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Keywords = snow darkening

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23 pages, 8885 KiB  
Article
Development of a New Analytical Method for the Characterization and Quantification of the Organic and Inorganic Carbonaceous Fractions in Snow Samples Using TOC and TOT Analysis
by Mattia Borelli, Andrea Bergomi, Valeria Comite, Vittoria Guglielmi, Chiara Andrea Lombardi, Stefania Gilardoni, Biagio Di Mauro, Marina Lasagni and Paola Fermo
Atmosphere 2023, 14(2), 371; https://doi.org/10.3390/atmos14020371 - 13 Feb 2023
Cited by 3 | Viewed by 1641
Abstract
Different Light-Absorbing Snow Impurities (LASI) can deposit on snow- and ice-covered surfaces. These particles are able to decrease snow and ice albedo and trigger positive albedo feedback. The aim of this work was to develop a new method to quantify the carbonaceous fractions [...] Read more.
Different Light-Absorbing Snow Impurities (LASI) can deposit on snow- and ice-covered surfaces. These particles are able to decrease snow and ice albedo and trigger positive albedo feedback. The aim of this work was to develop a new method to quantify the carbonaceous fractions that are present in snow and ice samples that contribute significantly to their darkening. Currently, in the literature, there is an absence of a unified and accepted method to perform these studies. To set up the method proposed here, snow samples were collected at two Italian locations, Claviere and Val di Pejo (Northern Italy). The samples were analyzed using two main techniques, Total Organic Carbon analysis (TOC analysis) and Thermal Optical analysis in Transmittance mode (TOT), which enabled the speciation of the carbonaceous fraction into organic (OC), inorganic (IC), and elemental carbon (EC), and further into the soluble and insoluble parts. The results highlighted a correlation between the nature of the sample (i.e., location, age, and exposure of the snow) and the experimental results, giving validity to the method. For example, the abundant presence of terrigenous constituents was reflected in high amounts of insoluble IC. Moreover, due to the trend between insoluble IC and Elemental Carbon (EC), the role of IC in TOT analysis was investigated. Indeed, IC turned out to be an interfering agent, suggesting that the two techniques (TOC analysis and TOT) are complementary and therefore need to be used in parallel when performing these studies. Finally, the results obtained indicate that the newly proposed method is suitable for studying the carbonaceous fractions in snow samples. Full article
(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)
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17 pages, 2564 KiB  
Article
Forest Fire Effects on Landscape Snow Albedo Recovery and Decay
by Max Gersh, Kelly E. Gleason and Anton Surunis
Remote Sens. 2022, 14(16), 4079; https://doi.org/10.3390/rs14164079 - 20 Aug 2022
Cited by 6 | Viewed by 2111
Abstract
Surface snow albedo (SSA) darkens immediately following a forest fire, while landscape snow albedo (LSA) brightens as more of the snow-covered surface becomes visible under the charred canopy. The duration and variability of the post-fire snow albedo recovery process remain unknown beyond a [...] Read more.
Surface snow albedo (SSA) darkens immediately following a forest fire, while landscape snow albedo (LSA) brightens as more of the snow-covered surface becomes visible under the charred canopy. The duration and variability of the post-fire snow albedo recovery process remain unknown beyond a few years following the fire. We evaluated the temporal variability of post-fire snow albedo recovery relative to burn severity across a chronosequence of eight burned forests burned from 2000 to 2019, using pre- and post-fire daily, seasonal, and annual landscape snow albedo data derived from the Moderate Resolution Imaging Spectroradiometer (MOD10A1). Post-fire annual LSA increased by 21% the first year following the fire and increased continually by 33% on average across all eight forest fires and burn severity classifications over the period of record (18 years following a fire). Post-fire LSA measurements increased by 63% and 53% in high and moderate burn severity areas over ten years following fire. While minimum and maximum snow albedo values increased relative to annual post-fire LSA recovery, daily snow albedo decay following fresh snowfall accelerated following forest fire during the snowmelt period. Snow albedo recovery over 10 years following fire did not resemble the antecedent pre-fire unburned forest but more resembled open meadows. The degradation of forest canopy structure is the key driver underlying the paradox of the post-fire snow albedo change (SSA vs. LSA). Full article
(This article belongs to the Special Issue Remote Sensing for Mountain Vegetation and Snow Cover)
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16 pages, 3366 KiB  
Article
Sampling, Filtering, and Analysis Protocols to Detect Black Carbon, Organic Carbon, and Total Carbon in Seasonal Surface Snow in an Urban Background and Arctic Finland (>60° N)
by Outi Meinander, Enna Heikkinen, Minna Aurela and Antti Hyvärinen
Atmosphere 2020, 11(9), 923; https://doi.org/10.3390/atmos11090923 - 29 Aug 2020
Cited by 11 | Viewed by 4210
Abstract
Black carbon (BC), organic carbon (OC), and total carbon (TC) in snow are important for their climatic and cryospheric effects. They are also part of the global carbon cycle. Atmospheric black and organic carbon (including brown carbon) may deposit and darken snow surfaces. [...] Read more.
