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The new Energy Exascale Earth System Model Version 1 (E3SMv1) developed for the U.S. Department of Energy has significant new treatments of aerosols and light‐absorbing snow impurities as well as their interactions with clouds and radiation. This study describes seven sets of new aerosol‐related treatments (involving emissions, new particle formation, aerosol transport, wet scavenging and resuspension, and snow radiative transfer) and examines how they affect global aerosols and radiative forcing in E3SMv1. Altogether, they give a reduced total aerosol radiative forcing (−1.6 W/m2) and sensitivity in cloud liquid water to aerosols, but an increased sensitivity in cloud droplet size to aerosols. A new approach for H2SO4 production and loss largely reduces a low bias in small particles concentrations and leads to substantial increases in cloud condensation nuclei concentrations and cloud radiative cooling. Emitting secondary organic aerosol precursor gases from elevated sources increases the column burden of secondary organic aerosol, contributing substantially to global clear‐sky aerosol radiative cooling (−0.15 out of −0.5 W/m2). A new treatment of aerosol resuspension from evaporating precipitation, developed to remedy two shortcomings of the original treatment, produces a modest reduction in aerosols and cloud droplets; its impact depends strongly on the model physics and is much stronger in E3SM Version 0. New treatments of the mixing state and optical properties of snow impurities and snow grains introduce a positive present‐day shortwave radiative forcing (0.26 W/m2), but changes in aerosol transport and wet removal processes also affect the concentration and radiative forcing of light‐absorbing impurities in snow/ice. Plain Language Summary Aerosol and aerosol‐cloud interactions continue to be a major uncertainty in Earth system models, impeding their ability to reproduce the observed historical warming and to project changes in global climate and water cycle. The U.S. DOE Energy Exascale Earth System Model version 1 (E3SMv1), a state‐of‐the‐science Earth system model, was developed to use exascale computing to address the grand challenge of actionable predictions of variability and change in the Earth system critical to the energy sector. It has been publicly released with new treatments in many aspects, including substantial modifications to the physical treatments of aerosols in the atmosphere and light‐absorbing impurities in snow/ice, aimed at reducing some known biases or correcting model deficiencies in representing aerosols, their life cycle, and their impacts in various components of the Earth system. Compared to its predecessors (without the new treatments) and observations, E3SMv1 shows improvements in characterizing global distributions of aerosols and their radiative effects. We conduct sensitivity experiments to understand the impact of individual changes and provide guidance for future development of E3SM and other Earth system models. Key Points A description and assessment of new aerosol treatments in the Energy Exascale Earth System Model Version 1 (E3SMv1) is provided Contributions to the total aerosol‐related radiative forcing by individual new treatments and different processes are quantified Some of the new treatments are found to depend on model physics and require further improvement for E3SM or other Earth system models

A physically based snow albedo model (PBSAM), which can be used in a general circulation model, is developed. PBSAM calculates broadband albedos and the solar heating profile in snowpack as functions of snow grain size and concentrations of snow impurities, black carbon and mineral dust, in snow with any layer structure and under any solar illumination condition. The model calculates the visible and near‐infrared (NIR) albedos by dividing each broadband spectrum into several spectral subbands to simulate the change in spectral distribution of solar radiation in the broadband spectra at the snow surface and in the snowpack. PBSAM uses (1) the look‐up table method for calculations of albedo and transmittance in spectral subbands for a homogeneous snow layer, (2) an “adding” method for calculating the effect of an inhomogeneous snow structure on albedo and transmittance, and (3) spectral weighting of radiative parameters to obtain the broadband values from the subbands. We confirmed that PBSAM can calculate the broadband albedos of single‐ and two‐layer snow models with good accuracy by comparing them with those calculated by a spectrally detailed radiative transfer model (RTM). In addition, we used radiation budget measurements and snow pit data obtained during the two winters from 2007 to 2009 at Sapporo, Hokkaido, Japan, for simulation of the broadband albedos by PBSAM and compared the results with the in situ measurements. A five‐layer snow model with one visible subband and three NIR subbands were necessary for accurate simulation. Comparison of solar heating profiles calculated by PBSAM with those calculated by the spectrally detailed RTM showed that PBSAM calculated accurate solar heating profiles when at least three subbands were used in both the visible and NIR bands. Key Points Broadband snow albedo model as function of snow parameters for GCM is presented The model was validated with long‐term radiation budget and snow pit work data Solar heating profile in snowpack can be calculated as well

