Malte Meinshausen1,2,3, Elisabeth Vogel1,2, Alexander Nauels1,2, Katja Lorbacher1,2, Nicolai Meinshausen4, David Etheridge5, Paul Fraser5, Stephen A. Montzka6, Peter Rayner2, Cathy Trudinger5, Paul Krummel5, Urs Beyerle7, Josep G. Cannadell8, John S. Daniel9, Ian Enting10,*, Rachel M. Law5, Simon O'Doherty11, Ron G. Prinn12, Stefan Reimann13, Mauro Rubino5,14, Guus J. M. Velders15, Martin K. Vollmer13, and Ray Weiss161Australian-German Climate & Energy College, The University of Melbourne, Parkville, Victoria, Australia 2Department of Earth Sciences, The University of Melbourne, Parkville, Victoria, Australia 3Potsdam Institute for Climate Impact Research, Potsdam, Germany 4Seminar for Statistics, Swiss Federal Institute of Technology (ETH Zurich), Zurich, Switzerland 5CSIRO Oceans and Atmosphere, Aspendale, Victoria, Australia 6NOAA, Earth System Research Laboratory, Global Monitoring Division, Boulder, Colorado, USA 7Institute for Atmospheric and Climate Science, Swiss Federal Institute of Technology, Zurich (ETH Zurich), Switzerland 8Global Carbon Project, CSIRO Oceans and Atmosphere, Canberra, ACT, Australia 9NOAA, Earth System Research Laboratory, Chemical Sciences Division, Boulder, Colorado, USA 10The University of Melbourne, Victoria, Australia 11University of Bristol, Bristol, United Kingdom 12MIT, Cambridge, MA, United States 13Empa, Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Air Pollution and Environmental Technology, Switzerland 14Dipartimento di matematica e fisica, Seconda Università degli studi di Napoli, 81100 Caserta, Italy 15National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands 16Scripps Institution of Oceanography, La Jolla, CA, United States *retired
Received: 02 Jul 2016 – Accepted for review: 05 Aug 2016 – Discussion started: 05 Aug 2016
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.
Meinshausen, M., Vogel, E., Nauels, A., Lorbacher, K., Meinshausen, N., Etheridge, D., Fraser, P., Montzka, S. A., Rayner, P., Trudinger, C., Krummel, P., Beyerle, U., Cannadell, J. G., Daniel, J. S., Enting, I., Law, R. M., O'Doherty, S., Prinn, R. G., Reimann, S., Rubino, M., Velders, G. J. M., Vollmer, M. K., and Weiss, R.: Historical greenhouse gas concentrations, Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-169, in review, 2016.