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Current sea-level rise partly stems from increased surface melting and meltwater runoff from the Greenland ice sheet. Multi-year snow, also known as firn, covers about 80% of the ice sheet and retains part of the surface meltwater. Since the firn cold content integrates its physical and thermal characteristics, it is a valuable tool for determining the meltwater-retention potential of firn. We use gap-filled climatological data from nine automatic weather stations in the ice-sheet accumulation area to drive a surface-energy-budget and firn model, validated against firn density and temperature observations, over the 1998-2017 period. Our results show a stable top 20 m firn cold content (CC20) at most sites. Only at the lower-elevation Dye-2 site did CC20 decrease, by 24% in 2012, before recovering to its original value by 2017. Heat conduction towards the surface is the main process feeding CC20 at all nine sites, while CC20 reduction occurs through low-cold-content fresh-snow addition at the surface during snowfall and latent-heat release when meltwater refreezes. Our simulations suggest that firn densification, while reducing pore space for meltwater retention, increases the firn cold content, enhances near-surface meltwater refreezing and potentially sets favourable conditions for ice-slab formation., SCOPUS: ar.j, info:eu-repo/semantics/published

Depositions of light-absorbing particles (LAPs), such as black carbon (BC) and dust, on the snow surface modulate the snow albedo; therefore, they are considered key factors of snow-atmosphere interaction in the present-day climate system. However, their detailed roles have not yet been fully elucidated, mainly due to the lack of in-situ measurements. Here, we develop a new model chain NHM-Chem-SMAP, which is composed of a detailed regional meteorology-chemistry model and a multilayered physical snowpack model, and evaluate it using LAPs concentrations data measured at Sapporo, Japan during the 2011-2012 winter. NHM-Chem-SMAP successfully reproduces the in-situ measured seasonal variations in the mass concentrations of BC and dust in the surface snowpack. Furthermore, we find that LAPs from domestic and foreign sources played a role in shortening the snow cover duration by 5 and 10 days, respectively, compared to the completely pure snow condition.

Clouds have been recognized to enhance surface melt on the Greenland Ice Sheet (GrIS). However, quantitative estimates of the effects of clouds on the GrIS melt area and ice-sheet-wide surface mass balance are still lacking. Here we assess the effects of clouds with a state-of-the-art regional climate model, conducting a numerical sensitivity test in which adiabatic atmospheric conditions as well as zero cloud water/ice amounts are assumed (i.e., clear-sky conditions), although the precipitation rate is the same as in the control all-sky simulation. By including or excluding clouds, we quantify time-integrated feedbacks for the first time. We find that clouds were responsible for a 3.1%, 0.3%, and 0.7% increase in surface melt extent (of the total GrIS area) in 2012, 2013, and 2014, respectively. During the same periods, clouds reduced solar heating and thus daily runoff by 1.6, 0.8, and 1.0 Gt day−1, respectively: clouds did not enhance surface mass loss. In the ablation areas, the presence of clouds results in a reduction of downward latent heat flux at the snow/ice surface so that much less energy is available for surface melt, which highlights the importance of indirect time-integrated feedbacks of cloud radiative effects.

Surface albedo of snow and ice is substantially reduced by inorganic impurities, such as aeolian mineral dust (MD) and black carbon (BC), and also by organic impurities, such as microbes that live in the snow. In this paper, we present the temporal changes of surface albedo, snow grain size, MD, BC and snow algal cell concentration observed on a snowpack in northwest Greenland during the ablation season of 2014 and our attempt to reproduce the changes in albedo with a physically based snow albedo model. We also attempt to reproduce the effects of inorganic impurities and the red snow algae (Sanguina nivaloides) on albedo. Concentrations of MD and red snow algae in the surface snow were found to increase in early August, while snow grain size and BC were found to not significantly change throughout the ablation season. Surface albedo was found to have decreased by 0.08 from late July to early August. The albedo simulated by the model agreed with the albedo observed during the study period. However, red snow algae exerted little effect on surface albedo in early August. This is probably owing to the abundance of smaller cells (4.9×104 cells L−1) when compared with the cell abundance of red snow reported by previous studies in the Arctic region (∼108 cells L−1). The simulation of snow albedo until the end of the melting season, with a snow algae model, revealed that the reduction in albedo attributed to red snow algae could equal 0.004, out of a total reduction of 0.102 arising from the three impurities on a snowpack in northwest Greenland. Finally, we conducted scenario simulations using the snow albedo model, coupled with the snow algae model, in order to simulate the possible effects of red snow blooming on snow albedo under warm conditions in northwest Greenland. The result suggests that albedo reduction by red snow algal growth under warm conditions (surface snow temperature of +1.5 ∘C) reached 0.04, equivalent to a radiative forcing of 7.5 W m−2 during the ablation season of 2014. This coupled albedo model has the potential to dynamically simulate snow albedo, including the effect of organic and inorganic impurities, leading to proper estimates of the surface albedo of snow cover in Greenland.

