Filters: Tags: Wildfire (X) > Extensions: Raster (X) > partyWithName: CERC Data Managers (X)

Filters Date Range Past year (0) Past month (0) Past week (0) Past day (0) Custom range... To   Search Types Downloadable (9) GeoTIFF (9) Map Service (9) Raster (9) Contacts Michael C Stambaugh U.S. Geological Survey U.S. Geological Survey - ScienceBase Categories Data (9) Tag Types Theme (9) Place (9) Tag Schemes Common geographic areas (9) None (9) USGS Thesaurus (9) View Results as: JSON ATOM CSV

Fire probability for 1900-1929 using GFDL baseline climate values Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: New Mexico, Oklahoma, Texas, climate change, mean fire interval, All tags... wildfire, wildfire frequency, Fewer tags Fire probability for 1900-1929 using CGCM baseline climate values Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: New Mexico, Oklahoma, Texas, climate change, mean fire interval, All tags... wildfire, wildfire frequency, Fewer tags Change in fire probability from baseline to 2040-2069 using CGCM-projected climate values Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: New Mexico, Oklahoma, Texas, climate change, mean fire interval, All tags... wildfire, wildfire frequency, Fewer tags Change in fire probability from baseline to 2040-2069 using HadCM3-projected climate values Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: New Mexico, Oklahoma, Texas, climate change, mean fire interval, All tags... wildfire, wildfire frequency, Fewer tags Change in fire probability from baseline to 2040-2069 using GFDL-projected climate values Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: New Mexico, Oklahoma, Texas, climate change, mean fire interval, All tags... wildfire, wildfire frequency, Fewer tags Change in fire probability from baseline to 2070-2099 using CGCM-projected climate values Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: New Mexico, Oklahoma, Texas, climate change, mean fire interval, All tags... wildfire, wildfire frequency, Fewer tags Change in fire probability from baseline to 2070-2099 using GFDL-projected climate values Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: New Mexico, Oklahoma, Texas, climate change, mean fire interval, All tags... wildfire, wildfire frequency, Fewer tags Change in fire probability from baseline to 2070-2099 using HadCM3-projected climate values Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: New Mexico, Oklahoma, Texas, climate change, mean fire interval, All tags... wildfire, wildfire frequency, Fewer tags Fire probability for 1900-1929 using HadCM3 baseline climate values Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: New Mexico, Oklahoma, Texas, climate change, mean fire interval, All tags... wildfire, wildfire frequency, Fewer tags