This has been attributed to model parameterizations, grid resolution, and the lack of appropriate observations with which to evaluate such simulations. The overarching goal of the Colorado State University Convective CLoud Outflows and UpDrafts Experiment (C³LOUD-Ex) was to enhance our understanding of deep convective storm processes and their representation within numerical models. To address this goal, a field campaign was conducted during July 2016 and May–June 2017 over northeastern Colorado, southeastern Wyoming, and southwestern Nebraska. Pivotal to the experiment was a novel “Flying Curtain” strategy designed around simultaneously employing a fleet of uncrewed aerial systems (UAS; or drones), high-frequency radiosonde launches, and surface observations to obtain detailed measurements of the spatial and temporal heterogeneities of cold pools. Updraft velocities were observed using targeted radiosondes and radars. Extensive datasets were successfully collected for 16 cold pool–focused and seven updraft-focused case studies. The updraft characteristics for all seven supercell updraft cases are compared and provide a useful database for model evaluation. An overview of the 16 cold pools’ characteristics is presented, and an in-depth analysis of one of the cold pool cases suggests that spatial variations in cold pool properties occur on spatial scales from O(100) m through to O(1) km. Processes responsible for the cold pool observations are explored and support recent high-resolution modeling results. |
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Minnie ; Rasmussen, Kristen ; Razin, Muhammad Naufal ; Riesenberg, Ryan ; Dellaripa, Emily Riley ; Slocum, Christopher J. ; Toms, Benjamin A. ; van den Heever, Adrian</creator><creatorcontrib>van den Heever, Susan C. ; Grant, Leah D. ; Freeman, Sean W. ; Marinescu, Peter J. ; Barnum, Julie ; Bukowski, Jennie ; Casas, Eleanor ; Drager, Aryeh J. ; Fuchs, Brody ; Herman, Gregory R. ; Hitchcock, Stacey M. ; Kennedy, Patrick C. ; Nielsen, Erik R. ; Park, J. Minnie ; Rasmussen, Kristen ; Razin, Muhammad Naufal ; Riesenberg, Ryan ; Dellaripa, Emily Riley ; Slocum, Christopher J. ; Toms, Benjamin A. ; van den Heever, Adrian</creatorcontrib><description>The intensity of deep convective storms is driven in part by the strength of their updrafts and cold pools. In spite of the importance of these storm features, they can be poorly represented within numerical models. This has been attributed to model parameterizations, grid resolution, and the lack of appropriate observations with which to evaluate such simulations. The overarching goal of the Colorado State University Convective CLoud Outflows and UpDrafts Experiment (C³LOUD-Ex) was to enhance our understanding of deep convective storm processes and their representation within numerical models. To address this goal, a field campaign was conducted during July 2016 and May–June 2017 over northeastern Colorado, southeastern Wyoming, and southwestern Nebraska. Pivotal to the experiment was a novel “Flying Curtain” strategy designed around simultaneously employing a fleet of uncrewed aerial systems (UAS; or drones), high-frequency radiosonde launches, and surface observations to obtain detailed measurements of the spatial and temporal heterogeneities of cold pools. Updraft velocities were observed using targeted radiosondes and radars. Extensive datasets were successfully collected for 16 cold pool–focused and seven updraft-focused case studies. The updraft characteristics for all seven supercell updraft cases are compared and provide a useful database for model evaluation. An overview of the 16 cold pools’ characteristics is presented, and an in-depth analysis of one of the cold pool cases suggests that spatial variations in cold pool properties occur on spatial scales from O(100) m through to O(1) km. 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Minnie</creatorcontrib><creatorcontrib>Rasmussen, Kristen</creatorcontrib><creatorcontrib>Razin, Muhammad Naufal</creatorcontrib><creatorcontrib>Riesenberg, Ryan</creatorcontrib><creatorcontrib>Dellaripa, Emily Riley</creatorcontrib><creatorcontrib>Slocum, Christopher J.