Jonas Svensson

Central Asia is a region with high-altitude mountains, hosting numerous glaciers and widespread seasonal snow cover, both of which play an integral role in the regional hydrological cycle. Despite their importance, observations of cryospheric and atmospheric variables are scarce in this area but are essential to assess the temporal and spatial changes induced by climate change. To address this gap, we present a diverse data set of cryospheric and atmospheric variables from the Zarafshon River Basin and the Hydrographic Party Glacier (GGP) in Tajikistan, spanning 2018–2025. The dataset includes glacier terminus positions and snow conditions, glacier ablation, high resolution aerial photography, meteorological variables, surface reflectance combined with snow chemistry, and atmospheric aerosol concentrations. These observations provide a valuable basis for research on glacier dynamics, snow processes, and atmosphere-cryosphere interactions in a region where monitoring has been sparse. The data are available at the Finnish Meteorological Institute data repository METIS: https://doi.org/10.57707/fmi-b2share.t4vwg-gf542 (Svensson et al., 2026).

Central Asia is a region with high-altitude mountains, hosting numerous glaciers and widespread seasonal snow cover, both of which have an integral role in the regional hydrological cycle. Despite their importance, observations of cryospheric and atmospheric variables are scarce in this area but are essential to assess the temporal and spatial changes induced by climate change. To address this gap, we present a diverse data set of cryospheric and atmospheric variables from the Zarafshon River Basin and the Hydrographic Party Glacier (GGP) in Tajikistan, spanning the time frame of 2018–2025. The data includes glacier terminus position and snow conditions, glacier ablation, high resolution aerial photography, meteorological variables, surface reflectance combined with snow chemistry, and atmospheric aerosol concentrations. These observations provide a valuable basis for research on glacier dynamics, snow processes, and atmosphere-cryosphere interactions in a region where monitoring has been sparse. The data are available at the Finnish Meteorological Institute data repository METIS: https://doi.org/10.57707/fmi-b2share.t4vwg-gf542 (Svensson et al., 2026).

The absorption of shortwave irradiance in snow depends on the physical properties of snow (e.g., snow grain size and shape, liquid water content, etc.) and light-absorbing particles (LAP). Originating from natural and anthropogenic sources, LAP has been reported to accelerate snowmelt significantly in different regions globally. Yet, our process-level understanding of LAP after deposition onto snow remains rather limited. Here we investigate the impacts of artificial deposition of different LAP onto snow surfaces in an outdoor environment of northern Finland. Following LAP dry deposition into a custom-made tent standing on top of the snowpack, the albedo was followed along with the properties of snow in snow pit measurements throughout the spring season. The results showed that the albedo decay at the end of the season for the different spots were linked to the initial amount and type of LAP that were deposited onto the snowpack. Measured snow temperature profiles from LAP doped snow versus natural reference snow illustrated that the LAP affected snow had higher temperatures in the subsurface snow layers. Collected snow samples analyzed for size distribution of soot particles revealed no apparent agglomeration of soot particles during thaw-freezing events taking place during the experiment. Despite the relatively large perturbation of the experimentally deposited LAP, their impact on the season length was only up to 3 days. Additional experiments are, nevertheless, needed to better constrain the effects of LAP on snow albedo, melt rate, and other associated processes.

Snow darkening by deposited light-absorbing particles (LAP) accelerates snowmelt and shifts the snow melt-out date (MOD). Here, we present a simple approach to estimate the snow albedo variability due to LAP deposition and test this method with data for 2 seasons (February–May 2016 and December 2016–June 2017) at a high-altitude valley site in the Central Himalayas, India. We derive a parameterization for the snow albedo that only depends on the daily observations of average ambient temperature and change in snow depth, as well as an assumed average concentration of LAP in snow precipitation. Linear regression between observed and parameterized albedo for the base case assuming an equivalent elemental carbon concentration [EC_eq] of 100 ng g^–1 in snow precipitation yields a slope of 0.75 and a Pearson correlation coefficient r² of 0.76. However, comparing the integrated amount of shortwave radiation absorbed during the winter season using observed albedo versus base case albedo resulted in rather small differences of 11% and 4% at the end of Seasons 1 and 2, respectively. The enhanced energy absorbed due to LAP at the end of the 2 seasons for the base case scenario (assuming an [EC_eq] of 100 ng g^–1 in snow precipitation) was 40% and 36% compared to pristine snow. A numerical evaluation with different assumed [EC_eq] in snow precipitation suggests that the relative sensitivity of snow albedo to changes in [EC_eq] remains rather constant for the 2 seasons. Doubling [EC_eq] augments the absorption by less than 20%, highlighting that the impact on a MOD is small even for a doubling of average LAP in snow precipitation.

