Snow Albedo Research Articles

An Operational Methodology for Validating Satellite-Based Snow Albedo Measurements Using a UAV

Snow albedo is highly variable over multiple temporal and spatial scales. This variability is more pronounced in areas that experience seasonal snowpack. Satellite retrievals, physically based models and parameterizations for snow albedo all require ground-based measurements for calibration, initialization, and validation. Ground measurements are generally made using upward and downward-facing pyranometers at opportunistically located weather stations that are sparsely distributed, particularly in mountainous regions. These station-based measurements cannot capture the spatial variability of albedo across the land surface. Uncrewed Aerial Vehicles (UAVs) equipped with upward and downward-facing pyranometers provide near-surface measurements of broadband albedo that are spatially distributed across landscapes, offering improvements over in-situ sensors. At the hillslope to watershed scale albedo measurements from UAVs taken over heterogeneous terrain are a function of the spatial variability in albedo and topography within the downward-facing sensor’s field-of-view (FOV). In this research we propose methods for topographic correction of UAV snow albedo measurements and comparison to gridded satellite albedo products. These methods account for the variability of surface topography and albedo within the sensor FOV, sensor tilt, and the angular response of pyranometers. We applied the proposed methodologies to UAV snow albedo measurements collected over an alpine meadow in southwest Montana, United States (45.23°, −111.28°). Sensitivity analyses were conducted to determine the effect of altering the processing FOV (PFOV) for both topographic corrections and comparison to coincident Landsat 8-derived albedo measurements. Validation from ground-based albedo measurements showed the topographic correction to reduce albedo measurement error considerably over mildly sloping terrain. Our sensitivity analyses demonstrated that outcomes from the topographic correction and satellite comparison are highly dependent on the specified PFOV. Based on field observations and analyses of UAV albedo measurements made at different altitudes, we provide guidelines for strategizing future UAV albedo surveys. This research presents considerable advances in the standardization of UAV-based albedo measurement. We establish the foundation for future research to utilize this platform to collect near-surface validation measurements over heterogeneous terrain with high accuracy and consistency.

Snow albedo reductions induced by the internal/external mixing of black carbon and mineral dust, and different snow grain shapes across northern China

Previous studies have indicated that black carbon (BC) potentially induces snow albedo reductions across northern China. However, the effects of other light-absorbing particles (LAPs, e.g., mineral dust, MD), snow grain shape, or BC–snow mixing state on snow albedo have been largely ignored. Here we evaluate the BC- and MD-induced snow albedo reductions and radiative forcings (RFs) using an updated Snow, Ice, and Aerosol Radiation radiative transfer model, considering all of the potential factors that can be derived from the field observations across northern China. The results highlight that the LAP-induced albedo reductions for nonspherical snow grains are 2%–30% less than those for spherical grains. Furthermore, BC–snow internal mixing can significantly enhance albedo reduction by a factor of 1.42–1.48 relative to external mixing, with snow grain radius ranging from 100 to 1000 μm. The mean regional BC + MD-induced snow albedo reductions are amplified by the increase of snow grain radius, ranging from 0.012 to 0.123 for fresh snow to 0.016–0.227 for old snow. Finally, we discuss the relative contributions of BC and MD to the albedo reductions and RFs, highlighting the dominant role of BC in reducing snow albedo across northern China.

Modelling light-absorbing particle–snow–radiation interactions and impacts on snow albedo: fundamentals, recent advances and future directions

Environmental context Snow albedo plays an important role in the Earth environment. Light-absorbing particles (LAPs) can significantly impact snow albedo through complex interactions and feedbacks over the global cryosphere. This study provides a unique review of the fundamentals, recent advances, challenges and future research directions in modelling LAP–snow–radiation interactions and impacts on snow albedo. Abstract Snow albedo plays a critical role in the Earth system through a strong positive climate feedback, modulating surface energy and water balance. Light-absorbing particles (LAPs), including black carbon, mineral dust, brown carbon, volcanic ash and snow algae, have been found to substantially reduce snow albedo and accelerate snow/ice melting across the global cryosphere. In the past decades, substantial observational and modelling efforts have been made to advance the understanding and quantification of LAP–snow–radiation interactions and impacts on snow albedo and hydro-climate, with important uncertainties still remaining. Here we provide a unique review of the fundamentals and recent scientific advances in modelling LAP–snow–radiation interactions from microscopic (particle level) to macroscopic (bulk snow optical properties and albedo) perspectives. We also discuss the current challenges and potential research directions on this topic to shed light on future studies.

