ORCID Profile
0000-0003-0599-4633
Current Organisations
Technical University of Denmark
,
Met Office
,
International Institute for Applied Systems Analysis
,
University of Leeds
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Publications
Supplementary material to "GIR v1.0.0: a generalised impulse-response model for climate uncertainty and future scenario exploration"
Publisher: Copernicus GmbH
Date: 27-01-2020
Radiative forcing of climate change from the Copernicus reanalysis of atmospheric composition
Publisher: Copernicus GmbH
Date: 25-01-2020
Abstract: Abstract. Radiative forcing provides an important basis for understanding and predicting global climate changes, but its quantification has historically been done independently for different forcing agents, involved observations to varying degrees, and studies have not always included a detailed analysis of uncertainties. The Copernicus Atmosphere Monitoring Service reanalysis is an optimal combination of modelling and observations of atmospheric composition. It provides a unique opportunity to rely on observations to quantify the monthly- and spatially-resolved global distributions of radiative forcing consistently for six of the largest forcing agents: carbon dioxide, methane, tropospheric ozone, stratospheric ozone, aerosol-radiation interactions, and aerosol-cloud interactions. These radiative forcing estimates account for adjustments in stratospheric temperatures, but do not account for rapid adjustments in the troposphere. On a global average and over the period 2003–2016, stratospherically adjusted radiative forcing of carbon dioxide has averaged +1.84 W m−2 (5–95% confidence interval: 1.46 to 2.22 W m−2) relative to 1750 and increased at a rate of 17 % per decade. The corresponding values for methane are +0.45 (0.35 to 0.55) W m−2 and 3 % per decade, but with a clear acceleration since 2007. Ozone radiative forcing averages +0.32 (0 to 0.64) W m−2 and aerosol radiative forcing averages −1.37 (−2.17 to −0.57) W m−2. Both have been relatively stable since 2003. Taking the six forcing agents together, there no indication of a slowdown or acceleration in the rate of increase in anthropogenic radiative forcing over the period. These ongoing radiative forcing estimates will monitor the impact on the Earth’s energy budget of the dramatic emission reductions towards net-zero that are needed to limit surface temperature warming to the Paris Agreement temperature targets. Indeed, such impacts should be clearly manifested in radiative forcing before being clear in the temperature record. In addition, this radiative forcing dataset can provide the input distributions needed by researchers involved in monitoring of climate change, detection and attribution, interannual to decadal prediction, and integrated assessment modelling. The data generated by this work are available at 0.24380/ads.1hj3y896 (Bellouin et al., 2020).
Reduced complexity model intercomparison project phase 1: Protocol, results and initial observations
Publisher: Copernicus GmbH
Date: 21-01-2020
DOI: 10.5194/GMD-2019-375
Abstract: Abstract. Here we present results from the first phase of the Reduced Complexity Model Intercomparison Project (RCMIP). RCMIP is a systematic examination of reduced complexity climate models (RCMs), which are used to complement and extend the insights from more complex Earth System Models (ESMs), in particular those participating in the Sixth Coupled Model Intercomparison Project (CMIP6). In Phase 1 of RCMIP, with 14 participating models namely ACC2, AR5IR (2 and 3 box versions), CICERO-SCM, ESCIMO, FaIR, GIR, GREB, Hector, Held et al. two layer model, MAGICC, MCE, OSCAR and WASP, we highlight the structural differences across various RCMs and show that RCMs are capable of reproducing global-mean surface air temperature (GSAT) changes of ESMs and historical observations. We find that some RCMs are capable of emulating the GSAT response of CMIP6 models to within a root-mean square error of 0.2 °C (of the same order of magnitude as ESM internal variability) over a range of scenarios. Running the same model configurations for both RCP and SSP scenarios, we see that the SSPs exhibit higher effective radiative forcing throughout the second half of the 21st Century. Comparing our results to the difference between CMIP5 and CMIP6 output, we find that the change in scenario explains approximately 46 % of the increase in higher end projected warming between CMIP5 and CMIP6. This suggests that changes in ESMs from CMIP5 to CMIP6 explain the rest of the increase, hence the higher climate sensitivities of available CMIP6 models may not be having as large an impact on GSAT projections as first anticipated. A second phase of RCMIP will complement RCMIP Phase 1 by exploring probabilistic results and emulation in more depth to provide results available for the IPCC's Sixth Assessment Report author teams.
