The surface water temperature of lakes is an important physical property of aquatic ecosystems and a significant indicator of climate change. The dataset combines the advantages of satellite observation and simulation to generate a comprehensive daily LSWT for 160 lakes on the Qinghai Tibet Plateau, which have limited in situ observations. The overall lake average LSWT based on MODIS in the comprehensive dataset includes daytime, nighttime, and daily averages from 2000 to 2017. This dataset and the established method are helpful for studying the changes in water and heat balance and their ecological effects on the Qinghai Tibet Plateau.
Obtained through a combination of experiments and simulations.
A simplified physical model (i.e. an improved air2water model) was calibrated using a daily average LSWT based on Modis, and a complete and consistent daily average LSWT dataset from 1978 to 2017 was reconstructed on this basis. Compare and validate the reconstructed LSWT dataset with satellite observation data and on-site observation data.
The data quality is good.
This work is licensed under
CC BY 4.0 (Creative Commons Attribution 4.0 International License).
CSTR:11738.11.NCDC.ZENODO.DB4164.2024
10.5281/zenodo.6637526
