Evaluating and improving cloud phase in the Community Atmosphere Model version 5 using spaceborne lidar observations
Spaceborne lidar observations from the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite are used to evaluate cloud amount and cloud phase in the Community Atmosphere Model version 5 (CAM5), the atmospheric component of a widely used state‐of‐the‐art global couple...
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Veröffentlicht in: | Journal of geophysical research. Atmospheres 2016-04, Vol.121 (8), p.4162-4176 |
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creator | Kay, Jennifer E. Bourdages, Line Miller, Nathaniel B. Morrison, Ariel Yettella, Vineel Chepfer, Helene Eaton, Brian |
description | Spaceborne lidar observations from the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite are used to evaluate cloud amount and cloud phase in the Community Atmosphere Model version 5 (CAM5), the atmospheric component of a widely used state‐of‐the‐art global coupled climate model (Community Earth System Model). By embedding a lidar simulator within CAM5, the idiosyncrasies of spaceborne lidar cloud detection and phase assignment are replicated. As a result, this study makes scale‐aware and definition‐aware comparisons between model‐simulated and observed cloud amount and cloud phase. In the global mean, CAM5 has insufficient liquid cloud and excessive ice cloud when compared to CALIPSO observations. Over the ice‐covered Arctic Ocean, CAM5 has insufficient liquid cloud in all seasons. Having important implications for projections of future sea level rise, a liquid cloud deficit contributes to a cold bias of 2–3°C for summer daily maximum near‐surface air temperatures at Summit, Greenland. Over the midlatitude storm tracks, CAM5 has excessive ice cloud and insufficient liquid cloud. Storm track cloud phase biases in CAM5 maximize over the Southern Ocean, which also has larger‐than‐observed seasonal variations in cloud phase. Physical parameter modifications reduce the Southern Ocean cloud phase and shortwave radiation biases in CAM5 and illustrate the power of the CALIPSO observations as an observational constraint. The results also highlight the importance of using a regime‐based, as opposed to a geographic‐based, model evaluation approach. More generally, the results demonstrate the importance and value of simulator‐enabled comparisons of cloud phase in models used for future climate projection.
Key Points
Scale‐aware and definition‐aware cloud phase evaluation now publicly available in CAM
When compared to lidar observations, CAM5 has excessive ice cloud and insufficient liquid cloud
Increasing supercooled liquid cloud reduces shortwave absorption bias, especially over Southern Ocean |
doi_str_mv | 10.1002/2015JD024699 |
format | Article |
fullrecord | <record><control><sourceid>proquest_hal_p</sourceid><recordid>TN_cdi_hal_primary_oai_HAL_insu_03727113v1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1794498821</sourcerecordid><originalsourceid>FETCH-LOGICAL-c5401-422194103e29df5dd4cb744a5e8a005c2d723b0f3b35608854d82d3da5babf5f3</originalsourceid><addsrcrecordid>eNqF0t2L1DAQAPAiCh539-YfEPBFxNV8tsnjsnfeByuCKPgW0mbq5kiTmrSV_e9NWTnEhzMvycAvM8wwVfWK4PcEY_qBYiLurzDltVLPqjNKarWRStXPH9_N95fVZc4PuByJGRf8rJquF-NnM7nwA5lgkRvGFJc16nycLRoPJgNyAU0HQLs4DHNw0xFtpyHm8QAJ0KdowaMFUnYxIIHmvP7Oo-mgjSkA8s6ahGKbIS2lUAz5onrRG5_h8s99Xn37eP11d7vZf7652233m05wTDacUqI4wQyosr2wlndtw7kRIA3GoqO2oazFPWuZqLGUgltJLbNGtKbtRc_Oq7envAfj9ZjcYNJRR-P07XavXcizxqyhDSFsIQW_OeEygJ8z5EkPLnfgvQkQ56yJJKUIE7j-P20U50pKumZ9_Q99iHMKpWtNeWlPUcHqpxRppKKyJmRV706qSzHnBP1jTwTrdQf03ztQODvxX87D8Umr72--XAmqyiR-A_kUsKM</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1789286116</pqid></control><display><type>article</type><title>Evaluating and improving cloud phase in the Community Atmosphere Model version 5 using spaceborne lidar observations</title><source>Wiley Free Content</source><source>Wiley Online Library Journals Frontfile Complete</source><source>Alma/SFX Local