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Book ; Online: Identifying climate model structural inconsistencies allows for tight constraint of aerosol radiative forcing

Regayre, Leighton A. / Deaconu, Lucia / Grosvenor, Daniel P. / Sexton, David M. H. / Symonds, Christopher / Langton, Tom / Watson-Paris, Duncan / Mulcahy, Jane P. / Pringle, Kirsty J. / Richardson, Mark / Johnson, Jill S. / Rostron, John W. / Gordon, Hamish / Lister, Grenville / Stier, Philip / Carslaw, Ken S.

eISSN:

2023

Abstract: Aerosol radiative forcing uncertainty affects estimates of climate sensitivity and limits model skill at making climate projections. Efforts to improve the representations of physical processes in climate models, including extensive comparisons with ... ...

Abstract	Aerosol radiative forcing uncertainty affects estimates of climate sensitivity and limits model skill at making climate projections. Efforts to improve the representations of physical processes in climate models, including extensive comparisons with observations, have not significantly constrained the range of possible aerosol forcing values. A far stronger constraint, in particular for the lower (most-negative) bound, can be achieved using global mean energy-balance arguments based on observed changes in historical temperature. Here, we show that structural deficiencies in a climate model, revealed as inconsistencies among observationally constrained cloud properties in the model, limit the effectiveness of observational constraint of the uncertain physical processes. We sample uncertainty in 37 model parameters related to aerosols, clouds and radiation in a perturbed parameter ensemble of the UK Earth System Model and evaluate 1 million model variants (different parameter settings from Gaussian Process emulators) against satellite-derived observations over several cloudy regions. We show that it is possible to reduce the parametric uncertainty in global mean aerosol forcing by more than 50 %, constraining it to a range in close agreement with energy-balance constraints (around −1.3 to −0.1 W m −2 ). However, our analysis of a very large set of model variants exposes model internal inconsistencies that would not be apparent in a small set of model simulations. Incorporating observations associated with these inconsistencies weakens the forcing constraint because they require a wider range of parameter values to accommodate conflicting information. Our estimated aerosol forcing range is the maximum feasible constraint using our structurally imperfect model and the chosen observations. Structural model developments targeted at the identified inconsistencies would enable a larger set of observations to be used for constraint, which would then narrow the uncertainty further. Such an approach provides a rigorous ...
Subject code	551
Language	English
Publishing date	2023-02-16
Publishing country	de
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Aerosols in the Pre-industrial Atmosphere.

Carslaw, Kenneth S / Gordon, Hamish / Hamilton, Douglas S / Johnson, Jill S / Regayre, Leighton A / Yoshioka, M / Pringle, Kirsty J

Current climate change reports

2017 Volume 3, Issue 1, Page(s) 1–15

Abstract: Purpose of review: We assess the current understanding of the state and behaviour of aerosols under pre-industrial conditions and the importance for climate.: Recent findings: Studies show that the magnitude of anthropogenic aerosol radiative forcing ...

Abstract	Purpose of review: We assess the current understanding of the state and behaviour of aerosols under pre-industrial conditions and the importance for climate. Recent findings: Studies show that the magnitude of anthropogenic aerosol radiative forcing over the industrial period calculated by climate models is strongly affected by the abundance and properties of aerosols in the pre-industrial atmosphere. The low concentration of aerosol particles under relatively pristine conditions means that global mean cloud albedo may have been twice as sensitive to changes in natural aerosol emissions under pre-industrial conditions compared to present-day conditions. Consequently, the discovery of new aerosol formation processes and revisions to aerosol emissions have large effects on simulated historical aerosol radiative forcing. Summary: We review what is known about the microphysical, chemical, and radiative properties of aerosols in the pre-industrial atmosphere and the processes that control them. Aerosol properties were controlled by a combination of natural emissions, modification of the natural emissions by human activities such as land-use change, and anthropogenic emissions from biofuel combustion and early industrial processes. Although aerosol concentrations were lower in the pre-industrial atmosphere than today, model simulations show that relatively high aerosol concentrations could have been maintained over continental regions due to biogenically controlled new particle formation and wildfires. Despite the importance of pre-industrial aerosols for historical climate change, the relevant processes and emissions are given relatively little consideration in climate models, and there have been very few attempts to evaluate them. Consequently, we have very low confidence in the ability of models to simulate the aerosol conditions that form the baseline for historical climate simulations. Nevertheless, it is clear that the 1850s should be regarded as an early industrial reference period, and the aerosol forcing calculated from this period is smaller than the forcing since 1750. Improvements in historical reconstructions of natural and early anthropogenic emissions, exploitation of new Earth system models, and a deeper understanding and evaluation of the controlling processes are key aspects to reducing uncertainties in future.
Language	English
Publishing date	2017-03-11
Publishing country	Switzerland
Document type	Journal Article ; Review
ISSN	2198-6061
ISSN	2198-6061
DOI	10.1007/s40641-017-0061-2
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: Identifying climate model structural inconsistencies allows for tight constraint of aerosol radiative forcing

