Snow Surface Albedo Research Articles

Research progress of light-absorbing impurities in glaciers of the Tibetan Plateau and its surroundings

Light-absorbing impurities (LAIs, including black carbon, organic carbon, and dust) deposited on glacier surface can have strong effects on mass and energy balance of the cryosphere. Widespread with amount of glaciers, the Tibetan Plateau (TP) is considered to be an ideal region to study the impact of LAIs to glacier melt. Based on recent studies of LAIs in glacial snow of the TP, we summarized the research progress of LAIs in glacial snow, including their concentrations and spatial distributions, especially focusing on discussion of sources of black carbon, and documenting the albedo reduction and radiative forcing caused by LAIs. Additionally, we identified research gaps and suggested future research directions. At present, spatial distribution of LAIs in glacial snow and ice from TP and its surroundings exist a significant difference due to natural/anthropogenic emission sources, local topography, atmospheric transportation, and different glacial surface (e.g., fresh snow, aged snow, granular ice, bare ice). In general, higher concentrations of BC occurred in the northern and southern regions; LAIs in aged snow or granular ice were higher by 1–2 order of magnitude than that in the fresh snow or snowpit. Characteristics of LAIs from different glacial surfaces were still limited especially in Tienshan regions, which need to be further studies. Since Industrial Revolution, BC in ice cores increased in recent decades which may be likely caused by increasing emissions of fossil fuel combustion and biomass burning in the South Asia and Central Asia. The process of snowmelt can enrich the BC concentrations in surface and change the mixture of BC with snow grains, which will further enhance the albedo reduction. Studies on post-deposition processes of other LAIs and their effects on snow surface albedo are urgent to be strengthened. Simulation results indicated that BC aerosol of the southern TP mainly originated from the South Asia, which can contributed to approximately 50% in non-monsoon season and 30% in monsoon season; anthropogenic sourced BC can contributed to 30%–70%. However, studies on enrichment and transport processes of LAIs in glacial surface snow still should be emphasized. Although LAIs initiated powerful snow albedo feedbacks and glacier melt, estimation of this effect was associated with a large uncertainty. Based snow ice and aerosol radiation (SNICAR) model, effects of BC and dust on albedo reduction were estimated to be less than 10% in the southern TP and more than 25% in the central and northern TP influencing by snow types. Simulation of BC on albedo effects were affected by mixture of BC, coatings with other components, and snow grains, which lead to different radiative forcing in different regions. For aged snow or granular ice, effects of BC and dust can give localized instantaneous radiative forcing to about near or more than 100 W m−2; for fresh or snowpit, BC and dust can result in a minor radiative forcing (mostly less than 10 W m−2). These effects of LAIs on albedo reduction and radiative forcing enhanced glacier melt, which will further affect the hydrological processes. Estimation represented that LAIs in snow can lead to approximately 15% of the total glacier melt in the southeast TP and 6.3% increasing glacier melt in the Pamir regions. However, there still existed differences between the observations and simulations of LAIs in snow, which was mostly related to the different deposition flux and snow accumulation. In the future, mixing state of LAIs in snow, and their synergistic effects of biogeochemical process and climate change will be a new research direction.

Snow specific surface area remote sensing retrieval using a microstructure based reflectance model

The snow specific area (SSA) is a quantity to describe the size of snow grains, which controls the albedo of snow surface. The remote sensing retrieval of snow SSA is important for large scale energy and snow physical properties studies. The previous SSA retrieval algorithms are based on snow reflectance forward models with shape assumptions of snow grains, which may cause bias in the quantitative retrieval of SSA. In this paper, a new SSA retrieval algorithm based on a recently developed snow reflectance model is presented. In the reflectance model, the microstructure of snow medium is simulated by computer and the light scattering process is modeled by Monte Carlo ray tracing and radiative transfer theory. Validation shows the model can accurately simulate snow surface reflectance even at large incident or observation zenith angles. Three datasets were used to validate the SSA retrieval algorithm. The validation results show that the SSA can be accurately estimated using MODIS data. The difference of SSA by using reflectance of different wavelengths are studied by MODIS band 5 and band 6 data. The SSA retrieval algorithm is then applied to seasonal snow cover to study the temporal and spatial pattern of snow surface optical grain size.

