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...
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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 |
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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 & Geoastrophysical Abstracts</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & 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> |
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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 |
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