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A Dynamically Computed Convective Time Scale for the Kain–Fritsch Convective Parameterization Scheme
Citation:
Bullock, R., Kiran Alapaty, J. Herwehe, AND J. Kain. A Dynamically Computed Convective Time Scale for the Kain–Fritsch Convective Parameterization Scheme. Monthly Weather Review. American Meteorological Society, Boston, MA, 143(6):2105-2120, (2015).
Impact/Purpose:
The National Exposure Research Laboratory′s (NERL′s)Atmospheric Modeling Division (AMAD) conducts research in support of EPA′s mission to protect human health and the environment. AMAD′s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation′s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.
Description:
Many convective parameterization schemes define a convective adjustment time scale τ as the time allowed for dissipation of convective available potential energy (CAPE). The Kain–Fritsch scheme defines τ based on an estimate of the advective time period for deep convective clouds within a grid cell, with limits of 1800 and 3600 s, based on practical cloud-lifetime considerations. In simulations from the Weather Research and Forecasting (WRF) Model using 12-km grid spacing, the value of τ often defaults to the lower limit, resulting in relatively rapid thermodynamics adjustments and high precipitation rates. Herein, a new computation for τ in the Kain–Fritsch scheme is implemented based on the depth of the buoyant layer and the convective velocity scale. This new τ formulation is applied using 12- and 36-km model grid spacing in conjunction with a previous modification that takes into account the radiation effects of parameterized convective clouds. The dynamically computed convective adjustment time scale is shown to reduce the precipitation bias by approximately 15% while also providing improved simulations of inland rainfall from tropical storms.