Anthropogenic activities on the Indo-Gangetic Plain emit vast amounts of light-absorbing particles (LAPs) into the atmosphere, modifying the atmospheric radiation state. With transport to the nearby Himalayas and deposition to its surfaces the particles contribute to glacier melt and snowmelt via darkening of the highly reflective snow. The central Himalayas have been identified as a region where LAPs are especially pronounced in glacier snow but still remain a region where measurements of LAPs in the snow are scarce. Here we study the deposition of LAPs in five snow pits sampled in 2016 (and one from 2015) within 1 km from each other from two glaciers in the Sunderdhunga Valley, in the state of Uttarakhand, India, in the central Himalayas. The snow pits display a distinct enriched LAP layer interleaved by younger snow above and older snow below. The LAPs exhibit a distinct vertical distribution in these different snow layers. For the analyzed elemental carbon (EC), the younger snow layers in the different pits show similarities, which can be characterized by a deposition constant of about 50 µg m⁻² mm⁻¹ snow water equivalent (SWE), while the old-snow layers also indicate similar values, described by a deposition constant of roughly 150 µg m⁻² mm⁻¹ SWE. The enriched LAP layer, contrarily, displays no similar trends between the pits. Instead, it is characterized by very high amounts of LAPs and differ in orders of magnitude for concentration between the pits. The enriched LAP layer is likely a result of strong melting that took place during the summers of 2015 and 2016, as well as possible lateral transport of LAPs. The mineral dust fractional absorption is slightly below 50 % for the young- and old-snow layers, whereas it is the dominating light-absorbing constituent in the enriched LAP layer, thus, highlighting the importance of dust in the region. Our results indicate the problems with complex topography in the Himalayas but, nonetheless, can be useful in large-scale assessments of LAPs in Himalayan snow.

Anthropogenic activities on the Indo-Gangetic Plain emit vast amounts of light-absorbing particles (LAP) into the atmosphere, modifying the atmospheric radiation scheme. With transport to the nearby Himalayan mountains and deposition to its surfaces the particles contribute to glacier and snowmelt via darkening of the highly reflective snow. The Central Himalayas have been identified as a region where LAP are especially pronounced in glacier snow, but still remain a region where measurements of LAP in the snow are scarce. Here we study the deposition of LAP in five snow pits sampled in 2016 (and one from 2015) from two glaciers in the Sunderdhunga valley, state of Uttarakhand, India, Central Himalaya. The snow pits display a distinct melt layer interleaved by younger snow above, and older snow below. The LAP exhibit a large vertical distribution in these different snow layers. For the analyzed elemental carbon (EC), the younger snow layers in the different pits show similarities, and can be characterized by a deposition constant of about 50 µg m⁻² mm⁻¹ while the old snow layers also indicate similar values, and can be described with deposition constant of roughly 150 µg m⁻² mm⁻¹. The melt layer, contrarily, display no similar trends between the pits. Instead, it is characterized by very high amounts of LAP, and differ in orders of magnitude for concentration between the pits. The melt layer is likely a result of strong melting that took place during the summers of 2015 and 2016. The mineral dust fractional absorption is slightly below 50 % for the young and old snow layer, whereas in the melt layer is the dominating light absorbing constituent, thus, highlighting the importance of dust in the region. Our results indicate the problems with complex topography in the Himalaya, but nonetheless, can be useful in large-scale assessments of LAP in Himalayan snow.

Glycosaminoglycan (GAG) chemical exchange saturation transfer (gagCEST) is a potential method for cartilage quality assessment. The aim of this study was to investigate how the gagCEST effect depends on the types and molecular organization of GAG typically found in articular cartilage. gagCEST was performed on different concentrations of GAG in various forms: free chains of chondroitin sulfate (CS) of different types (‐A and ‐C) and GAG bound to protein in aggregated and nonaggregated aggrecan extracted from calf articular cartilage. The measured magnetization transfer ratio asymmetry (MTR_asym) was compared with known GAG concentrations or GAG concentrations determined through biochemical analysis. The gagCEST effect was assessed through the linear regression coefficient with 95% confidence interval of MTR_asym per GAG concentration. We observed a lower gagCEST effect in phantoms containing a mixture of CS‐A and CS‐C compared with phantoms containing mainly CS‐A. The difference in response corresponds well to the difference in CS‐A concentration. GAG bound in aggrecan from calf articular cartilage, where CS‐A is assumed to be the major type of GAG, produed a similar gagCEST effect as that observed for free CS‐A. The effect was also similar for aggregated (ie, bound to hyaluronic acid) and nonaggregated aggrecan. In conclusion, our results indicate that the aggrecan structure in itself does not impact the gagCEST effect, but that the effect is strongly dependent on GAG type. In phantoms, the current implementation of gagCEST is sensitive to CS‐A while for CS‐C, the main GAG component in mature human articular cartilage, the sensitivity is limited. This difference in gagCEST sensitivity between GAG types detected in phantoms is a strong motivation to also explore the possibility of a similar effect in vivo.