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In situ meteorological data are essential to better understand ongoing environmental changes in the Arctic. Here, we present a dataset of quality-controlled meteorological observations by two automatic weather stations in northwest Greenland from July 2012 to the end of August 2020. The stations were installed in an accumulation area on the Greenland Ice Sheet (SIGMA-A site, 1490 m a.s.l.) and near the equilibrium line of the Qaanaaq Ice Cap (SIGMA-B site, 944 m a.s.l.). We describe the two-step sequence of quality-control procedures that we used to create increasingly reliable datasets by masking erroneous data records. We analyzed the resulting 2012–2020 time series of air temperature, positive degree-days, snow height, surface albedo, and histograms of longwave radiation (a proxy of cloud formation frequency). We found that snow height increased and albedo remained steady at the SIGMA-A site, whereas high air temperatures and clear-sky conditions prevailed while snow height and albedo decreased in the summers of 2015, 2019, and 2020 at the SIGMA-B site. Therefore, it appears that these weather conditions led to notable snow height degradation at the SIGMA-B site but not at the SIGMA-A site. We anticipate that this quality-control method and these datasets will aid in climate studies of northwest Greenland as well as contribute to the advancement of broader polar climate studies.

We reconstructed surface mass balance (SMB) around Dome Fuji, Antarctica, over the last 5000 years using the data from 15 shallow ice cores and seven snow pits. The depth–age relationships for the ice cores were determined by synchronizing them with a layer-counted ice core from West Antarctica (WAIS Divide ice core) using volcanic signals. The reconstructed SMB records for the last 4000 years show spatial patterns that may be affected by their locations relative to the ice divides around Dome Fuji, proximity to the ocean, and wind direction. The SMB records from the individual ice cores and snow pits were stacked to reconstruct the SMB history in the Dome Fuji area. The stacked record exhibits a long-term decreasing trend at -0.037±0.005 kg m−2 per century over the last 5000 years in the preindustrial period. The decreasing trend may be the result of long-term surface cooling over East Antarctica and the Southern Ocean and sea ice expansion in the water vapor source areas. The multidecadal to centennial variations of the Dome Fuji SMB after detrending the record shows four distinct periods during the last millennium: a mostly negative period before 1300 CE, a slightly positive period from 1300 to 1450 CE, a slightly negative period from 1450 to 1850 CE with a weak maximum around 1600 CE, and a strong increase after 1850 CE. These variations are consistent with those of previously reconstructed SMB records in the East Antarctic plateau. The low accumulation rate periods tend to coincide with the combination of strong volcanic forcings and solar minima for the last 1000 years, but the correspondence is not clear for the older periods, possibly because of the lack of coincidence of volcanic and solar forcings or the deterioration of the SMB record due to a smaller number of stacked cores.

The 13th Symposium on Polar Science/Interdisciplinary sessions [IA] Arctic research, Thu. 17 Nov.

The 13th Symposium on Polar Science/Special session [S] Towards the next six-year Japanese Antarctic Research Project (phase X), Tue. 15 Nov.

We reconstructed surface mass balance (SMB) around Dome Fuji, Antarctica, over the last 5000 years using the data from 15 shallow ice cores and 7 snow pits. The depth-age relationships for the ice cores were determined by synchronizing them with a layer-counted ice core from West Antarctica (WAIS Divide ice core) using volcanic signals. The reconstructed SMB records for the last 4000 years show spatial patterns that may be affected by their locations relative to the ice divides around Dome Fuji, proximity to the ocean, and wind direction. The SMB records from the individual ice cores and snow pits were stacked to reconstruct the SMB history in the Dome Fuji area. The stacked record exhibits a long-term decreasing trend at −0.037±0.005 kg m-2 per century over the last 5000 years in the preindustrial period. The decreasing trend may be the result of long-term surface cooling over East Antarctica and the Southern Ocean, and sea-ice expansion in the water vapor source areas. The multidecadal to centennial variations of the Dome Fuji SMB after detrending the record shows four distinct periods during the last millennium: mostly negative period before 1300 C.E., slightly positive for 1300–1450 C.E., slightly negative for 1450–1850 C.E. with a weak maximum around 1600 C.E., and strong increase after 1850 C.E. These variations are consistent with those of previously reconstructed SMB records in the East Antarctic plateau. The low accumulation rate periods tend to coincide with the combination of strong volcanic forcings and solar minima for the last 1000 years, but the correspondence is not clear for the older periods, possibly because of the lack of coincidence of volcanic and solar forcings, or the deterioration of the SMB record due to smaller number of stacked cores.

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.

The 11th Symposium on Polar Science/Ordinary sessions: [OM] Polar Meteorology and Glaciology, Poster presentations, Mon. 16 Nov. - Fri. 18 Dec.

The 11th Symposium on Polar Science/Ordinary sessions: [OM] Polar Meteorology and Glaciology, Poster presentations, Mon. 16 Nov. - Fri. 18 Dec.

