Articles | Volume 9, issue 1
https://doi.org/10.5194/ascmo-9-1-2023
https://doi.org/10.5194/ascmo-9-1-2023
02 Feb 2023
 | 02 Feb 2023

Modeling general circulation model bias via a combination of localized regression and quantile mapping methods

Benjamin James Washington, Lynne Seymour, and Thomas L. Mote

Model code and software

captseymour/MMSDM: Code for Washington, Seymour, and Mote (2023) Benjamin James Washington and Lynne Seymour https://doi.org/10.5281/zenodo.7497210

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Short summary
We develop new methodology to statistically model known bias in general atmospheric circulation models. We focus on Puerto Rico specifically because of other important ongoing and long-term ecological and environmental research taking place there. Our methods work even in the presence of Puerto Rico's broken climate record. With our methods, we find that climate change will not only favor a warmer and wetter climate in Puerto Rico, but also increase the frequency of extreme rainfall events.