Physics‐Based Narrowband Optical Parameters for Snow Albedo Simulation in Climate Models

AbstractAccurate snow albedo simulation is a prerequisite for climate models to produce reliable climate prediction. Climate models would benefit from schemes of snowpack radiative transfer that are responsive to changing atmospheric conditions. However, the uncertainties in the narrowband snow optical parameters used by these schemes have not been evaluated. Conventional methods typically compute these narrowband parameters as irradiance‐weighted averages of the spectral snow optical parameters, with the single scattering albedo being additionally weighted by the optically thick snowpack albedo. We first evaluate the effectiveness of the conventional methods as adopted by the widely used Community Land Model (CLM). Snow albedo calculations using the CLM narrowband optical parameters are relatively accurate for very thin snow (e.g., a bias of 0.01 for a 2‐cm snowpack). The error, however, becomes larger as snowpack thickens (with biases of up to 0.05 for semi‐infinite snowpack), because the snow radiative transfer is highly nonlinear and is most significant at wavelengths <1 μm. In this study, we propose a novel method to retrieve broadband optical parameters according to snow radiative transfer theory, reducing the albedo biases to <0.003 for 2 cm snowpacks and <0.005 for thick snowpacks. We find little impact in changing incident spectra on narrowband snow albedo. These newly derived narrowband optical parameters improve snow albedo accuracy by a factor of 10, allowing to trace the impacts of aerosol pollution in snow. The parameters are independent of which two‐stream approximation is used, and are thus applicable to sea ice, glaciers, and seasonal snow cover.

Methods of snowmelt calculation in the Antarctic oasis Larsemann Hills

The paper studies the validity of snowmelt calculation methods, which are mostly used in hydrology, for the Larsemann Hills oasis (East Antarctica). The study bases on snow surveys data obtained on catchments of Low Lake, Reid Lake and Stepped Lake during the 65th season of the Russian Antarctic Expedition (RAE) in 2019-2020. Materials of the fond of Arctic and Antarctic Research Institute (AARI) are also used: snow surveys data collected on the catchment of Stepped Lake during the 57th RAE season in 2012 and on catchments of Low Lake, Reid Lake, Scandrett Lake and Stepped Lake during the 62th RAE season in 2017. Considered three methods of snowmelt calculation were derived by Kuz'min P.P., Popov E.G., Vinogradov Yu.B. Results of calculation are compared with snowmelt value obtained according to snow surveys. The paper shows two variants of calculations: in the first albedo of snow is determined from function of snow age as different values for each day, in the second albedo is determined from remote sensing data as average value for all period. Results of snowmelt calculation depend on the method which sets value of snow albedo: relative inaccuracies of results obtained of all discussed methods are smaller when albedo is determined as average value. The equation by Kuz'min P.P. gives the smallest inaccuracies of snowmelt calculation results in relative to real snowmelt values estimated from snow survey data. This snowmelt calculation method in the majority of cases reviewed gives satisfactory results and should be recommended for estimation of snowmelt values for this Antarctic territory.