The Bristol CMIP6 Data Hackathon
Publisher: Wiley
Date: 25-02-2022
DOI: 10.1002/WEA.4161
Supplementary material to "FaIRv2.0.0: a generalised impulse-response model for climate uncertainty and future scenario exploration"
Publisher: Copernicus GmbH
Date: 24-11-2020
GIR v1.0.0: a generalised impulse-response model for climate uncertainty and future scenario exploration
Publisher: Copernicus GmbH
Date: 27-01-2020
DOI: 10.5194/GMD-2019-379
Abstract: Abstract. Here we present a Generalised Impulse Response (GIR) model for use in probabilistic future climate and scenario exploration, integrated assessment, policy analysis and teaching. This model is based on a set of only six equations, which correspond to the standard Impulse Response model used for greenhouse gas metric calculations by the IPCC, plus one physically-motivated additional equation to represent state-dependent feedbacks on the response timescales of each greenhouse gas cycle. These six equations are simple and transparent enough to be easily understood and implemented in other models without reliance on the original source code, but flexible enough to reproduce observed well-mixed greenhouse gas (GHG) concentrations and atmospheric lifetimes, best-estimate effective radiative forcing, and temperature response. We describe the assumptions and methods used in selecting the default parameters, but emphasize that other methods would be equally valid: our focus here is on identifying a minimum level of structural complexity. The tunable nature of the model lends it to use as a fully transparent emulator of complex Earth System Models, such as those participating in CMIP6, while also reproducing the behaviour of other simple climate models. We argue that this GIR model is adequate to reproduce the global temperature response to global emissions and effective radiative forcing, and that it should be used as a lowest-common denominator to provide consistency and continuity between different climate assessments. The model design is such that it can be written in tabular data analysis software, such as Excel, increasing the potential user base considerably.
FAIR v1.1: A simple emissions-based impulse response and carbon cycle model
Publisher: Copernicus GmbH
Date: 07-12-2017
DOI: 10.5194/GMD-2017-266
Abstract: 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 precursors and other agents. The ERFs are integrated into global mean surface temperature change. 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. For the historical period the ERF time series in FAIR emulates the results in the IPCC Fifth Assessment Report (AR5), whereas for RCP historical and future scenarios, the greenhouse gas concentrations in FAIR closely track the observations and projections in the RCPs. The constrained estimates of equilibrium climate sensitivity (ECS) of 2.79 (1.97 to 4.08) K, transient climate response (TCR) of 1.47 (1.03 to 2.23) K and transient climate response to cumulative CO2 emissions (TCRE) of 1.43 (1.01 to 2.16) K (1000 GtC)−1 (median and 5–95 % credible intervals) are in good agreement, with tighter uncertainty bounds, than AR5 (1.5 to 4.5 K, 1.0 to 2.5 K, and 0.8 to 2.5 K respectively). The ranges of future projections of temperature and ranges of estimates of ECS, TCR and TCRE are moderately sensitive to the historical temperature dataset used to constrain, prior distributions of ECS/TCR parameters, aerosol radiative forcing relationship and ERF from a doubling of CO2. 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. However, the range of temperature projections under the RCP scenarios for 2081–2100 in the constrained FAIR model ensemble are lower than the emissions-based estimates reported in AR5.
