Lake ice phenology is a seasonal cyclical feature that describes lake ice coverage. The change of lake ice phenology is an important part of carbon, water and energy process study, and one of the sensitive factors of climate change. This dataset is a lake ice phenology based on passive microwave inversion, including lake ice phenology of 200 lakes in the Tibetan Plateau and high latitudes area of the Northern Hemisphere from 2002 to 2018 (including freeze-up start date, freeze-up end date, break-up start date, and break-up end date of the lakes), data of some lakes can date back to 1978. This data is basically consistent with the MODIS monitoring results from the same time with an interpretation error of 2-4 days. Users can use this data to conduct climate change study in the Northern Hemisphere.

File naming and required software

The data is text data, including records of freeze-up start date, freeze-up end date, break-up start date, and break-up end date of 200 lakes from 2002 to 2018.

Data Citations Data citation guideline What's data citation?

Cite as:

Qiu, Y. (2019). The lake ice phenology dataset of the Northern Hemisphere (1978-2018). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Meteoro.tpdc.270981. CSTR: 18406.11.Meteoro.tpdc.270981. (Download the reference： RIS | Bibtex )

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

Support Program

CASEarth:Big Earth Data for Three Poles（grant No. XDA19070000） (No:XDA19000000)

Copyright & License

To respect the intellectual property rights, protect the rights of data authors, expand services of the data center, and evaluate the application potential of data, data users should clearly indicate the source of the data and the author of the data in the research results generated by using the data (including published papers, articles, data products, and unpublished research reports, data products and other results). For re-posting (second or multiple releases) data, the author must also indicate the source of the original data.

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