A simple model of snow albedo decay using observations from the Community Collaborative Rain, Hail, and Snow-Albedo (CoCoRaHS-Albedo) Network

ABSTRACTThe albedo of seasonal snow cover plays an important role in the global climate system due to its influence on Earth's radiation budget and energy balance. Volunteer Community Collaborative Rain, Hail, and Snow-Albedo (CoCoRaHS-Albedo) observers collected 3249 individual daily albedo, snow depth and density measurements using standardized techniques at dozens of sites across New Hampshire, USA over four winter seasons. The data show that albedo increases rapidly with snow depth up to ~0.14 m. Multiple linear regression models using snowpack age, snow depth or density, and air temperature provide reasonable approximations of surface snow albedo during times of albedo decay. However, the linear models also reveal systematic biases that highlight an important non-linearity in snow albedo decay. Modeled albedo values are reasonably accurate within the range of 0.6–0.9, but exhibit a tendency to overestimate lower albedo values and underestimate higher albedo values. We hypothesize that rapid reduction in high albedo fresh snow results from a decrease in snow specific surface area, while during melt-events the presence of liquid water in the snowpack accelerates metamorphism and grain growth. We conclude that the CoCoRaHS-Albedo volunteer observer network provides useful snow albedo, depth and density measurements and serves as an effective model for future measurement campaigns.

Automated Webcam Monitoring of Fractional Snow Cover in Northern Boreal Conditions

Fractional snow cover (FSC) is an important parameter to estimate snow water equivalent (SWE) and surface albedo important to climatic and hydrological applications. The presence of forest creates challenges to retrieve FSC accurately from satellite data, as forest canopy can block the sensor’s view of snow cover. In addition to the challenge related to presence of forest, in situ data of FSC—necessary for algorithm development and validation—are very limited. This paper investigates the estimation of FSC using digital imagery to overcome the obstacle caused by forest canopy, and the possibility to use this imagery in the validation of FSC derived from satellite data. FSC is calculated here using an algorithm based on defining a threshold value according to the histogram of an image, to classify a pixel as snow-covered or snow-free. Images from the MONIMET camera network, producing a continuous image series in Finland, are used in the analysis of FSC. The results obtained from automated image analysis of snow cover are compared with reference data estimated by visual inspection of same images. The results show the applicability and usefulness of digital imagery in the estimation of fractional snow cover in forested areas, with a Root Mean Squared Error (RMSE) in the range of 0.1–0.3 (with the full range of 0–1).

Large Increase in Incident Shortwave Radiation due to the Ozone Hole Offset by High Climatological Albedo over Antarctica

Despite increasing scientific scrutiny in recent years, the direct impact of the ozone hole on surface temperatures over Antarctica remains uncertain. Here, this question is explored by using the Community Earth System Model–Whole Atmosphere Community Climate Model (CESM-WACCM), contrasting two ensembles of runs with and without stratospheric ozone depletion. It is found that, during austral spring, the ozone hole leads to a surprisingly large increase in surface downwelling shortwave (SW) radiation over Antarctica of 3.8 W m−2 in clear sky and 1.8 W m−2 in all sky. However, despite this large increase in incident SW radiation, no ozone-induced surface warming is seen in the model. It is shown that the lack of a surface temperature response is due to reflection of most of the increased downward SW, resulting in an insignificant change to the net SW radiative heating. To first order, this reflection is simply due to the high climatological surface albedo of the Antarctic snow (97% in visible SW), resulting in a net zero ozone-induced surface SW forcing. In addition, it is shown that stratospheric ozone depletion has a negligible effect on longwave (LW) radiation and other components of the surface energy budget. These results suggest a minimal role for ozone depletion in forcing Antarctic surface temperature trends on a continental scale.

