This Special Issue (Volume 32) comprises the research results and related studies from the first half of the period from 2011-2015 of the “Snow Impurity and Glacial Microbe effects on abrupt warming in the Arctic” (SIGMA) Project funded by the Japan Society for the Promotion of Science (JSPS) Grant-in-Aid for Scientific Research (S) number 23221004 (http://www.mri-jma.go.jp/Dep/cl/cl6/sigma/sigma-e.html). The scientific background of the SIGMA Project is that many climate models cannot sufficiently simulate recent abrupt snow/ice melting in the Arctic. One of the possible causes for this limitation is albedo reduction due to light-absorbing snow impurities (LASI) such as black carbon (BC) and glacial microbes. We are conducting field campaigns mainly in the Qaanaaq areas of northwest Greenland where abrupt melting is occurring in addition to meteorological and snow observations in Japanese snow areas to better understand the contribution of light-adsorbing snow impurities to snow/ice melting. Snow metamorphism and albedo process model and glacial microbe model are being developed and incorporated into earth system model (EMS) of the Meteorological Research Institute. In the second half of the project, we will simulate the recent and future climates and clarify the quantitative contributions of BC and glacial microbes on the recent abrupt melting in the Arctic. A shallow ice core drilling on the Greenland ice sheet will also be conducted in 2014, by which the atmospheric aerosols and snow impurities after the Industrial Revolution will be reproduced. Furthermore, the temporal-spatial variations of snow physical parameters such as snow grain size and concentrations of LASI and glacial microbes will be retrieved with satellite remote sensing.
    On the other hand, we consider snow grain size to be an important physical parameter in the SIGMA Project for the following two reasons. Snow grain size is (1) an optical control factor for albedo and (2) a parameter to express snow metamorphism. These two reasons are strongly related to the recent abrupt snow melting in the Arctic through snow- and ice-albedo feedback. The snow grain size is also an important target that assists in monitoring changing snow conditions through satellite remote sensing. We are developing techniques to objectively measure the snow grain size as part of the SIGMA Project. This Special Issue contains those results.
    During the same research period as the SIGMA Project, the “Arctic Climate Change Research Project” (http://www.nipr.ac.jp/grene/e/index.html) as part of “Green Network of Excellence” (GRENE) Program funded by the Ministry of Education, Culture, Sports, Science, and Technology in Japan (MEXT) is conducting. A glaciologist group from the GRENE Arctic Project also chose the Qaanaaq areas in Greenland as their research field. Thus, the SIGMA Project has a strong collaboration with the GRENE Arctic Project and a portion of the collaborative research results also appears in this Special Issue.
    As mentioned above, this Special Issue contains the results of field measurements conducted in Greenland and Japan, laboratory measurements, and satellite remote sensing and modeling studies on snow and ice science of the SIGMA Project and related studies. However, some results related to atmospheric science are not contained in this issue because they are beyond the scope of Bulletin Glaciological Research (BGR).
    As Chief editor of this Special Issue, I sincerely thank this issue’s Editorial board members: Kouichi Nishimura, Hideaki Motoyama, Masahiro Hori, Akihiro Hachikubo, Sumito Matoba, Satoru Yamaguchi, and Nozomu Takeuchi. I also thank the Chief editor of BGR Atsushi Sato for his great support. Finally, I thank the Japanese Society of Snow and Ice for providing an opportunity to publish this issue as a special issue of BGR.

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Field activities of the “Snow Impurity and Glacial Microbe effects on abrupt warming in the Arctic” (SIGMA) Project in Greenland in the summer season of 2011-2013 are reported;this consists of (1) glaciological and meteorological observations and (2) biological observations.　In 2011, we conducted a field reconnaissance in the Qaanaaq, Ilulissat and Kangerlussuaq areas to enable continuous meteorological observations with automatic weather stations (AWS), campaign observations for glaciology, meteorology and Biology and shallow ice core drilling, which were planned for 2012-2014.　Based on the results, we chose the Qaanaaq area in northwest Greenland as our main activity area and the Kangerlussuaq area in mid-west Greenland partly for biological observations.　In 2012, we conducted field observations for (1) and (2) mentioned above together with installations of two AWSs at site SIGMA-A on The Greenland ice sheet (GrIS) and at site SIGMA-B on the Qaanaaq ice cap (QIC) from June to August.　Surface snow and ice over all of the QIC melted in July and August 2012, and most of the Glacier surface appeared to be dark-colored, probably due to mineral dust and glacial microbial products.　In 2013, we carried out similar observations in the Qaanaaq area.　However, the weather and Glacier surface conditions were considerably different from those in 2012.　Snow cover over the summer of 2013 remained over large areas with elevations higher than about 700 m on QIC.　Biological activity on the Glacier surface appears to be substantially lower as compared to that in 2012.

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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.

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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.

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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.

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The specific surface area (SSA) of snow can be used as an objective measurement to define the optical sphere diameter of snow; it is therefore a helpful parameter to describe the physical properties of snow, such as albedo.　Recently, measurement of snow SSA in the field has become easier with the use of optical methods based on near-infrared reflectance values (Ref).　However, existing optical methods have only been validated for dry snow conditions in the field.　In this study, we tested the possibility of applying the optical method using light with wavelength of around 900 nm (NIR photometry) to wet snow zones in Japan by comparing the findings with snow pit observation data.　Our results indicated that NIR photometry can be applied to wet snow zones before the main melt season when the liquid water content is small, but problems arose during melt season due to the appearance of darker layers with more high liquid water content.　To resolve these problems, we propose three improvements to NIR photometry: using three calibration targets ranging from high Ref to low Ref in coverage; establishing an estimation formula for SSA from measured Ref, including lower Ref values; and considering how water in the snow influences Ref.

