An Intercomparison between Reanalysis and Dropsonde Observations of the Total Water Vapor Transport in Individual Atmospheric Rivers
A recent study presented nearly two decades of airborne atmospheric river (AR) observations and concluded that, on average, an individual AR transports ∼5 × 10⁸ kg s−1 of water vapor. The study here compares those cases to ARs independently identified in reanalyses based on a refined algorithm that...
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Veröffentlicht in: | Journal of hydrometeorology 2018-02, Vol.19 (2), p.321-337 |
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description | A recent study presented nearly two decades of airborne atmospheric river (AR) observations and concluded that, on average, an individual AR transports ∼5 × 10⁸ kg s−1 of water vapor. The study here compares those cases to ARs independently identified in reanalyses based on a refined algorithm that can detect less well-structured ARs, with the dual-purpose of validating reanalysis ARs against observations and evaluating dropsonde representativeness relative to reanalyses. The first comparison is based on 21 dropsonde-observed ARs in the northeastern Pacific and those closely matched, but not required to be exactly collocated, in ERA-Interim (MERRA-2), which indicates a mean error of −22% (−8%) in AR width and +3% (−1%) in total integrated water vapor transport (TIVT) and supports the effectiveness of the AR detection algorithm applied to the reanalyses. The second comparison is between the 21 dropsonde ARs and ∼6000 ARs detected in ERA-Interim (MERRA-2) over the same domain, which indicates a mean difference of 5% (20%) in AR width and 5% (14%) in TIVT and suggests the limited number of dropsonde observations is a highly (reasonably) representative sampling of ARs in the northeastern Pacific. Sensitivities of the comparison to seasonal and geographical variations in AR width/TIVT are also examined. The results provide a case where dedicated observational efforts in specific regions corroborate with global reanalyses in better characterizing the geometry and strength of ARs regionally and globally. The results also illustrate that the reanalysis depiction of ARs can help inform the selection of locations for future observational and modeling efforts. |
doi_str_mv | 10.1175/jhm-d-17-0114.1 |
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Martin</creator><creatorcontrib>Guan, Bin ; Waliser, Duane E. ; Ralph, F. Martin</creatorcontrib><description>A recent study presented nearly two decades of airborne atmospheric river (AR) observations and concluded that, on average, an individual AR transports ∼5 × 10⁸ kg s−1 of water vapor. The study here compares those cases to ARs independently identified in reanalyses based on a refined algorithm that can detect less well-structured ARs, with the dual-purpose of validating reanalysis ARs against observations and evaluating dropsonde representativeness relative to reanalyses. The first comparison is based on 21 dropsonde-observed ARs in the northeastern Pacific and those closely matched, but not required to be exactly collocated, in ERA-Interim (MERRA-2), which indicates a mean error of −22% (−8%) in AR width and +3% (−1%) in total integrated water vapor transport (TIVT) and supports the effectiveness of the AR detection algorithm applied to the reanalyses. The second comparison is between the 21 dropsonde ARs and ∼6000 ARs detected in ERA-Interim (MERRA-2) over the same domain, which indicates a mean difference of 5% (20%) in AR width and 5% (14%) in TIVT and suggests the limited number of dropsonde observations is a highly (reasonably) representative sampling of ARs in the northeastern Pacific. Sensitivities of the comparison to seasonal and geographical variations in AR width/TIVT are also examined. The results provide a case where dedicated observational efforts in specific regions corroborate with global reanalyses in better characterizing the geometry and strength of ARs regionally and globally. The results also illustrate that the reanalysis depiction of ARs can help inform the selection of locations for future observational and modeling efforts.