Tendencies in current climate change and atmospheric circulation variability in the Arctic region of West Siberia

The main goal of this study is to carry out the investigation of the climatic parameters variability and the role of global atmospheric circulation in their trends over the Arctic region of West Siberia (60-70°N, 60-90°E) using reanalysis data. The characteristics of spatial and temporal variability of meteorological parameters (surface air temperature and soil temperature, atmospheric pressure, snow depth and surface albedo) were calculated using ERA-Interim reanalysis data over the period of 1979−2015. It was established that in the beginning of XXI century, there is an air and soil temperature decrease in winter and autumn and its statistically significant increase in spring and summer. The tendency to permafrost area degradation is observed for the Arctic region. The maximal changes are observed in low-temperature permafrost soils than in soils with higher temperature. This trend is accompanied by the decrease in snow cover depth and surface albedo. Global circulation indices variability, its relationships with meteorological parameters in West Siberia and with sea ice cover extent in the Arctic Seas indicate that atmospheric blocking processes, which are responsible for anticyclonic type of weather, were developed in the region during last decades.

The effects of forest litter on snow energy budget in the Tianshan Mountains, China

AbstractForest litter exerts an impact on the energy budget of snow surfaces, which lie beneath forest canopies. In this study, we measured shortwave and longwave radiation levels, as well as quantities of Asian spruce (Picea schrenkinan) forest litter, over 3 snow study plots that representing an open environment, 20% forest canopy openness (20% FCO), and 80% forest canopy openness (80% FCO). The fractional litter coverage (lc) was obtained through the binarization of digital photographs of forest litter. The effects of forest litter on snow surface albedo (α), snow surface temperature (Ts), upward shortwave and longwave radiation (K↑ and L↑), and sensible heat flux (H) were then analyzed. According to our results, the energy budget over snow surface influenced by forest litter principally due to forest litter forcing α decrease and Ts increase. The effects of forest litter on the energy budget increased with time and lc. We found that forest litter exerted the most significant impact on K↑ and L↑ at daytime during the latter stages of the snowmelt period. The influence of forest litter on H was more apparent on windy days. The presence of forest litter increased gains in shortwave radiation and losses in longwave radiation and decreased gains in H. Compared to the simulated energy (K↑ + L↑ + H) over a snow surface without litter, the calculated energy decreased by −13.4 W/m2 and increased by 9.0 W/m2, respectively, at the 20% FCO and 80% FCO sites during the latter stages of the snowmelt period. Overall, forest litter facilitated snow surface energy gains at the 80% FCO site and impeded them at the 20% FCO site during the latter stages of the snowmelt period.

The intraannual variability of land‐atmosphere coupling over North America in the Canadian Regional Climate Model (CRCM5)

AbstractThis study investigates the intraannual variability of soil moisture‐temperature coupling over North America. To this effect, coupled and uncoupled simulations are performed with the fifth‐generation Canadian Regional Climate Model (CRCM5), driven by ERA‐Interim. In coupled simulations, land and atmosphere interact freely; in uncoupled simulations, the interannual variability of soil moisture is suppressed by prescribing climatological values for soil liquid and frozen water contents. The study also explores projected changes to coupling by comparing coupled and uncoupled CRCM5 simulations for current (1981–2010) and future (2071–2100) periods, driven by the Canadian Earth System Model. Coupling differs for the northern and southern parts of North America. Over the southern half, it is persistent throughout the year while for the northern half, strongly coupled regions generally follow the freezing line during the cold months. Detailed analysis of the southern Canadian Prairies reveals seasonal differences in the underlying coupling mechanism. During spring and fall, as opposed to summer, the interactive soil moisture phase impacts the snow depth and surface albedo, which further impacts the surface energy budget and thus the surface air temperature; the air temperature then influences the snow depth in a feedback loop. Projected changes to coupling are also season specific: relatively drier soil conditions strengthen coupling during summer, while changes in soil moisture phase, snow depth, and cloud cover impact coupling during colder months. Furthermore, results demonstrate that soil moisture variability amplifies the frequency of temperature extremes over regions of strong coupling in current and future climates.