</creatorcontrib><creatorcontrib>Toms, Benjamin A.</creatorcontrib><creatorcontrib>van den Heever, Adrian</creatorcontrib><title>The Colorado State University Convective CLoud Outflows and UpDrafts Experiment (C³LOUD-Ex)</title><title>Bulletin of the American Meteorological Society</title><description>The intensity of deep convective storms is driven in part by the strength of their updrafts and cold pools. In spite of the importance of these storm features, they can be poorly represented within numerical models. This has been attributed to model parameterizations, grid resolution, and the lack of appropriate observations with which to evaluate such simulations. The overarching goal of the Colorado State University Convective CLoud Outflows and UpDrafts Experiment (C³LOUD-Ex) was to enhance our understanding of deep convective storm processes and their representation within numerical models. To address this goal, a field campaign was conducted during July 2016 and May–June 2017 over northeastern Colorado, southeastern Wyoming, and southwestern Nebraska. Pivotal to the experiment was a novel “Flying Curtain” strategy designed around simultaneously employing a fleet of uncrewed aerial systems (UAS; or drones), high-frequency radiosonde launches, and surface observations to obtain detailed measurements of the spatial and temporal heterogeneities of cold pools. Updraft velocities were observed using targeted radiosondes and radars. Extensive datasets were successfully collected for 16 cold pool–focused and seven updraft-focused case studies. The updraft characteristics for all seven supercell updraft cases are compared and provide a useful database for model evaluation. An overview of the 16 cold pools’ characteristics is presented, and an in-depth analysis of one of the cold pool cases suggests that spatial variations in cold pool properties occur on spatial scales from O(100) m through to O(1) km. Processes responsible for the cold pool observations are explored and support recent high-resolution modeling results.</description><subject>Cold</subject><subject>Cold pools</subject><subject>Convective clouds</subject><subject>Convective storms</subject><subject>Drone aircraft</subject><subject>Environmental conditions</subject><subject>Evaluation</subject><subject>Mathematical models</subject><subject>Modelling</subject><subject>Numerical models</subject><subject>Outflow</subject><subject>Pools</subject><subject>Precipitation</subject><subject>Radar</subject><subject>Radiosondes</subject><subject>Resolution</subject><subject>Spatial variations</subject><subject>Storms</subject><subject>Thunderstorms</subject><subject>Updraft</subject><subject>Velocity</subject><subject>Wind shear</subject><issn>0003-0007</issn><issn>1520-0477</issn><fulltext>false</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNo9UMtOwzAQtBBIlMKdC5IlLnBIWTtxnRwhKQ8pqIc2NyTLSRzRqsTBdkr7XfwBX4ajIi67mp3Z2dUgdElgQghndw_3r4sgC0gSAJBwQo7QiDAKAUScH6MRAISeAX6KzqxdDzCMyQi9Ld8VTvVGG1lrvHDSKVy0q60yduX2nmm3qnIe4zTXfY3nvWs2-sti2da46DIjG2fxbNcps_pQrcM36c93Pi-yYLa7PUcnjdxYdfHXx6h4nC3T5yCfP72k93lQ0YSTICEsrhitSBRRGvOwLFUDMaMMZMkI5zLmEsomqVjJFW9krYiKmrCEioWyjCsYo-uDb2f0Z6-sE2vdm9afFHTKo4QmQKlXwUFVGW2tUY3o_M_S7AUBMWQohgxFJkgihgz9eIyuDitr67T511NOgU99-QWAom35</recordid><startdate>20210701</startdate><enddate>20210701</enddate><creator>van den Heever, Susan C.</creator><creator>Grant, Leah D.</creator><creator>Freeman, Sean W.</creator><creator>Marinescu, Peter J.</creator><creator>Barnum, Julie</creator><creator>Bukowski, Jennie</creator><creator>Casas, Eleanor</creator><creator>Drager, Aryeh J.</creator><creator>Fuchs, Brody</creator><creator>Herman, Gregory R.</creator><creator>Hitchcock, Stacey M.</creator><creator>Kennedy, Patrick C.</creator><creator>Nielsen, Erik R.</creator><creator>Park, J. 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Minnie</creatorcontrib><creatorcontrib>Rasmussen, Kristen</creatorcontrib><creatorcontrib>Razin, Muhammad Naufal</creatorcontrib><creatorcontrib>Riesenberg, Ryan</creatorcontrib><creatorcontrib>Dellaripa, Emily Riley</creatorcontrib><creatorcontrib>Slocum, Christopher J.