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Pareto‐Optimal Estimates of California Precipitation Change
Author(s) -
Langenbrunner Baird,
Neelin J. David
Publication year - 2017
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 - 10.1002/2017gl075226
Subject(s) - precipitation , climatology , environmental science , climate change , range (aeronautics) , climate model , pareto principle , coupled model intercomparison project , middle latitudes , constraint (computer aided design) , meteorology , mathematics , mathematical optimization , geography , geology , oceanography , materials science , geometry , composite material
Abstract In seeking constraints on global climate model projections under global warming, one commonly finds that different subsets of models perform well under different objective functions, and these trade‐offs are difficult to weigh. Here a multiobjective approach is applied to a large set of subensembles generated from the Climate Model Intercomparison Project phase 5 ensemble. We use observations and reanalyses to constrain tropical Pacific sea surface temperatures, upper level zonal winds in the midlatitude Pacific, and California precipitation. An evolutionary algorithm identifies the set of Pareto‐optimal subensembles across these three measures, and these subensembles are used to constrain end‐of‐century California wet season precipitation change. This methodology narrows the range of projections throughout California, increasing confidence in estimates of positive mean precipitation change. Finally, we show how this technique complements and generalizes emergent constraint approaches for restricting uncertainty in end‐of‐century projections within multimodel ensembles using multiple criteria for observational constraints.