This dataset consists of four files including (1) Lake ice thickness of 16 large lakes measured by satellite altimeters for 1992-2019 (Altimetric LIT for 16 large lakes.xlsx); (2) Daily lake ice thickness and lake surface snow depth of 1,313 lakes with an area > 50 km2 in the Northern Hemisphere modeled by a one-dimensional remote sensing lake ice model for 2003-2018 (in NetCDF format); (3) Future lake ice thickness and surface snow depth for 2071-2099 modeled by the lake ice model with a modified ice growth module (table S1.xlsx); (4) A lookup table containing lake IDs, names, locations, and areas. This daily lake ice and snow thickness dataset could provide a benchmark for the estimation of global lake ice and snow mass, thereby improving our understanding of the ecological and economical significance of freshwater ice as well as its response to climate change.

File naming and required software

This data contains four files in total. The altimetric lake ice thickness is contained in Altimetric LIT for 16 large lakes.xlsx. The simulation results of the remote sensing lake ice model are stored in the NC file Remote Sensing Lake Ice Model Results 2003_ 2018.nc. The estimated future lake ice thickness is stored in the table S1. xlsx. The lake name look-up table is stored in look_ up_ table. xlsx.
NC files can be read with MATLAB or Python.

Data Citations Data citation guideline What's data citation?

Cite as:

Li, X., Long, D., Huang, Q., Zhao, F. (2022). Lake ice thickness in the Northern Hemisphere (1992-2019, 2071-2099). A Big Earth Data Platform for Three Poles, DOI: 10.5281/zenodo.5528542. (Download the reference： RIS | Bibtex )

Related Literatures:

1. Li, X., Long, D., Huang, Q., & Zhao, F. (2022). The state and fate of lake ice thickness in the Northern Hemisphere. Science Bulletin, 67(5), 537-546.( View Details | Bibtex)

Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.

Support Program

the Second Tibetan Plateau Scientific Expedition and Research (STEP) program (2019QZKK0105) (No:2019QZKK0105)

National Natural Science Foundation of China (92047301, 91547210 and 51722903)

Copyright & License

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License： This work is licensed under an Attribution 4.0 International (CC BY 4.0)