scholarly journals Impact of light-absorbing particles on snow albedo darkening and associated radiative forcing over high-mountain Asia: high-resolution WRF-Chem modeling and new satellite observations

2019 ◽  
Vol 19 (10) ◽  
pp. 7105-7128 ◽  
Author(s):  
Chandan Sarangi ◽  
Yun Qian ◽  
Karl Rittger ◽  
Kathryn J. Bormann ◽  
Ying Liu ◽  
...  
Keyword(s):  
Grain Size ◽  
Snow Cover ◽  
Spatial Resolution ◽  
Radiative Forcing ◽  
High Mountain ◽  
Western Himalayas ◽  
Snow Albedo ◽  
Microphysical Properties ◽  
Snow Properties ◽  
The Impact

Abstract. Light-absorbing particles (LAPs), mainly dust and black carbon, can significantly impact snowmelt and regional water availability over high-mountain Asia (HMA). In this study, for the first time, online aerosol–snow interactions are enabled and a fully coupled chemistry Weather Research and Forecasting (WRF-Chem) regional model is used to simulate LAP-induced radiative forcing on snow surfaces in HMA at relatively high spatial resolution (12 km, WRF-HR) compared with previous studies. Simulated macro- and microphysical properties of the snowpack and LAP-induced snow darkening are evaluated against new spatially and temporally complete datasets of snow-covered area, grain size, and impurity-induced albedo reduction over HMA. A WRF-Chem quasi-global simulation with the same configuration as WRF-HR but a coarser spatial resolution (1∘, WRF-CR) is also used to illustrate the impact of spatial resolution on simulations of snow properties and aerosol distribution over HMA. Due to a more realistic representation of terrain slopes over HMA, the higher-resolution model (WRF-HR) shows significantly better performance in simulating snow area cover, duration of snow cover, snow albedo and snow grain size over HMA, as well as an evidently better atmospheric aerosol loading and mean LAP concentration in snow. However, the differences in albedo reduction from model and satellite retrievals is large during winter due to associated overestimation in simulated snow fraction. It is noteworthy that Himalayan snow cover has high magnitudes of LAP-induced snow albedo reduction (4 %–8 %) in pre-monsoon seasons (both from WRF-HR and satellite estimates), which induces a snow-mediated radiative forcing of ∼30–50 W m−2. As a result, the Himalayas (specifically the western Himalayas) hold the most vulnerable glaciers and mountain snowpack to the LAP-induced snow darkening effect within HMA. In summary, coarse spatial resolution and absence of snow–aerosol interactions over the Himalayan cryosphere will result in significant underestimation of aerosol effects on snow melting and regional hydroclimate.

scholarly journals Impact of light-absorbing particles on snow albedo darkening and associated radiative forcing over High Mountain Asia: High resolution WRF-Chem modeling and new satellite observations

2018 ◽  
Author(s):  
Chandan Sarangi ◽  
Yun Qian ◽  
Karl Rittger ◽  
Kat J. Bormann ◽  
Ying Liu ◽  
...  
Keyword(s):  
Grain Size ◽  
Snow Cover ◽  
Spatial Resolution ◽  
Radiative Forcing ◽  
High Mountain ◽  
Western Himalayas ◽  
Snow Albedo ◽  
Snow Properties ◽  
Realistic Representation ◽  
The Impact

Abstract. Light-absorbing particles (LAPs), mainly dust and black carbon, can significantly impact snowmelt and regional water availability over High Mountain Asia (HMA). In this study, for the first time, online aerosol-snow interactions enabled and a fully coupled chemistry Weather Research and Forecasting (WRF-Chem) regional model is used to simulate LAP-induced radiative forcing on snow surfaces in HMA at relatively high spatial resolution (12 km, WRF-HR) than previous studies. Simulated macro- and micro-physical properties of the snowpack and LAP-induced snow darkening are evaluated against new spatially and temporally complete datasets of snow covered area, grain size, and impurities-induced albedo reduction over HMA. A WRF-Chem quasi-global simulation with the same configuration as WRF-HR but a coarser spatial resolution (1 degree, WRF-CR) is also used to illustrate the impact of spatial resolution on simulations of snow properties and aerosol distribution over HMA. Due to a more realistic representation of terrain slopes over HMA, the higher resolution model (WRF-HR) shows significantly better performance in simulating snow area cover, duration of snow cover, snow albedo and snow grain size over HMA, as well as an evidently better atmospheric aerosol loading and mean LAPs concentration in snow. However, the differences in albedo reduction from model and satellite retrievals is large during winter due to associated overestimation in simulated snow fraction. It is noteworthy that Himalayan snow cover have high magnitudes of LAP-induced snow albedo reduction (4–8 %) in summer (both from WRF-HR and satellite estimates), which, induces a snow-mediated radiative forcing of ∼ 30–50 W/m2. As a result, Himalayas (specifically western Himalayas) hold the most vulnerable glaciers and mountain snowpack to the LAP-induced snow darkening effect within HMA. In summary, coarse spatial resolution and absence of snow-aerosol interactions over Himalaya cryosphere will result in significant underestimation of aerosol effect on snow melting and regional hydroclimate.

