Ice-albedo Feedback Research Articles

Unveiling the Indian Ocean forcing on winter eastern warming – western cooling pattern over North America

While the tropical Pacific teleconnection to North America has been studied extensively, the impact of the Indian Ocean on North American climate has received less attention. Here, through observational analysis and hierarchy atmospheric model simulations with different complexity, we find that the Indian Ocean plays a crucial role in North American winter climate through a teleconnection termed the Indian Ocean - North America pattern. We show that in the warm Indian Ocean phase, this teleconnection contributes to anomalously cold winters along the west coast of the United States through advection with increased mountain snowfall, while simultaneously leading to warmer conditions over the Great Lakes region. Snow-albedo feedback amplifies these Rossby wave-induced surface anomalies. Remarkably, this teleconnection pattern is at work on both interannual and multi-decadal time scales, with its climatic impact being slightly less pronounced than that induced by tropical Pacific sea surface temperature anomalies. Our findings underscore the significance of the Indian Ocean in both the prediction and future projection of North American climate.

Contrasting the Penultimate Glacial Maximum and the Last Glacial Maximum (140 and 21 ka) using coupled climate–ice sheet modelling

Abstract. The configuration of the Northern Hemisphere ice sheets during the Penultimate Glacial Maximum differed to the Last Glacial Maximum. However, the reasons for this are not yet fully understood. These differences likely contributed to the varied deglaciation pathways experienced following the glacial maxima and may have had consequences for the interglacial sea level rise. To understand the differences between the North American Ice Sheet at the Last and Penultimate glacial maxima (21 and 140 ka), we perform two perturbed-physics ensembles of 62 simulations using a coupled atmosphere–ice sheet model, FAMOUS-ice, with prescribed surface ocean conditions, in which the North American and Greenland ice sheets are dynamically simulated with the Glimmer ice sheet model. We apply an implausibility metric to find ensemble members that match reconstructed ice extent and volumes at the Last and Penultimate glacial maxima. We use a resulting set of “plausible” parameters to perform sensitivity experiments to decompose the role of climate forcings (orbit, greenhouse gases) and initial conditions on the final ice sheet configurations. This confirms that the initial ice sheet conditions used in the model are extremely important in determining the difference in final ice volumes between both periods due to the large effect of the ice–albedo feedback. In contrast to evidence of a smaller Penultimate North American Ice Sheet, our results show that the climate boundary conditions at these glacial maxima, if considered in isolation, imply a larger Penultimate Glacial Maximum North American Ice Sheet than at the Last Glacial Maximum by around 6 m sea level equivalent. This supports the notion that the growth of the ice sheet prior to the glacial maxima is key in explaining the differences in North American ice volume.

Synergistic atmosphere-ocean-ice influences have driven the 2023 all-time Antarctic sea-ice record low

Antarctic sea ice extent (SIE) reached a new record low in February 2023. Here we examine the evolution of the coupled ocean-atmosphere-sea ice system during the 12 months preceding the record. The impact of preceding conditions is assessed with observations, reanalyses, and output from the regional ocean-sea ice coupled model NEMO3.6-LIM3. We find that the 2022-2023 sea ice annual cycle was characterized by consistently low SIE throughout the year, anomalously rapid sea ice retreat in December 2022, and nearly circumpolar negative SIE anomalies in February 2023. While advection-induced positive air temperature anomalies inhibited the sea ice growth in most regions, strong southerly winds in the Amundsen-Ross Sea caused by an anomalously deep Amundsen Sea Low in spring transported notable volumes of sea ice northward, triggering an unusually active ice-albedo feedback onshore and favoring accelerated melt towards the minimum. This study highlights the impacts of multifactorial processes during the preceding seasons to explain the recent summer sea ice minima.