Constraining Uncertainty in Aerosol Direct Forcing
Publisher: American Geophysical Union (AGU)
Date: 25-04-2020
DOI: 10.1029/2020GL087141
Changes in IPCC Scenario Assessment Emulators Between SR1.5 and AR6 Unraveled
Publisher: American Geophysical Union (AGU)
Date: 18-10-2022
DOI: 10.1029/2022GL099788
Abstract: The IPCC's scientific assessment of the timing of net‐zero emissions and 2030 emission reduction targets consistent with limiting warming to 1.5°C or 2°C rests on large scenario databases. Updates to this assessment, such as between the IPCC's Special Report on Global Warming of 1.5°C (SR1.5) of warming and the Sixth Assessment Report (AR6), are the result of intertwined, sometimes opaque, factors. Here we isolate one factor: the Earth System Model emulators used to estimate the global warming implications of scenarios. We show that warming projections using AR6‐calibrated emulators are consistent, to within around 0.1°C, with projections made by the emulators used in SR1.5. The consistency is due to two almost compensating changes: the increase in assessed historical warming between SR1.5 (based on AR5) and AR6, and a reduction in projected warming due to improved agreement between the emulators' response to emissions and the assessment to which it is calibrated.
FaIRv2.0.0: a generalized impulse response model for climate uncertainty and future scenario exploration
Publisher: Copernicus GmbH
Date: 27-05-2021
Abstract: Abstract. Here we present an update to the FaIR model for use in probabilistic future climate and scenario exploration, integrated assessment, policy analysis, and education. In this update we have focussed on identifying a minimum level of structural complexity in the model. The result is a set of six equations, five of which correspond to the standard impulse response model used for greenhouse gas (GHG) metric calculations in the IPCC's Fifth Assessment Report, plus one additional physically motivated equation to represent state-dependent feedbacks on the response timescales of each greenhouse gas cycle. This additional equation is necessary to reproduce non-linearities in the carbon cycle apparent in both Earth system models and observations. These six equations are transparent and sufficiently simple that the model is able to be ported into standard tabular data analysis packages, such as Excel, increasing the potential user base considerably. However, we demonstrate that the equations are flexible enough to be tuned to emulate the behaviour of several key processes within more complex models from CMIP6. The model is exceptionally quick to run, making it ideal for integrating large probabilistic ensembles. We apply a constraint based on the current estimates of the global warming trend to a million-member ensemble, using the constrained ensemble to make scenario-dependent projections and infer ranges for properties of the climate system. Through these analyses, we reaffirm that simple climate models (unlike more complex models) are not themselves intrinsically biased “hot” or “cold”: it is the choice of parameters and how those are selected that determines the model response, something that appears to have been misunderstood in the past. This updated FaIR model is able to reproduce the global climate system response to GHG and aerosol emissions with sufficient accuracy to be useful in a wide range of applications and therefore could be used as a lowest-common-denominator model to provide consistency in different contexts. The fact that FaIR can be written down in just six equations greatly aids transparency in such contexts.
Assessing the size and uncertainty of remaining carbon budgets
Publisher: Research Square Platform LLC
Date: 02-09-2022
DOI: 10.21203/RS.3.RS-1934427/V1
Abstract: The remaining carbon budget (RCB), the net amount of carbon dioxide humans can still emit without exceeding a chosen global warming limit, is often used to evaluate political action against the goals of the Paris Agreement. RCB estimates for 1.5C are small, and minor changes in their calculation can therefore result in large relative shifts. Here we evaluate recent RCB assessments by the IPCC and explain differences between them. We present calculation refinements together with robustness checks that increase confidence in RCB estimates. We conclude that the RCB for a 50% chance of keeping warming to 1.5C is around 300 GtCO2 as of January 2022, less than 8 years of current emissions. This estimate changes to 530 and 110 GtCO2 for a 33% and 66% chance, respectively. Key uncertainties affecting RCB estimates are the contribution of non-CO2 emissions, which depends on socioeconomic projections as much as on geophysical uncertainty, and the potential warming after net zero is reached.
