AGS-PRF: Improved Estimates of Southern California Precipitation Extremes through Model/Proxy Synthesis

Water resources in southern California are sensitive to variability in rainfall and snowfall, especially extreme precipitation associated with atmospheric rivers. Most of the work reconstructing extreme rainfall events and the mechanisms that drive them has been done in northern California, which has distinct climate patterns than southern California.

This creates a challenge for effective infrastructure planning and water management in southern California. The goals of this project are to combine tree-ring reconstructions of rainfall through time with historical weather observations and climate model simulations to analyze extreme rainfall variability through time in southern California. The project will reconstruct the range of variability in rainfall through time with the tree rings, and the models will be used to analyze the mechanisms that drive extreme rainfall variability in this region.

The project will include a public outreach talk on the results of this research at the Santa Barbara Botanic Garden.

Water resources in southern California rely on rain fall and snowpack, and the frequency and intensity of both vary interannually. Trends through time and the role of internal variability are uncertain, in part because existing tree-ring based reconstructions and analysis of precipitation variability focus on central and northern California, which has distinct climate patterns than southern California.

This creates a challenge for effective infrastructure planning and water management in southern California. The goals of this project are to combine tree-ring records, historical weather observations and climate simulations to analyze precipitation variability through time in southern California, with a focus on atmospheric rivers (ARs) and extremes of the precipitation distribution.

New subseasonal tree ring records (total ring width and earlywood width) that capture recent extreme winters will be generated and added to already-collected data from the region. These data will be used to quantify the characteristics of ARs and range of variability of extreme precipitation through time through regression to the Scripps Institute of Oceanography (SOI) AR catalog.

A suite of large-ensemble climate models will be used to analyze climate modes and the mechanisms that drive variability in extreme precipitation in this region. The project will compare of reconstructed precipitation variability from tree-rings with simulated precipitation variability in order to constrain model uncertainties.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.