Historical greenhouse gas concentrations for climate modelling (CMIP6)

Atmospheric greenhouse gas (GHG) concentrations are at unprecedented, record-high levels compared to the last 800000 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...

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Main Authors: Meinshausen, Malte, Vogel, Elisabeth, Nauels, Alexander, Lorbacher, Katja, Meinshausen, Nicolai, Etheridge, David M., Fraser, Paul J., Montzka, Stephen A., Rayner, Peter J., Trudinger, Cathy M., Krummel, Paul B., Beyerle, Urs, Canadell, Josep G., Daniel, John S., Enting, Ian G., Law, Rachel M. Law, Lunder, Chris R., O'Doherty, Simon, Prinn, Ron G., Reimann, Stefan, Rubino, Mauro, Velders, Guus J.M., Vollmer, Martin K., Wang, Ray H.J., Weiss, Ray
Format: Article in Journal/Newspaper
Language:unknown
Published: München : European Geopyhsical Union 2017
Subjects:
500
Online Access:https://dx.doi.org/10.34657/292
https://oa.tib.eu/renate/handle/123456789/3801
id ftdatacite:10.34657/292
record_format openpolar
spelling ftdatacite:10.34657/292 2023-05-15T16:39:07+02:00 Historical greenhouse gas concentrations for climate modelling (CMIP6) Meinshausen, Malte Vogel, Elisabeth Nauels, Alexander Lorbacher, Katja Meinshausen, Nicolai Etheridge, David M. Fraser, Paul J. Montzka, Stephen A. Rayner, Peter J. Trudinger, Cathy M. Krummel, Paul B. Beyerle, Urs Canadell, Josep G. Daniel, John S. Enting, Ian G. Law, Rachel M. Law Lunder, Chris R. O'Doherty, Simon Prinn, Ron G. Reimann, Stefan Rubino, Mauro Velders, Guus J.M. Vollmer, Martin K. Wang, Ray H.J. Weiss, Ray 2017 application/pdf https://dx.doi.org/10.34657/292 https://oa.tib.eu/renate/handle/123456789/3801 unknown München : European Geopyhsical Union Creative Commons Attribution 3.0 Unported CC BY 3.0 Unported https://creativecommons.org/licenses/by/3.0/legalcode cc-by-3.0 CC-BY Accuracy assessment aerosol boundary layer carbon dioxide climate effect climate modeling climate variation CMIP concentration composition experimental study greenhouse gas ice core latitudinal gradient methane nitrous oxide Northern Hemisphere radiative forcing spatiotemporal analysis 500 CreativeWork article 2017 ftdatacite https://doi.org/10.34657/292 2022-03-10T12:42:45Z Atmospheric greenhouse gas (GHG) concentrations are at unprecedented, record-high levels compared to the last 800000 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 284.3ppm, CH4 at 808.2ppb and N2O at 273.0ppb. 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). Article in Journal/Newspaper ice core DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic Accuracy assessment
aerosol
boundary layer
carbon dioxide
climate effect
climate modeling
climate variation
CMIP
concentration composition
experimental study
greenhouse gas
ice core
latitudinal gradient
methane
nitrous oxide
Northern Hemisphere
radiative forcing
spatiotemporal analysis
500
spellingShingle Accuracy assessment
aerosol
boundary layer
carbon dioxide
climate effect
climate modeling
climate variation
CMIP
concentration composition
experimental study
greenhouse gas
ice core
latitudinal gradient
methane
nitrous oxide
Northern Hemisphere
radiative forcing
spatiotemporal analysis
500
Meinshausen, Malte
Vogel, Elisabeth
Nauels, Alexander
Lorbacher, Katja
Meinshausen, Nicolai
Etheridge, David M.
Fraser, Paul J.
Montzka, Stephen A.
Rayner, Peter J.
Trudinger, Cathy M.
Krummel, Paul B.
Beyerle, Urs
Canadell, Josep G.
Daniel, John S.
Enting, Ian G.
Law, Rachel M. Law
Lunder, Chris R.
O'Doherty, Simon
Prinn, Ron G.
Reimann, Stefan
Rubino, Mauro
Velders, Guus J.M.
Vollmer, Martin K.
Wang, Ray H.J.
Weiss, Ray
Historical greenhouse gas concentrations for climate modelling (CMIP6)
topic_facet Accuracy assessment
aerosol
boundary layer
carbon dioxide
climate effect
climate modeling
climate variation
CMIP
concentration composition
experimental study
greenhouse gas
ice core
latitudinal gradient
methane
nitrous oxide
Northern Hemisphere
radiative forcing
spatiotemporal analysis
500
description Atmospheric greenhouse gas (GHG) concentrations are at unprecedented, record-high levels compared to the last 800000 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 284.3ppm, CH4 at 808.2ppb and N2O at 273.0ppb. 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).
format Article in Journal/Newspaper
author Meinshausen, Malte
Vogel, Elisabeth
Nauels, Alexander
Lorbacher, Katja
Meinshausen, Nicolai
Etheridge, David M.
Fraser, Paul J.
Montzka, Stephen A.
Rayner, Peter J.
Trudinger, Cathy M.
Krummel, Paul B.
Beyerle, Urs
Canadell, Josep G.
Daniel, John S.
Enting, Ian G.
Law, Rachel M. Law
Lunder, Chris R.
O'Doherty, Simon
Prinn, Ron G.
Reimann, Stefan
Rubino, Mauro
Velders, Guus J.M.
Vollmer, Martin K.
Wang, Ray H.J.
Weiss, Ray
author_facet Meinshausen, Malte
Vogel, Elisabeth
Nauels, Alexander
Lorbacher, Katja
Meinshausen, Nicolai
Etheridge, David M.
Fraser, Paul J.
Montzka, Stephen A.
Rayner, Peter J.
Trudinger, Cathy M.
Krummel, Paul B.
Beyerle, Urs
Canadell, Josep G.
Daniel, John S.
Enting, Ian G.
Law, Rachel M. Law
Lunder, Chris R.
O'Doherty, Simon
Prinn, Ron G.
Reimann, Stefan
Rubino, Mauro
Velders, Guus J.M.
Vollmer, Martin K.
Wang, Ray H.J.
Weiss, Ray
author_sort Meinshausen, Malte
title Historical greenhouse gas concentrations for climate modelling (CMIP6)
title_short Historical greenhouse gas concentrations for climate modelling (CMIP6)
title_full Historical greenhouse gas concentrations for climate modelling (CMIP6)
title_fullStr Historical greenhouse gas concentrations for climate modelling (CMIP6)
title_full_unstemmed Historical greenhouse gas concentrations for climate modelling (CMIP6)
title_sort historical greenhouse gas concentrations for climate modelling (cmip6)
publisher München : European Geopyhsical Union
publishDate 2017
url https://dx.doi.org/10.34657/292
https://oa.tib.eu/renate/handle/123456789/3801
genre ice core
genre_facet ice core
op_rights Creative Commons Attribution 3.0 Unported
CC BY 3.0 Unported
https://creativecommons.org/licenses/by/3.0/legalcode
cc-by-3.0
op_rightsnorm CC-BY
op_doi https://doi.org/10.34657/292
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