Creation and Verification of a High-Resolution Multi-Parameter Surface Meteorological Assimilation Dataset for the Tibetan Plateau for 2010–2020 Available Online

Abstract

The Qinghai–Tibet Plateau (QTP) is a crucial component of the global climate system, influencing the regional and global climate through complex thermal and dynamic mechanisms. The high-altitude region, which is the largest part of the extra-polar cryosphere, encompasses extensive mountain glaciers, permafrost, and seasonally frozen land, making it highly sensitive to global climate change. However, the challenging environmental conditions, such as the harsh terrain and high altitude, coupled with sparse weather station distribution and weak observatory representation, make it difficult to accurately quantify the atmospheric conditions and land–atmosphere coupling systems and their effects on the surrounding areas. To address these challenges, we utilized the Weather Research and Forecasting (WRF) model and a three-dimensional variational (3DVAR) assimilation method to create a high-resolution assimilated dataset (HRAD). The QTP-HRAD, covering the spatial range of 70 to 110°E and 25 to 40°N, was validated using both surface weather station observations and the European Center for Medium-Range Weather Forecasts Reanalysis V5, and can now be utilized for further studies on land–atmosphere interactions, water cycling and radiation energy transfer processes, and extreme weather events in the region.

Land–Atmosphere Interactions and Effects on the Climate of the Tibetan Plateau and Surrounding Regions II

“…The results showed that both MODIS and GIMMS data showed a common increase in the normalized difference vegetation index on the TP for all timescales, while the former has had a larger greening area since 2000 [18]. In addition, Wen et al [19] utilized the weather research and forecasting (WRF) model and a three-dimensional variational assimilation method to create a highresolution assimilated dataset (HRAD) with a spatial resolution of 0.05 • × 0.05 • and a temporal resolution of 1 h. The correlation coefficients of the 2 m temperature, surface temperature and surface pressure were relatively high, all above 0.9, and those of relative humidity and wind speed were approximately 0.7 and 0.5, respectively [19].…”