Assessing the consistency of institutional pathways with the Paris Agreement
Publisher: Copernicus GmbH
Date: 28-03-2022
DOI: 10.5194/EGUSPHERE-EGU22-9739
Abstract: & & Scientifically rigorous guidance to policy makers on mitigation options for meeting the Paris Agreement long-term temperature goal requires an evaluation of long-term global-warming implications of greenhouse gas emissions pathways. Here, we present a uniform and transparent methodology to evaluate the climate outcome, and hence the Paris Agreement consistency of influential institutional emission scenarios from the grey literature, including those from the International Energy Agency& sup& ,2& /sup& , BP& sup& & /sup& , and Shell& sup& & /sup& . We first identify challenges to performing such an assessment and then proceed to outline a sequence of steps to address these challenges by harmonizing& sup& & /sup& all emissions to a consistent base-year (2010), extending all pathways to 2100, and filling in missing emission species& sup& & /sup& . We employ two simple climate models, MAGICC& sup& & /sup& and FaIR& sup& ,9& /sup& to assess peak and end-of-century temperatures, and find that few published scenarios that claim to be compatible with the Paris Agreement are so.& & & & & & & & & & strong& References& /strong& & & & & & strong& & . & /strong& International Energy Agency. World Energy Outlook 2020. (2020).& & & & . International Energy Agency. Net Zero by 2050 - A Roadmap for the Global Energy Sector. (2021).& & & & . BP. Global Energy Outlook 2020. (2020).& & & & . Shell. The Energy Transformation Scenarios. (2021)& & & & & . Gidden, M. J. et al. A methodology and implementation of automated emissions harmonization for use in Integrated Assessment Models. Environ. Model. Softw. 105, 187& #8211 (2018)& & & & . Lamboll, R. D., Nicholls, Z. R. J., Kikstra, J. S., Meinshausen, M. & Rogelj, J. Silicone v1.0.0& #8239 : an open-source Python package for inferring missing emissions data for climate change research. Geosci. Model Dev 13, 5259& #8211 (2020)& & & & . Meinshausen, M., Raper, S. C. B. & Wigley, T. M. L. Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 - Part 1: Model description and calibration. Atmos. Chem. Phys. 11, 1417& #8211 (2011).& & & & . Smith, C. J. et al. FAIR v1.3: A simple emissions-based impulse response and carbon cycle model. Geosci. Model Dev. 11, 2273& #8211 (2018)& & & & . Millar, J. R., Nicholls, Z. R., Friedlingstein, P. & Allen, M. R. A modified impulse-response representation of the global near-surface air temperature and atmospheric concentration response to carbon dioxide emissions. Atmos. Chem. Phys. 17, 7213& #8211 (2017).& &
Institutional decarbonization scenarios evaluated against the Paris Agreement 1.5 °C goal
Publisher: Springer Science and Business Media LLC
Date: 16-08-2022
DOI: 10.1038/S41467-022-31734-1
Abstract: Scientifically rigorous guidance to policy makers on mitigation options for meeting the Paris Agreement long-term temperature goal requires an evaluation of long-term global-warming implications of greenhouse gas emissions pathways. Here we employ a uniform and transparent methodology to evaluate Paris Agreement compatibility of influential institutional emission scenarios from the grey literature, including those from Shell, BP, and the International Energy Agency. We compare a selection of these scenarios analysed with this methodology to the Integrated Assessment Model scenarios assessed by the Intergovernmental Panel on Climate Change. We harmonize emissions to a consistent base-year and account for all greenhouse gases and aerosol precursor emissions, ensuring a self-consistent comparison of climate variables. An evaluation of peak and end-of-century temperatures is made, with both being relevant to the Paris Agreement goal. Of the scenarios assessed, we find that only the IEA Net Zero 2050 scenario is aligned with the criteria for Paris Agreement consistency employed here. We investigate root causes for misalignment with these criteria based on the underlying energy system transformation.
