Surface Albedo Feedback Research Articles

Sea ice feedbacks cause more greenhouse cooling than greenhouse warming at high northern latitudes on multi-century timescales

Abstract In contrast to surface greenhouse warming, surface greenhouse cooling has been less explored, especially on multi-century timescales. Here, we assess the processes controlling the pacing and magnitude of the multi-century surface temperature response to instantaneously doubling and halving atmospheric carbon dioxide concentrations in a modern global coupled climate model. Over the first decades, surface greenhouse warming is larger and faster than surface greenhouse cooling both globally and at high northern latitudes (45–90° N). Yet, this initial multi-decadal response difference does not persist. After year 150, additional surface warming is negligible, but surface cooling and sea ice expansion continues. Notably, the equilibration timescale for high northern latitude surface cooling (∼437 years) is more than double the equivalent timescale for warming. The high northern latitude responses differ most at the sea ice edge. Under greenhouse cooling, the sea ice edge slowly creeps southward into the mid-latitude oceans amplified by positive lapse rate and surface albedo feedbacks. While greenhouse warming and sea ice loss at high northern latitudes occurs on multi-decadal timescales, greenhouse cooling and sea ice expansion occurs on multi-century timescales. Overall, this work shows the importance of multi-century timescales and sea ice processes for understanding high northern latitude climate responses.

A global–land snow scheme (GLASS) v1.0 for the GFDL Earth System Model: formulation and evaluation at instrumented sites

Abstract. Snowpacks modulate water storage over extended land regions and at the same time play a central role in the surface albedo feedback, impacting the climate system energy balance. Despite the complexity of snow processes and their importance for both land hydrology and global climate, several state-of-the-art land surface models and Earth System Models still employ relatively simple descriptions of the snowpack dynamics. In this study we present a newly-developed snow scheme tailored to the Geophysical Fluid Dynamics Laboratory (GFDL) land model version 4.1. This new snowpack model, named GLASS (Global LAnd–Snow Scheme), includes a refined and dynamical vertical-layering snow structure that allows us to track the temporal evolution of snow grain properties in each snow layer, while at the same time limiting the model computational expense, as is necessary for a model suited to global-scale climate simulations. In GLASS, the evolution of snow grain size and shape is explicitly resolved, with implications for predicted bulk snow properties, as they directly impact snow depth, snow thermal conductivity, and optical properties. Here we describe the physical processes in GLASS and their implementation, as well as the interactions with other surface processes and the land–atmosphere coupling in the GFDL Earth System Model. The performance of GLASS is tested over 10 experimental sites, where in situ observations allow for a comprehensive model evaluation. We find that when compared to the current GFDL snow model, GLASS improves predictions of seasonal snow water equivalent, primarily as a consequence of improved snow albedo. The simulated soil temperature under the snowpack also improves by about 1.5 K on average across the sites, while a negative bias of about 1 K in snow surface temperature is observed.

Impacts of Atlantic meridional overturning circulation weakening on Arctic amplification

Enhanced warming of the Arctic region relative to the rest of the globe, known as Arctic amplification, is caused by a variety of diverse factors, many of which are influenced by the Atlantic meridional overturning circulation (AMOC). Here, we quantify the role of AMOC changes in Arctic amplification throughout the twenty-first century by comparing two suites of climate model simulations under the same climate change scenario but with two different AMOC states: one with a weakened AMOC and another with a steady AMOC. We find that a weakened AMOC can reduce annual mean Arctic warming by 2 °C by the end of the century. A primary contributor to this reduction in warming is surface albedo feedback, related to a smaller sea ice loss due to AMOC slowdown. Another major contributor is the changes in ocean heat uptake. The weakened AMOC and its associated anomalous ocean heat transport divergence lead to increased ocean heat uptake and surface cooling. These two factors are inextricably linked on seasonal timescales, and their relative importance for Arctic amplification can vary by season. The weakened AMOC can also abate Arctic warming via lapse rate feedback, creating marked cooling from the surface to lower-to-mid troposphere while resulting in relatively weaker cooling in the upper troposphere. Additionally, the weakened AMOC increases the low-level cloud fraction over the North Atlantic warming hole, causing significant cooling there via shortwave (sw) cloud feedback despite the overall effect of sw cloud feedback being a slight warming of the average temperature over the Arctic.

