Historical greenhouse gas concentrations

Abstract. Atmospheric greenhouse gas concentrations are at unprecedented, record-high levels compared to pre-industrial reconstructions over the last 800,000 years. Those elevated greenhouse gas concentrations warm the planet and together with net cooling effects by aerosols, they are the reason of observed climate change over the past 150 years. An accurate representation of those concentrations is hence important to understand and model recent and future climate change. So far, community efforts to create composite datasets with seasonal and latitudinal information have focused on marine boundary layer conditions and recent trends since 1980s. Here, we provide consolidated data sets of historical atmospheric (volume) mixing ratios of 43 greenhouse gases specifically for the purpose of climate model runs. The presented datasets are based on AGAGE and NOAA networks and a large set of literature studies. In contrast to previous intercomparisons, the new datasets are latitudinally resolved, and include seasonality over the period between year 0 to 2014. We assimilate data for CO2, methane (CH4) and nitrous oxide (N2O), 5 chlorofluorocarbons (CFCs), 3 hydrochlorofluorocarbons (HCFCs), 16 hydrofluorocarbons (HFCs), 3 halons, methyl bromide (CH3Br), 3 perfluorocarbons (PFCs), sulfur hexafluoride (SF6), nitrogen triflouride (NF3) and sulfuryl fluoride (SO2F2). We estimate 1850 annual and global mean surface mixing ratios of CO2 at 284.3 ppmv, CH4 at 808.2 ppbv and N2O at 273.0 ppbv and quantify the seasonal and hemispheric gradients of surface mixing ratios. Compared to earlier intercomparisons, the stronger implied radiative forcing in the northern hemisphere winter (due to the latitudinal gradient and seasonality) may help to improve the skill of climate models to reproduce past climate and thereby reduce uncertainty in future projections.

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Historical greenhouse gas concentrations for climate modelling (CMIP6)

Geoscientific Model Development ◽

10.5194/gmd-10-2057-2017 ◽

2017 ◽

Vol 10 (5) ◽

pp. 2057-2116 ◽

Cited By ~ 118

Author(s):

Malte Meinshausen ◽

Elisabeth Vogel ◽

Alexander Nauels ◽

Katja Lorbacher ◽

Nicolai Meinshausen ◽

...

Keyword(s):

Greenhouse Gas ◽

Radiative Forcing ◽

Sulfur Hexafluoride ◽

Marine Boundary Layer ◽

Climate Model ◽

Climate Modelling ◽

Large Set ◽

Time Series Modelling ◽

Recent Climate ◽

Cooling Effects

Abstract. Atmospheric greenhouse gas (GHG) concentrations are at unprecedented, record-high levels compared to the last 800 000 years. Those elevated GHG concentrations warm the planet and – partially offset by net cooling effects by aerosols – are largely responsible for the observed warming over the past 150 years. An accurate representation of GHG concentrations is hence important to understand and model recent climate change. So far, community efforts to create composite datasets of GHG concentrations with seasonal and latitudinal information have focused on marine boundary layer conditions and recent trends since the 1980s. Here, we provide consolidated datasets of historical atmospheric concentrations (mole fractions) of 43 GHGs to be used in the Climate Model Intercomparison Project – Phase 6 (CMIP6) experiments. The presented datasets are based on AGAGE and NOAA networks, firn and ice core data, and archived air data, and a large set of published studies. In contrast to previous intercomparisons, the new datasets are latitudinally resolved and include seasonality. We focus on the period 1850–2014 for historical CMIP6 runs, but data are also provided for the last 2000 years. We provide consolidated datasets in various spatiotemporal resolutions for carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), as well as 40 other GHGs, namely 17 ozone-depleting substances, 11 hydrofluorocarbons (HFCs), 9 perfluorocarbons (PFCs), sulfur hexafluoride (SF6), nitrogen trifluoride (NF3) and sulfuryl fluoride (SO2F2). In addition, we provide three equivalence species that aggregate concentrations of GHGs other than CO2, CH4 and N2O, weighted by their radiative forcing efficiencies. For the year 1850, which is used for pre-industrial control runs, we estimate annual global-mean surface concentrations of CO2 at 284.3 ppm, CH4 at 808.2 ppb and N2O at 273.0 ppb. The data are available at https://esgf-node.llnl.gov/search/input4mips/ and http://www.climatecollege.unimelb.edu.au/cmip6. While the minimum CMIP6 recommendation is to use the global- and annual-mean time series, modelling groups can also choose our monthly and latitudinally resolved concentrations, which imply a stronger radiative forcing in the Northern Hemisphere winter (due to the latitudinal gradient and seasonality).

