Nesting Elterman Model and Spatiotemporal Linear Mixed-Effects Model to Predict the Daily Aerosol Optical Depth over the Southern Central Hebei Plain, China

Aerosol optical depth (AOD), an important indicator of atmospheric aerosol load, characterizes the impacts on radiation balance and turbidity. The nesting Elterman model a spatiotemporal linear mixed-effects (ST-LME) model, which is referred to as ST-Elterman retrieval (ST-ERM), was employed improve temporal resolution AOD prediction. This produces daily in Southern Central Hebei Plain (SCHP) region, China. Results show that ST-ERM can effectively capture variability correlations between meteorological variables. After being validated against Multi-Angle Implementation Atmospheric Correction (MAIAC) AOD, correlation coefficient retrieved from MAIAC observations 2017 reached 0.823. Nash–Sutcliffe efficiency (Ef) ST-ERM-retrieved greater than or equal 0.50 at 72 95 stations 2017. relative error (Er) less 14% all except for Shijiazhuang (17.5%), Fengfeng (17.8%), Raoyang (30.1%) stations. significantly outperforms conventional meteorology–AOD prediction approaches, such revised (R-ERM). Thus, shows great potential estimation study regions with missingness data.