Evaluation of CMIP3 and CMIP5 Wind Stress Climatology Using Satellite Measurements and Atmospheric Reanalysis Products
Wind stress measurements from the Quick Scatterometer (QuikSCAT) satellite and two atmospheric reanalysis products are used to evaluate the annual mean and seasonal cycle of wind stress simulated by phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5). The ensemble CMIP3 and...
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description | Wind stress measurements from the Quick Scatterometer (QuikSCAT) satellite and two atmospheric reanalysis products are used to evaluate the annual mean and seasonal cycle of wind stress simulated by phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5). The ensemble CMIP3 and CMIP5 wind stresses are very similar to each other. Generally speaking, there is no significant improvement of CMIP5 over CMIP3. The CMIP ensemble–average zonal wind stress has eastward biases at midlatitude westerly wind regions (30°–50°N and 30°–50°S, with CMIP being too strong by as much as 55%), westward biases in subtropical–tropical easterly wind regions (15°–25°N and 15°–25°S), and westward biases at high-latitude regions (poleward of 55°S and 55°N). These biases correspond to too strong anticyclonic (cyclonic) wind stress curl over the subtropical (subpolar) ocean gyres, which would strengthen these gyres and influence oceanic meridional heat transport. In the equatorial zone, significant biases of CMIP wind exist in individual basins. In the equatorial Atlantic and Indian Oceans, CMIP ensemble zonal wind stresses are too weak and result in too small of an east–west gradient of sea level. In the equatorial Pacific Ocean, CMIP zonal wind stresses are too weak in the central and too strong in the western Pacific. These biases have important implications for the simulation of various modes of climate variability originating in the tropics. The CMIP as a whole overestimate the magnitude of seasonal variability by almost 50% when averaged over the entire global ocean. The biased wind stress climatologies in CMIP not only have implications for the simulated ocean circulation and climate variability but other air–sea fluxes as well. |
doi_str_mv | 10.1175/jcli-d-12-00591.1 |
format | Article |
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The ensemble CMIP3 and CMIP5 wind stresses are very similar to each other. Generally speaking, there is no significant improvement of CMIP5 over CMIP3. The CMIP ensemble–average zonal wind stress has eastward biases at midlatitude westerly wind regions (30°–50°N and 30°–50°S, with CMIP being too strong by as much as 55%), westward biases in subtropical–tropical easterly wind regions (15°–25°N and 15°–25°S), and westward biases at high-latitude regions (poleward of 55°S and 55°N). These biases correspond to too strong anticyclonic (cyclonic) wind stress curl over the subtropical (subpolar) ocean gyres, which would strengthen these gyres and influence oceanic meridional heat transport. In the equatorial zone, significant biases of CMIP wind exist in individual basins. In the equatorial Atlantic and Indian Oceans, CMIP ensemble zonal wind stresses are too weak and result in too small of an east–west gradient of sea level. In the equatorial Pacific Ocean, CMIP zonal wind stresses are too weak in the central and too strong in the western Pacific. These biases have important implications for the simulation of various modes of climate variability originating in the tropics. The CMIP as a whole overestimate the magnitude of seasonal variability by almost 50% when averaged over the entire global ocean. The biased wind stress climatologies in CMIP not only have implications for the simulated ocean circulation and climate variability but other air–sea fluxes as well.</description><identifier>ISSN: 0894-8755</identifier><identifier>EISSN: 1520-0442</identifier><identifier>DOI: 10.1175/jcli-d-12-00591.1</identifier><language>eng</language><publisher>Boston, MA: American Meteorological Society</publisher><subject>20th century ; Air-sea flux ; Atmospheric models ; Atmospherics ; Bias ; Climate ; Climate change ; Climate models ; Climate variability ; Climatology ; Data assimilation ; Earth, ocean, space ; Easterlies ; Exact sciences and technology ; External geophysics ; General circulation models ; Global climate models ; Gyres ; Heat transport ; Intercomparison ; Latitude ; Marine ; Mathematical models ; Meridional heat transport ; Meteorology ; Modeling ; Ocean basins ; Ocean circulation ; Ocean currents ; Oceanic climates ; Oceans ; Remote sensing ; Satellites ; Scatterometers ; Sea level ; Seasonal variability ; Seasonal variation ; Seasonal variations ; Simulation ; Stresses ; Temperate regions ; Tropical environments ; Water circulation ; Weather ; Westerlies ; Wind ; Wind measurement ; Wind stress ; Wind stress curl ; Winds and their effects ; Zonal winds</subject><ispartof>Journal of climate, 2013-08, Vol.26 (16), p.5810-5826</ispartof><rights>2013 American Meteorological Society</rights><rights>2015 INIST-CNRS</rights><rights>Copyright American Meteorological Society Aug 15, 2013</rights><rights>Copyright American Meteorological Society 2013</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c528t-5a22341b9640042c147863f696b4313220330d4d4f3f54719ed157530cb76a983</citedby><cites>FETCH-LOGICAL-c528t-5a22341b9640042c147863f696b4313220330d4d4f3f54719ed157530cb76a983</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/26192728$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/26192728$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,776,780,799,3668,27901,27902,57992,58225</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=27643349$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Lee, Tong</creatorcontrib><creatorcontrib>Waliser, Duane E.</creatorcontrib><creatorcontrib>Li, Jui-Lin F.</creatorcontrib><creatorcontrib>Landerer, Felix W.</creatorcontrib><creatorcontrib>Gierach, Michelle M.</creatorcontrib><title>Evaluation of CMIP3 and CMIP5 Wind Stress Climatology Using Satellite Measurements and Atmospheric Reanalysis Products</title><title>Journal of climate</title><description>Wind stress measurements from the Quick Scatterometer (QuikSCAT) satellite and two atmospheric reanalysis products are used to evaluate the annual mean and seasonal cycle of wind stress simulated by phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5). The ensemble CMIP3 and CMIP5 wind stresses are very similar to each other. Generally speaking, there is no significant improvement of CMIP5 over CMIP3. The CMIP ensemble–average zonal wind stress has eastward biases at midlatitude westerly wind regions (30°–50°N and 30°–50°S, with CMIP being too strong by as much as 55%), westward biases in subtropical–tropical easterly wind regions (15°–25°N and 15°–25°S), and westward biases at high-latitude regions (poleward of 55°S and 55°N). These biases correspond to too strong anticyclonic (cyclonic) wind stress curl over the subtropical (subpolar) ocean gyres, which would strengthen these gyres and influence oceanic meridional heat transport. In the equatorial zone, significant biases of CMIP wind exist in individual basins. In the equatorial Atlantic and Indian Oceans, CMIP ensemble zonal wind stresses are too weak and result in too small of an east–west gradient of sea level. In the equatorial Pacific Ocean, CMIP zonal wind stresses are too weak in the central and too strong in the western Pacific. These biases have important implications for the simulation of various modes of climate variability originating in the tropics. The CMIP as a whole overestimate the magnitude of seasonal variability by almost 50% when averaged over the entire global ocean. The biased wind stress climatologies in CMIP not only have implications for the simulated ocean circulation and climate variability but other air–sea fluxes as well.</description><subject>20th century</subject><subject>Air-sea flux</subject><subject>Atmospheric models</subject><subject>Atmospherics</subject><subject>Bias</subject><subject>Climate</subject><subject>Climate change</subject><subject>Climate models</subject><subject>Climate variability</subject><subject>Climatology</subject><subject>Data assimilation</subject><subject>Earth, ocean, space</subject><subject>Easterlies</subject><subject>Exact sciences and technology</subject><subject>External geophysics</subject><subject>General circulation models</subject><subject>Global climate models</subject><subject>Gyres</subject><subject>Heat transport</subject><subject>Intercomparison</subject><subject>Latitude</subject><subject>Marine</subject><subject>Mathematical models</subject><subject>Meridional heat transport</subject><subject>Meteorology</subject><subject>Modeling</subject><subject>Ocean basins</subject><subject>Ocean circulation</subject><subject>Ocean currents</subject><subject>Oceanic climates</subject><subject>Oceans</subject><subject>Remote