scholarly journals Why Hasn’t Earth Warmed as Much as Expected?

2010 ◽  
Vol 23 (10) ◽  
pp. 2453-2464 ◽  
Author(s):  
Stephen E. Schwartz ◽  
Robert J. Charlson ◽  
Ralph A. Kahn ◽  
John A. Ogren ◽  
Henning Rodhe
Keyword(s):  
Climate Sensitivity ◽  
Atmospheric Aerosols ◽  
Climate Models ◽  
Substantial Reduction ◽  
Heat Content ◽  
Historical Record ◽  
Intergovernmental Panel ◽  
Aerosol Forcing ◽  
Best Estimate ◽  
Earth’S Climate

Abstract The observed increase in global mean surface temperature (GMST) over the industrial era is less than 40% of that expected from observed increases in long-lived greenhouse gases together with the best-estimate equilibrium climate sensitivity given by the 2007 Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). Possible reasons for this warming discrepancy are systematically examined here. The warming discrepancy is found to be due mainly to some combination of two factors: the IPCC best estimate of climate sensitivity being too high and/or the greenhouse gas forcing being partially offset by forcing by increased concentrations of atmospheric aerosols; the increase in global heat content due to thermal disequilibrium accounts for less than 25% of the discrepancy, and cooling by natural temperature variation can account for only about 15%. Current uncertainty in climate sensitivity is shown to preclude determining the amount of future fossil fuel CO2 emissions that would be compatible with any chosen maximum allowable increase in GMST; even the sign of such allowable future emissions is unconstrained. Resolving this situation, by empirical determination of the earth’s climate sensitivity from the historical record over the industrial period or through use of climate models whose accuracy is evaluated by their performance over this period, is shown to require substantial reduction in the uncertainty of aerosol forcing over this period.

scholarly journals Estimates of climate system properties incorporating recent climate change

2018 ◽  
Vol 4 (1/2) ◽  
pp. 19-36 ◽  
Author(s):  
Alex G. Libardoni ◽  
Chris E. Forest ◽  
Andrei P. Sokolov ◽  
Erwan Monier
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
21St Century ◽  
Climate Sensitivity ◽  
Temperature Rise ◽  
Heat Content ◽  
Climate System ◽  
Model Parameters ◽  
Aerosol Forcing ◽  
Global Mean

Abstract. Historical time series of surface temperature and ocean heat content changes are commonly used metrics to diagnose climate change and estimate properties of the climate system. We show that recent trends, namely the slowing of surface temperature rise at the beginning of the 21st century and the acceleration of heat stored in the deep ocean, have a substantial impact on these estimates. Using the Massachusetts Institute of Technology Earth System Model (MESM), we vary three model parameters that influence the behavior of the climate system: effective climate sensitivity (ECS), the effective ocean diffusivity of heat anomalies by all mixing processes (Kv), and the net anthropogenic aerosol forcing scaling factor. Each model run is compared to observed changes in decadal mean surface temperature anomalies and the trend in global mean ocean heat content change to derive a joint probability distribution function for the model parameters. Marginal distributions for individual parameters are found by integrating over the other two parameters. To investigate how the inclusion of recent temperature changes affects our estimates, we systematically include additional data by choosing periods that end in 1990, 2000, and 2010. We find that estimates of ECS increase in response to rising global surface temperatures when data beyond 1990 are included, but due to the slowdown of surface temperature rise in the early 21st century, estimates when using data up to 2000 are greater than when data up to 2010 are used. We also show that estimates of Kv increase in response to the acceleration of heat stored in the ocean as data beyond 1990 are included. Further, we highlight how including spatial patterns of surface temperature change modifies the estimates. We show that including latitudinal structure in the climate change signal impacts properties with spatial dependence, namely the aerosol forcing pattern, more than properties defined for the global mean, climate sensitivity, and ocean diffusivity.

scholarly journals Observational Constraint on Greenhouse Gas and Aerosol Contributions to Global Ocean Heat Content Changes

2020 ◽  
Vol 33 (24) ◽  
pp. 10579-10591
Author(s):  
Elodie Charles ◽  
Benoit Meyssignac ◽  
Aurélien Ribes
Keyword(s):  
Greenhouse Gas ◽  
Radiative Forcing ◽  
Climate Models ◽  
Ghg Emissions ◽  
Heat Content ◽  
Ocean Heat Content ◽  
Global Ocean ◽  
Detection And Attribution ◽  
Aerosol Forcing ◽  
Bivariate Method