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THE SCIENCE UNDERLYING THE ISSUE OF CLIMATE CHANGE AND PROSPECTS FOR ADAPTATION

The APPEA Journal ◽

10.1071/aj00039 ◽

2001 ◽

Vol 41 (1) ◽

pp. 689

Author(s):

C.D. Mitchell ◽

G.I. Pearman

Keyword(s):

Climate Change ◽

Risk Management ◽

Greenhouse Gas ◽

Climate Model ◽

Global Climate ◽

Regional Climate ◽

Initial Response ◽

Lower Atmosphere ◽

Future Climate Change ◽

Atmospheric Concentration

The prospect of global-scale changes in climate resulting from changes in atmospheric greenhouse gas concentrations has produced a complex set of public and private- sector responses. This paper reviews several elements of this issue that are likely to be most important to industry.Scientific research continues to provide evidence to suggest that global climate will change significantly over the coming decades due to increases in the atmospheric concentration of greenhouse gases. Nonetheless, there exists a debate over the difference between observations of temperature retrieved from satellite and temperature measurements taken from the surface. Recent research undertaken to inform the debate is discussed, with the conclusion that there are real differences in trend between the surface and the lower atmosphere that can be explained in physical terms. Attention is turning to developing an understanding as to why climate model results show apparently consistent trends between the surface and the lower atmosphere, in contrast to these observations.While such uncertainties in the underlying science have been used to question whether action on the greenhouse issues is necessary, the initial response, as evidenced by international negotiations, has been to start mitigating greenhouse gas emissions. Adaptation to future climate change has received less attention than mitigation. A number of reasons for this are discussed, including the fact that regional scenarios of climate change are uncertain.The principles of risk management may be one way to manage the uncertainties associated with projections of regional climate change. Although the application of risk management to the potential impacts of climate change requires further investigation, elements of such a framework are identified, and include:Identifying the critical climate-related thresholds that are important to industry and its operations (for example, a 1-in-100 year return tropical cyclone).Using this understanding to analyse, and where possible quantify, industry’s pre-existing or baseline adaptive state through the use of sensitivity surfaces and quantified thresholds (for example, were facilities designed for a 1-in-100 event or a 1-in-500 year event?)Establishing probabilistic statements or scenarios of climate that are relevant to industry practice (for example, risk of a storm surge may be more important to operations than elevated wind strength; if so, what is the probability that an event will exceed the design threshold during the lifetime of the facility?).Bringing information on existing adaptive mechanisms together with climate scenarios to produce a quantitative risk assessment.Deciding on risk treatment (additional adaptive measures).

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FAIR v1.3: a simple emissions-based impulse response and carbon cycle model

Geoscientific Model Development ◽

10.5194/gmd-11-2273-2018 ◽

2018 ◽

Vol 11 (6) ◽

pp. 2273-2297 ◽

Cited By ~ 37

Author(s):

Christopher J. Smith ◽

Piers M. Forster ◽

Myles Allen ◽

Nicholas Leach ◽

Richard J. Millar ◽

...

Keyword(s):

