Global Mean Surface Temperature Change Research Articles

Role of external forcing in the time-varying trends of global-mean surface temperature under current and future climates

The decadal-scale global-mean surface temperature (GMST) trend fluctuates between rapid-warming, slow-warming and cooling under the combined action of external forcing (EX) and internal variability. However, the principal contributors to the time-varying trends of GMST across decadal scales in current and future climates remain elusive. Here, by leveraging observations and initial-condition large ensembles, we unravel that historical GMST trend fluctuations are predominantly driven by EX on timescales exceeding ∼9 years within the current climate, with anthropogenic and volcanic aerosols being the primary drivers. However, in the warming climate, the significant contribution of EX on decadal scales is projected to decrease. This is primarily due to anthropogenic aerosol mitigation efforts and the absence of unpredictable volcanism. Despite the continuous increase in greenhouse gases, these factors are expected to delay the emergence of EX-dominance to ∼14-year timescale. Our results quantitatively underscore the pivotal role of the EX in modulating GMST trend fluctuations and its potential weakening at decadal scales in the warming climate, indicating that predicting near-term changes in GMST may become less certain in the future.

A new conceptual model ofglobaloceanheatuptake.

We formulate a new conceptual model, named "MT2", to describe global ocean heat uptake, as simulated by atmosphere-ocean general circulation models (AOGCMs) forced by increasing atmospheric CO2, as a function of global-mean surface temperature change T and the strength of the Atlantic meridional overturning circulation (AMOC, M). MT2 has two routes whereby heat reaches the deep ocean. On the basis of circumstantial evidence, we hypothetically identify these routes as low- and high-latitude. In low latitudes, which dominate the global-mean energy balance, heat uptake is temperature-driven and described by the two-layer model, with global-mean T as the temperature change of the upper layer. In high latitudes, a proportion p (about 14%) of the forcing is taken up along isopycnals, mostly in the Southern Ocean, nearly like a passive tracer, and unrelated to T. Because the proportion p depends linearly on the AMOC strength in the unperturbed climate, we hypothesise that high-latitude heat uptake and the AMOC are both affected by some characteristic of the unperturbed global ocean state, possibly related to stratification. MT2 can explain several relationships among AOGCM projections, some found in this work, others previously reported: Ocean heat uptake efficiency correlates strongly with the AMOC. Global ocean heat uptake is not correlated with the AMOC. Transient climate response (TCR) is anticorrelated with the AMOC. T projected for the late twenty-first century under high-forcing scenarios correlates more strongly with the effective climate sensitivity than with the TCR.

Tropical mountain ice core δ18O: A Goldilocks indicator for global temperature change.

Very high tropical alpine ice cores provide a distinct paleoclimate record for climate changes in the middle and upper troposphere. However, the climatic interpretation of a key proxy, the stable water oxygen isotopic ratio in ice cores (δ18Oice), remains an outstanding problem. Here, combining proxy records with climate models, modern satellite measurements, and radiative-convective equilibrium theory, we show that the tropical δ18Oice is an indicator of the temperature of the middle and upper troposphere, with a glacial cooling of -7.35° ± 1.1°C (66% CI). Moreover, it severs as a "Goldilocks-type" indicator of global mean surface temperature change, providing the first estimate of glacial stage cooling that is independent of marine proxies as -5.9° ± 1.2°C.Combined with all estimations available gives the maximum likelihood estimate of glacial cooling as -5.85° ± 0.51°C.

A transient coupled general circulation model (CGCM) simulation of the past 3 million years

