Measurement of the specific surface area of snow using infrared reflectance in an integrating sphere at 1310 and 1550 nm

International audienceEven though the specific surface area (SSA) and the snow area index (SAI) of snow are crucial variables to determine the chemical and climatic impact of the snow cover, few data are available on the subject. We propose here a novel method to measure snow SSA and SAI. It is based on the measurement of the hemispherical infrared reflectance of snow samples using the DUFISSS instrument (DUal Frequency Integrating Sphere for Snow SSA measurement). DUFISSS uses the 1310 or 1550 nm radiation of laser diodes, an integrating sphere 15 cm in diameter, and InGaAs photodiodes. For SSA60 m2 kg−1, snow is usually of low density (typically 30 to 100 kg m−3), resulting in insufficient optical depth and 1310 nm radiation reaches the bottom of the sample, causing artifacts. The 1550 nm radiation is therefore used for SSA>60 m2 kg−1. Reflectance is then in the range 5 to 12% and the accuracy on SSA is 12%. We propose empirical equations to determine SSA from reflectance at both wavelengths, with that for 1310 nm taking into account the snow density. DUFISSS has been used to measure the SSA of snow and the SAI of snowpacks in polar and Alpine regions

Snow spectral albedo at Summit, Greenland: measurements and numerical simulations based on physical and chemical properties of the snowpack

The broadband albedo of surface snow is determined both by the near-surface profile of the physical and chemical properties of the snowpack and by the spectral and angular characteristics of the incident solar radiation. Simultaneous measurements of the physical and chemical properties of snow were carried out at Summit Camp, Greenland (72°36´ N, 38°25´ W, 3210 m a.s.l.) in May and June 2011, along with spectral albedo measurements. One of the main objectives of the field campaign was to test our ability to predict snow spectral albedo by comparing the measured albedo to the albedo calculated with a radiative transfer model, using measured snow physical and chemical properties. To achieve this goal, we made daily measurements of the snow spectral albedo in the range 350–2200 nm and recorded snow stratigraphic information down to roughly 80 cm. The snow specific surface area (SSA) was measured using the DUFISSS instrument (DUal Frequency Integrating Sphere for Snow SSA measurement, Gallet et al., 2009). Samples were also collected for chemical analyses including black carbon (BC) and dust, to evaluate the impact of light absorbing particulate matter in snow. This is one of the most comprehensive albedo-related data sets combining chemical analysis, snow physical properties and spectral albedo measurements obtained in a polar environment. The surface albedo was calculated from density, SSA, BC and dust profiles using the DISORT model (DIScrete Ordinate Radiative Transfer, Stamnes et al., 1988) and compared to the measured values. Results indicate that the energy absorbed by the snowpack through the whole spectrum considered can be inferred within 1.10%. This accuracy is only slightly better than that which can be obtained considering pure snow, meaning that the impact of impurities on the snow albedo is small at Summit. In the near infrared, minor deviations in albedo up to 0.014 can be due to the accuracy of radiation and SSA measurements and to the surface roughness, whereas deviations up to 0.05 can be explained by the spatial heterogeneity of the snowpack at small scales, the assumption of spherical snow grains made for DISORT simulations and the vertical resolution of measurements of surface layer physical properties. At 1430 and around 1800 nm the discrepancies are larger and independent of the snow properties; we propose that they are due to errors in the ice refractive index at these wavelengths. This work contributes to the development of physically based albedo schemes in detailed snowpack models, and to the improvement of retrieval algorithms for estimating snow properties from remote sensing data

Mass-balance and ablation processes of a perennial polar ice patch on the northern coast of Ellesmere Island

Ice patches have implications for landscape and ecosystem dynamics in polar deserts, however, the understanding of the driving factors that control their spatio-temporal variability is limited. This study aims to assess the seasonal and long-term evolution of ice patches on Ward Hunt Island (WHI; 83°N, Canadian High Arctic) based on field measurements of surface mass and energy balance. Results show that mass gains of the ice patch systems occur mostly through drifting snow, making them highly linked to the topography as well as the frequency and magnitude of wind events. Summer ablation is primarily driven by net radiation, but the short-term variability in melt rate is driven by sensible heat fluxes. The highest ablation rates occur during the passage of warm fronts that combine strong winds and mild temperatures. Conversely, foggy days reduce fluxes of solar radiation and sensible heat to the snow/ice surface, thereby suppressing ablation. Ice patches are less climate-sensitive than other cryospheric elements due to a feedback between snow accumulation and topography, however, summer ablation is strongly influenced by micrometeorology. Model projections of these factors suggest that conditions will become critical for preserving ice patches at WHI and along the northern coast of Ellesmere Island as early as in the next decades

