Intercalibration of FY-4A AGRI Thermal Infrared Channels against AHI Channels Using the Double Difference Method
This letter addresses the intercalibration of the thermal infrared channels 11 (8.0~9.0 μm), 12 (10.3~11.3 μm), 13 (11.5~12.5 μm) and 14 (13.2~13.8 μm) of the Advanced Geostationary Radiation Imager (AGRI) on Chinese Fengyun 4A (FY-4A) satellite against the Advanced Himawari Imager (AHI) on the Hima...
Saved in:
Published in | IEEE geoscience and remote sensing letters Vol. 20; p. 1 |
---|---|
Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Piscataway
IEEE
01.01.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | This letter addresses the intercalibration of the thermal infrared channels 11 (8.0~9.0 μm), 12 (10.3~11.3 μm), 13 (11.5~12.5 μm) and 14 (13.2~13.8 μm) of the Advanced Geostationary Radiation Imager (AGRI) on Chinese Fengyun 4A (FY-4A) satellite against the Advanced Himawari Imager (AHI) on the Himawari 8 using the Double Difference (DD) method with the data in January and July of 2020. To transfer the radiometric calibration from AHI to FY-4A AGRI, an accurate thermal infrared radiative transfer model and intercalibration equations are constructed. The results show that the AGRI channel 12 is well calibrated, and keeps stable in the two months. However, in other AGRI thermal infrared channels, radiometric calibration biases are obviously observed, especially the AGRI channel 11, in which the calibration biases vary by hemisphere and month. The observations in the AGRI channels 13 and 14 are about 0.83 K and 0.50 K underestimated, respectively. In the AGRI channel 11, the observations are averagely 2.36 K and 4.08 K overestimated in North hemisphere and South hemisphere, respectively. Moreover, in South hemisphere, the observations in the AGRI channel 11 in the July are averagely 0.55 K warmer than those in the January. The intercalibration coefficients were obtained by linear regression, and finally the radiometric calibration biases in the AGRI thermal infrared channels were successfully removed. |
---|---|
AbstractList | This letter addresses the intercalibration of the thermal infrared (TIR) channels 11 (8.0–9.0 [Formula Omitted]), 12 (10.3–11.3 [Formula Omitted]), 13 (11.5–[Formula Omitted]), and 14 (13.2–13.8 [Formula Omitted]) of the Advanced Geostationary Radiation Imager (AGRI) on Chinese Fengyun 4A (FY-4A) satellite against the Advanced Himawari Imager (AHI) on the Himawari 8 using the double difference (DD) method with the data in January and July of 2020. To transfer the radiometric calibration from AHI to FY-4A AGRI, an accurate TIR radiative transfer model and intercalibration equations are constructed. The results show that AGRI channel 12 is well calibrated and keeps stable in the two months. However, in other AGRI TIR channels, radiometric calibration biases are obviously observed, especially AGRI channel 11, in which the calibration biases vary by hemisphere and month. The observations in AGRI channels 13 and 14 are about 0.83 and 0.50 K underestimated, respectively. In AGRI channel 11, the observations are averagely 2.36 and 4.08 K overestimated in Northern Hemisphere and Southern Hemisphere, respectively. Moreover, in Southern Hemisphere, the observations in AGRI channel 11 in July are averagely 0.55 K warmer than those in January. The intercalibration coefficients were obtained by linear regression, and finally, the radiometric calibration biases in the AGRI TIR channels were successfully removed. This letter addresses the intercalibration of the thermal infrared channels 11 (8.0~9.0 μm), 12 (10.3~11.3 μm), 13 (11.5~12.5 μm) and 14 (13.2~13.8 μm) of the Advanced Geostationary Radiation Imager (AGRI) on Chinese Fengyun 4A (FY-4A) satellite against the Advanced Himawari Imager (AHI) on the Himawari 8 using the Double Difference (DD) method with the data in January and July of 2020. To transfer the radiometric calibration from AHI to FY-4A AGRI, an accurate thermal infrared radiative transfer model and intercalibration equations are constructed. The results show that the AGRI channel 12 is well calibrated, and keeps stable in the two months. However, in other AGRI thermal infrared channels, radiometric calibration biases are obviously observed, especially the AGRI channel 11, in which the calibration biases vary by hemisphere and month. The observations in the AGRI channels 13 and 14 are about 0.83 K and 0.50 K underestimated, respectively. In the AGRI channel 11, the observations are averagely 2.36 K and 4.08 K overestimated in North hemisphere and South hemisphere, respectively. Moreover, in South hemisphere, the observations in the AGRI channel 11 in the July are averagely 0.55 K warmer than those in the January. The intercalibration coefficients were obtained by linear regression, and finally the radiometric calibration biases in the AGRI thermal infrared channels were successfully removed. |
Author | Xin, Yi-Chun Jiang, Geng-Ming |
Author_xml | – sequence: 1 givenname: Geng-Ming orcidid: 0000-0002-8022-1959 surname: Jiang fullname: Jiang, Geng-Ming organization: School of Information Science and Technology, Key Laboratory for Information Science of Electromagnetic Waves (Ministry of Education), Fudan University, Shanghai, China – sequence: 2 givenname: Yi-Chun surname: Xin fullname: Xin, Yi-Chun organization: School of Information Science and Technology, Key Laboratory for Information Science of Electromagnetic Waves (Ministry of Education), Fudan University, Shanghai, China |
BookMark | eNp9kEFLwzAUx4NMcJt-APES8NzZJE2bHMd0W2EizA30VNL2dcvo0plkB7-9rRsKHjy9P4__7z34DVDPNAYQuiXhiJBQPixmy9cRDSkdMcoIFfIC9QnnIgh5QnpdjnjApXi7QgPndmFIIyGSPjqkxoMtVK1zq7xuDG4qPH0PojEez5YpXm3B7lWNU1NZZaHEk60yBmqH1UZp4zwez9Pf5dpps8F-C_ixOeZ1O3RVgQVTAH4Gv23Ka3RZqdrBzXkO0Xr6tJrMg8XLLJ2MF0FBKfMBjUmpcoh4IiiBhOciF6zipCAFlWXES8ZzBkyKsIhLQhlNVEw4tCHnkjLFhuj-dPdgm48jOJ_tmqM17cuMJknEWERj1raSU6uwjXMWqqzQ_tuDt0rXGQmzTm_W6c06vdlZb0uSP-TB6r2yn_8ydydGA8BPX0oZR4ywL42WhhQ |
CODEN | IGRSBY |
CitedBy_id | crossref_primary_10_1109_TGRS_2024_3385657 |
Cites_doi | 10.1016/S0034-4257(98)00045-5 10.1109/jstars.2021.3104829 10.1029/2010JD014988 10.1175/2007jamc1590.1 10.1016/j.rse.2006.07.015 10.11834/jrs.20198235 10.1109/IGARSS.2017.8127928 10.1109/JSTARS.2018.2801305 10.1364/AO.36.002609 10.1109/TGRS.2013.2295260 10.1109/ACCESS.2020.2984090 10.1109/tgrs.2021.3086801 10.1109/JSTARS.2021.3104829 10.1080/01431160802392638 10.1109/TGRS.2022.3215806 10.1109/tgrs.2021.3111975 |
ContentType | Journal Article |
Copyright | Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023 |
Copyright_xml | – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023 |
DBID | 97E RIA RIE AAYXX CITATION 7SC 7SP 7TG 7UA 8FD C1K F1W FR3 H8D H96 JQ2 KL. KR7 L.G L7M L~C L~D |
DOI | 10.1109/LGRS.2022.3231289 |
DatabaseName | IEEE All-Society Periodicals Package (ASPP) 2005–Present IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Electronic Library (IEL) CrossRef Computer and Information Systems Abstracts Electronics & Communications Abstracts Meteorological & Geoastrophysical Abstracts Water Resources Abstracts Technology Research Database Environmental Sciences and Pollution Management ASFA: Aquatic Sciences and Fisheries Abstracts Engineering Research Database Aerospace Database Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources ProQuest Computer Science Collection Meteorological & Geoastrophysical Abstracts - Academic Civil Engineering Abstracts Aquatic Science & Fisheries Abstracts (ASFA) Professional Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional |
