Increased variation in interannual weather due to climate change can exert a powerful influence on the population dynamics of a species. Understanding the influence of severe weather is important for managing weather-sensitive species. While best management practices target vital rates that are affected by weather, focusing on a single vital rate may not be sufficient if other vital rates are secondarily limiting. A comprehensive modeling framework to forecast future population dynamics while incorporating weather scenarios and vital rate variation within observed ranges that can be affected by management actions are necessary. A potential approach is to combine an integrated population model (IPM) with a population viability analysis (PVA) to generate novel insights about population dynamics. We used the northern bobwhite (Colinus virginianus), a rapidly declining gamebird sensitive to snowfall along the northern extents of the species' range, to demonstrate the utility of a coupled IPM-PVA framework for projecting the response of a population to weather, management, and changes in vital rates. We created an IPM using two sources of count data spanning seven years, five years of winter survival data, and two years of breeding season demographics for a declining bobwhite population in southwestern Ohio during 2007-2015. Quasi-extinction probability at the end of the decadal projection during 2019-2029 was 0.384-0.410 for mild, average, and severe winter weather scenarios. Quasi-extinction probability declined to 0.326 with 20% improvement in nest success and summer survival rates. A concurrent 20% increase in winter survival further reduced quasi-extinction probability to 0.263, which is a˜36% reduction in quasi-extinction probability compared with the baseline scenario with no changes in vital rates. These results suggest that longterm viability of this population may depend on extensive management of winter habitat to improve survival but will also require management actions to improve fecundity after severe winters. Our modeling approach demonstrated how IPMs can be used to project population responses to future weather conditions and overcome some of the pitfalls of traditional PVA. The coupled framework presented here can serve as a tool for managers to make climate-informed management decisions.