Warmer climate projections in CMIP6: the role of changes in the greenhouse gas concentrations from CMIP5 to CMIP6

Many modelling groups have contributed with CMIP6 scenario experiments to the CMIP6 archive. The analysis of CMIP6 future projections has started and first results indicate that CMIP6 projections are warmer than their counterparts from CMIP5. To some extent this is explained with the higher climate sensitivity of many of the new generation of climate models. However, not only have models been updated since CMIP5 but also the forcings have changed from RCPs to SSPs. The new SSPs have been designed to have the same instantaneous radiative forcing at the end of the 21st century. However, we find that in the EC-Earth3 model the effective radiative forcing differs substantially when the GHG concentrations from the SSP are replaced by those from the corresponding RCP with the same nameplate RF. We estimate that for the SSP5-8.5 and SSP2-4.5 scenarios 50% or more of the stronger warming in CMIP6 than CMIP5 for the EC-Earth model can be explained by changes in GHG gas concentrations. Other changes in the forcing datasets such as aerosols only play a minor role for the additional warming. The discrepancy between RCP and SSP forcing datasets needs to be accounted for when comparing CMIP5 and CMIP6 climate projections and should be properly conveyed to the climate impact, adaptation and mitigation communities.

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Tropospheric Adjustment Induces a Cloud Component in CO2 Forcing

Journal of Climate ◽

10.1175/2007jcli1834.1 ◽

2008 ◽

Vol 21 (1) ◽

pp. 58-71 ◽

Cited By ~ 229

Author(s):

Jonathan Gregory ◽

Mark Webb

Keyword(s):

Radiative Forcing ◽

Climate Models ◽

Surface Air Temperature ◽

Co2 Concentration ◽

Climate Feedback ◽

Climate Projections ◽

Feedback Parameter ◽

Tropospheric Adjustment ◽

Effective Radiative Forcing ◽

Global Mean

Abstract The radiative forcing of CO2 and the climate feedback parameter are evaluated in several climate models with slab oceans by regressing the annual-mean global-mean top-of-atmosphere radiative flux against the annual-mean global-mean surface air temperature change ΔT following a doubling of atmospheric CO2 concentration. The method indicates that in many models there is a significant rapid tropospheric adjustment to CO2 leading to changes in cloud, and reducing the effective radiative forcing, in a way analogous to the indirect and semidirect effects of aerosol. By contrast, in most models the cloud feedback is small, defined as the part of the change that evolves with ΔT. Comparison with forcing evaluated by fixing sea surface conditions gives qualitatively similar results for the cloud components of forcing, both globally and locally. Tropospheric adjustment to CO2 may be responsible for some of the model spread in equilibrium climate sensitivity and could affect time-dependent climate projections.

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Estimating the Effective Radiative Forcing of Contrail Cirrus

Journal of Climate ◽

10.1175/jcli-d-19-0467.1 ◽

2020 ◽

Vol 33 (5) ◽

pp. 1991-2005 ◽

Cited By ~ 4

Author(s):

Marius Bickel ◽

Michael Ponater ◽

Lisa Bock ◽

Ulrike Burkhardt ◽

Svenja Reineke

Keyword(s):

Surface Temperature ◽

Radiative Forcing ◽

Climate Models ◽

Climate Model ◽

Climate Impact ◽

Lapse Rate ◽

Reference Case ◽

Radiative Forcings ◽

Effective Radiative Forcing ◽

Climate Model Simulations

AbstractEvidence from previous climate model simulations has suggested a potentially low efficacy of contrails to force global mean surface temperature changes. In this paper, a climate model with a state-of-the-art contrail cirrus representation is used for fixed sea surface temperature simulations in order to determine the effective radiative forcing (ERF) from contrail cirrus. ERF is expected to be a good metric for intercomparing the quantitative importance of different contributions to surface temperature and climate impact. Substantial upscaling of aviation density is necessary to ensure statistically significant results from our simulations. The contrail cirrus ERF is found to be less than 50% of the respective instantaneous or stratosphere adjusted radiative forcings, with a best estimate of roughly 35%. The reduction of ERF is much more substantial for contrail cirrus than it is for a CO2 increase when both stratosphere adjusted forcings are of similar magnitude. Analysis of all rapid radiative adjustments contributing to the ERF indicates that the reduction is mainly induced by a compensating effect of natural clouds that provide a negative feedback. Compared to the CO2 reference case, a less positive combined water vapor and lapse rate adjustment also contributes to a more distinct reduction of contrail cirrus ERF, but not as much as the natural cloud adjustment. Based on the experience gained in this paper, respective contrail cirrus simulations with interactive ocean will be performed as the next step toward establishing contrail cirrus efficacy. ERF results of contrail cirrus from other climate models equipped with suitable parameterizations are regarded as highly desirable.

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Regional emission metrics for short-lived climate forcers from multiple models

Atmospheric Chemistry and Physics ◽

10.5194/acp-16-7451-2016 ◽

2016 ◽

Vol 16 (11) ◽

pp. 7451-7468 ◽

Cited By ~ 16

Author(s):

Borgar Aamaas ◽

Terje K. Berntsen ◽

Jan S. Fuglestvedt ◽

Keith P. Shine ◽

Nicolas Bellouin

Keyword(s):

East Asia ◽

Radiative Forcing ◽

Climate Models ◽

Global Climate ◽

Climate Impact ◽

Ozone Precursors ◽

Direct Forcing ◽

Rf Values ◽

Global Temperature Change ◽

The Impact

Abstract. For short-lived climate forcers (SLCFs), the impact of emissions depends on where and when the emissions take place. Comprehensive new calculations of various emission metrics for SLCFs are presented based on radiative forcing (RF) values calculated in four different (chemical-transport or coupled chemistry–climate) models. We distinguish between emissions during summer (May–October) and winter (November–April) for emissions in Europe and East Asia, as well as from the global shipping sector and global emissions. The species included in this study are aerosols and aerosol precursors (BC, OC, SO2, NH3), as well as ozone precursors (NOx, CO, VOCs), which also influence aerosols to a lesser degree. Emission metrics for global climate responses of these emissions, as well as for CH4, have been calculated using global warming potential (GWP) and global temperature change potential (GTP), based on dedicated RF simulations by four global models. The emission metrics include indirect cloud effects of aerosols and the semi-direct forcing for BC. In addition to the standard emission metrics for pulse and sustained emissions, we have also calculated a new emission metric designed for an emission profile consisting of a ramping period of 15 years followed by sustained emissions, which is more appropriate for a gradual implementation of mitigation policies.For the aerosols, the emission metric values are larger in magnitude for emissions in Europe than East Asia and for summer than winter. A variation is also observed for the ozone precursors, with largest values for emissions in East Asia and winter for CO and in Europe and summer for VOCs. In general, the variations between the emission metrics derived from different models are larger than the variations between regions and seasons, but the regional and seasonal variations for the best estimate also hold for most of the models individually. Further, the estimated climate impact of an illustrative mitigation policy package is robust even when accounting for the fact that the magnitude of emission metrics for different species in a given model is correlated. For the ramping emission metrics, the values are generally larger than for pulse or sustained emissions, which holds for all SLCFs. For SLCFs mitigation policies, the dependency of metric values on the region and season of emission should be considered.

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Continuous online monitoring of ice-nucleating particles: development of the automated Horizontal Ice Nucleation Chamber (HINC-Auto)

Atmospheric Measurement Techniques ◽

10.5194/amt-14-269-2021 ◽

2021 ◽

Vol 14 (1) ◽

pp. 269-293

Author(s):

Cyril Brunner ◽

Zamin A. Kanji

Keyword(s):

Radiative Forcing ◽

Climate Models ◽

Water Saturation ◽

Sampling Site ◽

Temporal Analysis ◽

Ice Nucleation ◽

Spatiotemporal Variability ◽

Stable Phase ◽

Climate Projections ◽

Tropospheric Aerosol

Abstract. The incomplete understanding of aerosol–cloud interactions introduces large uncertainties when simulating the cloud radiative forcing in climate models. The physical and optical properties of a cloud, as well as the evolution of precipitation, are strong functions of the cloud hydrometeor phase. Aerosol particles support the phase transition of water in the atmosphere from a meta-stable to a thermodynamically preferred stable phase. In the troposphere, the transition of liquid droplets to ice crystals in clouds, via ice-nucleating particles (INPs) which make up only a tiny fraction of all tropospheric aerosol, is of particular relevance. For accurate cloud modeling in climate projections, the parameterization of cloud processes and information such as the concentrations of atmospheric INPs are needed. Presently, only few continuous real-time INP counters are available and the data acquisition often still requires a human operator. To address this restriction, we developed HINC-Auto, a fully automated online INP counter, by adapting an existing custom-built instrument, the Horizontal Ice Nucleation Chamber. HINC-Auto was able to autonomously sample INPs in the immersion mode at a temperature of 243 K and a water saturation ratio of 1.04 for 97 % of the time for 90 consecutive days. Here, we present the technical setup used to acquire automation, discuss improvements to the experimental precision and sampling time, and validate the instrument performance. In the future, the chamber will allow a detailed temporal analysis (including seasonal and annual variability) of ambient INP concentrations observing repeated meteorological phenomena compared to previous episodic events detected during campaigns. In addition, by deploying multiple chambers at different locations, a spatiotemporal variability of INPs at any sampling site used for monitoring INP analysis can be achieved for temperatures ≤ 243 K.