DatabaseTitle | CrossRef Civil Engineering Abstracts Aquatic Science & Fisheries Abstracts (ASFA) Professional Technology Research Database Computer and Information Systems Abstracts – Academic Electronics & Communications Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts Water Resources Abstracts Environmental Sciences and Pollution Management Computer and Information Systems Abstracts Professional Aerospace Database Meteorological & Geoastrophysical Abstracts Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources ASFA: Aquatic Sciences and Fisheries Abstracts Engineering Research Database Advanced Technologies Database with Aerospace Meteorological & Geoastrophysical Abstracts - Academic |
DatabaseTitleList | Civil Engineering Abstracts |
Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/ sourceTypes: Publisher |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Geography Geology |
EISSN | 1558-0571 |
EndPage | 1 |
ExternalDocumentID | 10_1109_LGRS_2022_3231289 9996431 |
Genre | orig-research |
GeographicLocations | Southern Hemisphere |
GeographicLocations_xml | – name: Southern Hemisphere |
GrantInformation_xml | – fundername: National Natural Science Foundation of China grantid: 41871222 funderid: 10.13039/501100001809 |
GroupedDBID | 0R~ 29I 4.4 5GY 6IK 97E AAJGR AARMG AASAJ AAWTH ABAZT ABQJQ ABVLG ACGFO ACIWK AENEX AFRAH AGQYO AHBIQ AKJIK AKQYR ALMA_UNASSIGNED_HOLDINGS ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ CS3 EBS HZ~ H~9 IFIPE IPLJI JAVBF LAI M43 O9- OCL P2P RIA RIE RNS ~02 5VS AAYXX AETIX AGSQL AIBXA CITATION EJD RIG 7SC 7SP 7TG 7UA 8FD C1K F1W FR3 H8D H96 JQ2 KL. KR7 L.G L7M L~C L~D |
ID | FETCH-LOGICAL-c223t-261dabe457821e75b8b83f51c1c29d45d35b3e3980c6d12327a615e232b5923a3 |
IEDL.DBID | RIE |
ISSN | 1545-598X |
IngestDate | Mon Jun 30 08:10:17 EDT 2025 Tue Jul 01 03:45:53 EDT 2025 Thu Apr 24 23:03:35 EDT 2025 Wed Aug 27 02:29:10 EDT 2025 |
IsPeerReviewed | true |
IsScholarly | true |
Language | English |
License | https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html https://doi.org/10.15223/policy-029 https://doi.org/10.15223/policy-037 |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c223t-261dabe457821e75b8b83f51c1c29d45d35b3e3980c6d12327a615e232b5923a3 |
Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
ORCID | 0000-0002-8022-1959 |
PQID | 2774334263 |
PQPubID | 75725 |
PageCount | 1 |
ParticipantIDs | crossref_primary_10_1109_LGRS_2022_3231289 crossref_citationtrail_10_1109_LGRS_2022_3231289 ieee_primary_9996431 proquest_journals_2774334263 |
ProviderPackageCode | CITATION AAYXX |
PublicationCentury | 2000 |
PublicationDate | 2023-01-01 |
PublicationDateYYYYMMDD | 2023-01-01 |
PublicationDate_xml | – month: 01 year: 2023 text: 2023-01-01 day: 01 |
PublicationDecade | 2020 |
PublicationPlace | Piscataway |
PublicationPlace_xml | – name: Piscataway |
PublicationTitle | IEEE geoscience and remote sensing letters |
PublicationTitleAbbrev | LGRS |
PublicationYear | 2023 |
Publisher | IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher_xml | – name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
References | ref13 ref12 ref15 ref14 ref11 ref10 ref2 ref1 ref17 ref16 ref8 ref7 ref9 ref4 ref3 ref6 ref5 |
