I will use three current projects to showcase how statistics can help answer questions involving climate change and sustainability. The first is integrating pollen, genetic and species distribution model data to recover glacial refugia in the Alaska area, and the second regards county-level crop yield prediction using functional covariates such as daily max/min temperature series. The last example is to develop a new method to estimate asynchronous changepoint for spatially functional time series. I will also show how this new method can be used to analyze climate data and daily covid cases. All these examples illustrate how the model respects data heterogeneity and exploits spatial correlation to improve statistical inference.