Evaluation of Three Air Temperature Reanalysis Datasets in the Alpine Region of the Qinghai–Tibet Plateau

Surface air temperature is a critical element in the surface–atmosphere interaction, energy exchange, and water cycle. Multi-source fusion reanalysis products (hereafter referred to as reanalysis) have spatiotemporal continuity broad applicability that can provide key data support for various studies such glacier melting, soil freeze-thaw desertification, ecosystem, climate change alpine region of Qinghai–Tibet Plateau (QTP). observations collected at 17 weather stations High-cold Observation Research Network Land Process Environment China (HORN) over period 2017–2018 are implemented evaluate advanced widely used surface datasets, which include European Centre Medium-Range Weather Forecasts (ECMWF) Fifth Generation Reanalysis (ERA5L), U.S. Global Data Assimilation System (GLDAS), Meteorological Administration (CLDAS). Results follows: (1) Evaluation results temporal changes spatial distribution characteristics indicate three datasets consistent with in-situ QTP. CLDAS more better describe details variation than ERA5L GLDAS. (2) For evaluation period, 0.53 °C higher observation, while GLDAS lower observation by ?3.45 ?1.40 °C, respectively. (3) The accuracy under different elevations land covers. We resampled resolution 0.25° two most common interpolation methods analyze impact on results. found small. In summary, all certain QTP, significantly present paper important implications selection climate, sustainable development