Possible albedo reduction due to light absorbing impurities (LAI) in snowpack observed at various sites in the world are investigated. Reviewing previously measured black carbon (BC) concentrations, their values distribute in a range of 0.07-0.25 ppbw (ng of BC in g of snow) in Antarctica, 0.55-20 ppbw in Greenland Ice Sheet (GrIS), 4.4-87.6 ppbw for the other Arctic except GrIS, and 4-1221 ppbw for mid-latitudes. As albedo reduction rate by LAI depends on snow grain size, it is more enhanced by larger grain snow such as melt form (melting snow) than smaller grain snow such as precipitation particles (new snow). By assuming two typical snow grain radii rs = 1000 and 50 µm, respectively for those snow grain shapes, the albedo reduction as a function of BC concentration can be calculated with physically based snow albedo model. The result indicates that albedo in Antarctic snow is not affected by BC in any case of snow grain radius. In GrIS albedo reduction due to BC is small around 0.006 for rs = 50 µm (new snow) but it rises to 0.026 for rs = 1000 µm (melting snow), suggesting a few percent of albedo reduction could occur under warmer climate condition due to enhanced snow metamorphism. In the other Arctic except GrIS, the maximum albedo reductions for rs = 50 µm (1000 µm) are 0.015 (0.064) at the maximum BC concentration (87.6 ppbw). For. mid-latitudes, it is 0.070 (0.24) for rs = 50 µm (1000 µm) at the maximum BC concentration (1221 ppbw). These results mean albedo reduction in highly polluted area of mid-latitudes cannot be ignored even in case of new snow and is more serious for melting snow.We have conducted energy budget and snow pit observations at Sapporo (43°N, 141°E, 15 m a.s.l), Japan since 2005. In addition, elemental carbon (EC~BC) and mineral dust concentrations in snowpack were also monitored for snow samples collected twice a week from 2007 by the thermal optical reflectance (TOT) method and gravimetric measurement of a filter. During 10 years from 2007 to 2017, the medians of EC and dust concentrations are 196 ppbw and 2700 ppbw, respectively. Using those data, contribution of LAI to albedo reduction and the radiative forcing (RF) were estimated. The 10-year-mean albedo reduction and RF due to BC+dust are 0.053 and +6.7 Wm-2, respectively, in which BC effect on albedo reduction is 5.6 times larger than dust. The albedo reduction by BC+dust for only melting period is 0.151, that is 4.8 times larger than that for accumulation period. The effect of LAI on albedo reduction is enhanced by snow grain growth as well as an increase of LAI in melting period compared to that for accumulation season.

Cryoconite holes are water-filled cylindrical holes formed on ablation ice surfaces and commonly observed on glaciers worldwide. Temporal changes of cryoconite holes characteristically −2, 40–55% of the incoming flux). In contrast, holes developed in sunny conditions correspond to high solar radiation (186–278 W m−2, 63–88%). Results suggest that the dimensions of holes drastically changed depending on the weather conditions and that frequent cloudy, warm and windy conditions would cause a decay of holes and weathering crust, inducing an increase in the cryoconite coverage on the ice, consequently darkening the glacier surface.

