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IPSL-CM5A-LR Historical Prescribed Burn Windows for the Southeast United States 1950-1999

Dates

Publication Date
Start Date
1950
End Date
1999

Citation

Kupfer, J.A., Terando, A.J., Gao, P., and Tirpak, B.E., 2021, Historical and Future Prescribed Burn Windows for the Southeast United States: U.S. Geological Survey data release, https://doi.org/10.5066/P95BV7GE.

Summary

Prescribed burning is a critical tool for managing wildfire risks and meeting ecological objectives, but its safe and effective application requires that specific meteorological criteria are met. This dataset contains results from a study examining the potential impacts of projected climatic change on prescribed burning in the southeastern United States. A set of burn window criteria (suitable weather conditions within which burning may occur based on maximum daily temperature, daily average relative humidity, and daily average wind speed), were applied to projections from an ensemble of Global Climate Models (GCM) under two greenhouse gas emission scenarios, as well as past observations for comparison. Data are provided as decadal [...]

Contacts

Point of Contact :
Adam J Terando
Originator :
John Kupfer, Adam J Terando, Peng Gao, Blair E Tirpak
Metadata Contact :
Adam J Terando
Publisher :
U.S. Geological Survey
USGS Mission Area :
Ecosystems
SDC Data Owner :
Climate Adaptation Science Centers
Distributor :
U.S. Geological Survey - ScienceBase

Attached Files

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Extension: IPSL-CM5A-LR_res_hist_percentDaysSuitable_01_1950_1999.zip
IPSL-CM5A-LR_res_hist_percentDaysSuitable_01_1950_1999.tif 1.19 MB
IPSL-CM5A-LR_res_hist_percentDaysSuitable_01_1950_1999.tif-ColorRamp.SLD 2.07 KB
Extension: IPSL-CM5A-LR_res_hist_percentDaysSuitable_02_1950_1999.zip
IPSL-CM5A-LR_res_hist_percentDaysSuitable_02_1950_1999.tif 1.12 MB
IPSL-CM5A-LR_res_hist_percentDaysSuitable_02_1950_1999.tif-ColorRamp.SLD 2.07 KB
Extension: IPSL-CM5A-LR_res_hist_percentDaysSuitable_03_1950_1999.zip
IPSL-CM5A-LR_res_hist_percentDaysSuitable_03_1950_1999.tif 1.2 MB
IPSL-CM5A-LR_res_hist_percentDaysSuitable_03_1950_1999.tif-ColorRamp.SLD 2.07 KB
Extension: IPSL-CM5A-LR_res_hist_percentDaysSuitable_04_1950_1999.zip
IPSL-CM5A-LR_res_hist_percentDaysSuitable_04_1950_1999.tif 1.16 MB
IPSL-CM5A-LR_res_hist_percentDaysSuitable_04_1950_1999.tif-ColorRamp.SLD 2.07 KB
Extension: IPSL-CM5A-LR_res_hist_percentDaysSuitable_05_1950_1999.zip
IPSL-CM5A-LR_res_hist_percentDaysSuitable_05_1950_1999.tif 1.19 MB
IPSL-CM5A-LR_res_hist_percentDaysSuitable_05_1950_1999.tif-ColorRamp.SLD 2.07 KB
Extension: IPSL-CM5A-LR_res_hist_percentDaysSuitable_06_1950_1999.zip
IPSL-CM5A-LR_res_hist_percentDaysSuitable_06_1950_1999.tif 1.25 MB
IPSL-CM5A-LR_res_hist_percentDaysSuitable_06_1950_1999.tif-ColorRamp.SLD 2.07 KB
Extension: IPSL-CM5A-LR_res_hist_percentDaysSuitable_07_1950_1999.zip
IPSL-CM5A-LR_res_hist_percentDaysSuitable_07_1950_1999.tif 1.35 MB
IPSL-CM5A-LR_res_hist_percentDaysSuitable_07_1950_1999.tif-ColorRamp.SLD 2.07 KB
Extension: IPSL-CM5A-LR_res_hist_percentDaysSuitable_08_1950_1999.zip
IPSL-CM5A-LR_res_hist_percentDaysSuitable_08_1950_1999.tif 1.35 MB
IPSL-CM5A-LR_res_hist_percentDaysSuitable_08_1950_1999.tif-ColorRamp.SLD 2.07 KB
Extension: IPSL-CM5A-LR_res_hist_percentDaysSuitable_09_1950_1999.zip
IPSL-CM5A-LR_res_hist_percentDaysSuitable_09_1950_1999.tif 1.2 MB
IPSL-CM5A-LR_res_hist_percentDaysSuitable_09_1950_1999.tif-ColorRamp.SLD 2.07 KB
Extension: IPSL-CM5A-LR_res_hist_percentDaysSuitable_10_1950_1999.zip
IPSL-CM5A-LR_res_hist_percentDaysSuitable_10_1950_1999.tif 1.14 MB
IPSL-CM5A-LR_res_hist_percentDaysSuitable_10_1950_1999.tif-ColorRamp.SLD 2.07 KB
Extension: IPSL-CM5A-LR_res_hist_percentDaysSuitable_11_1950_1999.zip
IPSL-CM5A-LR_res_hist_percentDaysSuitable_11_1950_1999.tif 1.14 MB
IPSL-CM5A-LR_res_hist_percentDaysSuitable_11_1950_1999.tif-ColorRamp.SLD 2.07 KB
Extension: IPSL-CM5A-LR_res_hist_percentDaysSuitable_12_1950_1999.zip
IPSL-CM5A-LR_res_hist_percentDaysSuitable_12_1950_1999.tif 1.19 MB
IPSL-CM5A-LR_res_hist_percentDaysSuitable_12_1950_1999.tif-ColorRamp.SLD 2.07 KB

Purpose

Prescribed fire is a critical tool for managing wildfire risks and meeting ecological objectives, but its safe and effective application requires that specific meteorological criteria (i.e., a 'burn window') are met. Given climate change projections and projected changes in key environmental factors that constrain prescribed burning, it is clear that predicting the future of fire will require a better understanding of whether environmental criteria defined by managers who conduct prescribed fires can still be met. Gaining this understanding is especially important because the use of prescribed fire is now so widespread in the United States that the total area burned annually by prescribed fires often exceeds that burned by wildfires. This dataset assesses how opportunities for prescribed burning would be influenced by projected changes in climate with a focus on the southeastern U.S. The dataset models historic conditions as multi-year averages for each month by decade by GCM for 1950-1999.

Map

Spatial Services

ScienceBase WMS

ScienceBase WCS

Communities

  • National and Regional Climate Adaptation Science Centers
  • Southeast CASC

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