@article{1616, keywords = {climate attribution, extreme events, ExtGPD, extreme value statistics, Climate change, extreme precipitation}, author = {J. Nanditha and Gabriele Villarini and Hanbeen Kim and Philippe Naveau}, title = {Strong Linkage Between Observed Daily Precipitation Extremes and Anthropogenic Emissions Across the Contiguous United States}, abstract = {Abstract The results of probabilistic event attribution studies depend on the choice of the extreme value statistics used in the analysis, particularly with the arbitrariness in the selection of appropriate thresholds to define extremes. We bypass this issue by using the Extended Generalized Pareto Distribution (ExtGPD), which jointly models low precipitation with a generalized Pareto distribution and extremes with a different Pareto tail, to conduct daily precipitation attribution across the contiguous United States (CONUS). We apply the ExtGPD to 12 general circulation models from the Coupled Model Intercomparison Project Phase 6 and compare counterfactual scenarios with and without anthropogenic emissions. Observed precipitation by the Climate Prediction Center is used for evaluating the GCMs. We find that greenhouse gases rather than natural variability can explain the observed magnitude of extreme daily precipitation, especially in the temperate regions. Our results highlight an unambiguous linkage of anthropogenic emissions to daily precipitation extremes across CONUS.}, year = {2024}, journal = {Geophysical Research Letters}, volume = {51}, number = {20}, pages = {e2024GL109553}, url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2024GL109553}, doi = {https://doi.org/10.1029/2024GL109553}, note = {e2024GL109553 2024GL109553}, }