Emerging Applications of Global Climate Models: From Predicting Weather Extremes to Assessing Energy Risk
First global climate models (GCMs) developed from numerical weather models, but GCMs’ low spatial resolution has long obstructed their applications in understanding and predicting weather features. The obstruction recently loosened with advancements in high-resolution GCMs. This multi-part talk will discuss emerging applications of GCMs in understanding climate risk and predicting weather extremes. The first part explores climate risk using a GCM that skillfully simulates real-world hurricane activity. We construct idealized experiments and evaluate influential ideas on how hurricane activity varies in diverse climates. Unexpected simulation findings reconcile divergent ideas and highlight future hurricane risk in midlatitude regions. The second part examines atmospheric baroclinic waves, which drive everyday extratropical weather but are often associated with the ‘low predictability’ stereotype. We challenge that stereotype by analyzing wave statistics in large-ensemble GCM simulations and systematically mapping the ocean-related (potential) predictability. Despite model issues, our analyses and prediction experiments show that subseasonal-to-seasonal predictability of baroclinic wave activity is abundant. The statistical predictability is exceptional for some baroclinic waves linked to weather extremes (e.g., atmospheric rivers). Our multi-line research suggests high-resolution GCMs’ new capability promises wide-reaching research opportunities and may help to address challenges in the energy transition.