Surface albedo of snow and ice is substantially reduced by inorganic impurities, such as aeolian mineral dust (MD) and black carbon (BC), and also by organic impurities, such as microbes that live in the snow. In this paper, we present the temporal changes of surface albedo, snow grain size, MD, BC, and snow algal cell concentration observed on a snowpack in northwest Greenland during the ablation season of 2014 and our attempt to reproduce the changes in albedo with a physically based snow albedo model. We also attempt to reproduce the effects of inorganic impurities and the red snow algae (Chlamydomonas nivalis) on albedo. Concentrations of MD and red snow algae in the surface snow were found to increase in early August, while snow grain size and BC were found to not significantly change throughout the ablation season. Surface albedo was found to have decreased by 0.08 from late July to early August. The albedo simulated by the model agreed with the albedo observed during the study period. However, red snow algae exerted little effect on surface albedo in early August. This is probably owing to the abundance of smaller cells (4.9 × 104 cells L^-1) when compared with the cell abundance of typical red algal snow (~ 108 cells L−1). The simulation of snow albedo until the end of the melting season, with an algal growth model, revealed that the reduction in albedo attribute to red algae could equal 0.004, out of a total reduction of 0.102 arising from the three impurities on a snowpack in northwest Greenland. Finally, we conducted scenario simulations using the snow albedo model, coupled with the algal growth model, in order to simulate the possible effects of red algal blooming on snow albedo under warm conditions in northwest Greenland. The result suggests that albedo reduction by red snow algal growth under warm conditions (surface snow temperature of +1.5 °C) reached 0.04, equivalent to a radiative forcing of 7.5 W m−2 during the ablation season of 2014. This coupled albedo model has the potential to dynamically simulate snow albedo, including the effect of organic and inorganic impurities, leading to proper estimates of the surface albedo of snow cover in Greenland.

To improve surface mass balance (SMB) estimates for the Greenland Ice Sheet (GrIS), we developed a 5 km resolution regional climate model combining the Japan Meteorological Agency Non-Hydrostatic atmospheric Model and the Snow Metamorphism and Albedo Process model (NHM–SMAP) with an output interval of 1 h, forced by the Japanese 55-year reanalysis (JRA-55). We used in situ data to evaluate NHM–SMAP in the GrIS during the 2011–2014 mass balance years. We investigated two options for the lower boundary conditions of the atmosphere: an offline configuration using snow, firn, and ice albedo, surface temperature data from JRA-55, and an online configuration using values from SMAP. The online configuration improved model performance in simulating 2 m air temperature, suggesting that the surface analysis provided by JRA-55 is inadequate for the GrIS and that SMAP results can better simulate physical conditions of snow/firn/ice. It also reproduced the measured features of the GrIS climate, diurnal variations, and even a strong mesoscale wind event. In particular, it successfully reproduced the temporal evolution of the GrIS surface melt area extent as well as the record melt event around 12 July 2012, at which time the simulated melt area extent reached 92.4 %. Sensitivity tests showed that the choice of calculation schemes for vertical water movement in snow and firn has an effect as great as 200 Gt year−1 in the GrIS-wide accumulated SMB estimates; a scheme based on the Richards equation provided the best performance.

Albedo parameterization is of fundamental importance for accurate representation of high-latitude climate variability by modeling studies. Field observations show that near-infrared snow albedo decreases dramatically when surface air temperature exceeds −2 °C. This can influence reproduction of sea ice simulations taking into consideration the importance of the drastic change in albedo in early melt season for the seasonal change of sea ice extent. Therefore, we conducted global ocean data-assimilative simulation experiments using a modified snow albedo parameterization. The modified parameterization reduced the albedo directly and achieved a comparable indirect reduction via changes in the modeled snow and sea ice distributions (ice–albedo feedback). As a result, sea ice thickness was reduced by more than 0.4–1 cm over most of the central Arctic Ocean. Sea ice velocities were also reduced by enhanced ocean drag with weakened surface ocean circulation in the Beaufort Gyre. In the Southern Ocean, the modified parameterization caused snow thicknesses to be decreased by up to 2 cm in the Weddell Sea. These impacts, which were generally larger than the spread of ensemble experiment results and therefore robust, at least in our model, provide useful information for quantifying the results of albedo modification in climate modeling studies.

