Regional estimates of deep convective transport have been made through use of a traveling one-dimensional model, regional transport models driven by parameterized convective mass fluxes from me so scale meteorological models, and a statistical -dynamical approach. Chatfield and Del any (1990) simulated convective transport for a hypothetical case over South America during the biomass bunting season using a traveling one-dimensional model containing cloud-scale vertical transport and chemistry. They showed that the "mix-then-cpok" scenario of rapid vertical transport of ozone precursors in deep convection allowed a more persistent increase in the tropospheric ozone column over a wide region than did the "cook-then-mix" scenario of transport in a fair weather boundary layer for several days prior to venting.

Pickering et al. (1992c) used a combination of deep convective cloud cover statistics from the International Satellite Cloud Climatology Project (ISCCP) and convective transport statistics from GCE model simulations of prototype storms to estimate that between 10 and 40% of CO from biomass burning in the Brazilian state of Rondonia is vented from the boundary layer by deep convection. The statistical-dynamical approach was also used by Thompson et al. (1994) to estimate the convective transport component of the boundary layer CO budget for the central United States for the month of June (Fig. 9). Deep convective venting of the boundary layer dominated other components of the CO budget during early summer, providing a net (upward minus downward) flux of 18.1 x 108 kg CO/month to the free troposphere. In this respect the central United States acts as a "chimney" for the country.

Regional chemical transport models (CTMs) have been used for applications such as simulations of photochemical ozone production, acid deposition, and fine particulate matter. Walcek et al. (1990) included a parameterization of cloud-scale

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