Estimation of Seasonal Snow Mass Balance all over Japan Using a High-Resolution Atmosphere-Snow Model Chain

Despite the importance of seasonal snow in Japan, quantitative information on seasonal snow mass in the whole area is lacking. To understand the current mass balance of seasonal snow cover, we develop a method to quantify the mass balance of seasonal snow all over Japan using the Japan Meteorological Agency's operational regional atmospheric model, Local Forecast Model (LFM), as well as the snow physics model, Snow Metamorphism and Albedo Process (SMAP). Our model simulations using the LFM-SMAP model chain show that the seasonal snow water equivalent (SWE) evolution is mostly controlled by snowfall and runoff. It is estimated that the seasonal peak area-integrated SWE in Japan reaches 42.2 Gt on average during the 2017-2022 winters, and 60.1 Gt (+43% with respect to the average) and 22.0 Gt (−48%) during relatively heavy (2017-2018) and relatively light (2019-2020) snow years, respectively. The ratios between seasonal peak area-integrated SWE and winter-accumulated (November to February) snowfall amounts for the heavy, average, and light snow years are 83%, 74%, and 59%, respectively.

The underlying green biciliate morphology of the orange snow alga Sanguina aurantia

In the summer, blooms of microalgae appear on alpine and polar snowfields, creating expanses of red snow sometimes called 'watermelon snow'1. These blooms are attracting research attention because they decrease snow albedo, thereby accelerating the effects of global warming on snowmelt2. Currently, meltwater from alpine snowfields provides one-sixth of the world's population with water for drinking, agriculture, and the generation of hydroelectric power3. Each spring, the surface of new snow is colonized by microscopic organisms from unknown sources. One possibility is that when the melt begins, ciliated cells swim up from the substrate below to populate the snow surface. However, Sanguina, a cosmopolitan genus that frequently dominates high-alpine and arctic blooms4,5, are thick-walled, red or orange in colour, and immotile. Here, we describe a culture of motile green biciliate cells isolated from a sample of red snow. Using cross-referenced Bayesian and maximum-likelihood phylogenetic methods for two genetic markers, ITS2 and rbcL, we establish the green biciliate as belonging to the genus Sanguina. Compensatory-base-change analysis of ITS2 rRNA structure delimits the green culture as S. aurantia, conspecific with individual, thick-walled immotile orange cells, picked from field samples collected in British Columbia and Svalbard. Using single cells was invaluable for comparing sequences derived from thick-walled red and orange Sanguina cells, which do not exist in culture, with the cultured green biciliates.

SNICAR-ADv3: a community tool for modeling spectral snow albedo

Abstract. The Snow, Ice, and Aerosol Radiative (SNICAR) model has been used in various capacities over the last 15 years to model the spectral albedo of snow with light-absorbing constituents (LACs). Recent studies have extended the model to include an adding-doubling two-stream solver and representations of non-spherical ice particles; carbon dioxide snow; snow algae; and new types of mineral dust, volcanic ash, and brown carbon. New options also exist for ice refractive indices and solar-zenith-angle-dependent surface spectral irradiances used to derive broadband albedo. The model spectral range was also extended deeper into the ultraviolet for studies of extraterrestrial and high-altitude cryospheric surfaces. Until now, however, these improvements and capabilities have not been merged into a unified code base. Here, we document the formulation and evaluation of the publicly available SNICAR-ADv3 source code, web-based model, and accompanying library of constituent optical properties. The use of non-spherical ice grains, which scatter less strongly into the forward direction, reduces the simulated albedo perturbations from LACs by ∼9 %–31 %, depending on which of the three available non-spherical shapes are applied. The model compares very well against measurements of snow albedo from seven studies, though key properties affecting snow albedo are not fully constrained with measurements, including ice effective grain size of the top sub-millimeter of the snowpack, mixing state of LACs with respect to ice grains, and site-specific LAC optical properties. The new default ice refractive indices produce extremely high pure snow albedo (>0.99) in the blue and ultraviolet part of the spectrum, with such values only measured in Antarctica so far. More work is needed particularly in the representation of snow algae, including experimental verification of how different pigment expressions and algal cell concentrations affect snow albedo. Representations and measurements of the influence of liquid water on spectral snow albedo are also needed.