The surface energy balance (SEB) from 30 June to 14 July 2012 at site SIGMA (Snow Impurity and Glacial Microbe effects on abrupt warming in the Arctic)-A, (78 deg 03 min N, 67 deg 38 min W; 1490 m a.s.l.) on the northwest Greenland Ice Sheet (GrIS) was investigated by using in situ atmospheric and snow measurements as well as numerical modeling with a one-dimensional multi-layered physical snowpack model called SMAP (Snow Metamorphism and Albedo Process). At SIGMA-A, remarkable near-surface snowmelt and continuous heavy rainfall (accumulated precipitation between 10 and 14 July was estimated to be 100 mm) were observed after 10 July 2012. Application of the SMAP model to the GrIS snowpack was evaluated based on the snow temperature profile, snow surface temperature, surface snow grain size, and shortwave albedo, all of which the model simulated reasonably well. Above all, the fact that the SMAP model successfully reproduced frequently observed rapid increases in snow albedo under cloudy conditions highlights the advantage of the physically based snow albedo model (PBSAM) incorporated in the SMAP model. Using such data and model, we estimated the SEB at SIGMA-A from 30 June to 14 July 2012. Radiation-related fluxes were obtained from in situ measurements, whereas other fluxes were calculated with the SMAP model. By examining the components of the SEB, we determined that low-level clouds accompanied by a significant temperature increase played an important role in the melt event observed at SIGMA-A. These conditions induced a remarkable surface heating via cloud radiative forcing in the polar region., 形態: カラー図版あり, Physical characteristics: Original contains color illustrations, 資料番号: PA1610008000

Light-absorbing snow impurities of elemental carbon (EC), organic carbon (OC), and mineral dust have been measured at three locations at elevations from 1,469 to 1,992 m on August 1, 2011, and at the site SIGMA-A (78°N, 68°W, elevation 1,490 m) on the northwest Greenland ice sheet (GrIS) during the period from June 28 to July 12, 2012. At SIGMA-A, a remarkable snow surface lowering together with snow melting was observed during the observation period in 2012, when a record surface melting event occurred over the GrIS. The concentrations in the surface were 0.9, 3.8, and 107 ppbw for EC, OC, and dust, respectively, at the beginning of the period, which increased to 4.9, 17.2, and 1327 ppbw for EC, OC, and dust, respectively, at the end. The EC and dust concentrations were remarkably higher than those at the three locations in 2011 and the recent measurements at Summit. However, our measurements for EC and OC could be underestimated because a recent study indicates that the collection efficiency of a quartz fiber filter, which we employed, is low. We confirm that the snow surface impurity concentrations were enhanced in the observation period, which can be explained by the effects of sublimation/evaporation and snow melt amplification associated with drastic melting. Scanning electron microscopy analysis of surface snow impurities on July 12 revealed that the major component of snow impurities is mineral dust with size larger than 5 μm, which suggests possible emission source areas are peripheral bare soil regions of Greenland and/or the Canadian Arctic.

The specific surface area (SSA) of snow is of particular interest to researchers because SSA is strongly related to snow albedo and is a comparatively better indicator of snow’s complexity than grain size. The time variation of SSA for fresh snow samples was observed in the laboratory under isothermal conditions at 226 K and 254 K using the gas adsorption method and Brunauer-Emmett-Teller theory. The SSA of the snow samples decreased with time under isothermal metamorphism. The decrease in SSA was fitted with the logarithmic equation proposed by Legagneux et al. (2003), and adjustable parameters were obtained. The rate of decrease in SSA depended on the shape of the initial snow type and temperature. Dendritic snow samples exhibited large initial SSAs, and their SSAs decreased faster compared with those of fragmented (collected from drifting snow) and plate-like precipitation particles with relatively small initial SSAs. The rate of decrease in SSA was lower at 226 K than that at 254 K.

