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The Global Nature of Early‐Afternoon and Late‐Night Convection Through the Eyes of the A‐Train
Characterizing macrophysical properties of deep convective systems on a global scale is a precursor to understanding their influence on Earth's Energy Budget and Water Cycle. This study documents the properties of global convective objects (COs) in the early afternoon (1:30 p.m. local time; LT)...
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Published in: | Journal of geophysical research. Atmospheres 2022-07, Vol.127 (13), p.n/a |
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description | Characterizing macrophysical properties of deep convective systems on a global scale is a precursor to understanding their influence on Earth's Energy Budget and Water Cycle. This study documents the properties of global convective objects (COs) in the early afternoon (1:30 p.m. local time; LT) and overnight (1:30 a.m. LT) measurements from the A‐Train satellite constellation. CloudSat measurements are used to identify convective cores and establish their intensity, while other A‐Train data sets define cloud structure, storm spatial extent, rainfall yield, and radiative effects of each CO. Global distributions of storm characteristics are consistent with previous studies in which the most intense convection is located over tropical land, particularly over the Amazon and Congo Basin, while the largest COs occur over the Maritime Continent. Despite their limited twice‐daily sampling, A‐Train measurements capture that early afternoon convection over tropical land is both more intense and produces heavier rainfall than nighttime land‐based convection, while the day‐night differences are minimal over the tropical ocean. High‐resolution estimates of updraft cores reveal that CO size increases as the number of distinct cores in a CO increases owing to an increase in nonconvective rain and anvil cloud area. Convective objects generally cool the environment, which is strongest over the Northern Hemisphere midlatitudes, but cooling weakens as the nonconvective cloud fraction increases such that 30% of COs actually exert a net warming effect. These results suggest that A‐Train measurements may capture bulk connections between deep convective cloud features, precipitation, and radiative effects despite a lack of complete diurnal sampling.
Plain Language Summary
Storm clouds have a large impact on Earth's weather and climate. They produce a large fraction of global rainfall in short intense downpours and can both cool and warm the environment by reflecting sunlight and reducing emitted thermal radiation. Whether they cool or warm the atmosphere depends on cloud size and thickness as well as rainfall amount. These features impact the moisture and energy transfer within local and large‐scale environments, which influence weather patterns. Yet, it is difficult to represent the influences that storms have on a global scale in climate and weather forecasting models. This work provides a global perspective of early afternoon and late night storm signatures and their energy a |
doi_str_mv | 10.1029/2022JD036438 |
format | article |
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Plain Language Summary
Storm clouds have a large impact on Earth's weather and climate. They produce a large fraction of global rainfall in short intense downpours and can both cool and warm the environment by reflecting sunlight and reducing emitted thermal radiation. Whether they cool or warm the atmosphere depends on cloud size and thickness as well as rainfall amount. These features impact the moisture and energy transfer within local and large‐scale environments, which influence weather patterns. Yet, it is difficult to represent the influences that storms have on a global scale in climate and weather forecasting models. This work provides a global perspective of early afternoon and late night storm signatures and their energy and rainfall contributions. Using global satellite observations, storms are the strongest and produce the heaviest rainfall over tropical land during early afternoon, but they are the largest over tropical ocean. Storms generally cool the Earth at this time of day, but cooling weakens as the amount of nonraining cloud within the storm grows. This work may help improve storm representation in numerical models by connecting properties, such as the cloud size, strength, and frequency, to rain rates and energy output to better assess features that have the largest impact on weather and climate.