Impact of dust-cloud-radiation interactions on surface albedo: a case study of ‘Tiramisu’ snow in Urumqi, China

Dust–cloud–surface radiation interactions are a complex nonlinear relation referring to the influences of both atmospheric dust and dust-on-snow on surface albedo. A ‘Tiramisu’ snow event occurred on 1 December 2018, in Urumqi, China, providing an excellent testbed for exploring the comprehensive effect induced by atmospheric dust and those deposited atop fresh snowpack on surface radiation. A detailed analysis indicates that the decrease of snow albedo by 0.17–0.26 (22%–34%) is contributed by the effects both the dust–cloud interactions and dust-on-snow at synoptic scale in this case. In particular, dust well mixed with ice clouds at altitudes of 2.5–5.5 km disrupted the ‘seeder–feeder’ structure of clouds and heterogeneous ice nucleation. Dust-induced changes in the low layer of ice clouds (3.3–5.5 km) under a low temperature of –20 °C resulted in a 31.8% increase in the ice particle radius and 84.6% increase in the ice water path, which acted to indirectly buffer the incident solar radiation reaching the surface. Dust particles deposited on the snow surface further caused snow darkening since the snow albedo was found to decrease by 11.8%–23.3%. These findings underscore the importance of considering the comprehensive effect of dust–cloud–radiation interactions in the future.

A versatile method for computing optimized snow albedo from spectrally fixed radiative variables: VALHALLA v1.0

Abstract. In climate models, the snow albedo scheme generally calculates only a narrowband or broadband albedo, which leads to significant uncertainties. Here, we present the Versatile ALbedo calculation metHod based on spectrALLy fixed radiative vAriables (VALHALLA version 1.0) to optimize spectral snow albedo calculation. For this optimization, the energy absorbed by the snowpack is calculated by the spectral albedo model Two-streAm Radiative TransfEr in Snow (TARTES) and the spectral irradiance model Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART). This calculation takes into account the spectral characteristics of the incident radiation and the optical properties of the snow based on an analytical approximation of the radiative transfer of snow. For this method, 30 wavelengths, called tie points (TPs), and 16 reference irradiance profiles are calculated to incorporate the absorbed energy and the reference irradiance. The absorbed energy is then interpolated for each wavelength between two TPs with adequate kernel functions derived from radiative transfer theory for snow and the atmosphere. We show that the accuracy of the absorbed energy calculation primarily depends on the adaptation of the irradiance of the reference profile to that of the simulation (absolute difference <1 W m−2 for broadband absorbed energy and absolute difference <0.005 for broadband albedo). In addition to the performance in terms of accuracy and calculation time, the method is adaptable to any atmospheric input (broadband, narrowband) and is easily adaptable for integration into a radiative scheme of a global or regional climate model.

Impact of snow‐albedo feedback termination on terrestrial surface climate at midhigh latitudes: Sensitivity experiments with an atmospheric general circulation model

AbstractTo examine the effect of the snow‐albedo feedback (SAF) on the current surface climate across terrestrial regions at mid–high latitudes, we perform a series of idealized sensitivity experiments using an atmospheric general circulation model (AGCM), in which the snow albedo is assumed to be considerably smaller than that in the control experiment. When the snow albedo is reduced, the fall and spring surface air temperatures (SATs) in northern Eurasia are considerably higher than those in the control experiment. Particularly, the spring SAT at terrestrial high latitudes rises by more than 10°C, due to low snow albedo. Despite the small surface snow albedo during both fall and spring, the fall temperature difference between the two experiments is smaller than that during spring. The feedback with the hydrological effect, which accelerates snowmelt, is either nonexistent or weak during periods of seasonally low air temperatures. This result indicates that the hydrological effect significantly influences the SAF, and different magnitudes of the hydrological effect including cloud differences are a possible source of SAF uncertainty between models. The radiative albedo effect also impacts the evolution of the snow area in central Asia and eastern Europe through changes in lateral water vapour transport. Furthermore, the experiments indicate that the cooling effect of snow on land is necessary for the strength of the Siberian High and the pattern of Arctic Oscillation, suggesting that snow cover may also significantly extend the duration of Arctic Oscillation effects.

