Space-time dependence of compound hot-dry events in the United States: assessment using a multi-site multi-variable weather generator

Despite their potential importance, the climatological characteristics of these joint events have received little attention regardless of growing interest in climate change impacts on compound events. Here, we ask how event timescale relates to (1) spatial patterns of compound hot-dry events in the United States, (2) the spatial extent of compound hot-dry events, and (3) the importance of temperature and precipitation as drivers of compound events.

To study such rare spatial and multivariate events, we introduce a multi-site multivariable weather generator (PRSim.weather), which enables generation of a large number of spatial multivariate hot-dry events. We show that the stochastic model realistically simulates distributional and temporal autocorrelation characteristics of temperature and precipitation at single sites, dependencies between the two variables, spatial correlation patterns, and spatial heat and meteorological drought indicators and their co-occurrence probabilities.