Albedo Reduction Research Articles

Climate change and disturbance interact to alter landscape reflectivity (albedo) in boreal forests across a large latitudinal gradient in Siberia

Boreal forests form the largest terrestrial biome globally. Climate change is expected to induce large changes in vegetation of high latitude ecosystems, but there is considerable uncertainty about where, when, and how those changes will occur. Such vegetation change produces major feedback to the climate system, including by modifying albedo (reflectivity). Our study used the LANDIS-II forest landscape model to project forest dynamics on four representative landscapes (1 M ha) for 280 years into the future under a range of climate scenarios across a broad latitudinal gradient in Siberia. The model estimated the albedo of the vegetation and any snow on each landscape grid-cell through time to quantify surface albedo change in response to climate change and disturbances. We found that the shortening of the snow-covered season (winter) decreased annual average albedo dramatically, and climate change facilitated the invasion of tundra by boreal trees in the northernmost landscape (reducing albedo in all seasons). However, in other landscapes, albedo increased in summer due to disturbances (fire, wind, insects, harvest), eliminating or reducing leaf area in the short-term, and in the mid-term by promoting more reflective forest types (deciduous, light conifers). This increased albedo was somewhat ephemeral and under climate change was overwhelmed by the shortening of the snow-covered season that greatly reduced albedo. We conclude that the primary driver of the overall reflectivity of boreal ecosystems is not vegetation, but rather, the length of the snow-covered season. Because climate change is likely to dramatically shorten the snow season, the concurrent reduction of albedo has the potential to act as a powerful positive feedback for climate change. Managing natural and anthropogenic disturbances may be the only tool with potential to mitigate the reduction of albedo by climate change in boreal ecosystems because management to encourage more reflective forest types has relatively small effect.

Laboratory Experiments Suggest a Limited Impact of Increased Nitrogen Deposition on Snow Algae Blooms.

Snow algal blooms decrease snow albedo and increase local melt rates. However, the causes behind the size and frequency of these blooms are still not well understood. One factor likely contributing is nutrient availability, specifically nitrogen and phosphorus. The nutrient requirements of the taxa responsible for these blooms are not known. Here, we assessed the growth of three commercial strains of snow algae under 24 different nutrient treatments that varied in both absolute and relative concentrations of nitrogen and phosphorus. After 38 days of incubation, we measured total biomass and cell size and estimated their effective albedo reduction surface. Snow algal strains tended to respond similarly and achieved bloom-like cell densities over a wide range of nutrient conditions. However, the molar ratio of nitrogen to phosphorus at which maximum biomass was achieved was between 4 and 7. Our data indicate a high requirement for phosphorus for snow algae and highlights phosphorus availability as a critical factor influencing the frequency and extent of snow algae blooms and their potential contribution to snow melt through altered albedo. Snow algae can thrive across a range of nitrogen (N) and phosphorus (P) conditions, with a higher P requirement for optimal growth. Our study suggests that increased N deposition may have a limited impact on snow algae bloom occurrence and size, emphasising P as a key factor influencing these blooms and their potential to accelerate snow melt by lowering albedo.

Assimilation of Satellite Albedo to Improve Simulations of Glacier Hydrology

ABSTRACTWildfires and heatwaves have recently affected the hydrological system in unprecedented ways due to climate change. In cold regions, these extremes cause rapid reductions in snow and ice albedo due to soot deposition and unseasonal melt. Snow and ice albedo dynamics control net shortwave radiation and the available energy for melt and runoff generation. Many albedo algorithms in hydrological models cannot accurately simulate albedo dynamics because they were developed or parameterised based on historical observations. Remotely sensed albedo data assimilation (DA) can potentially improve model performance by updating modelled albedo with observations. This study seeks to diagnose the effects of remotely sensed snow and ice albedo DA on the prediction of streamflow from glacierized basins during wildfires and heatwaves. Sentinel‐2 20‐m albedo estimates were assimilated into a glacio‐hydrological model created using the Cold Regions Hydrological Modelling Platform (CRHM) in two Canadian Rockies glacierized basins, Athabasca Glacier Research Basin (AGRB) and Peyto Glacier Research Basin (PGRB). The study was conducted in 2018 (wildfires), 2019 (soot/algae), 2020 (normal) and 2021 (heatwaves). DA was employed to assimilate albedo into CRHM to simulate streamflow and was compared to a control run (CTRL) using off‐the‐shelf albedo parameters. Albedo DA benefited streamflow predictions during wildfires for both basins, with a KGE coefficient improvement of 0.18 and 0.20 in AGRB and PGRB, respectively. Four‐year DA streamflow predictions were superior to CTRL in PGRB, but DA was slightly better in AGRB. DA was not beneficial to streamflow predictions during heatwaves. DA improved streamflow predictions by decreasing positive bias, showing that albedo DA can reveal unknown albedo and snowpack dynamics in remote glacier zones that are poorly simulated in models. These findings corroborate the power of observational tools to incorporate near real‐time information into hydrological models to better inform water managers of the streamflow response to wildfires and heatwaves.

