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The Impacts of Horizontal Resolution on the Seasonally Dependent Biases of the Northeastern Pacific ITCZ in Coupled Climate Models

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  • 1 Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington
  • 2 Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California
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ABSTRACT

The double-ITCZ bias has puzzled the climate modeling community for more than two decades. Here we show that, over the northeastern Pacific Ocean, precipitation and sea surface temperature (SST) biases are seasonally dependent in the NCAR CESM1 and 37 CMIP5 models, with positive biases during boreal summer–autumn and negative biases during boreal winter–spring, although the easterly wind bias persists year round. This seasonally dependent bias is found to be caused by the model’s failure to reproduce the climatological seasonal wind reversal of the North American monsoon. During winter–spring, the observed easterly wind dominates, so the simulated stronger wind speed enhances surface evaporation and lowers SST. It is opposite when the observed wind turns to westerly during summer–autumn. An easterly wind bias, mainly evident in the lower troposphere, also occurs in the atmospheric model when the observed SST is prescribed, suggesting that it is of atmospheric origin. When the atmospheric model resolution is doubled in the CESM1, both SST and precipitation are improved in association with the reduced easterly wind bias. During boreal spring, when the double-ITCZ bias is most significant, the northern and southern ITCZ can be improved by 29.0% and 18.8%, respectively, by increasing the horizontal resolution in the CESM1. When dividing the 37 CMIP5 models into two groups on the basis of their horizontal resolutions, it is found that both the seasonally dependent biases over the northeastern Pacific and year-round biases over the southeastern Pacific are reduced substantially in the higher-resolution models, with improvement of ~30% in both regions during boreal spring. Close relationships between wind and precipitation biases over the northeastern and southeastern Pacific are also found among CMIP5 models.

© 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Fengfei Song, fengfei.song@pnnl.gov

ABSTRACT

The double-ITCZ bias has puzzled the climate modeling community for more than two decades. Here we show that, over the northeastern Pacific Ocean, precipitation and sea surface temperature (SST) biases are seasonally dependent in the NCAR CESM1 and 37 CMIP5 models, with positive biases during boreal summer–autumn and negative biases during boreal winter–spring, although the easterly wind bias persists year round. This seasonally dependent bias is found to be caused by the model’s failure to reproduce the climatological seasonal wind reversal of the North American monsoon. During winter–spring, the observed easterly wind dominates, so the simulated stronger wind speed enhances surface evaporation and lowers SST. It is opposite when the observed wind turns to westerly during summer–autumn. An easterly wind bias, mainly evident in the lower troposphere, also occurs in the atmospheric model when the observed SST is prescribed, suggesting that it is of atmospheric origin. When the atmospheric model resolution is doubled in the CESM1, both SST and precipitation are improved in association with the reduced easterly wind bias. During boreal spring, when the double-ITCZ bias is most significant, the northern and southern ITCZ can be improved by 29.0% and 18.8%, respectively, by increasing the horizontal resolution in the CESM1. When dividing the 37 CMIP5 models into two groups on the basis of their horizontal resolutions, it is found that both the seasonally dependent biases over the northeastern Pacific and year-round biases over the southeastern Pacific are reduced substantially in the higher-resolution models, with improvement of ~30% in both regions during boreal spring. Close relationships between wind and precipitation biases over the northeastern and southeastern Pacific are also found among CMIP5 models.

© 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Fengfei Song, fengfei.song@pnnl.gov
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