Sensitivity of the shortwave radiative budget to the parameterization of ice crystal effective radius

Computer Science – Performance

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Atmospheric Processes: Clouds And Cloud Feedbacks, Atmospheric Composition And Structure: Cloud/Radiation Interaction, Atmospheric Composition And Structure: Radiation: Transmission And Scattering, Atmospheric Processes: Regional Modeling, Atmospheric Processes: Clouds And Aerosols

Scientific paper

A new effective particle size (R eff) parameterization for ice clouds has been formulated based on depth into cloud relative to cloud top. This parameterization has been developed based on an extensive data set of lidar and radar ice cloud retrievals. Using this parameterization within the stand-alone radiation code from the European Centre for Medium Range Weather Forecasting (cy23r4), the performance of the new parameterization is compared with the more commonly used parameterizations based on temperature and/or ice water content. An evaluation is performed on the basis of observed shortwave fluxes for 13 days with persistent ice cloud decks, with no liquid clouds beneath, over the Cabauw Experimental Site for Atmospheric Research in the Netherlands. For each of these clouds the shortwave flux is calculated after which the distribution of the differences between the observed and modeled shortwave fluxes from the combined 13 days are compared with each other. The new parameterization shows a median absolute difference of 0.7 W m-2 relative to the observations. The control parameterization based on temperature shows a median absolute difference of 15 W m-2. Within the framework of the KNMI regional climate model (RACMO2), the new parameterization yields an effective particle size versus temperature distribution very similar to the observed distributions from lidar and radar retrievals. Results from a 1-year integration indicate that the domain averaged monthly mean planetary albedo and transmissivity change by a maximum of 2.6 and 2.4%, respectively, using the new parameterization compared to the temperature-based parameterization.

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