Key Points
The A‐Train observes several thousand convective objects (COs) to link cloud, rainfall, and radiative features despite limited diurnal sampling
Convection is the most intense over land, but the largest systems with the strongest radiative effects occur over tropical ocean
COs generally cool the tropics at 1:30 p.m./a.m. local time but this effect weakens as the number of embedded cores increases</description><identifier>ISSN: 2169-897X</identifier><identifier>EISSN: 2169-8996</identifier><identifier>DOI: 10.1029/2022JD036438</identifier><language>eng</language><publisher>Washington: Blackwell Publishing Ltd</publisher><subject>Anvil clouds ; Atmospheric models ; Carbon monoxide ; Climate ; Climate and weather ; Climate models ; Cloud structure ; Clouds ; Connecting ; Convection ; Convective clouds ; Convective systems ; Cooling ; Cores ; Earth ; Energy budget ; Energy output ; Energy transfer ; Geophysics ; Global precipitation ; Hydrologic cycle ; Hydrological cycle ; Mathematical models ; Moisture effects ; Night ; Northern Hemisphere ; Numerical models ; Oceans ; Rain ; Rainfall ; Rainfall amount ; Sampling ; Satellite constellations ; Satellite observation ; Satellites ; Storm clouds ; Storms ; Sunlight ; Thermal radiation ; Time of use ; Tropical climate ; Updraft ; Weather forecasting ; Weather patterns</subject><ispartof>Journal of geophysical research. Atmospheres, 2022-07, Vol.127 (13), p.n/a</ispartof><rights>2022. The Authors.</rights><rights>2022. This article is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3452-efc92f5aa3d568083ca809f6b73cca1ea5709647067f408fac54c392114311b33</citedby><cites>FETCH-LOGICAL-c3452-efc92f5aa3d568083ca809f6b73cca1ea5709647067f408fac54c392114311b33</cites><orcidid>0000-0002-7584-4836 ; 0000-0002-5293-9138</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,27905,27906</link.rule.ids></links><search><creatorcontrib>Pilewskie, J. A.</creatorcontrib><creatorcontrib>L’Ecuyer, T. S.</creatorcontrib><title>The Global Nature of Early‐Afternoon and Late‐Night Convection Through the Eyes of the A‐Train</title><title>Journal of geophysical research. Atmospheres</title><description>Characterizing macrophysical properties of deep convective systems on a global scale is a precursor to understanding their influence on Earth's Energy Budget and Water Cycle. This study documents the properties of global convective objects (COs) in the early afternoon (1:30 p.m. local time; LT) and overnight (1:30 a.m. LT) measurements from the A‐Train satellite constellation. CloudSat measurements are used to identify convective cores and establish their intensity, while other A‐Train data sets define cloud structure, storm spatial extent, rainfall yield, and radiative effects of each CO. Global distributions of storm characteristics are consistent with previous studies in which the most intense convection is located over tropical land, particularly over the Amazon and Congo Basin, while the largest COs occur over the Maritime Continent. Despite their limited twice‐daily sampling, A‐Train measurements capture that early afternoon convection over tropical land is both more intense and produces heavier rainfall than nighttime land‐based convection, while the day‐night differences are minimal over the tropical ocean. High‐resolution estimates of updraft cores reveal that CO size increases as the number of distinct cores in a CO increases owing to an increase in nonconvective rain and anvil cloud area. Convective objects generally cool the environment, which is strongest over the Northern Hemisphere midlatitudes, but cooling weakens as the nonconvective cloud fraction increases such that 30% of COs actually exert a net warming effect. These results suggest that A‐Train measurements may capture bulk connections between deep convective cloud features, precipitation, and radiative effects despite a lack of complete diurnal sampling.
Plain Language Summary
Storm clouds have a large impact on Earth's weather and climate. They produce a large fraction of global rainfall in short intense downpours and can both cool and warm the environment by reflecting sunlight and reducing emitted thermal radiation. Whether they cool or warm the atmosphere depends on cloud size and thickness as well as rainfall amount. These features impact the moisture and energy transfer within local and large‐scale environments, which influence weather patterns. Yet, it is difficult to represent the influences that storms have on a global scale in climate and weather forecasting models. This work provides a global perspective of early afternoon and late night storm signatures and their energy and rainfall contributions. Using global satellite observations, storms are the strongest and produce the heaviest rainfall over tropical land during early afternoon, but they are the largest over tropical ocean. Storms generally cool the Earth at this time of day, but cooling weakens as the amount of nonraining cloud within the storm grows. This work may help improve storm representation in numerical models by connecting properties, such as the cloud size, strength, and frequency, to rain rates and energy output to better assess features that have the largest impact on weather and climate.