Abstract. Driven primarily by variations in the earth's axis wobble, tilt, and orbit eccentricity, our planet experienced massive glacial/interglacial reorganizations of climate and atmospheric CO2 concentrations during the Pleistocene (2.58 million years ago (Ma)–11.7 thousand years ago (ka)). Even after decades of research, the underlying climate response mechanisms to these astronomical forcings have not been fully understood. To further quantify the sensitivity of the earth system to orbital-scale forcings, we conducted an unprecedented quasi-continuous coupled general climate model simulation with the Community Earth System Model version 1.2 (CESM1.2, ∼3.75∘ horizontal resolution), which covers the climatic history of the past 3 million years (3 Myr). In addition to the astronomical insolation changes, CESM1.2 is forced by estimates of CO2 and ice-sheet topography which were obtained from a simulation previously conducted with the CLIMBER-2 earth system model of intermediate complexity. Our 3 Ma simulation consists of 42 transient interglacial/glacial simulation chunks, which were partly run in parallel to save computing time. The chunks were subsequently merged, accounting for spin-up and overlap effects to yield a quasi-continuous trajectory. The computer model data were compared against a plethora of paleo-proxy data and large-scale climate reconstructions. For the period from the Mid-Pleistocene Transition (MPT, ∼1 Ma) to the late Pleistocene we find good agreement between simulated and reconstructed temperatures in terms of phase and amplitude (−5.7 ∘C temperature difference between Last Glacial Maximum and Holocene). For the earlier part (3–1 Ma), differences in orbital-scale variability occur between model simulation and the reconstructions, indicating potential biases in the applied CO2 forcing. Our model-proxy data comparison also extends to the westerlies, which show unexpectedly large variance on precessional timescales, and hydroclimate variables in major monsoon regions. Eccentricity-modulated precessional variability is also responsible for the simulated changes in the amplitude and flavors of the El Niño–Southern Oscillation. We further identify two major modes of planetary energy transport, which played a crucial role in Pleistocene climate variability: the first obliquity and CO2-driven mode is linked to changes in the Equator-to-pole temperature gradient; the second mode regulates the interhemispheric heat imbalance in unison with the eccentricity-modulated precession cycle. During the MPT, a pronounced qualitative shift occurs in the second mode of planetary energy transport: the post-MPT eccentricity-paced variability synchronizes with the CO2 forced signal. This synchronized feature is coherent with changes in global atmospheric and ocean circulations, which might contribute to an intensification of glacial cycle feedbacks and amplitudes. Comparison of this paleo-simulation with greenhouse warming simulations reveals that for an RCP8.5 greenhouse gas emission scenario, the projected global mean surface temperature changes over the next 7 decades would be comparable to the late Pleistocene glacial-interglacial range; but the anthropogenic warming rate will exceed any previous ones by a factor of ∼100.

Critical Review on Radiative Forcing and Climate Models for Global Climate Change since 1970

This review identifies a critical problem in the fundamental physics of current climate models. The large greenhouse effect of rising CO2 assumed in climate models is assessed by six key observations from ground- and satellite-based measurements. This assessment is enhanced by statistical analyses and model calculations of global or regional mean surface temperature changes by conventional climate models and by a conceptual quantum physical model of global warming due to halogen-containing greenhouse gases (halo-GHGs). The postulated large radiative forcing of CO2 in conventional climate models does not agree with satellite observations. Satellite-observed warming pattern resembles closely the atmospheric distribution of chlorofluorocarbons (CFCs). This review helps understand recent remarkable observations of reversals from cooling to warming in the lower stratosphere over most continents and in the upper stratosphere at high latitudes, surface warming cessations in the Antarctic, North America, UK, and Northern-Hemisphere (NH) extratropics, and the stabilization in NH or North America snow cover, since the turn of the century. The complementary observation of surface temperature changes in 3 representative regions (Central England, the Antarctic, and the Arctic) sheds new light on the primary mechanism of global warming. These observations agree well with not CO2-based climate models but the CFC-warming quantum physical model. The latter offers parameter-free analytical calculations of surface temperature changes, exhibiting remarkable agreement with observations. These observations overwhelmingly support an emerging picture that halo-GHGs made the dominant contribution to global warming in the late 20th century and that a gradual reversal in warming has occurred since ~2005 due to the phasing out of halo-GHGs. Advances and insights from this review may help humans make rational policies to reverse the past warming and maintain a healthy economy and ecosystem.

Why Is Climate Sensitivity for Solar Forcing Smaller than for an Equivalent CO2 Forcing?