We developed a multilayered physical snowpack model named Snow Metamorphism and Albedo Process (SMAP), which is intended to be incorporated into general circulation models for climate simulations. To simulate realistic physical states of snowpack, SMAP incorporates a state‐of‐the‐art physically based snow albedo model, which calculates snow albedo and solar heating profile in snowpack considering effects of snow grain size and snow impurities explicitly. We evaluated the performance of SMAP with meteorological and snow impurities (black carbon and dust) input data measured at Sapporo, Japan during two winters: 2007–2008 and 2008–2009, and found SMAP successfully reproduced all observed variations of physical properties of snowpack for both winters. We have thus confirmed that SMAP is suitable for climate simulations. With SMAP, we also investigated the effects of snow impurities on snowmelt at Sapporo during the two winters. We found that snowpack durations at Sapporo were shortened by 19 days during the 2007–2008 winter and by 16 days during the 2008–2009 winter due to radiative forcings caused by snow impurities. The estimated radiative forcings due to snow impurities during the accumulation periods were 3.7 W/m2 (it corresponds to albedo reduction in 0.05) and 3.2 W/m2 (albedo reduction in 0.05) for the 2007–2008 and 2008–2009 winters, respectively. While during the ablation periods they were 25.9 W/m2 (albedo reduction in 0.18) and 21.0 W/m2 (albedo reduction in 0.17) for each winter, respectively. Key Points A physical snowpack model named SMAP is developed The model is validated in detail using observations Snowpack durations at Sapporo were shortened by impurities

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.

Over the period 2021–2024, glaciers in Western Canada and the conterminous US (WCAN‐US), and Switzerland respectively lost mass at rates of 22.2 ± 9.0 and 1.5 ± 0.3 Gt yr−1 representing a twofold increase in mass loss compared to the period 2010–2020. Since 2020, total ice volume was depleted by 12% (WCAN‐US) and 13% (Switzerland). Meteorological conditions that favored high rates of mass loss included low winter snow accumulation, early‐season heat waves, and prolonged warm, dry conditions. High transient snow lines, and impurity loading due to wildfires (WCAN‐US) or Saharan dust (Switzerland) darkened glaciers and thereby increased mass loss via greater absorbed shortwave radiation available for melt. This ice‐albedo feedback will lead to continued high rates of thinning unless recently exposed dark ice and firn at high elevations is buried by seasonal snowfall. Physical models that simulate impurity deposition and movement through firn and ice are needed to improve future projections of glacier mass change.

Light absorbing impurities (LAI) initiate powerful snow albedo feedbacks, yet due to a scarcity of observations and measurements, LAI radiative forcing is often neglected or poorly constrained in climate and hydrological models. To support physically-based modeling of LAI processes, daily measurements of dust and black carbon (BC) stratigraphy, optical grain size, snow density and spectral albedo were collected over the 2013 ablation season in the Rocky Mountains, CO. Surface impurity concentrations exhibited a wide range of values (0.02–6.0 mg g−1 pptw) with 98% of mass being deposited by three episodic dust events in April. Even minor dust loading initiated albedo decline, and the negative relationship between dust concentrations and albedo was log-linear. As melt progressed, individual dust layers coalesced and emerged at the snow surface, with minimal mass loss to meltwater scavenging. The observations show that the convergence of dust layers at the surface reduced albedo to 0.3 and snow depth declined ~50% faster than other years with similar depth but less dust. The rapid melt led to an unexpected reduction in both grain size and density in uppermost surface layers. BC concentrations co-varied with dust concentrations but were several orders of magnitude lower (<1–20 ppb).