AbstractObservations and climate models are combined to identify an anthropogenic warming signature in the upper ocean heat content (OHC) changes since 1971. We apply a new detection and attribution analysis developed by Ribes et al. that uses a symmetric treatment of the magnitude and the pattern of the climate response to each radiative forcing. A first estimate of the OHC response to natural, anthropogenic, greenhouse gas, and other forcings is derived from a large ensemble of CMIP5 simulations. Observational datasets from historical reconstructions are then used to constrain this estimate. A spatiotemporal observational mask is applied to compare simulations with actual observations and to overcome reconstruction biases. Results on the 0–700-m layer from 1971 to 2005 show that the global OHC would have increased since 1971 by 2.12 ± 0.21 × 107 J m−2 yr−1 in response to GHG emissions alone. But this has been compensated for by other anthropogenic influences (mainly aerosol), which induced an OHC decrease of 0.84 ± 0.18 × 107 J m−2 yr−1. The natural forcing has induced a slight global OHC decrease since 1971 of 0.13 ± 0.09 × 107 J m−2 yr−1. Compared to previous studies we have separated the effect of the GHG forcing from the effect of the other anthropogenic forcing on OHC changes. This has been possible by using a new detection and attribution (D&A) method and by analyzing simultaneously the global OHC trends over 1957–80 and over 1971–2005. This bivariate method takes advantage of the different time variation of the GHG forcing and the aerosol forcing since 1957 to separate both effects and reduce the uncertainty in their estimates.

scholarly journals Black Carbon Increases Frequency of Extreme ENSO Events

2019 ◽  
Vol 32 (23) ◽  
pp. 8323-8333 ◽  
Author(s):  
Sijia Lou ◽  
Yang Yang ◽  
Hailong Wang ◽  
Jian Lu ◽  
Steven J. Smith ◽  
...  
Keyword(s):  
Black Carbon ◽  
Climate Models ◽  
Climate Model ◽  
Southern Oscillation ◽  
Global Climate ◽  
Global Climate Model ◽  
Co2 Concentration ◽  
Enso Events ◽  
Aerosol Forcing ◽  
Earth’S Climate

ABSTRACT El Niño–Southern Oscillation (ENSO) is the leading mode of Earth’s climate variability at interannual time scales with profound ecological and societal impacts, and it is projected to intensify in many climate models as the climate warms under the forcing of increasing CO2 concentration. Since the preindustrial era, black carbon (BC) emissions have substantially increased in the Northern Hemisphere. But how BC aerosol forcing may influence the occurrence of the extreme ENSO events has rarely been investigated. In this study, using simulations of a global climate model, we show that increases in BC emissions from both the midlatitudes and Arctic weaken latitudinal temperature gradients and northward heat transport, decrease tropical energy divergence, and increase sea surface temperature over the tropical oceans, with a surprising consequential increase in the frequency of extreme ENSO events. A corollary of this study is that reducing BC emissions might serve to mitigate the possible increasing frequency of extreme ENSO events under greenhouse warming, if the modeling result can be translated into the climate in reality.

scholarly journals Increased absorption by coarse aerosol particles over the Gangetic–Himalayan region

2014 ◽  
Vol 14 (3) ◽  
pp. 1159-1165 ◽  
Author(s):  
V. S. Manoharan ◽  
R. Kotamarthi ◽  
Y. Feng ◽  
M. P. Cadeddu
Keyword(s):  
Atmospheric Aerosols ◽  
Radiative Forcing ◽  
Climate Models ◽  
Monsoon Season ◽  
Regional Scale ◽  
Chemical Properties ◽  
Aerosol Forcing ◽  
Post Monsoon Season ◽  
Absorbing Aerosols ◽  
Coarse Aerosol

Abstract. Each atmospheric aerosol type has distinctive light-absorption characteristics related to its physical/chemical properties. Climate models treat black carbon as the main light-absorbing component of carbonaceous atmospheric aerosols, while absorption by some organic aerosols is also considered, particularly at ultraviolet wavelengths. Most absorbing aerosols are assumed to be < 1 μm in diameter (sub-micron). Here we present results from a recent field study in India, primarily during the post-monsoon season (October–November), suggesting the presence of absorbing aerosols sized 1–10 μm. Absorption due to super-micron-sized particles was nearly 30% greater than that due to smaller particles. Periods of increased absorption by larger particles ranged from a week to a month. Radiative forcing calculations under clear-sky conditions show that super-micron particles account for nearly 44% of the total aerosol forcing. The origin of the large aerosols is unknown, but meteorological conditions indicate that they are of local origin. Such economic and habitation conditions exist throughout much of the developing world. Hence, large absorbing particles could be an important component of the regional-scale atmospheric energy balance.

