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Drivers of post-fire albedo across Alaska and Canada: implications for climate feedbacks
Stefano
Potter, Woods Hole Research Center, spotter@whrc.org
(Presenter)
Kylen
Solvik, Woods Hole Research Center, ksolvik@whrc.org
Angela
Erb, University of Massachusetts Boston, angela.erb001@umb.edu
Scott
J.
Goetz, Northern Arizona University, scott.goetz@nau.edu
Jill
F.
Johnstone, University of Saskatchewan, jill.johnstone@usask.ca
Michelle
C.
Mack, Northern Arizona University, michelle.mack@nau.edu
James
T.
Randerson, University Of California, Irvine, jranders@uci.edu
Miguel
O.
Román, NASA Goddard Space Flight Center, miguel.o.roman@nasa.gov
Crystal
Schaaf, University of Massachusetts Boston, crystal.schaaf@umb.edu
Merritt
R.
Turetsky, University of Guelph, mrt@uoguelph.ca
Sander
Veraverbeke, Vrije Universiteit, Amsterdam, The Netherlands, sveraver@uci.edu
Zhuosen
Wang, NASA GSFC, zhuosen.wang@nasa.gov
Brendan
M.
Rogers, Woods Hole Research Center, brogers@whrc.org
Understanding how altered fire regimes impact vegetation composition and energy budgets is critical to forecasting regional and global climate change. High-severity fires cause winter and spring albedo to increase due to increased snow exposure and replacement of evergreen conifers by deciduous broadleaf trees. Although summer albedo decreases initially due to the deposition of black carbon and charred surfaces, it typically increases for several decades thereafter when younger and brighter deciduous trees dominate. The net effect of these albedo changes is expected to result in substantive radiative cooling, but there has been little research to examine how albedo trajectories differ spatially and temporally as a result of differences in topography, climate and soil properties, and what the associated implications for future energy balances are.
Here we investigate drivers of post-fire monthly albedo trajectories across Canada and Alaska using a new Collection V006 500 m MODIS daily blue-sky albedo product and historical fires from the Canadian and Alaskan National Fire Databases. The impacts of landscape position, soils, climate, time since fire, and ecoregion on monthly albedo trajectories are explored using a Random Forest model. The resulting monthly models are then used to predict long term albedo under the Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios.
Models show that temperature and ecoregion are the most influential drivers of post fire albedo in the spring and autumn. In the summer ecoregion is again important, but year since fire and soil texture are more important than climate variables. In the future, the model predicts that as climate change intensifies, spring albedo will decrease due mainly to declining snow cover and warmer temperatures. In the summer this trend is reversed, although variation between future scenarios is small. These results indicate that there will be diminished post fire radiative cooling in the future. Future steps are to quantify how the radiative forcing will change under future climate, and to integrate albedo projections into a comprehensive fire-forcing framework that also considers biogeochemical feedbacks.
Associated Project(s):
Poster Location ID: 96
Session Assigned: Fire Disturbance
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