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Interactions of Cumulus Convection and the Boundary Layer Over the Southern Great Plains

Krueger, S.K. (a), Luo, Y. (a), Lazarus, S.M. (a), and Xu, K.-M. (b), University of Utah (a), NASA Langley Research Center (b)
Eleventh Atmospheric Radiation Measurement (ARM) Science Team Meeting

We are using observations and cloud-resolving model (CRM) simulations to better understand the interaction between deep cumulus convection and the boundary layer over the southern Great Plains of the United States. The observations are from a 29-day ARM SCM IOP that took place at the ARM SGP site during June and July 1997. The cumulus effects in the boundary layer are due to rain evaporation and fluxes due to cumulus updrafts and downdrafts. These effects can substantially modify the boundary layer in regions of deep cumulus convection. The resulting cold pools may initiate new convection via lifting at their leading edge. We can estimate the cumulus effects in the boundary layer using ARM observations obtained during SCM IOPs. The ARM variational analysis provides Q_1 (the large-scale heat source due to sub-grid scale processes) and Q_2 (the large-scale water vapor sink due to sub-grid scale processes). In addition, we have estimates of Q_R (the large-scale radiative heating rate), the surface fluxes of sensible and latent heat due to turbulence, and the boundary layer depth. The turbulent flux profiles can be approximated using the observed surface fluxes and the boundary layer depth. The total cumulus effects in the boundary layer can then be estimated. Our CRM simulations can be analyzed analogously. Unlike the observations, the CRM simulations can also provide estimates of the individual components of the cumulus effects (i.e., rain evaporation and the cumulus fluxes of sensible and latent heat), as well as turbulent flux profiles based on third-moment turbulence closure. We have completed the observational analyses of three convectively active periods and one inactive period during the Summer 1997 SCM IOP. We plan to analyze the corresponding CRM results and compare them to the observational analyses, as well as to results from the NCEP single-column model.

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