Greening‐Induced Biophysical Impacts Lead to Earlier Spring and Autumn Phenology in Temperate and Boreal Forests

AbstractTree phenology, the timing of periodic biological events in trees, is highly sensitive to climate change. Previous studies have indicated that forest greening can impact the local climate by modifying the seasonal surface energy budget. However, the understanding of tree phenological responses to forest greening at large spatial scales remains limited. Utilizing satellite‐derived phenological and leaf area index data spanning from 2001 to 2021, herein we show that forest greening led to earlier spring and autumn phenology in both temperate and boreal forests. Our findings demonstrated that forest greening during winter and spring contributed to a reduction in surface albedo, resulting in biophysical warming and consequently advancing spring leaf phenology. Conversely, forest greening in summer and autumn induced biophysical cooling through increased evapotranspiration, leading to an earlier onset of autumn leaf phenology. Our findings highlight the significant impact of forest greening‐induced local seasonal climate changes on shaping tree phenology in temperate and boreal forests. It is crucial to consider these greening‐induced alterations in microclimate conditions when modeling changes in tree phenology under future climate warming scenarios.

Small reduction in land surface albedo due to solar panel expansion worldwide

Photovoltaic (PV) panel deployment for decarbonization may reduce local terrestrial albedo, triggering a positive radiative forcing that counteracts the desired negative radiative forcing from carbon emission reductions. Yet, this potential adverse impact remains uncertain due to limited observations at PV sites. Herein we employ a robust linear parameterization method to quantify PV-induced albedo changes based on satellite data globally. We find an overall albedo decrease of −1.28 (−1.80, −0.90) × 10−2 (median and interquartile range), specific for land-cover types and climate regimes. However, the extent of albedo reduction is markedly lower than simplistic assumed values in simulating climate feedback for solar farming in Earth system models. Moreover, the albedo-induced positive radiative forcing can be offset by negative radiative forcing from clean solar generation in most PV farms within one year. Our findings underscore PV’s potential in mitigating global warming and stress the need for more accurate model estimations.

Photolytic Degradation of Water‐Soluble Organic Carbon in Snowmelts: Changes in Molecular Characteristics, Brown Carbon Chromophores, and Radiative Effects

AbstractWater‐soluble organic carbon (WSOC) deposited in ambient snowpack play key roles in regional carbon cycle and surface energy budget, but the impacts of photo‐induced processes on its optical and chemical properties are poorly understood yet. In this study, melted samples of the seasonal snow collected from northern Xinjiang, northwestern China, were exposed to ultraviolet (UV) radiation to investigate the photolytic transformations of WSOC. Molecular characteristics and chemical composition of WSOC and its brown carbon (BrC) constituents were investigated using high‐performance liquid chromatography interfaced with a photodiode array detector and a high‐resolution mass spectrometer. Upon illumination, formation of nitrogen‐ and sulfur‐containing species with high molecular weight was observed in snow samples influenced by soil‐ and plant‐derived organics. In contrast, the representative sample collected from remote region showed the lowest molecular diversity and photolytic reactivity among all samples, in which no identified BrC chromophores decomposed upon illumination. Approximately 65% of chromophores in urban samples endured UV irradiation. However, most of BrC composed of phenolic/lignin‐derived compounds and flavonoids disappeared in the illuminated samples containing WSOC from soil‐ and plant‐related sources. Effects of the photochemical degradation of WSOC on the potential modulation of snow albedo were estimated. Apparent half‐lives of WSOC estimated as albedo reduction in 300–400 nm indicated 0.1–0.4 atmospheric equivalent days, which are shorter than typical photolysis half‐lives of ambient biomass smoke aerosol. This study provides new insights into the roles of WSOC in snow photochemistry and snow surface energy balance.

