Connecting tornado and extreme convective weather occurrence to climate variability and change

The past few years have raised important questions about how the occurrence of tornadoes and other extreme convective weather relates to internal climate variability and anthropogenic climate change.

This talk will begin with a discussion of some of the attempts to reveal such relationships using the historical tornado database, which require proper treatment of the biases inherent in the report-based data.

Progress has also been made using global and regional climate model simulations, despite the fact that the models are much too coarse to explicitly resolve convective phenomena. The basis for such an “implicit” modeling approach will be described, as will its limitations, which include an inability to unambiguously predict the likelihood of specific convective phenomena.

Most of these limitations are removed with a climate modeling approach that allows explicit representation of deep convective storms. This “explicit” and hence more computationally intensive approach couples a non-hydrostatic mesoscale model to a global climate model. The global model output provides the initial and boundary conditions for the mesoscale model – for example, the Weather Research and Forecasting model (WRF) – which therefore functions as a high-resolution dynamical downscaler. Our downscaling procedure involves a multi-decadal sequence of daily integrations of WRF, with advanced statistical methods to identify and classify the severe convective weather in the model output.

Some closing discussion will be devoted to how both approaches are being adapted to yield seasonal predictions of tornadoes and other extreme convective weather.