The IPCC Sixth Assessment Report WGIII climate assessment of mitigation pathways: from emissions to global temperatures
Publisher: Copernicus GmbH
Date: 20-12-2022
Abstract: Abstract. While the Intergovernmental Panel on Climate Change (IPCC) physical science reports usually assess a handful of future scenarios, the Working Group III contribution on climate mitigation to the IPCC's Sixth Assessment Report (AR6 WGIII) assesses hundreds to thousands of future emissions scenarios. A key task in WGIII is to assess the global mean temperature outcomes of these scenarios in a consistent manner, given the challenge that the emissions scenarios from different integrated assessment models (IAMs) come with different sectoral and gas-to-gas coverage and cannot all be assessed consistently by complex Earth system models. In this work, we describe the “climate-assessment” workflow and its methods, including infilling of missing emissions and emissions harmonisation as applied to 1202 mitigation scenarios in AR6 WGIII. We evaluate the global mean temperature projections and effective radiative forcing (ERF) characteristics of climate emulators FaIRv1.6.2 and MAGICCv7.5.3 and use the CICERO simple climate model (CICERO-SCM) for sensitivity analysis. We discuss the implied overshoot severity of the mitigation pathways using overshoot degree years and look at emissions and temperature characteristics of scenarios compatible with one possible interpretation of the Paris Agreement. We find that the lowest class of emissions scenarios that limit global warming to “1.5 ∘C (with a probability of greater than 50 %) with no or limited overshoot” includes 97 scenarios for MAGICCv7.5.3 and 203 for FaIRv1.6.2. For the MAGICCv7.5.3 results, “limited overshoot” typically implies exceedance of median temperature projections of up to about 0.1 ∘C for up to a few decades before returning to below 1.5 ∘C by or before the year 2100. For more than half of the scenarios in this category that comply with three criteria for being “Paris-compatible”, including net-zero or net-negative greenhouse gas (GHG) emissions, median temperatures decline by about 0.3–0.4 ∘C after peaking at 1.5–1.6 ∘C in 2035–2055. We compare the methods applied in AR6 with the methods used for SR1.5 and discuss their implications. This article also introduces a “climate-assessment” Python package which allows for fully reproducing the IPCC AR6 WGIII temperature assessment. This work provides a community tool for assessing the temperature outcomes of emissions pathways and provides a basis for further work such as extending the workflow to include downscaling of climate characteristics to a regional level and calculating impacts.
The IPCC Sixth Assessment Report WGIII climate assessment of mitigation pathways: from emissions to global temperatures
Publisher: Copernicus GmbH
Date: 28-06-2022
DOI: 10.5194/EGUSPHERE-2022-471
Abstract: Abstract. While the IPCC’s physical science report usually assesses a handful of future scenarios, the IPCC Sixth Assessment Working Group III report (AR6 WGIII) on climate mitigation assesses hundreds to thousands of future emissions scenarios. A key task is to assess the global-mean temperature outcomes of these scenarios in a consistent manner, given the challenge that the emission scenarios from different integrated assessment models come with different sectoral and gas-to-gas coverage and cannot all be assessed consistently by complex Earth System Models. In this work, we describe the “climate assessment” workflow and its methods, including infilling of missing emissions and emissions harmonisation as applied to 1,202 mitigation scenarios in AR6 WGIII. We evaluate the global-mean temperature projections and effective radiative forcing characteristics (ERF) of climate emulators FaIRv1.6.2, MAGICCv7.5.3, and CICERO-SCM, discuss overshoot severity of the mitigation pathways using overshoot degree years, and look at an interpretation of compatibility with the Paris Agreement. We find that the lowest class of emission scenarios that limit global warming to “1.5 °C (with a probability of greater than 50 %) with no or limited overshoot” includes 90 scenarios for MAGICCv7.5.3, and 196 for FaIRv1.6.2. For the MAGICCv7.5.3 results, “limited overshoot” typically implies exceedance of median temperature projections of up to about 0.1 °C for up to a few decades, before returning to below 1.5 °C by or before the year 2100. For more than half of the scenarios of this category that comply with three criteria for being “Paris-compatible”, including net-zero or net-negative greenhouse gas (GHG) emissions, are projected to see median temperatures decline by about 0.3–0.4 °C after peaking at 1.5–1.6 °C in 2035–2055. We compare the methods applied in AR6 with the methods used for SR1.5 and discuss the implications. This article also introduces a ‘climate-assessment’ Python package which allows for fully reproducing the IPCC AR6 WGIII temperature assessment. This work can be the start of a community tool for assessing the temperature outcomes related to emissions pathways, and potential further work extending the workflow from emissions to global climate by downscaling climate characteristics to a regional level and calculating impacts.
