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

• Published in: Remote Sensing
• Main Authors: Xiaohang Wen, Xian Zhu, Maoshan Li, Mei Chen, Shaobo Zhang, Xianyu Yang, Zhiyuan Zheng, Yikun Qin, Yu Zhang, Shihua Lv
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2023
• Subjects: Tibetan Plateau; assimilation dataset; land–atmosphere interaction; WRF model; Science; Q; permafrost
• Online Access: https://doi.org/10.3390/rs15112906; https://doaj.org/article/cc0e097fce854154a625d33e74770f8d

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.