Historical reconstruction of glacier mass balance and its contribution to water resources in the Sawir Mountains from 2000 to 2020

Glacial changes are crucial to regional water resources and ecosystems in the Sawir Mountains. However, glacial changes, including the mass balance and glacial meltwater of the Sawir Mountains, have sparsely been reported. Three model calibration strategies were constructed including a regression model based on albedo and in-situ mass balance of Muz Taw Glacier (A-Ms), regression model based on albedo and geodetic mass balance of valley, cirque, and hanging glaciers (A-Mr), and degree-day model (DDM) to obtain a reliable glacier mass balance in the Sawir Mountains and provide the latest understanding in the contribution of glacial meltwater runoff to regional water resources. The results indicated that the glacial albedo reduction was significant from 2000 to 2020 for the entire Sawir Mountains, with a rate of 0.015 (10a)−1, and the spatial pattern was higher in the east compared to the west. Second, the three strategies all indicated that the glacier mass balance has been continuously negative during the past 20 periods, and the average annual glacier mass balance was −1.01 m w.e. Third, the average annual glacial meltwater runoff in the Sawir Mountains from 2000 to 2020 was 22 × 106 m3, and its contribution to streamflow was 25.81 % from 2000 to 2018. The glacier contribution rates in the Ulkun- Ulastu, Lhaster, and Kendall River basins were 31.37 %, 22.51 %, and 19.27 %, respectively.

Measured black carbon deposition over the central Himalayan glaciers: Concentrations in surface snow and impact on snow albedo reduction

Deposition of ambient black carbon (BC) aerosols over snow-covered areas reduces surface albedo and accelerates snowmelt. Based on in-situ atmospheric BC data and the WRF-Chem model, we estimated the dry and wet deposition of BC over the Yala glacier of the central Himalayan region in Nepal during 2016–2018. The maximum and minimum BC dry deposition was reported in pre- and post-monsoon respectively. Approximately 50% of annual dry deposition occurred in the pre-monsoon season (March to May) and 27% of the annual dry deposition occurred in April. The total dry BC deposition rate was estimated as ∼4.6 μg m−2 day−1 providing a total deposition of 531 μg m−2 during the pre-monsoon season. The contribution of biomass burning and fossil fuel sources to BC deposition on an annual basis was 28% and 72% respectively. The annual accumulated wet deposition of BC was 196 times higher than the annual dry deposition. The ten months of observed dry deposition of BC (October 1, 2016 to August 31, 2017 – except December 2016) was ∼39% lower than that of WRF-Chem's estimated annual dry deposition from September 1, 2016 to August 31, 2017 partially due to model bias. The deposited content of BC over the snow surface has an important role in albedo reduction, therefore snow samples were collected from the surface of the Yala Glacier and the surrounding region in April 2016, 2017, and 2018. Samples were analyzed for BC mass concentration through the thermal optical analysis and single particle soot photometer method. The BC calculated via the thermal optical method was in the range of 352–854 ng g−1, higher than the BC calculated through the particle soot photometer method and estimated BC in 2 cm surface snow (imperial equation). The maximum surface snow albedo reduction due to BC was 8.8%, estimated by a widely used snow radiative transfer model and a linear regression equation.

Mitigation of black carbon emissions could immediately reduce 6.3% of glacier melting in the Qilian Mountains

Global warming in tandem with surface albedo reduction caused by black carbon (BC) deposition on glaciers accelerated glacier melting; however, their respective contributions remain unclear. Glaciers in the Qilian Mountains are crucial for the development of oases in the Hexi Corridor; however, their area has decreased by more than 20% over the past half-century. Thus, this study developed a dynamic deposition model for light-absorbing particles (LAPs), coupled with a surface energy and mass balance model. We comprehensively assessed the effects of BC and warming on the melting of a typical glacier in the Qilian Mountains based on the coupled model. BC on the glacier surface caused 13.1% of annual glacier-wide melting, of which directly deposited atmospheric BC reduced the surface albedo by 0.02 and accounted for 9.1% of glacier melting. The air temperature during 2000–2010 has increased by 1.5 °C relative to that during the 1950s, accounting for 51.9% of current glacier melting. Meanwhile, BC emission have increased by 4.6 times compared to those of the early Industrial Revolution recorded in an ice core, accounting conservatively for 6.3% of current glacier melting. Mitigating BC emissions has a limited influence on current glacier melting; however, in the long-term, mitigation should exert a noteworthy impact on glacier melting through the self-purification of glaciers.