</creatorcontrib><creatorcontrib>Toms, Benjamin A.</creatorcontrib><creatorcontrib>van den Heever, Adrian</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Aqualine</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>STEM Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Database (1962 - current)</collection><collection>ProQuest Agriculture & Environmental Science Database</collection><collection>ProQuest Central Essentials</collection><collection>eLibrary</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>SciTech Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>ProQuest Research Library</collection><collection>ProQuest Science Journals</collection><collection>Research Library (Corporate)</collection><collection>ProQuest advanced technologies & aerospace journals</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Environmental Science Database</collection><collection>ProQuest Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>University of Michigan</collection><collection>SIRS Editorial</collection><jtitle>Bulletin of the American Meteorological Society</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>no_fulltext</fulltext></delivery><addata><au>van den Heever, Susan C.</au><au>Grant, Leah D.</au><au>Freeman, Sean W.</au><au>Marinescu, Peter J.</au><au>Barnum, Julie</au><au>Bukowski, Jennie</au><au>Casas, Eleanor</au><au>Drager, Aryeh J.</au><au>Fuchs, Brody</au><au>Herman, Gregory R.</au><au>Hitchcock, Stacey M.</au><au>Kennedy, Patrick C.</au><au>Nielsen, Erik R.</au><au>Park, J. Minnie</au><au>Rasmussen, Kristen</au><au>Razin, Muhammad Naufal</au><au>Riesenberg, Ryan</au><au>Dellaripa, Emily Riley</au><au>Slocum, Christopher J.</au><au>Toms, Benjamin A.</au><au>van den Heever, Adrian</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Colorado State University Convective CLoud Outflows and UpDrafts Experiment (C³LOUD-Ex)</atitle><jtitle>Bulletin of the American Meteorological Society</jtitle><date>2021-07-01</date><risdate>2021</risdate><volume>102</volume><issue>7</issue><spage>E1283</spage><epage>E1305</epage><pages>E1283-E1305</pages><issn>0003-0007</issn><eissn>1520-0477</eissn><abstract>The intensity of deep convective storms is driven in part by the strength of their updrafts and cold pools. In spite of the importance of these storm features, they can be poorly represented within numerical models. This has been attributed to model parameterizations, grid resolution, and the lack of appropriate observations with which to evaluate such simulations. The overarching goal of the Colorado State University Convective CLoud Outflows and UpDrafts Experiment (C³LOUD-Ex) was to enhance our understanding of deep convective storm processes and their representation within numerical models. To address this goal, a field campaign was conducted during July 2016 and May–June 2017 over northeastern Colorado, southeastern Wyoming, and southwestern Nebraska. Pivotal to the experiment was a novel “Flying Curtain” strategy designed around simultaneously employing a fleet of uncrewed aerial systems (UAS; or drones), high-frequency radiosonde launches, and surface observations to obtain detailed measurements of the spatial and temporal heterogeneities of cold pools. Updraft velocities were observed using targeted radiosondes and radars. Extensive datasets were successfully collected for 16 cold pool–focused and seven updraft-focused case studies. The updraft characteristics for all seven supercell updraft cases are compared and provide a useful database for model evaluation. An overview of the 16 cold pools’ characteristics is presented, and an in-depth analysis of one of the cold pool cases suggests that spatial variations in cold pool properties occur on spatial scales from O(100) m through to O(1) km. Processes responsible for the cold pool observations are explored and support recent high-resolution modeling results.</abstract><cop>Boston</cop><pub>American Meteorological Society</pub><doi>10.1175/BAMS-D-19-0013.1</doi><oa>free_for_read</oa></addata></record> |