The specific surface area and chemical composition of diamond dust near Barrow, Alaska

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95687/1/jgrd17349.pd

Vegetation type is an important predictor of the arctic summer land surface energy budget

Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994-2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm(-2)) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.An international team of researchers finds high potential for improving climate projections by a more comprehensive treatment of largely ignored Arctic vegetation types, underscoring the importance of Arctic energy exchange measuring stations.Peer reviewe

Vegetation type is an important predictor of the arctic summer land surface energy budget

Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm−2) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types

Should We Not Further Study the Impact of Microbial Activity on Snow and Polar Atmospheric Chemistry?

International audienceSince 1999, atmospheric and snow chemists have shown that snow is a very active photochemical reactor that releases reactive gaseous species to the atmosphere including nitrogen oxides, hydrocarbons, aldehydes, halocarbons, carboxylic acids and mercury. Snow photochemistry therefore affects the formation of ozone, a potent greenhouse gas, and of aerosols, which affect the radiative budget of the planet and, therefore, its climate. In parallel, microbiologists have investigated microbes in snow, identified and quantified species, and sometimes discussed their nutrient supplies and metabolism, implicitly acknowledging that microbes could modify snow chemical composition. However, it is only in the past 10 years that a small number of studies have revealed that microbial activity in cold snow (< 0 • C, in the absence of significant amounts of liquid water) could lead to the release of nitrogen oxides, halocarbons, and mercury into the atmosphere. I argue here that microbes may have a significant effect on snow and atmospheric composition, especially during the polar night when photochemistry is shut off. Collaborative studies between microbiologists and snow and atmospheric chemists are needed to investigate this little-explored field

Chemistry in the Cryosphere

International audienc

Microphysique du manteau neigeux (évolution de la surface spécifique de la neige dans les Alpes et l'Antarctique ; impact sur la chimie atmosphérique)

La glace, sous forme de neige, recouvre jusqu'à 50 % des surfaces émergées de l'hémisphère Nord en hiver : elle est donc présente de façon importante à la surface de la terre. Elle interagit avec l'atmosphère par des processus complexes, comme la catalyse de réactions hétérogènes ou l'échange de gaz traces réactifs adsorbés à la surface des cristaux de neige, la diffusion en phase solide, les cycles de sublimation/condensation de glace qui entraînent des solutés. Leur compréhension et leur quantification requièrent la connaissance de divers paramètres physiques dont la surface spécifique (SS) de la neige, définie comme la surface accessible aux gaz par unité de masse. L'importance de ce paramètre et le peu de données existant dans la littérature a incité à effectuer ce travail sur l'étude de la SS de la neige et son évolution dans le manteau neigeux. La SS a été déterminée par l'absorption de méthane à 77K. Afin de comprendre les processus responsables de l'évolution de la SS, des macrophotographies et des images obtenues par microscopie électronique à balayage ont été utilisées. L'ensemble de nos résultats (176 mesures de SS) obtenus dans les Alpes et l'Artique a montré que la SS de la neige est très variable : elle est comprise entre 1540 et 100 cm2/g. Notre étude montre que la SS décroît avec le temps et que les principaux facteurs déterminant la cinétique de décroissance sont la température et le vent. A Alert, (Arctique canadien), l'étude détaillée de la microphysique du manteau neigeux a permis de mesurer directement la capacité d'adsorption de gaz traces réactifs par le manteau neigeux. Sa surface totale a été mesurée entre 1160 et 3710m2/m2. Nous avons ainsi démontré que le manteau neigeux pouvait séquestrer une grande partie des espèces présentes dans le système (neige+couche limite). Les mesures de SS ont également été utilisées pour déterminer les processus d'incorportion du formaldéhyde dans la neige.GRENOBLE1-BU Sciences (384212103) / SudocSudocFranceF