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The effects of climate model similarity on probabilistic climate projections and the implications for local, risk‐based adaptation planning
Author(s) -
Steinschneider Scott,
McCrary Rachel,
Mearns Linda O.,
Brown Casey
Publication year - 2015
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1002/2015gl064529
Subject(s) - climate model , probabilistic logic , climate change , coupled model intercomparison project , environmental science , variance (accounting) , probability density function , statistical model , adaptation (eye) , climatology , econometrics , statistics , mathematics , ecology , geology , economics , physics , accounting , optics , biology
Approaches for probability density function (pdf) development of future climate often assume that different climate models provide independent information, despite model similarities that stem from a common genealogy (models with shared code or developed at the same institution). Here we use an ensemble of projections from the Coupled Model Intercomparison Project Phase 5 to develop probabilistic climate information, with and without an accounting of intermodel correlations, for seven regions across the United States. We then use the pdfs to estimate midcentury climate‐related risks to a water utility in one of the regions. We show that the variance of climate changes is underestimated across all regions if model correlations are ignored, and in some cases, the mean change shifts as well. When coupled with impact models of the hydrology and infrastructure of a water utility, the underestimated likelihood of large climate changes significantly alters the quantification of risk for water shortages by midcentury.