Wildfire, Ecosystems and Climate in Siberia: Developing Weather and Climate Data Sets For Use in Fire Weather and Bioclimatic Models
David
Westberg, Science Systems and Applications Inc., david.j.westberg@nasa.gov
Amber
Soja, National Institute of Aerospace, resident NASA LaRC, amber.j.soja@nasa.gov
(Presenting)
Paul
Stackhouse, NASA Langley Research Center, paul.w.stackhouse@nasa.gov
A primary driving force of land cover change in boreal regions is fire, and extreme fire seasons are influenced by local weather and ultimately climate. Already, there is evidence of an increased number of extreme fire seasons in Siberia that correlate with current warming. Fire is a catalyst of change, which strongly affects the carbon balance, particularly in boreal regions where the largest amount of terrestrial carbon is stored. Our overall goal is to explore the degree to which current and future climate variability has and will affect wildfire-induced land cover change and to highlight the significance of the interaction between the biosphere and the climate system.
Developing reliable weather and climate data provides the backbone of this research. The number of Siberian surface observation stations are sparse; they do not consistently record data; and they have been declining over the 1983-2006 period.
GEOS-4 meteorological parameters, interpolated to a 1x1 degree grid, compare well with the National Climatic Data Center (NCDC) surface station data, covering the burning season from March through October for the entire 1983-2006 period. The GEOS-4 data can be used in areas where no surface stations are available or are sparsely distributed. One additional advantage of the GEOS-4/GPCP data is its consistency in space and time making it easily portable to multiple data applications or models.
The Canadian Fire Weather Index (FWI) is generated to analyze differences in an extreme fire year (2002) and a normal fire year (1999) in Yakutia. Both the GEOS-4 meteorological and GPCP data are used as input to the FWI. These data compare well in magnitude (< 10 FWI units) and variability to the 1999 and 2002 Yakutian site data. This agreement gives us optimism that these data could be used as inputs to a fire weather prediction system or in a bioclimatic model.
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