Climate Change ◽

Greenhouse Gases ◽

Radiative Forcing ◽

Climate Models ◽

Climate Model ◽

Future Climate Change ◽

Climate Response ◽

Transient Climate Response ◽

Carbon Cycle Model ◽

Future Projections

Abstract. Simple climate models can be valuable if they are able to replicate aspects of complex fully coupled earth system models. Larger ensembles can be produced, enabling a probabilistic view of future climate change. A simple emissions-based climate model, FAIR, is presented, which calculates atmospheric concentrations of greenhouse gases and effective radiative forcing (ERF) from greenhouse gases, aerosols, ozone and other agents. Model runs are constrained to observed temperature change from 1880 to 2016 and produce a range of future projections under the Representative Concentration Pathway (RCP) scenarios. The constrained estimates of equilibrium climate sensitivity (ECS), transient climate response (TCR) and transient climate response to cumulative CO2 emissions (TCRE) are 2.86 (2.01 to 4.22) K, 1.53 (1.05 to 2.41) K and 1.40 (0.96 to 2.23) K (1000 GtC)−1 (median and 5–95 % credible intervals). These are in good agreement with the likely Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) range, noting that AR5 estimates were derived from a combination of climate models, observations and expert judgement. The ranges of future projections of temperature and ranges of estimates of ECS, TCR and TCRE are somewhat sensitive to the prior distributions of ECS∕TCR parameters but less sensitive to the ERF from a doubling of CO2 or the observational temperature dataset used to constrain the ensemble. Taking these sensitivities into account, there is no evidence to suggest that the median and credible range of observationally constrained TCR or ECS differ from climate model-derived estimates. The range of temperature projections under RCP8.5 for 2081–2100 in the constrained FAIR model ensemble is lower than the emissions-based estimate reported in AR5 by half a degree, owing to differences in forcing assumptions and ECS∕TCR distributions.

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Climate warming from managed grasslands cancels the cooling effect of carbon sinks in sparsely grazed and natural grasslands

Nature Communications ◽

10.1038/s41467-020-20406-7 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Jinfeng Chang ◽

Philippe Ciais ◽

Thomas Gasser ◽

Pete Smith ◽

Mario Herrero ◽

...

Keyword(s):

Climate Change ◽

Greenhouse Gas ◽

Nitrogen Deposition ◽

Climate Warming ◽

Radiative Forcing ◽

Future Climate Change ◽

Surface Model ◽

Carbon Sinks ◽

Regional Patterns ◽

Natural Grasslands

AbstractGrasslands absorb and release carbon dioxide (CO2), emit methane (CH4) from grazing livestock, and emit nitrous oxide (N2O) from soils. Little is known about how the fluxes of these three greenhouse gases, from managed and natural grasslands worldwide, have contributed to past climate change, or the roles of managed pastures versus natural grasslands. Here, global trends and regional patterns of the full greenhouse gas balance of grasslands are estimated for the period 1750 to 2012. A new spatially explicit land surface model is applied, to separate the direct effects of human activities from land management and the indirect effects from climate change, increasing CO2 and regional changes in nitrogen deposition. Direct human management activities are simulated to have caused grasslands to switch from a sink to a source of greenhouse gas, because of increased livestock numbers and accelerated conversion of natural lands to pasture. However, climate change drivers contributed a net carbon sink in soil organic matter, mainly from the increased productivity of grasslands due to increased CO2 and nitrogen deposition. The net radiative forcing of all grasslands is currently close to neutral, but has been increasing since the 1960s. Here, we show that the net global climate warming caused by managed grassland cancels the net climate cooling from carbon sinks in sparsely grazed and natural grasslands. In the face of future climate change and increased demand for livestock products, these findings highlight the need to use sustainable management to preserve and enhance soil carbon storage in grasslands and to reduce greenhouse gas emissions from managed grasslands.

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Constraints on radiative forcing and future climate change from observations and climate model ensembles

Nature ◽

10.1038/416719a ◽

2002 ◽

Vol 416 (6882) ◽

pp. 719-723 ◽

Cited By ~ 260

Author(s):

Reto Knutti ◽

Thomas F. Stocker ◽

Fortunat Joos ◽

Gian-Kasper Plattner

Keyword(s):

Climate Change ◽

Radiative Forcing ◽

Climate Model ◽

Future Climate ◽

Future Climate Change ◽

Climate Model Ensembles ◽

Model Ensembles

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Dry season water availability changes attributed to human-induced climate change

10.5194/egusphere-egu2020-12658 ◽

2020 ◽

Author(s):

Ryan S. Padrón ◽

Lukas Gudmundsson ◽

Agnès Ducharne ◽

David M. Lawrence ◽

Jiafu Mao ◽

...

Keyword(s):

