A predictive model for the spectral “bioalbedo” of snow

Abstract

We present the first physical model for the spectral “bioalbedo” of snow, which predicts the spectral reflectance of snowpacks contaminated with variable concentrations of red snow algae with varying diameters and pigment concentrations and then estimates the effect of the algae on snowmelt. The biooptical model estimates the absorption coefficient of individual cells; a radiative transfer scheme calculates the spectral reflectance of snow contaminated with algal cells, which is then convolved with incoming spectral irradiance to provide albedo. Albedo is then used to drive a point‐surface energy balance model to calculate snowpack melt rate. The model is used to investigate the sensitivity of snow to algal biomass and pigmentation, including subsurface algal blooms. The model is then used to recreate real spectral albedo data from the High Sierra (CA, USA) and broadband albedo data from Mittivakkat Gletscher (SE Greenland). Finally, spectral “signatures” are identified that could be used to identify biology in snow and ice from remotely sensed spectral reflectance data. Our simulations not only indicate that algal blooms can influence snowpack albedo and melt rate but also highlight that “indirect” feedback related to their presence are a key uncertainty that must be investigated.

The role of microbes in snowmelt and radiative forcing on an Alaskan icefield

“…The generation of meltwater through microbes' albedoreducing properties motivates an hypothesis of bio-geophysical feedback on glacial landscapes 13,16 , such as the Greenland ice sheet. This feedback hypothesis, whereby microbes increase because they produce needed meltwater, is an active research area [13][14][15][16][17][18][19] , yet field experiments testing its assumptions are absent.Glacier microbiomes are water-limited 21,22 , because ice is generally not metabolically available, and oligotrophic, because their nutrient content equals that of precipitation plus deposition by airborne dust, pollen, and so on, with only limited N-fixation by local cyanobacteria 21,22 . Moreover, rapidly percolating water through large-grained snow may exacerbate both water-and nutrient limitation for algae in supraglacial snow-covered habitat 7 .…”

“…The generation of meltwater through microbes' albedoreducing properties motivates an hypothesis of bio-geophysical feedback on glacial landscapes 13,16 , such as the Greenland ice sheet. This feedback hypothesis, whereby microbes increase because they produce needed meltwater, is an active research area [13][14][15][16][17][18][19] , yet field experiments testing its assumptions are absent.…”

Inorganic carbon addition stimulates snow algae primary productivity

“…These efforts are complicated by the difficulty in separating abiotic albedo from biologically induced darkening, or bio-albedo, as well as a paucity of data on snow algae distribution and density. However, a recently developed spectral model for bio-albedo which includes snow physical properties and meteorological data indicates that algal blooms can influence snowpack albedo and melt rate [19]. The model indicated that algae biomass has a greater effect than pigment concentration, suggesting a positive correlation between supraglacial algal blooms and accelerated melt.…”

“…In Sierra Nevada snowfields, snow algae abundance was negatively correlated to surface albedo [15] and a recent study quantified the role of snow algae communities in snowmelt on an icefield in Alaska [16]. Similarly, in the Arctic, red algal blooms darken the snow/ice surface, lowering surface albedo (by as much as 13% over the melt season) [17] and increasing melt rates [18,19].…”

“…In Sierra Nevada snowfields, snow algae abundance was negatively correlated to surface albedo [15] and a recent study quantified the role of snow algae communities in snowmelt on an icefield in Alaska [16]. Similarly, in the Arctic, red algal blooms darken the snow/ice surface, lowering surface albedo (by as much as 13% over the melt season) [17] and increasing melt rates [18,19].Allochthonous material delivered to snow and ice surfaces such as forest fire-derived black carbon, Saharan or pro-glacial mineral dust, volcanic ash, and anthropogenic pollution causes increased absorption of solar radiation and locally accelerated melting. These effects can be far reaching-a darkening of the Greenland ice sheet has been * Trinity L. Hamilton…”