Climatic Effects of Ocean Salinity on M Dwarf Exoplanets

Ocean salinity is known to dramatically affect the climates of Earth-like planets orbiting Sun-like stars, with high salinity leading to less ice and higher surface temperature. However, how ocean composition impacts climate under different conditions, such as around different types of stars or at different positions within the habitable zone, has not been investigated. We used ROCKE-3D, an ocean-atmosphere general circulation model, to simulate how planetary climate responds to ocean salinities for planets with G-star versus M dwarf hosts at several stellar fluxes. We find that increasing ocean salinity from 20 to 100 g kg−1 in our model results in nonlinear ice reduction and warming on G-star planets, sometimes causing abrupt transitions to different climate states. Conversely, sea ice on M dwarf planets responds more gradually and linearly to increasing salinity. Moreover, reductions in sea ice on M dwarf planets are not accompanied by significant surface warming as on G-star planets. High salinity can modestly bolster the resilience of M dwarf planets against snowball glaciation and allow these planets to retain surface liquid water further from their host star, but the effects are muted compared to G-star planets that experience snowball bifurcation and climate hysteresis due to the ice-albedo feedback.

Earth's Sea Ice Radiative Effect From 1980 to 2023

AbstractSea ice cools Earth by reducing its absorbed solar energy. We combine radiative transfer modeling with satellite‐derived surface albedo, sea ice, and cloud distributions to quantify the top‐of‐atmosphere sea ice radiative effect (SIRE). Averaged over 1980–2023, Arctic and Antarctic SIREs range from −0.64 to −0.86 W m−2 and −0.85 to −0.98 W m−2, respectively, with different cloud data sets and assumptions of climatological versus annually‐varying clouds. SIRE trends, however, are relatively insensitive to these assumptions. Arctic SIRE has weakened quasi‐linearly at a rate of 0.04–0.05 W m−2 decade−1, implying a 21%–27% reduction in the reflective power of Arctic sea ice since 1980. Antarctic sea ice exhibited a regime change in 2016, resulting in 2016–2023 Antarctic and global SIRE being 0.08–0.12 and 0.22–0.27 W m−2 weaker, respectively, relative to 1980–1988. Global sea ice has therefore lost 13%–15% of its planetary cooling effect since the early/mid 1980s, and the implied global sea ice albedo feedback is 0.24–0.38 W m−2 K−1.

Northern hemisphere land-atmosphere feedback from prescribed plant phenology in CESM

Abstract Plant phenology influences both the terrestrial carbon cycle and land-atmosphere interactions, and therefore can potentially modify large-scale circulations in the atmosphere. However, considerable discrepancies are present among models and between model simulations and observations of plant phenology, adding large uncertainties to future climate projections. Here we modified plant phenology in the Northern Hemisphere in the Community Earth System Model and conducted simulations to characterize how differences in plant phenology influence land-atmosphere coupling. Plant phenology changes the land surface and land-atmosphere interactions by directly modulating absorbed solar radiation and evapotranspiration and indirectly modifying cloud feedback and snow-albedo feedback. Over the Northern Hemisphere, the largest effects occur from March to June when seasonal deciduous phenology is modified from satellite-derived values to model simulations, which results in a >3K increase in surface temperature that propagates to 500hPa (~5km height). Phenology-induced changes in canopy evapotranspiration and surface temperature depend on soil moisture availability during the growing season. Surface temperature decreases significantly due to increasing latent heat flux and cloud reflection where soil moisture is abundant, while soil moisture control over evapotranspiration increases and surface temperature remains little-changed or even increases in more arid regions. Characterizing the influence of phenology on biogeophysical processes is critical, as significant impacts are present both at the land surface and in the atmospheric layers above.

