Published October 7, 2022
| Version v1
Software
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Software for "Detecting changes in global extremes under the GLENS-SAI climate intervention strategy"
- 1. Department of Atmospheric Science, Colorado State University, Fort Collins, CO
Description
We train a simple machine learning model to predict whether a map of global extremes came from an RCP8.5 or stratospheric aerosol injection simulation. The timing of accurate predictions acts as a quantification of the time to detection of a geoengineered climate. Regional changes in extreme temperatures and extreme precipitation under SAI are robustly detected within 1 and 15 years of injection, respectively.
Files
data_preprocessing.ipynb
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