Quantifying Changes in the Arctic Shortwave Cloud Radiative Effects

AbstractThe shortwave cloud radiative effect (SWCRE) is important for the Arctic surface radiation budget and is a major source of inter‐model spread in simulating Arctic climate. To better understand the individual contributions of various radiative processes to changes in SWCRE, we extend the existing Approximate Partial Radiative Perturbation (APRP) method by adding the absorptivity for the upward beam, considering differences in reflectivity between upward and downward beams, and analyzing the cloud masking effect resulting from changes in surface albedo. Using data from CMIP model experiments, the study decomposes the SWCRE over the Arctic surface and analyzes inter‐model differences in quadrupled CO2 simulations. The study accounts for the influence of surface albedo, cloud amount, and cloud microphysics in the response of SWCRE to Arctic warming. In the sunlit season, CMIP models exhibit a strong, negative SWCRE with a large inter‐model spread. Arctic clouds dampen the surface albedo feedback by reflecting incoming solar radiation and further decrease the shortwave radiation reflected by surface, a fraction of which is scattered back to the surface by clouds. Specifically, this accounts for the majority of the inter‐model spread in SWCRE. In addition, increased (decreased) cloud amount and cloud liquid water reduce (increase) incoming shortwave fluxes at the surface, but they are found to be not critical to the Arctic surface radiation budget and its inter‐model variation. Overall, the extended APRP method offers a useful tool for analyzing the complex interactions between clouds and radiative processes, accurately decomposes the individual SWCRE responses at the Arctic surface.

Extreme summer temperature anomalies over Greenland largely result from clear-sky radiation and circulation anomalies

The polar regions have been undergoing amplified warming in recent years. In particular, Greenland has experienced anomalously warm summers with intense melt rates. We employ a surface radiation budget framework to examine the causes for positive and negative summer temperature anomaly events over Greenland from 1979 to 2021. We found a dominant contribution of the clear-sky downwelling longwave radiation and the surface albedo feedback to temperature anomalies. Atmospheric temperature perturbations dominate the effect of anomalous emissivity on clear-sky downwelling longwave radiation. In warm years, enhanced turbulent heat exchange due to increased surface temperature and diabatic warming in the troposphere induces adiabatic heating of the atmosphere, enhanced moisture advection, and a high-pressure anomaly with a blocking-like anti-cyclonic circulation anomaly following peak temperature days. Different modes of natural climate variability, in particular, related to blocking over Greenland, can further amplify or dampen the ongoing warming trend, causing extreme temperature events.

Elevation-dependent warming: observations, models, and energetic mechanisms

Abstract. Observational data and numerical models suggest that, under climate change, elevated land surfaces warm faster than non-elevated ones. Proposed drivers of this “elevation-dependent warming” (EDW) include surface albedo and water vapour feedbacks, the temperature dependence of longwave emission, and aerosols. Yet the relative importance of each proposed mechanism both regionally and at large scales is unclear, highlighting an incomplete physical understanding of EDW. Here we expand on previous regional studies and use gridded observations, atmospheric reanalysis, and a range of climate model simulations to investigate EDW over the historical period across the tropics and subtropics (40° S to 40° N). Observations, reanalysis, and fully coupled models exhibit annual mean warming trends (1959–2014), binned by surface elevation, which are larger over elevated surfaces and broadly consistent across datasets. EDW varies by season, with stronger observed signals in local winter and autumn. Analysis of large ensembles of single-forcing simulations (1959–2005) suggests historical EDW is likely a forced response of the climate system rather than an artefact of internal variability and is primarily driven by increasing greenhouse gas concentrations. To gain quantitative insight into the mechanisms contributing to large-scale EDW, a forcing–feedback framework based on top-of-atmosphere energy balance is applied to the fully coupled models. This framework identifies the Planck and surface albedo feedbacks as being robust drivers of EDW (i.e. enhancing warming over elevated surfaces), with energy transport by the atmospheric circulation also playing an important role. In contrast, water vapour and cloud feedbacks along with weaker radiative forcing in elevated regions oppose EDW. Implications of the results for understanding future EDW are discussed.