Collection</source><creator>Kay, Jennifer E. ; Bourdages, Line ; Miller, Nathaniel B. ; Morrison, Ariel ; Yettella, Vineel ; Chepfer, Helene ; Eaton, Brian</creator><creatorcontrib>Kay, Jennifer E. ; Bourdages, Line ; Miller, Nathaniel B. ; Morrison, Ariel ; Yettella, Vineel ; Chepfer, Helene ; Eaton, Brian</creatorcontrib><description>Spaceborne lidar observations from the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite are used to evaluate cloud amount and cloud phase in the Community Atmosphere Model version 5 (CAM5), the atmospheric component of a widely used state‐of‐the‐art global coupled climate model (Community Earth System Model). By embedding a lidar simulator within CAM5, the idiosyncrasies of spaceborne lidar cloud detection and phase assignment are replicated. As a result, this study makes scale‐aware and definition‐aware comparisons between model‐simulated and observed cloud amount and cloud phase. In the global mean, CAM5 has insufficient liquid cloud and excessive ice cloud when compared to CALIPSO observations. Over the ice‐covered Arctic Ocean, CAM5 has insufficient liquid cloud in all seasons. Having important implications for projections of future sea level rise, a liquid cloud deficit contributes to a cold bias of 2–3°C for summer daily maximum near‐surface air temperatures at Summit, Greenland. Over the midlatitude storm tracks, CAM5 has excessive ice cloud and insufficient liquid cloud. Storm track cloud phase biases in CAM5 maximize over the Southern Ocean, which also has larger‐than‐observed seasonal variations in cloud phase. Physical parameter modifications reduce the Southern Ocean cloud phase and shortwave radiation biases in CAM5 and illustrate the power of the CALIPSO observations as an observational constraint. The results also highlight the importance of using a regime‐based, as opposed to a geographic‐based, model evaluation approach. More generally, the results demonstrate the importance and value of simulator‐enabled comparisons of cloud phase in models used for future climate projection.
Key Points
Scale‐aware and definition‐aware cloud phase evaluation now publicly available in CAM
When compared to lidar observations, CAM5 has excessive ice cloud and insufficient liquid cloud
Increasing supercooled liquid cloud reduces shortwave absorption bias, especially over Southern Ocean</description><identifier>ISSN: 2169-897X</identifier><identifier>EISSN: 2169-8996</identifier><identifier>DOI: 10.1002/2015JD024699</identifier><language>eng</language><publisher>Washington: Blackwell Publishing Ltd</publisher><subject>Air temperature ; Atmosphere ; Atmospheres ; Atmospheric models ; Brackish ; CALIPSO (Pathfinder satellite) ; Climate ; climate model ; Climate models ; Cloud amount ; Cloud detection ; cloud phase ; Clouds ; Communities ; Computer simulation ; Embedded systems ; Embedding ; Future climates ; Geophysics ; Global climate ; Greenland ; Ice ; Ice clouds ; Ice cover ; Lidar ; Liquids ; Marine ; Meteorological satellites ; Meteorology ; Ocean-atmosphere interaction ; Oceans ; Parameter modification ; Phase assignment ; Physical properties ; Radiation ; Satellite observation ; Satellites ; Sciences of the Universe ; Sea level ; Sea level rise ; Seasonal variation ; Seasonal variations ; Short wave radiation ; Simulators ; Southern Ocean ; Spaceborne lidar ; Storm tracks ; Storms ; supercooled liquid clouds ; Surface temperature ; Surface-air temperature relationships ; Tracks (paths)</subject><ispartof>Journal of geophysical research. Atmospheres, 2016-04, Vol.121 (8), p.4162-4176</ispartof><rights>2016. American Geophysical Union. All Rights Reserved.</rights><rights>Copyright</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5401-422194103e29df5dd4cb744a5e8a005c2d723b0f3b35608854d82d3da5babf5f3</citedby><cites>FETCH-LOGICAL-c5401-422194103e29df5dd4cb744a5e8a005c2d723b0f3b35608854d82d3da5babf5f3</cites><orcidid>0000-0002-3571-2185</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2F2015JD024699$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2F2015JD024699$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>230,314,776,780,881,1411,1427,27901,27902,45550,45551,46384,46808</link.rule.ids><backlink>$$Uhttps://insu.hal.science/insu-03727113$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Kay, Jennifer E.