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Fire probability for 1900-1929 using GFDL baseline climate values

Dates

Publication Date
Start Date
1900-01-01
End Date
1929-12-31

Citation

Stambaugh, M.C., 2018, Fire probability for 1900-1929 using GFDL baseline climate values: U.S. Geological Survey data release, https://doi.org/10.5066/F7PK0F4V.

Summary

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 (CFP) clipped to [...]

Contacts

Point of Contact :
Michael C Stambaugh
Originator :
Michael C Stambaugh
Metadata Contact :
CERC Data Managers
Publisher :
U.S. Geological Survey
Distributor :
U.S. Geological Survey - ScienceBase

Attached Files

Click on title to download individual files attached to this item.

Extension: fireprob_gfdl_base.zip
fireprob_gfdl_base.tif 7.88 MB
fireprob_gfdl_base.tif-ColorRamp.SLD 2.03 KB

Purpose

Data were collected to model potential changes in wildfire probability for Texas, Oklahoma, and New Mexico. Identification and description of these conditions may help anticipate fire regimes changes that will affect human health, agriculture, species conservation, and nutrient and water cycling.

Map

Spatial Services

ScienceBase WMS

ScienceBase WCS

Communities

  • Columbia Environmental Research Center (CERC)

Tags

Provenance

Data source
Input directly

Additional Information

Identifiers

Type Scheme Key
DOI https://www.sciencebase.gov/vocab/category/item/identifier doi:10.5066/F7PK0F4V

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