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Variable Resolution Modeling of the Large-Scale Atmospheric Circulation Response to North Atlantic Sea-Surface Temperature (SST) Anomalies

$341,245FY2021GEONSF

University Of Washington, Seattle WA

Investigators

Abstract

The extent to which the atmospheric circulation responds to changes in the underlying sea surface temperature (SST) is a central topic in climate dynamics. In the tropics the response of atmospheric circulation to SST variability is easily seen in the evolution of El Nino events. But in the middle and high latitudes there is no comparably strong and unambiguous attribution of circulation change to variations in underlying SST. Nevertheless recent research suggests that SST variability associated with the meandering of the Gulf Stream affects the decade-to-decade variability of the wintertime atmospheric circulation over much of the Northern Hemisphere. The observational evidence is suggestive but not conclusive, as the inherent noisiness of circulation variability and the short length of the observational record do not permit definitive attribution. Climate model simulations offer a way around the shortness of the observed record, along with the ability to design controlled experiments, and models using moderate resolution (say one gridpoint per degree of latitude and longitude) can generate very long simulations. But such simulations have not generally shown a circulation response to Gulf Stream SST variations, and recent experiments suggest that much higher resolutions are necessary to capture the physics and dynamics leading to the circulation response. Unfortunately global simulations using such high resolutions are too computationally intensive to permit in-depth experimentation. Research under this award considers the effects of Gulf Stream SST variations using a variable resolution (VR) model in which the grid spacing over most of the world is one degree but resolution over the Arctic and northern North Atlantic is increased to 1/8th degree, or about 12km between gridpoints. The model is a version of the Community Atmosphere Model (CAM), the atmospheric component model of the Community Earth System Model (CESM). Preliminary results show a robust hemispheric circulation response, with a spatial pattern similar to the North Atlantic Oscillation, forced by an imposed SST change representative of a Gulf Stream fluctuation. Further work compares the VR-CAM simulations with CAM simulations at lower resolution to identify the physics and dynamics captured by the high resolution. One hypothesis is that higher resolution is necessary to capture the influence of SST change on the rising motions associated with frontal weather systems as they cross the Gulf Stream. A further goal of the project is to use machine learning to develop parameterizations of the small-scale effects captured in the VR simulations so that they can be represented approximately at coarser and less computationally intensive model resolutions. The work has societal relevance due to the desirability of better understanding of decade-to-decade changes in the wintertime circulation over the Northern Hemisphere. Recent work suggests that the decadal circulation variabililty is more predictable than would be expected based on climate model simulations, suggesting that models may be missing key ingredients needed for successful long-range predictions. The work performed here may thus contribute to the development of models capable of long-range predictions with substantial societal value. In addition, the project contributes to the development of VR-CAM, which will be made available to the worldwide community of CESM users and developers. The Principal Investigators conduct outreach to the public through the University of Washington Program on Climate Change, as well as the Science Communication Fellowship Program at the Pacific Science Center in Seattle. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

View original record on NSF Award Search →