Regayre, Leighton A. / Deaconu, Lucia / Grosvenor, Daniel P. / Sexton, David / Symonds, Christopher C. / Langton, Tom / Watson-Paris, Duncan / Mulcahy, Jane P. / Pringle, Kirsty J. / Richardson, Mark / Johnson, Jill S. / Rostron, John / Gordon, Hamish / Lister, Grenville / Stier, Philip / Carslaw, Ken S.

eISSN:

2022

Abstract	Aerosol radiative forcing uncertainty affects estimates of climate sensitivity and limits model skill at making climate projections. Efforts to improve the representations of physical processes in climate models, including extensive comparisons with observations, have not significantly constrained the range of possible aerosol forcing values. A far stronger constraint, in particular for the lower (most-negative) bound, can be achieved using global mean energy-balance arguments based on observed changes in historical temperature. Here, we show that structural deficiencies in a climate model, revealed as inconsistencies among observationally constrained cloud properties, limit the effectiveness of observational constraint of the uncertain physical processes. We sample uncertainty in 37 model parameters related to aerosols, clouds and radiation in a perturbed parameter ensemble of the UK Earth System Model and evaluate one million model variants (different parameter settings from Gaussian Process emulators) against satellite-derived observations over several cloudy regions. We show it is possible to reduce the parametric uncertainty in global mean aerosol forcing by more than 50 % to a range in close agreement with energy-balance constraints (around -1.3 to -0.1 W m -2 ). However, incorporating observations associated with model inconsistencies weakens the constraint because the inconsistencies introduce conflicting information about relationships between model parameter values and aerosol forcing. Our estimated aerosol forcing range is the maximum feasible constraint using these observations and our structurally imperfect model. Structural model developments, targeted at the inconsistencies identified here, would enable a larger set of observations to be used for constraint, which would then narrow the uncertainty further.
Subject code	551
Language	English
Publishing date	2022-11-28
Publishing country	de
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Aerosols in the Pre-industrial Atmosphere

Carslaw, Kenneth S / Gordon, Hamish / Hamilton, Douglas S / Johnson, Jill S / Regayre, Leighton A / Yoshioka, M / Pringle, Kirsty J

Curr Clim Change Rep. 2017 Mar., v. 3, no. 1

2017

Abstract: PURPOSE OF REVIEW: We assess the current understanding of the state and behaviour of aerosols under pre-industrial conditions and the importance for climate. RECENT FINDINGS: Studies show that the magnitude of anthropogenic aerosol radiative forcing over ...