Nonstationary thermodynamic and dynamic contributions to the interannual variability of winter sea ice growth in the Kara–Laptev Seas

The Kara–Laptev Seas (KLS), known as the ‘Ice Factory of the Arctic’, witnesses rising instead of falling winter sea ice growth (WSIG) under the shrinkage of Arctic ice. However, knowledge of the large year-to-year variation is still unclear. Combining a seasonal ice concentration budget, a composite analysis, and a typical case study, we study both the interannual variability of WSIG in the KLS and the associated air-sea forcings during 1985–2021. Results quantitatively reveal that, during 1985–2021, thermodynamic melt in the melting season (April–August) contributed 80.3% to the interannual ice loss difference and promoted the subsequent WSIG by the recovery mechanism in the KLS. This consistent thermodynamic melt is caused by the strengthened summer Beaufort High, transporting heat and introducing a locally positive ice-albedo feedback. However, since 2010, the dynamic growth during the freezing season (October–February) has increasingly stimulated the WSIG. Typical cases in 2013 and 2017 indicate that the overlying anticyclonic atmospheric regime restricts the ice drift from the KLS and contributes to the dynamic growth of 41.6% of the WSIG difference, while the turbulent-heat-induced thermodynamic growth in winter is down to 58.4%. In short, we reveal an unstable relationship between the summer ice loss and the subsequent WSIG under the background of Arctic warming. Our study points out that the distinct dynamic ice growth driven by surface winds or ocean currents during the freezing season is likely to increase in the near future, with thinner and more mobile seasonal ice predominating in the Arctic.

Atmospheric oxygenation as a potential trigger for climate cooling

Secular changes in atmospheric CO2 and consequent global climate variations, are commonly attributed to global outgassing and the efficiency of silicate weathering, which may have been linked to mountain formation, land/arc distribution, and plant colonization through geological time. Although oxidative weathering has been shown to exert a significant role in the propagation of weathering fronts through the oxidation of Fe-bearing minerals, the influence of atmospheric O2 concentration (pO2) on silicate weathering, CO2 consumption, and global climate has not been thoroughly evaluated. This study presents a numerical model aimed at estimating the effects of pO2 on the climate, considering the influence of pO2 on the regolith thickness and thus weathering duration of granitic domains. Our model simulations reveal that an increase in weathering efficiency, through deeper penetration of the oxidative weathering front in the granitic regolith, would independently introduce a steady-state climate cooling of up to ∼8 °C, in step with one-order of magnitude rise in pO2. This temperature change may have repeatedly initiated the runaway ice-albedo feedback, leading to global glacial events (e.g., Neoproterozoic Snowball Earth). Increasing granitic weathering efficiency caused by a substantial pO2 increase may also have contributed to the development of icehouse climate during the Phanerozoic.

Anthropogenic influence on the extremely low September sea ice and hot summer of 2020 over the Arctic and its future risk of occurrence

During 2020, the Arctic is marked by extremely low sea ice coverage and hot climate. September Sea Ice Extent (SIE) was about 2.3 million km2 below the 1979–2014 mean and the 2nd lowest on the 1979–2020 record, while regional summer (June–August, JJA) mean 2 m air temperature (TAS) was about 1.3 °C above the 1979–2014 mean and was the hottest on record at the time. Locally, September Sea Ice Concentration (SIC) was approximately 70% lower and JJA TAS can be as much as 6.0 °C higher than the 1979–2014 mean. Although the proximate cause for the extreme event was the continuously favorable atmospheric circulation patterns, wind conditions and ice-albedo feedback, the main objective of this paper is probabilistic extreme event attribution studies to assess the anthropogenic influence. Based on the CMIP6 multi-model ensemble products, modeled long-term trends of Arctic sea ice and TAS are consistent with observed trends when including anthropogenic forcing or greenhouse gas (GHG) forcing, while cannot exhibit observed trends with only aerosol or natural forcing. Further analysis reveals that human influence including GHG forcing has substantially increased the probability of occurrence of the 2020-like extreme events, which are rare in aerosol-only or natural-only forcing. The frequencies of 2020-like low SIE increase by 19 times with all forcing and 16 times with GHG forcing than with natural forcing. Future climate simulations under different Shared Socioeconomic Pathway (SSP) scenarios of SSP126, SSP245 and SSP585 show that the 2020-like extreme event that is currently considered rare is projected to become the norm and almost occur 1-in-1 year beyond 2041–2060. The probabilities will be approximately in the range of 0.84–1.00 for SIE and 0.76–0.99 for TAS from low emission of SSP126 to high emission of SSP585.