</creatorcontrib><creatorcontrib>Bourdages, Line</creatorcontrib><creatorcontrib>Miller, Nathaniel B.</creatorcontrib><creatorcontrib>Morrison, Ariel</creatorcontrib><creatorcontrib>Yettella, Vineel</creatorcontrib><creatorcontrib>Chepfer, Helene</creatorcontrib><creatorcontrib>Eaton, Brian</creatorcontrib><title>Evaluating and improving cloud phase in the Community Atmosphere Model version 5 using spaceborne lidar observations</title><title>Journal of geophysical research. Atmospheres</title><description>Spaceborne lidar observations from the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite are used to evaluate cloud amount and cloud phase in the Community Atmosphere Model version 5 (CAM5), the atmospheric component of a widely used state‐of‐the‐art global coupled climate model (Community Earth System Model). By embedding a lidar simulator within CAM5, the idiosyncrasies of spaceborne lidar cloud detection and phase assignment are replicated. As a result, this study makes scale‐aware and definition‐aware comparisons between model‐simulated and observed cloud amount and cloud phase. In the global mean, CAM5 has insufficient liquid cloud and excessive ice cloud when compared to CALIPSO observations. Over the ice‐covered Arctic Ocean, CAM5 has insufficient liquid cloud in all seasons. Having important implications for projections of future sea level rise, a liquid cloud deficit contributes to a cold bias of 2–3°C for summer daily maximum near‐surface air temperatures at Summit, Greenland. Over the midlatitude storm tracks, CAM5 has excessive ice cloud and insufficient liquid cloud. Storm track cloud phase biases in CAM5 maximize over the Southern Ocean, which also has larger‐than‐observed seasonal variations in cloud phase. Physical parameter modifications reduce the Southern Ocean cloud phase and shortwave radiation biases in CAM5 and illustrate the power of the CALIPSO observations as an observational constraint. The results also highlight the importance of using a regime‐based, as opposed to a geographic‐based, model evaluation approach. More generally, the results demonstrate the importance and value of simulator‐enabled comparisons of cloud phase in models used for future climate projection.
Key Points
Scale‐aware and definition‐aware cloud phase evaluation now publicly available in CAM
When compared to lidar observations, CAM5 has excessive ice cloud and insufficient liquid cloud
Increasing supercooled liquid cloud reduces shortwave absorption bias, especially over Southern Ocean</description><subject>Air temperature</subject><subject>Atmosphere</subject><subject>Atmospheres</subject><subject>Atmospheric models</subject><subject>Brackish</subject><subject>CALIPSO (Pathfinder satellite)</subject><subject>Climate</subject><subject>climate model</subject><subject>Climate models</subject><subject>Cloud amount</subject><subject>Cloud detection</subject><subject>cloud phase</subject><subject>Clouds</subject><subject>Communities</subject><subject>Computer simulation</subject><subject>Embedded systems</subject><subject>Embedding</subject><subject>Future climates</subject><subject>Geophysics</subject><subject>Global climate</subject><subject>Greenland</subject><subject>Ice</subject><subject>Ice clouds</subject><subject>Ice cover</subject><subject>Lidar</subject><subject>Liquids</subject><subject>Marine</subject><subject>Meteorological satellites</subject><subject>Meteorology</subject><subject>Ocean-atmosphere interaction</subject><subject>Oceans</subject><subject>Parameter modification</subject><subject>Phase assignment</subject><subject>Physical properties</subject><subject>Radiation</subject><subject>Satellite observation</subject><subject>Satellites</subject><subject>Sciences