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Nonlocal Turbulent Mixing Based on Convective Adjustment Concepts (Ntac)
Authors:William H Raymond
Institution:(1) Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin, 1225 West Dayton Street, Madison, Wisconsin, 53706, U.S.A.
Abstract:A nonlocal turbulent mixing parameterization is introduced in this study and denoted by the acronym NTAC, which stands for Nonlocal parameterization of Turbulent mixing using convective Adjustment Concepts. NTAC uses the average value of quantities in the turbulent domain in much the same way that local convective adjustment schemes use the average potential temperature. Averages are determined in the region with non-convective turbulence using information from the two end layers (denoted by TLA, Two Layer Average), while all layers contribute to the average in regions with convective turbulence (denoted by CLA, Convective Layer Average). The NTAC parameterization estimates the mixing percentage and uses this percentage as a mixing coefficient. These percentages are determined from a simplified turbulent kinetic energy equation. The scheme is versatile, conservative, and when programmed efficiently the proposed parameterization is a computationally acceptable nonlocal procedure that can be used in many existing numerical weather prediction forecast models.Numerical weather forecast model simulations using the NTAC parameterization and traditional K-theory are compared against radiosonde data. The accuracy of the proposed NTAC parameterization is found to be competitive with K theory. The greatest improvement of the NTAC over K-theory occurs during the daytime and early nighttime hours when (dry) convective activity is high. Also, areal cloud coverage is increased by the NTAC parameterization. Our findings show that the greatest nonlocal vertical mixing occurs between the layer nearest the earth's surface and the remaining layers making up the planetary boundary layer.
Keywords:Convective adjustment  Turbulence  Mixing  Nonlocal mixing  Parameterization  Numerical weather prediction
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