A Quality Control Procedure for Climatological Studies Using Argo Data in the North Pacific Western Boundary Current Region
A quality control (QC) procedure is developed to estimate monthly mean climatologies from the large Argo dataset (2005–12) over the North Pacific western boundary current region. In addition to the individual QC procedure, which checks for instrumental, transmission, and gross errors, the paper desc...
Gespeichert in:
Veröffentlicht in: | Journal of atmospheric and oceanic technology 2016-12, Vol.33 (12), p.2717-2733 |
---|---|
Hauptverfasser: | , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 2733 |
---|---|
container_issue | 12 |
container_start_page | 2717 |
container_title | Journal of atmospheric and oceanic technology |
container_volume | 33 |
creator | Jia, Wenjing Wang, Dong Pinardi, Nadia Simoncelli, Simona Storto, Andrea Masina, Simona |
description | A quality control (QC) procedure is developed to estimate monthly mean climatologies from the large Argo dataset (2005–12) over the North Pacific western boundary current region. In addition to the individual QC procedure, which checks for instrumental, transmission, and gross errors, the paper describes and shows the impact of climatological checks (collective QC) on the quality of both processed profiles and resultant climatological distributions. Objective analysis (OA) is applied progressively to produce the gridded climatological fields. The method uses horizontal regional climatological averages defined in five regime-oriented subregions in the Kuroshio area and the Japan Sea. Performing the QC procedure on specific coherent subregions produces improved profiling data and climatological fields because more details about the local hydrodynamics are taken into consideration. Nonrepresentative data and random noises are more effectively rejected by this method, which has value both in defining a climatological mean and identifying outlier data. Assessing with both profiling and coordinated datasets, the agreement is reasonably good (particularly for those areas with abundant observations), but the results (although already smoothed) can capture more detailed or mesoscale features for further regional studies. The method described has the potential to meet future challenges in processing accumulating Argo observations in the coming decades. |
doi_str_mv | 10.1175/JTECH-D-15-0140.1 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2826250377</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2826250377</sourcerecordid><originalsourceid>FETCH-LOGICAL-c364t-843dea11ec03638fc183a877e551c2b83ce32b571958fc01adca5a38634188dc3</originalsourceid><addsrcrecordid>eNotkM1OwzAQhC0EEqXwANwscQ544zh2jyUtf6qgQCuOlus4ratgF9s5VLw8gXJaaXc0s_MhdAnkGoCzm6fFtHrIJhmwjEDRL4_QAFhOMlLk5TEaEE5HGWE8P0VnMW4JIUChHKDvMX7tVGvTHlfepeBbPA9em7oLBjc-4Kq1nyr51q-tVi1-T11tTcTLaN0aj8Pa44lKCluH08bgZx_SBs-Vto3V-MPEZILDt75ztQp9RBeCcQm_mbX17hydNKqN5uJ_DtHybrroa8xe7h-r8SzTtCxSJgpaGwVgNKElFY0GQZXg3DAGOl8Jqg3NV4zDiPVHAqrWiikqSlqAELWmQ3R18N0F_9X1P8mt74LrI2Uu8jJnhHLeq-Cg0sHHGEwjd6GvHvYSiPxlLP8Yy4kEJn8ZS6A_76JwEg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2826250377</pqid></control><display><type>article</type><title>A Quality Control Procedure for Climatological Studies Using Argo Data in the North Pacific Western Boundary Current Region</title><source>American Meteorological Society</source><source>EZB-FREE-00999 freely available EZB journals</source><source>Alma/SFX Local Collection</source><creator>Jia, Wenjing ; Wang, Dong ; Pinardi, Nadia ; Simoncelli, Simona ; Storto, Andrea ; Masina, Simona</creator><creatorcontrib>Jia, Wenjing ; Wang, Dong ; Pinardi, Nadia ; Simoncelli, Simona ; Storto, Andrea ; Masina, Simona</creatorcontrib><description>A quality control (QC) procedure is developed to estimate monthly mean climatologies from the large Argo dataset (2005–12) over the North Pacific western boundary current region. In addition to the individual QC procedure, which checks for instrumental, transmission, and gross errors, the paper describes and shows the impact of climatological checks (collective QC) on the quality of both processed profiles and resultant climatological distributions. Objective analysis (OA) is applied progressively to produce the gridded climatological fields. The method uses horizontal regional climatological averages defined in five regime-oriented subregions in the Kuroshio area and the Japan Sea. Performing the QC procedure on specific coherent subregions produces improved profiling data and climatological fields because more details about the local hydrodynamics are taken into consideration. Nonrepresentative data and random noises are more effectively rejected by this method, which has value both in defining a climatological mean and identifying outlier data. Assessing with both profiling and coordinated datasets, the agreement is reasonably good (particularly for those areas with abundant observations), but the results (although already smoothed) can capture more detailed or mesoscale features for further regional studies. The method described has the potential to meet future challenges in processing accumulating Argo observations in the coming decades.