Projected land ice contributions to twenty-first-century sea level rise
Publisher: Springer Science and Business Media LLC
Date: 05-05-2021
Stochastic generation of synthetic minutely irradiance time series derived from mean hourly weather observation data
Publisher: Elsevier BV
Date: 05-2015
Supplementary material to The IPCC Sixth Assessment Report WGIII climate assessment of mitigation pathways: from emissions to global temperatures
Publisher: Copernicus GmbH
Date: 28-06-2022
Uncompensated claims to fair emission space risk putting Paris Agreement goals out of reach
Publisher: IOP Publishing
Date: 02-2023
Abstract: Addressing questions of equitable contributions to emission reductions is important to facilitate ambitious global action on climate change within the ambit of the Paris Agreement. Several large developing regions with low historical contributions to global warming have a strong moral claim to a large proportion of the remaining carbon budget (RCB). However, this claim needs to be assessed in a context where the RCB consistent with the long-term temperature goal (LTTG) of the Paris Agreement is rapidly diminishing. Here we assess the potential tension between the moral claim to the remaining carbon space by large developing regions with low per capita emissions, and the collective obligation to achieve the goals of the Paris Agreement. Based on scenarios underlying the IPCC’s 6th Assessment Report, we construct a suite of scenarios that combine the following elements: (a) two quantifications of a moral claim to the remaining carbon space by South Asia, and Africa, (b) a ‘highest possible emission reduction’ effort by developed regions (DRs), and (c) a corresponding range for other developing regions (ODR). We find that even the best effort by DRs cannot compensate for a unilateral claim to the remaining carbon space by South Asia and Africa. This would put the LTTG firmly out of reach unless ODRs cede their moral claim to emissions space and, like DRs, pursue highest possible emission reductions, which would also constitute an inequitable outcome. Furthermore, regions such as Latin America would need to provide large-scale negative emissions with potential risks and negative side effects. Our findings raise important questions of perspectives on equity in the context of the Paris Agreement including on the critical importance of climate finance. A failure to provide adequate levels of financial support to compensate large developing regions to emit less than their moral claim will put the Paris Agreement at risk.
FAIR v1.3: a simple emissions-based impulse response and carbon cycle model
Publisher: Copernicus GmbH
Date: 18-06-2018
Abstract: 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 CO2 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 CO2 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.
Uncompensated claims to fair emission space risk putting Paris Agreement goals out of reach
Publisher: Wiley
Date: 04-11-2022
FaIRv2.0.0: a generalised impulse-response model for climate uncertainty and future scenario exploration
Publisher: Copernicus GmbH
Date: 24-11-2020
DOI: 10.5194/GMD-2020-390
Abstract: Abstract. Here we present an update to the FaIR model for use in probabilistic future climate and scenario exploration, integrated assessment, policy analysis and education. In this update we have focussed on identifying a minimum level of structural complexity in the model. The result is a set of six equations, five of which correspond to the standard Impulse Response model used for greenhouse gas (GHG) metric calculations in the IPCC's fifth assessment report, plus one additional physically-motivated additional equation to represent state-dependent feedbacks on the response timescales of each greenhouse gas cycle. This additional equation is necessary to reproduce non-linearities in the carbon cycle apparent in both Earth System Models and observations. These six equations are transparent and sufficiently simple that the model is able to be written in standard tabular data analysis packages, such as Excel increasing the potential user base considerably. However, we demonstrate that the equations are flexible enough to be tuned to emulate the behaviour of several key processes within more complex models from CMIP6. The model is exceptionally quick to run, making it ideal for integrating large probabilistic ensembles. We apply a constraint based on the current estimates of the global warming trend to a one million member ensemble, using the constrained ensemble to make scenario dependent projections and infer ranges for properties of the climate system. Through these analyses, we reaffirm that simple climate models (unlike more complex models) are not themselves intrinsically biased hot or cold: it is the choice of parameters and how those are selected that determines the model response, something that appears to have been misunderstood in the past. This updated FaIR model is able to reproduce the global climate system response to GHG and aerosol emissions with sufficient accuracy to be useful in a wide range of applications and therefore could be used as a lowest common denominator model to provide consistency in different contexts. The fact that FaIR can be written down in just six equations greatly aids transparency in such contexts.
