Observational evidence that cloud feedback amplifies global warming
A key challenge of our time is to accurately estimate future global warming in response to a doubling of atmospheric carbon dioxide—a number known as the climate sensitivity . This number is highly uncertain, mainly because it remains unclear how clouds will change with warming. Such changes in clouds could strongly amplify or dampen global warming, providing a climate feedback. Here, we perform a statistical learning analysis that provides a global observational constraint on the future cloud response. This constraint supports that cloud feedback will amplify global warming, making it very unlikely that climate sensitivity is smaller than 2 °C. Code to perform the ridge-regression calculation has been deposited in GitHub (<https://github.com/peernow/PNAS2021>). Previously published data were used for this work. All observational, reanalysis, and GCM datasets used in this study are publicly available. CMIP data were obtained from the UK Center for Environmental Data Analysis portal (<https://esgf-index1.ceda.ac.uk/search/cmip6-ceda/>). CERES data were obtained from the NASA Langley Research Center CERES ordering tool (<https://ceres.larc.nasa.gov/data>). Data for CFSR and MERRA2 were obtained from the Collaborative REAnalysis Technical Environment (CREATE) project (<https://esgf-node.llnl.gov/search/create-ip/>). JRA-55 data were downloaded from the National Center for Atmospheric Research/University Corporation for Atmospheric Research Research Data Archive (<https://rda.ucar.edu/datasets/ds628.1/>). ERA5 data were downloaded from the Copernicus Climate Data Store (<https://doi.org/10.24381/cds.f17050d7> and <https://doi.org/10.24381/cds.f17050d7>).