HR: 1340h
AN: GC23A-0992 [Abstracts]
TI: Wildfire, Ecosystems and Climate in Siberia: Developing Weather and Climate Data Sets for Use in Fire Weather and Bioclimatic Models
AU: * Westberg, D J
EM: David.J.Westberg@nasa.gov
AF: Science Systems and Applications Inc., 1 Enterprise Parkway
Suite 200, Hampton, VA 23666, United States
AU: Soja, A J
EM: Amber.J.Soja@nasa.gov
AF: NASA Langley Research Center, Mail Stop 420, Hampton, VA 23681, United States
AU: Stackhouse, P W
EM: Paul.W.Stackhouse@nasa.gov
AF: NASA Langley Research Center, Mail Stop 420, Hampton, VA 23681, United States
AB:
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. It is predicted that fire frequency, area burned, fire severity, fire season
length, and severe fire seasons will increase under current climate change scenarios. Already, there is evidence
of an increased number of extreme fire seasons in Siberia that correlate with current warming. 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, which is to examine the
relationships between weather, extreme fire events, and fire-induced land cover change in the changing climate
of Siberia.
The primary focus in this presentation is the description of the assembled weather and climate data sets and the
verification efforts, followed by an example where the data set is used in a fire prediction application. Ground-
based weather observations from the National Climatic Data Center (NCDC) for the years 1983-2006, have been
used to verify various modeled meteorological parameters from the NASA Goddard Earth Observing System
version 4 (GEOS-4) data. Specifically, we have extracted "Summary of the Day" and "Integrated Surface Hourly
(ISH)" weather data from the NCDC. The ISH data has been processed to obtain hourly observation times for all
stations in Siberia, including Mongolia and parts of northern China. A subset of these stations have been
selected for validation purposes if they meet a criteria of having at least 75% of the possible reporting
observations per day and 75% of the possible days in each month. GEOS-4 data interpolated to a 1x1 degree
grid have compared well with the NCDC station data, covering the burning season from April through September
and for the entire 1983-2006 period. In cases where large differences exist between the NCDC station and the
GEOS-4 grid elevations, lapse rate corrections have been applied to the temperature parameters. With the
declining number of Siberian surface observation stations through the 1983-2006 period, using GEOS-4 data
ensures data coverage over the entire Siberian region and through the entire data set period.
One advantage of the GEOS-4 data is that it is consistent and spatially explicit, which makes it easily portable to
multiple data applications or models. One such application being used in this study is the Canadian Forest Fire
Weather Index (FWI) System developed by the Canadian Forestry Service. Using local noon values of air
temperature, relative humidity, wind speed, and daily rainfall as input, the FWI assesses the conditions of forest
fire burning potential for the day. Typically, local weather observation stations supply these meteorological
parameters. In Siberia, the density of stations is limited; hence results may not be representative of the spatial
reality. GEOS-4 data, on the other hand, provides complete temporal and spatial coverage. Using the GEOS-4
meteorological data as input into the FWI, the generated indices compare well with large and small fires in the
1983 to 2006 timeframe.
DE: 0550 Model verification and validation
DE: 1630 Impacts of global change (1225)
DE: 1631 Land/atmosphere interactions (1218, 1843, 3322)
DE: 1632 Land cover change
DE: 1637 Regional climate change
SC: Global Environmental Change [GC]
MN: 2007 Fall Meeting