The “Perfect Storm”: Can Atmospheric Models Improve Confidence In Probable Maximum Precipitation (PMP)?

ABSTRACT ONLY - The flood that would result from the greatest depth of precipitation “meteorologically possible”, or Probable Maximum Precipitation (PMP) is used to ensure the safety of nuclear power plants, among other high-risk structures. Historically, PMP has been estimated by scaling (extrapolating) depth-area-duration relationships obtained from severe historical storms, following guidelines from the so-called Hydrometeorological Reports (HMRs). Over the last decade, frameworks that leverage numerical weather prediction models to predict precipitation resulting from the addition of moisture (called relative humidity maximization, or RHM) have been developed. Incorporating current understanding of precipitation processes in those model-based methods represents an important advance. Nonetheless, model-based PMP still relies on key assumptions: (1) that severe historical storms achieved maximum efficiency (moisture conversion to precipitation), such that only moisture needs to be maximized and (2) that maximizing moisture (i.e., saturating the atmosphere) near the target basin is realistic and consistently maximizes precipitation. Numerical weather prediction models allow us to re-evaluate those assumptions and perform scenario analyses to develop physically-based guidelines on how to reliably maximize storms. Additionally, as the use of model-based tools introduces new challenges such as model uncertainty, our scenarios include different model setups and parametrizations that aim to characterize the magnitude of this uncertainty.Focusing on the Feather River basin in California, we downscale the most severe historical storms from ERA5 reanalysis using the WRF model. Using these high-resolution simulations, we seek to identify key attributes of these storms (storm orientation, convection and large-scale convergence) that control precipitation efficiency and we characterize the nonlinear precipitation response to the addition of moisture in our simulations. In so doing, we highlight that PMP would be better presented as an ensemble of values, such that uncertainty can be communicated, rather than a single estimate, and develop guidance for the engineering community on how to consistently maximize storms.