Black carbon (BC), organic carbon (OC), and total carbon (TC) in snow are important for their climatic and cryospheric effects. They are also part of the global carbon cycle. Atmospheric black and organic carbon (including brown carbon) may deposit and darken snow surfaces. Currently, there are no standardized methods for sampling, filtering, and analysis protocols to detect carbon in snow. Here, we describe our current methods and protocols to detect carbon in seasonal snow using the OCEC thermal optical method, a European standard for atmospheric elemental carbon (EC). We analyzed snow collected within and around the urban background SMEARIII (Station for Measuring Ecosystem-Atmosphere Relations) at Kumpula (60° N) and the Arctic GAW (Global Atmospheric Watch) station at Sodankylä (67° N). The median BC, OC, and TC in snow samples (ntot = 30) in Kumpula were 1118, 5279, and 6396 ppb, and in Sodankylä, they were 19, 1751, and 629 ppb. Laboratory experiments showed that error due to carbon attached to a sampling bag (n = 11) was <0.01%. Sonication slightly increased the measured EC, while wetting the filter or filtering the wrong side up indicated a possible sample loss. Finally, we discuss the benefits and drawbacks of OCEC to detect carbon in snow. Full article
(This article belongs to the Special Issue Interaction of Air Pollution with Snow and Seasonality Effects)
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20 pages, 9493 KiB  
Article
Landsat-Based Estimation of the Glacier Surface Temperature of Hailuogou Glacier, Southeastern Tibetan Plateau, Between 1990 and 2018
by Haijun Liao, Qiao Liu, Yan Zhong and Xuyang Lu
Remote Sens. 2020, 12(13), 2105; https://doi.org/10.3390/rs12132105 - 1 Jul 2020
Cited by 18 | Viewed by 4201
Abstract
Glacier surface temperature (GST) is influenced by both the energy flux from the atmosphere above and the thermal dynamics at the ice–water–debris interfaces. However, previous studies on GST are inadequate in time series research and mountain glacier surface temperature retrieval. We evaluate the [...] Read more.
Glacier surface temperature (GST) is influenced by both the energy flux from the atmosphere above and the thermal dynamics at the ice–water–debris interfaces. However, previous studies on GST are inadequate in time series research and mountain glacier surface temperature retrieval. We evaluate the GST variability at Hailuogou glacier, a temperate glacier located in Southeastern Tibetan Plateau, from 1990 to 2018. We utilized a modified mono-window algorithm to calculate the GST using the Landsat 8 thermal infrared sensor (TIRS) band 10 data and Landsat 5 thematic mapper (TM) band 6 data. Three essential parameters, including the emissivity of ice and snow, atmospheric transmittance, and effective mean atmospheric temperature, were employed in the GST algorithm. The remotely-sensed temperatures were compared with two other single-channel algorithms to validate GST algorithm’s accuracy. Results from different algorithms showed a good agreement, with a mean difference of about 0.6 ℃. Our results showed that the GST of the Hailuogou glacier, both in the upper debris-free part and the lower debris-covered tongue, has experienced a slightly increasing trend at a rate of 0.054 ℃ a−1 during the past decades. Atmospheric warming, expanding debris cover in the lower part, and a darkening debris-free accumulation area are the main causes of the warming of the glacier surface. Full article
(This article belongs to the Special Issue Applications of Remote Sensing in Glaciology)
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14 pages, 2218 KiB  
Article
Possible Impacts of Snow Darkening Effects on the Hydrological Cycle over Western Eurasia and East Asia
by Jeong Sang, Maeng-Ki Kim, William K. M. Lau and Kyu-Myong Kim
Atmosphere 2019, 10(9), 500; https://doi.org/10.3390/atmos10090500 - 27 Aug 2019
Cited by 6 | Viewed by 2554
Abstract
In this paper, we investigated the possible impact of snow darkening effect (SDE) by light-absorbing aerosols on the regional changes of the hydrological cycle over Eurasia using the NASA GEOS-5 Model with aerosol tracers and a state-of-the-art snow darkening module, the Goddard SnoW [...] Read more.
