This study evaluates the performance of eleven Planetary Boundary Layer (PBL) schemes within the Weather Research and Forecasting (WRF) model over the Central Amazon Basin, focusing on contrasting wet and dry season conditions observed during the GoAmazon2014/5 campaign. High-resolution (1 km) simulations were conducted for representative periods in each season and validated against in situ observations. Model performance was assessed using multiple statistical metrics with the explicit separation of daytime convective and nighttime stable PBL regimes. Results reveal substantial variability among PBL schemes, strongly modulated by the season and diurnal cycle. Overall performance was higher during the wet period, whereas dry period simulations exhibited larger uncertainties, particularly under nocturnal conditions. The Shin–Hong (SH) PBL scheme had the best skill on average to reproduce the observed PBL height (PBLH) during the wet period, while the University of Washington (UW) PBL scheme was the best during the dry period. The Mellor–Yamada–Janjic (MYJ) PBL scheme had the best skill for daytime PBLH in both periods. Spatial analysis demonstrated how PBL schemes impact the PBLH distribution over the Central Amazon Basin, revealing a river-influenced pattern. These findings highlight the strong sensitivity of the Amazon PBL depth to PBL schemes and underscore the importance of appropriate PBL parameterizations and the vertical resolution for tropical applications.
Mantovani et al. (2026) studied this question.