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GIR v1.0.0: a generalised impulse-response model for climate uncertainty and future scenario exploration

10.5194/gmd-2019-379 ◽

2020 ◽

Cited By ~ 1

Author(s):

Nicholas James Leach ◽

Zebedee Nicholls ◽

Stuart Jenkins ◽

Christopher J. Smith ◽

John Lynch ◽

...

Keyword(s):

Greenhouse Gas ◽

Impulse Response ◽

Radiative Forcing ◽

Climate Models ◽

Temperature Response ◽

Structural Complexity ◽

Common Denominator ◽

Response Model ◽

State Dependent ◽

Effective Radiative Forcing

Abstract. Here we present a Generalised Impulse Response (GIR) model for use in probabilistic future climate and scenario exploration, integrated assessment, policy analysis and teaching. This model is based on a set of only six equations, which correspond to the standard Impulse Response model used for greenhouse gas metric calculations by the IPCC, plus one physically-motivated additional equation to represent state-dependent feedbacks on the response timescales of each greenhouse gas cycle. These six equations are simple and transparent enough to be easily understood and implemented in other models without reliance on the original source code, but flexible enough to reproduce observed well-mixed greenhouse gas (GHG) concentrations and atmospheric lifetimes, best-estimate effective radiative forcing, and temperature response. We describe the assumptions and methods used in selecting the default parameters, but emphasize that other methods would be equally valid: our focus here is on identifying a minimum level of structural complexity. The tunable nature of the model lends it to use as a fully transparent emulator of complex Earth System Models, such as those participating in CMIP6, while also reproducing the behaviour of other simple climate models. We argue that this GIR model is adequate to reproduce the global temperature response to global emissions and effective radiative forcing, and that it should be used as a lowest-common denominator to provide consistency and continuity between different climate assessments. The model design is such that it can be written in tabular data analysis software, such as Excel, increasing the potential user base considerably.

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The Climate Impact of COVID19 Induced Contrail Changes

10.5194/acp-2021-210 ◽

2021 ◽

Author(s):

Andrew Gettelman ◽

Chieh-Chieh Chen ◽

Charles G. Bardeen

Keyword(s):

Surface Temperature ◽

Land Surface ◽

Radiative Forcing ◽

Climate Impact ◽

Climate Impacts ◽

Infrared Heating ◽

Boreal Summer ◽

Surface Temperature Change ◽

Effective Radiative Forcing ◽

Standard Deviations

Abstract. The COVID19 pandemic caused significant economic disruption in 2020 and severely impacted air traffic. We use a state of the art Earth System Model and ensembles of tightly constrained simulations to evaluate the effect of the reductions in aviation traffic on contrail radiative forcing and climate in 2020. In the absence of any COVID19 pandemic caused reductions, the model simulates a contrail Effective Radiative Forcing (ERF) 62 ± 59 m Wm−2 (2 standard deviations). The contrail ERF has complex spatial and seasonal patterns that combine the offsetting effect of shortwave (solar) cooling and longwave (infrared) heating from contrails and contrail cirrus. Cooling is larger in June–August due to the preponderance of aviation in the N. Hemisphere, while warming occurs throughout the year. The spatial and seasonal forcing variations also map onto surface temperature variations. The net land surface temperature change due to contrails in a normal year is estimated at 0.13 ± 0.04 K (2 standard deviations) with some regions warming as much as 0.7 K. The effect of COVID19 reductions in flight traffic decreased contrails. The unique timing of such reductions, which were maximum in N. Hemisphere spring and summer when the largest contrail cooling occurs, means that cooling due to fewer contrails in boreal spring and fall was offset by warming due to fewer contrails in boreal summer to give no significant annual averaged ERF from contrail changes in 2020. Despite no net significant global ERF, because of the spatial and seasonal timing of contrail ERF, some land regions that would have cooled slightly (minimum −0.2 K) but significantly from contrail changes in 2020. The implications for future climate impacts of contrails are discussed.

