Robust observational constraint of uncertain aerosol processes and emissions in a climate model and the effect on aerosol radiative forcing

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dc.contributor.authorJohnson, JSen_AU
dc.contributor.authorRegayre, LAen_AU
dc.contributor.authorYoshioka, Men_AU
dc.contributor.authorPringle, KJen_AU
dc.contributor.authorTurnock, STen_AU
dc.contributor.authorBrowse, Jen_AU
dc.contributor.authorSexton, DMHen_AU
dc.contributor.authorRostron, JWen_AU
dc.contributor.authorSchutgens, NAJen_AU
dc.contributor.authorPartridge, DGen_AU
dc.contributor.authorLiu, DTen_AU
dc.contributor.authorAllan, JDen_AU
dc.contributor.authorCoe, Hen_AU
dc.contributor.authorDing, AJen_AU
dc.contributor.authorCohen, DDen_AU
dc.contributor.authorAntancio, AJen_AU
dc.contributor.authorKakkari, Ven_AU
dc.contributor.authorAsmi, Een_AU
dc.contributor.authorCarslaw, KSen_AU
dc.date.accessioned2022-02-24T04:09:34Zen_AU
dc.date.available2022-02-24T04:09:34Zen_AU
dc.date.issued2020-08-13en_AU
dc.date.statistics2022-02-03en_AU
dc.description.abstractThe effect of observational constraint on the ranges of uncertain physical and chemical process parameters was explored in a global aerosol–climate model. The study uses 1 million variants of the Hadley Centre General Environment Model version 3 (HadGEM3) that sample 26 sources of uncertainty, together with over 9000 monthly aggregated grid-box measurements of aerosol optical depth, PM2.5, particle number concentrations, sulfate and organic mass concentrations. Despite many compensating effects in the model, the procedure constrains the probability distributions of parameters related to secondary organic aerosol, anthropogenic SO2 emissions, residential emissions, sea spray emissions, dry deposition rates of SO2 and aerosols, new particle formation, cloud droplet pH and the diameter of primary combustion particles. Observational constraint rules out nearly 98 % of the model variants. On constraint, the ±1σ (standard deviation) range of global annual mean direct radiative forcing (RFari) is reduced by 33 % to −0.14 to −0.26 W m−2, and the 95 % credible interval (CI) is reduced by 34 % to −0.1 to −0.32 W m−2. For the global annual mean aerosol–cloud radiative forcing, RFaci, the ±1σ range is reduced by 7 % to −1.66 to −2.48 W m−2, and the 95 % CI by 6 % to −1.28 to −2.88 W m−2. The tightness of the constraint is limited by parameter cancellation effects (model equifinality) as well as the large and poorly defined “representativeness error” associated with comparing point measurements with a global model. The constraint could also be narrowed if model structural errors that prevent simultaneous agreement with different measurement types in multiple locations and seasons could be improved. For example, constraints using either sulfate or PM2.5 measurements individually result in RFari±1σ ranges that only just overlap, which shows that emergent constraints based on one measurement type may be overconfident. © The Authors CC-BY Licence 4.0en_AU
dc.description.sponsorshipThis research has been supported by the Natural Environment Research Council (grant nos. NE/J024252/1, NE/I020059/1, NE/P013406/1, NE/F019874/1, NE/D004624/1, NE/H008136/1, NE/D006570/1, NE/E011454/1, NE/E016200/1 and NE/I028696/1), the Newton Fund (grant no. UK–China Research and Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China), the National Centre for Atmospheric Science, the Engineering and Physical Sciences Research Council (grant no. EP/K000225/1), the European Union (grant no. ACTRIS-2 (262254)) and the Horizon 2020 (grant no. INTAROS (727890)). We made use of the N8 HPC facility funded from the N8 consortium, an Engineering and Physical Sciences Research Council Grant to use ARCHER (EP/K000225/1) and the JASMIN facility (http://www.jasmin.ac.uk/; last access: 17 September 2019) via the Centre for Environmental Data Analysis funded by NERC and the UK Space Agency and delivered by the Science and Technology Facilities Council. We acknowledge the following additional funding: the Royal Society Wolfson Merit Award (Carslaw); a doctoral training grant from NERC and a CASE studentship with the Met Office Hadley Centre (Regayre).en_AU
dc.identifier.citationJohnson, J. S., Regayre, L. A., Yoshioka, M., Pringle, K. J., Turnock, S. T., Browse, J., Sexton, D. M. H., Rostron, J. W., Schutgens, N. A. J., Partridge, D. G., Liu, D., Allan, J. D., Coe, H., Ding, A., Cohen, D. D., Atanacio, A., Vakkari, V., Asmi, E., & Carslaw, K. S. (2020). Robust observational constraint of uncertain aerosol processes and emissions in a climate model and the effect on aerosol radiative forcing. Atmospheric Chemistry and Physics, 20, 9491–9524. doi:10.5194/acp-20-9491-2020en_AU
dc.identifier.issn1680-7324en_AU
dc.identifier.journaltitleAtmospheric Chemistry and Physicsen_AU
dc.identifier.pagination9491-9524en_AU
dc.identifier.urihttps://doi.org/10.5194/acp-20-9491-2020en_AU
dc.identifier.urihttps://apo.ansto.gov.au/dspace/handle/10238/12859en_AU
dc.identifier.volume20en_AU
dc.language.isoenen_AU
dc.publisherCopernicus Publicationsen_AU
dc.subjectAerosolsen_AU
dc.subjectExhaust gasesen_AU
dc.subjectClimatesen_AU
dc.subjectIndustrial wastesen_AU
dc.subjectEnvironmenten_AU
dc.subjectSulfur dioxideen_AU
dc.subjectRadiative forcingen_AU
dc.subjectDropletsen_AU
dc.titleRobust observational constraint of uncertain aerosol processes and emissions in a climate model and the effect on aerosol radiative forcingen_AU
dc.typeJournal Articleen_AU
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