A dataset for lake level changes in the Tibetan Plateau from 2002 and 2010 to 2021 using multi-altimeter data

Abstract. The Tibetan Plateau (TP), known as the Roof of the World and the Water Tower of Asia, has the largest number of lakes in the world, and, because of its high altitude and the near absence of disturbances by human activity, the plateau has long been an important site for studying global climate change. Hydrological stations cannot be readily set up in this region, and in situ gauge data are not always publicly accessible. Satellite radar altimetry has become a very important alternative to in situ observations as a source of data. Estimation of the water levels of lakes via radar altimetry is often limited by temporal and spatial coverage, and, therefore, multi-altimeter data are often used to monitor lake levels. Restricted by the accuracy of waveform processing and the interval period between different altimetry missions, the accuracy and the sampling frequency of the water level series are typically low. By processing and merging data from eight different altimetry missions (Envisat, ICESat-1, CryoSat-2, Jason-1, Jason-2, Jason-3, SARAL, and Sentinel-3A), the developed datasets provided the water level changes for 361 lakes (larger than 10 km2) on the TP from 2002 to 2021 (181 lakes for the time series from 2002 to 2021 and 180 lakes for the time series from 2010 to 2021). The lake level change series shows good consistency with in situ measurements, demonstrating a median root-mean-square error (RMSE) of 0.19 m across eight validation gauges. The dataset further exhibits robust agreement with established satellite altimetry products (DAHITI, Hydroweb, and G-REALM), with median RMSE values below 0.30 m in all cross-validation comparisons. The present datasets and associated approaches are valuable for calculating the changes in lake storage, trend analyses of the lake levels, short-term monitoring of the overflow of lakes and flooding disasters on the plateau, and the relationships between changes in the lake ecosystems and changes in the water resources. Data described in this article can be accessed at PANGAEA under https://doi.org/10.1594/PANGAEA.973443 (Chen et al., 2024).