Sea Ice Loss, Water Vapor Increases, and Their Interactions with Atmospheric Energy Transport in Driving Seasonal Polar Amplification

Abstract The ice–albedo feedback associated with sea ice loss contributes to polar amplification, while the water vapor feedback contributes to tropical amplification of surface warming. However, these feedbacks are not independent of atmospheric energy transport, raising the possibility of complex interactions that may obscure the drivers of polar amplification, in particular its manifestation across the seasonal cycle. Here, we apply a radiative transfer hierarchy to an idealized aquaplanet global climate model coupled to a thermodynamic sea ice model. The climate responses and radiative feedbacks are decomposed into the contributions from sea ice loss, including both retreat and thinning, and the radiative effect of water vapor changes. We find that summer sea ice retreat causes winter polar amplification through ocean heat uptake and release, and the resulting decrease in dry energy transport weakens the magnitude of warming. Moreover, sea ice thinning is found to suppress summer warming and enhance winter warming, additionally contributing to winter amplification. The water vapor radiative effect produces seasonally symmetric polar warming via offsetting effects: enhanced moisture in the summer hemisphere induces the summer water vapor feedback and simultaneously strengthens the winter latent energy transport in the winter hemisphere by increasing the meridional moisture gradient. These results reveal the importance of changes in atmospheric energy transport induced by sea ice retreat and increased water vapor to seasonal polar amplification, elucidating the interactions among these physical processes.

On the effects of the timing of an intense cyclone on summertime sea-ice evolution in the Arctic

Abstract This study investigates the impacts of the timing of an extreme cyclone that occurred in August 2012 on the sea-ice volume evolution based on the Arctic Ice Ocean Prediction System (ArcIOPS). By applying a novel cyclone removal algorithm to the atmospheric forcing during 4–12 August 2012, we superimpose the derived cyclone component onto the atmospheric forcing one month later or earlier. This study finds that although the extreme cyclone leads to strong sea-ice volume loss in all runs, large divergence occurs in sea-ice melting mechanism in response to various timing of the cyclone. The extreme cyclone occurred in August, when enhanced ice volume loss is attributed to ice bottom melt primarily and ice surface melt secondarily. If the cyclone occurs one month earlier, ice surface melt dominates ice volume loss, and earlier appearance of open water within the ice zone initiates positive ice-albedo feedback, leading to a long lasting of the cyclone-induced impacts for approximately one month, and eventually a lower September ice volume. In contrast, if the cyclone occurs one month later, ice bottom melt entirely dominates ice volume loss, and the air-open water heat flux in the ice zone tends to offset ice volume loss.

Extremes of summer Arctic sea ice reduction investigated with a rare event algorithm

Various studies identified possible drivers of extremes of Arctic sea ice reduction, such as observed in the summers of 2007 and 2012, including preconditioning, local feedback mechanisms, oceanic heat transport and the synoptic- and large-scale atmospheric circulations. However, a robust quantitative statistical analysis of extremes of sea ice reduction is hindered by the small number of events that can be sampled in observations and numerical simulations with computationally expensive climate models. Recent studies tackled the problem of sampling climate extremes by using rare event algorithms, i.e., computational techniques developed in statistical physics to reduce the computational cost required to sample rare events in numerical simulations. Here we apply a rare event algorithm to ensemble simulations with the intermediate complexity coupled climate model PlaSim-LSG to investigate extreme negative summer pan-Arctic sea ice area anomalies under pre-industrial greenhouse gas conditions. Owing to the algorithm, we estimate return times of extremes orders of magnitude larger than feasible with direct sampling, and we compute statistically significant composite maps of dynamical quantities conditional on the occurrence of these extremes. We find that extremely low sea ice summers in PlaSim-LSG are associated with preconditioning through the winter sea ice-ocean state, with enhanced downward longwave radiation due to an anomalously moist and warm spring Arctic atmosphere and with enhanced downward sensible heat fluxes during the spring-summer transition. As a consequence of these three processes, the sea ice-albedo feedback becomes active in spring and leads to an amplification of pre-existing sea ice area anomalies during summer.

