Preprints
https://doi.org/10.5194/essd-2023-250
https://doi.org/10.5194/essd-2023-250
27 Nov 2023
 | 27 Nov 2023
Status: this preprint is currently under review for the journal ESSD.

MODIS Daily Cloud-gap-filled Fractional Snow Cover Dataset of the Asian Water Tower Region (2000–2022)

Fangbo Pan, Lingmei Jiang, Gongxue Wang, Jinmei Pan, Jinyu Huang, Cheng Zhang, Huizhen Cui, Jiangwei Yang, Zhaojun Zheng, Shengli Wu, and Jiancheng Shi

Abstract. Accurate long-term daily Cloud-gap-filled fractional snow cover products are essential for climate change and snow hydrological studies in the Asia Water Tower (AWT) region, but existing Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover products are not sufficient. In this study, the multiple endmember spectral mixture analysis algorithm based on automatic endmember extraction (MESMA-AGE) and the multistep spatiotemporal interpolation algorithm (MSTI) are used to produce the MODIS daily cloud-gap-filled fractional snow cover product over the AWT region (AWT MODIS FSC). The AWT MODIS FSC product have a spatial resolution of 0.005°, and spans from 2000 to 2022. The 2745 scenes of Landsat-8 images are used for the areal scale accuracy assessment. The fractional snow cover accuracy metrics, including coefficient of determination (R2), root mean squared error (RMSE), and mean absolute error (MAE) are 0.80, 0.16 and 0.10, respectively. The binarized identification accuracy metrics, including overall accuracy (OA), producer’s accuracy (PA), and user’s accuracy (UA), are 95.17 %, 97.34 % and 97.59 %, respectively. Snow depth data observed at 175 meteorological stations are used to evaluate accuracy at point scale, yielding the following accuracy metrics: an OA of 93.26 %, a PA of 84.41 %, a UA of 82.14 %, and a cohen’s kappa (CK) value of 0.79. Snow depth observations from meteorological stations are also used to assess the fractional snow cover resulting from different weather conditions, with an OA of 95.36 % (88.96 %), a PA of 87.75 % (82.26 %), a UA of 86.86 % (78.86 %) and a CK of 0.84 (0.72) under the MODIS clear sky observations (spatiotemporal reconstruction based on the MSTI algorithm). The AWT MODIS FSC product can provide quantitative spatial distribution information of snowpack for mountain hydrological models, land surface models, and numerical weather prediction in the Asia Water Tower region. This dataset is freely available from the National Tibetan Plateau Data Centre at https://doi.org/10.11888/Cryos.tpdc.272503 (Jiang et al., 2022) or from the Zenodo platform at https://zenodo.org/doi/10.5281/zenodo.10005826.

Fangbo Pan, Lingmei Jiang, Gongxue Wang, Jinmei Pan, Jinyu Huang, Cheng Zhang, Huizhen Cui, Jiangwei Yang, Zhaojun Zheng, Shengli Wu, and Jiancheng Shi

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2023-250', Anonymous Referee #1, 08 Jan 2024
  • RC2: 'Comment on essd-2023-250', Anonymous Referee #2, 06 Feb 2024
Fangbo Pan, Lingmei Jiang, Gongxue Wang, Jinmei Pan, Jinyu Huang, Cheng Zhang, Huizhen Cui, Jiangwei Yang, Zhaojun Zheng, Shengli Wu, and Jiancheng Shi

Data sets

MODIS Daily Cloud-gap-filled Fractional Snow Cover Dataset of the Asian Water Tower Region (2000-2022) Lingmei Jiang, Fangbo Pan, Gongxue Wang, Jinmei Pan, Jiancheng Shi, Cheng Zhang, and Jinyu Huang https://zenodo.org/doi/10.5281/zenodo.10005826

Fangbo Pan, Lingmei Jiang, Gongxue Wang, Jinmei Pan, Jinyu Huang, Cheng Zhang, Huizhen Cui, Jiangwei Yang, Zhaojun Zheng, Shengli Wu, and Jiancheng Shi

Viewed

Total article views: 306 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
220 69 17 306 17 16
  • HTML: 220
  • PDF: 69
  • XML: 17
  • Total: 306
  • BibTeX: 17
  • EndNote: 16
Views and downloads (calculated since 27 Nov 2023)
Cumulative views and downloads (calculated since 27 Nov 2023)

Viewed (geographical distribution)

Total article views: 306 (including HTML, PDF, and XML) Thereof 306 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 04 Mar 2024
Download
Short summary
It is important to strengthen the continuous monitoring of snow cover as a key indicator of imbalance in the Asian Water Tower (AWT) region. We generate long-term daily gap-free fractional snow cover products over the AWT at 0.005° resolution from 2000 to 2022 based on the multiple endmember spectral mixture analysis algorithm and the gap-filling algorithm. It can provide highly accurate, quantitative fractional snow cover information for subsequent studies such as hydrology and climate.
Altmetrics