scholarly journals The Impact of Recent Forcing and Ocean Heat Uptake Data on Estimates of Climate Sensitivity

2018 ◽  
Vol 31 (15) ◽  
pp. 6051-6071 ◽  
Author(s):  
Nicholas Lewis ◽  
Judith Curry
Keyword(s):  
Climate Sensitivity ◽  
Climate Models ◽  
Temperature Data ◽  
Historical Period ◽  
Climate Feedbacks ◽  
Ocean Heat Uptake ◽  
Transient Climate Response ◽  
Surface Temperature Change ◽  
Aerosol Forcing ◽  
The Impact

Energy budget estimates of equilibrium climate sensitivity (ECS) and transient climate response (TCR) are derived based on the best estimates and uncertainty ranges for forcing provided in the IPCC Fifth Assessment Report (AR5). Recent revisions to greenhouse gas forcing and post-1990 ozone and aerosol forcing estimates are incorporated and the forcing data extended from 2011 to 2016. Reflecting recent evidence against strong aerosol forcing, its AR5 uncertainty lower bound is increased slightly. Using an 1869–82 base period and a 2007–16 final period, which are well matched for volcanic activity and influence from internal variability, medians are derived for ECS of 1.50 K (5%–95% range: 1.05–2.45 K) and for TCR of 1.20 K (5%–95% range: 0.9–1.7 K). These estimates both have much lower upper bounds than those from a predecessor study using AR5 data ending in 2011. Using infilled, globally complete temperature data give slightly higher estimates: a median of 1.66 K for ECS (5%–95% range: 1.15–2.7 K) and 1.33 K for TCR (5%–95% range: 1.0–1.9 K). These ECS estimates reflect climate feedbacks over the historical period, assumed to be time invariant. Allowing for possible time-varying climate feedbacks increases the median ECS estimate to 1.76 K (5%–95% range: 1.2–3.1 K), using infilled temperature data. Possible biases from non–unit forcing efficacy, temperature estimation issues, and variability in sea surface temperature change patterns are examined and found to be minor when using globally complete temperature data. These results imply that high ECS and TCR values derived from a majority of CMIP5 climate models are inconsistent with observed warming during the historical period.

scholarly journals The Pliocene Model Intercomparison Project Phase 2: large-scale climate features and climate sensitivity

2020 ◽  
Vol 16 (6) ◽  
pp. 2095-2123 ◽  
Author(s):  
Alan M. Haywood ◽  
Julia C. Tindall ◽  
Harry J. Dowsett ◽  
Aisling M. Dolan ◽  
Kevin M. Foley ◽  
...  
Keyword(s):  
Climate Sensitivity ◽  
Large Scale ◽  
Climate Models ◽  
Temperature Response ◽  
Surface Air Temperature ◽  
System Response ◽  
Phase 2 ◽  
Model Intercomparison ◽  
Intergovernmental Panel ◽  
Intercomparison Project

Abstract. The Pliocene epoch has great potential to improve our understanding of the long-term climatic and environmental consequences of an atmospheric CO2 concentration near ∼400 parts per million by volume. Here we present the large-scale features of Pliocene climate as simulated by a new ensemble of climate models of varying complexity and spatial resolution based on new reconstructions of boundary conditions (the Pliocene Model Intercomparison Project Phase 2; PlioMIP2). As a global annual average, modelled surface air temperatures increase by between 1.7 and 5.2 ∘C relative to the pre-industrial era with a multi-model mean value of 3.2 ∘C. Annual mean total precipitation rates increase by 7 % (range: 2 %–13 %). On average, surface air temperature (SAT) increases by 4.3 ∘C over land and 2.8 ∘C over the oceans. There is a clear pattern of polar amplification with warming polewards of 60∘ N and 60∘ S exceeding the global mean warming by a factor of 2.3. In the Atlantic and Pacific oceans, meridional temperature gradients are reduced, while tropical zonal gradients remain largely unchanged. There is a statistically significant relationship between a model's climate response associated with a doubling in CO2 (equilibrium climate sensitivity; ECS) and its simulated Pliocene surface temperature response. The mean ensemble Earth system response to a doubling of CO2 (including ice sheet feedbacks) is 67 % greater than ECS; this is larger than the increase of 47 % obtained from the PlioMIP1 ensemble. Proxy-derived estimates of Pliocene sea surface temperatures are used to assess model estimates of ECS and give an ECS range of 2.6–4.8 ∘C. This result is in general accord with the ECS range presented by previous Intergovernmental Panel on Climate Change (IPCC) Assessment Reports.

scholarly journals Effective radiative forcing and adjustments in CMIP6 models

2020 ◽  
Vol 20 (16) ◽  
pp. 9591-9618 ◽  
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.

scholarly journals Climate sensitivity uncertainty: when is good news bad?