Optical effect of Andean mineral dust onto snow surface spectral albedo

Light absorbing particles (LAPs) present high absorbance and contribute to reducing the snow albedo when deposited on snow surfaces. This deposition can be caused by aerosols transported from natural or anthropogenic, either distant or nearby sources. In this study, snow was artificially contaminated with soil samples collected in the Central Andes (near El Yeso dam) to simulate the most common nearby source of Mineral Dust (MD) deposition onto snow surface. Andean soil samples previously conditioned were characterized through Single Particle Optical Sizing (SPOS), X-ray diffraction (XRD) analysis, and Scanning Electron Microscope (SEM) for the determination of optical properties. Spectral snow albedo was measured in situ with a spectroradiometric system. To evaluate the heterogeneity of the particle distribution over the snow surface, aerial photographs were taken with a drone to apply a visual color segmentation of the surface and to determine the equivalent MD concentration. Experimental snow albedo was compared with theoretical values obtained with the OptiPar radiative transfer model. Inputs for the model were: the MD refractive index (calculated from the mineralogical composition and morphology of MD) and particle size, cloudiness, snow density, surface roughness, snow grain size, and LAPs concentration (obtained from the snow samples collected during the experiments and analyzed in the laboratory). Small black carbon concentrations were found in natural snow and considered in the simulations. Spectral albedo measurements showed high albedo reductions in the UV and VIS range (300–800 nm), being less significant in the NIR range (800–1700 nm). A nonlinear behavior was observed in broadband albedo when increasing MD concentration. For lower values of MD concentration (lower than 1500 mg⋅kg−1), a significant albedo reduction rate of 0.1 units per 1000 mg⋅kg−1 was found, while at higher concentrations (¿ 3500 mg⋅kg−1), such reduction tends to the minimum. Simulated values with OptiPar are in agreement with measured albedo, but some differences are observed, probably due to the refractive index considered, the snow surface roughness, and the non-uniform MD concentration in snow.

Dust storms from the Taklamakan Desert significantly darken snow surface on surrounding mountains

Abstract. The Taklamakan Desert (TD) is a major source of mineral dust emissions into the atmosphere. These dust particles have the ability to darken the surface of snow on the surrounding high mountains after deposition, significantly impacting the regional radiation balance. However, previous field measurements have been unable to capture the effects of severe dust storms accurately, and their representation on regional scales has been inadequate. In this study, we propose a modified remote-sensing approach that combines data from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite and simulations from the Snow, Ice, and Aerosol Radiative (SNICAR) model. This approach allows us to detect and analyze the substantial snow darkening resulting from dust storm deposition. We focus on three typical dust events originating from the Taklamakan Desert and observe significant snow darkening over an area of ∼ 2160, ∼ 610, and ∼ 640 km2 in the Tien Shan, Kunlun, and Qilian mountains, respectively. Our findings reveal that the impact of dust storms extends beyond the local high mountains, reaching mountains located approximately 1000 km away from the source. Furthermore, we observe that dust storms not only darken the snowpack during the spring but also in the summer and autumn seasons, leading to increased absorption of solar radiation. Specifically, the snow albedo reduction (radiative forcing) triggered by severe dust deposition is up to 0.028–0.079 (11–31.5 W m−2), 0.088–0.136 (31–49 W m−2), and 0.092–0.153 (22–38 W m−2) across the Tien Shan, Kunlun, and Qilian mountains, respectively. This further contributes to the aging of the snow, as evidenced by the growth of snow grain size. Comparatively, the impact of persistent but relatively slow dust deposition over several months during non-event periods is significantly lower than that of individual dust events. This highlights the necessity of giving more attention to the influence of extreme events on the regional radiation balance. This study provides a deeper understanding of how a single dust event can affect the extensive snowpack and demonstrates the potential of employing satellite remote sensing to monitor large-scale snow darkening.

