A53A-3205:
The Influence of Land Cover Characterization on Emissions Estimates from the Fire INventory from NCAR (FINN)

Friday, 19 December 2014
Christine Wiedinmyer1, Yosuke Kimura2, Elena McDonald-Buller2 and Jeff Zheng2, (1)National Center for Atmospheric Research, Boulder, CO, United States, (2)University of Texas at Austin, Austin, TX, United States
Abstract:
Wildland fires and open burning can be substantial sources of ozone precursors and particulate matter. An increase in future drought frequency under changing climatic conditions may have complex and profound effects on the occurrence of fires. The Fire INventory from the National Center for Atmospheric Research (FINN) is a global fire emissions model that provides estimates from the open burning of biomass, including wildfires, agricultural fires, and prescribed burning, at a resolution of approximately 1 km2. FINN is especially applicable for use in global and regional chemical transport models because of its high spatial and temporal resolution necessary for capturing daily and diurnal variations in emissions and chemistry, consistency across geopolitical boundaries, and chemical speciation profiles for volatile organic compound emissions associated with fires. Land cover characterization is an essential component of the model, which determines the applied emission factors and fuel loadings. In the default FINN configuration, the type of vegetation burned at each fire pixel is determined by the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Type (LCT) product. The MODIS Vegetation Continuous Fields (VCF) product is used to identify the density of the vegetation at each active fire location. This study considers the effects of using alternative global or regional land cover databases in FINN on emissions estimates. These include GlobCover, which is a global land cover data product derived from observations by the MERIS sensor aboard the ENVISAT satellite mission, and a high-resolution regional land cover database for Texas and its neighboring states. The current representations of croplands in FINN and other global fire models lack specificity in distinguishing crop types. Cropland characterization and assignment of crop-specific emissions factors and fuel loadings in FINN are explored.