scholarly journals Case study of spatial and temporal variability of snow cover, grain size, albedo and radiative forcing in the Sierra Nevada and Rocky Mountain snowpack derived from imaging spectroscopy

2016 ◽  
Vol 10 (3) ◽  
pp. 1229-1244 ◽  
Author(s):  
Felix C. Seidel ◽  
Karl Rittger ◽  
S. McKenzie Skiles ◽  
Noah P. Molotch ◽  
Thomas H. Painter
Keyword(s):  
Grain Size ◽  
Spatial Variability ◽  
Snow Cover ◽  
Sierra Nevada ◽  
Rocky Mountains ◽  
Radiative Forcing ◽  
Infrared Imaging ◽  
Spatial And Temporal Variability ◽  
Snow Albedo ◽  
The Mean

Abstract. Quantifying the spatial distribution and temporal change in mountain snow cover, microphysical and optical properties is important to improve our understanding of the local energy balance and the related snowmelt and hydrological processes. In this paper, we analyze changes of snow cover, optical-equivalent snow grain size (radius), snow albedo and radiative forcing by light-absorbing impurities in snow and ice (LAISI) with respect to terrain elevation and aspect at multiple dates during the snowmelt period. These snow properties are derived from the NASA/JPL Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data from 2009 in California's Sierra Nevada and from 2011 in Colorado's Rocky Mountains, USA. Our results show a linearly decreasing snow cover during the ablation period in May and June in the Rocky Mountains and a snowfall-driven change in snow cover in the Sierra Nevada between February and May. At the same time, the snow grain size is increasing primarily at higher elevations and north-facing slopes from 200 microns to 800 microns on average. We find that intense snowmelt renders the mean grain size almost invariant with respect to elevation and aspect. Our results confirm the inverse relationship between snow albedo and grain size, as well as between snow albedo and radiative forcing by LAISI. At both study sites, the mean snow albedo value decreases from approximately 0.7 to 0.5 during the ablation period. The mean snow grain size increased from approximately 150 to 650 microns. The mean radiative forcing increases from 20 W m−2 up to 200 W m−2 during the ablation period. The variability of snow albedo and grain size decreases in general with the progression of the ablation period. The spatial variability of the snow albedo and grain size decreases through the melt season while the spatial variability of radiative forcing remains constant.

scholarly journals Case study of spatial and temporal variability of snow cover, grain size, albedo and radiative forcing in the Sierra Nevada and Rocky Mountain snowpack derived from imaging spectroscopy

2016 ◽  
Author(s):  
F. C. Seidel ◽  
K. Rittger ◽  
S. M. Skiles ◽  
T. H. Painter
Keyword(s):  
Grain Size ◽  
Spatial Variability ◽  
Snow Cover ◽  
Sierra Nevada ◽  
Rocky Mountains ◽  
Radiative Forcing ◽  
Infrared Imaging ◽  
Spatial And Temporal Variability ◽  
Snow Albedo ◽  
The Mean

Abstract. Quantifying the spatial distribution and temporal change in mountain snow cover, microphysical and optical properties is important to improve our understanding of the local energy balance and the related snowmelt and hydrological processes. In this paper, we analyze changes of snow cover, optical-equivalent snow grain size, snow albedo, and radiative forcing by Light Absorbing Impurities in Snow and Ice (LAISI) with respect to terrain elevation and aspect at multiple dates during the snowmelt period. These snow properties are derived from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data from 2009 of the maritime snowpack in California’s Sierra Nevada and from 2011 of the continental snowpack in Colorado’s Rocky Mountains, USA. Our results show a linearly decreasing snow cover during the ablation season in the Rocky Mountains and a snowfall driven change in snow cover in the Sierra Nevada. At the same time, the snow grain size is increasing primarily at higher elevations and north facing slopes from 200 microns to 800 microns on average. We find that intense snowmelt renders the mean grain size almost invariant with respect to elevation and aspect. Our results confirm the inverse relationship between snow albedo and grain size, as well as between snow albedo and radiative forcing by LAISI. At both study sites, the mean snow albedo value decreases from approximately 0.7 to 0.5. The mean snow grain size increased from approximately 150 to 650 microns. The mean radiative forcing increases from 20 W m−2 up to 200 W m−2 during the ablation period. The variability of snow albedo and grain size decreases in general with the progression of the ablation period. The spatial variability of the snow albedo and grain size decreases through the melt season while the spatial variability of radiative forcing remains constant.

