A54B-02:
On the Specification of Smoke Injection Heights for Aerosol Forecasting

Friday, 19 December 2014: 4:15 PM
Arlindo da Silva, NASA Goddard Space Flight Center, Greenbelt, MD, United States, Caitlin Schaefer, University of Washington Seattle Campus, Seattle, WA, United States and Cynthia A Randles, GESTAR/Morgan State University/NASA GSFC Code 614, Greenbelt, MD, United States
Abstract:
The proper forecasting of biomass burning (BB) aerosols in global or regional transport models requires not only the specification of emission rates with sufficient temporal resolution but also the injection layers of such emissions. While current near realtime biomass burning inventories such as GFAS, QFED, FINN, GBBEP and FLAMBE provide such emission rates, it is left for each modeling system to come up with its own scheme for distributing these emissions in the vertical.
A number of operational aerosol forecasting models deposits BB emissions in the near surface model layers, relying on the model's parameterization of turbulent and convective transport to determine the vertical mass distribution of BB aerosols. Despite their simplicity such schemes have been relatively successful reproducing the vertical structure of BB aerosols, except for those large fires that produce enough buoyancy to puncture the PBL and deposit the smoke at higher layers. Plume Rise models such as the so-called 'Freitas model', parameterize this sub-grid buoyancy effect, but require the specification of fire size and heat fluxes, none of which is readily available in near real-time from current remotely-sensed products.
In this talk we will introduce a bayesian algorithm for estimating file size and heat fluxes from MODIS brightness temperatures. For small to moderate fires the Freitas model driven by these heat flux estimates produces plume tops that are highly correlated with the GEOS-5 model estimate of PBL height. Comparison to MINX plume height
estimates from MISR indicates moderate skill of this scheme predicting the injection height of large fires. As an alternative, we make use of OMPS UV aerosol index data in combination with estimates of Overshooting Convective Tops (from MODIS and Geo-stationary satellites) to detect PyCu events and specify the BB emission vertical mass distribution in such cases. We will present a discussion of case studies during the SEAC4RS field campaign in August-September 2013.