An evaluation of high‐resolution regional climate model simulations of snow cover and albedo over the Rocky Mountains, with implications for the simulated snow‐albedo feedback

AbstractThe snow‐albedo feedback (SAF) strongly influences climate over midlatitude mountainous regions. However, over these regions the skill of regional climate models (RCMs) at simulating properties such as snow cover and surface albedo is poorly characterized. These properties are evaluated in a pair of 7 year long high‐resolution RCM simulations with the Weather Research and Forecasting model over the central Rocky Mountains. Key differences between the simulations include the computational domain (regional versus continental) and land surface model used (Noah versus Noah‐MP). Simulations are evaluated against high‐resolution satellite estimates of snow cover and albedo from the Moderate Resolution Imaging Spectroradiometer. Both simulations generally reproduce the observed seasonal and spatial variability of snow cover and also exhibit important biases. One simulation substantially overpredicts subpixel fractional snow cover over snowy pixels (by up to 0.4) causing large positive biases in surface albedo, likely due in part to inadequate representation of canopy effects. The other simulation exhibits a negative bias in areal snow extent (as much as 19% of the analysis domain). Surface measurements reveal large positive biases in snow albedo (exceeding 0.2) during late spring caused by neglecting radiative effects of impurities deposited onto snow. Semi‐idealized climate change experiments show substantially different magnitudes of SAF‐enhanced warming in the two simulations that can be tied to the differences in snow cover in their control climates. More confident projections of regional climate change over mountains will require further work to evaluate and improve representation of snow cover and albedo in RCMs.

Impacts of snow and organic soils parameterization on northern Eurasian soil temperature profiles simulated by the ISBA land surface model

Abstract. In this study we analyzed how an improved representation of snowpack processes and soil properties in the multilayer snow and soil schemes of the Interaction Soil-Biosphere-Atmosphere (ISBA) land surface model impacts the simulation of soil temperature profiles over northern Eurasian regions. For this purpose, we refine ISBA's snow layering algorithm and propose a parameterization of snow albedo and snow compaction/densification adapted from the detailed Crocus snowpack model. We also include a dependency on soil organic carbon content for ISBA's hydraulic and thermal soil properties. First, changes in the snowpack parameterization are evaluated against snow depth, snow water equivalent, surface albedo, and soil temperature at a 10 cm depth observed at the Col de Porte field site in the French Alps. Next, the new model version including all of the changes is used over northern Eurasia to evaluate the model's ability to simulate the snow depth, the soil temperature profile, and the permafrost characteristics. The results confirm that an adequate simulation of snow layering and snow compaction/densification significantly impacts the snowpack characteristics and the soil temperature profile during winter, while the impact of the more accurate snow albedo computation is dominant during the spring. In summer, the accounting for the effect of soil organic carbon on hydraulic and thermal soil properties improves the simulation of the soil temperature profile. Finally, the results confirm that this last process strongly influences the simulation of the permafrost active layer thickness and its spatial distribution.

