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Title: Spatial and temporal agreement in climate model simulations of the Interdecadal Pacific Oscillation

Accelerated warming and hiatus periods in the long-term rise of Global Mean Surface Temperature (GMST) have, in recent decades, been associated with the Interdecadal Pacific Oscillation (IPO). Critically, decadal climate prediction relies on the skill of state-of-the-art climate models to reliably represent these low-frequency climate variations. We undertake a systematic evaluation of the simulation of the IPO in the suite of Coupled Model Intercomparison Project 5 (CMIP5) models. We track the IPO in pre-industrial (control) and all-forcings (historical) experiments using the IPO tripole index (TPI). The TPI is explicitly aligned with the observed spatial pattern of the IPO, and circumvents assumptions about the nature of global warming. We find that many models underestimate the ratio of decadal-to-total variance in sea surface temperatures (SSTs). However, the basin-wide spatial pattern of positive and negative phases of the IPO are simulated reasonably well, with spatial pattern correlation coefficients between observations and models spanning the range 0.4–0.8. Deficiencies are mainly in the extratropical Pacific. Models that better capture the spatial pattern of the IPO also tend to more realistically simulate the ratio of decadal to total variance. Of the 13% of model centuries that have a fractional bias in the decadal-to-total TPI variance ofmore » 0.2 or less, 84% also have a spatial pattern correlation coefficient with the observed pattern exceeding 0.5. This result is highly consistent across both IPO positive and negative phases. This is evidence that the IPO is related to one or more inherent dynamical mechanisms of the climate system.« less
Authors:
 [1] ;  [2] ;  [3] ;  [4] ;  [1] ;  [5] ;  [1] ;  [3] ;  [6] ;  [1] ;  [7]
  1. Univ. of Melbourne, VIC (Australia). School of Earth Sciences; Australian Research Council's Centre of Excellence for Climate System Science, Melbourne, VIC (Australia)
  2. National Center for Atmospheric Research, Boulder, CO (United States)
  3. Bureau of Meteorology, Melbourne, VIC (Australia)
  4. Met Office, Exeter (United Kingdom). Hadley Centre; Univ. of East Anglia, Norwich (United Kingdom). School of Environmental Sciences; Univ. of Gothenburg (Sweden). Dept. of Earth Sciences; Univ. of Southern Queensland, Toowoomba, QLD (Australia). International Centre for Applied Climate Sciences
  5. Commonwealth Scientific and Industrial Research Organization (CSIRO) Agriculture and Food, Hobart, TAS (Australia)
  6. Australian Research Council's Centre of Excellence for Climate System Science, Melbourne, VIC (Australia); Monash Univ., Melbourne, VIC (Australia). School of Earth, Atmosphere and Environment
  7. Univ. of Bern (Switzerland). Inst. of Geography. Oeschger Centre for Climate Change Research
Publication Date:
Grant/Contract Number:
FC2-97ER62402; LP150100062; CE110001028; GA01101; PZ00P2_154802
Type:
Accepted Manuscript
Journal Name:
Environmental Research Letters
Additional Journal Information:
Journal Volume: 12; Journal Issue: 4; Journal ID: ISSN 1748-9326
Publisher:
IOP Publishing
Research Org:
National Center for Atmospheric Research, Boulder, CO (United States); Univ. of Melbourne, VIC (Australia); Univ. of Bern (Switzerland); Met Office, Exeter (United Kingdom)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); National Science Foundation (NSF); Australian Research Council (ARC) (Australia); Dept. for Business, Energy and Industrial Strategy (BEIS) (United Kingdom); Dept. for Environment, Food and Rural Affairs (DEFRA) (United Kingdom); Swiss National Science Foundation (NSF) (Switzerland)
Contributing Orgs:
Australian Research Council's Centre of Excellence for Climate System Science, Melbourne, VIC (Australia); Bureau of Meteorology, Melbourne, VIC (Australia); Univ. of East Anglia, Norwich (United Kingdom); Univ. of Gothenburg (Sweden); Univ. of Southern Queensland, Toowoomba, QLD (Australia); Commonwealth Scientific and Industrial Research Organization (CSIRO) Agriculture and Food, Hobart, TAS (Australia); Monash Univ., Melbourne, VIC (Australia)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Interdecadal Pacific Oscillation; Pacific Decadal Oscillation; Pacific Decadal Variability; IPO; PDO; CMIP5; model evaluation
OSTI Identifier:
1361666

Henley, Benjamin J., Meehl, Gerald, Power, Scott B., Folland, Chris K., King, Andrew D., Brown, Jaclyn N., Karoly, David J., Delage, Francois, Gallant, Ailie J. E., Freund, Mandy, and Neukom, Raphael. Spatial and temporal agreement in climate model simulations of the Interdecadal Pacific Oscillation. United States: N. p., Web. doi:10.1088/1748-9326/aa5cc8.
