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Cloud-Resolving Large-Eddy Simulation of Tropical Convective Development and Surface Fluxes Public Deposited

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  • Cloud-resolving large-eddy simulations (LES) on a 500 km × 500 km periodic domain coupled to a thermodynamic ocean mixed layer are used to study the effect of large-scale moisture convergence M on the convective population and heat and moisture budgets of the tropical atmosphere, for several simulations with M representative of the suppressed, transitional, and active phases of the Madden–Julian oscillation (MJO). For a limited-area model without an imposed vertical velocity, M controls the overall vertical temperature structure. Moisture convergence equivalent to ~200 W m⁻² (9 mm day⁻¹) maintains the observed temperature profile above 5 km. Increased convective heating for simulations with higher M is partially offset by greater infrared cooling, suggesting a potential negative feedback that helps maintain the weak temperature gradient conditions observed in the tropics. Surface evaporation decreases as large-scale moisture convergence increases, and is only a minor component of the overall water budget for convective conditions representing the active phase of the MJO. Cold pools generated by evaporation of precipitation under convective conditions are gusty, with roughly double the wind stress of their surroundings. Consistent with observations, enhanced surface evaporation due to cold pool gusts is up to 40% of the mean, but has a small effect on the total moisture budget compared to the imposed large-scale moisture convergence.
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  • Skyllingstad, E. D., & de Szoeke, S. P. (2015). Cloud-resolving large-eddy simulation of tropical convective development and surface fluxes. Monthly Weather Review, 143(7), 2441-2458. doi:10.1175/MWR-D-14-00247.1
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  • 143
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  • 7
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  • This research was funded by the National Science Foundation Grant OCE-1129419, the Office of Naval Research Grant N00014-10-1-0299, and the National Oceanic and Atmospheric Administration Grants NA11OAR4310076 and NA13OAR4310157. We would like to acknowledge high-performance computing support from Yellowstone (ark:/85065/d7wd3xhc) provided by NCAR's Computational and Information Systems Laboratory, sponsored by the National Science Foundation, and from the Department of Defense High Performance Computer Modernization Program.
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