HR: 0800h
AN: B41B-0103    [Abstracts]
TI: Global Fire Patterns and Trends from ENSO Events Estimated Using an Enhanced Ecosystem Model
AU: * Girod, C M
EM: cary@eos.sr.unh.edu
AF: Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Morse Hall, 39 College Road, Durham, NH 03824 United States
AU: King, T W
EM: kingaw@ornl.gov
AF: Environmental Sciences Division, Oak Ridge National Laboratory, P.O. Box 2008, Mail Stop 6037 , Oak Ridge, TN 37831 United States
AU: Hurtt, G C
EM: george.hurtt@unh.edu
AF: Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Morse Hall, 39 College Road, Durham, NH 03824 United States
AB: Fires play a major role in structuring terrestrial ecosystems and in the exchanges between the biosphere and the atmosphere. They can affect vegetation density, size distribution, species composition, carbon and nutrient content of soils, as well as particulate and trace gas emissions. Since fires are strongly influenced by climate, their location, frequency, and severity may also be affected by climate change and variability. Models are needed to estimate the patterns and consequences of future fires. For reliability, these models should be validated with information from the past. A fire sub-model driven by climate and biomass was implemented in the 1§x1§ resolution Global Terrestrial Ecosystem Carbon model (GTEC 1.0) and was run for the years 1901 to 1998. Simulated fires were aggregated by vegetation type and by region and compared favorably to patterns from satellite-based fire products. For example, in 1997 model estimates of regional fire activity were within 1.4% in Northern Asia, 4.2% in Central America, 9.6% in North America, 11.5% in Europe, and 16.9% of all regions averaged globally when compared with the European Space Agency Fire Atlas. In order to identify spatial and temporal patterns that specifically relate to the El Nino Southern Oscillation (ENSO) phenomenon, model estimates were compared to the Southern Oscillation Index (SOI). The model correctly predicted fire variability in regions strongly affected by ENSO. Results suggest that this model could be used to predict global fire trends under climate change scenarios, and used as a component in Earth system models to assess the many potential consequences of altered global fire patterns.
DE: 3344 Paleoclimatology
DE: 1699 General or miscellaneous
DE: 1812 Drought
DE: 0400 Biogeosciences
SC: Biogeosciences [B]
MN: 2004 AGU Fall Meeting