Abstract	PURPOSE OF REVIEW: We assess the current understanding of the state and behaviour of aerosols under pre-industrial conditions and the importance for climate. RECENT FINDINGS: Studies show that the magnitude of anthropogenic aerosol radiative forcing over the industrial period calculated by climate models is strongly affected by the abundance and properties of aerosols in the pre-industrial atmosphere. The low concentration of aerosol particles under relatively pristine conditions means that global mean cloud albedo may have been twice as sensitive to changes in natural aerosol emissions under pre-industrial conditions compared to present-day conditions. Consequently, the discovery of new aerosol formation processes and revisions to aerosol emissions have large effects on simulated historical aerosol radiative forcing. We review what is known about the microphysical, chemical, and radiative properties of aerosols in the pre-industrial atmosphere and the processes that control them. Aerosol properties were controlled by a combination of natural emissions, modification of the natural emissions by human activities such as land-use change, and anthropogenic emissions from biofuel combustion and early industrial processes. Although aerosol concentrations were lower in the pre-industrial atmosphere than today, model simulations show that relatively high aerosol concentrations could have been maintained over continental regions due to biogenically controlled new particle formation and wildfires. Despite the importance of pre-industrial aerosols for historical climate change, the relevant processes and emissions are given relatively little consideration in climate models, and there have been very few attempts to evaluate them. Consequently, we have very low confidence in the ability of models to simulate the aerosol conditions that form the baseline for historical climate simulations. Nevertheless, it is clear that the 1850s should be regarded as an early industrial reference period, and the aerosol forcing calculated from this period is smaller than the forcing since 1750. Improvements in historical reconstructions of natural and early anthropogenic emissions, exploitation of new Earth system models, and a deeper understanding and evaluation of the controlling processes are key aspects to reducing uncertainties in future.
Keywords	aerosols ; biofuels ; climate ; climate change ; climate models ; combustion ; emissions ; land use change ; radiative forcing ; simulation models ; uncertainty ; wildfires
Language	English
Dates of publication	2017-03
Size	p. 1-15.
Publishing place	Springer International Publishing
Document type	Article
Note	Review
ISSN	2198-6061
DOI	10.1007/s40641-017-0061-2
Database	NAL-Catalogue (AGRICOLA)

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Book ; Online: FAIR v1.3

Smith, Christopher J. / Forster, Piers M. / Allen, Myles / Leach, Nicholas / Millar, Richard J. / Passerello, Giovanni A. / Regayre, Leighton A.

eISSN: 1991-9603

a simple emissions-based impulse response and carbon cycle model

2019

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, ... ...

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 CO 2 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 CO 2 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.
Subject code	333
Language	English
Publishing date	2019-01-28
Publishing country	de
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: The importance of comprehensive parameter sampling and multiple observations for robust constraint of aerosol radiative forcing

Johnson, Jill S. / Regayre, Leighton A. / Yoshioka, Masaru / Pringle, Kirsty J. / Lee, Lindsay A. / Sexton, David M. H. / Rostron, John W. / Booth, Ben B. B. / Carslaw, Kenneth S.

eISSN: 1680-7324

2019

Abstract: Observational constraint of simulated aerosol and cloud properties is an essential part of building trustworthy climate models for calculating aerosol radiative forcing. Models are usually tuned to achieve good agreement with observations, but tuning ... ...

Abstract	Observational constraint of simulated aerosol and cloud properties is an essential part of building trustworthy climate models for calculating aerosol radiative forcing. Models are usually tuned to achieve good agreement with observations, but tuning produces just one of many potential variants of a model, so the model uncertainty cannot be determined. Here we estimate the uncertainty in aerosol effective radiative forcing (ERF) in a tuned climate model by constraining 4 million variants of the HadGEM3-UKCA aerosol–climate model to match nine common observations (top-of-atmosphere shortwave flux, aerosol optical depth, PM 2.5 , cloud condensation nuclei at 0.2 % supersaturation (CCN 0.2 ), and concentrations of sulfate, black carbon and organic carbon, as well as decadal trends in aerosol optical depth and surface shortwave radiation.) The model uncertainty is calculated by using a perturbed parameter ensemble that samples 27 uncertainties in both the aerosol model and the physical climate model, and we use synthetic observations generated from the model itself to determine the potential of each observational type to constrain this uncertainty. Focusing over Europe in July, we show that the aerosol ERF uncertainty can be reduced by about 30 % by constraining it to the nine observations, demonstrating that producing climate models with an observationally plausible “base state” can contribute to narrowing the uncertainty in aerosol ERF. However, the uncertainty in the aerosol ERF after observational constraint is large compared to the typical spread of a multi-model ensemble. Our results therefore raise questions about whether the underlying multi-model uncertainty would be larger if similar approaches as adopted here were applied more widely. The approach presented in this study could be used to identify the most effective observations for model constraint. It is hoped that aerosol ERF uncertainty can be further reduced by introducing process-related constraints; however, any such results will be robust only if the enormous number of potential model variants is explored.
Subject code	551
Language	English
Publishing date	2019-02-01
Publishing country	de
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Aerosol and physical atmosphere model parameters are both important sources of uncertainty in aerosol ERF

