Climatology of near-surface wind speed from observational, reanalysis and high-resolution regional climate model data over the Tibetan Plateau

The Tibetan Plateau is the highest and most extensive upland region in the world, with an average elevation over 4,000 m above sea level. It is referred to as the water tower of Asia because it is the source region of several major rivers in Asia, hence providing water resources to almost two billion people. As near-surface wind speed plays a key role in regulating surface evaporation and thus the hydrological cycle, among other implications, it is crucial to explore its spatio-temporal characteristics over this region. However, due to its vast and complex geographical area with steep terrain, high elevations, and harsh environmental conditions, in-situ measurements are scarce and mostly located in valleys, limiting the understanding of wind speed climate across the Tibetan Plateau.This study explores the climatology of near-surface wind speed over the Tibetan Plateau by using for the first time homogenized (i.e., variations caused by non-climatic factors have been removed) observations from 104 measuring stations, together with reanalysis products and regional climate model simulations. By exploring wind characteristics with a focus on seasonal cycle through cluster analysis, three regions of distinct wind regimes are identified: (1) the central Tibetan Plateau; (2) the eastern and the peripheral areas of the plateau; and (3) the Qaidam basin, a topographic depression strongly influenced by the blocking effect of the surrounding mountainous terrain. Notably, the ERA5 reanalysis, with its improvements in spatial and temporal resolution, model physics and data assimilation, demonstrates closer agreement to the measured wind conditions than its predecessor ERA-Interim. However, the newest ERA5-Land product does not show improvements compared to ERA5, most likely because they share most of the parametrizations. Furthermore, the two analyzed dynamical downscalings of ERA5 fail to capture the observed wind statistics and exhibit notable biases and discrepancies also when investigating the diurnal variations.