Modeling environmental data, such as regional wind speed or temperature, is a complicated business. To model data statistically requires significant assumptions about its behavior over time and space—yet arriving at those assumptions requires an understanding of the data that can generally only be obtained by modeling. It’s a catch-22 that presents a major obstacle to progress in large-scale environmental and climate modeling, particularly for extreme events.