Surface Albedo Feedback, Seasonal Heat Storage and Meridional Heat Transport Determine the Seasonality of Recent Warming in Antarctica

AbstractThe reanalysis data suggest that recent surface warming over Antarctica start in 2016. In this study, using reanalysis data and numerical simulations, I attempt to determine the important mechanisms accounting for seasonal surface warming in Antarctica. The results suggested that seasonal surface warming in Antarctica is mainly determined by the surface energy budget over the Antarctic via horizontal heat advection. The surface energy budget anomaly over the Antarctic, which is mainly determined by anomalous solar radiation absorption, anomalous ocean heat content, and anomalous meridional atmospheric heat transport (AHT), is triggered by Antarctic sea‐ice loss and thus determines the observational seasonality of recent warming in Antarctica via surface horizontal heat advection. In austral summer (December–January–February), additional solar radiation absorption induced by sea‐ice loss and additional AHT from lower latitudes increase the energy budget over the Antarctic. Surface warming, more longwave radiation, and additional energy stored in the upper (deeper) ocean for short (long) time periods explain the additional energy sinks. During austral autumn‐winter (March–August), additional seasonal heat storage (SHS; mainly stored in the upper ocean) is released to the atmosphere and warms the surface. Although the AHT anomaly contributes similarly to the solar radiation absorption/SHS anomaly during April–August, the poleward AHT largely decreased in June due to the weaker eddy activity induced by strong warming at Southern Hemisphere midlatitudes, which counteracts the additional SHS release and cools the Antarctic(a).

Sensitivity of Arctic Surface Temperature to Including a Comprehensive Ocean Interior Reflectance to the Ocean Surface Albedo Within the Fully Coupled CESM2

AbstractAlmost all current climate models simplify the ocean surface albedo (OSA) by assuming the reflected solar energy without the ocean interior contribution. In this study, an improved ocean surface albedo scheme is incorporated into the Community Earth System Model version 2 (CESM2) to assess the sensitivity of Arctic surface temperature to including ocean interior reflectance to the OSA. Fully coupled CESM2 simulations with and without ocean interior reflectance are subsequently performed, we focus on the analysis of Arctic surface temperature responses. Incorporating ocean interior reflectance increases absorbed solar radiation and warms the ocean, enhancing seasonal heat storage and release across the Arctic Ocean, and increasing sea ice reduction and positive climate feedbacks that elevates Arctic surface temperature. Seasonal variations in air‐surface temperature differences induce changes in turbulent heat flux patterns, concurrently modifying dynamic advection and moisture processes that affect boundary layer humidity and low clouds, especially in winter. Based on partitioning physical processes in the thermodynamic energy equation, surface air warming is induced primarily through positive heating anomalies of vertical advection, latent heat release, and longwave radiative forcing. Through an examination of the surface energy budget, skin temperature warming is driven predominantly by increased downward longwave radiation, positive surface albedo feedback in summer, and increased conductive heat transport from the ocean particularly in winter. Significant effects of ocean interior reflectance on the Arctic Ocean, including sea surface warming and sea ice reduction, justify the importance of ocean interior reflectance in climate models for better understanding of ongoing Arctic climate changes.

