Analysis and visualization scripts used for "The impact of stratospheric aerosol injection on extreme fire weather risk"

Scripts used for analyzing and visualizing data for "The impact of stratospheric aerosol injection on extreme fire weather risk" by Touma, Hurrel, Tye and Dagon published in Earth's Future. All scripts written by Danielle Touma and are in python (*.py) or Jupyter Notebook (*.ipynb) format. Abstract of paper: Stratospheric aerosol injection (SAI) would potentially be effective in limiting global warming and preserving large-scale temperature patterns; however, there are still gaps in understanding the impact of SAI on wildfire risk. In this study, extreme fire weather is assessed in an Earth system model experiment that deploys SAI beginning in 2035, targeting a global temperature increase of 1.5 degrees Celsius above pre-industrial levels under a moderate warming scenario. After SAI deployment, increases in extreme fire weather event frequency from climate change are dampened over much of the globe, including the Mediterranean, northeast Brazil, and eastern Europe. However, SAI has little impact over the western Amazon and northern Australia and causes larger increases in extreme fire weather frequency in west central Africa relative to the moderate emissions scenario. Variations in the impacts of warming and SAI on moisture conditions on different time scales determine the spatiotemporal differences in extreme fire weather frequency changes, and are plausibly linked to changes in synoptic-scale circulation. This study highlights that regional and spatial heterogeneities of SAI climate effects simulated in a model are amplified when assessing wildfire risk, and that these differences must be accounted for when quantifying the possible benefit of SAI.