Snow grain size retrieval over the polar ice sheets with the Ice, Cloud, and land Elevation Satellite (ICESat) observations

Snow grain size is an important parameter for cryosphere studies. As a proof of concept, this paper presents an approach to retrieve this parameter over Greenland, East and West Antarctica ice sheets from surface reflectances observed with the Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud, and land Elevation Satellite (ICESat) at 1064nm. Spaceborne lidar observations overcome many of the disadvantages in passive remote sensing, including difficulties in cloud screening and low sun angle limitations and hence tend to provide more accurate and stable retrievals. Results from the GLAS L2A campaign, which began on 25 September and lasted until 19 November, 2003, show that the mode of the grain size distribution over Greenland is the largest (~300µm) among the three, West Antarctica is the second (~220µm) and East Antarctica is the smallest (~190µm). Snow grain sizes are larger over the coastal regions compared to inland the ice sheets. These results are consistent with previous studies. Applying the broadband snow surface albedo parameterization scheme developed by Garder and Sharp (2010) to the retrieved snow grain size, ice sheet surface albedo is also derived. In the future, more accurate retrievals can be achieved with multiple wavelengths lidar observations.

The global land shortwave cryosphere radiative effect during the MODIS era

Abstract. The shortwave cryosphere radiative effect (CrRE) is the instantaneous influence of snow and ice cover on Earth's top-of-atmosphere (TOA) solar energy budget. Here, we apply measurements from the MODerate resolution Imaging Spectroradiometer (MODIS), combined with microwave retrievals of snow presence and radiative kernels produced from four different models, to derive CrRE over global land during 2001–2013. We estimate global annual-mean land CrRE during this period of −2.6 W m−2, with variations from −2.2 to −3.0 W m−2 resulting from use of different kernels and variations of −2.4 to −2.6 W m−2 resulting from different algorithmic determinations of snow presence and surface albedo. Slightly more than half of the global land CrRE originates from perennial snow on Antarctica, whereas the majority of the northern hemispheric effect originates from seasonal snow. Consequently, the northern hemispheric land CrRE peaks at −6.0 W m−2 in April, whereas the southern hemispheric effect more closely follows the austral insolation cycle, peaking at −9.0 W m−2 in December. Mountain glaciers resolved in 0.05° MODIS data contribute about −0.037 W m−2 (1.4 %) of the global effect, with the majority (94 %) of this contribution originating from the Himalayas. Interannual trends in the global annual-mean land CrRE are not statistically significant during the MODIS era, but trends are positive (less negative) over large areas of northern Asia, especially during spring, and slightly negative over Antarctica, possibly due to increased snowfall. During a common overlap period of 2001–2008, our MODIS estimates of the northern hemispheric land CrRE are about 18 % smaller (less negative) than previous estimates derived from coarse-resolution AVHRR data, though interannual variations are well correlated (r = 0.78), indicating that these data are useful in determining longer-term trends in land CrRE.

Summer Surface Albedo of Sea Ice in Pacific Arctic Sector as Measured during the CHINARE 2010 cruise

Knowledge of Arctic snow and ice surface albedo is essential to understand local energy budget and snow/ice albedo feedback under global warming scenario. In situ measured albedo plays an essential role by providing ground truth reference for remote sensing monitoring of albedo at large scale. Such measurements with portable and fixed-location spectroradiometers were conducted in one 12-day (long-term) and several short-term (3–4 hours) ice stations over the Pacific Arctic sector during the summer 2010 Chinese National Arctic Research Expedition (CHINARE). Results show that the wavelength-integrated albedo across 350 to 2200 nm of bare ice was ∼0.56 to 0.68 in the lower latitudes and marginal ice zone, while albedo of snow-covered ice reduced from 0.75–0.86 to 0.42–0.61 during the mid-August period of the 12-day ice station (86°48′N to 87°20′N). The albedo variation and evolution of melt ponds were examined with details during the 12-day ice station. It is found that albedo of melt pond reduced from 0.68 (melt pond snow, 9 August) and 0.66 (melt pond ice, 9 August) to 0.32 (melt pond water and ice, 17 August) in one week as a rainfall event occurred. Such rapid decreasing of snow and sea ice albedo and evident difference between the pack ice zone and marginal ice zone may contribute to the surface albedo feedback and rapidly shrinking summer sea ice extent in the Arctic Ocean.

