Abstract

Earth system models parameterize ocean surface fluxes of heat, moisture, and momentum with empirical bulk flux algorithms, which introduce biases and uncertainties into simulations. We investigate the atmosphere and ocean model sensitivity to algorithm choice in the Energy Exascale Earth System Model (E3SM). Flux differences between algorithms are larger in atmosphere simulations (where wind speeds can vary) than ocean simulations (where wind speeds are fixed by forcing data). Surface flux changes lead to global scale changes in the energy and water cycles, notably including ocean heat uptake and global mean precipitation rates. Compared to the control algorithm, both COARE and University of Arizona (UA) algorithms reduce global mean precipitation and top of atmosphere radiative biases. Further, UA may slightly reduce biases in ocean meridional heat transport. We speculate that changes seen here, especially in the ocean, could be even larger in coupled simulations.

Highlights

  • Ocean surface fluxes of heat, moisture, and momentum control the ocean’s impact on weather and climate

  • What is perhaps more surprising is the degree of consistency of the global mean latent heat flux and net surface heat flux sensitivity

  • The impact of wind speed-flux feedbacks on the atmosphere simulation sensitivity highlights the central role of wind speed in determining fluxes

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Summary

Introduction

Ocean surface fluxes of heat, moisture, and momentum control the ocean’s impact on weather and climate. The methods used to calculate ocean surface turbulent fluxes in numerical models and global observational products rely on bulk flux algorithms. These algorithms use “bulk” quantities—sea surface temperature (SST) and near-surface values of air temperature, humidity, and wind speed— which are easier to measure than direct measurements of fluxes (e.g., Edson et al, 1998), and can be measured by remote sensing platforms. Bulk algorithms have been compared by Zeng et al (1998), Brunke et al (2002, 2003), and Brodeau et al (2016), among others While these studies are valuable for understanding how different aspects of algorithm design affect surface flux estimates, they have one limitation when it comes to understanding impacts on model results: they are based on comparison of fluxes using pre-specified bulk variables.

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