Climate Change ◽

Greenhouse Gas ◽

Water Availability ◽

Land Surface ◽

Radiative Forcing ◽

Climate Model ◽

Dry Season ◽

Eastern Africa ◽

Northern Asia ◽

Climate Model Simulations

Human-induced climate change poses potential impacts on the availability of water resources. Previous assessments of warming-induced changes in dryness, however, are influenced by short observational records and show conflicting results due to uncertainties in the response of evapotranspiration. In this study we use novel observation-based water availability reconstructions from data-driven and land surface models from 1902 to 2014; a period during which the Earth has warmed approximately 1&#176;C relative to pre-industrial conditions. These reconstructions reveal consistent changes in average water availability of the driest month of the year during the last 30 years compared to the first half of the 20th&#160;century. We conduct a simple attribution approach based on a spatial correlation analysis between the reconstructions and different climate model simulations. Results indicate that the spatial pattern of changes is extremely likely influenced by human-induced greenhouse gas emissions as it is consistent with climate model estimates that include historical radiative forcing, whereas the pattern is not expected from natural climate variability given by climate simulations with greenhouse gas levels set to pre-industrial conditions. Changes in water availability are characterized by drier dry seasons predominantly in extratropical latitudes and including Europe, Western North America, Northern Asia, Southern South America, Australia, and Eastern Africa. Finally, we find that the intensification of the dry season is generally a consequence of increasing evapotranspiration rather than decreasing precipitation.

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Incorrect Asian aerosols affecting the attribution and projection of regional climate change in CMIP6 models

npj Climate and Atmospheric Science ◽

10.1038/s41612-020-00159-2 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Zhili Wang ◽

Lei Lin ◽

Yangyang Xu ◽

Huizheng Che ◽

Xiaoye Zhang ◽

...

Keyword(s):

Climate Change ◽

Radiative Forcing ◽

Impact Analysis ◽

Climate Model ◽

Regional Climate ◽

Eastern China ◽

Coupled Model ◽

Regional Climate Change ◽

Anthropogenic Aerosol ◽

Wide Range

AbstractAnthropogenic aerosol (AA) forcing has been shown as a critical driver of climate change over Asia since the mid-20th century. Here we show that almost all Coupled Model Intercomparison Project Phase 6 (CMIP6) models fail to capture the observed dipole pattern of aerosol optical depth (AOD) trends over Asia during 2006–2014, last decade of CMIP6 historical simulation, due to an opposite trend over eastern China compared with observations. The incorrect AOD trend over China is attributed to problematic AA emissions adopted by CMIP6. There are obvious differences in simulated regional aerosol radiative forcing and temperature responses over Asia when using two different emissions inventories (one adopted by CMIP6; the other from Peking university, a more trustworthy inventory) to driving a global aerosol-climate model separately. We further show that some widely adopted CMIP6 pathways (after 2015) also significantly underestimate the more recent decline in AA emissions over China. These flaws may bring about errors to the CMIP6-based regional climate attribution over Asia for the last two decades and projection for the next few decades, previously anticipated to inform a wide range of impact analysis.

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Projecting malaria hazard from climate change in eastern Africa using large ensembles to estimate uncertainty

Geospatial health ◽

10.4081/gh.2016.393 ◽

2016 ◽

Vol 11 (1s) ◽

Cited By ~ 8

Author(s):

Joseph Leedale ◽

Adrian M. Tompkins ◽

Cyril Caminade ◽

Anne E. Jones ◽

Grigory Nikulin ◽

...

Keyword(s):

Climate Change ◽

Malaria Transmission ◽

Climate Models ◽

Climate Model ◽

Eastern Africa ◽

Future Climate Change ◽

Climate Projections ◽

Model Ensemble ◽

East African Community ◽

Recent Climate

The effect of climate change on the spatiotemporal dynamics of malaria transmission is studied using an unprecedented ensemble of climate projections, employing three diverse bias correction and downscaling techniques, in order to partially account for uncertainty in climate- driven malaria projections. These large climate ensembles drive two dynamical and spatially explicit epidemiological malaria models to provide future hazard projections for the focus region of eastern Africa. While the two malaria models produce very distinct transmission patterns for the recent climate, their response to future climate change is similar in terms of sign and spatial distribution, with malaria transmission moving to higher altitudes in the East African Community (EAC) region, while transmission reduces in lowland, marginal transmission zones such as South Sudan. The climate model ensemble generally projects warmer and wetter conditions over EAC. The simulated malaria response appears to be driven by temperature rather than precipitation effects. This reduces the uncertainty due to the climate models, as precipitation trends in tropical regions are very diverse, projecting both drier and wetter conditions with the current state-of-the-art climate model ensemble. The magnitude of the projected changes differed considerably between the two dynamical malaria models, with one much more sensitive to climate change, highlighting that uncertainty in the malaria projections is also associated with the disease modelling approach.

