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Dynamic controlled atmosphere (DCA) storage offers potential economic advantage for organic apple storage, but quantifying these benefits requires accounting for packout uncertainty, seasonal price dynamics, environmental, and location-specific heterogeneity. We developed an integrated empirical simulation that links multiyear storage trials with Monte Carlo revenue modeling to quantify DCA performance relative to controlled atmosphere and regular atmosphere storage. Storage experiments evaluated quality retention or packouts across storage durations and were represented by beta-distributions. A three-stage least squares model identified seasonal price patterns and key determinants of organic apple prices, producing monthly price predictions. Predicted prices were combined with simulated packouts to estimate by cultivar, storage length, and orchard the probability that DCA is revenue superior. Economic outcomes were cultivar, year, and site specific. For organic ‘Gala’ ( Malus domestica ), the probability that DCA dominates increased from 37.6% in Spring 2022 to 91.8% in Summer 2024, with median revenue advantages for DCA reaching $170,488 per storage room at peak. For ‘Honeycrisp’, orchard-level heterogeneity was pronounced. Orchard 1 achieved 100% DCA dominance in Spring 2024, whereas ‘Honeycrisp’ orchard 2 showed variable performance (high of 77.0% to 78.6% in Summer 2022 and Summer 2023). Weather-sensitivity analysis indicated location-specific responses. Elevated harvest temperatures slightly reduced DCA dominance for ‘Gala’ but sharply reduced it for ‘Honeycrisp’ (−26.1 percentage points on average). These findings indicate that DCA adoption should be tailored to cultivar, storage duration, and local environmental conditions. The framework provides probabilistic decision support for adoption and timing of DCA in organic apple supply chains by integrating storage performance, price seasonality, and packout uncertainty.