Analysis of the ability of fire weather to assess large-scale extreme fire events in Siberia in preparation for future fire weather prediction

Fire is the dominant disturbance that precipitates ecosystem change in boreal regions, and fire is largely under the control of weather and climate. Boreal systems contain the largest pool of terrestrial carbon, and Russia holds 2/3 of the boreal forests. Fire frequency, fire severity, area burned and fire season length are predicted to increase in boreal regions under current climate change scenarios. Therefore to predict fire weather and ecosystem change, we must understand the factors that influence fire regimes and at what scale these are viable. The goal of this research is to assess the viability of large-scale (1o) data to be used to assess fire weather severity and fire regimes, so that large-scale data can be confidently used to predict future fire regimes using large-scale fire weather data. A reanalysis and surface station dataset are used to generate fire weather, and these data are compared to an area burned product. Overall the Fire Weather Indices (FWI) derived from GEOS-4 reanalysis meteorological parameters compare well with the NCDC surface station data across Siberia. FWI, derived from station and satellite data, are able to capture the regions where fires are extreme and minimal in Sakha, Siberia.