We quantified the influence of sea surface temperature (SST) in the Niño 1+2 region and precipitation on the NDVI dynamics of the dry forest along Peru’s northern coast during 2003–2023. We used monthly series from MODIS (NDVI), CHIRPS (precipitation), and NOAA SST, seasonally standardized (z-score). We applied a 36-month rolling correlation, time–frequency analysis (XWT/WTC), and autoregressive models with exogenous regressors (ARX). Cross-correlation showed that NDVI responds with a positive one-month lag to both SST and precipitation, with correlation coefficients of 0.764 and 0.613, respectively. Among four AR(2) models evaluated, the ARX with lagged SST provided the best fit (AIC = 295.35), slightly outperforming the combined SST+precipitation model (AIC = 295.46). Akaike weights favored the former on grounds of parsimony. The results indicate a positive sensitivity of NDVI t...