The dataset reconstructed a wide coverage, long-term lake surface temperature data product. Based on the basic characteristics and data foundation of water and heat balance in lakes on the Qinghai Tibet Plateau, the team improved the one-dimensional energy balance model of lakes and used the Google Earth Engine (GEE) platform to calibrate and validate the model by obtaining the time series of the average temperature of the entire lake based on MOD11A1 data. For the first time, a daily lake surface temperature dataset of 160 lakes on the Qinghai Tibet Plateau from 1978 to 2017 was reconstructed. This data product has a wide coverage, long time span, and high time resolution, which can provide important technical and data support for understanding the response of energy balance of lakes on the Qinghai Tibet Plateau to climate change. Further testing shows that the data product has good consistency with the measured lake surface temperature on the ground.
The folder also includes vector data of lakes, as well as daily data of lakes using products such as MOD11A1 as calibration and validation data.
The dataset is developed by integrating remote sensing and numerical simulation techniques.
Improve the one-dimensional energy balance model of the lake and use the Google Earth Engine (GEE) platform to calibrate and validate the model by obtaining the time series of the average temperature of the entire lake based on MOD11A1 data.
The data quality is good.
This work is licensed under a
Creative
Commons Attribution 4.0 International License.
CSTR:11738.11.NCDC.ZENODO.DB3944.2023
10.5281/zenodo.5111400