Don McKenzie and Susan O'Neill
Thursday, June 1, 2006
Climatic change, fire, and air quality
Don McKenzie – USDA Forest Service & JISAO/CSES Climate Impacts Group
Susan O'Neill – USDA Natural Resources Conservation Service
Jack Chen, Jeremy Avise, Brian Lamb – Washington State University
Narasimhan Larkin – USDA Forest Service
Eric Salathé, Jeremy Littell, Robert Norheim – University of Washington & JISAO/CSES Climate Impacts Group
Cliff Mass – University of Washington
Christine Wiedinmyer, Alex Guenther – National Center for Atmospheric Research
Climate change, population growth, and land use changes are closely interrelated forces that may cause significant changes in air quality within the US. Changes in ecosystem dynamics and regional weather features such as temperature and circulation patterns can have a large impact on biogenic emissions and the occurrence and distribution of wildfires in forested and grassland areas. The EPA-funded Science to Achieve Results (STAR) project and Forest Service HAZE project address future US air quality and regional haze in the context of a changing climate. To do this, a comprehensive modeling system has been implemented that involves downscaling the NCAR/DOE Parallel Climate Model (PCM) output to a regional scale with the MM5 model, and downscaling global pollutant concentrations from the MOZART2 model with the SMOKE/CMAQ air quality modeling system. The global models are forced with the IPCC SRES A2, “business as usual”, climatic scenario, which has the most extreme projected conditions: a large global population and a high atmospheric loading of greenhouse gases. US-wide air quality simulations have been completed for the current climate case (1990-1999) and an initial test run completed for each July month in the future climate case (2045-2055).
A major task in this project is the simulation of actual fires, whether under current or future conditions. Statistical models can predict annual or seasonal averages of fire extent at scales from watersheds to eco-regions, but both fire forecasting and estimation of fire effects such as smoke production, carbon release, and air-quality reduction require daily or hourly time steps to be useful. We present a Fire Scenario Builder (FSB) that uses a simultaneous weighting of known influences on fire occurrence to create mapped distributions of fire probabilities, including both the likelihood of a fire occurring and the probabilistic distribution of fire sizes. Key input layers are mesoscale meteorology (MM5), atmospheric stability indices (CAPE), fuel moisture (from NFDRS), and mean-field estimates of seasonal area burned at the same scale as the meteorology. Combining these influences into a probabilistic model produces downscaled (to daily) estimates of fire-occurrence probability and fire sizes. To date we have FSB results of simulations at 12-km for the Pacific Northwest for one fire season (2003) and at 36-km for the western United States, using simulated meteorology for a future (2045-2054) decade. Our next goal is to link the FSB to SMOKE/CMAQ in two analyses: continental-scale changes in fire emissions from the 36-km simulations and changes in visibility over national parks and wilderness areas in the Pacific Northwest and northern Rocky Mountains, using the 12-km PNW domain. The FSB provides a partly mechanistic alternative to probabilistic estimates of fire frequency or natural fire rotation from historical fire-regime statistics, and is best used at intermediate scales between those associated with global vegetation models and those associated with landscape fire succession models.
Dr. Don McKenzie is a Quantitative Fire Ecologist with the USDA Forest Service and a Principal with the Climate Impacts Group.
Dr. Susan O'Neill is a Physical Scientist with the USDA Natural Resources Conservation Service.