What Causes the Unobserved Early‐Spring Snowpack Ablation in Convection‐Permitting WRF Modeling Over Utah Mountains?

AbstractAccurate prediction of snowpack evolution and ablation is critical to supporting weather and hydrological applications. Convection‐permitting modeling has been shown to well capture observed snowpack evolution over many western United States (U.S.) mountain ranges, but some significant ablation biases still remain. In this study, we conduct process‐level snowpack analyses of a widely used convection‐permitting (4‐km) weather research and forecasting (WRF) modeling product (WRF4km) for the contiguous U.S. to understand the mechanisms causing its unobserved early‐spring snow ablation over Utah mountains. Analyses across Utah Snowpack Telemetry (SNOTEL) sites show that the unobserved snowpack ablation during mid‐February to late‐March in WRF4km is driven by multiple strong melting events. The melting results from the enhanced downward sensible heat flux to snowpack and enhanced ground solar radiation absorption, with generally larger contributions from the former before early March and from the latter after early March. The enhanced downward sensible heat flux to snowpack is mainly due to the enhanced surface heat exchange coefficient induced by high surface wind speeds. The enhanced ground solar radiation absorption is driven by both enhanced surface downward solar radiation and strong melting‐induced snow cover reduction that is caused by deficiencies in Noah‐MP snow‐related parameterizations used in WRF4km. The substantial snow cover reduction during melting decreases surface albedo and hence triggers a positive albedo feedback that further accelerates melting. Our analyses reveal possible deficiencies in WRF and Noah‐MP (e.g., canopy processes and snow albedo) and shed light on future directions for model improvements.

Scripts and data used to generate all plots published in "SNICAR-AD v3: A Community Tool for Modeling Spectral Snow Albedo"

Scripts and data used to generate all plots published in "SNICAR-AD v3: A Community Tool for Modeling Spectral Snow Albedo"

Warming amplification with both altitude and latitude in the Tibetan Plateau

AbstractMany studies have examined elevation‐dependent warming in mountain regions of the world, yet little attempt has been undertaken to examine the relationship of the observed warming with both altitude and latitude on a regional scale. Here, based on the mean temperature series (1961–2015) of 105 stations in the Tibetan Plateau, the signals of warming amplification with these two factors are quantified using four groups of methods. The results, highly consistent for the different methods, confirm that the warming for the Tibetan Plateau is not only elevation‐dependent, but also latitude‐dependent, and the magnitude of altitudinal amplification trend is two orders of magnitude larger than that of latitudinal amplification trend on the annual and seasonal scales over the period 1961–2015. The annual warming is amplified by 0.066°C 10 year−1·km−1 of altitude and 0.016 × 10−2°C 10 year−1·km−1 of latitude (or 0.018°C 10 year−1·degree−1 of latitude), with the highest altitudinal (latitudinal) amplification in winter (autumn), followed by autumn (winter) and the lowest in spring and summer. Meanwhile, the estimates of altitude and latitude components of the regional warming shows that the contribution of latitude to the regional warming is larger than that of altitude on the annual scale and for all seasons excepting summer, due primarily to the much larger range of latitude than the range of altitude covered by all the stations used. Moreover, analysis of the number of snow cover days demonstrates that the snow albedo feedback has played a significant role in enhancing the warming in the Tibetan Plateau during the recent sub‐period 1996–2015, due to the decrease of snow cover days in the spring, autumn and winter seasons. These results highlight an integrated picture of Tibetan Plateau warming amplification, and a clear snow albedo feedback effect on the regional amplification, allowing better investigation of impacts and mechanisms.

Retrieval of Snow Albedo and Total Ozone Column from Single-View MSI/S-2 Spectral Reflectance Measurements over Antarctica

We proposed a simple algorithm to retrieve the total ozone column and snow properties (spectral albedo and effective light absorption path) using the high spatial resolution single–view MSI/S-2 measurements over Antarctica. In addition, the algorithm allows the retrieval of the snow grain size on a scale of 10–20 m. This algorithm should be useful for the understanding of intra-pixel total ozone and snow albedo variability in complement to satellite observations performed on a much coarser spatial resolution scale (0.3–1 km and even larger spatial scales).