scholarly journals Observing Snow Cover and Water Resource Changes in the High Mountain Asia Region in Comparison with Global Mountain Trends over 2000–2018

2020 ◽  
Vol 12 (23) ◽  
pp. 3913
Author(s):  
Claudia Notarnicola
Keyword(s):  
Water Resources ◽  
Confidence Interval ◽  
Snow Cover ◽  
Water Storage ◽  
High Mountain ◽  
Global Level ◽  
Total Water ◽  
Mountain Areas ◽  
Snow Cover Extent ◽  
The Impact

The quantification of snow cover changes and of the related water resources in mountain areas has a key role for understanding the impact on several sectors such as ecosystem services, tourism and energy production. By using NASA-Moderate Resolution Imaging Spectroradiometer (MODIS) images from 2000 to 2018, this study analyzes changes in snow cover in the High Mountain Asia region and compares them with global mountain areas. Globally, snow cover extent and duration are declining with significant trends in around 78% of mountain areas, and the High Mountain Asia region follows similar trends in around 86% of the areas. As an example, Shaluli Shan area in China shows significant negative trends for both snow cover extent and duration, with −11.4% (confidence interval: −17.7%, −5.5%) and −47.3 days (confidence interval: −70.4 days, −24.4 days) at elevations >5500 m a.s.l. respectively. In spring, an earlier snowmelt of −13.5 days (confidence interval: −24.3 days, −2.0 days) in 4000–5500 m a.s.l. is detected. On the other side, Tien Shan area shows an earlier snow onset of −28.8 days (confidence interval: −44.3 days, −8.2 days) between 2500 and 4000 m a.s.l., governed by decreasing temperature and increasing snowfall. In the current analysis, the Tibetan Plateau shows no significant changes. Regarding water resources, by using Gravity Recovery and Climate Experiment (GRACE) data it was found that around 50% of areas in the High Mountain Asia region and 30% at global level are suffering from significant negative temporal trends of total water storage (including groundwater, soil moisture, surface water, snow, and ice) in the period 2002–2015. In the High Mountain Asia region, this negative trend involves around 54% of the areas during spring period, while at a global level this percentage lies between 25% and 30% for all seasons. Positive trends for water storage are detected in a maximum 10% of the areas in High Mountain Asia region and in around 20% of the areas at global level. Overall snow mass changes determine a significant contribution to the total water storage changes up to 30% of the areas in winter and spring time over 2002–2015.

scholarly journals Light-absorbing impurities in snow cover across Northern Xinjiang, China

2019 ◽  
Vol 65 (254) ◽  
pp. 940-956 ◽  
Author(s):  
Xinyue Zhong ◽  
Shichang Kang ◽  
Wei Zhang ◽  
Junhua Yang ◽  
Xiaofei Li ◽  
...  
Keyword(s):  
Snow Cover ◽  
Radiative Forcing ◽  
Dominant Factor ◽  
Weather Research And Forecasting ◽  
Ecological Security ◽  
Snow Albedo ◽  
Northern Xinjiang ◽  
Snow Cover Duration ◽  
Average Contribution ◽  
Semi Arid

AbstractLight-absorbing impurities (LAIs, e.g. black carbon (BC), organic carbon (OC), mineral dust (MD)) deposited on snow cover reduce albedo and accelerate its melting. Northern Xinjiang (NX) is an arid and semi-arid inland region, where snowmelt leads to frequent floods that have been a serious threat to local ecological security. There is still a lack of quantitative assessments of the effects of LAIs on snowmelt in the region. This study investigates spatial variations of LAIs in snow and its effect on snow albedo, radiative forcing (RF) and snowmelt across NX. Results showed that concentrations of BC, OC (only water-insoluble OC), MD ranged from 32 to 8841 ng g−1, 77 to 8568 ng g−1 and 0.46 to 236 µg g−1, respectively. Weather Research and Forecasting Chemistry model suggested that residential emission was the largest source of BC. Snow, Ice, and Aerosol Radiative modelling showed that the average contribution of BC and MD to snow albedo reduction was 17 and 3%, respectively. RF caused by BC significantly exceeded RF caused by MD. In different scenarios, changes in snow cover duration (SCD) caused by BC and MD decreased by 1.36 ± 0.61 to 6.12 ± 3.38 d. Compared with MD, BC was the main dominant factor in reducing snow albedo and SCD across NX.

