Articles | Volume 16, issue 8
https://doi.org/10.5194/essd-16-3795-2024
https://doi.org/10.5194/essd-16-3795-2024
Data description paper
 | 
27 Aug 2024
Data description paper |  | 27 Aug 2024

Generation of global 1 km all-weather instantaneous and daily mean land surface temperatures from MODIS data

Bing Li, Shunlin Liang, Han Ma, Guanpeng Dong, Xiaobang Liu, Tao He, and Yufang Zhang

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2024-16', Anonymous Referee #1, 20 Mar 2024
    • AC1: 'Reply on RC1', Bing Li, 18 May 2024
  • RC2: 'Comment on essd-2024-16', Anonymous Referee #2, 22 May 2024
    • AC2: 'Reply on RC2', Bing Li, 29 May 2024

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Bing Li on behalf of the Authors (18 Jun 2024)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (25 Jun 2024) by Jing Wei
RR by Anonymous Referee #1 (26 Jun 2024)
RR by Anonymous Referee #2 (01 Jul 2024)
ED: Publish subject to minor revisions (review by editor) (03 Jul 2024) by Jing Wei
AR by Bing Li on behalf of the Authors (05 Jul 2024)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (12 Jul 2024) by Jing Wei
AR by Bing Li on behalf of the Authors (14 Jul 2024)  Manuscript 
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Short summary
This study describes 1 km all-weather instantaneous and daily mean land surface temperature (LST) datasets on the global scale during 2000–2020. It is the first attempt to synergistically estimate all-weather instantaneous and daily mean LST data on a long  global-scale time series. The generated datasets were evaluated by the observations from in situ stations and other LST datasets, and the evaluation indicated that the dataset is sufficiently reliable.
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