Predictability of the Minimum Sea Ice Extent from Winter Fram Strait Ice Area Export: Model versus Observations

Abstract Observations show predictive skill of the minimum sea ice extent (Min SIE) from late winter anomalous offshore ice drift along the Eurasian coastline, leading to local ice thickness anomalies at the onset of the melt season—a signal then amplified by the ice–albedo feedback. We assess whether the observed seasonal predictability of September sea ice extent (Sept SIE) from Fram Strait Ice Area Export (FSIAE; a proxy for Eurasian coastal divergence) is present in global climate model (GCM) large ensembles, namely the CESM2-LE, GISS-E2.1-G, FLOR-LE, CNRM-CM6-1, and CanESM5. All models show distinct periods where winter FSIAE anomalies are negatively correlated with the May sea ice thickness (May SIT) anomalies along the Eurasian coastline, and the following Sept Arctic SIE, as in observations. Counterintuitively, several models show occasional periods where winter FSIAE anomalies are positively correlated with the following Sept SIE anomalies when the mean ice thickness is large, or late in the simulation when the sea ice is thin, and/or when internal variability increases. More important, periods with weak correlation between winter FSIAE and the following Sept SIE dominate, suggesting that summer melt processes generally dominate over late-winter preconditioning and May SIT anomalies. In general, we find that the coupling between the winter FSIAE and ice thickness anomalies along the Eurasian coastline at the onset of the melt season is a ubiquitous feature of GCMs and that the relationship with the following Sept SIE is dependent on the mean Arctic sea ice thickness.

Sea-ice thermodynamics can determine waterbelt scenarios for Snowball Earth

Abstract. Snowball Earth refers to multiple periods in the Neoproterozoic during which geological evidence indicates that the Earth was largely covered in ice. A Snowball Earth results from a runaway ice–albedo feedback, but there is an ongoing debate about how the feedback stopped: with fully ice-covered oceans or with a narrow strip of open water around the Equator. The latter states are called waterbelt states and are an attractive explanation for Snowball Earth events because they provide a refugium for the survival of photosynthetic aquatic life, while still explaining Neoproterozoic geology. Waterbelt states can be stabilized by bare sea ice in the subtropical desert regions, which lowers the surface albedo and stops the runaway ice–albedo feedback. However, the choice of sea-ice model in climate simulations significantly impacts snow cover on ice and, consequently, surface albedo. Here, we investigate the robustness of waterbelt states with respect to the thermodynamical representation of sea ice. We compare two thermodynamical sea-ice models, an idealized zero-layer Semtner model, in which sea ice is always in equilibrium with the atmosphere and ocean, and a three-layer Winton model that is more sophisticated and takes into account the heat capacity of ice. We deploy the global icosahedral non-hydrostatic atmospheric (ICON-A) model in an idealized aquaplanet setup and calculate a comprehensive set of simulations to determine the extent of the waterbelt hysteresis. We find that the thermodynamic representation of sea ice strongly influences snow cover on sea ice over the range of all simulated climate states. Including heat capacity by using the three-layer Winton model increases snow cover and enhances the ice–albedo feedback. The waterbelt hysteresis found for the zero-layer model disappears in the three-layer model, and no stable waterbelt states are found. This questions the relevance of a subtropical bare sea-ice region for waterbelt states and might help explain drastically varying model results on waterbelt states in the literature.