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The 1D multilayered physical snowpack model Snow Metamorphism and Albedo Process (SMAP), which was originally designed for climate studies, is now updated by incorporating a detailed water movement scheme, realistic snow settlement process and limitation for the Richardson number to ensure minimum turbulent exchanges even under highly stable atmospheric conditions.　The evaluation of the updated version of SMAP was first performed using the data obtained at Sapporo, Japan, during the 2007-2009 winters and the effectiveness of these updates was demonstrated in terms of snow depth and snow surface temperature.　However, we pointed out that the choice of maximum Richardson number should be further examined.　To test the reliability of SMAP under different climate conditions, we applied it to Naga oka, Japan, during the 2011-2012 winter.　At Nagaoka, we performed snow-soil-coupled simulations, because ground heat flux was not available during the study period.　For this purpose, we developed a soil submodel for SMAP. Consequently, we confirmed that the updated version performed better than the old version in terms of mass balance simulations at Nagaoka too.　Although mass balance-related parameters of the snowpack simulated by the updated version agreed well with observations during the accumulation period, the model substantially overestimated snow depth, as well as column-integrated snow water equivalent during the ablation period.　By discussing the reasons for these discrepancies, we highlighted that further investigation on snow-melt processes for thick seasonal snowpack is necessary.

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To determine the transport processes of water vapor and aerosols over the northwestern Greenland ice sheet, we undertook a glaciological observation at a coastal site on the northwestern part of the ice sheet and revealed spatial variations in δ¹⁸O and in the concentrations of chemical substances in surface snow and the snowpack.　On the outlet glacier (the Meehan glacier), water vapor and sea salt were transported from the coast.　On the inland ice sheet in northwestern Greenland, water vapor, mineral dust, anthropogenic substances such as NO₃^－ and SO₄^2－, and CH₃SO₃^－ from marine phytoplankton were transported from the west coast of Greenland via the central part of the Greenland ice sheet.

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Spatial variations in impurities (cryoconite) on the glacier surface were investigated on Qaanaaq Ice Cap and Tugto Glacier in the northwest Greenland in the melting season of 2012.　Abundance of impurities ranged from 0.36 to 119 g m^-2 (dry weight, mean:18.8 g m^-2) on bare ice and from 0.01 to 8.7 g m^-2 (mean:3.6 g m^-2) on snow surface at the study sites.　On Qaanaaq Glacier (an outlet glacier of Qaanaaq Ice Cap) impurity abundance was greatest at mid-elevations, with fewer impurities at upper and lower sites.　Surface reflectivity was lowest in the mid-elevation area, suggesting that impurities substantially reduce ice surface albedo at mid-elevations on glacier surfaces.　Organic matter content in the impurities ranged from 1.4 to 12.0% (mean:5.4%) on the ice and from 3.2 to 10.6% (mean:6.7%) on the snow surface.　Microscopy revealed that impurities in the ice areas mainly consisted of cryoconite granules, which are aggregations of mineral particles, filamentous cyanobacteria and other microbes and organic matter, while those in snow areas consisted of mineral particles and snow algae.　Results suggest that the spatial variation in the abundance of impurities is caused by supply of mineral particles both from air and ice, and microbial production of organic matter on the glacier surface.

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    Glaciological observations were conducted in 2012 and 2013 at the SIGMA-A site on the northwest Greenland ice sheet (78°03’06”N, 67°37’42”W, 1490 m a.s.l.) as part of the Snow Impurity and Glacial Microbe effects on abrupt warming in the Arctic (SIGMA) project.　The meteorological conditions during the two observations were quite different.　The meteorological condition during the 2012 observation period was warm, and heavy rainfall occurred during the observation period, thus the snow was very wet.　In contrast, the meteorological condition during the observation period in 2013 was cold, with a blowing snow event, thus the snow was quite dry.
    The glaciological observations in 2012 consisted of 1) snow-stake measurements, 2) snow pit observations, 3) grain size observations for validation of satellite-derived snow products, 4) snow specific surface area measurements using a near-infrared camera, 5) snow sampling for chemical analyses, and 6) drilling of firn cores with a hand auger.　The glaciological observations in 2013 consisted of 1) snow-stake measurements, 2) snow pit observations, and 3) snow sampling for chemical analyses.

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The mineralogical composition of cryoconite on a glacial surface was investigated on six glaciers in northwest Greenland (Qaanaaq, Qaqortaq, Tugto, Bowdoin, Sun, and Scarlet Heart).　The X-ray diffraction analysis showed that the cryoconites mainly contained seven silicate minerals: hornblende, quartz, potassium feldspar, plagioclase, illite, kaolinite, and chlorite.　Semi-quantitative mineralogical analysis of the silicate mineral composition on the Qaanaaq Glacier showed little variation among the samples collected from five different elevations.　This indicates that the minerals on the glacier were probably dominated by dust from a unique source, which is recently transported from local sediments, including soil and moraine.　On the other hand, the mineral composition varied significantly among the glaciers.　Based on the clay mineral content, the glaciers could be classified into three groups.　Type A: high clay mineral content, composed of illite and kaolinite, found on Qaanaaq, Qaqortaq, and Tugto;Type B: high clay mineral content, composed of only kaolinite, found on Sun;and Type C: lower clay mineral content, composed of only kaolinite, found on Bowdoin and Scarlet Heart.　The geographical distribution of the types of glaciers did not correspond with the geology in this area, indicating that the mineralogical composition is not determined just by the geological conditions around glaciers, but also by other factors, such as the redistribution of sediments by glacial, fluvial, or coastal processes.

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