References_xml | – ident: ref12 doi: 10.1016/S0034-4257(98)00045-5 – ident: ref9 doi: 10.1109/jstars.2021.3104829 – ident: ref7 doi: 10.1029/2010JD014988 – ident: ref15 doi: 10.1175/2007jamc1590.1 – ident: ref11 doi: 10.1016/j.rse.2006.07.015 – ident: ref6 doi: 10.11834/jrs.20198235 – ident: ref2 doi: 10.1109/IGARSS.2017.8127928 – ident: ref5 doi: 10.1109/JSTARS.2018.2801305 – ident: ref14 doi: 10.1364/AO.36.002609 – ident: ref16 doi: 10.1109/TGRS.2013.2295260 – ident: ref8 doi: 10.1109/ACCESS.2020.2984090 – ident: ref10 doi: 10.1109/tgrs.2021.3086801 – ident: ref17 doi: 10.1109/JSTARS.2021.3104829 – ident: ref4 doi: 10.1080/01431160802392638 – ident: ref13 doi: 10.1109/TGRS.2022.3215806 – ident: ref1 doi: 10.1109/tgrs.2021.3111975 – ident: ref3 doi: 10.1109/JSTARS.2018.2801305 |
SSID | ssj0024887 |
Score | 2.356866 |
Snippet | This letter addresses the intercalibration of the thermal infrared channels 11 (8.0~9.0 μm), 12 (10.3~11.3 μm), 13 (11.5~12.5 μm) and 14 (13.2~13.8 μm) of the... This letter addresses the intercalibration of the thermal infrared (TIR) channels 11 (8.0–9.0 [Formula Omitted]), 12 (10.3–11.3 [Formula Omitted]), 13... |
SourceID | proquest crossref ieee |
SourceType | Aggregation Database Enrichment Source Index Database Publisher |
StartPage | 1 |
SubjectTerms | AHI Calibration Channels Coefficients double difference method FY-4A AGRI Intercalibration Northern Hemisphere Radiation Radiative transfer Satellite imagery Southern Hemisphere thermal infrared channels |
Title | Intercalibration of FY-4A AGRI Thermal Infrared Channels against AHI Channels Using the Double Difference Method |
URI | https://ieeexplore.ieee.org/document/9996431 https://www.proquest.com/docview/2774334263 |
Volume | 20 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1Lb9NAEB6VShVcoA8QoS3aAyfEprZ3ndjHCJFH1XAorRRO1uzDbUXkVCU5lF_fmfUmRQUhTl5Zu9JK33j3m_HMfAAflHXYtx6lcaWRGrWRRVZriagI7szUJgRzpl9740t9OstnW_BpUwvjvQ_JZ77Lw_Av3y3sikNlJ0zONRdNPyPHra3VeuyrVwQxPGYEMi-LWfyDmSblydno_Bt5glnWVcRmMlZ0_-0OCqIqf5zE4XoZvoLpemNtVsmP7mppuvbXk56N_7vzXXgZeaYYtIaxB1u-2YfnUfL8-n4fdkZB0_f-AG5DVJCwYs-ZcRKLWgy_Sz0Qg9H5RJAl0ek9F5OmvuN0dcEVCQ3dqQKv8IbopRiMJ48vQxKCIF4piJybOT2iBov1Yhr0ql_D5fDLxeexjEIM0hJ7WEryshwar7n1fer7uSlMoeo8tanNSqdzp3KjvCqLxPYcc7Q-ElHyNDA5EUhUb2C7WTT-LYhegmQcDhUWjiyjNtqqAvs-R5Om2MMOJGtoKhu7lLNYxrwK3kpSVoxmxWhWEc0OfNwsuW1bdPxr8gGjs5kYgenA0Rr_Kn7EP6uMqLFS3NH-3d9XHcILVp9vIzJHsL28W_lj4ihL8z4Y5wP_7uHk |
linkProvider | IEEE |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1NTxsxEB0hKkQvpUCrptDiQ09VHXbXdrJ7jBD5gIQDBSk9rfy1tGq0QTQ50F_fGa8TUKkqTmutbMnSm_W88c7MA_gkrNNd6zU3rjBcaml4nlWSay0Q7sxUJlzmTC46w2t5NlXTDfiyroXx3ofkM9-mYfiX7-Z2SVdlx0TOJRVNv0C_r9KmWuuhs14e5PCIE3BV5NP4DzNNiuPx4PIrxoJZ1hbIZzLSdH_khYKsypOzODiY_g5MVltr8kp-tpcL07a__-ra-Ny9v4ZXkWmyXmMau7Dh6z3YjqLn3-_3YGsQVH3v9-E23AsiWhQ7E1JsXrH-Ny57rDe4HDG0JTy_Z2xUV3eUsM6oJqFGr8r0jf6BBJP1hqOHlyENgSGzZEjPzQwfUYXFejYJitVv4Lp_enUy5FGKgVvkDwuOcZbTxktqfp_6rjK5yUWlUpvarHBSOaGM8KLIE9txxNK6GqmSx4FRSCG1eAub9bz274B1Eo3m4bTQuUPbqIy0Itddr7RJU93RLUhW0JQ29iknuYxZGeKVpCgJzZLQLCOaLfi8XnLbNOn43-R9Qmc9MQLTgsMV_mX8jH-VGZJjIain_ft_rzqC7eHVZFyORxfnB_CStOib-5lD2FzcLf0HZCwL8zEY6h_zD-Ut |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Intercalibration+of+FY-4A+AGRI+Thermal+Infrared+Channels+against+AHI+Channels+Using+the+Double+Difference+Method&rft.jtitle=IEEE+geoscience+and+remote+sensing+letters&rft.au=Jiang%2C+Geng-Ming&rft.au=Xin%2C+Yi-Chun&rft.date=2023-01-01&rft.pub=IEEE&rft.issn=1545-598X&rft.spage=1&rft.epage=1&rft_id=info:doi/10.1109%2FLGRS.2022.3231289&rft.externalDocID=9996431 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1545-598X&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1545-598X&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1545-598X&client=summon |