Synergies and trade-offs between provisioning and climate-regulating ecosystem services in reindeer herding ecosystems

Reindeer (Rangifer tarandus) pastoralism utilizes vast boreo-arctic taiga and tundra as grazing land. Highly fluctuating population sizes pose major challenges to the economy and livelihood of indigenous herder communities. In this study we investigated the effect of population fluctuations on core provisioning and regulating ecosystem services in two Sámi reindeer herding districts with contrasting fluctuation trends. We compared 50-year long time series on herd size, meat production, forage productivity, carbon footprint, and CO2-equivalence metrics for surface albedo change based on the radiative forcing concept. Our results show, for both districts, that the economic benefits from the provisioning services were higher than the costs from the regulating services. Still, there were major contrasts; the district with moderate and stable reindeer density gained nearly the double on provisioning services per unit area. The costs from increasing heat absorption due to reduction in surface albedo caused by replacement of high-reflective lichens with low-reflective woody plants, was 10.5 times higher per unit area in the district with large fluctuations. Overall, the net economic benefits per unit area were 237 % higher in the district with stable reindeer density. These results demonstrate that it is possible to minimize trade-offs between economic benefits from reindeer herding locally and global economic costs in terms of climate-regulating services by minimizing fluctuations in herds that are managed at sustainable densities.

Unintended consequences of planting native and non‐native trees in treeless ecosystems to mitigate climate change

Abstract Naturally treeless ecosystems are being replaced by native and non‐native trees worldwide, often through deliberate afforestation using forestry tree species. By introducing species having novel traits, such as relatively rapid growth, many afforestation efforts also produce numerous changes in ecosystems, at the landscape scale. Trees are considered critical for climate change mitigation; indeed, many current carbon sequestration strategies rely on trees. Planting trees or allowing trees to naturally colonize through range expansions can be seen as an ideal way to increase atmospheric carbon capture. For example, a snapshot approach may show that introducing trees into treeless ecosystems enhances aboveground accumulation of carbon, helping increase ecosystem carbon storage. However, considering other impacts such as reductions in soil carbon or albedo and increased fire severity (through increases in fuel loads and connectivity) reduces the effectiveness of afforestation strategies for climate change amelioration. Additional negative impacts of afforestation are also likely, such as the reduction of native biodiversity and productivity, substantial water yield losses, and changes in nutrient cycles, which can exacerbate other global change drivers. Further, tree invasions originating from afforestation can exacerbate these negative impacts. Synthesis. This review highlights that the positive and negative impacts of planting trees in naturally treeless ecosystems as a strategy to mitigate climate change are idiosyncratic, depending on the location where trees are introduced, the time period trees are allowed to grow, and risks of spread and impacts associated with specific tree species. Although planting trees can potentially be a tool to fight climate change, a greater consideration of their impacts is required to minimize the unexpected negative consequences of afforestation efforts.

Impacts of physical parameterization scheme of snow and soil properties over the Tibetan Plateau on the simulation of summer rainfall in China

Accurate representation of soil and snow state variables in the land surface model is crucial for good simulation results. In order to investigate the potential impacts of the overestimated snow cover over the Tibetan Plateau (TP) on precipitation over China, we designed comparative experiments over TP with and without updated soil texture data, soil hydrological parameters, and the fresh snow density scheme to address this issue with the Weather Research and Forecasting Model (WRF). The results show that snow cover fraction (SCF) and surface albedo in winter on the TP were overestimated in the WRF control experiment (CTL), with albedo bias exceeding 0.4 in the western TP. The SCF in the WRF improved experiment (WRFIM) is about 8% lower than that of the CTL, and the bias is decreased to 0.2–0.3 in the interior of the TP. The thermal and dynamic effects of the TP in winter have a significant impact on the weather and climate of East Asia during summer. Thus, the simulated summer rainfall bias is significantly reduced by WRFIM in North China, and the mid-lower reaches of the Yangtze River, along with the spatial correlation coefficient between the observed-based and WRF-simulated rainfall increased from 0.76 in CTL to 0.88 in WRFIM. The WRFIM-simulated reductions in snow cover and albedo cause a decrease in upward shortwave radiation and eventually increase net surface radiation. The horizontal temperature gradient of the atmosphere is increased in the WRFIM compared to the CTL, and the increased temperature in the lower and middle layers accommodates more water vapor, which is not conducive to precipitation formation. Correspondingly, the Western Pacific Subtropical High at 500 hPa in the middle troposphere weakened. The low-level anticyclonic circulation at 850 hPa also weakened to the east, affecting water vapor transport in eastern China. It leads to a decrease in the water vapor transported northward by southeasterly from the western Pacific Ocean and a decrease in the water vapor flux reaching North China. This work indicates that accurate characterization of soil properties and snow cover on the TP is crucial for improving the simulation bias of summer rainfall in China.