A colorful look at climate sensitivity

Abstract. The radiative response to warming and to changing concentrations of CO2 is studied in spectral space. If, at a particular wavenumber, the emission temperature of the constituent controlling the emission to space does not change its emission temperature, as is the case when water vapor adopts a fixed relative humidity in the troposphere or for CO2 emissions in the stratosphere, spectral emissions become independent of surface temperature, giving rise to the idea of spectral masking. This way of thinking allows one to derive simple, physically informative, and surprisingly accurate expressions for the clear-sky radiative forcing, the radiative response to warming, and hence climate sensitivity. Extending these concepts to include the effects of clouds leads to the expectation that (i) clouds dampen the clear-sky response to forcing; (ii) diminutive clouds near the surface, which are often thought to be unimportant, may be effective at enhancing the clear-sky sensitivity over deep moist tropical boundary layers; (iii) even small changes in high clouds over deep moist regions in the tropics make these regions radiatively more responsive to warming than previously believed; and (iv) spectral masking by clouds may contribute substantially to polar amplification. The analysis demonstrates that the net effect of clouds on warming is ambiguous, if not moderating, justifying the assertion that the clear-sky (fixed relative humidity) climate sensitivity – which, after accounting for surface albedo feedbacks, we estimate to be about 3 K – provides a reasonable prior for Bayesian updates accounting for how clouds are distributed, how they might change, and deviations associated with changes in relative humidity with temperature. These effects are best assessed by quantifying the distribution of clouds and water vapor and how they change in temperature rather than geographic space.

Mechanisms of Tibetan Plateau Warming Amplification in Recent Decades and Future Projections

Abstract Earth’s surface warming by external forcing depends on location. Warming amplification, or greater surface warming than the global average, occurs in the Arctic and high-elevation regions, including the Tibetan Plateau (TP). We examined the major drivers of TP warming amplification in recent decades (1979–2020) and under future climate scenarios (2061–2100) by applying local energy budget diagnosis of multiple radiative kernels based on state-of-the-art reanalysis datasets and coupled model simulations. From 1979 to 2020, both the snow–albedo feedback and cloud–radiation feedback strongly affected the seasonality of TP warming (summer vs winter). Snow cover and albedo decreased significantly in winter but showed only small changes in summer. TP total and low-level cloud cover increased in summer, causing cooling, and decreased in winter, causing warming. During winter, TP warming amplification (1.84 from 1979 to 2020) is weaker than Arctic amplification (3.64) because the positive contribution of the surface albedo feedback to TP warming is not as strong as the dual warming effects of the lapse rate feedback and surface heat flux observed in the Arctic. Our attribution analyses based on the preindustrial control (piControl) and Historical simulations of phase 6 of the Coupled Model Intercomparison Project confirmed that TP warming is caused by external forcing. Because the external forcing associated with anthropogenic activity is increasing, TP warming will continue to the end of the twenty-first century. Under likely future warming scenarios, winter TP warming amplification is still less than in the Arctic due to the effects of the lapse rate feedback and surface heat flux. Significance Statement Over the Tibetan Plateau, warming amplification, which refers to greater surface warming than the global average (∼75% more warming than the global average from 1979 to 2020), has resulted in melting permafrost, retreating glaciers, and decreasing biodiversity. This study quantified the relative effects of eight physical processes on the warming amplification over the Tibetan Plateau. In the boreal winter, the reduction in snow cover and albedo are the leading contributors (about 49%) to Tibetan Plateau warming, meaning that melting snow exposes darker ground that absorbs more sunlight than snow does. In a warmer future climate, continued melting snow cover is projected to further enhance Tibetan Plateau warming amplification.

Data for paper "Surface Albedo Feedback, Seasonal Heat Storage and Meridional Heat Transport Determine the Seasonality of Recent Antarctica Warming"

data for paper "Surface Albedo Feedback, Seasonal Heat Storage and Meridional Heat Transport Determine the Seasonality of Recent Antarctica Warming"

The role of the Southern Ocean in the global climate response to carbon emissions.

