https://essopenarchive.org/users/622124/articles/645378-quantifying-climate-distinguishability-after-stratospheric-aerosol-injection-using-explainable-artificial-intelligence
*Authors* - Antonios Mamalakis - Elizabeth A. Barnes - James Wilson Hurrell Peer review timeline 25 May 2023Submitted to *ESS Open Archive * <https://essopenarchive.org/inst/20904> *01 Jun 2023**Published* in *ESS Open Archive* *Cite as: *Antonios Mamalakis, Elizabeth A. Barnes, James Wilson Hurrell. Quantifying “climate distinguishability” after stratospheric aerosol injection using explainable artificial intelligence. *ESS Open Archive .* June 01, 2023. DOI: 10.22541/essoar.168565419.96137434/v1 <https://doi.org/10.22541/essoar.168565419.96137434/v1> Abstract Stratospheric aerosol injection (SAI) has been proposed as a possible complementary solution to limit global warming and its societal consequences. However, the climate impacts of such intervention remain unclear. Here, we introduce an explainable artificial intelligence (XAI) framework to quantify how distinguishable an SAI climate might be from a pre-deployment climate. A suite of neural networks is trained on Earth system model data to learn to distinguish between pre- and post-deployment periods across a variety of climate variables. The network accuracy is analogous to the “climate distinguishability” between the periods, and the corresponding distinctive patterns are identified using XAI methods to gain insights into the emerging signals from SAI. For many variables, the two periods are less distinguishable under SAI than under a no-SAI scenario, suggesting that the specific intervention modeled decelerates future climatic changes. Other climate variables for which the intervention has negligible effect are also highlighted. *Source: ESS OPEN ARCHIVE* -- You received this message because you are subscribed to the Google Groups "geoengineering" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/geoengineering/CAHJsh9-p1mmbHjdfS7f9R0yc8vYEKk3cT-%3DO-ZZNRAQ%2B0Az2SQ%40mail.gmail.com.
