Declines in Peak Snow Water Equivalent and Elevated Snowmelt Rates Following the 2020 Cameron Peak Wildfire in Northern Colorado

McGrath, Daniel; Zeller, Lucas; Bonnell, Randall; Reis, Wyatt; Kampf, Stephanie K.; Williams, Keith; Okal, Marianne; Olsen‐Mikitowicz, Alex; Bump, Ella; Sears, Megan G.; Rittger, Karl

doi:10.1029/2022gl101294

Cited by 7 publications

(3 citation statements)

References 28 publications

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“…Independent of the reason for a later snow-free date, the result is still an increase in LSA over a longer period relative to nearby unburned areas. Previous research has shown that snow ablates earlier in burned areas compared to control unburned areas (Gleason et al, 2013;Kampf et al, 2022;McGrath et al, 2023) in studies using field observations and MOD10A1 SCF to determine a melt-out date. Our results largely agree with these results, but we argue snow depletion date alone does not tell the whole story.…”

Section: Discussionmentioning

confidence: 99%

Response of Land Surface Albedo to Fire Disturbance in the Sierra Nevada Seasonal Snow Zone Over the MODIS Record

Gayler,

Skiles

2024

Earth's Future

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Wildfires in the snow zone can brighten winter and spring landscapes by removing forest canopy, revealing underlying snow cover. Land surface albedo (LSA) alterations associated with transitioning from a canopied, snow‐hiding vegetation regime to a snow‐revealing landscape have impacts on the surface energy balance, with implications for climate and water supply. Forest fires are increasing in frequency, size, and elevation, but the change in LSA due to fire in the seasonal snow zone (SSZ) is poorly understood. This study addresses this knowledge gap for the Sierra Nevada, where recent climatic changes have contributed to droughts, earlier and more rapidly declining snowpacks, and worsening wildfire impacts. Remotely sensed snow fraction and LSA data from Moderate Resolution Imaging Spectrometer were used to assess the impact of wildfire on landscapes in the Sierra Nevada SSZ by comparing LSA in burn scars to unburned control areas and the historical average LSA, then quantifying the surface radiative forcing (RF) associated with change in LSA. Among high and moderate burn severity fires, winter LSA varied depending on snow cover, land characteristics, and burn severity, ranging from 0.12 in low‐snow fire scars to 0.47 in snow‐covered fire scars. This study adds to understanding of how landscapes respond to wildfires and the subsequent impacts on the surface energy balance.

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Section: Discussionmentioning

confidence: 99%

Response of Land Surface Albedo to Fire Disturbance in the Sierra Nevada Seasonal Snow Zone Over the MODIS Record

Gayler,

Skiles

2024

Earth's Future

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“…Climate warming threatens snow–water storage through feedbacks between declining snowpacks and increased forest fire activity (Fassnacht & López‐Moreno, 2020; Gleason et al, 2019; Kampf et al, 2022; McGrath et al, 2023; Viviroli et al, 2007). The majority of water in the American West is seasonally stored in snowpack, with ecosystems and human communities relying on snowmelt as a source of water in the drier periods of late spring and summer (Li et al, 2017; Liu et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

“…The overall net change in combined net shortwave and longwave radiative forcing on snowpack following canopy removal depends on the forest structure and snow climate (Lundquist et al, 2013; Musselman et al, 2008; Varhola et al, 2010). In addition to the enhanced radiation effects, forest canopy removal may also increase the turbulent fluxes at the snow surface ultimately reducing snow–water storage and increasing snow melt rates (Harpold et al, 2014; McGrath et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

Modelling postfire recovery of snow albedo and forest structure to understand drivers of decades of reduced snow water storage and advanced snowmelt timing

Surunis,

Gleason

2024

Hydrological Processes

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Forest fires darken snow albedo and degrade forest structure, ultimately reducing peak snow–water storage, and advancing snowmelt timing for up to 15 years following fire. To date, no volumetric estimates of watershed‐scale postfire effects on snow–water storage and snowmelt timing have been quantified over decades of postfire recovery. Using postfire parameterizations in a spatially‐distributed snow mass and energy balance model, SnowModel, we estimated postfire recovery of forest fire effects on snow–water equivalent (SWE) and snowmelt timing over decades following fire. Using this model, we quantified volumetric recovery of forest fire effects on snow hydrology across a chronosequence of eight sub‐alpine forests burned between 2000 and 2019 in the Triple Divide of western Wyoming. We found that immediately following fire, forest fire effects reduced snow–water storage by 6.8% (SD = 11.2%) and advanced the snow disappearance date by 31 days (SD = 9 days). Across the 15‐year recovery following fire, forest fire effects reduced snow–water storage by 4.5% (SD = 11.4%). Postfire effects on snow hydrology generally recovered over time, but still persisted beyond 15‐years following fire due to the observed postfire shift from forest to open meadow. Estimates of postfire reductions on peak SWE summed over the entire 15‐year postfire recovery period were 18 times greater than the immediate losses in the first winter following fire alone. These lasting effects of forest fires on snow hydrology decades following fire highlight the importance of postfire parameterizations for more accurate watershed‐scale volumetric estimates of forest fire effects on snow–water resources.

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Wildfire Impacts for Temperature Index Snowpack Model Parameters

Giovando,

Niemann,

Fassnacht

2024

Hydrological Processes

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Streamflow derived from snowmelt is a key source of water for communities and agricultural producers in the western U.S. As wildfires become larger and more frequent in the West (due in part to climate change), it is increasingly important to understand their potential impacts on snowpack. Temperature‐index models remain widely used to simulate snowpack in post‐wildfire assessments due to their low data requirements. However, there is limited information on how the key parameters of such models change due to wildfires. The objectives of this study are to (1) quantify the observed changes in the melt‐rate function and the rain‐snow temperature threshold due to wildfires and (2) develop methods to adjust the melt‐rate function and rain‐snow temperature threshold (or Px Temperature) to simulate the potential impacts of wildfires on snowpack. To accomplish these goals, snow water equivalent data from 42 SNOTEL sites that have been impacted by wildfire are used to estimate the changes in the melt‐rate functions and Px Temperatures between the pre‐and post‐wildfire periods. Then, general linear models (GLMs) are developed to estimate the changes in the model parameters based on readily available topographic, climatic, and land cover information. The results indicate that late season melt‐rates typically increase after a wildfire for sites in northern and central ecoregions of the western U.S. Px Temperature also changes for many sites, but the direction and magnitude of change is highly variable between sites. Nearly all the GLMs can estimate the observed parameter changes better than simply using the average observed changes. However, substantial variation in the parameter values is not explained by the GLMs.

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Declines in Peak Snow Water Equivalent and Elevated Snowmelt Rates Following the 2020 Cameron Peak Wildfire in Northern Colorado

Cited by 7 publications

References 28 publications

Response of Land Surface Albedo to Fire Disturbance in the Sierra Nevada Seasonal Snow Zone Over the MODIS Record

Response of Land Surface Albedo to Fire Disturbance in the Sierra Nevada Seasonal Snow Zone Over the MODIS Record

Modelling postfire recovery of snow albedo and forest structure to understand drivers of decades of reduced snow water storage and advanced snowmelt timing

Wildfire Impacts for Temperature Index Snowpack Model Parameters

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