Reduced Complexity Model Intercomparison Project Phase 2: Synthesizing Earth System Knowledge for Probabilistic Climate Projections
Publisher: American Geophysical Union (AGU)
Date: 06-2021
DOI: 10.1029/2020EF001900
Abstract: Over the last decades, climate science has evolved rapidly across multiple expert domains. Our best tools to capture state‐of‐the‐art knowledge in an internally self‐consistent modeling framework are the increasingly complex fully coupled Earth System Models (ESMs). However, computational limitations and the structural rigidity of ESMs mean that the full range of uncertainties across multiple domains are difficult to capture with ESMs alone. The tools of choice are instead more computationally efficient reduced complexity models (RCMs), which are structurally flexible and can span the response dynamics across a range of domain‐specific models and ESM experiments. Here we present Phase 2 of the Reduced Complexity Model Intercomparison Project (RCMIP Phase 2), the first comprehensive intercomparison of RCMs that are probabilistically calibrated with key benchmark ranges from specialized research communities. Unsurprisingly, but crucially, we find that models which have been constrained to reflect the key benchmarks better reflect the key benchmarks. Under the low‐emissions SSP1‐1.9 scenario, across the RCMs, median peak warming projections range from 1.3 to 1.7°C (relative to 1850–1900, using an observationally based historical warming estimate of 0.8°C between 1850–1900 and 1995–2014). Further developing methodologies to constrain these projection uncertainties seems paramount given the international community's goal to contain warming to below 1.5°C above preindustrial in the long‐term. Our findings suggest that users of RCMs should carefully evaluate their RCM, specifically its skill against key benchmarks and consider the need to include projections benchmarks either from ESM results or other assessments to reduce ergence in future projections.
Forecasting Operational Conditions: A case-study from dewatering of biomass at an industrial wastewater treatment plant
Publisher: Elsevier
Date: 2022
Assessing the size and uncertainty of remaining carbon budgets
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-7143
Abstract: The remaining carbon budget (RCB), the net amount of carbon dioxide humans can still emit without exceeding a chosen global warming limit, is often used to evaluate political action against the goals of the Paris Agreement. RCB estimates for 1.5C are small, and minor changes in their calculation can therefore result in large relative shifts. Here we evaluate recent RCB assessments by the IPCC and explain differences between them. We present calculation refinements together with robustness checks that increase confidence in RCB estimates. We conclude that the RCB for a 50% chance of keeping warming to 1.5C is around 250 GtCO2 as of January 2023, around 6 years of current CO2 emissions. This estimate changes to 480 and 60 GtCO2 for a 33% and 66% chance, respectively. Key uncertainties affecting RCB estimates are the contribution of non-CO2 emissions, which depends on socioeconomic projections as much as on geophysical uncertainty, and potential warming after net zero is reached.&
Changes in IPCC scenario assessment emulators between SR1.5 and AR6 unravelled
Publisher: Wiley
Date: 20-09-2022
Reduced Complexity Model Intercomparison Project Phase 2: Synthesising Earth system knowledge for probabilistic climate projections
Publisher: Wiley
Date: 23-11-2020
Reduced Complexity Model Intercomparison Project Phase 2: Synthesising Earth system knowledge for probabilistic climate projections
Publisher: Wiley
Date: 17-03-2021
Cloud cover effect of clear-sky index distributions and differences between human and automatic cloud observations
Publisher: Elsevier BV
Date: 03-2017
A precautionary approach to carbon dioxide removal needs
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-14436
Abstract: A central finding of the most recent reports of the Intergovernmental Panel on Climate Change (IPCC) is that net zero CO2 emissions are required for stabilizing CO2-induced global average surface temperature increase. However, given substantial uncertainties of the earth system response after reaching net zero CO2, outcomes of long-term declining, or continuously increasing global temperatures after achieving and maintaining net zero CO2 emissions cannot be excluded. At the same time, nearly all emission reduction pathways& assessed by the IPCC, which are consistent with global climate goals, require large-scale deployment of carbon dioxide removal (CDR) to balance remaining positive emissions and to draw down temperatures after a peak. Using evidence from Earth System Models and Simple Climate Models we show that peaking global mean temperature may potentially require net CO2 removals of the order of several hundred gigatonnes (Gt) sustained over multiple decades in case of strong positive earth system feedbacks. We also estimate the contribution of scenario uncertainty (e.g., reduction in emissions of different greenhouse gases) to such net CO2 removal figures. A precautionary approach to ensure a very high chance of peaking of global mean temperature may therefore require the availability of substantial amounts of CDR. Our findings have direct implications for CDR needs in order to achieve the long-term temperature goal of the Paris Agreement. The potential risk of strong earth system feedback outcomes have to be carefully considered when discussing temperature reversal in case of a (temporary) overshoot above the 1.5& #176 C threshold, in particular as there are well-documented biophysical, technological and sustainability limits to CDR deployment.
