Ensembles of Global Climate Model Variants Designed for the Quantification and Constraint of Uncertainty in Aerosols and Their Radiative Forcing

M. Yoshioka*, L. A. Regayre, K. J. Pringle, J. S. Johnson, G. W. Mann, D. G. Partridge, D. M.H. Sexton, G. M.S. Lister, N. Schutgens, P. Stier, Z. Kipling, N. Bellouin, J. Browse, B. B.B. Booth, C. E. Johnson, B. Johnson, J. D.P. Mollard, L. Lee, K. S. Carslaw

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review


Tropospheric aerosol radiative forcing has persisted for many years as one of the major causes of uncertainty in global climate model simulations. To sample the range of plausible aerosol and atmospheric states and perform robust statistical analyses of the radiative forcing, it is important to account for the combined effects of many sources of model uncertainty, which is rarely done due to the high computational cost. This paper describes the designs of two ensembles of the Met Office Hadley Centre Global Environment Model-U.K. Chemistry and Aerosol global climate model and provides the first analyses of the uncertainties in aerosol radiative forcing and their causes. The first ensemble was designed to comprehensively sample uncertainty in the aerosol state, while the other samples additional uncertainties in the physical model related to clouds, humidity, and radiation, thereby allowing an analysis of uncertainty in the aerosol effective radiative forcing. Each ensemble consists of around 200 simulations of the preindustrial and present-day atmospheres. The uncertainty in aerosol radiative forcing in our ensembles is comparable to the range of estimates from multimodel intercomparison projects. The mean aerosol effective radiative forcing is −1.45 W/m2 (credible interval of −2.07 to −0.81 W/m2), which encompasses but is more negative than the −1.17 W/m2 in the 2013 Atmospheric Chemistry and Climate Model Intercomparison Project and −0.90 W/m2 in the Intergovernmental Panel on Climate Change Fifth Assessment Report. The ensembles can be used to reduce aerosol radiative forcing uncertainty by challenging them with multiple measurements as well as to isolate potential causes of multimodel differences.

Original languageEnglish
Pages (from-to)3728-3754
Number of pages27
JournalJournal of Advances in Modeling Earth Systems
Issue number11
Publication statusPublished - 1 Nov 2019


10.5281/zenodo.2556552 This research was funded by the Natural Environment Research Council (NERC) under Grants NE/J024252/1 (GASSP) and NE/P013406/1 (A‐CURE); the European Union ACTRIS‐2 project under Grant 262254; the NERC Grant NE/I020059/1 (ACID‐PRUF; Yoshioka, Partridge, Carslaw). This work and its contributors (by name, Johnson, Sexton, and Carslaw) were supported by the U.K.‐China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund. B. Johnson, C. Johnson, and B. Booth were supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra. P. Stier acknowledges funding from the European Research Council (ERC) project RECAP under the European Union's Horizon 2020 research and innovation programme with Grant agreement 724602. Z. Kipling received funding from the NERC Grant NE/J022624/1 (GASSP), a Met Office CASE award, and the ERC Grant FP7‐280025 (ACCLAIM). We acknowledge the following additional funding: the Royal Society Wolfson Merit Award (Carslaw), a doctoral training grant from the Natural Environment Research Council, and a CASE studentship with the Met Office Hadley Centre (Regayre). M. Yoshioka, G.W. Mann, and K. S. Carslaw received funding from the National Centre for Atmospheric Science (NCAS), one of the U.K. Natural Environment Research Council (NERC) research centers via the ACSIS long‐term science programme on the Atlantic climate system. This work used the ARCHER UK National Supercomputing Service ( http://www.archer.ac.uk/ ). ARCHER project allocation n02‐chem was used for base model development and screening simulations, and n02‐NEJ024252, n02‐FREEPPE, and the Leadership Project allocation n02‐CCPPE were used to create the ensembles. The JASMIN facility ( http://www.jasmin.ac.uk/ ) via the Centre for Environmental Data Analysis was used for data storage and processing, which is funded by NERC and the U.K. Space Agency and delivered by the Science and Technology Facilities Council. We uploaded data used to produce the figures in this paper at Zenodo (DOI: ). We appreciate the commitment given by participants in the expert elicitation, particularly C. Johnson, B. Johnson, J. Mollard, S. Turnock, D. Hamilton, A. Schmidt, C. Scott, R. Stevens, E. Butt, C. Reddington, M. Woodhouse, D. Spracklen, and O. Wild. Additionally, we would like to thank Dr Peter Tunved (University of Stockholm), Dr Tuomas Laurila (Finish meteorological institute) and Dr John Ogren (NOAA) for the provision of Arctic aerosol data via the EBAS and IASOA data portals. Finally, we would like to thank Dr Richard Leaitch for the provision of aerosol observations from the Alert observatory in Canada.

FundersFunder number
European Union ACTRIS‐2NE/I020059/1
Met Office CASEFP7‐280025
Met Office Climate Science
Met Office Hadley Centre
Met Office Hadley Centre Climate Programme
NERC and the U.K. Space Agency
Office Climate Science for Service Partnership
Royal Society Wolfson
U.K. Space Agency
U.K.-China Research & Innovation Partnership Fund
U.K.‐China Research & Innovation Partnership Fund
National Oceanic and Atmospheric Administration
Center for Advanced Systems and Engineering, Syracuse University
Horizon 2020 Framework Programme262254, 280025, FP7-280025, NE/J022624/1
Newton Fund
Department for Business, Energy and Industrial Strategy, UK Government
Natural Environment Research CouncilNE/P013406/1, NE/J024252/1
Science and Technology Facilities Council
Department for Environment, Food and Rural Affairs, UK Government
Royal Society
National Eye Research Centre
National Centre for Atmospheric Science
European Commission
European Research Council
Horizon 2020724602


    • aerosols
    • emulators
    • ERF
    • perturbed parameter ensemble
    • radiative forcing
    • uncertainty


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