Light-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.

Snow in the environment acts as a host to rich chemistry and provides a matrix for physical exchange of contaminants within the ecosystem. The goal of this review is to summarise the current state of knowledge of physical processes and chemical reactivity in surface snow with relevance to polar regions. It focuses on a description of impurities in distinct compartments present in surface snow, such as snow crystals, grain boundaries, crystal surfaces, and liquid parts. It emphasises the microscopic description of the ice surface and its link with the environment. Distinct differences between the disordered air-ice interface, often termed quasi-liquid layer, and a liquid phase are highlighted. The reactivity in these different compartments of surface snow is discussed using many experimental studies, simulations, and selected snow models from the molecular to the macro-scale. Although new experimental techniques have extended our knowledge of the surface properties of ice and their impact on some single reactions and processes, others occurring on, at or within snow grains remain unquantified. The presence of liquid or liquid-like compartments either due to the formation of brine or disorder at surfaces of snow crystals below the freezing point may strongly modify reaction rates. Therefore, future experiments should include a detailed characterisation of the surface properties of the ice matrices. A further point that remains largely unresolved is the distribution of impurities between the different domains of the condensed phase inside the snowpack, i.e. in the bulk solid, in liquid at the surface or trapped in confined pockets within or between grains, or at the surface. While surface-sensitive laboratory techniques may in the future help to resolve this point for equilibrium conditions, additional uncertainty for the environmental snowpack may be caused by the highly dynamic nature of the snowpack due to the fast metamorphism occurring under certain environmental conditions. Due to these gaps in knowledge the first snow chemistry models have attempted to reproduce certain processes like the long-term incorporation of volatile compounds in snow and firn or the release of reactive species from the snowpack. Although so far none of the models offers a coupled approach of physical and chemical processes or a detailed representation of the different compartments, they have successfully been used to reproduce some field experiments. A fully coupled snow chemistry and physics model remains to be developed.

One of the primary controls upon the melting of the Greenland Ice Sheet (GrIS) is albedo, a measure of how much solar radiation that hits a surface is reflected without being absorbed. Lower-albedo snow and ice surfaces therefore warm more quickly. There is a major difference in the albedo of snow-covered versus bare-ice surfaces, but observations also show that there is substantial spatio-temporal variability of up to ∼0.4 in bare-ice albedo. Variability in bare-ice albedo has been attributed to a number of processes including the accumulation of light-absorbing impurities (LAIs) and the changing physical properties of the near-surface ice. However, the combined impact of these processes upon albedo remains poorly constrained. Here we use field observations to show that pigmented glacier algae are ubiquitous and cause surface darkening both within and outside the south-west GrIS “dark zone” but that other factors including modification of the ice surface by algal bloom presence, surface topography and weathering crust state are also important in determining patterns of daily albedo variability. We further use observations from an unmanned aerial system (UAS) to examine the scale gap in albedo between ground versus remotely sensed measurements made by Sentinel-2 (S-2) and MODIS. S-2 observations provide a highly conservative estimate of algal bloom presence because algal blooms occur in patches much smaller than the ground resolution of S-2 data. Nevertheless, the bare-ice albedo distribution at the scale of 20 m×20 m S-2 pixels is generally unimodal and unskewed. Conversely, bare-ice surfaces have a left-skewed albedo distribution at MODIS MOD10A1 scales. Thus, when MOD10A1 observations are used as input to energy balance modelling, meltwater production can be underestimated by ∼2 %. Our study highlights that (1) the impact of the weathering crust state is of similar importance to the direct darkening role of light-absorbing impurities upon ice albedo and (2) there is a spatial-scale dependency in albedo measurement which reduces detection of real changes at coarser resolutions.