Abstract Previous studies have shown that climate sensitivity, defined as the global mean surface temperature change per unit radiative forcing, is smaller for solar radiative forcing compared to an equivalent CO2 radiative forcing. We investigate the causes for this difference using the NCAR CAM4 model. The contributions to the climate feedback parameter, which is inversely related to climate sensitivity, are estimated for water vapor, lapse rate, Planck, albedo, and cloud feedbacks using the radiative kernel technique. The total feedback estimated for CO2 and solar radiative forcing from our model simulations is −1.23 and −1.45 W m−2 K−1, respectively. We find that the difference in feedback between the two cases is primarily due to differences in lapse rate, water vapor, and cloud feedbacks, which together explain 65% of the difference in total feedback. The rest comes from Planck and albedo feedbacks. The differences in feedbacks arise mainly from differences in the horizontal (meridional) structure of forcing and the consequent warming. Our study provides important insights into the effects of the meridional structure of forcing on climate feedback, which is important for evaluating global climate change from different forcing agents. Significance Statement An increase in atmospheric CO2 concentration or an increase in incoming solar radiation leads to a rise in the radiative budget and consequent climate warming, which is amplified by the presence of multiple climate feedbacks. These feedbacks, from changes in surface albedo, combined effect of water vapor and the vertical lapse rate of temperature, and changes in clouds, differ between solar and CO2 forcing. Using radiative kernels, this study quantifies these individual feedbacks for an equivalent radiative change caused by an increase in CO2 or incoming solar radiation, showing how the differences arise from differences in the meridional patterns of warming. In agreement with prior studies, these differences can explain the smaller efficacy of solar forcing compared to CO2 forcing.

Radiative effects of observationally constrained tropical upper-level clouds in a radiative-convective equilibrium model

Tropical upper-level clouds (TUCs) control the radiation budget in a climate system and strongly influence surface temperatures. This study examines global mean surface temperature changes due to the percent change in TUC cover, which is referred to as the tropical upper-level cloud radiative effect (TUCRE, in units of Kelvin per %). We use a radiative-convective equilibrium model that can control both upper- and lower-level cloud layers separately in three idealized regions (extratropics, tropical moist, and tropical dry regions) and two sub-regions (clear-moist and cloudy-moist regions) within the tropical moist regions. In the simulation, tropical reflectivity based on the TUC fraction assumes a primary role in determining the TUCRE. Accurate estimate of the TUCRE requires careful prescriptions according to actual satellite observations. We use the extent of TUC fraction and reflectivity obtained from 18 years (2003–2020) of satellite data on daily MODIS cloud properties. Our results show that the estimated net TUCRE ranges from 0.19 to 0.33 K/%, with a higher TUC fraction leading to higher temperatures (a warming effect) in the climate system. This means that a longwave TUCRE dominates over a shortwave TUCRE. When upper- and lower-level clouds interplay in the model, the range of the TUCRE was greater with a combination of two cloud layers, although all values were positive. The TUCRE is greater by 0.22 to 0.40 K/% when upper- and lower-level clouds are negatively coupled, because the Earth warms due to a decline in the reflectance of solar radiation. When upper- and lower-level clouds are positively coupled, the TUCRE is lower by 0.14 to 0.30 K/%, as less radiation reaches the Earth through combined cloud layers. Finally, we test the sensitivity of the TUCRE with five TUC fractions and 15 combinations of tropical reflectivity. Comparing our results with the TUCREs estimated from climate models will help us understand how TUC cover affects climate, and should greatly reduce uncertainty associated with cloud feedback.

Through an Ice Sheet, Darkly

Through an Ice Sheet, Darkly

Prescribing stratospheric chemistry overestimates southern hemisphere climate change during austral spring in response to quadrupled CO2

