Climate-driven weather shift poses a serious challenge to cotton production and particularly crop phenology stages in arid, drip-irrigated systems like Xinjiang, China, where temperature extremes events disrupt different growth-development stages and limit yield potential. Our existing research study influences APSIM-cotton model calibration to optimize suitable sowing windows, phenological compatibility with climate-smart favorable planting windows under drip irrigation conditions for yield enhancement in water-limited agricultural systems. To evaluate the impact of warming temperatures on cotton phenology and yield, the APSIM-cotton model was calibrated and validated for sowing-times, phenology, growth, and yield employing 40-years of historical climate data, cotton yield data from six agrometeorological locations, and two years of field trials with five different sowing dates. The model calculates the yield gap and production-limiting variables when surface temperatures rise. Results of APSIM-model validation showed that the difference in sowing-emergence was +2.7 days, for sowing-squaring +5.3 days, for squaring-flowering +6.6 days, and for flowering-boll open +3.8, and boll openmaturity +4.8 days. The observed warming trend from 1961 to 2020 represented a predicted yield decrease of 1.4 % decade-1 in Xinjiang due to a significant temperature increase of 0.37SC decade-1. Interannual temperature variability influenced cotton growth and yield more than any other climatic factor. APSIM-cotton model simulations optimized the value of different sowing dates in extending the growth period and enhancing natural resource optimization. Quantifications of sowing-emergence, emergence-flowering, flowering-boll open, and full crop maturity phases were negatively interrelated with the rise in temperature -3.14, -2.15, -2.09, and -1.17 days SC-1. The present study concludes that climate-smart adapting sowing windows (15-25 April) of cotton runs a practical approach for increasing yield and mitigating climate change risks.