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Effective radiative forcing and adjustments in CMIP6 models

Atmospheric Chemistry and Physics ◽

10.5194/acp-20-9591-2020 ◽

2020 ◽

Vol 20 (16) ◽

pp. 9591-9618 ◽

Cited By ~ 9

Author(s):

Christopher J. Smith ◽

Ryan J. Kramer ◽

Gunnar Myhre ◽

Kari Alterskjær ◽

William Collins ◽

...

Keyword(s):

Climate Sensitivity ◽

Radiative Forcing ◽

Climate Models ◽

Coupled Model ◽

Internal Variability ◽

Cmip5 Models ◽

Model Intercomparison ◽

Aerosol Forcing ◽

Intercomparison Project ◽

Effective Radiative Forcing

Abstract. The effective radiative forcing, which includes the instantaneous forcing plus adjustments from the atmosphere and surface, has emerged as the key metric of evaluating human and natural influence on the climate. We evaluate effective radiative forcing and adjustments in 17 contemporary climate models that are participating in the Coupled Model Intercomparison Project (CMIP6) and have contributed to the Radiative Forcing Model Intercomparison Project (RFMIP). Present-day (2014) global-mean anthropogenic forcing relative to pre-industrial (1850) levels from climate models stands at 2.00 (±0.23) W m−2, comprised of 1.81 (±0.09) W m−2 from CO2, 1.08 (± 0.21) W m−2 from other well-mixed greenhouse gases, −1.01 (± 0.23) W m−2 from aerosols and −0.09 (±0.13) W m−2 from land use change. Quoted uncertainties are 1 standard deviation across model best estimates, and 90 % confidence in the reported forcings, due to internal variability, is typically within 0.1 W m−2. The majority of the remaining 0.21 W m−2 is likely to be from ozone. In most cases, the largest contributors to the spread in effective radiative forcing (ERF) is from the instantaneous radiative forcing (IRF) and from cloud responses, particularly aerosol–cloud interactions to aerosol forcing. As determined in previous studies, cancellation of tropospheric and surface adjustments means that the stratospherically adjusted radiative forcing is approximately equal to ERF for greenhouse gas forcing but not for aerosols, and consequentially, not for the anthropogenic total. The spread of aerosol forcing ranges from −0.63 to −1.37 W m−2, exhibiting a less negative mean and narrower range compared to 10 CMIP5 models. The spread in 4×CO2 forcing has also narrowed in CMIP6 compared to 13 CMIP5 models. Aerosol forcing is uncorrelated with climate sensitivity. Therefore, there is no evidence to suggest that the increasing spread in climate sensitivity in CMIP6 models, particularly related to high-sensitivity models, is a consequence of a stronger negative present-day aerosol forcing and little evidence that modelling groups are systematically tuning climate sensitivity or aerosol forcing to recreate observed historical warming.

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The Annual Cycle of Fractional Atmospheric Shortwave Absorption in Observations and Models: Spatial Structure, Magnitude, and Timing

Journal of Climate ◽

10.1175/jcli-d-19-0212.1 ◽

2019 ◽

Vol 32 (20) ◽

pp. 6729-6748 ◽

Cited By ~ 1

Author(s):

M. Schwarz ◽

D. Folini ◽

S. Yang ◽

M. Wild

Keyword(s):

Water Vapor ◽

Biomass Burning ◽

Annual Cycle ◽

Climate Models ◽

Global Scale ◽

Shortwave Radiation ◽

Minor Role ◽

Annual Cycles ◽

Regional Feature ◽

A Minor

We use the best currently available in situ and satellite-derived surface and top-of-the-atmosphere (TOA) shortwave radiation observations to explore climatological annual cycles of fractional (i.e., normalized by incoming radiation at the TOA) atmospheric shortwave absorption [Formula: see text] on a global scale. The analysis reveals that [Formula: see text] is a rather regional feature where the reported nonexisting [Formula: see text] in Europe is an exception rather than the rule. In several regions, large and distinctively different [Formula: see text] are apparent. The magnitudes of [Formula: see text] reach values up to 10% in some regions, which is substantial given that the long-term global mean atmospheric shortwave absorption is roughly 23%. Water vapor and aerosols are identified as major drivers for [Formula: see text] while clouds seem to play only a minor role for [Formula: see text]. Regions with large annual cycles in aerosol emissions from biomass burning also show the largest [Formula: see text]. As biomass burning is generally related to human activities, [Formula: see text] is likely also anthropogenically intensified or forced in the respective regions. We also test if climate models are able to simulate the observed pattern of [Formula: see text]. In regions where [Formula: see text] is driven by the annual cycle of natural aerosols or water vapor, the models perform well. In regions with large [Formula: see text] induced by biomass-burning aerosols, the models’ performance is very limited.