The interaction of stratospheric chemistry with a changing climate from an abrupt CO2 quadrupling is assessed using the coupled atmosphere–ocean Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM). Two abrupt 4 × CO2 experiments were performed, one with interactive stratospheric chemistry and the other with a prescribed stratospheric chemistry that does not simulate stratospheric ozone response to 4 × CO2. The interactive and prescribed chemistry experiments simulate similar global mean surface temperature change. Nevertheless, interactive chemistry is critical to capture the Southern Hemisphere tropospheric midlatitude jet response to 4 × CO2. When stratospheric ozone response to 4 × CO2 is neglected, GEOSCCM overestimates Southern Hemisphere tropospheric circulation change. This stratospheric chemistry-induced climate impact has large seasonal variability. During the austral spring season September–October–November (SON), prescribed chemistry yields a stronger poleward shift and intensification of the Southern Hemisphere midlatitude tropospheric jet, surface wind stress, and the Southern Ocean meridional overturning circulation than occurs with interactive chemistry. In other seasons interactive and prescribed chemistry have similar effects on the Southern Hemisphere circulation. The seasonality of stratospheric chemistry-induced climate impact is related to the seasonality of Antarctic lower stratospheric ozone response to 4 × CO2. In contrast to this stratospheric ozone response to 4 × CO2, stratospheric ozone recovery from decline of the ozone depleting substances has its largest impact on the Southern Hemisphere tropospheric circulation in austral summer (December–January–February), but no effects in SON. It is found that the different seasonality for these two stratospheric ozone layer change scenarios is related to the different seasonality of tropopause meridional temperature gradient response.

Climate change impacts on flood peaks in Britain for a range of global mean surface temperature changes

AbstractAn increase in extreme weather events is leading to increased flood occurrence and risk in many areas. Although climate mitigation strategies are being implemented, it is widely accepted that societies must adapt to climate variability and climate change. Traditional climate change impact studies have used projections for future time‐slices, often for a range of possible emissions scenarios. Recently however, there has been a move to instead consider climate change impacts relative to global mean surface temperature (GMST) change, to try to encourage action to avoid the more severe impacts from higher GMST changes. To support adaptation planning, more localised information on impacts is required. Here, data on the potential range of changes in flood peaks is generated by combining flood response surfaces and the new UK Climate Projections 2018, for every river cell on a 1 km grid across Britain, for GMST changes of 1–4.5°C. The results show significant spatial variation, with impacts typically higher in the west than the east, and generally increasing with GMST change. Some southern regions show flood peak changes accelerating with GMST change. The changes in flood peaks can be translated into changes in flood inundation and associated flood risk under alternative adaptation assumptions.

Evaluating the Nature and Extent of Changes to Climate Sensitivity Between FGOALS‐g2 and FGOALS‐g3

AbstractEquilibrium climate sensitivity (ECS) and its related feedbacks are important metrics that can be used to measure the global mean surface temperature change in future climate projections, and the cloud feedback (CF) is considered to be the main contributor to ECS uncertainties. However, the use of different CF methods significantly affects the CF amplitudes, and the sign of the CF may also change. Combining the radiative kernel approach with a simplified CF method, the differences in the ECS and associated feedbacks between two versions of the Flexible Global Ocean–Atmosphere–Land System model (i.e., FGOALS‐g2 and FGOALS‐g3) were analyzed. Results show that the ECS of FGOALS‐g3 is smaller than that of FGOALS‐g2 (2.8 vs. 3.3 K). The main feedback processes that contribute to the ECS change in FGOALS‐g3 are the weaker surface albedo feedback and stronger negative shortwave CF. The reduced surface albedo feedback in FGOALS‐g3 can be attributed mainly to the differences in the simulations of sea ice area, surface temperature, and the Atlantic Meridional Overturning Circulation, as well as their interactions, compared with FGOALS‐g2. The enhanced negative shortwave CF in FGOALS‐g3 is directly related to the strengthened feedback of cloud area fraction and liquid water path. Furthermore, these changes can be traced back to the different atmospheric moist processes, parameter tuning, ocean grid, and external forcings used in FGOALS‐g3, as these all affect the mean climate state of the model.