High-resolution dynamic downscaling of historical and future climate projections over Central Asia

Climate change poses various challenges for agriculture and water management practices in Central Asia (CA). Central to these challenges are cryosphere dynamics, fragile mountain ecosystems, and ongoing natural hazards that highlight the need for robust projections of regional climate change. For the first time, dynamic downscaling was conducted in Central Asia at a spatial resolution of 5 km. This produced a regional dataset that incorporated periods between 1980 and 2000 and 2076 to 2096. Results show that dynamic downscaling significantly improves the simulation of temperature and precipitation across CA compared to General Circulation Models (GCMs) and other Regional Climate Models (RCMs) due to better representation of topography and related meteorological fields. Our analysis shows that there will be a significant warming trend in Central Asia with a projected increase of 6°C under the Shared Socioeconomic Pathway (SSP) scenario SSP5-8.5 from 2076 to 2096. Pronounced warming is detected over mountainous areas of CA from autumn to spring, which can be explained by the snow-albedo feedback. Precipitation increases are projected from winter to spring and decreases are projected from summer to autumn.

Impact-induced initiation of Snowball Earth: A model study

During the Neoproterozoic and Paleoproterozoic eras, geological evidence points to several “Snowball Earth” episodes when most of Earth’s surface was covered in ice. These global-scale glaciations represent the most marked climate changes in Earth’s history. We show that the impact winter following an asteroid impact comparable in size to the Chicxulub impact could have led to a runaway ice-albedo feedback and global glaciation. Using a state-of-the-art atmosphere-ocean climate model, we simulate the climate response following an impact for preindustrial, Last Glacial Maximum (LGM), Cretaceous-like, and Neoproterozoic climates. While warm ocean temperatures in the preindustrial and Cretaceous-like climates prevent Snowball initiation, the colder oceans of the LGM and cold Neoproterozoic climate scenarios rapidly form sea ice and demonstrate high sensitivity to the initial condition of the ocean. Given suggestions of a cold pre-Snowball climate, we argue the initiation of Snowball Earth by a large impact is a robust possible mechanism, as previously suggested by others, and conclude by discussing geologic tests.

Evaluating and Enhancing Snow Compaction Process in the Noah‐MP Land Surface Model

AbstractThe accuracy of snow density in land surface model (LSM) simulations impacts the accuracy of simulated terrestrial water and energy budgets. However, there has been little research that has focused on enhancing snow compaction in operationally used LSMs. A baseline snow simulation with the widely used Noah‐MP LSM systematically overestimates snow depth by 55 mm even after removing daily snow water equivalent (SWE) biases. To reduce uncertainties associated with snow compaction, we enhance the most sensitive Noah‐MP snow compaction parameter—the empirical parameter for compaction due to overburden (Cbd)—such that Cbd is calculated as a function of surface air temperature as opposed to a fixed value in the baseline simulation. This enhancement improves accuracy in simulated snow compaction across the majority of western U.S. (WUS) SNOTEL test sites (biases reduced at 88% of test sites), with modest bias reductions in cooler accumulation periods (biases reduced at 70% of test sites) and substantial improvements during warmer ablation periods (biases reduced at 99% of test sites). Relatively larger improvements during warm conditions are attributable to the default Cbd value being reasonable for cold temperatures (≤−5°C). Improvements in simulated snow depth and density with observations outside of the training sites and optimization periods support that the snow compaction enhancement is transferable in space and time. Differences between enhanced and baseline gridded simulations across the total WUS support that the enhancement can have important impacts on snowpack evolution, snow albedo feedback, and snow hydrology.

Cloud- and ice-albedo feedbacks drive greater Greenland Ice Sheet sensitivity to warming in CMIP6 than in CMIP5

