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Climate Research

There are three global questions behind the climate research being conducted in support of the WALTER project:

• What fine-scale information will be needed to assess the relative contribution of climate variability and change, and human land uses to fire regimes and consequences for natural ecosystems?

• What correlations can be found wildfire patterns and climatic conditions and events?

• How do these factors interact to produce particular types and levels of wildfire and of fire hazard?

The climate research is focused on understanding the relationship between seasonal climate patterns and fuel moisture so that climate analogs (e.g. a wet winter that increases biomass followed by a dry spring results in higher potential for fire) can help in forecasting fuel productivity. Our efforts to capture seasonal climate variability and inform surface conditions with climate data over complex terrains and varying soils involve the integration historical climate data at a one-kilometer spatial resolution and daily temporal coverage (e.g. DAYMET).

Interannual climate is also taken into account in the fire sensitivity mapping. The influence of longer term, inter-annual climate variability associated with ENSO (El Nino-Southern Oscillation) conditions can help generate synoptic climate patterns so that their influence can be incorporated in the assessment of wildland fire sensitivity. This includes regional climate data (the 1 km climate variable surfaces and the Palmer Drought Severity Index (PDSI) which lags fire risk) as well as low frequency teleconnection patterns (ENSO and PDO). The relationship of fire history data and indices of teleconnection patterns will help us understand how these modulate fire regimes at different sites.

Indexing Wildfire Risk: the Climate Component

Traditionally, fire models have concentrated on tactical approaches, utilizing weather information to help fight fires. Climate forecasts, with their longer view, lend themselves to the strategic nature of FCS-1. Matching historic climate data with size, intensity, extent, and other characteristics of historic fires will allow an assessment of the relationship between climate and fire. This will provide fine-scale information necessary to assess the relative contribution of climate variability and change for strategic planning based on climate forecasts.

The indexing of wildfire risk introduced on the Wildfire page is influenced in FCS-1 by climate. The preliminary wildfire sensitivity map (see the FCS-1 Model) will be adjusted by climate-cued fuel moisture. Seasonal climate analogs (e.g. a wet winter that increases biomass followed by a dry spring results in higher potential for fire) will provide a temporal element in assessing fuel productivity. These analogs are used to cue the appropriate fuel moisture map, derived from a near-surface moisture index generated from satellite data. Our efforts to capture seasonal climate variability and inform surface conditions with climate data over complex terrains and varying soils involve the integration historical climate data at a one-kilometer spatial resolution and daily temporal coverage (e.g. DAYMET).

Interannual climate is also taken into account in the fire sensitivity mapping. The influence of longer term, inter-annual climate variability associated with ENSO (El Nino-Southern Oscillation) conditions can help generate synoptic climate patterns so that their influence can be incorporated in the assessment of wildland fire sensitivity. This includes regional climate data (the 1 km climate variable surfaces and the Palmer Drought Severity Index (PDSI) which lags fire risk) as well as low frequency teleconnection patterns (ENSO and PDO). The relationship of fire history [link to Model - Fire History page] data and indices of teleconnection patterns will help us understand how these modulate fire regimes at different sites.