</description><identifier>ISSN: 1525-755X</identifier><identifier>EISSN: 1525-7541</identifier><identifier>DOI: 10.1175/jhm-d-17-0114.1</identifier><language>eng</language><publisher>Boston: American Meteorological Society</publisher><subject>Aircraft ; Algorithms ; Atmospheric models ; Climate ; Coasts ; Detection ; Dropsonde ; Dropsonde observations ; Geographical variations ; Humidity ; Hydrologic cycle ; Identification ; Intercomparison ; Laboratories ; Modelling ; Precipitation ; SPECIAL MERRA-2 COLLECTION ; Studies ; Transport ; Water vapor ; Water vapor transport ; Water vapour ; Width ; Wind</subject><ispartof>Journal of hydrometeorology, 2018-02, Vol.19 (2), p.321-337</ispartof><rights>2018 American Meteorological Society</rights><rights>Copyright American Meteorological Society Feb 2018</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c398t-78be6fc2800a94bd6e20bc3cf5b9414e80759b54e2c06d6a2502f9e5adb9890e3</citedby><cites>FETCH-LOGICAL-c398t-78be6fc2800a94bd6e20bc3cf5b9414e80759b54e2c06d6a2502f9e5adb9890e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/26406423$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/26406423$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,780,784,803,3681,27924,27925,58017,58250</link.rule.ids></links><search><creatorcontrib>Guan, Bin</creatorcontrib><creatorcontrib>Waliser, Duane E.</creatorcontrib><creatorcontrib>Ralph, F. Martin</creatorcontrib><title>An Intercomparison between Reanalysis and Dropsonde Observations of the Total Water Vapor Transport in Individual Atmospheric Rivers</title><title>Journal of hydrometeorology</title><description>A recent study presented nearly two decades of airborne atmospheric river (AR) observations and concluded that, on average, an individual AR transports ∼5 × 10⁸ kg s−1 of water vapor. The study here compares those cases to ARs independently identified in reanalyses based on a refined algorithm that can detect less well-structured ARs, with the dual-purpose of validating reanalysis ARs against observations and evaluating dropsonde representativeness relative to reanalyses. The first comparison is based on 21 dropsonde-observed ARs in the northeastern Pacific and those closely matched, but not required to be exactly collocated, in ERA-Interim (MERRA-2), which indicates a mean error of −22% (−8%) in AR width and +3% (−1%) in total integrated water vapor transport (TIVT) and supports the effectiveness of the AR detection algorithm applied to the reanalyses. The second comparison is between the 21 dropsonde ARs and ∼6000 ARs detected in ERA-Interim (MERRA-2) over the same domain, which indicates a mean difference of 5% (20%) in AR width and 5% (14%) in TIVT and suggests the limited number of dropsonde observations is a highly (reasonably) representative sampling of ARs in the northeastern Pacific. Sensitivities of the comparison to seasonal and geographical variations in AR width/TIVT are also examined. 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The results also illustrate that the reanalysis depiction of ARs can help inform the selection of locations for future observational and modeling efforts.</description><subject>Aircraft</subject><subject>Algorithms</subject><subject>Atmospheric models</subject><subject>Climate</subject><subject>Coasts</subject><subject>Detection</subject><subject>Dropsonde</subject><subject>Dropsonde observations</subject><subject>Geographical variations</subject><subject>Humidity</subject><subject>Hydrologic cycle</subject><subject>Identification</subject><subject>Intercomparison</subject><subject>Laboratories</subject><subject>Modelling</subject><subject>Precipitation</subject><subject>SPECIAL MERRA-2 COLLECTION</subject><subject>Studies</subject><subject>Transport</subject><subject>Water vapor</subject><subject>Water vapor transport</subject><subject>Water