Key Points
The A‐Train observes several thousand convective objects (COs) to link cloud, rainfall, and radiative features despite limited diurnal sampling
Convection is the most intense over land, but the largest systems with the strongest radiative effects occur over tropical ocean
COs generally cool the tropics at 1:30 p.m./a.m. local time but this effect weakens as the number of embedded cores increases</description><subject>Anvil clouds</subject><subject>Atmospheric models</subject><subject>Carbon monoxide</subject><subject>Climate</subject><subject>Climate and weather</subject><subject>Climate models</subject><subject>Cloud structure</subject><subject>Clouds</subject><subject>Connecting</subject><subject>Convection</subject><subject>Convective clouds</subject><subject>Convective systems</subject><subject>Cooling</subject><subject>Cores</subject><subject>Earth</subject><subject>Energy budget</subject><subject>Energy output</subject><subject>Energy transfer</subject><subject>Geophysics</subject><subject>Global precipitation</subject><subject>Hydrologic cycle</subject><subject>Hydrological cycle</subject><subject>Mathematical models</subject><subject>Moisture effects</subject><subject>Night</subject><subject>Northern Hemisphere</subject><subject>Numerical models</subject><subject>Oceans</subject><subject>Rain</subject><subject>Rainfall</subject><subject>Rainfall amount</subject><subject>Sampling</subject><subject>Satellite constellations</subject><subject>Satellite observation</subject><subject>Satellites</subject><subject>Storm clouds</subject><subject>Storms</subject><subject>Sunlight</subject><subject>Thermal radiation</subject><subject>Time of use</subject><subject>Tropical climate</subject><subject>Updraft</subject><subject>Weather forecasting</subject><subject>Weather patterns</subject><issn>2169-897X</issn><issn>2169-8996</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><recordid>eNp9kM9KAzEQxoMoWLQ3HyDg1dX82WSTY2lrtZQKsoK3kKZJd8u6qdldZW8-gs_ok5hSEU8ODDPM_Phm-AC4wOgaIyJvCCJkPkGUp1QcgQHBXCZCSn7822fPp2DYNFsUQyCasnQA1nlh4azyK13BpW67YKF3cKpD1X99fI5ca0PtfQ11vYYL3do4XJabooVjX79Z05ZxlxfBd5sCtlFq2ttmr7DvRxHOgy7rc3DidNXY4U89A0-303x8lyweZvfj0SIx8RmSWGckcUxrumZcIEGNFkg6vsqoMRpbzTIkeZohnrkUCacNSw2VBOOUYryi9AxcHnR3wb92tmnV1nehjicV4UIwmcWM1NWBMsE3TbBO7UL5okOvMFJ7K9VfKyNOD_h7Wdn-X1bNZ48TFq0l9BtxXXX-</recordid><startdate>20220716</startdate><enddate>20220716</enddate><creator>Pilewskie, J. A.</creator><creator>L’Ecuyer, T. S.</creator><general>Blackwell Publishing Ltd</general><scope>24P</scope><scope>WIN</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H8D</scope><scope>H96</scope><scope>KL.</scope><scope>KR7</scope><scope>L.G</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0002-7584-4836</orcidid><orcidid>https://orcid.org/0000-0002-5293-9138</orcidid></search><sort><creationdate>20220716</creationdate><title>The Global Nature of Early‐Afternoon and Late‐Night Convection Through the Eyes of the A‐Train</title><author>Pilewskie, J. A. ; L’Ecuyer, T. S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3452-efc92f5aa3d568083ca809f6b73cca1ea5709647067f408fac54c392114311b33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Anvil clouds</topic><topic>Atmospheric models</topic><topic>Carbon monoxide</topic><topic>Climate</topic><topic>Climate and weather</topic><topic>Climate models</topic><topic>Cloud structure</topic><topic>Clouds</topic><topic>Connecting</topic><topic>Convection</topic><topic>Convective clouds</topic><topic>Convective systems</topic><topic>Cooling</topic><topic>Cores</topic><topic>Earth</topic><topic>Energy budget</topic><topic>Energy output</topic><topic>Energy transfer</topic><topic>Geophysics</topic><topic>Global precipitation</topic><topic>Hydrologic cycle</topic><topic>Hydrological cycle</topic><topic>Mathematical models</topic><topic>Moisture effects</topic><topic>Night</topic><topic>Northern Hemisphere</topic><topic>Numerical models</topic><topic>Oceans</topic><topic>Rain</topic><topic>Rainfall</topic><topic>Rainfall amount</topic><topic>Sampling</topic><topic>Satellite constellations</topic><topic>Satellite observation</topic><topic>Satellites</topic><topic>Storm clouds</topic><topic>Storms</topic><topic>Sunlight</topic><topic>Thermal radiation</topic><topic>Time of use</topic><topic>Tropical climate</topic><topic>Updraft</topic><topic>Weather forecasting</topic><topic>Weather patterns</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pilewskie, J. A.</creatorcontrib><creatorcontrib>L’Ecuyer, T. S.</creatorcontrib><collection>Wiley Open Access Journals</collection><collection>Wiley Online Library Open Access</collection><collection>CrossRef</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Journal of geophysical research. Atmospheres</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pilewskie, J. A.