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Geographically versus dynamically defined boundary layer cloud regimes and their use to evaluate general circulation model cloud parameterizations
Regimes of tropical low‐level clouds are commonly identified according to large‐scale subsidence and lower tropospheric stability (LTS). This definition alone is insufficient for the distinction between regimes and limits the comparison of low‐level clouds from CloudSat radar observations and the EC...
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Published in: | Geophysical research letters 2013-09, Vol.40 (18), p.4951-4956 |
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description | Regimes of tropical low‐level clouds are commonly identified according to large‐scale subsidence and lower tropospheric stability (LTS). This definition alone is insufficient for the distinction between regimes and limits the comparison of low‐level clouds from CloudSat radar observations and the ECHAM5 GCM run with the COSP radar simulator. Comparisons of CloudSat radar cloud altitude‐reflectivity histograms for stratocumulus and shallow cumulus regimes, as defined above, show nearly identical reflectivity profiles, because the distinction between the two regimes is dependent upon atmospheric stability below 700 hPa and observations above 1.5 km. Regional subsets, near California and Hawaii, for example, have large differences in reflectivity profiles than the dynamically defined domain; indicating different reflectivity profiles exist under a given large‐scale environment. Regional subsets are better for the evaluation of low‐level clouds in CloudSat and ECHAM5 as there is less contamination between 2.5 km and 7.5 km from precipitating hydrometeors which obscured cloud reflectivities.
Key Points
Identification of low clouds by large‐scale dynamics insufficient for radarStratocumulus and shallow cumulus regimes have nearly identical reflectivitiesGeographical regions are better for evaluating low-level clouds with a radar |
doi_str_mv | 10.1002/grl.50945 |
format | article |
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Key Points
Identification of low clouds by large‐scale dynamics insufficient for radarStratocumulus and shallow cumulus regimes have nearly identical reflectivitiesGeographical regions are better for evaluating low-level clouds with a radar</description><identifier>ISSN: 0094-8276</identifier><identifier>EISSN: 1944-8007</identifier><identifier>DOI: 10.1002/grl.50945</identifier><identifier>CODEN: GPRLAJ</identifier><language>eng</language><publisher>Washington, DC: Blackwell Publishing Ltd</publisher><subject>Altitude ; Atmospheric stability ; boundary layer clouds ; Boundary layers ; Circulation ; Clouds ; CloudSat ; Computer simulation ; Contamination ; COSP ; Cumulus clouds ; Dynamic tests ; Earth sciences ; Earth, ocean, space ; ECHAM5 ; Evaluation ; Exact sciences and technology ; General circulation ; General circulation models ; Histograms ; Hydrometeors ; Identification ; Parametrization ; Profiles ; Radar ; radar simulator ; Reflectance ; Reflectivity ; Regional ; Regional analysis ; Simulation ; Simulators ; Stability ; Stratocumulus clouds ; Subsidence ; Tropical climate ; tropical low clouds</subject><ispartof>Geophysical research letters, 2013-09, Vol.40 (18), p.4951-4956</ispartof><rights>2013. American Geophysical Union. All Rights Reserved.</rights><rights>2014 INIST-CNRS</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4945-45d6b4fe1a795cf09af82aa3d648770f7ae2e5e7b23be420acf2551a26e0102d3</citedby><cites>FETCH-LOGICAL-c4945-45d6b4fe1a795cf09af82aa3d648770f7ae2e5e7b23be420acf2551a26e0102d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fgrl.50945$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fgrl.50945$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,11514,27924,27925,46468,46892</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=27885696$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Nam, Christine C.W.</creatorcontrib><creatorcontrib>Quaas, Johannes</creatorcontrib><title>Geographically versus dynamically defined boundary layer cloud regimes and their use to evaluate general circulation model cloud parameterizations</title><title>Geophysical research letters</title><addtitle>Geophys. Res. Lett</addtitle><description>Regimes of tropical low‐level clouds are commonly identified according to large‐scale subsidence and lower tropospheric stability (LTS). This definition alone is insufficient for the distinction between regimes and limits the comparison of low‐level clouds from CloudSat radar observations and the ECHAM5 GCM run with the COSP radar simulator. Comparisons of CloudSat radar cloud altitude‐reflectivity histograms for stratocumulus and shallow cumulus regimes, as defined above, show nearly identical reflectivity profiles, because the distinction between the two regimes is dependent upon atmospheric stability below 700 hPa and observations above 1.5 km. Regional subsets, near California and Hawaii, for example, have large differences in reflectivity profiles than the dynamically defined domain; indicating different reflectivity profiles exist under a given large‐scale environment. Regional subsets are better for the evaluation of low‐level clouds in CloudSat and ECHAM5 as there is less contamination between 2.5 km and 7.5 km from precipitating hydrometeors which obscured cloud reflectivities.