The effect of the Southern Ocean on global climate change is assessed using Earth system model projections following an idealized 1% annual rise in atmospheric CO2. For this scenario, the Southern Ocean plays a significant role in sequestering heat and anthropogenic carbon, accounting for 40% ± 5% of heat uptake and 44% ± 2% of anthropogenic carbon uptake over the global ocean (with the Southern Ocean defined as south of 36°S). This Southern Ocean fraction of global heat uptake is however less than in historical scenarios with marked hemispheric contrasts in radiative forcing. For this idealized scenario, inter-model differences in global and Southern Ocean heat uptake are strongly affected by physical feedbacks, especially cloud feedbacks over the globe and surface albedo feedbacks from sea-ice loss in high latitudes, through the top-of-the-atmosphere energy balance. The ocean carbon response is similar in most models with carbon storage increasing from rising atmospheric CO2, but weakly decreasing from climate change with competing ventilation and biological contributions over the Southern Ocean. The Southern Ocean affects a global climate metric, the transient climate response to emissions, accounting for 28% of its thermal contribution through its physical climate feedbacks and heat uptake, and so affects inter-model differences in meeting warming targets. This article is part of a discussion meeting issue 'Heat and carbon uptake in the Southern Ocean: the state of the art and future priorities'.

Multiple Equilibria in a Coupled Climate–Carbon Model

Abstract Multiple stable equilibria are intrinsic to many complex dynamical systems, and have been identified in a hierarchy of climate models. Motivated by the idea that the Quaternary glacial–interglacial cycles could have resulted from orbitally forced transitions between multiple stable states mediated by internal feedbacks, this study investigates the existence and mechanisms of multiple equilibria in an idealized, energy-conserving atmosphere–ocean–sea ice general circulation model with a fully coupled carbon cycle. Four stable climates are found for identical insolation and global carbon inventory: an ice-free Warm climate, two intermediate climates (Cold and Waterbelt), and a fully ice-covered Snowball climate. A fifth state, a small ice cap state between Warm and Cold, is found to be barely unstable. Using custom radiative kernels and a thorough sampling of the model’s internal variability, three equilibria are investigated through the state dependence of radiative feedback processes. For fast feedbacks, the systematic decrease in surface albedo feedback from Cold to Warm states is offset by a similar increase in longwave water vapor feedback. At longer time scales, the key role of the carbon cycle is a dramatic lengthening of the adjustment time comparable to orbital forcings near the Warm state. The dynamics of the coupled climate–carbon system are thus not well separated in time from orbital forcings, raising interesting possibilities for nonlinear triggers for large climate changes. Significance Statement How do carbon cycle and other physical processes affect the physical and mathematical properties of the climate system? We use a complex climate model coupled with a carbon cycle to simulate the climate evolution under different initial conditions. Four stable climate states are possible, from the Snowball Earth, in which ice covers the whole planet, to the Warm state, an ice-free world. The carbon cycle drives the global climate change at an extremely slower pace after sea ice retreats. Sea ice and water vapor, on the other hand, constitute the major contributing factors that accelerate faster climate change.

Drivers of elevation-dependent warming over the Tibetan Plateau

The response of the warming magnitude over the Tibetan Plateau (TP; elevation ≥ 3000 m) to global climate change is not spatially uniform. Rather, it enhances with elevation, referred to as elevation-dependent warming (EDW). The degree of EDW over the TP is season-dependent, with the largest amplitude of 0.21°C km −1 observed during boreal winter. Several factors have been proposed in previous studies as possible drivers of TP EDW, but the relative importance of these factors has been less studied. To quantitatively identify the major drivers of TP EDW in winter over recent decades (1979–2018), the authors applied the radiative kernels diagnostic method with several datasets. The results robustly suggest that, the surface albedo feedback associated with changes in snow cover plays the leading role in TP EDW. Observations show that the snow cover has reduced significantly over regions with high elevation during the winters of the past four decades, leading to reductions in outgoing shortwave radiation and thus EDW. 摘要 青藏高原 (海拔≥ 3000 m 地区) 对全球气候变化的变暖响应是空间不均匀的, 其增温幅度会随着海拔升高而增大, 被称为海拔依赖性增温. 青藏高原海拔依赖性增温具有季节依赖性, 在冬季最为显著, 达0.21°C km −1 . 在以往的研究中, 众多因素被认为是青藏高原海拔依赖性增温的可能驱动因素, 但关于这些因素相对重要性的研究较少. 基于多个数据集, 本文应用辐射核 (radiative kernel) 技术方法定量诊断了近几十年 (1979–2018年) 冬季不同物理过程对青藏高原海拔依赖性增温的贡献. 结果表明, 与积雪变化相关的地表反照率反馈在其中起主导作用. 观测数据分析显示, 在过去40年的冬季，高海拔地区的积雪覆盖率显著减少, 导致地表反射的短波辐射减少, 从而促进了海拔依赖性增温.

