The Contribution of United States Aircraft Reconnaissance Data to the China Meteorological Administration Tropical Cyclone Intensity Data: An Evaluation of Homogeneity

This paper investigates the homogeneity of United States aircraft reconnaissance data and the impact of these data on the homogeneity of the tropical cyclone (TC) best track data for the seasons 1949–1987 generated by the China Meteorological Administration (CMA). The evaluation of the reconnaissanc...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Advances in atmospheric sciences 2024-04, Vol.41 (4), p.639-654
Hauptverfasser: Ying, Ming, Lu, Xiaoqin
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 654
container_issue 4
container_start_page 639
container_title Advances in atmospheric sciences
container_volume 41
creator Ying, Ming
Lu, Xiaoqin
description This paper investigates the homogeneity of United States aircraft reconnaissance data and the impact of these data on the homogeneity of the tropical cyclone (TC) best track data for the seasons 1949–1987 generated by the China Meteorological Administration (CMA). The evaluation of the reconnaissance data shows that the minimum central sea level pressure (MCP) data are relatively homogeneous, whereas the maximum sustained wind (MSW) data show both overestimations and spurious abrupt changes. Statistical comparisons suggest that both the reconnaissance MCP and MSW were well incorporated into the CMA TC best track dataset. Although no spurious abrupt changes were evident in the reconnaissance-related best track MCP data, two spurious changepoints were identified in the remainder of the best-track MCP data. Furthermore, the influence of the reconnaissance MSWs seems to extend to the best track MSWs unrelated to reconnaissance, which might reflect the optimistic confidence in making higher estimates due to the overestimated extreme wind “observations”. In addition, the overestimation of either the reconnaissance MSWs or the best track MSWs was greater during the early decades compared to later decades, which reflects the important influence of reconnaissance data on the CMA TC best track dataset. The wind–pressure relationship (WPR) used in the CMA TC best track dataset is also evaluated and is found to overestimate the MSW, which may lead to inhomogeneity within the dataset between the aircraft reconnaissance era and the satellite era.
doi_str_mv 10.1007/s00376-023-3040-7
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2937813344</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2937813344</sourcerecordid><originalsourceid>FETCH-LOGICAL-c268t-732bdd6d5424f76bc9b65f33a3eddab519b4c571d71f1abc7f96661e43062df83</originalsourceid><addsrcrecordid>eNp1kctKAzEUhoMoWC8P4C7gejSZzCQz7kq9VFAEreuQSU5qZJrUJBX6RL6m01Zx5erA4fu_c-BH6IySC0qIuEyEMMELUrKCkYoUYg-NaMNp0daM7aMRKWte0JqRQ3SU0vtAt6yhI_Q1ewM8CT5H162yCx4Hi1-9y2DwS1YZEh67qKOyGT-DDt4rl5LyGvC1ygrngPPG8Oa8wo-QIcTQh7nTqsdjs3DepRzVVjyLYbndT9a6Dx7wvc_gk8vrreoKjz2--VT9Sv3-MQ2LMAcPA3KCDqzqE5z-zGP0enszm0yLh6e7-8n4odAlb3IhWNkZw01dlZUVvNNtx2vLmGJgjOpq2naVrgU1glqqOi1syzmnUDHCS2MbdozOd95lDB8rSFm-h1X0w0lZtkw0lLGqGii6o3QMKUWwchndQsW1pERu-pC7PuTQh9z0IcWQKXeZNLB-DvHP_H_oG_6JkNE</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2937813344</pqid></control><display><type>article</type><title>The Contribution of United States Aircraft Reconnaissance Data to the China Meteorological Administration Tropical Cyclone Intensity Data: An Evaluation of Homogeneity</title><source>SpringerNature Journals</source><source>Alma/SFX Local Collection</source><creator>Ying, Ming ; Lu, Xiaoqin</creator><creatorcontrib>Ying, Ming ; Lu, Xiaoqin</creatorcontrib><description>This paper investigates the homogeneity of United States aircraft reconnaissance data and the impact of these data on the homogeneity of the tropical cyclone (TC) best track data for the seasons 1949–1987 generated by the China Meteorological Administration (CMA). The evaluation of the reconnaissance data shows that the minimum central sea level pressure (MCP) data are relatively homogeneous, whereas the maximum sustained wind (MSW) data show both overestimations and spurious abrupt changes. Statistical comparisons suggest that both the reconnaissance MCP and MSW were well incorporated into the CMA TC best track dataset. Although no spurious abrupt changes were evident in the reconnaissance-related best track MCP data, two spurious changepoints were identified in the remainder of the best-track MCP data. Furthermore, the influence of the reconnaissance MSWs seems to extend to the best track MSWs unrelated to reconnaissance, which might reflect the optimistic confidence in making higher estimates due to the overestimated extreme wind “observations”. In addition, the overestimation of either the reconnaissance MSWs or the best track MSWs was greater during the early decades compared to later decades, which reflects the important influence of reconnaissance data on the CMA TC best track dataset. The wind–pressure relationship (WPR) used in the CMA TC best track dataset is also evaluated and is found to overestimate the MSW, which may lead to inhomogeneity within the dataset between the aircraft reconnaissance era and the satellite era.