</description><identifier>ISSN: 0739-0572</identifier><identifier>EISSN: 1520-0426</identifier><identifier>DOI: 10.1175/JTECH-D-15-0140.1</identifier><language>eng</language><publisher>Boston: American Meteorological Society</publisher><subject>Bathymetry ; Boundary currents ; Climatic analysis ; Climatological means ; Climatology ; Data analysis ; Data processing ; Data transmission ; Datasets ; Fields ; Hydrodynamics ; Mesoscale features ; Methods ; Objective analysis ; Oceans ; Outliers (statistics) ; Procedures ; Profiling ; Quality control ; Regions ; Salinity</subject><ispartof>Journal of atmospheric and oceanic technology, 2016-12, Vol.33 (12), p.2717-2733</ispartof><rights>Copyright American Meteorological Society 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c364t-843dea11ec03638fc183a877e551c2b83ce32b571958fc01adca5a38634188dc3</citedby><cites>FETCH-LOGICAL-c364t-843dea11ec03638fc183a877e551c2b83ce32b571958fc01adca5a38634188dc3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,3668,27901,27902</link.rule.ids></links><search><creatorcontrib>Jia, Wenjing</creatorcontrib><creatorcontrib>Wang, Dong</creatorcontrib><creatorcontrib>Pinardi, Nadia</creatorcontrib><creatorcontrib>Simoncelli, Simona</creatorcontrib><creatorcontrib>Storto, Andrea</creatorcontrib><creatorcontrib>Masina, Simona</creatorcontrib><title>A Quality Control Procedure for Climatological Studies Using Argo Data in the North Pacific Western Boundary Current Region</title><title>Journal of atmospheric and oceanic technology</title><description>A quality control (QC) procedure is developed to estimate monthly mean climatologies from the large Argo dataset (2005–12) over the North Pacific western boundary current region. In addition to the individual QC procedure, which checks for instrumental, transmission, and gross errors, the paper describes and shows the impact of climatological checks (collective QC) on the quality of both processed profiles and resultant climatological distributions. Objective analysis (OA) is applied progressively to produce the gridded climatological fields. The method uses horizontal regional climatological averages defined in five regime-oriented subregions in the Kuroshio area and the Japan Sea. Performing the QC procedure on specific coherent subregions produces improved profiling data and climatological fields because more details about the local hydrodynamics are taken into consideration. Nonrepresentative data and random noises are more effectively rejected by this method, which has value both in defining a climatological mean and identifying outlier data. Assessing with both profiling and coordinated datasets, the agreement is reasonably good (particularly for those areas with abundant observations), but the results (although already smoothed) can capture more detailed or mesoscale features for further regional studies. The method described has the potential to meet future challenges in processing accumulating Argo observations in the coming decades.</description><subject>Bathymetry</subject><subject>Boundary currents</subject><subject>Climatic analysis</subject><subject>Climatological means</subject><subject>Climatology</subject><subject>Data analysis</subject><subject>Data processing</subject><subject>Data transmission</subject><subject>Datasets</subject><subject>Fields</subject><subject>Hydrodynamics</subject><subject>Mesoscale features</subject><subject>Methods</subject><subject>Objective analysis</subject><subject>Oceans</subject><subject>Outliers (statistics)</subject><subject>Procedures</subject><subject>Profiling</subject><subject>Quality control</subject><subject>Regions</subject><subject>Salinity</subject><issn>0739-0572</issn><issn>1520-0426</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNotkM1OwzAQhC0EEqXwANwscQ544zh2jyUtf6qgQCuOlus4ratgF9s5VLw8gXJaaXc0s_MhdAnkGoCzm6fFtHrIJhmwjEDRL4_QAFhOMlLk5TEaEE5HGWE8P0VnMW4JIUChHKDvMX7tVGvTHlfepeBbPA9em7oLBjc-4Kq1nyr51q-tVi1-T11tTcTLaN0aj8Pa44lKCluH08bgZx_SBs-Vto3V-MPEZILDt75ztQp9RBeCcQm_mbX17hydNKqN5uJ_DtHybrroa8xe7h-r8SzTtCxSJgpaGwVgNKElFY0GQZXg3DAGOl8Jqg3NV4zDiPVHAqrWiikqSlqAELWmQ3R18N0F_9X1P8mt74LrI2Uu8jJnhHLeq-Cg0sHHGEwjd6GvHvYSiPxlLP8Yy4kEJn8ZS6A_76JwEg</recordid><startdate>20161201</startdate><enddate>20161201</enddate><creator>Jia, Wenjing</creator><creator>Wang, Dong</creator><creator>Pinardi, Nadia</creator><creator>Simoncelli, Simona</creator><creator>Storto, Andrea</creator><creator>Masina, Simona</creator><general>American Meteorological Society</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TG</scope><scope>7TN</scope><scope>7UA</scope><scope>7XB</scope><scope>88F</scope><scope>88I</scope><scope>8AF</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H8D</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KL.