Preprints
https://doi.org/10.5194/essd-2023-441
https://doi.org/10.5194/essd-2023-441
10 Jan 2024
 | 10 Jan 2024
Status: this preprint was under review for the journal ESSD but the revision was not accepted.

A dataset of 190 lakes' ice phenology on the Tibetan Plateau extracted from AMSR2 data

Yu Cai, Jingjing Wang, Yao Xiao, Zifei Wang, Xiaoyi Shen, Haili Li, and Chang-Qing Ke

Abstract. The utilization of passive microwave land‒water mixed pixels in extracting lake ice phenology has been underestimated. There are still many small and medium-sized lakes whose ice phenology has not been recorded, especially in regions such as the Tibetan Plateau, for which there are very few in situ observations. In this study, the changing characteristics of mixed pixels during freeze‒thaw processes are discussed. Using air temperature to reduce the seasonal variation in brightness temperature series, Advanced Microwave Scanning Radiometer 2 (AMSR2) data were used to extract the ice phenology of 194 lakes that could represent 78 % of the total lake area on the Tibetan Plateau from September 2012 to August 2022. The lake ice phenology results show high consistency compared with the Moderate Resolution Imaging Spectroradiometer (MODIS)-derived lake ice phenology dataset and demonstrate better performance than the existing AMSR2-derived dataset. This ice phenology dataset covers the largest number of lakes in the Tibetan Plateau region, fills a gap or increases the integrity of ice phenology records for at least one hundred small lakes and provides complete pixel-scale freeze‒thaw processes on the lake surface. The dataset will provide valuable information to the user community about the spatial distribution of and changes in ice cover in lakes, especially small lakes, over the last decade. The dataset is available at https://doi.org/10.11888/Cryos.tpdc.300796 (Cai and Ke, 2023).

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Yu Cai, Jingjing Wang, Yao Xiao, Zifei Wang, Xiaoyi Shen, Haili Li, and Chang-Qing Ke

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2023-441', Anonymous Referee #1, 17 Feb 2024
    • AC2: 'Reply on RC1', Yu Cai, 22 Apr 2024
  • RC2: 'Comment on essd-2023-441', Anonymous Referee #2, 18 Mar 2024
    • AC1: 'Reply on RC2', Yu Cai, 22 Apr 2024

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2023-441', Anonymous Referee #1, 17 Feb 2024
    • AC2: 'Reply on RC1', Yu Cai, 22 Apr 2024
  • RC2: 'Comment on essd-2023-441', Anonymous Referee #2, 18 Mar 2024
    • AC1: 'Reply on RC2', Yu Cai, 22 Apr 2024
Yu Cai, Jingjing Wang, Yao Xiao, Zifei Wang, Xiaoyi Shen, Haili Li, and Chang-Qing Ke

Data sets

Lake ice phenology on the Tibetan Plateau extracted from AMSR2 data (2013-2022) Yu Cai and Chang-Qing Ke https://doi.org/10.11888/Cryos.tpdc.300796

Yu Cai, Jingjing Wang, Yao Xiao, Zifei Wang, Xiaoyi Shen, Haili Li, and Chang-Qing Ke

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Short summary
In this study, we re-explored the potential of passive microwaves in extracting lake ice freeze-thaw events. Brightness temperature and air temperature data were used to extract freeze-up and break-up records of 194 lakes on the Tibetan Plateau, providing complete lake ice records for a large number of small and medium-sized lakes for the first time. The dataset will provide valuable data for users interested in lake ice cover on the Tibetan Plateau over the last decade.
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