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Anthropogenic aerosol forcing – insights from multiple estimates from aerosol-climate models with reduced complexity

Atmospheric Chemistry and Physics ◽

10.5194/acp-19-6821-2019 ◽

2019 ◽

Vol 19 (10) ◽

pp. 6821-6841 ◽

Cited By ~ 10

Author(s):

Stephanie Fiedler ◽

Stefan Kinne ◽

Wan Ting Katty Huang ◽

Petri Räisänen ◽

Declan O'Donnell ◽

...

Keyword(s):

Radiative Forcing ◽

Climate Models ◽

Coupled Model ◽

Cloud Droplet ◽

Internal Variability ◽

Anthropogenic Aerosol ◽

Aerosol Forcing ◽

Effective Radiative Forcing ◽

Absolute Magnitudes ◽

Natural Aerosols

Abstract. This study assesses the change in anthropogenic aerosol forcing from the mid-1970s to the mid-2000s. Both decades had similar global-mean anthropogenic aerosol optical depths but substantially different global distributions. For both years, we quantify (i) the forcing spread due to model-internal variability and (ii) the forcing spread among models. Our assessment is based on new ensembles of atmosphere-only simulations with five state-of-the-art Earth system models. Four of these models will be used in the sixth Coupled Model Intercomparison Project (CMIP6; Eyring et al., 2016). Here, the complexity of the anthropogenic aerosol has been reduced in the participating models. In all our simulations, we prescribe the same patterns of the anthropogenic aerosol optical properties and associated effects on the cloud droplet number concentration. We calculate the instantaneous radiative forcing (RF) and the effective radiative forcing (ERF). Their difference defines the net contribution from rapid adjustments. Our simulations show a model spread in ERF from −0.4 to −0.9 W m−2. The standard deviation in annual ERF is 0.3 W m−2, based on 180 individual estimates from each participating model. This result implies that identifying the model spread in ERF due to systematic differences requires averaging over a sufficiently large number of years. Moreover, we find almost identical ERFs for the mid-1970s and mid-2000s for individual models, although there are major model differences in natural aerosols and clouds. The model-ensemble mean ERF is −0.54 W m−2 for the pre-industrial era to the mid-1970s and −0.59 W m−2 for the pre-industrial era to the mid-2000s. Our result suggests that comparing ERF changes between two observable periods rather than absolute magnitudes relative to a poorly constrained pre-industrial state might provide a better test for a model's ability to represent transient climate changes.

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Probabilistic climate projections with Minimal CMIP Emulator (MCE)

10.5194/egusphere-egu21-13697 ◽

2021 ◽

Author(s):

Junichi Tsutsui

Keyword(s):

Climate Sensitivity ◽

Radiative Forcing ◽

Climate Models ◽

Model Parameters ◽

Climate Projections ◽

Second Phase ◽

Impulse Response Functions ◽

Model Intercomparison ◽

Probabilistic Climate Projections ◽

Intercomparison Project

One of the key applications of simple climate models is probabilistic climate projections to assess a variety of emission scenarios in terms of their compatibility with global warming mitigation goals. The second phase of the Reduced Complexity Model Intercomparison Project (RCMIP) compares nine participating models for their probabilistic projection methods through scenario experiments, focusing on consistency with given constraints for climate indicators including radiative forcing, carbon budget, warming trends, and climate sensitivity. The MCE is one of the nine models, recently developed by the author, and has produced results that well match the ranges of the constraints. The model is based on impulse response functions and parameterized physics of effective radiative forcing and carbon uptake over ocean and land. Perturbed model parameters are generated from statistical models and constrained with a Metropolis-Hastings independence sampler. A parameter subset associated with CO2-induced warming is assured to have a covariance structure as diagnosed from complex climate models of the Coupled Model Intercomparison Project (CMIP). The model's simplicity and the successful results imply that a method with less complicated structures and fewer control parameters has an advantage when building reasonable perturbed ensembles in a transparent way despite less capacity to emulate detailed Earth system components. Experimental results for future scenarios show that the climate sensitivity of CMIP models is overestimated overall, suggesting that probabilistic climate projections need to be constrained with observed warming trends.

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