Influence of aerosol radiative effects on surface temperature and snow melt in the Himalayan region

Recent increases in surface temperature and snow melt acceleration in the Himalayan region are influenced by many factors. Here we investigate the influence of absorbing aerosols, including black carbon and dust, on surface temperature and snow melt in western, central, and eastern parts of the India-Nepal Himalayan region (INHR). We compare 40-y simulations (1971–2010) one with all evolving forcing agents representative of a present-day aerosol scenario, compared to a low aerosol forcing scenario. The difference between these scenarios shows a significant increase in surface air temperature, with higher warming in parts of Western and Central Himalaya (~0.2–2 °C) in the months of April and May. Higher absorbing aerosol (BC and dust abundance) both at the surface and in the atmospheric column, in the present-day aerosol simulations, led to increases in atmospheric radiative forcing and surface shortwave heating rate forcing (SWHRF), compared to the low aerosol forcing case. Therefore, the absorbing aerosols cause anomalous atmospheric heat energy transfer to land due to high surface SWHRF and changes in surface energy flux, leading to snow melt. The present model version did not parameterize snow albedo feedback, which would increase the magnitudes of the changes simulated here.

Recent strengthening of snow and ice albedo feedback driven by Antarctic sea-ice loss

The decline of the Arctic cryosphere during recent decades has lowered the region’s surface albedo, reducing its ability to reflect solar radiation back to space. It is not clear what role the Antarctic cryosphere plays in this regard, but new remote-sensing-based techniques and datasets have recently opened the possibility to investigate its role. Here, we leverage these to show that the surface albedo reductions from sustained post-2000 losses in Arctic snow and ice cover equate to increasingly positive snow and ice albedo feedback relative to a 1982–1991 baseline period, with a decadal trend of +0.08 ± 0.04 W m–2 decade–1 between 1992 and 2015. During the same period, the expansion of the Antarctic sea-ice pack generated a negative feedback, with a decadal trend of −0.06 ± 0.02 W m–2 decade–1. However, substantial Antarctic sea-ice losses during 2016–2018 completely reversed the trend, increasing the three-year mean combined Arctic and Antarctic snow and ice albedo feedback to +0.26 ± 0.15 W m–2. This reversal highlights the importance of Antarctic sea-ice loss to the global snow and ice albedo feedback. The 1992–2018 mean feedback is equivalent to approximately 10% of anthropogenic CO2 emissions over the same period; the share may rise markedly should 2016–2018 snow and ice conditions become common, although increasing long-wave emissions will probably mediate the impact on the total radiative-energy budget. Recent strengthening of the snow/ice albedo feedback is due to Antarctic sea-ice loss, according to satellite observations of surface albedo.

The influence of forest fire aerosol and air temperature on glacier albedo, western North America

Over the past decade, western North America glaciers experienced strong mass loss. Regional mass loss during the ablation season is influenced by air temperature, but the importance of other factors such as changes in surface albedo remains uncertain. We examine changes in surface albedo for 17 glaciated regions of western North America as documented in a 20-year record (2000 to 2019) of MODIS daily snow albedo (MOD10A1). Trend analysis reveals that albedo declined for 4% to 81% of the albedo grid cells, and the largest negative trends were situated south of 60°N and in the provinces of British Columbia and Alberta. Sen's slope estimates indicate that 15 of 17 regions showed a decline of which the majority of the largest declines occurred within 100 m of glacier median elevation, suggesting that these declines are driven by a rise of the transient snowline. For most regions, albedo correlates strongly to temperature, and albedo trend in the Chugach region of Alaska, the South Coast, Southern Interior and Central and Southern Rockies of Canada show a significant relationship to aerosols optical depth. Temperature is approximately 2–6 times more predictive of the variation in albedo than AOD for the majority of regions, except the Southern Interior and Southern Rockies where albedo shows a greater dependence on AOD. Investigation of broadband albedo (MCD43A3) for snow grid cells above glacier median elevation in the Central and Southern Rockies shows that declines in the visible and near infrared portions of the spectrum are linked to the presence of forest fire generated aerosols. The results of this study indicate that glacier surface mass balance experiences a regional dependence on forest fire generated light absorbing particles.