Detection and attribution of climate change: A deep learning and variational approach

Abstract Twelve climate models and observations are used to attribute the global mean surface temperature (GMST) changes from 1900 to 2014 to external climate forcings. The external forcings are decomposed into the effects of the well-mixed greenhouse gas concentration variation, the effects of anthropogenic aerosol concentration changes, and the effects of natural forcings. First, a convolutional neural network (CNN) is trained to estimate the simulated historical GMST from single-forcing experiments using outputs from the multi-model ensemble. We then use this CNN to solve the attribution problem using an original variational inversion approach. The variational inversion is first validated using historical climate simulations as pseudo-observations. Then we perform an inversion from observations. This provides a distribution of the GMST resulting from the three forcings. For 2014, inversions estimate that the greenhouse gases changes are responsible for a GMST anomaly within [0.8 $ {}^{\circ } $ C,1.9 $ {}^{\circ } $ C], while anthropogenic aerosols and natural forcings anomalies are within [−0.7 $ {}^{\circ } $ C,−0.1 $ {}^{\circ } $ C] and [−0.1 $ {}^{\circ } $ C,0.3 $ {}^{\circ } $ C], respectively. The method designed here can be adapted and extended to attribute the changes of other variables or to focus on the regional scale.

Similar patterns of tropical precipitation and circulation changes under solar and greenhouse gas forcing

Theory and model evidence indicate a higher global hydrological sensitivity for the same amount of surface warming to solar as to greenhouse gas (GHG) forcing, but regional patterns are highly uncertain due to their dependence on circulation and dynamics. We analyse a multi-model ensemble of idealized experiments and a set of simulations of the last millennium and we demonstrate similar global signatures and patterns of forced response in the tropical Pacific, of higher sensitivity for the solar forcing. In the idealized simulations, both solar and GHG forcing warm the equatorial Pacific, enhance precipitation in the central Pacific, and weaken and shift the Walker circulation eastward. Centennial variations in the solar forcing over the last millennium cause similar patterns of enhanced equatorial precipitation and slowdown of the Walker circulation in response to periods with stronger solar forcing. Similar forced patterns albeit of considerably weaker magnitude are identified for variations in GHG concentrations over the 20th century, with the lower sensitivity explained by fast atmospheric adjustments. These findings differ from previous studies that have typically suggested divergent responses in tropical precipitation and circulation between the solar and GHG forcings. We conclude that tropical Walker circulation and precipitation might be more susceptible to solar variability rather than GHG variations during the last-millennium, assuming comparable global mean surface temperature changes.

Suppressed Late‐20th Century Warming in CMIP6 Models Explained by Forcing and Feedbacks

AbstractFor the 1960–2000 period, the latest generation of climate models (Coupled Model Intercomparison Project Phase 6 [CMIP6]) shows less global mean surface temperature change relative to pre‐industrial than that seen in observations. In contrast, the previous generation of models (CMIP5) performed well over this period. It has been hypothesized that this suppressed late‐20th Century warming seen in CMIP6 is caused by a stronger aerosol forcing. However, we find this to be only part of the story. Not only is the aerosol forcing marginally more negative in CMIP6 compared to CMIP5, the greenhouse gas forcing in CMIP6 is also weaker than in CMIP5. These forcing differences are amplified by differences in climate sensitivity between the CMIP5 and CMIP6 ensemble, which leads to both a stronger aerosol cooling over 1960–1990 and a stronger greenhouse gas induced warming from 1990, returning the warming post‐2000 toward the observed level.

Projections of South Asian Summer Monsoon Under Global Warming from 1.5° to 5°C

AbstractThe South Asian summer monsoon (SASM) is one of the most crucial climate components in boreal summer. The future potential changes in the SASM have great importance for climate change adaption and policy setting in this populous region. To understand the SASM changes and its link with the global warming of 1.5°C to 5°C above the preindustrial level, we investigate the changes in the SASM circulation and precipitation based on a large-ensemble simulation conducted with Canadian Earth System Model version 2 (CanESM2). With the global mean surface temperature (GMST) increase, the large-ensemble mean of SASM circulation is projected to weaken almost linearly while the precipitation and precipitable water to enhance quasi-linearly. A double anticyclone along the tropical Indian Ocean is a major anomalous circulation pattern for each additional degree of warming and is responsible for the weakening of the lower-level westerlies. The decreased upper-level land-sea thermal contrast (TCupper) is the main thermal driver for the weakening of the SASM circulation while the lower-level thermal contrast contributes little. The non-linearly decreased TCupper is mainly related to the temperature response to the increased CO2 forcing and convection induced latent heat release in the tropics. The increase in the SASM precipitation is mainly due to the quasi-linearly increased positive contribution of the thermodynamic component, while the dynamic component has a negative impact. Both horizontal moisture advection and moisture convergence contribute to the precipitation increase, and moisture convergence plays a dominant role. These results provide new insight that the SASM changes can be roughly scaled by the GMST changes.