</description><identifier>ISSN: 0256-1530</identifier><identifier>EISSN: 1861-9533</identifier><identifier>DOI: 10.1007/s00376-023-3040-7</identifier><language>eng</language><publisher>Heidelberg: Science Press</publisher><subject>Aircraft ; Atmospheric Sciences ; Cyclones ; Datasets ; Earth and Environmental Science ; Earth Sciences ; Geophysics/Geodesy ; Homogeneity ; Hurricanes ; Inhomogeneity ; Meteorology ; Original Paper ; Reconnaissance aircraft ; Sea level pressure ; Tropical cyclone intensities ; Tropical cyclones ; Wind</subject><ispartof>Advances in atmospheric sciences, 2024-04, Vol.41 (4), p.639-654</ispartof><rights>Institute of Atmospheric Physics/Chinese Academy of Sciences, and Science Press 2024</rights><rights>Institute of Atmospheric Physics/Chinese Academy of Sciences, and Science Press 2024.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c268t-732bdd6d5424f76bc9b65f33a3eddab519b4c571d71f1abc7f96661e43062df83</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00376-023-3040-7$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00376-023-3040-7$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>315,781,785,27929,27930,41493,42562,51324</link.rule.ids></links><search><creatorcontrib>Ying, Ming</creatorcontrib><creatorcontrib>Lu, Xiaoqin</creatorcontrib><title>The Contribution of United States Aircraft Reconnaissance Data to the China Meteorological Administration Tropical Cyclone Intensity Data: An Evaluation of Homogeneity</title><title>Advances in atmospheric sciences</title><addtitle>Adv. Atmos. Sci</addtitle><description>This paper investigates the homogeneity of United States aircraft reconnaissance data and the impact of these data on the homogeneity of the tropical cyclone (TC) best track data for the seasons 1949–1987 generated by the China Meteorological Administration (CMA). The evaluation of the reconnaissance data shows that the minimum central sea level pressure (MCP) data are relatively homogeneous, whereas the maximum sustained wind (MSW) data show both overestimations and spurious abrupt changes. Statistical comparisons suggest that both the reconnaissance MCP and MSW were well incorporated into the CMA TC best track dataset. Although no spurious abrupt changes were evident in the reconnaissance-related best track MCP data, two spurious changepoints were identified in the remainder of the best-track MCP data. Furthermore, the influence of the reconnaissance MSWs seems to extend to the best track MSWs unrelated to reconnaissance, which might reflect the optimistic confidence in making higher estimates due to the overestimated extreme wind “observations”. In addition, the overestimation of either the reconnaissance MSWs or the best track MSWs was greater during the early decades compared to later decades, which reflects the important influence of reconnaissance data on the CMA TC best track dataset. The wind–pressure relationship (WPR) used in the CMA TC best track dataset is also evaluated and is found to overestimate the MSW, which may lead to inhomogeneity within the dataset between the aircraft reconnaissance era and the satellite era.</description><subject>Aircraft</subject><subject>Atmospheric Sciences</subject><subject>Cyclones</subject><subject>Datasets</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Geophysics/Geodesy</subject><subject>Homogeneity</subject><subject>Hurricanes</subject><subject>Inhomogeneity</subject><subject>Meteorology</subject><subject>Original Paper</subject><subject>Reconnaissance aircraft</subject><subject>Sea level pressure</subject><subject>Tropical cyclone intensities</subject><subject>Tropical cyclones</subject><subject>Wind</subject><issn>0256-1530</issn><issn>1861-9533</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp1kctKAzEUhoMoWC8P4C7gejSZzCQz7kq9VFAEreuQSU5qZJrUJBX6RL6m01Zx5erA4fu_c-BH6IySC0qIuEyEMMELUrKCkYoUYg-NaMNp0daM7aMRKWte0JqRQ3SU0vtAt6yhI_Q1ewM8CT5H162yCx4Hi1-9y2DwS1YZEh67qKOyGT-DDt4rl5LyGvC1ygrngPPG8Oa8wo-QIcTQh7nTqsdjs3DepRzVVjyLYbndT9a6Dx7wvc_gk8vrreoKjz2--VT9Sv3-MQ2LMAcPA3KCDqzqE5z-zGP0enszm0yLh6e7-8n4odAlb3IhWNkZw01dlZUVvNNtx2vLmGJgjOpq2naVrgU1glqqOi1syzmnUDHCS2MbdozOd95lDB8rSFm-h1X0w0lZtkw0lLGqGii6o3QMKUWwchndQsW1pERu-pC7PuTQh9z0IcWQKXeZNLB-DvHP_H_oG_6JkNE</recordid><startdate>20240401</startdate><enddate>20240401</enddate><creator>Ying, Ming</creator><creator>Lu, Xiaoqin</creator><general>Science Press</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope></search><sort><creationdate>20240401</creationdate><title>The Contribution of United States Aircraft Reconnaissance Data to the China