The Greenland Ice Sheet (GrIS) mass loss has been accelerating at a rate of about 20 ± 10 Gt/yr2 since the end of the 1990's, with around 60 % of this mass loss directly attributed to enhanced surface meltwater runoff. However, in the climate and glaciology communities, different approaches exist on how to model the different surface mass balance (SMB) components using: (1) complex physically-based climate models which are computationally expensive; (2) intermediate complexity energy balance models; (3) simple and fast positive degree day models which base their inferences on statistical principles and are computationally highly efficient. Additionally, many of these models compute the SMB components based on different spatial and temporal resolutions, with different forcing fields as well as different ice sheet topographies and extents, making inter-comparison difficult. In the GrIS SMB model intercomparison project (GrSMBMIP) we address these issues by forcing each model with the same data (i.e., the ERA-Interim reanalysis) except for two global models for which this forcing is limited to the oceanic conditions, and at the same time by interpolating all modelled results onto a common ice sheet mask at 1 km horizontal resolution for the common period 1980–2012. The SMB outputs from 13 models are then compared over the GrIS to (1) SMB estimates using a combination of gravimetric remote sensing data from GRACE and measured ice discharge, (2) ice cores, snow pits, in-situ SMB observations, and (3) remotely sensed bare ice extent from MODerate-resolution Imaging Spectroradiometer (MODIS). Our results reveal that the mean GrIS SMB of all 13 models has been positive between 1980 and 2012 with an average of 340 ± Gt/yr, but has decreased at an average rate of −7.3 Gt/yr2 (with a significance of 96 %), mainly driven by an increase of 8.0 Gt/yr2 (with a significance of 98 %) in meltwater runoff. Spatially, the largest spread among models can be found around the margins of the ice sheet, highlighting the need for accurate representation of the GrIS ablation zone extent and processes driving the surface melt. In addition, a higher density of in-situ SMB observations is required, especially in the south-east accumulation zone, where the model spread can reach 2 mWE/yr due to large discrepancies in modelled snowfall accumulation. Overall, polar regional climate models (RCMs) perform the best compared to observations, in particular for simulating precipitation patterns. However, other simpler and faster models have biases of same order than RCMs with observations and remain then useful tools for long-term simulations. Finally, it is interesting to note that the ensemble mean of the 13 models produces the best estimate of the present day SMB relative to observations, suggesting that biases are not systematic among models.

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.

During spring 2017, we conducted research expeditions to the SIGMA-A site, which is located on the northwestern Greenland Ice Sheet. We maintained an automated weather station (AWS) to enable continuous meteorological observations. We extended 1.5-m long poles of the AWS and replaced two aerovane sensors, two thermo-hydrometers and an ultrasonic snow gauge. We also drilled an ice core and recovered a core with a total length of 60.06 m, conducted stratigraphic observations, and measured the density of the ice core. In addition, we conducted snow-pit observations and snow sampling, measured the specific surface area of snow using near-infrared reflectance, performed sunphotometry observations, and measured the spectral albedo. To schedule research activities in the field camp and helicopter pick-up flights, we received weather forecasts from the Meteorological Research Institute of Japan through the Internet using a satellite phone every day. We took a male dog to the field camp to alert us to approaching animals.

The Tenth Symposium on Polar Science/Ordinary sessions: [OM] Polar Meteorology and Glaciology, Wed. 4 Dec. / 2F Auditorium, National Institute of Polar Research

This paper describes in situ meteorological forcing and evaluation data, and bias-corrected reanalysis forcing data, for cold regions modelling at ten sites. The long-term datasets (one maritime, one arctic, three boreal and five mid-latitude alpine) are the reference sites chosen for evaluating models participating in the Earth System Model-Snow Model Intercomparison Project. Periods covered by the in situ data vary between seven and twenty years of hourly meteorological data, with evaluation data (snow depth, snow water equivalent, albedo, soil temperature and surface temperature) available at varying temporal intervals. 30-year (1980–2010) time-series have been extracted from a global gridded surface meteorology dataset (Global Soil Wetness Project Phase 3) for the grid cells containing the reference sites, interpolated to one-hour timesteps and bias corrected. Although applied to all sites, the bias corrections are particularly important for mountain sites that are hundreds of meters higher than the grid elevations; as a result, uncorrected air temperatures are too high and snowfall amounts are too low in comparison with in situ measurements. The discussion considers the importance of data sharing to the identification of errors and how the publication of these datasets contributes to good practice, consistency and reproducibility in Geosciences. Supplementary material provides information on instrumentation, an estimate of the percentages of missing values, and gap-filling methods at each site. It is hoped that these datasets will be used as benchmarks for future model development and that their ease of use and availability will help model developers quantify model uncertainties and reduce model errors. The data are published in the repository PANGAEA and available at: https://doi.org/10.1594/PANGAEA.897575.