Regayre, Leighton A. / Johnson, Jill S. / Yoshioka, Masaru / Pringle, Kirsty J. / Sexton, David M. H. / Booth, Ben B. B. / Lee, Lindsay A. / Bellouin, Nicolas / Carslaw, Kenneth S.

eISSN: 1680-7324

2018

Abstract: Changes in aerosols cause a change in net top-of-the-atmosphere (ToA) short-wave and long-wave radiative fluxes; rapid adjustments in clouds, water vapour and temperature; and an effective radiative forcing (ERF) of the planetary energy budget. The ... ...

Abstract	Changes in aerosols cause a change in net top-of-the-atmosphere (ToA) short-wave and long-wave radiative fluxes; rapid adjustments in clouds, water vapour and temperature; and an effective radiative forcing (ERF) of the planetary energy budget. The diverse sources of model uncertainty and the computational cost of running climate models make it difficult to isolate the main causes of aerosol ERF uncertainty and to understand how observations can be used to constrain it. We explore the aerosol ERF uncertainty by using fast model emulators to generate a very large set of aerosol–climate model variants that span the model uncertainty due to 27 parameters related to atmospheric and aerosol processes. Sensitivity analyses shows that the uncertainty in the ToA flux is dominated (around 80 %) by uncertainties in the physical atmosphere model, particularly parameters that affect cloud reflectivity. However, uncertainty in the change in ToA flux caused by aerosol emissions over the industrial period (the aerosol ERF) is controlled by a combination of uncertainties in aerosol (around 60 %) and physical atmosphere (around 40 %) parameters. Four atmospheric and aerosol parameters account for around 80 % of the uncertainty in short-wave ToA flux (mostly parameters that directly scale cloud reflectivity, cloud water content or cloud droplet concentrations), and these parameters also account for around 60 % of the aerosol ERF uncertainty. The common causes of uncertainty mean that constraining the modelled planetary brightness to tightly match satellite observations changes the lower 95 % credible aerosol ERF value from −2.65 to −2.37 W m −2 . This suggests the strongest forcings (below around −2.4 W m −2 ) are inconsistent with observations. These results show that, regardless of the fact that the ToA flux is 2 orders of magnitude larger than the aerosol ERF, the observed flux can constrain the uncertainty in ERF because their values are connected by constrainable process parameters. The key to reducing the aerosol ERF uncertainty further will be to identify observations that can additionally constrain individual parameter ranges and/or combined parameter effects, which can be achieved through sensitivity analysis of perturbed parameter ensembles.
Subject code	551
Language	English
Publishing date	2018-07-13
Publishing country	de
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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

Johnson, Jill S. / Regayre, Leighton A. / Yoshioka, Masaru / Pringle, Kirsty J. / Turnock, Steven T. / Browse, Jo / Sexton, David M. H. / Rostron, John W. / Schutgens, Nick A. J. / Partridge, Daniel G. / Liu, Dantong / Allan, James D. / Coe, Hugh / Ding, Aijun / Cohen, David D. / Atanacio, Armand / Vakkari, Ville / Asmi, Eija / Carslaw, Ken S.

eISSN: 1680-7324

2020

Abstract: The 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) ...

Abstract	The 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, PM 2.5 , 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 SO 2 emissions, residential emissions, sea spray emissions, dry deposition rates of SO 2 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 ±1 σ (standard deviation) range of global annual mean direct radiative forcing (RF ari ) 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, RF aci , the ±1 σ 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 PM 2.5 measurements individually result in RF ari ±1 σ ranges that only just overlap, which shows that emergent constraints based on one measurement type may be overconfident.
Subject code	511 ; 333
Language	English
Publishing date	2020-08-13
Publishing country	de
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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