vapour</subject><subject>Width</subject><subject>Wind</subject><issn>1525-755X</issn><issn>1525-7541</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNo9kN1LwzAUxYsoOKfPPgkBn7sladI2j2NTN5kMxvx4C2l7y1LWpibZZO_-4bZM9nQP3N85l3uC4J7gESEJH1fbOixCkoSYEDYiF8GAcMrDhDNyedb86zq4ca7CGDNB0kHwO2nQovFgc1O3ympnGpSB_wFo0BpUo3ZHpx1STYFm1rTdugC0yhzYg_LaNA6ZEvktoI3xaoc-VReFPlRrLNpY1bhOeKT7G4U-6GLfMRNfG9duweocrfUBrLsNrkq1c3D3P4fB-_PTZjoPl6uXxXSyDPNIpD5M0gziMqcpxkqwrIiB4iyP8pJnghEGKU64yDgDmuO4iBXlmJYCuCoykQoM0TB4POW21nzvwXlZmb3tfnSS9h0SkSSso8YnKrfGOQulbK2ulT1KgmWPydf5m5xJksi-akk6x8PJUTlv7BmnMcMxo1H0B7ilflw</recordid><startdate>20180201</startdate><enddate>20180201</enddate><creator>Guan, Bin</creator><creator>Waliser, Duane E.</creator><creator>Ralph, F. 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Martin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c398t-78be6fc2800a94bd6e20bc3cf5b9414e80759b54e2c06d6a2502f9e5adb9890e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Aircraft</topic><topic>Algorithms</topic><topic>Atmospheric models</topic><topic>Climate</topic><topic>Coasts</topic><topic>Detection</topic><topic>Dropsonde</topic><topic>Dropsonde observations</topic><topic>Geographical variations</topic><topic>Humidity</topic><topic>Hydrologic cycle</topic><topic>Identification</topic><topic>Intercomparison</topic><topic>Laboratories</topic><topic>Modelling</topic><topic>Precipitation</topic><topic>SPECIAL MERRA-2 COLLECTION</topic><topic>Studies</topic><topic>Transport</topic><topic>Water vapor</topic><topic>Water vapor transport</topic><topic>Water vapour</topic><topic>Width</topic><topic>Wind</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Guan, Bin</creatorcontrib><creatorcontrib>Waliser, Duane E.</creatorcontrib><creatorcontrib>Ralph, F. 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Martin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An Intercomparison between Reanalysis and Dropsonde Observations of the Total Water Vapor Transport in Individual Atmospheric Rivers</atitle><jtitle>Journal of hydrometeorology</jtitle><date>2018-02-01</date><risdate>2018</risdate><volume>19</volume><issue>2</issue><spage>321</spage><epage>337</epage><pages>321-337</pages><issn>1525-755X</issn><eissn>1525-7541</eissn><abstract>A recent study presented nearly two decades of airborne atmospheric river (AR) observations and concluded that, on average, an individual AR transports ∼5 × 10⁸ kg s−1 of water vapor. The study here compares those cases to ARs independently identified in reanalyses based on a refined algorithm that can detect less well-structured ARs, with the dual-purpose of validating reanalysis ARs against observations and evaluating dropsonde representativeness relative to reanalyses. The first comparison is based on 21 dropsonde-observed ARs in the northeastern Pacific and those closely matched, but not required to be exactly collocated, in ERA-Interim (MERRA-2), which indicates a mean error of −22% (−8%) in AR width and +3% (−1%) in total integrated water vapor transport (TIVT) and supports the effectiveness of the AR detection algorithm applied to the reanalyses. The second comparison is between the 21 dropsonde ARs and ∼6000 ARs detected in ERA-Interim (MERRA-2) over the same domain, which indicates a mean difference of 5% (20%) in AR width and 5% (14%) in TIVT and suggests the limited number of dropsonde observations is a highly (reasonably) representative sampling of ARs in the northeastern Pacific. Sensitivities of the comparison to seasonal and geographical variations in AR width/TIVT are also examined. 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subjects | Aircraft Algorithms Atmospheric models Climate Coasts Detection Dropsonde Dropsonde observations Geographical variations Humidity Hydrologic cycle Identification Intercomparison Laboratories Modelling Precipitation SPECIAL MERRA-2 COLLECTION Studies Transport Water vapor Water vapor transport Water vapour Width Wind |
title | An Intercomparison between Reanalysis and Dropsonde Observations of the Total Water Vapor Transport in Individual Atmospheric Rivers |
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