In this paper, we investigated the possible impact of snow darkening effect (SDE) by light-absorbing aerosols on the regional changes of the hydrological cycle over Eurasia using the NASA GEOS-5 Model with aerosol tracers and a state-of-the-art snow darkening module, the Goddard SnoW Impurity Module (GOSWIM) for the land surface. Two sets of ten-member ensemble experiments for 10 years were carried out forced by prescribed sea surface temperature (2002–2011) with different atmospheric initial conditions, with and without SDE, respectively. Results show that SDE can exert a significant regional influence in partitioning the contributions of evaporative and advective processes on the hydrological cycle, during spring and summer season. Over western Eurasia, SDE-induced rainfall increase during early spring can be largely explained by the increased evaporation from snowmelt. Rainfall, however, decreases in early summer due to the reduced evaporation as well as moisture divergence and atmospheric subsidence associated with the development of an anomalous mid- to upper-tropospheric anticyclonic circulation. On the other hand, in the East Asian monsoon region, moisture advection from the adjacent ocean is a main contributor to rainfall increase in the melting season. A warmer land-surface caused by earlier snowmelt and subsequent drying further increases moisture transport and convergence significantly enhancing rainfall over the region. Our findings suggest that the SDE may play an important role in leading to hotter and drier summers over western Eurasia, through coupled land-atmosphere interaction, while enhancing East Asian summer monsoonal precipitation via enhanced land-ocean thermal contrast and moisture transport due to the SDE-induced warmer Eurasian continent. Full article
(This article belongs to the Special Issue Analysis of Oceanic and Terrestrial Atmospheric Moisture Sources)
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18 pages, 2523 KiB  
Article
Impact of Snow Darkening by Deposition of Light-Absorbing Aerosols on Snow Cover in the Himalayas–Tibetan Plateau and Influence on the Asian Summer Monsoon: A Possible Mechanism for the Blanford Hypothesis
by William K. M. Lau and Kyu-Myong Kim
Atmosphere 2018, 9(11), 438; https://doi.org/10.3390/atmos9110438 - 12 Nov 2018
Cited by 46 | Viewed by 7668
Abstract
The impact of snow darkening by deposition of light-absorbing aerosols (LAAs) on snow cover over the Himalayas–Tibetan Plateau (HTP) and the influence on the Asian summer monsoon were investigated using the NASA Goddard Earth Observing System Model Version 5 (GEOS-5). The authors found [...] Read more.
The impact of snow darkening by deposition of light-absorbing aerosols (LAAs) on snow cover over the Himalayas–Tibetan Plateau (HTP) and the influence on the Asian summer monsoon were investigated using the NASA Goddard Earth Observing System Model Version 5 (GEOS-5). The authors found that during April–May–June, the deposition of LAAs on snow led to a reduction in surface albedo, initiating a sequence of feedback processes, starting with increased net surface solar radiation, rapid snowmelt in the HTP and warming of the surface and upper troposphere, followed by enhanced low-level southwesterlies and increased dust loading over the Himalayas–Indo-Gangetic Plain. The warming was amplified by increased dust aerosol heating, and subsequently amplified by latent heating from enhanced precipitation over the Himalayan foothills and northern India, via the elevated heat pump (EHP) effect during June–July–August. The reduced snow cover in the HTP anchored the enhanced heating over the Tibetan Plateau and its southern slopes, in conjunction with an enhancement of the Tibetan Anticyclone, and the development of an anomalous Rossby wave train over East Asia, leading to a weakening of the subtropical westerly jet, and northward displacement and intensification of the Mei-Yu rain belt. The authors’ results suggest that the atmosphere-land heating induced by LAAs, particularly desert dust, plays a fundamental role in physical processes underpinning the snow–monsoon relationship proposed by Blanford more than a century ago. Full article
(This article belongs to the Special Issue Monsoons)
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24 pages, 9013 KiB  
Article
Onboard Spectral and Spatial Cloud Detection for Hyperspectral Remote Sensing Images
by Haoyang Li, Hong Zheng, Chuanzhao Han, Haibo Wang and Min Miao
Remote Sens. 2018, 10(1), 152; https://doi.org/10.3390/rs10010152 - 20 Jan 2018
Cited by 25 | Viewed by 7285
Abstract
The accurate onboard detection of clouds in hyperspectral images before lossless compression is beneficial. However, conventional onboard cloud detection methods are not applicable all the time, especially for shadowed clouds or darkened snow-covered surfaces that are not identified in normalized difference snow index [...] Read more.
The accurate onboard detection of clouds in hyperspectral images before lossless compression is beneficial. However, conventional onboard cloud detection methods are not applicable all the time, especially for shadowed clouds or darkened snow-covered surfaces that are not identified in normalized difference snow index (NDSI) tests. In this paper, we propose a new spectral-spatial classification strategy to enhance the performance of an orbiting cloud screen obtained on hyperspectral images by integrating a threshold exponential spectral angle map (TESAM), adaptive Markov random field (aMRF) and dynamic stochastic resonance (DSR). TESAM is applied to roughly classify cloud pixels based on spectral information. Then aMRF is used to do optimal process by using spatial information, which improved the classification performance significantly. Nevertheless, misclassifications occur due to noisy data in the onboard environments, and DSR is employed to eliminate noise data produced by aMRF in binary labeled images. We used level 0.5 data from Hyperion as a dataset, and the average tested accuracy of the proposed algorithm was 96.28% by test. This method can provide cloud mask for the on-going EO-1 and related satellites with the same spectral settings without manual intervention. Experiments indicate that the proposed method has better performance than the conventional onboard cloud detection methods or current state-of-the-art hyperspectral classification methods. Full article
(This article belongs to the Section Remote Sensing Image Processing)
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