Quantifying the skill of CMIP5 models in simulating seasonal albedo and snow cover evolution

AbstractEffectively modeling the influence of terrestrial snow on climate in general circulation models is limited by imperfect knowledge and parameterization of arctic and subarctic climate processes and a lack of reliable observations for model evaluation and improvement. This study uses a number of satellite‐derived data sets to evaluate how well the current generation of climate models from the Fifth Coupled Model Intercomparison Project (CMIP5) simulate the seasonal cycle of climatological snow cover fraction (SCF) and surface albedo over the Northern Hemisphere snow season (September–June). Using a variety of metrics, the CMIP5 models are found to simulate SCF evolution better than that of albedo. The seasonal cycle of SCF is well reproduced despite substantial biases in simulated surface albedo of snow‐covered land (αsfc_snow), which affect both the magnitude and timing of the seasonal peak in αsfc_snow during the fall snow accumulation period, and the springtime snow ablation period. Insolation weighting demonstrates that the biases in αsfc_snow during spring are of greater importance for the surface energy budget. Albedo biases are largest across the boreal forest, where the simulated seasonal cycle of albedo is biased high in 15/16 CMIP5 models. This bias is explained primarily by unrealistic treatment of vegetation masking and subsequent overestimation (more than 50% in some cases) of peak αsfc_snow rather than by biases in SCF. While seemingly straightforward corrections to peak αsfc_snow could yield significant improvements to simulated snow albedo feedback, changes in αsfc_snow could potentially introduce biases in other important model variables such as surface temperature.

In situ observations of black carbon in snow and the corresponding spectral surface albedo reduction

AbstractBlack carbon (BC) particles emitted from incomplete combustion of fossil fuel and biomass and deposited on snow and ice darken the surface and reduce the surface albedo. Even small initial surface albedo reductions may have larger adjusted effects due to snow morphology changes and changes in the sublimation and snow melt rate. Most of the literature on the effect of BC on snow surface albedo is based on numerical models, and few in situ field measurements exist to confirm this reduction. Here we present an extensive set of concurrent in situ measurements of spectral surface albedo, BC concentrations in the upper 5 cm of the snowpack, snow physical parameters (grain size and depth), and incident solar flux characteristics from the Arctic. From this data set (with median BC concentrations ranging from 5 to 137 ng BC per gram of snow) we are able to separate the BC signature on the snow albedo from the natural snow variability. Our measurements show a significant correlation between BC in snow and spectral surface albedo. Based on these measurements, parameterizations are provided, relating the snow albedo, as a function of wavelength, to the equivalent BC content in the snowpack. The term equivalent BC used here is the elemental carbon concentration inferred from the thermo‐optical method adjusted for the fraction of non‐BC constituents absorbing sunlight in the snow. The first parameterization is a simple equation which efficiently describes the snow albedo reduction due to the equivalent BC without including details on the snow or BC microphysics. This can be used in models when a simplified description is needed. A second parameterization, including snow grain size information, shows enhanced correspondence with the measurements. The extracted parameterizations are valid for wavelength bands 400–900 nm, constrained for BC concentrations between 1 and 400 ng g−1, and for an optically thick snowpack. The parameterizations are purely empirical, and particular focus was on the uncertainties associated with the measurements, and how these uncertainties propagate in the parameterizations. Integrated, the first parameterization (based only on the equivalent BC) gives a broadband (400–900 nm) snow albedo reduction of 0.004 due to 10 ng equivalent BC per gram of snow, while the effect is almost 5 times larger for BC concentrations 1 order of magnitude higher. The study shows that the reconstructed albedo from the second parameterization (including information on the snow grain size) corresponds better to the radiative transfer model Snow, Ice, and Aerosol Radiation albedo than the reconstructed albedo from the first parameterization (excluding grain size information).