Combined effect of algae and dust on snow spectral and broadband albedo

The optical properties of snow can be strongly modified by the presence of a variety of impurities including mineral dust and snow algae. We made use of measured concentration of snow algae and mineral dust to parameterize the BioSNICAR radiative transfer model. Surficial snow samples were gathered during a field campaign on 7th July 2020 at the Presena glacier (Rhaetian Alps). We collected 18 samples of surface snow containing different amount of snow algae and mineral dust. Through radiative transfer simulations we estimated an average broadband albedo reduction of 7.4 ± 6.1 % and 35.3 ± 7.4 % compared to clean snow, caused by snow algae and mineral dust presence, respectively. When we considered the combined effect of snow algae and dust, we estimated a broadband albedo reduction equal to 40.8 ± 8.4 %. We estimated an average instantaneous radiative forcing induced by snow algae, mineral dust and both impurities equals to 42.3 (± 36.1) W/m2, 203.7 (±45.5) W/m2, and 211.8 (±45.9) W/m2, respectively.Using BioSNICAR simulations, we also tested a series of narrowband spectral indices to determine the concentration of mineral dust and snow algae from multi- and hyper-spectral data. Results showed that most spectral indices used for snow algae mapping are correlated also with mineral dust concentration. We found that only an index correlates uniquely with snow algae: the scaled band integral at 680 nm. A new spectral index, namely the Green Blue Normalized Index, is therefore proposed to discriminate mineral dust from snow algae when both impurities are present. The high spectral resolution of current (e.g. PRISMA, EnMAP) and future (e.g. CHIME, SBG) hyperspectral satellite missions will be fundamental to decouple the effect of mineral dust and snow algae on the optical properties of snow. In fact, from those data it is possible to calculate all narrowband indices presented in this study.

Albedo as a Competing Warming Effect of Urban Greening

AbstractUrban greening is often proposed for urban heat island (UHI) mitigation because vegetation provides shade and increases evapotranspiration. However, vegetation has lower albedo and higher emissivity than the bare soil it often replaces, which increases incoming energy fluxes. Here, we use the Weather Research and Forecasting model to quantify and compare the albedo and non‐albedo effects (i.e., changes in emissivity, surface roughness, and evaporative fluxes) of urban greening in the Los Angeles Basin under policy relevant urban greening scenarios. When albedo‐induced effects were included in the model, daytime surface temperatures in urban areas warmed by 0.70 ± 0.89°C with increases in the sensible heat flux outweighing increases in the latent heat flux from increased evapotranspiration. In contrast, daytime surface temperatures cooled by 0.27 ± 0.72°C when the albedo‐induced effects were ignored. At night, including albedo‐induced effects of urban greening resulted in only half the cooling modeled in the non‐albedo simulations. Near surface air temperatures also had contrasting model results, with nighttime cooling of 0.21 ± 0.47°C outweighing slight daytime warming of 0.04 ± 0.32°C in the non‐albedo simulations and daytime warming of 0.33 ± 0.41°C outweighing slight nighttime cooling of 0.05 ± 0.46°C in the albedo simulations. Our results reveal the critical role that albedo plays in determining the net surface climate effects of urban greening. Reductions in albedo from urban greening should be carefully considered by policy makers and urban planners, especially as high albedo roofs and pavements are simultaneously being deployed for UHI mitigation in many cities.

The distribution and drivers of microbial pigments in the cryoconite of four Tibetan glaciers.

Microbial pigments play a significant role in glacier albedo reduction, thereby contributing to accelerated glacier retreat. The Tibetan Plateau has experienced rapid glacier retreat in recent decades due to global warming, yet there is limited understanding of microbial pigment distribution in the region. Here, we investigated the pigment concentration and composition in cryoconite from four glaciers. Our results showed that chlorophylls were the dominant pigments in Palong No. 4 (PL) and Jiemayangzong (JMYZ) glaciers located in the south of the Tibetan Plateau, while carotenoids were dominant in Qiangyong (QY) and Tanggula (TGL) glaciers located in the central region. Additionally, the chlorophyll b to chlorophyll a ratio, which is an indicator of the algae-to-cyanobacteria ratio, was higher in PL and JMYZ compared to QY and TGL. By using Random Forest Regression and Structural Equation Modelling, we determined that the concentrations of chlorophyll a, chlorophyll b, and carotenoids were associated with autotrophic bacteria relative abundance, climatic factors, and a combination of bacterial and climatic factors, respectively. This study is the first to describe the distribution of microbial pigments in cryoconite from Tibetan glaciers, providing additional support on the influence of algal pigment on glacier retreat.