Key Points
Identification of low clouds by large‐scale dynamics insufficient for radarStratocumulus and shallow cumulus regimes have nearly identical reflectivitiesGeographical regions are better for evaluating low-level clouds with a radar</description><subject>Altitude</subject><subject>Atmospheric stability</subject><subject>boundary layer clouds</subject><subject>Boundary layers</subject><subject>Circulation</subject><subject>Clouds</subject><subject>CloudSat</subject><subject>Computer simulation</subject><subject>Contamination</subject><subject>COSP</subject><subject>Cumulus clouds</subject><subject>Dynamic tests</subject><subject>Earth sciences</subject><subject>Earth, ocean, space</subject><subject>ECHAM5</subject><subject>Evaluation</subject><subject>Exact sciences and technology</subject><subject>General circulation</subject><subject>General circulation models</subject><subject>Histograms</subject><subject>Hydrometeors</subject><subject>Identification</subject><subject>Parametrization</subject><subject>Profiles</subject><subject>Radar</subject><subject>radar simulator</subject><subject>Reflectance</subject><subject>Reflectivity</subject><subject>Regional</subject><subject>Regional analysis</subject><subject>Simulation</subject><subject>Simulators</subject><subject>Stability</subject><subject>Stratocumulus clouds</subject><subject>Subsidence</subject><subject>Tropical climate</subject><subject>tropical low clouds</subject><issn>0094-8276</issn><issn>1944-8007</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><recordid>eNqFkV1rFDEUhgdRcK1e-A8CIujFtElm8jGXUupUWCuIIngTziZntqmZmTWZqU5_hr_Y2F17IahXgZPnfTiHtyieMnrMKOUn2xiOBW1qca9YsaauS02pul-saJ6Vmiv5sHiU0hWltKIVWxU_Why3EXaX3kIIC7nGmOZE3DJAfxg57PyAjmzGeXAQFxJgwUhsGGdHIm59j4nA4Mh0iT6SOSGZRoLXEGaYkGxxwAiBWB_tHGDy40D60WE4GHYQoccJo7-5_UyPiwcdhIRPDu9R8fH12YfT83L9rn1z-mpd2jrfV9bCyU3dIQPVCNvRBjrNASona60U7RQgR4Fqw6sN1pyC7bgQDLhEyih31VHxYu_dxfHrjGkyvU8WQ4ABxzkZJhUTUtdc_R8VvGkE1UJn9Nkf6NU4xyEfYljDqJJNNv6TknnZSufyMvVyT9k4phSxM7vo-1yBYdT8qtvkus1t3Zl9fjBCyr11EQbr012AK62FbGTmTvbcNx9w-bvQtO_Xv83lPuHThN_vEhC_GKkqJcyni9a0rBXi88Vbw6qf5ZfKBA</recordid><startdate>20130928</startdate><enddate>20130928</enddate><creator>Nam, Christine C.W.</creator><creator>Quaas, Johannes</creator><general>Blackwell Publishing Ltd</general><general>American Geophysical Union</general><general>John Wiley & Sons, Inc</general><scope>BSCLL</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7TN</scope><scope>8FD</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></search><sort><creationdate>20130928</creationdate><title>Geographically versus dynamically defined boundary layer cloud regimes and their use to evaluate general circulation model cloud parameterizations</title><author>Nam, Christine C.W. ; Quaas, Johannes</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4945-45d6b4fe1a795cf09af82aa3d648770f7ae2e5e7b23be420acf2551a26e0102d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Altitude</topic><topic>Atmospheric stability</topic><topic>boundary layer clouds</topic><topic>Boundary layers</topic><topic>Circulation</topic><topic>Clouds</topic><topic>CloudSat</topic><topic>Computer simulation</topic><topic>Contamination</topic><topic>COSP</topic><topic>Cumulus clouds</topic><topic>Dynamic tests</topic><topic>Earth sciences</topic><topic>Earth, ocean, space</topic><topic>ECHAM5</topic><topic>Evaluation</topic><topic>Exact sciences and technology</topic><topic>General circulation</topic><topic>General circulation models</topic><topic>Histograms</topic><topic>Hydrometeors</topic><topic>Identification</topic><topic>Parametrization</topic><topic>Profiles</topic><topic>Radar</topic><topic>radar simulator</topic><topic>Reflectance</topic><topic>Reflectivity</topic><topic>Regional</topic><topic>Regional analysis</topic><topic>Simulation</topic><topic>Simulators</topic><topic>Stability</topic><topic>Stratocumulus clouds</topic><topic>Subsidence</topic><topic>Tropical climate</topic><topic>tropical low clouds</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nam, Christine C.W.