Elevation Correction of ERA5 Reanalysis Temperature over the Qilian Mountains of China

Abstract

Air temperature acts as a key indicator of climate change. In regions with high elevations and scarce meteorological stations, reanalysis temperature datasets are vital for estimating temperatures. However, due to the presence of biases in the observational data of these reanalysis datasets, it becomes necessary to perform bias correction to augment the accuracy of modeling and prediction. In the present study, a temperature lapse rate model was utilized to correct the ERA5 reanalysis temperature data within the Qilian Mountains (QLMs) in China from 1979 to 2017. The research results show that the constructed temperature lapse rate can effectively reflect the vertical temperature change characteristics in the Qilian Mountains. As the altitude increases, the absolute value of the temperature lapse rate on the northern slope decreases, while the absolute value of the temperature lapse rate on the southern slope increases. The accuracy of the corrected ERA5 temperature data is significantly improved, especially in winter. Among the 17 meteorological stations, 13 stations show a statistically significant improvement in accuracy after correction in winter, accounting for approximately 76.5% of the total stations. This study can provide a reliable data reference for climate research, ecological environment monitoring, and other fields in the Qilian Mountains area.