scholarly journals Hindcasting and forecasting of regional methane from coal mine emissions in the Upper Silesian Coal Basin using the online nested global regional chemistry–climate model MECO(n) (MESSy v2.53)

2020 ◽  
Vol 13 (4) ◽  
pp. 1925-1943 ◽  
Author(s):  
Anna-Leah Nickl ◽  
Mariano Mertens ◽  
Anke Roiger ◽  
Andreas Fix ◽  
Axel Amediek ◽  
...  
Keyword(s):  
Coal Mining ◽  
Spatial Resolution ◽  
Radiative Forcing ◽  
Climate Model ◽  
Mitigation Strategies ◽  
Climate Mitigation ◽  
Coal Basin ◽  
Airborne Measurements ◽  
Upper Silesian Coal Basin ◽  
The Impact

Abstract. Methane is the second most important greenhouse gas in terms of anthropogenic radiative forcing. Since pre-industrial times, the globally averaged dry mole fraction of methane in the atmosphere has increased considerably. Emissions from coal mining are one of the primary anthropogenic methane sources. However, our knowledge about different sources and sinks of methane is still subject to great uncertainties. Comprehensive measurement campaigns and reliable chemistry–climate models, are required to fully understand the global methane budget and to further develop future climate mitigation strategies. The CoMet 1.0 campaign (May to June 2018) combined airborne in situ, as well as passive and active remote sensing measurements to quantify the emissions from coal mining in the Upper Silesian Coal Basin (USCB, Poland). Roughly 502 kt of methane is emitted from the ventilation shafts per year. In order to help with the flight planning during the campaigns, we performed 6 d forecasts using the online coupled, three-time nested global and regional chemistry–climate model MECO(n). We applied three-nested COSMO/MESSy instances going down to a spatial resolution of 2.8 km over the USCB. The nested global–regional model system allows for the separation of local emission contributions from fluctuations in the background methane. Here, we introduce the forecast set-up and assess the impact of the model's spatial resolution on the simulation of methane plumes from the ventilation shafts. Uncertainties in simulated methane mixing ratios are estimated by comparing different airborne measurements to the simulations. Results show that MECO(3) is able to simulate the observed methane plumes and the large-scale patterns (including vertically integrated values) reasonably well. Furthermore, we obtain reasonable forecast results up to forecast day four.

scholarly journals Snow depths and grain-size relationships with relevance for passive microwave studies

1993 ◽  
Vol 17 ◽  
pp. 171-176 ◽  
Author(s):  
Richard L. Armstrong ◽  
Alfred Chang ◽  
Albert Rango ◽  
Edward Josberger
Keyword(s):  
Grain Size ◽  
Snow Cover ◽  
Regional Scale ◽  
Passive Microwave ◽  
Microwave Radiometry ◽  
Grain Sizes ◽  
Snow Properties ◽  
Average Grain Size ◽  
Retrieval Algorithms ◽  
Passive Microwave Radiometry

The application of passive microwave radiometry to the remote sensing of snow properties is based on the ratio of emitted to scattered portions of the upwelling radiation. Increased scattering is indicative of increased snow amount, i.e. the number of snow grains present. However, scattering is also directly proportional to snow grain-size for a given snow amount. Current snow cover retrieval algorithms produce inaccurate results when snow grain-sizes are unusually large. Therefore, it is necessary to characterize snow grain-size on a regional scale (and perhaps local scale in extreme situations) in order to adjust passive microwave algorithms. Preliminary analysis indicates that: (1) algorithms are not as sensitive to the presence of large grain-sizes as the initial theory had indicated; (2) standard deviation of grain-size diameters throughout the total snow cover may often be less than 0.5 mm, thus average grain-size data may often serve to characterize the detailed stratigraphy of the total snow cover; (3) conditions in subfreezing snow which produce grain-sizes that greatly exceed a mean diameter value of 1–2 mm result from snow cover/climate relationships which can be modelled/monitored on a regional scale. A preliminary method is investigated for selecting snow retrieval algorithms according to prevailing regional-scale grain-size.

scholarly journals Snow albedo sensitivity to macroscopic surface roughness using a new ray tracing model

2019 ◽  
Author(s):  
Fanny Larue ◽  
Ghislain Picard ◽  
Laurent Arnaud ◽  
Inès Ollivier ◽  
Clément Delcourt ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Smooth Surface ◽  
Incident Angle ◽  
The Sun ◽  
Multiple Reflections ◽  
Snow Albedo ◽  
Snow Properties ◽  
Angle Effect ◽  
Effective Angle ◽  
The Impact

