Abstract: Extreme temperature events are becoming increasingly frequent due to global warming. This poses a serious threat to the crop production. Cotton is an important cash crop in China, and Xinjiang accounts for 20% of the global cotton production. Studying the effects of extreme temperatures on cotton yields is important for developing the Chinese cotton industry. In this study, we used the Mann-Kendall trend test and Sens slope method to analyze the spatial and temporal characteristics of yield variation and assessed the response of cotton yield to temperature extremes using the copula function based on historical climate data and cotton yield data in Xinjiang from 1990 to 2019. The results show that the upward trend in cotton yield from 1990 to 2019 was highly significant (P<0.01) in 86% of Xinjiang. The probability of an increase in cotton production because of extreme temperature effects was greater than 20% in 41.7% of the southern border but only 26.1% of the northern border. The probability of cotton yield reduction because of extreme temperatures was less than 30% in 92.6% of the areas across Xinjiang, and areas with a probability of yield reduction greater than 30% were concentrated north of the Tianshan Mountains. The cotton climatic yield was significantly affected by the minimum daily temperature during the cotton growth period and the maximum daily temperature during the cotton growth period among the six extreme climate indicators. The probability of a yield reduction of more than 133 kg·hm^–2 increased by 16%, and the probability of a yield increase of more than 137 kg·hm^–2 decreased by 10% as the minimum daily temperature during the cotton growth period increased, but increased by 17% and decreased by 12% as the maximum daily temperature during the cotton growth period increased. This study demonstrates that cotton production in Xinjiang exhibited an upward trend from 1990 to 2019. The likelihood of a negative impact on cotton yield increases with increases in the minimum daily minimum temperature during the cotton growth period and maximum daily maximum temperature for the cotton growth period. It is beneficial to reduce the risks associated with cotton production, establish production plans, and encourage the growth of the cotton industry’s ability to adapt to climate change to clarify how cotton yield occurrence probability responds to extreme climate indicators.