The Non-Linear Response of Rain-on-snow Floods to a Warming World: Perspectives from High-Resolution Storyline Simulations
The combination of deep, ripe, antecedent snowpack and sudden warm, moist, rain events can result in significant flooding that wouldn't exist if either condition occurred independently. The cool season hydrologic event of record for the Susquehanna River Basin in the Mid-Atlantic United States (U.S.) is the January 1996 flood, an event driven by rapid ablation of existing snow by an inland extratropical cyclone. While this compound event is a key benchmark for many hydrologists in the northeastern U.S., neither the depth of antecedent snowpack nor the synoptic weather pattern were particularly notable in isolation.
Storylines are an approach to exploring climate risk through evaluation of physically-consistent events under plausible scenarios. Such storylines are powerful tools for tying stakeholder risk awareness and decision-making to climate model projections. In this talk, we apply a 14km version of the Department of Energy's Energy Exascale Earth System Model (E3SM) initialized with historical and counterfactual conditions to reforecast the 1996 Mid-Atlantic flood under different climate regimes. Possible outcomes are generated by applying the anthropogenic fingerprint from future climate projections at various warming thresholds to the model's initial and boundary conditions. We find stark non-linearities in surface runoff and streamflow exist under progressively warmer environments due to the complex interplay of pre-event surface evolution and thermodynamic changes in weather features. While we focus on the 1996 Mid-Atlantic flood, we also explore this approach with a more classic rain-on-snow event in the mountainous western U.S.: the January 1997 flood. This work emphasizes large sensitivity of cool-season flooding to event timing and concurrence and challenges associated with communicating associated risk.