</scope><scope>L.G</scope><scope>L7M</scope><scope>M1Q</scope><scope>M2O</scope><scope>M2P</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>S0X</scope></search><sort><creationdate>20161201</creationdate><title>A Quality Control Procedure for Climatological Studies Using Argo Data in the North Pacific Western Boundary Current Region</title><author>Jia, Wenjing ; Wang, Dong ; Pinardi, Nadia ; Simoncelli, Simona ; Storto, Andrea ; Masina, Simona</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c364t-843dea11ec03638fc183a877e551c2b83ce32b571958fc01adca5a38634188dc3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Bathymetry</topic><topic>Boundary currents</topic><topic>Climatic analysis</topic><topic>Climatological means</topic><topic>Climatology</topic><topic>Data analysis</topic><topic>Data processing</topic><topic>Data transmission</topic><topic>Datasets</topic><topic>Fields</topic><topic>Hydrodynamics</topic><topic>Mesoscale features</topic><topic>Methods</topic><topic>Objective analysis</topic><topic>Oceans</topic><topic>Outliers (statistics)</topic><topic>Procedures</topic><topic>Profiling</topic><topic>Quality control</topic><topic>Regions</topic><topic>Salinity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jia, Wenjing</creatorcontrib><creatorcontrib>Wang, Dong</creatorcontrib><creatorcontrib>Pinardi, Nadia</creatorcontrib><creatorcontrib>Simoncelli, Simona</creatorcontrib><creatorcontrib>Storto, Andrea</creatorcontrib><creatorcontrib>Masina, Simona</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Water Resources Abstracts</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>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Aerospace Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Military Database</collection><collection>Research Library</collection><collection>Science Database</collection><collection>Research Library (Corporate)</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>SIRS Editorial</collection><jtitle>Journal of atmospheric and oceanic technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jia, Wenjing</au><au>Wang, Dong</au><au>Pinardi, Nadia</au><au>Simoncelli, Simona</au><au>Storto, Andrea</au><au>Masina, Simona</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Quality Control Procedure for Climatological Studies Using Argo Data in the North Pacific Western Boundary Current Region</atitle><jtitle>Journal of atmospheric and oceanic technology</jtitle><date>2016-12-01</date><risdate>2016</risdate><volume>33</volume><issue>12</issue><spage>2717</spage><epage>2733</epage><pages>2717-2733</pages><issn>0739-0572</issn><eissn>1520-0426</eissn><abstract>A quality control (QC) procedure is developed to estimate monthly mean climatologies from the large Argo dataset (2005–12) over the North Pacific western boundary current region. In addition to the individual QC procedure, which checks for instrumental, transmission, and gross errors, the paper describes and shows the impact of climatological checks (collective QC) on the quality of both processed profiles and resultant climatological distributions. Objective analysis (OA) is applied progressively to produce the gridded climatological fields. The method uses horizontal regional climatological averages defined in five regime-oriented subregions in the Kuroshio area and the Japan Sea. Performing the QC procedure on specific coherent subregions produces improved profiling data and climatological fields because more details about the local hydrodynamics are taken into consideration. Nonrepresentative data and random noises are more effectively rejected by this method, which has value both in defining a climatological mean and identifying outlier data. Assessing with both profiling and coordinated datasets, the agreement is reasonably good (particularly for those areas with abundant observations), but the results (although already smoothed) can capture more detailed or mesoscale features for further regional studies. The method described has the potential to meet future challenges in processing accumulating Argo observations in the coming decades.</abstract><cop>Boston</cop><pub>American Meteorological Society</pub><doi>10.1175/JTECH-D-15-0140.1</doi><tpages>17</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0739-0572 |
ispartof | Journal of atmospheric and oceanic technology, 2016-12, Vol.33 (12), p.2717-2733 |
issn | 0739-0572 1520-0426 |
language | eng |
recordid | cdi_proquest_journals_2826250377 |
source | American Meteorological Society; EZB-FREE-00999 freely available EZB journals; Alma/SFX Local Collection |
subjects | Bathymetry Boundary currents Climatic analysis Climatological means Climatology Data analysis Data processing Data transmission Datasets Fields Hydrodynamics Mesoscale features Methods Objective analysis Oceans Outliers (statistics) Procedures Profiling Quality control Regions Salinity |
title | A Quality Control Procedure for Climatological Studies Using Argo Data in the North Pacific Western Boundary Current Region |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-28T21%3A30%3A19IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20Quality%20Control%20Procedure%20for%20Climatological%20Studies%20Using%20Argo%20Data%20in%20the%20North%20Pacific%20Western%20Boundary%20Current%20Region&rft.jtitle=Journal%20of%20atmospheric%20and%20oceanic%20technology&rft.au=Jia,%20Wenjing&rft.date=2016-12-01&rft.volume=33&rft.issue=12&rft.spage=2717&rft.epage=2733&rft.pages=2717-2733&rft.issn=0739-0572&rft.eissn=1520-0426&rft_id=info:doi/10.1175/JTECH-D-15-0140.1&rft_dat=%3Cproquest_cross%3E2826250377%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2826250377&rft_id=info:pmid/&rfr_iscdi=true |