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Author(s):
Kelly E. Gleason, Anne W. Nolin
Year Published:

Cataloging Information

Topic(s):
Fire Behavior
Weather
Ecosystem(s):
Subalpine dry spruce-fir forest, Montane dry mixed-conifer forest

NRFSN number: 14443
Record updated:

As large, high-severity forest fires increase and snowpacks become more vulnerable to climate change across the western USA, it is important to understand post-fire disturbance impacts on snow hydrology. Here, we examine, quantify, parameterize, model, and assess the post-fire radiative forcing effects on snow to improve hydrologic modelling of snow-dominated watersheds having experienced severe forest fires. Following a 2011 high-severity forest fire in the Oregon Cascades, we measured snow albedo, monitored snow, and micrometeorological conditions, sampled snow surface debris, and modelled snowpack energy and mass balance in adjacent burned forest (BF) and unburned forest sites. For three winters following the fire, charred debris in the BF reduced snow albedo, accelerated snow albedo decay, and increased snowmelt rates thereby advancing the date of snow disappearance compared with the unburned forest. We demonstrate a new parameterization of post-fire snow albedo as a function of days-since-snowfall and net snowpack energy balance using an empirically based exponential decay function. Incorporating our new post-fire snow albedo decay parameterization in a spatially distributed energy and mass balance snow model, we show significantly improved predictions of snow cover duration and spatial variability of snow water equivalent across the BF, particularly during the late snowmelt period. Field measurements, snow model results, and remote sensing data demonstrate that charred forests increase the radiative forcing to snow and advance the timing of snow disappearance for several years following fire. 

Citation

Gleason, K.E.; Nolin, A.W. 2016. Charred forests accelerate snow albedo decay: parameterizing the post-fire radiative forcing on snow for three years following fire. Hydrological Processes. DOI: 10.1002/hyp.10897

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