Improvement of sea ice thermodynamics with variable sea ice salinity and melt pond parameterizations in an OGCM

Enhanced representation of sea ice processes in ocean modeling studies is required for advancing our understanding and prediction of the climate variability. In the present study, we improved the sea ice thermodynamics in an OGCM by introducing processes for variable sea ice salinity and melt ponds on sea ice. The former affects the latent heat and conductivity of sea ice as well as the salt budget in the ocean–sea ice system. We formulated salinification and desalination processes based on previous observational studies. Melt ponds enhance summertime surface melting by reducing the surface albedo. In our formulation of the melt pond thermodynamics, the shortwave radiation absorbed in the pond was partly released to the air and partly conducted to the underlying sea ice. By adopting these parameterizations, seasonal cycles of the sea ice salinity distributions in both hemispheres were generally reproduced. Simulated seasonal and interannual variations in the Arctic melt pond area and associated surface albedo reductions were basically consistent with observational estimates. The melt pond effect reduced the Arctic sea ice volume by about 1.5 × 103 km3 in the summer; half of this impact remained throughout the year. Our results suggest that the new parameterizations have the potential to improve the seasonal evolution of the sea ice thickness and concentration distributions, which would contribute to prediction studies.

Field study on the diffusion and advection effects of vehicle-emitted soot aerosols on snow albedo in the Chilean Andes

Emissions from road traffic are one of the most important sources of soot aerosols and they can affect the surfaces in the area. In the case of snow surfaces, this effect may lead to changes in the radiative forcing and snow melt, also influenced by particle transport such as particle diffusion and advection. An experimental campaign in The Andes, Chile, was carried out measuring the radiance and irradiance of the snow perpendicularly to a road with high traffic load, together with the meteorological conditions (to identify the diffusion and advection phenomena), the aerosol size distribution, the concentration of particles (PM1, PM2.5 and PM10), and the concentration of black carbon (BC) in both, the atmosphere and the snowpack. The aim of the study was to quantify the contribution of four factors affecting the albedo (black carbon -BC- concentration in snow, grain size, cloudiness, and roughness) by comparing the measured albedo of the contaminated snow surface with that of the same surface prior to contamination, considered as a reference. Results showed a trade-off between diffusion and advection. Close to the road, diffusion was predominant, leading to an increase in BC concentration and a reduction in snow albedo. On the contrary, far from the road, where winds are channeled along the centre of the valley, advection of particles became dominant, leading to another increase in particle concentration and another reduction in snow albedo. Among the factors contributing to reduce the snow albedo, BC concentration dominates at all distances from the road, although the effect of the grain size becomes as significant as that of BC in the centre of the valley, with the effects of surface roughness and cloudiness remaining minor. This information can be used in snow models to get a better knowledge of the effect of particle deposition on albedo reductions.

Snow Albedo Reduction in the Colombian Andes Mountains Due to 2000 to 2020 Saharan Dust Intrusions Events

This article investigates the snow albedo changes in Colombian tropical glaciers, namely, Sierra Nevada de Santa Marta (SNSM), Sierra Nevada del Cocuy (NSC), Nevado del Ruíz (NDR), Nevado Santa Isabel (NDS), Nevado del Tolima (NDT), and Nevado del Huila (NDH). They are associated with the possible mineral dust deposition from the Sahara Desert during the June and July months using snow albedo (SA), snow cover (SC), and land surface temperature (LST) from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA’s Terra and Aqua satellites. And mineral dust (MD) from The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), both of them during 2000–2020. Results show the largest snow albedo reductions were observed at 39.39%, 32.1%, and 30.58% in SNC, SNSM, and NDR, respectively. Meanwhile, a multiple correlation showed that the glaciers where MD contributed the most to SA behavior were 35.4%, 24%, and 21.4% in NDS, NDC, and NDR. Results also display an increasing trend of dust deposition on Colombian tropical glaciers between 2.81 × 10−3 µg·m−2·year−1 and 6.58 × 10−3 µg·m−2·year−1. The results may help recognize the influence of Saharan dust on reducing snow albedo in tropical glaciers in Colombia. The findings from this study also have the potential to be utilized as input for both regional and global climate models. This could enhance our comprehension of how tropical glaciers are impacted by climate change.