Enhancing Great Plains Nocturnal Precipitation and Low-Level Jets in AM4 with an Extended CLUBB Closure

In this study, we extend the Cloud Layers Unified by Binormals (CLUBB) turbulence scheme within the GFDL atmospheric model (AM4) by implementing direct momentum-flux prognosis and a multiscale turbulent length scale, to improve the simulation of nocturnal precipitation and associated Low-Level Jets (LLJs) over the Great Plains (GP). Towards this aim, we set up four AM4-CLUBB configurations: diagnosed momentum flux, prognosed momentum flux, diagnosed momentum flux with a multiscale turbulent lengtshcale, and prognosed momentum flux with a multiscale turbulent lengtshcale. Simulations are evaluated against the AM4 control, the Integrated Multi-satellitE Retrievals for GPM (IMERG), and the Doppler wind radar profiles from the Atmospheric Radiation Measurement (ARM) program. Results show that all AM4-CLUBB configurations improve the precipitation timing from the unrealistic midday peak seen in the AM4 control simulation toward the satellite-observed nocturnal maximum. The configuration that prognoses momentum flux and uses a multi-scale turbulent length scale, best matches the timing and intensity of GP precipitation rate. This configuration is also that which more accurately simulates the ARM-observed nocturnal LLJ wind profiles, while increasing the frequency of counter-gradient momentum fluxes near the LLJ core compared to prognosing momentum fluxes with the original AM4-CLUBB turbulent lengthscale. Momentum budget analysis attributes this increase to a nearly fivefold enhancement in the buoyancy production term when using the multiscale formulation, and leads to stronger nocturnal convective activity, as diagnosed from the greater vertical velocity skewness and plume asymmetry.

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Publication Details

Published
2025-08-14
DOI
https://doi.org/10.22541/au.175519398.83690415/v1
Primary Topic
Expert finding and Q&A systems
Type
article
Field-Weighted Citation Impact
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article

Enhancing Great Plains Nocturnal Precipitation and Low-Level Jets in AM4 with an Extended CLUBB Closure

Expert finding and Q&A systems
article

Enhancing Great Plains Nocturnal Precipitation and Low-Level Jets in AM4 with an Extended CLUBB Closure

article en

Abstract

In this study, we extend the Cloud Layers Unified by Binormals (CLUBB) turbulence scheme within the GFDL atmospheric model (AM4) by implementing direct momentum-flux prognosis and a multiscale turbulent length scale, to improve the simulation of nocturnal precipitation and associated Low-Level Jets (LLJs) over the Great Plains (GP). Towards this aim, we set up four AM4-CLUBB configurations: diagnosed momentum flux, prognosed momentum flux, diagnosed momentum flux with a multiscale turbulent lengtshcale, and prognosed momentum flux with a multiscale turbulent lengtshcale. Simulations are evaluated against the AM4 control, the Integrated Multi-satellitE Retrievals for GPM (IMERG), and the Doppler wind radar profiles from the Atmospheric Radiation Measurement (ARM) program. Results show that all AM4-CLUBB configurations improve the precipitation timing from the unrealistic midday peak seen in the AM4 control simulation toward the satellite-observed nocturnal maximum. The configuration that prognoses momentum flux and uses a multi-scale turbulent length scale, best matches the timing and intensity of GP precipitation rate. This configuration is also that which more accurately simulates the ARM-observed nocturnal LLJ wind profiles, while increasing the frequency of counter-gradient momentum fluxes near the LLJ core compared to prognosing momentum fluxes with the original AM4-CLUBB turbulent lengthscale. Momentum budget analysis attributes this increase to a nearly fivefold enhancement in the buoyancy production term when using the multiscale formulation, and leads to stronger nocturnal convective activity, as diagnosed from the greater vertical velocity skewness and plume asymmetry.

Swedish Meteorological and Hydrological Institute (SE), Pennsylvania State University (US), National Oceanic and Atmospheric Administration (US), Stockholm University (SE), NOAA Geophysical Fluid Dynamics Laboratory (US), Princeton University (US), University of Wisconsin–Milwaukee (US)
National Science Foundation, National Oceanic and Atmospheric Administration
Climate action
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Expert finding and Q&A systems
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