4.6 Article

A framework for detection and attribution of regional precipitation change: Application to the United States historical record

Journal

CLIMATE DYNAMICS
Volume 60, Issue 3-4, Pages 705-741

Publisher

SPRINGER
DOI: 10.1007/s00382-022-06321-1

Keywords

Extreme precipitation; Natural variability; Local impacts; Anthropogenic aerosols; CMIP6; DAMIP; Pearl causality

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This study develops a framework for regional detection and attribution of precipitation using output from global climate models, and applies it to the contiguous United States. By conducting tests using model output, the study is able to detect systematic trends in precipitation, attribute these trends to anthropogenic forcings, compute the effects of forcings over time, and map the effects of individual forcings.
Despite the emerging influence of anthropogenic climate change on the global water cycle, at regional scales the combination of observational uncertainty, large internal variability, and modeling uncertainty undermine robust statements regarding the human influence on precipitation. Here, we use output from global climate models in a perfect-data sense to develop a framework for conducting regional detection and attribution (D&A) for precipitation, starting with the contiguous United States (CONUS) where observational uncertainty is lower than in other regions. Our unified approach can simultaneously detect systematic trends in mean and extreme precipitation, attribute trends to anthropogenic forcings, compute the effects of forcings as a function of time, and map the effects of individual forcings. Model output is used to conduct a set of tests that yield a parsimonious representation for characterizing seasonal precipitation over the CONUS for the historical record (1900 to present day), which ensures our D&A is insensitive to structural uncertainty. Our framework is developed using synthetic data in a Pearl-causal perspective wherein causality can be identified using intervention-based simulations. While the hypothesis-based framework and accompanying generalized D&A formula we develop should be widely applicable, we include a strong caution that the hypothesis-guided simplification of the formula for the historical climatic record of CONUS as described in this paper will likely fail to hold in other geographic regions and under future warming.

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