A physically-driven multivariate framework for reconstructing and improving photosynthetically active radiation in humid tropical coastal site: a local site-adaptation case study

Estimating Photosynthetically Active Radiation (PAR) in the humid tropics is limited by prevailing cloud cover and a sparse network of weather stations. This study develops a five-phase framework to verify, reconstruct, and improve PAR estimates in a coastal region of Ecuador, using the CERES satellite product as a basis. The core is a benchmarking of six configurations (M0–M5), proposing a multivariate physical model (M3) that integrates seven predictors: GHI, zenith angle, relative humidity, temperature, precipitable water, cloud type, and AOD. Using only six months of in situ measurements, it proved feasible to reconstruct the complete annual series. M3 increased the coefficient of determination R² from 0.71 to 0.79 and reduced the overall RMSE to 32%, producing physically more consistent reconstructions than stochastic and quantile mapping methods. A marked satellite underestimation was detected at sunset (RMSE 68%, bias − 45%). Annually, M3 corrected the accumulated energy from 10,705 to 10,981 mol m⁻², approaching the 11,446 mol m⁻² measured in situ, a 37% reduction in annual bias. Because in situ data covered only July–December 2024, skill was assessed by internal cross-validation (leave-one-month-out R² ≈ 0.83), while January–June is reported as a reconstruction. Robustness to severe multicollinearity (VIF > 20) was confirmed with Ridge, LASSO, and PCR.