</creatorcontrib><creatorcontrib>Quaas, Johannes</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Technology Research Database</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>Geophysical research letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nam, Christine C.W.</au><au>Quaas, Johannes</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Geographically versus dynamically defined boundary layer cloud regimes and their use to evaluate general circulation model cloud parameterizations</atitle><jtitle>Geophysical research letters</jtitle><addtitle>Geophys. Res. Lett</addtitle><date>2013-09-28</date><risdate>2013</risdate><volume>40</volume><issue>18</issue><spage>4951</spage><epage>4956</epage><pages>4951-4956</pages><issn>0094-8276</issn><eissn>1944-8007</eissn><coden>GPRLAJ</coden><abstract>Regimes of tropical low‐level clouds are commonly identified according to large‐scale subsidence and lower tropospheric stability (LTS). This definition alone is insufficient for the distinction between regimes and limits the comparison of low‐level clouds from CloudSat radar observations and the ECHAM5 GCM run with the COSP radar simulator. Comparisons of CloudSat radar cloud altitude‐reflectivity histograms for stratocumulus and shallow cumulus regimes, as defined above, show nearly identical reflectivity profiles, because the distinction between the two regimes is dependent upon atmospheric stability below 700 hPa and observations above 1.5 km. Regional subsets, near California and Hawaii, for example, have large differences in reflectivity profiles than the dynamically defined domain; indicating different reflectivity profiles exist under a given large‐scale environment. Regional subsets are better for the evaluation of low‐level clouds in CloudSat and ECHAM5 as there is less contamination between 2.5 km and 7.5 km from precipitating hydrometeors which obscured cloud reflectivities.
Key Points
Identification of low clouds by large‐scale dynamics insufficient for radarStratocumulus and shallow cumulus regimes have nearly identical reflectivitiesGeographical regions are better for evaluating low-level clouds with a radar</abstract><cop>Washington, DC</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1002/grl.50945</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Altitude Atmospheric stability boundary layer clouds Boundary layers Circulation Clouds CloudSat Computer simulation Contamination COSP Cumulus clouds Dynamic tests Earth sciences Earth, ocean, space ECHAM5 Evaluation Exact sciences and technology General circulation General circulation models Histograms Hydrometeors Identification Parametrization Profiles Radar radar simulator Reflectance Reflectivity Regional Regional analysis Simulation Simulators Stability Stratocumulus clouds Subsidence Tropical climate tropical low clouds |
title | Geographically versus dynamically defined boundary layer cloud regimes and their use to evaluate general circulation model cloud parameterizations |
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