CMIP5 Intermodel Relationships in the Baseline Southern Ocean Climate System and With Future Projections

AbstractClimate models exhibit a broad range in the simulated properties of the climate system. In the early historical period, the absolute global mean surface air temperature in Coupled Model Intercomparison Project, Phase 5 (CMIP5) models spans a range of ∼12°C – 15°C. Other climate variables may be linked to global mean temperature, and so accurate representation of the baseline climate state is crucial for meaningful future climate projections. In CMIP5 baseline climate states, statistically significant intermodel correlations between Southern Ocean surface temperature, outgoing shortwave radiation, cloudiness, the position of the mid‐latitude eddy‐driven jet, and Antarctic sea ice area are found. The baseline temperature relationships extend to projected future changes in the same set of variables, impacting on the projected global mean surface temperature change. Models with initially cooler Southern Ocean tend to exhibit more global warming, and vice versa for initially warmer models. These relationships arise due to a “capacity for change”. For example, cold‐biased models tend to have more cloud cover, sea ice, and equatorward jet initially, and thus a greater capacity to lose cloud cover and sea ice, and for the jet to shift poleward under global warming. A first look at emerging data from CMIP6 reveals a shift of the relationship from the Southern Ocean towards the Antarctic region, possibly due to reductions in Southern Ocean biases, such as in westerly wind representation.

Main processes affecting global average surface temperature

<p indent=0mm>Since the industrial revolution, the greenhouse effect caused by greenhouse gas emissions has led to an increase in the net radiative forcing on the Earth’s surface, and the global mean surface temperature (GMST) has continued to rise, accompanied by multi-time scale oscillations including inter-annual decadal and multi-decadal oscillations. Changes in GMST, which reflect the integrated response of the climate system to the combination of external radiation forcing and internal natural variables, are one of the key indicators for understanding the impact of human activities on global climate change. Previous studies have basically determined the contribution of major physical modes of the global surface temperature, such as the El Niño-Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO) based on Empirical Orthogonal Function (EOF) method. In addition to the above climate modes, the physical processes affecting GMST changes also include volcanic eruptions, observation data system errors and so on. Based on the above research progress and these two basic assumptions (there is no long-term changing trend due to factors such as natural variabilities, volcanic eruption events, or system error of observation equipment; a single event does not affect the remotely related structure of the main physical mode), EOF decomposition is applied to the surface temperature of ERSST v3b and HadISST v1.1 ocean observation data in this paper, so as to obtain the TR warming trend item with ENSO, PDO and AMO removed, and thus, by using Ensemble Empirical Mode Decomposition (EEMD) method, to break down each TR time series into components on multiple different time scales and summarize them into low frequencies, high frequency and trend items. The land and ocean data (HadCRUT.4.6) are used to compare ocean data (ERSST v3b and HadISST v1.1) results and conduct a statistical analysis on the errors introduced by EMD methods. This study found that the main physical processes affecting changes in the GMST include global warming caused by the anthropogenic greenhouse gas emissions, the cooling effects caused by aerosols, the internal variables in the global climate system, the system errors caused by changes in the observing system, data noise, and other factors that have not yet been identified. Based on ERSST V3b and HadISST v1.1 observational data, this study also analyzed and determined the impact and contribution of each factor to GMST changes. This could be a key step to identify the effects of human activities and natural variability on global climate change. There are two main conclusive contributions in this paper. One contribution was to quantify the time scale and intensity of the impact of volcanic eruptions on GMST. We estimated the impact of five major volcanic eruptions since 1950 (Agung, 1963; Merapi, 1974; St. Helens, 1980; Pinatubo, 1991; Nabro, 2011). The cumulative effects of these five major volcano events in ERSST and HadISST approximately caused global warming to slow down by 0.32−0.47 and 0.45−0.67°C, respectively. Another major contribution is to find that the TR item of GMST still has a recent global warming mitigation phenomenon after the removal of the three major climate models, that is, there are some processes in the Earth’s climate system that are different from the above three physical models, which could significantly affect the TR changes. Therefore, global warming tends to slow down (warming hiatus). In modern climate conditions, anthropogenic radiative forcing continues to increase, and the heat absorbed by the global climate system continues to increase during global warming hiatus period. That is, even if the amount of heat energy used to heat up the surface of the global surface reduced, this “reduced” amount of heat still remains in the climate system, such as the mid-deep ocean. The results further underscore the necessity for understanding the critical physical processes that lead to global warming from the perspective of the energy balance of the climate system.