Henley, Benjamin J., Meehl, Gerald, Power, Scott B., Folland, Chris K., King, Andrew D., Brown, Jaclyn N., Karoly, David J., Delage, Francois, Gallant, Ailie J. E., Freund, Mandy, & Neukom, Raphael. Spatial and temporal agreement in climate model simulations of the Interdecadal Pacific Oscillation. United States. doi:10.1088/1748-9326/aa5cc8.
Henley, Benjamin J., Meehl, Gerald, Power, Scott B., Folland, Chris K., King, Andrew D., Brown, Jaclyn N., Karoly, David J., Delage, Francois, Gallant, Ailie J. E., Freund, Mandy, and Neukom, Raphael. 2017. "Spatial and temporal agreement in climate model simulations of the Interdecadal Pacific Oscillation". United States. doi:10.1088/1748-9326/aa5cc8. https://www.osti.gov/servlets/purl/1361666.
@article{osti_1361666,
title = {Spatial and temporal agreement in climate model simulations of the Interdecadal Pacific Oscillation},
author = {Henley, Benjamin J. and Meehl, Gerald and Power, Scott B. and Folland, Chris K. and King, Andrew D. and Brown, Jaclyn N. and Karoly, David J. and Delage, Francois and Gallant, Ailie J. E. and Freund, Mandy and Neukom, Raphael},
abstractNote = {Accelerated warming and hiatus periods in the long-term rise of Global Mean Surface Temperature (GMST) have, in recent decades, been associated with the Interdecadal Pacific Oscillation (IPO). Critically, decadal climate prediction relies on the skill of state-of-the-art climate models to reliably represent these low-frequency climate variations. We undertake a systematic evaluation of the simulation of the IPO in the suite of Coupled Model Intercomparison Project 5 (CMIP5) models. We track the IPO in pre-industrial (control) and all-forcings (historical) experiments using the IPO tripole index (TPI). The TPI is explicitly aligned with the observed spatial pattern of the IPO, and circumvents assumptions about the nature of global warming. We find that many models underestimate the ratio of decadal-to-total variance in sea surface temperatures (SSTs). However, the basin-wide spatial pattern of positive and negative phases of the IPO are simulated reasonably well, with spatial pattern correlation coefficients between observations and models spanning the range 0.4–0.8. Deficiencies are mainly in the extratropical Pacific. Models that better capture the spatial pattern of the IPO also tend to more realistically simulate the ratio of decadal to total variance. Of the 13% of model centuries that have a fractional bias in the decadal-to-total TPI variance of 0.2 or less, 84% also have a spatial pattern correlation coefficient with the observed pattern exceeding 0.5. This result is highly consistent across both IPO positive and negative phases. This is evidence that the IPO is related to one or more inherent dynamical mechanisms of the climate system.},
doi = {10.1088/1748-9326/aa5cc8},
journal = {Environmental Research Letters},
number = 4,
volume = 12,
place = {United States},
year = {2017},
month = {1}
}