MPC Member Publications

This database contains a listing of population studies publications written by MPC Members. Anyone can add a publication by an MPC student, faculty, or staff member to this database; new citations will be reviewed and approved by MPC administrators.

Full Citation

Title: Physics-guided probabilistic modeling of extreme precipitation under climate change

Citation Type: Journal Article

Publication Year: 2020

ISSN: 20452322

DOI: 10.1038/s41598-020-67088-1

PMID: 32581227

Abstract: Earth System Models (ESMs) are the state of the art for projecting the effects of climate change. However, longstanding uncertainties in their ability to simulate regional and local precipitation extremes and related processes inhibit decision making. Existing state-of-the art approaches for uncertainty quantification use Bayesian methods to weight ESMs based on a balance of historical skills and future consensus. Here we propose an empirical Bayesian model that extends an existing skill and consensus based weighting framework and examine the hypothesis that nontrivial, physics-guided measures of ESM skill can help produce reliable probabilistic characterization of climate extremes. Specifically, the model leverages knowledge of physical relationships between temperature, atmospheric moisture capacity, and extreme precipitation intensity to iteratively weight and combine ESMs and estimate probability distributions of return levels. Out-of-sample validation suggests that the proposed Bayesian method, which incorporates physics-guidance, has the potential to derive reliable precipitation projections, although caveats remain and the gain is not uniform across all cases.

Url: https://doi.org/10.1038/s41598-020-67088-1

User Submitted?: No

Authors: Kodra, Evan; Bhatia, Udit; Chatterjee, Snigdhansu; Chen, Stone; Ganguly, Auroop Ratan

Periodical (Full): Scientific Reports

Issue: 1

Volume: 10

Pages: 1-11

Countries:

IPUMS NHGIS NAPP IHIS ATUS Terrapop