Meteorological Administration Tropical Cyclone Intensity Data: An Evaluation of Homogeneity</title><author>Ying, Ming ; Lu, Xiaoqin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c268t-732bdd6d5424f76bc9b65f33a3eddab519b4c571d71f1abc7f96661e43062df83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Aircraft</topic><topic>Atmospheric Sciences</topic><topic>Cyclones</topic><topic>Datasets</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Geophysics/Geodesy</topic><topic>Homogeneity</topic><topic>Hurricanes</topic><topic>Inhomogeneity</topic><topic>Meteorology</topic><topic>Original Paper</topic><topic>Reconnaissance aircraft</topic><topic>Sea level pressure</topic><topic>Tropical cyclone intensities</topic><topic>Tropical cyclones</topic><topic>Wind</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ying, Ming</creatorcontrib><creatorcontrib>Lu, Xiaoqin</creatorcontrib><collection>CrossRef</collection><collection>Meteorological &amp; Geoastrophysical Abstracts</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy &amp; Non-Living Resources</collection><collection>Meteorological &amp; Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) Professional</collection><jtitle>Advances in atmospheric sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ying, Ming</au><au>Lu, Xiaoqin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Contribution of United States Aircraft Reconnaissance Data to the China Meteorological Administration Tropical Cyclone Intensity Data: An Evaluation of Homogeneity</atitle><jtitle>Advances in atmospheric sciences</jtitle><stitle>Adv. Atmos. Sci</stitle><date>2024-04-01</date><risdate>2024</risdate><volume>41</volume><issue>4</issue><spage>639</spage><epage>654</epage><pages>639-654</pages><issn>0256-1530</issn><eissn>1861-9533</eissn><abstract>This paper investigates the homogeneity of United States aircraft reconnaissance data and the impact of these data on the homogeneity of the tropical cyclone (TC) best track data for the seasons 1949–1987 generated by the China Meteorological Administration (CMA). The evaluation of the reconnaissance data shows that the minimum central sea level pressure (MCP) data are relatively homogeneous, whereas the maximum sustained wind (MSW) data show both overestimations and spurious abrupt changes. Statistical comparisons suggest that both the reconnaissance MCP and MSW were well incorporated into the CMA TC best track dataset. Although no spurious abrupt changes were evident in the reconnaissance-related best track MCP data, two spurious changepoints were identified in the remainder of the best-track MCP data. Furthermore, the influence of the reconnaissance MSWs seems to extend to the best track MSWs unrelated to reconnaissance, which might reflect the optimistic confidence in making higher estimates due to the overestimated extreme wind “observations”. In addition, the overestimation of either the reconnaissance MSWs or the best track MSWs was greater during the early decades compared to later decades, which reflects the important influence of reconnaissance data on the CMA TC best track dataset. The wind–pressure relationship (WPR) used in the CMA TC best track dataset is also evaluated and is found to overestimate the MSW, which may lead to inhomogeneity within the dataset between the aircraft reconnaissance era and the satellite era.</abstract><cop>Heidelberg</cop><pub>Science Press</pub><doi>10.1007/s00376-023-3040-7</doi><tpages>16</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0256-1530
ispartof Advances in atmospheric sciences, 2024-04, Vol.41 (4), p.639-654
issn 0256-1530
1861-9533
language eng
recordid cdi_proquest_journals_2937813344
source SpringerNature Journals; Alma/SFX Local Collection
subjects Aircraft
Atmospheric Sciences
Cyclones
Datasets
Earth and Environmental Science
Earth Sciences
Geophysics/Geodesy
Homogeneity
Hurricanes
Inhomogeneity
Meteorology
Original Paper
Reconnaissance aircraft
Sea level pressure
Tropical cyclone intensities
Tropical cyclones
Wind
title The Contribution of United States Aircraft Reconnaissance Data to the China Meteorological Administration Tropical Cyclone Intensity Data: An Evaluation of Homogeneity
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-16T05%3A59%3A58IST&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=The%20Contribution%20of%20United%20States%20Aircraft%20Reconnaissance%20Data%20to%20the%20China%20Meteorological%20Administration%20Tropical%20Cyclone%20Intensity%20Data:%20An%20Evaluation%20of%20Homogeneity&rft.jtitle=Advances%20in%20atmospheric%20sciences&rft.au=Ying,%20Ming&rft.date=2024-04-01&rft.volume=41&rft.issue=4&rft.spage=639&rft.epage=654&rft.pages=639-654&rft.issn=0256-1530&rft.eissn=1861-9533&rft_id=info:doi/10.1007/s00376-023-3040-7&rft_dat=%3Cproquest_cross%3E2937813344%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=2937813344&rft_id=info:pmid/&rfr_iscdi=true