Computation of a distributed glacier surface albedo proxy using airborne laser scanning intensity data and in-situ spectro-radiometric measurements

In recent years, multi-temporal topographic measurements from airborne laser scanning (ALS) have been increasingly used as a source of spatially explicit and accurate information to calculate geodetic glacier mass balances. Simultaneous to collecting topographic data, most ALS instruments record the backscattered intensity for each laser emission and therefore provide additional information on the reflectance characteristics of the surveyed surface. Along with air temperature, the surface albedo of snow and ice was identified as a major driving factor of glacier melt. Consequently, better knowledge on the spatial distribution of the glacier albedo could substantially improve energy balance based glacier melt modeling. In this study, we collected on-glacier spectro-radiometric and albedometer measurements to serve as a ground reference to radiometrically calibrate high resolution ALS intensity data into a distributed albedo proxy map. This method resulted in an albedo proxy with values between 0.6 on the glacier tongue and 0.9 on fresh snow in high altitudes. 99.6% of all values fell within the albedo boundary conditions, i.e. values between 0 and 1. Corrected near-infrared ALS intensity data provided a distributed product that allows simulating albedo in glacier energy and mass balance models more realistically. Remaining challenges are (i) a different surface albedo response in the visual part of the electro-magnetic spectrum, (ii) the low radiometric resolution of the ALS system for higher intensity values, and (iii) an insufficient correction of the snow bi-directional reflectance distribution function (BRDF).

Catchment response to bark beetle outbreak and dust-on-snow in the Colorado Rocky Mountains

Summary Since 2002, the headwaters of the Colorado River and nearby basins have experienced extensive changes in land cover at sub-annual timescales. Widespread tree mortality from bark beetle infestation has taken place across a range of forest types, elevation, and latitude. Extent and severity of forest structure alteration have been observed through a combination of aerial survey, satellite remote-sensing, and in situ measurements. Additional perturbations have resulted from deposition of dust from regional dry-land sources on mountain snowpacks that strongly alter the snow surface albedo, driving earlier and faster snowmelt runoff. One challenge facing past studies of these forms of disturbance is the relatively small magnitude of the disturbance signals within the larger climatic signal. The combined impacts of forest disturbance and dust-on-snow are explored within a hydrologic modeling framework. We drive the Distributed Hydrology Soil and Vegetation Model (DHSVM) with observed meteorological data, time-varying maps of leaf area index and forest properties to emulate bark beetle impacts, and parameterizations of snow albedo based on observations of dust forcing. Results from beetle-killed canopy alteration suggest slightly greater snow accumulation as a result of less interception and reduced canopy sublimation and evapotranspiration, contributing to overall increases in annual water yield between 8% and 13%. However, understory regeneration roughly halves the changes in water yield. A purely observation-based estimate of runoff coefficient change with cumulative forest mortality shows comparable sensitivities to simulated results; however, positive water yield changes are not statistically significant ( p ⩽ 0.05). The primary hydrologic impact of dust-on-snow forcing is an increased rate of snowmelt associated with more extreme dust deposition, producing earlier peak streamflow rates on the order of 1–3 weeks. Simulations of combined bark beetle and dust-on-snow produced little compounding effects, due to the relatively exclusive nature of their impacts. Potential changes in water yield and peak streamflow timing have important implications for regional water management decisions.

Modelling snow ice and superimposed ice on landfast sea ice in Kongsfjorden, Svalbard

Snow ice and superimposed ice formation on landfast sea ice in a Svalbard fjord, Kongsfjorden, was investigated with a high-resolution thermodynamic snow and sea-ice model, applying meteorological weather station data as external forcing. The model shows that sea-ice formation occurs both at the ice bottom and at the snow/ice interface. Modelling results indicated that the total snow ice and superimposed ice, which formed at the snow/ice interface, was about 14 cm during the simulation period, accounting for about 15% of the total ice mass and 35% of the total ice growth. Introducing a time-dependent snow density improved the modelled results, and a time-dependent oceanic heat flux parameterization yielded reasonable ice growth at the ice bottom. Model results suggest that weather conditions, in particular air temperature and precipitation, as well as snow thermal properties and surface albedo are the most critical factors for the development of snow ice and superimposed ice in Kongsfjorden. While both warming air and higher precipitation led to increased snow ice and superimposed ice forming in Kongsfjorden in the model runs, the processes were more sensitive to precipitation than to air temperature.Keywords: Snow ice; superimposed ice; thermodynamic modelling; landfast sea ice; Kongsfjorden.(Published: 24 August 2015)Citation: Polar Research 2015, 34, 20828, http://dx.doi.org/10.3402/polar.v34.20828

