Advances in Statistical Climatology, Meteorology and Oceanography
Advances in Statistical Climatology, Meteorology and Oceanography
ASCMO
Articles | Volume 9, issue 1
Articles | Volume 9, issue 1
https://doi.org/10.5194/ascmo-9-1-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ascmo-9-1-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 9, issue 1
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

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Latest update: 15 Jul 2024
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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.
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