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.

The Ninth Symposium on Polar Science/Interdisciplinary sessions: [IF] Toward Future Plan of the Arctic and Antarctic Science, Thu. 6 Dec. / 2F Auditorium, National Institute of Polar Research

The Ninth Symposium on Polar Science/Ordinary sessions: [OM] Polar meteorology and glaciology, Wed. 5 Dec. / Entrance Hall (1st floor), National Institute of Polar Research

The Ninth Symposium on Polar Science/Ordinary sessions: [OM] Polar meteorology and glaciology, Wed. 5 Dec. / 3F Multipurpose Conference room, National Institute of Polar Research

The Greenland ice sheet (GrIS) is known to be contributing to sea level rise in a warming climate. The snow cover on the ice sheet is the direct link between a potentially warmer atmosphere and the ice itself. However, little is known about the microstructure and especially about the spatial and temporal variability of the snow cover, except from indirect evidence from remote sensing. The detailed snowpack stratigraphy is relevant for processes such as the albedo feedback, water infiltration and firn densification. During a field campaign in 2015, spatially distributed snow observations of the GrIS were gathered at stations belonging to the Greenland Climate Network (GC-Net). High-resolution snow profiles of density, specific surface area and hardness were measured. Hardness was measured with the SnowMicroPen, which was also used to assess the spatial variability of the snow density with depth. The snow cover model SNOWPACK was forced with reanalysis data from the model NHM-SMAP. The measured mean density of the upper snow cover was in good agreement with the simulations using constant densities for snow accumulation, i.e. new snow, depending on the geographical location on the GrIS. However, the observed stratigraphy in terms of density and SSA could not be reproduced. We found that for a one-dimensional snowpack model it is difficult to parameterize for snowpacks undergoing multiple erosion and redeposition events, as is typical for the GrIS and other perennial polar snowpacks. This limitation may be a drawback to understanding past and future changes of the snow, and the associated processes.

As part of the terrestrial branch of the Japan-funded Arctic Climate Change Research Project (GRENE-TEA), which aims to clarify the role and function of the Arctic terrestrial system in the climate system, and assess the influence of its changes on a global scale, this model intercomparison project (GTMIP) is planned and being conducted to (1) enhance communication and understanding between the "minds and hands" (i.e., between the modelling and field scientists) and (2) assess the uncertainty and variations stemming from variability in model implementation/design and in model outputs due to climatic and historical conditions in the Arctic terrestrial regions. This paper provides an overview and the experiment protocol of Stage 1 of the project, site simulations driven by statistically fitted data created using the GRENE-TEA site observations for the last three decades. The target metrics for the model evaluation cover key processes in both physics and biogeochemistry, including energy budgets, snow, permafrost, phenology, and carbon budgets. The preliminary results on four metrics (annual mean latent heat flux, annual maximum snow depth, gross primary production, and net ecosystem production) already demonstrate the range of variations in reproducibility among existing models and sites. Full analysis on annual as well as seasonal time scales, to be conducted upon completion of model outputs submission, will delineate inter-dependence among the key processes, and provide the clue for improving the model performance.

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

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.

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.

第3回極域科学シンポジウム/特別セッション「これからの北極研究」11月28日（水） 国立極地研究所 2階大会議室

Ground-based measurements of spectral degree of linear polarization (DLP) of various snow types were made during intensive field campaigns in a snowfield in Hokkaido, Japan, and on the northwest Greenland ice sheet in 2012. Spectral measurements were conducted under the solar zenith angle of approximately the Brewster angle in order to quantify the polarization properties of light reflected from snow. We obtained spectral DLPs for five different snow types in both field campaigns including precipitation particles, needles, surface hoar, melt forms, and melt freeze crust covering the snow surface. The measurements showed that in the visible region the spectral dependence of the DLP was small while in the near infrared region it increased with increasing snow grain size with some distinct local peaks. The angular dependence indicated that the DLP exhibited small angular dependence in the visible region while in the near-infrared region it exhibited large and broad peaks in the forward direction. Especially for the melt-freeze crust, the DLP approached 1.0 at wavelengths close to λ = 1.5 and 2.0 μm. These features can be explained by (1) the relative contribution of surface versus volume scattering to the reflected light, (2) the incident angle (solar zenith angle) of approximately the Brewster angle, and (3) the ratio between direct and diffuse components of the solar radiation incident on the snow surface. The spectral DLP was found to be quiet sensitive to the incident solar radiation and solar elevation as well as snow optical properties. Comparison between the spectral DLP and snow grain size obtained by snow pit work shows that the DLP for λ > 1.5 μm was very sensitive to large snow grains close to the surface. This finding suggests that polarization measurements obtained from airborne/satellite polarimeters will be useful for surface snow grain size retrievals and help improve the accuracy of such retrievals based on the intensity-only measurements, especially for the large snow grain sizes., 資料番号: PA1510023000