This repository contains the source code (MATLAB/Python) and processed datasets used to reproduce the analysis in the manuscript submitted to Global Biogeochemical Cycles. With ongoing global warming, the frequency and intensity of extreme events have increased markedly, posing severe threats to plant photosynthesis. Midday photosynthetic depression (MPD), occurring when vegetation experiences environmental stress around noon, plays a critical role in regulating ecosystem carbon cycling. However, most existing studies have focused on simply describing the shape of the diurnal photosynthetic curve at leaf, ecosystem, or regional scales, lacking a unified quantitative index to assess MPD intensity across global ecosystems and the systematic evaluation of how individual and compound stressors modulate its strength remains unknown. Here, using hourly measurements from 136 eddy-covariance sites, we develop a new metric, midday depression intensity (MDI), to quantify MDP across global ecosystems and to investigate its responses to environmental drivers and extreme climatic events. By accounting for radiation-driven regulation of diurnal photosynthesis, MDI effectively captures MPD under diverse stress conditions through an improved quantification of potential diurnal gross primary productivity (GPP) trajectory. Both water and heat stress significantly increase MDI (mean increase across all sites: 1.74% and 2.67%, p < 0.05), while compound water-heat stress exerts the strongest amplification (mean increase: 9.43%, p < 0.05). Integrating five environmental factors, machine-learning models accurately predict MDI across all aridity and stress levels (R² = 0.76 to 0.81), with best performance achieved with XGBoost method in drylands (R² = 0.81). Vapor pressure deficit (VPD) consistently emerges as the dominant driver of MDI, while soil water content (SWC) and air temperature (TA) serve as key secondary factors under water- and heat-stress conditions, respectively. As TA and VPD increase or soil moisture declines, ecosystems face a higher risk of intensified MPD. Our findings demonstrate the capability of MDI for monitoring midday photosynthetic depression across ecosystems and reveal how environmental drivers and extreme events regulate it, advancing understanding of ecosystem-climate interactions at fine temporal scales.