A novel statistical decomposition of the historical change in global mean surface temperature

According to the characteristics of forced and unforced components to climate change, sophisticated statistical models were used to fit and separate multiple scale variations in the global mean surface temperature (GMST) series. These include a combined model of the multiple linear regression and autoregressive integrated moving average models to separate the contribution of both the anthropogenic forcing (including anthropogenic factors (GHGs, aerosol, land use, Ozone, etc) and the natural forcing (volcanic eruption and solar activities)) from internal variability in the GMST change series since the last part of the 19th century (which explains about 91.6% of the total variances). The multiple scale changes (inter-annual variation, inter-decadal variation, and multi-decadal variation) are then assessed for their periodic features in the remaining residuals of the combined model (internal variability explains the rest 8.4% of the total variances) using the ensemble empirical mode decomposition method. Finally, the individual contributions of the anthropogenic factors are attributed using a partial least squares regression model.

A future perspective of historical contributions to climate change

Countries’ historical contributions to climate change have been on the agenda for more than two decades and will most likely continue to be an element in future international discussions and negotiations on climate. Previous studies have quantified the historical contributions to climate change across a range of choices and assumptions. In contrast, we quantify how historical contributions to changes in global mean surface temperature (GMST) may change in the future for a broad set of choices using the quantification of the shared socioeconomic pathways (SSPs). We calculate the contributions for five coarse geographical regions used in the SSPs. Historical emissions of long-lived gases remain important for future contributions to warming, due to their accumulation and the inertia of climate system, and historical emissions are even more important for strong mitigation scenarios. When only accounting for future emissions, from 2015 to 2100, there is surprisingly little variation in the regional contributions to GMST change between the different SSPs and different mitigation targets. The largest variability in the regional future contributions is found across the different integrated assessment models (IAMs). This suggests the characteristics of the IAMs are more important for calculated future historical contributions than variations across SSP or forcing target.

Including albedo in time‐dependent LCA of bioenergy

AbstractAlbedo change during feedstock production can substantially alter the life cycle climate impact of bioenergy. Life cycle assessment (LCA) studies have compared the effects of albedo and greenhouse gases (GHGs) based on global warming potential (GWP). However, using GWP leads to unequal weighting of climate forcers that act on different timescales. In this study, albedo was included in the time‐dependent LCA, which accounts for the timing of emissions and their impacts. We employed field‐measured albedo and life cycle emissions data along with time‐dependent models of radiative transfer, biogenic carbon fluxes and nitrous oxide emissions from soil. Climate impacts were expressed as global mean surface temperature change over time (∆T) and as GWP. The bioenergy system analysed was heat and power production from short‐rotation willow grown on former fallow land in Sweden. We found a net cooling effect in terms of ∆T per hectare (−3.8 × 10–11 K in year 100) and GWP100 per MJ fuel (−12.2 g CO2e), as a result of soil carbon sequestration via high inputs of carbon from willow roots and litter. Albedo was higher under willow than fallow, contributing to the cooling effect and accounting for 34% of GWP100, 36% of ∆T in year 50 and 6% of ∆T in year 100. Albedo dominated the short‐term temperature response (10–20 years) but became, in relative terms, less important over time, owing to accumulation of soil carbon under sustained production and the longer perturbation lifetime of GHGs. The timing of impacts was explicit with ∆T, which improves the relevance of LCA results to climate targets. Our method can be used to quantify the first‐order radiative effect of albedo change on the global climate and relate it to the climate impact of GHG emissions in LCA of bioenergy, alternative energy sources or land uses.