A climatic data-based analysis was performed to quantify the overwintering survival and emergence of diapausing boll weevils in the Rolling Plains of Texas. The analysis described four relationships that enabled estimations of 1) the amount of degree-days required for a cohort to begin spring emergence, 2) the amount of degree-days required for the cohort to complete emergence, 3) overwintering survival, and 4) cumulative emergence. Both overwintering survival and emergence were influenced by the day of the year when the weevils were placed in the overwintering habitat (DOY_in), the amount of rainfall, and habitat temperatures experienced by the weevils during diapause. Multiple least squares regression analyses describing the degree-days required for the weevils to start emergence (DD_start) and the degree-days required for all weevils to emerge (DD_emerg) explained 88 and 77% of the variability in the data, respectively. With independent data, 75 and 36% of the variability were explained for DD_start and DD_emerg, respectively. Multiple regression analysis with DOY_in, negative degree-days, rainfall, DD, and their first order interactions explained 99% of the variability in overwintering survival. With independent data, 74% of the variability was explained by the survival function. The spring/summer emergence pattern for the overwintering weevils was described by a sigmoid function that explained 95 and 92% of the variability for the verification data set and the independent data set, respectively.