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Spatial patterns and driving mechanisms of mid‐Holocene hydroclimate in western North America
Author(s) -
Hermann Nicholas Wayne,
Oster Jessica Leigh,
Ibarra Daniel Enrique
Publication year - 2018
Publication title -
journal of quaternary science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.142
H-Index - 94
eISSN - 1099-1417
pISSN - 0267-8179
DOI - 10.1002/jqs.3023
Subject(s) - holocene , climatology , anticyclone , proxy (statistics) , paleoclimatology , arid , precipitation , climate model , climate change , atmospheric circulation , before present , climate pattern , environmental science , geology , physical geography , geography , oceanography , meteorology , paleontology , machine learning , computer science
Mid‐Holocene paleoclimate proxy records from drought‐sensitive western North America suggest widespread aridity in areas dominated by winter precipitation. We present spatial comparisons of a diverse network of moisture‐sensitive proxies with 12 global circulation model simulations from the Paleoclimate Model Intercomparison Project to determine the most important atmospheric drivers behind observed mid‐Holocene aridity in this region. Although model‐proxy agreement is low for most models, in part reflecting small mid‐Holocene precipitation anomalies, three show relatively strong agreement by successfully simulating arid conditions across the Pacific Northwest. The model that shows the strongest spatial agreement with the proxy network reveals an anticyclonic wind anomaly that is similar to but weaker than anomalies noted during west‐wide drought episodes of the past 500 years. This model suggests increased transient upper level ridging that reduced winter water vapor transport from the south‐west during the mid‐Holocene. These mechanisms are similar to those suggested to have supported megadrought conditions in western North America during the Medieval Climate Anomaly and which are also simulated in anthropogenic warming scenarios. Future work on quantitative proxy records to enhance temporal and spatial coverage, and explicitly address issues of seasonality, will improve the quality of future climate model–data comparison studies.