Extra-tropical origin of equatorial Pacific cold bias in climate models with links to cloud albedo
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General circulation models frequently suffer from a substantial cold bias in equatorial Pacific sea surface temperatures (SSTs). For instance, the majority of the climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) have this particular problem (17 out of the 26 models evaluated in the present study). Here, we investigate the extent to which these equatorial cold biases are related to mean climate biases generated in the extra-tropics and then communicated to the equator via the oceanic subtropical cells (STCs). With an evident relationship across the CMIP5 models between equatorial SSTs and upper ocean temperatures in the extra-tropical subduction regions, our analysis suggests that cold SST biases within the extra-tropical Pacific indeed translate into a cold equatorial bias via the STCs. An assessment of the relationship between these extra-tropical SST biases and local surface heat flux components indicates a link to biases in the simulated shortwave fluxes. Further sensitivity studies with a climate model (CESM) in which extra-tropical cloud albedo is systematically varied illustrate the influence of cloud albedo perturbations, not only directly above the oceanic subduction regions but across the extra-tropics, on the equatorial bias. The CESM experiments reveal a quadratic relationship between extra-tropical Pacific albedo and the root-mean-square-error in equatorial SSTs—a relationship with which the CMIP5 models generally agree. Thus, our study suggests that one way to improve the equatorial cold bias in the models is to improve the representation of subtropical and mid-latitude cloud albedo.
KeywordsCold tongue bias Tropical Pacific couple modeling Extra-tropical cloud albedo
This research is supported by grants from NOAA:NA14OAR4310277 and NSF:AGS-1405272, as well as Grants NSF:AGS-1338427, NASA:NNX14AM19G, and NOAA:NA14OAR4310160. The CESM project is supported by the National Science Foundation and the Department of Energy Office of Science. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Table 1 of this paper) for producing and making available their model output. For CMIP the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We also acknowledge the U.K. Met. Office for use of the HadISST dataset downloaded from http://www.metoffice.gov.uk/hadobs/hadisst/; WOA 2013 from https://www.nodc.noaa.gov/OC5/woa13/; CERES-EBAF Ed2.8 obtained from the National Aeronautics and Space Administration Langley Research Center Atmospheric Science Data Center (http://ceres.larc.nasa.gov/cmip5_data.php); the Large and Yeager COREV2 dataset from https://climatedataguide.ucar.edu/climate-data/large-yeager-air-sea-surface-flux-corev2-1949-2006; the WHOI OAFlux from http://oaflux.whoi.edu/data.html; IFREMER turbulent fluxes from http://apdrc.soest.hawaii.edu/datadoc/ifremer_flux_day.php; and the ISCCP D2 Data from http://isccp.giss.nasa.gov/products/browsed2.html. We thank Brian Dobbins for his assistance in setting up the CESM simulations, as well as Bohua Huang and Matthew Thomas for insightful discussions.
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