UMBC High Performance Computing Facility
Please note that this page is under construction. We are documenting the
240-node cluster maya that will be available after Summer 2014.
Currently, the 84-node cluster tara still operates independently,
until it becomes part of maya at the end of Summer 2014.
Please see the 2013 Resources Pages under the Resources tab for tara information.
Improving estimates of CO emissions from biomass burning
using FRP and its applicability to atmospheric models
Lynn Sparling, Department of Physics
Thishan Dharshana Karandana Gamalathge, Department of Physics
Ray Hoff, Department of Physics
Vanderlei Martins, Department of Physics
Charles Ichoku, NASA
Biomass burning is getting increasing attention because large areas of
the globe burn each year, and these fires emit large amounts of smoke
and trace gases. In an attempt to find a relationship between total
carbon monoxide (CO) production and fire radiative energy (FRE), a
previous study has found proportionality between these two variables
with a relatively high correlation coefficient. However, that study was
performed under laboratory conditions, which might not replicate actual
conditions in forest fires. In our work, we are using CO total columns
retrieved from Terra-MOPITT and fire radiative power (FRP) measurements
from Terra-MODIS to investigate a similar relationship for actual
landscape fires. As a preliminary study for this task, we selected a few
prominent fires that were observed from the Terra satellite.
Interestingly, based on the analysis so far for the California fires in
2007, we have seen a convincing graphical association between CO total
column and FRP. Once the process is completed for other fires, we are
planning on utilizing this quantitative relationship between CO emission
rates and FRP to derive CO emissions from fires globally for use in
atmospheric models to forecast CO distribution. In this way, we will
help improve forecast tools for biomass burning emissions, based on
satellite data, which we can access in near real time. Moreover, this
would positively contribute to the estimates of biomass burning
contribution to global warming.