Strengthened Impacts of November Snow Cover Over Siberia on the Out-of-phase Change in the Siberian High Between December and January Since 2000 and Implication for Intraseasonal Climate Prediction

This study investigates the out-of-phase change in the Siberian High (SH) between December and January (stronger than normal in December and weaker than normal in January, and vice versa). The results show that the monthly reversal frequency of the SH between December and January increases significantly after 2000 from 30% (1981–2000) to 63% (2001-2019). Correspondingly, the influence of November snow cover over Siberia on the phase reversal of the SH has intensified after 2000. The reasons may be as follows. Higher snow depth over Siberia (SSD) in November corresponds to stronger diabatic cooling and increased snow accumulation over Siberia in November and December, which may strengthen the SH in December via the positive feedback of snow albedo. The dynamic mechanisms between the higher SSD in November and weaker SH in January are further investigated from the perspective of troposphere–stratosphere interaction. Such anomalously higher SSD with strong upward heat flux induces the upward-propagating wave activity flux in November and December over the Urals and Siberia, leading to a weaker and warmer stratospheric polar vortex in January. Subsequently, the anomalies of the stratospheric polar vortex signal propagate downwards, giving rise to a negative Arctic Oscillation–like structure in the troposphere and a weakening of the SH in January. This mechanism can be partly reproduced in CMIP6. Additionally, the variability of the September–October Arctic sea ice mainly leads to coherent variations of the SH in December and January via the eddy–mean flow interaction before 2000. Furthermore, the preceding November snow cover over Siberia enhances the intraseasonal prediction skill for the winter SH after 2000. Meanwhile, considering the previous November SSD, the prediction accuracy for the out-of-phase change in the SH between December and January increases from 16% (outputs of the NCEP’s Climate Forecast System, version 2) to 75%.

Black carbon and mineral dust in snow cover across a typical city of Northeast China

Light-absorbing impurities (LAIs), including black carbon (BC) and mineral dust (MD), in snow cover reduce snow albedo and accelerate the snow melting rate, thus influencing the regional water resources, ecological environmental security, and climate change. There is still a lack of quantitative assessments of the impacts of BC and MD on snowmelt in urban areas. This study was conducted from December 2018 to March 2019. A total of 120 snow samples were collected in Harbin, Northeast China to quantitatively assess the concentration characteristics of BC and MD in snow cover in different urban polluted areas and the impacts on snow albedo, radiative forcing, and snow melting. Average concentrations of BC and MD in snow cover in Harbin were 126,121.03 ng g−1 and 1419.6 μg g−1, respectively. Average concentrations of BC and MD in the industrial area were the highest, which were 4.06 and 3.13 times higher, respectively, than those in the suburban area. BC or MD decreased the average snow albedo by 0.3677 (58.49%) and 0.0583 (18.18%) with radiative forcing of 44.94 W m−2 and 7.58 W m−2, respectively. BC and MD in the industrial area, residential area, and suburban area decreased the average albedo by 0.449 (59.55%), 0.3758 (45.86%), and 0.2959 (37.65%), respectively. The impacts on snow melting time in Harbin were mainly attributed to BC, which advanced snow melting by 7.9 ± 1.16 d, while MD advanced snow melting by 3.7 ± 0.9 d. Under the combined effect of BC and MD, the industrial area, residential area, and suburban area in the city experienced advanced snow melting by 9.66 ± 0.38 d, 7.97 ± 0.31 d, and 6.67 ± 0.65 d, respectively. The results can be used to assess the contribution of intense human disturbance to snow melting.