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AN APPROACH TO REPRESENT MESOSCALE (SUBGRID-SCALE) FLUXES IN GCMs DEMONSTRATED WITH SIMULATIONS OF LOCAL DEFORESTATION IN AMAZONIA

Published online by Cambridge University Press:  05 November 2011

R. Avissar
Affiliation:
Rutgers University
F. Chen
Affiliation:
Rutgers University
Reinder A. Feddes
Affiliation:
Agricultural University, Wageningen, The Netherlands
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Summary

ABSTRACT Mesoscale circulations generated by landscape discontinuities (i.e. ‘seabreeze’ like circulations) are likely to have a significant impact on the hydrological cycle, the climate, and the weather. However, these processes are not represented in large-scale atmospheric models (e.g. general circulation models (GCMs)), which have an inappropriate grid-scale resolution. Assuming that atmospheric variables can be separated into large-scale, mesoscale, and turbulent-scale, Avissar and Chen (1993) developed a set of prognostic equations applicable in GCMs for momentum, temperature, moisture, and any other gaseous or aerosol material, which include both mesoscale and turbulent fluxes. They suggested using the mean mesoscale kinetic energy (MKE) per unit of mass for parametrizing these mesoscale fluxes in such models. In the present study, which complements the work of Avissar and Chen (1993), we simulated the atmospheric planetary boundary layer (PBL) that develops above a locally deforested area of the Amazonian region, to illustrate the relationships that exist: (i) between the diurnal variation of MKE and the diurnal variation of mesoscale latent and sensible heat fluxes; and (ii) between landscape discontinuities resulting from horizontal gradients of moisture at the ground surface and MKE. We compared MKE with turbulence kinetic energy (TKE) to emphasize the magnitude of mesoscale processes, as compared to turbulent processes. This analysis illustrates the potential use of MKE to bridge between landscape discontinuities and mesoscale fluxes and, therefore, to parametrize mesoscale fluxes generated by such subgrid-scale landscape discontinuities in GCMs and other largescale atmospheric models. […]

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Publisher: Cambridge University Press
Print publication year: 1995

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