of the Universe</subject><subject>Sea level</subject><subject>Sea level rise</subject><subject>Seasonal variation</subject><subject>Seasonal variations</subject><subject>Short wave radiation</subject><subject>Simulators</subject><subject>Southern Ocean</subject><subject>Spaceborne lidar</subject><subject>Storm tracks</subject><subject>Storms</subject><subject>supercooled liquid clouds</subject><subject>Surface temperature</subject><subject>Surface-air temperature relationships</subject><subject>Tracks (paths)</subject><issn>2169-897X</issn><issn>2169-8996</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNqF0t2L1DAQAPAiCh539-YfEPBFxNV8tsnjsnfeByuCKPgW0mbq5kiTmrSV_e9NWTnEhzMvycAvM8wwVfWK4PcEY_qBYiLurzDltVLPqjNKarWRStXPH9_N95fVZc4PuByJGRf8rJquF-NnM7nwA5lgkRvGFJc16nycLRoPJgNyAU0HQLs4DHNw0xFtpyHm8QAJ0KdowaMFUnYxIIHmvP7Oo-mgjSkA8s6ahGKbIS2lUAz5onrRG5_h8s99Xn37eP11d7vZf7652233m05wTDacUqI4wQyosr2wlndtw7kRIA3GoqO2oazFPWuZqLGUgltJLbNGtKbtRc_Oq7envAfj9ZjcYNJRR-P07XavXcizxqyhDSFsIQW_OeEygJ8z5EkPLnfgvQkQ56yJJKUIE7j-P20U50pKumZ9_Q99iHMKpWtNeWlPUcHqpxRppKKyJmRV706qSzHnBP1jTwTrdQf03ztQODvxX87D8Umr72--XAmqyiR-A_kUsKM</recordid><startdate>20160427</startdate><enddate>20160427</enddate><creator>Kay, Jennifer E.</creator><creator>Bourdages, Line</creator><creator>Miller, Nathaniel B.</creator><creator>Morrison, Ariel</creator><creator>Yettella, Vineel</creator><creator>Chepfer, Helene</creator><creator>Eaton, Brian</creator><general>Blackwell Publishing Ltd</general><general>American Geophysical Union</general><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><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0002-3571-2185</orcidid></search><sort><creationdate>20160427</creationdate><title>Evaluating and improving cloud phase in the Community Atmosphere Model version 5 using spaceborne lidar observations</title><author>Kay, Jennifer E. ; Bourdages, Line ; Miller, Nathaniel B. ; Morrison, Ariel ; Yettella, Vineel ; Chepfer, Helene ; Eaton, Brian</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5401-422194103e29df5dd4cb744a5e8a005c2d723b0f3b35608854d82d3da5babf5f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Air temperature</topic><topic>Atmosphere</topic><topic>Atmospheres</topic><topic>Atmospheric models</topic><topic>Brackish</topic><topic>CALIPSO (Pathfinder satellite)</topic><topic>Climate</topic><topic>climate model</topic><topic>Climate models</topic><topic>Cloud amount</topic><topic>Cloud detection</topic><topic>cloud phase</topic><topic>Clouds</topic><topic>Communities</topic><topic>Computer simulation</topic><topic>Embedded systems</topic><topic>Embedding</topic><topic>Future climates</topic><topic>Geophysics</topic><topic>Global climate</topic><topic>Greenland</topic><topic>Ice</topic><topic>Ice clouds</topic><topic>Ice cover</topic><topic>Lidar</topic><topic>Liquids</topic><topic>Marine</topic><topic>Meteorological satellites</topic><topic>Meteorology</topic><topic>Ocean-atmosphere interaction</topic><topic>Oceans</topic><topic>Parameter modification</topic><topic>Phase assignment</topic><topic>Physical properties</topic><topic>Radiation</topic><topic>Satellite observation</topic><topic>Satellites</topic><topic>Sciences of the Universe</topic><topic>Sea level</topic><topic>Sea level rise</topic><topic>Seasonal variation</topic><topic>Seasonal variations</topic><topic>Short wave radiation</topic><topic>Simulators</topic><topic>Southern Ocean</topic><topic>Spaceborne lidar</topic><topic>Storm tracks</topic><topic>Storms</topic><topic>supercooled liquid clouds</topic><topic>Surface temperature</topic><topic>Surface-air temperature relationships</topic><topic>Tracks (paths)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kay, Jennifer E.</creatorcontrib><creatorcontrib>Bourdages, Line</creatorcontrib><creatorcontrib>Miller, Nathaniel B.