</au><au>L’Ecuyer, T. S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Global Nature of Early‐Afternoon and Late‐Night Convection Through the Eyes of the A‐Train</atitle><jtitle>Journal of geophysical research. Atmospheres</jtitle><date>2022-07-16</date><risdate>2022</risdate><volume>127</volume><issue>13</issue><epage>n/a</epage><issn>2169-897X</issn><eissn>2169-8996</eissn><abstract>Characterizing macrophysical properties of deep convective systems on a global scale is a precursor to understanding their influence on Earth's Energy Budget and Water Cycle. This study documents the properties of global convective objects (COs) in the early afternoon (1:30 p.m. local time; LT) and overnight (1:30 a.m. LT) measurements from the A‐Train satellite constellation. CloudSat measurements are used to identify convective cores and establish their intensity, while other A‐Train data sets define cloud structure, storm spatial extent, rainfall yield, and radiative effects of each CO. Global distributions of storm characteristics are consistent with previous studies in which the most intense convection is located over tropical land, particularly over the Amazon and Congo Basin, while the largest COs occur over the Maritime Continent. Despite their limited twice‐daily sampling, A‐Train measurements capture that early afternoon convection over tropical land is both more intense and produces heavier rainfall than nighttime land‐based convection, while the day‐night differences are minimal over the tropical ocean. High‐resolution estimates of updraft cores reveal that CO size increases as the number of distinct cores in a CO increases owing to an increase in nonconvective rain and anvil cloud area. Convective objects generally cool the environment, which is strongest over the Northern Hemisphere midlatitudes, but cooling weakens as the nonconvective cloud fraction increases such that 30% of COs actually exert a net warming effect. These results suggest that A‐Train measurements may capture bulk connections between deep convective cloud features, precipitation, and radiative effects despite a lack of complete diurnal sampling.
Plain Language Summary
Storm clouds have a large impact on Earth's weather and climate. They produce a large fraction of global rainfall in short intense downpours and can both cool and warm the environment by reflecting sunlight and reducing emitted thermal radiation. Whether they cool or warm the atmosphere depends on cloud size and thickness as well as rainfall amount. These features impact the moisture and energy transfer within local and large‐scale environments, which influence weather patterns. Yet, it is difficult to represent the influences that storms have on a global scale in climate and weather forecasting models. This work provides a global perspective of early afternoon and late night storm signatures and their energy and rainfall contributions. Using global satellite observations, storms are the strongest and produce the heaviest rainfall over tropical land during early afternoon, but they are the largest over tropical ocean. Storms generally cool the Earth at this time of day, but cooling weakens as the amount of nonraining cloud within the storm grows. This work may help improve storm representation in numerical models by connecting properties, such as the cloud size, strength, and frequency, to rain rates and energy output to better assess features that have the largest impact on weather and climate.
Key Points
The A‐Train observes several thousand convective objects (COs) to link cloud, rainfall, and radiative features despite limited diurnal sampling
Convection is the most intense over land, but the largest systems with the strongest radiative effects occur over tropical ocean
COs generally cool the tropics at 1:30 p.m./a.m. local time but this effect weakens as the number of embedded cores increases</abstract><cop>Washington</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1029/2022JD036438</doi><tpages>20</tpages><orcidid>https://orcid.org/0000-0002-7584-4836</orcidid><orcidid>https://orcid.org/0000-0002-5293-9138</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Anvil clouds Atmospheric models Carbon monoxide Climate Climate and weather Climate models Cloud structure Clouds Connecting Convection Convective clouds Convective systems Cooling Cores Earth Energy budget Energy output Energy transfer Geophysics Global precipitation Hydrologic cycle Hydrological cycle Mathematical models Moisture effects Night Northern Hemisphere Numerical models Oceans Rain Rainfall Rainfall amount Sampling Satellite constellations Satellite observation Satellites Storm clouds Storms Sunlight Thermal radiation Time of use Tropical climate Updraft Weather forecasting Weather patterns |
title | The Global Nature of Early‐Afternoon and Late‐Night Convection Through the Eyes of the A‐Train |
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