2015 ◽  
Vol 373 (2055) ◽  
pp. 20150092 ◽  
Author(s):  
Mark C. Freeman ◽  
Gernot Wagner ◽  
Richard J. Zeckhauser
Keyword(s):  
Climate Change ◽  
Climate Sensitivity ◽  
Atmospheric Carbon Dioxide ◽  
Climate Science ◽  
Well Being ◽  
Bad News ◽  
Good News ◽  
Intergovernmental Panel ◽  
Best Estimate ◽  
Ipcc Report

Climate change is real and dangerous. Exactly how bad it will get, however, is uncertain. Uncertainty is particularly relevant for estimates of one of the key parameters: equilibrium climate sensitivity—how eventual temperatures will react as atmospheric carbon dioxide concentrations double. Despite significant advances in climate science and increased confidence in the accuracy of the range itself, the ‘likely’ range has been 1.5–4.5°C for over three decades. In 2007, the Intergovernmental Panel on Climate Change (IPCC) narrowed it to 2–4.5°C, only to reverse its decision in 2013, reinstating the prior range. In addition, the 2013 IPCC report removed prior mention of 3°C as the ‘best estimate’. We interpret the implications of the 2013 IPCC decision to lower the bottom of the range and excise a best estimate. Intuitively, it might seem that a lower bottom would be good news. Here we ask: when might apparently good news about climate sensitivity in fact be bad news in the sense that it lowers societal well-being? The lowered bottom value also implies higher uncertainty about the temperature increase, definitely bad news. Under reasonable assumptions, both the lowering of the lower bound and the removal of the ‘best estimate’ may well be bad news.

scholarly journals Emergent constraints on Equilibrium Climate Sensitivity in CMIP5: do they hold for CMIP6?

2020 ◽  
Author(s):  
Manuel Schlund ◽  
Axel Lauer ◽  
Pierre Gentine ◽  
Steven C. Sherwood ◽  
Veronika Eyring
Keyword(s):  
Climate Sensitivity ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Correlation Coefficients ◽  
Co2 Concentration ◽  
Significance Test ◽  
Intergovernmental Panel ◽  
Equilibrium Climate Sensitivity ◽  
Best Estimate ◽  
Emergent Constraints

Abstract. An important metric for temperature projections is the equilibrium climate sensitivity (ECS) which is defined as the global mean surface air temperature change caused by a doubling of the atmospheric CO2 concentration. The range for ECS assessed by the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report is between 1.5 and 4.5 K and has not decreased over the last decades. Among other methods, emergent constraints are potentially promising approaches to reduce the range of ECS by combining observations and output from Earth System Models (ESMs). In this study, we systematically analyze 11 published emergent constraints on ECS that have mostly been derived from models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) project. These emergent constraints are – except for one that is based on temperature variability – all directly or indirectly based on cloud processes, which stem the major source of uncertainty in ECS. The focus of the study is on testing if these emergent constraints hold for ESMs participating in the new Phase 6 (CMIP6). Since none of the emergent constraints considered here has been derived using the CMIP6 ensemble, CMIP6 can be used for cross-checking of the emergent constraints on a new model ensemble. The application of the emergent constraints to CMIP6 data shows a large decrease of the correlation coefficients for most emergent relationships, indicating that nearly all of the constraints are less skillful in predicting ECS than they were in CMIP5. Many do not appear sufficiently skillful to be useful in constraining ECS, and several of them do not pass a significance test. This is likely because of changes in the representation of cloud processes from CMIP5 to CMIP6, but may in some cases also be due to spurious statistical relationships or a too small number of models in the ensemble the emergent constraint was originally derived from. The emergent-constrained best estimate of ECS increased from CMIP5 to CMIP6, with a best estimate range of 2.97–3.88 K for CMIP5 and 3.41–4.36 K for CMIP6. This can be at least partly explained by the increased number of high-ECS models in CMIP6 with an ECS above 4.5 K without a corresponding change in the constraint predictors. Our results support previous studies concluding that emergent constraints should be based on an independently verifiable physical mechanism, and that emergent constraints focusing on specific processes contributing to ECS are more promising than emergent constraints based on statistical model analysis.

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