</creatorcontrib><creatorcontrib>Morrison, Ariel</creatorcontrib><creatorcontrib>Yettella, Vineel</creatorcontrib><creatorcontrib>Chepfer, Helene</creatorcontrib><creatorcontrib>Eaton, Brian</creatorcontrib><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><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>Journal of geophysical research. Atmospheres</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kay, Jennifer E.</au><au>Bourdages, Line</au><au>Miller, Nathaniel B.</au><au>Morrison, Ariel</au><au>Yettella, Vineel</au><au>Chepfer, Helene</au><au>Eaton, Brian</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evaluating and improving cloud phase in the Community Atmosphere Model version 5 using spaceborne lidar observations</atitle><jtitle>Journal of geophysical research. Atmospheres</jtitle><date>2016-04-27</date><risdate>2016</risdate><volume>121</volume><issue>8</issue><spage>4162</spage><epage>4176</epage><pages>4162-4176</pages><issn>2169-897X</issn><eissn>2169-8996</eissn><abstract>Spaceborne lidar observations from the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite are used to evaluate cloud amount and cloud phase in the Community Atmosphere Model version 5 (CAM5), the atmospheric component of a widely used state‐of‐the‐art global coupled climate model (Community Earth System Model). By embedding a lidar simulator within CAM5, the idiosyncrasies of spaceborne lidar cloud detection and phase assignment are replicated. As a result, this study makes scale‐aware and definition‐aware comparisons between model‐simulated and observed cloud amount and cloud phase. In the global mean, CAM5 has insufficient liquid cloud and excessive ice cloud when compared to CALIPSO observations. Over the ice‐covered Arctic Ocean, CAM5 has insufficient liquid cloud in all seasons. Having important implications for projections of future sea level rise, a liquid cloud deficit contributes to a cold bias of 2–3°C for summer daily maximum near‐surface air temperatures at Summit, Greenland. Over the midlatitude storm tracks, CAM5 has excessive ice cloud and insufficient liquid cloud. Storm track cloud phase biases in CAM5 maximize over the Southern Ocean, which also has larger‐than‐observed seasonal variations in cloud phase. Physical parameter modifications reduce the Southern Ocean cloud phase and shortwave radiation biases in CAM5 and illustrate the power of the CALIPSO observations as an observational constraint. The results also highlight the importance of using a regime‐based, as opposed to a geographic‐based, model evaluation approach. More generally, the results demonstrate the importance and value of simulator‐enabled comparisons of cloud phase in models used for future climate projection.
Key Points
Scale‐aware and definition‐aware cloud phase evaluation now publicly available in CAM
When compared to lidar observations, CAM5 has excessive ice cloud and insufficient liquid cloud
Increasing supercooled liquid cloud reduces shortwave absorption bias, especially over Southern Ocean</abstract><cop>Washington</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1002/2015JD024699</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-3571-2185</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Air temperature Atmosphere Atmospheres Atmospheric models Brackish CALIPSO (Pathfinder satellite) Climate climate model Climate models Cloud amount Cloud detection cloud phase Clouds Communities Computer simulation Embedded systems Embedding Future climates Geophysics Global climate Greenland Ice Ice clouds Ice cover Lidar Liquids Marine Meteorological satellites Meteorology Ocean-atmosphere interaction Oceans Parameter modification Phase assignment Physical properties Radiation Satellite observation Satellites Sciences of the Universe Sea level Sea level rise Seasonal variation Seasonal variations Short wave radiation Simulators Southern Ocean Spaceborne lidar Storm tracks Storms supercooled liquid clouds Surface temperature Surface-air temperature relationships Tracks (paths) |
title | Evaluating and improving cloud phase in the Community Atmosphere Model version 5 using spaceborne lidar observations |
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