The potential of the thermal infrared (TIR) remote sensing for discriminating surface snow types was examined by analyzing TIR radiances acquired from space over the Greenland ice sheet. The brightness temperature difference (BTD) between TIR wavelengths of 11 and 12μm was found to increase in accordance with in situ observed evolutions of surface snow type. Spatial and temporal distributions of BTD over the entire ice sheet indicated that BTD has a sensitivity of about 1.2 K for variations of the possible snow types. The observed behaviors of BTD were coincident with those predicted by a radiative transfer calculation using previous in situ measured snow emissivities, although some biases on the order of 0.1-0.3 K remain. The dependence of BTD on the surface snow type was also consistent with the behaviors of snow reflectance at the shortwave infrared (SWIR) wavelength 1.6μm, which is a measure of snow grain size, except for the case of melting wet snow. The inconsistency in the wet snow case was considered to be due to the different optical responses of the TIR and SWIR signals to wet snow, which suggested the possibility of using TIR signals to discriminate wet/dry conditions of snow cover in an old stage. As a result, it is determined that TIR remote sensing has potential not only as an approach supplementary to the SWIR method for assessing surface snow types in daytime but also as the only method for simultaneous retrieval of snow type and surface temperature in nighttime., 資料番号: PA1510067000

To clarify the effect of light absorbing impurities including glacial microbes spectral albedo measurements using a spectrometer for spectral domains of the ultraviolet, visible and near-infrared have been carried out on ablation area in Qaanaaq Glacier in northwestern Greenland in July 2011. The almost glacier surfaces in the ablation area were covered with cryoconite (biogenic dust) on thin ice grain layer above bare ice. There were also snow-covered surfaces including red snow (snow algae). The measured spectral albedos had a remarkable contrast between red snow surface and cryoconite-covered ice surface in the spectral domain from the ultraviolet to the visible, where red snow albedo increased rapidly with the wavelength, while the cryoconite albedo was relatively flat to the wavelength. We simulated the spectral albedos of these surfaces with a radiative transfer model for the atmosphere-snow system. The single scattering properties are calculated with Mie theory by assuming red snow gains to be spherical and with geometric optics by assuming ice grains of cryoconite surface to be non-spherical Voronoi aggregates. We calculated the effect of glacial microbes as snow (ice) impurities using a mineral dust model by changing the imaginary part of refractive index so as to fit the theoretically calculated spectral albedo to the measurement. Finally the imaginary part of refractive indices for red snow and cryoconite at the wavelengths less than 1.0 μm were retrieved. It was found that cryoconite has uniformly higher light absorption compared to mineral dust and red snow has strong light absorption at the wavelengths less than 0.6 μm.

[1] We developed a multilayered physical snowpack model named Snow Metamorphism and Albedo Process (SMAP), which is intended to be incorporated into general circulation models for climate simulations. To simulate realistic physical states of snowpack, SMAP incorporates a state-of-the-art physically based snow albedo model, which calculates snow albedo and solar heating profile in snowpack considering effects of snow grain size and snow impurities explicitly. We evaluated the performance of SMAP with meteorological and snow impurities (black carbon and dust) input data measured at Sapporo, Japan during two winters: 2007–2008 and 2008–2009, and found SMAP successfully reproduced all observed variations of physical properties of snowpack for both winters. We have thus confirmed that SMAP is suitable for climate simulations. With SMAP, we also investigated the effects of snow impurities on snowmelt at Sapporo during the two winters. We found that snowpack durations at Sapporo were shortened by 19 days during the 2007–2008 winter and by 16 days during the 2008–2009 winter due to radiative forcings caused by snow impurities. The estimated radiative forcings due to snow impurities during the accumulation periods were 3.7 W/m2 (it corresponds to albedo reduction in 0.05) and 3.2 W/m2 (albedo reduction in 0.05) for the 2007–2008 and 2008–2009 winters, respectively. While during the ablation periods they were 25.9 W/m2 (albedo reduction in 0.18) and 21.0 W/m2 (albedo reduction in 0.17) for each winter, respectively.