A high-resolution near-surface meteorological forcing dataset for arid Xinjiang (3DVAR-MF-XJ)

Hydroclimatic assessment in Xinjiang is constrained by sparse observations, complex terrain and systematic biases in widely used gridded and reanalysis products. Here we present the Three-Dimensional Variational Xinjiang Meteorological Forcing Dataset (3DVAR-MF-XJ), a 0.1° gridded near-surface dataset for 1961-2020 at hourly and daily resolution, including 2 m air temperature, relative humidity, 10 m wind speed, surface pressure, downward shortwave radiation and precipitation. 3DVAR-MF-XJ is generated using a hybrid framework in which regional modelling with three-dimensional variational data assimilation first produces dynamically consistent fields (3DVAR-XJ), followed by station-constrained bias correction on a common 0.1° grid. Evaluation against 30 withheld stations and independent benchmark products shows reduced mean and root-mean-square errors, higher correlations, and improved representation of precipitation over complex terrain and shortwave radiation at high elevations relative to ERA5, ERA5-Land and CN05.1. For precipitation, RMSE is reduced by 65.6%, 64.9% and 49.3% relative to ERA5, ERA5-Land and CN05.1, respectively. 3DVAR-MF-XJ provides a unified, well-documented forcing dataset for hydrological, ecological and land-atmosphere applications in arid Xinjiang.