Understanding model spread in sea ice volume by attribution of model differences in seasonal ice growth and melt

Abstract. Arctic sea ice is declining rapidly, but predictions of its future loss are made difficult by the large spread both in present-day and in future sea ice area and volume; hence, there is a need to better understand the drivers of model spread in sea ice state. Here we present a framework for understanding differences between modelled sea ice simulations based on attributing seasonal ice growth and melt differences. In the method presented, the net downward surface flux is treated as the principal driver of seasonal sea ice growth and melt. An energy balance approach is used to estimate the pointwise effect of model differences in key Arctic climate variables on this surface flux and hence on seasonal sea ice growth and melt. We compare three models with very different historical sea ice simulations: HadGEM2-ES, HadGEM3-GC3.1 and UKESM1.0. The largest driver of differences in ice growth and melt between these models is shown to be the ice area in summer (representing the surface albedo feedback) and the ice thickness distribution in winter (the thickness–growth feedback). Differences in snow and melt pond cover during the early summer exert a smaller effect on the seasonal growth and melt, hence representing the drivers of model differences in both this and in the sea ice volume. In particular, the direct impacts on sea ice growth and melt of differing model parameterisations of snow area and of melt ponds are shown to be small but non-negligible.

Cloud and Surface Albedo Feedbacks Reshape 21st Century Warming in Successive Generations of An Earth System Model

AbstractThe relative importance of radiative feedbacks and emissions scenarios in controlling surface warming patterns is challenging to quantify across model generations. We analyze three variants of the Community Earth System Model (CESM) with differing equilibrium climate sensitivities under identical CMIP5 historical and high‐emissions scenarios. CESM1, our base model, exhibits Arctic‐amplified warming with the least warming in the Southern Hemisphere middle latitudes. A variant of CESM1 with enhanced extratropical shortwave cloud feedbacks shows slightly increased late‐21st century warming at all latitudes. In the next‐generation model, CESM2, global‐mean warming is also slightly greater, but the warming is zonally redistributed in a pattern mirroring cloud and surface albedo feedbacks. However, if the nominally equivalent CMIP6 scenario is applied to CESM2, the redistributed warming pattern is preserved, but global‐mean warming is significantly greater. These results demonstrate how model structural differences and scenario differences combine to produce differences in climate projections across model generations.

Arctic Climate Feedbacks in ERA5 Reanalysis: Seasonal and Spatial Variations and the Impact of Sea‐Ice Loss

AbstractRadiative climate feedbacks in the Arctic have been extensively studied, but their spatial and seasonal variations have not been thoroughly examined. Using ERA5 reanalysis data, we examine seasonal variations in Arctic climate feedbacks and their relationship to sea‐ice loss based on changes from 1950–1979 to 1990–2019. The spring and summer seasons experienced large sea‐ice loss, strong surface albedo feedback, and large oceanic heat uptake. Arctic clouds exerted small net cooling in May‐June‐July but moderate warming during the cold season, especially over areas with large sea‐ice loss where cloud liquid and ice water content increased. Arctic water vapor feedback peaked in summer but was weak and uncorrelated with sea‐ice loss. Arctic positive lapse rate feedback (LRF) was strongest in winter over areas with large sea‐ice loss and weak inversion but uncorrelated with atmospheric stability, suggesting that oceanic heating from sea‐ice loss led to enhanced surface warming and the positive LRF.