Relationship between the Concentration of Impurity and Albedo in Snow Surface

Recent decline of cryosphere typified by retreat of glaciers is often explained by temperature rise due to global warming. However, the existence of glaciers shrinking since before 1950s warming accelerated suggested that decline of cryosphere may be due to not only temperature rise, but also another possibility. As a possible cause of snow and ice melting, it has been pointed out that the surface albedo reduction due to increase of snow impurity, aeolian dust and anthropogenic pollutant, for example. To clarify the quantitative relationship between albedo and impurity in snow surface, we investigated the correlativity of turbidity and metal concentration in snow to the snow surface albedo from the simultaneous observations on the snow-covered area in Yamagata, Japan. The observed albedo shows a tendency of decrease with the turbidity increase in snow surface, we could find strong correlation between the albedo and the turbidity in 76% of contribution factor using logarithmic regression analysis. The relationship of albedo to total concentration of Fe and Al in snow surface shows the similar tendency to turbidity, we could model the relationship using logarithmic equation with high value of contribution ratio, 74% and 66%, respectively. The concentration ratio of Fe/Al is nearly constant with about 0.75, which is close to mean crustal ratio of both elements, therefore, it can be said there is a strong correlation between the albedo and the concentration of mineral particle in snow surface. We cannot find a significant correlation between the albedo and total concentration of Na in snow surface. It can be considered that Na existed as dissolved ion has not significant effect to the albedo in snow surface. These results indicate that the snow albedo correlates strongly with the particulate matter in snow surface, which is typified by mineral particle.

A 10 year record of black carbon and dust from a Mera Peak ice core (Nepal): variability and potential impact on melting of Himalayan glaciers

Abstract. A shallow ice core was extracted at the summit of Mera Peak at 6376 m a.s.l. in the southern flank of the Nepalese Himalaya range. From this core, we reconstructed the seasonal deposition fluxes of dust and refractory black carbon (rBC) since 1999. This archive presents well preserved seasonal cycles based on a monsoonal precipitation pattern. According to the seasonal precipitation regime in which 80% of annual precipitation falls between June and September, we estimated changes in the concentrations of these aerosols in surface snow. The analyses revealed that mass fluxes are a few orders of magnitude higher for dust (10.4 ± 2.8 g m−2 yr−1 than for rBC (7.9 ± 2.8 mg m−2 yr−1). The relative lack of seasonality in the dust record may reflect a high background level of dust inputs, whether from local or regional sources. Over the 10-year record, no deposition flux trends were detected for any of the species of interest. The data were then used to simulate changes in the surface snow albedo over time and the potential melting caused by these impurities. Mean potential melting caused by dust and rBC combined was 713 kg m−2 yr−1, and for rBC alone, 342 kg m−2 yr−1 for rBC under certain assumptions. Compared to the melting rate measured using the mass and energy balance at 5360 m a.s.l. on Mera Glacier between November 2009 and October 2010, i.e. 3000 kg m−2 yr−1 and 3690 kg m−2 yr−1 respectively, the impact of rBC represents less than 16% of annual potential melting while the contribution of dust and rBC combined to surface melting represents a maximum of 26%. Over the 10-year period, rBC variability in the ice core signal primarily reflected variability of the monsoon signal rather than variations in the intensity of emissions.