sensing</subject><subject>Satellites</subject><subject>Scatterometers</subject><subject>Sea level</subject><subject>Seasonal variability</subject><subject>Seasonal variation</subject><subject>Seasonal variations</subject><subject>Simulation</subject><subject>Stresses</subject><subject>Temperate regions</subject><subject>Tropical environments</subject><subject>Water circulation</subject><subject>Weather</subject><subject>Westerlies</subject><subject>Wind</subject><subject>Wind measurement</subject><subject>Wind stress</subject><subject>Wind stress curl</subject><subject>Winds and their effects</subject><subject>Zonal 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winds</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lee, Tong</creatorcontrib><creatorcontrib>Waliser, Duane E.</creatorcontrib><creatorcontrib>Li, Jui-Lin F.</creatorcontrib><creatorcontrib>Landerer, Felix W.</creatorcontrib><creatorcontrib>Gierach, Michelle M.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Aqualine</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Agricultural Science Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Military Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>STEM Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology 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Reanalysis Products</atitle><jtitle>Journal of climate</jtitle><date>2013-08-01</date><risdate>2013</risdate><volume>26</volume><issue>16</issue><spage>5810</spage><epage>5826</epage><pages>5810-5826</pages><issn>0894-8755</issn><eissn>1520-0442</eissn><abstract>Wind stress measurements from the Quick Scatterometer (QuikSCAT) satellite and two atmospheric reanalysis products are used to evaluate the annual mean and seasonal cycle of wind stress simulated by phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5). The ensemble CMIP3 and CMIP5 wind stresses are very similar to each other. Generally speaking, there is no significant improvement of CMIP5 over CMIP3. The CMIP ensemble–average zonal wind stress has eastward biases at midlatitude westerly wind regions (30°–50°N and 30°–50°S, with CMIP being too strong by as much as 55%), westward biases in subtropical–tropical easterly wind regions (15°–25°N and 15°–25°S), and westward biases at high-latitude regions (poleward of 55°S and 55°N). These biases correspond to too strong anticyclonic (cyclonic) wind stress curl over the subtropical (subpolar) ocean gyres, which would strengthen these gyres and influence oceanic meridional heat transport. In the equatorial zone, significant biases of CMIP wind exist in individual basins. In the equatorial Atlantic and Indian Oceans, CMIP ensemble zonal wind stresses are too weak and result in too small of an east–west gradient of sea level. In the equatorial Pacific Ocean, CMIP zonal wind stresses are too weak in the central and too strong in the western Pacific. These biases have important implications for the simulation of various modes of climate variability originating in the tropics. The CMIP as a whole overestimate the magnitude of seasonal variability by almost 50% when averaged over the entire global ocean. The biased wind stress climatologies in CMIP not only have implications for the simulated ocean circulation and climate variability but other air–sea fluxes as well.</abstract><cop>Boston, MA</cop><pub>American Meteorological Society</pub><doi>10.1175/jcli-d-12-00591.1</doi><tpages>17</tpages><oa>free_for_read</oa></addata></record> |
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subjects | 20th century Air-sea flux Atmospheric models Atmospherics Bias Climate Climate change Climate models Climate variability Climatology Data assimilation Earth, ocean, space Easterlies Exact sciences and technology External geophysics General circulation models Global climate models Gyres Heat transport Intercomparison Latitude Marine Mathematical models Meridional heat transport Meteorology Modeling Ocean basins Ocean circulation Ocean currents Oceanic climates Oceans Remote sensing Satellites Scatterometers Sea level Seasonal variability Seasonal variation Seasonal variations Simulation Stresses Temperate regions Tropical environments Water circulation Weather Westerlies Wind Wind measurement Wind stress Wind stress curl Winds and their effects Zonal winds |
title | Evaluation of CMIP3 and CMIP5 Wind Stress Climatology Using Satellite Measurements and Atmospheric Reanalysis Products |
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