Green Sahara tipping points in transient climate model simulations of the Holocene

The ‘Greening’ and subsequent desertification of the Sahara during the early to mid-Holocene is a dramatic example of natural climate change. We analyse a suite of simulations with a newly palaeo-conditioned configuration of the HadCM3 coupled model that is able to capture an abrupt desertification of North Africa during this time. We find that this model crosses a threshold of moisture availability for vegetation at around 6000 years before present. The resultant rapid reduction in vegetation cover acts to reduce precipitation through moisture recycling and surface albedo feedbacks. Precursor drying events which are not directly forced also indicate that the model is close to a critical moisture level. Similar precursor-like events appear in a Holocene record from the East of the continent, hinting that the natural system may resemble some of the properties of this model simulation. The overall response is not fundamentally altered by the inclusion of solar irradiance variations or volcanic eruptions. The simulated timing of the abrupt transition is mostly controlled by orbital forcing and local positive feedbacks, but it is also modulated to some extent by the state of the atmosphere and ocean. Comparisons with proxy records across North Africa show good agreement with the model simulations, although the simulations remain overly dry in the East. Overall, a threshold response may present a useful model of the real transition, but more high-resolution palaeoclimate records would help to discriminate among the predictions of climate models.

Observational Constraint on the Contribution of Surface Albedo Feedback to the Amplified Tibetan Plateau Surface Warming

AbstractSurface albedo feedback (SAF) is one of the main causes of amplified warming over the Tibetan Plateau (TP). Several recent studies have used the latest reanalysis datasets to evaluate the SAF induced warming, but without fully considering the fidelity of the surface albedo change and surface downward solar radiation in the reanalysis datasets, which directly affect the amplitude of SAF induced warming. This study finds that the state‐of‐the‐art reanalysis datasets (ERA‐Interim, ERA5, MERRA, MERRA‐2, JRA‐55 and CRA) and climate models that participated in the Coupled Model Intercomparison Project Phase 6 (CMIP6) exhibit varying biases compared with observations in both surface albedo change and surface downward solar radiation over the TP. The state‐of‐the‐art reanalysis datasets present no obvious advantages over the lower resolution but less constrained CMIP6 multi‐model ensemble in representing SAF related processes over the TP. The surface albedo change drives most of the spread in SAF induced warming. The reanalysis datasets and CMIP6 climate models reveal a significant linear relationship between surface albedo change and its contribution to surface temperature change over the TP. Using the observation constrained linear relationship and satellite surface albedo products, the spread of warming contribution due to SAF in reanalysis datasets and climate models is greatly reduced, the estimated TP warming due to SAF is in the range of 0.26–0.50 K in winter and 0.27–0.77 K in spring over recent decades.

Impact of stratospheric aerosol intervention geoengineering on surface air temperature in China: a surface energy budget perspective

Abstract. Stratospheric aerosol intervention (SAI) geoengineering is a proposed scheme to counteract anthropogenic global warming, but the climate response to SAI, with great regional disparities, remains uncertain. In this study, we use Geoengineering Model Intercomparison Project G4 experiment simulations from six models that counteract anthropogenic forcing under medium–low emissions (Representative Concentration Pathway 4.5 – RCP4.5) by injecting a certain amount of SO2 into the stratosphere every year to investigate the surface air temperature response to SAI geoengineering over China. We have found that SAI has led to surface cooling over China during the last 40 years of injection simulation (2030–2069), which varies among models, regions, and seasons. Decreased tropospheric temperature and water vapor and increased stratospheric aerosols induce robust decreases in downward clear-sky longwave and shortwave radiation fluxes at the surface, respectively, dominating the temperature change over China. Changes in cloud effective forcing and surface albedo feedback also relate to the temperature response but with large spatial and seasonal variations. We find that the increased summer cloud cover and winter surface albedo lead to strong cooling, while the decreased summer cloud cover and winter surface albedo lead to weak cooling or even insignificant warming for the certain subregions and models. Our results suggest that cloud and land surface processes in models dominate the spatial pattern of SAI-induced surface air temperature change over China.