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Chemical and climatic drivers of radiative forcing due to changes in stratospheric and tropospheric ozone over the 21st century

10.5194/acp-2017-741 ◽

2017 ◽

Author(s):

Antara Banerjee ◽

Amanda C. Maycock ◽

John A. Pyle

Keyword(s):

Greenhouse Gas ◽

Tropospheric Ozone ◽

Radiative Forcing ◽

Climate Model ◽

Stratospheric Ozone ◽

Radiative Forcings ◽

Climatic Drivers ◽

Ozone Precursor ◽

Ozone Depleting Substances ◽

Projected Changes

Abstract. The ozone radiative forcings (RFs) resulting from projected changes in climate, ozone-depleting substances (ODSs), non-methane ozone precursor emissions and methane between the years 2000 and 2100 are calculated using simulations from the UM-UKCA chemistry-climate model. Projected measures to improve air-quality through reductions in tropospheric ozone precursor emissions present a co-benefit for climate, with a net global mean ozone RF of −0.09 Wm−2. This is opposed by a positive ozone RF of 0.07 Wm−2 due to future decreases in ODSs, which is mainly driven by an increase in tropospheric ozone through stratosphere-to-troposphere exchange. An increase in methane abundance by more than a factor of two (as projected by the RCP8.5 scenario) is found to drive an ozone RF of 0.19 Wm−2, which would greatly outweigh the climate benefits of tropospheric non-methane ozone precursor reductions. A third of the ozone RF due to the projected increase in methane results from increases in stratospheric ozone. The sign of the ozone RF due to future changes in climate (including the radiative effects of greenhouse gas concentrations, sea surface temperatures and sea ice changes) is shown to be dependent on the greenhouse gas emissions pathway, with a positive RF (0.06 Wm−2) for RCP4.5 and a negative RF (−0.07 Wm−2) for the RCP8.5 scenario. This dependence arises from differences in the contribution to RF from stratospheric ozone changes.

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An update of IPCC climate reference regions for subcontinental analysis of climate model data: definition and aggregated datasets

Earth System Science Data ◽

10.5194/essd-12-2959-2020 ◽

2020 ◽

Vol 12 (4) ◽

pp. 2959-2970

Author(s):

Maialen Iturbide ◽

José M. Gutiérrez ◽

Lincoln M. Alves ◽

Joaquín Bedia ◽

Ruth Cerezo-Mota ◽

...

Keyword(s):

Climate Change ◽

Climate Model ◽

Climate Adaptation ◽

Regional Climate ◽

Atmospheric Model ◽

Future Climate Change ◽

Intergovernmental Panel ◽

Temperature And Precipitation ◽

Scatter Plots ◽

Projected Changes

Abstract. Several sets of reference regions have been used in the literature for the regional synthesis of observed and modelled climate and climate change information. A popular example is the series of reference regions used in the Intergovernmental Panel on Climate Change (IPCC) Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Adaptation (SREX). The SREX regions were slightly modified for the Fifth Assessment Report of the IPCC and used for reporting subcontinental observed and projected changes over a reduced number (33) of climatologically consistent regions encompassing a representative number of grid boxes. These regions are intended to allow analysis of atmospheric data over broad land or ocean regions and have been used as the basis for several popular spatially aggregated datasets, such as the Seasonal Mean Temperature and Precipitation in IPCC Regions for CMIP5 dataset. We present an updated version of the reference regions for the analysis of new observed and simulated datasets (including CMIP6) which offer an opportunity for refinement due to the higher atmospheric model resolution. As a result, the number of land and ocean regions is increased to 46 and 15, respectively, better representing consistent regional climate features. The paper describes the rationale for the definition of the new regions and analyses their homogeneity. The regions are defined as polygons and are provided as coordinates and a shapefile together with companion R and Python notebooks to illustrate their use in practical problems (e.g. calculating regional averages). We also describe the generation of a new dataset with monthly temperature and precipitation, spatially aggregated in the new regions, currently for CMIP5 and CMIP6, to be extended to other datasets in the future (including observations). The use of these reference regions, dataset and code is illustrated through a worked example using scatter plots to offer guidance on the likely range of future climate change at the scale of the reference regions. The regions, datasets and code (R and Python notebooks) are freely available at the ATLAS GitHub repository: https://github.com/SantanderMetGroup/ATLAS (last access: 24 August 2020), https://doi.org/10.5281/zenodo.3998463 (Iturbide et al., 2020).

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Historical greenhouse gas concentrations