Abstract. The Greenland Ice Sheet (GrIS) has been losing mass since the 1990s as a direct consequence of rising temperatures and has been projected to continue to lose mass at an accelerating pace throughout the 21st century, making it one of the largest contributors to future sea-level rise. The latest Coupled Model Intercomparison Project Phase 6 (CMIP6) models produce a greater Arctic amplification signal and therefore also a notably larger mass loss from the GrIS when compared to the older CMIP5 projections, despite similar forcing levels from greenhouse gas emissions. However, it is also argued that the strength of regional factors, such as melt–albedo feedbacks and cloud-related feedbacks, will partly impact future melt and sea-level rise contribution, yet little is known about the role of these regional factors in producing differences in GrIS surface melt projections between CMIP6 and CMIP5. In this study, we use high-resolution (15 km) regional climate model simulations over the GrIS performed using the Modèle Atmosphérique Régional (MAR) to physically downscale six CMIP5 Representative Concentration Pathway (RCP) 8.5 and five CMIP6 Shared Socioeconomic Pathway (SSP) 5-8.5 extreme high-emission-scenario simulations. Here, we show a greater annual mass loss from the GrIS at the end of the 21st century but also for a given temperature increase over the GrIS, when comparing CMIP6 to CMIP5. We find a greater sensitivity of Greenland surface mass loss in CMIP6 centred around summer and autumn, yet the difference in mass loss is the largest during autumn with a reduction of 27.7 ± 9.5 Gt per season for a regional warming of +6.7 ∘C and 24.6 Gt per season more mass loss than in CMIP5 RCP8.5 simulations for the same warming. Assessment of the surface energy budget and cloud-related feedbacks suggests a reduction in high clouds during summer and autumn – despite enhanced cloud optical depth during autumn – to be the main driver of the additional energy reaching the surface, subsequently leading to enhanced surface melt and mass loss in CMIP6 compared to CMIP5. Our analysis highlights that Greenland is losing more mass in CMIP6 due to two factors: (1) a (known) greater sensitivity to greenhouse gas emissions and therefore warmer temperatures and (2) previously unnotified cloud-related surface energy budget changes that enhance the GrIS sensitivity to warming.

Elevation-dependence of warming due to aerosol-induced snow darkening over the Himalayan-Tibetan region

Temperature trends over the high-altitude mountains depict an increase with elevation during recent years. These stratified warming trends observed over the Himalayan-Tibetan (HT) regions are higher than the mean warming trends observed over low-elevation regions of South and East Asia, which is attributed to several factors including snow albedo feedback, clouds and water vapor feedback. In this study, we demonstrate the effects of deposition of absorbing aerosols like black carbon and dust on snow albedo and its implications for elevation-dependent warming (EDW). Though the aerosol concentration decreases with elevation, warming due to aerosol-induced snow darkening increases with elevation. Further, surface cooling due to the direct radiative effects (DRE) of aerosols is found to decrease with elevation, which also favors higher warming at high altitudes. The effects of both the deposition of absorbing aerosols on snow albedo and the surface cooling due to the DRE of atmospheric aerosols could strengthen EDW. This study clearly shows the potential of albedo feedback due to aerosol-cryosphere interaction as one of the physical mechanisms contributing to the observed EDW over the HT region.

Assessing Climate Sensitivity and Mechanisms in a One-Dimensional Climate Energy Balance Model

Addressing the pressing concerns surrounding climate sensitivity, particularly within the context of Earth's changing climate, remains a pivotal endeavor. In this paper, the earth global temperature variation modeled by a one-dimensional climate energy balance model (EBM) is studied using a variance-based sensitivity analysis. The outcomes of this study offer a comprehensive analysis on each parameter that govern Earth's climate dynamics. Specifically, the analyses highlight that land albedo possesses the most substantial First-Order Sobol indices; the solar multiplier and the constant coefficient in the linearized Stefan-Boltzmann Law emerge as the second and third-largest contributor to Sobol indices, while the sensitivity of albedo of ice, temperature dependent coefficient of linearized Stefan-Boltzmann Law, and Transfer Coefficient remain insignificance. The analysis also suggests the non-negligible role of ice-albedo feedback and supports the hypothesis of the "Snowball Earth". This research holds significance as it uniquely addresses Earth's climate sensitivity using a one-dimensional Energy Balance Model, offering fundamental yet essential insights into the dynamics of earth's climate system, particularly its temperature variations.