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Comparison of Single Cloud Model (SCM) Results for March of 2000 to the Prototype ARM Microbase Value Added Products (VAPs)

Kim, B.-G.(a), Klein, S.A.(b), Miller, M.A.(c), and Johnson, K.L.(c), Princeton University (a), GFDL/NOAA (b), Brookhaven National Laboratory (c)
Fourteenth Atmospheric Radiation Measurement (ARM) Science Team Meeting

The sophistication of cloud models in global climate model has increased dramatically over the last several decades. For latest improvements to be completely realized, however, model development must be followed by appropriate advancement of validation procedures to include more quantitative and strict assessments of model performances. Such procedures require the detailed observations of the evolving cloud state, which could be provided by the ARM program. In this study, one-month (March of 2000) of measurements over the ARM Southern Great Plain (SGP) site are used to evaluate treatment of clouds in the single cloud model (SCM) which uses the same parameterization as are in the GFDL climate model. Liquid and ice water equivalent reflectivities (Z) from the radar are first translated into liquid and ice water content (LWC and IWC), using given LWC-Z and IWC-Z relationships. The radar reflectivity is assumed to be temperature-dependent weighted fractions of the liquid and ice water reflectivities. The column integrated LWC is set equal to the liquid water path from the microwave radiometer (MWR), regardless of the precipitation. Meanwhile, clouds are parameterized with separate prognostic variables for the liquid and ice specific humidities in the model. Cloud fraction is also treated as a prognostic variable of the model following the parameterization of Tiedtke (1993). The SCM is forced with the variational forcing from Zhang et al. (1997). The preliminary results demonstrate that model cloud fractions are well correspondent with radar observations and generally model cloud persists slightly longer than observations. Also better agreement in cloud fraction is indicated in the lower layers.

Note: This is the poster abstract presented at the meeting; an extended version was not provided by the author(s).