Abstract. Most models simulating snow albedo assume a flat and smooth surface, neglecting surface roughness. However, the presence of macroscopic roughness leads to a systematic decrease in albedo due to two effects: 1) photons are trapped in concavities (multiple reflection effect) and, 2) when the sun is low, the roughness sides facing the sun experience an overall decrease in the local incident angle relative to a smooth surface, promoting higher absorption, whilst the other sides has weak contributions because of the increased incident angle or because they are shadowed (called the effective angle effect here). This paper aims to quantify the impact of surface roughness on albedo and to assess the respective role of these two effects, with 1) observations over varying amounts of surface roughness, and 2) simulations using the new Rough Surface Ray Tracer (RSRT) model, based on a Monte Carlo method for photon transport calculation. The observations include spectral albedo (400–1050 nm) over manually-created roughness surfaces with multiple geometrical characteristics. Measurements highlight that even a low fraction of surface roughness features (7 % of the surface) causes an albedo decrease of 0.02 at 1000 nm when the solar zenith angle (Өs) is larger than 50°. For higher fractions (13 %, 27 % and 63 %), and when the roughness orientation is perpendicular to the sun, the decrease is of 0.03–0.04 at 700 nm and of 0.06–0.10 at 1000 nm. The impact is 20 % lower when roughness orientation is parallel to the sun. The observations are subsequently compared to RSRT simulations. Accounting for surface roughness improves the model observation agreement by a factor two at 700 nm and 1000 nm (errors of 0.03 and 0.04, respectively), compared to simulations considering a flat smooth surface. The model is used to explore the albedo sensitivity to surface roughness with varying snow properties and illumination conditions. Both multiple reflections and the effective angle effect have more impact with low SSA (

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

2021 ◽  
Vol 13 (21) ◽  
pp. 4404
Author(s):  
Alexander Kokhanovsky ◽  
Simon Gascoin ◽  
Laurent Arnaud ◽  
Ghislain Picard
Keyword(s):  
Spatial Resolution ◽  
Total Ozone ◽  
Spatial Scales ◽  
Simple Algorithm ◽  
Snow Albedo ◽  
Single View ◽  
Total Ozone Column ◽  
Snow Properties ◽  
Resolution Single ◽  
Ozone Column

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).

scholarly journals Measurements and modeling of snow albedo at Alerce Glacier, Argentina: effects of volcanic ash, snow grain size, and cloudiness

2020 ◽  
Vol 14 (12) ◽  
pp. 4581-4601
Author(s):  
Julián Gelman Constantin ◽  
Lucas Ruiz ◽  
Gustavo Villarosa ◽  
Valeria Outes ◽  
Facundo N. Bajano ◽  
...  
Keyword(s):  
Grain Size ◽  
Mass Balance ◽  
Volcanic Ash ◽  
Impurity Content ◽  
Field Measurements ◽  
Glacier Mass Balance ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
Snow Albedo ◽  
The Impact

Abstract. The impact of volcanic ash on seasonal snow and glacier mass balance has been much less studied than that of carbonaceous particles and mineral dust. We present here the first field measurements on the Argentinian Andes, combined with snow albedo and glacier mass balance modeling. Measured impurity content (1.1 mg kg−1 to 30 000 mg kg−1) varied abruptly in snow pits and snow and firn cores, due to high surface enrichment during the ablation season and possibly local or regional wind-driven resuspension and redeposition of dust and volcanic ash. In addition, we observed high spatial heterogeneity, due to glacier topography and the prevailing wind direction. Microscopic characterization showed that the major component was ash from recent Calbuco (2015) and Cordón Caulle (2011) volcanic eruptions, with a minor presence of mineral dust and black carbon. We also found a wide range of measured snow albedo (0.26 to 0.81), which reflected mainly the impurity content and the snow and firn grain size (due to aging). We updated the SNow, ICe, and Aerosol Radiation (SNICAR) albedo model to account for the effect of cloudiness on incident radiation spectra, improving the match of modeled and measured values. We also ran sensitivity studies considering the uncertainty in the main measured parameters (impurity content and composition, snow grain size, layer thickness, etc.) to identify the field measurements that should be improved to facilitate the validation of the snow albedo model. Finally, we studied the impact of these albedo reductions on Alerce Glacier using a spatially distributed surface mass balance model. We found a large impact of albedo changes on glacier mass balance, and we estimated that the effect of observed ash concentrations can be as high as a 1.25 m water equivalent decrease in the annual surface mass balance (due to a 34 % increase in the melt during the ablation season).

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