Evaluation and statistical bias correction of ERA5-Land meteorological variables for a humid river basin in Southwest China.

ABSTRACT: High-quality meteorological data are essential for climate monitoring and renewable energy applications. ERA5-Land, a newly released high-resolution reanalysis dataset, provides a wide range of meteorological variables, but its accuracy remains a concern. This study evaluated the performance of ERA5-Land in the Lower Jinsha River Basin, the largest clean energy base in China, focusing on precipitation, wind speed, air temperature, and solar radiation. A statistical bias correction procedure was developed, combining month-specific regression fitting with daily and hourly adjustments. Results indicated that air temperature estimates agreed best with ground observations, with a coefficient of determination (R²) exceeding 0.87 and percent bias (Pbias) below 15%, followed by solar ra

SUBMITTER: Zhang L 

PROVIDER: S-EPMC12635310 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature