Comparative Evaluation of CMIP5 and CMIP6 GCMs in Reproducing Regional Precipitation Climatology in Mexico

Reliable precipitation projections are essential for water-resource management, flood-risk assessment, and drought preparedness in hydroclimatically complex regions such as Mexico, where uncertainty remains high due to monsoon dynamics, complex topography, and tropical moisture transport. This study evaluates paired CMIP5 and CMIP6 global climate models in simulating the historical (1940–2005) precipitation annual cycle across four regions of Mexico (NW, NE, SW, SE). Model outputs were compared against ERA5 and cross-validated with CRU using complementary metrics assessing error magnitude, variability, temporal phase, and spatial coherence. Results indicate that CMIP6 provides moderate but regionally heterogeneous improvements rather than a uniform advance. The most consistent gains occur in NE and SE Mexico, where dry biases are reduced and seasonal amplitude is better represented. In contrast, SW Mexico exhibits persistent summer wet biases linked to monsoon–topography interactions, while improvements in NW Mexico are mainly confined to selected individual CMIP6 models and are not consistently reflected in the ensemble median. A marked SW–SE summer dipole bias highlights ongoing deficiencies in representing moisture transport and convection. These findings demonstrate that increased model complexity does not guarantee improved regional skill and that ensemble medians may mask individual model performance, underscoring the need for targeted model selection, multi-dataset validation, and bias-correction strategies.