A perspective on the next generation of Earth system model scenarios: towards representative emission pathways (REPs)
Publisher: Copernicus GmbH
Date: 06-09-2023
DOI: 10.5194/GMD-2023-176
Sensitivity of Historical Climate Simulations to Uncertain Aerosol Forcing
Publisher: American Geophysical Union (AGU)
Date: 25-06-2020
DOI: 10.1029/2019GL085806
Assessing the size and uncertainty of remaining carbon budgets
Publisher: Springer Science and Business Media LLC
Date: 30-10-2023
pyam: Analysis and visualisation of integrated assessment and macro-energy scenarios
Publisher: F1000 Research Ltd
Date: 28-06-2021
DOI: 10.12688/OPENRESEUROPE.13633.1
Abstract: The open-source Python package pyam provides a suite of features and methods for the analysis, validation and visualization of reference data and scenario results generated by integrated assessment models, macro-energy tools and other frameworks in the domain of energy transition, climate change mitigation and sustainable development. It bridges the gap between scenario processing and visualisation solutions that are "hard-wired" to specific modelling frameworks and generic data analysis or plotting packages. The package aims to facilitate reproducibility and reliability of scenario processing, validation and analysis by providing well-tested and documented methods for timeseries aggregation, downscaling and unit conversion. It supports various data formats, including sub-annual resolution using continuous time representation and "representative timeslices". The code base is implemented following best practices of collaborative scientific-software development. This manuscript describes the design principles of the package and the types of data which can be handled. The usefulness of pyam is illustrated by highlighting several recent applications.
Supplementary material to "Reduced complexity model intercomparison project phase 1: Protocol, results and initial observations"
Publisher: Copernicus GmbH
Date: 21-01-2020
Radiative forcing of climate change from the Copernicus reanalysis of atmospheric composition
Publisher: Copernicus GmbH
Date: 16-07-2020
DOI: 10.5194/ESSD-12-1649-2020
Abstract: Abstract. Radiative forcing provides an important basis for understanding and predicting global climate changes, but its quantification has historically been done independently for different forcing agents, has involved observations to varying degrees, and studies have not always included a detailed analysis of uncertainties. The Copernicus Atmosphere Monitoring Service reanalysis is an optimal combination of modelling and observations of atmospheric composition. It provides a unique opportunity to rely on observations to quantify the monthly and spatially resolved global distributions of radiative forcing consistently for six of the largest forcing agents: carbon dioxide, methane, tropospheric ozone, stratospheric ozone, aerosol–radiation interactions, and aerosol–cloud interactions. These radiative-forcing estimates account for adjustments in stratospheric temperatures but do not account for rapid adjustments in the troposphere. On a global average and over the period 2003–2017, stratospherically adjusted radiative forcing of carbon dioxide has averaged +1.89 W m−2 (5 %–95 % confidence interval: 1.50 to 2.29 W m−2) relative to 1750 and increased at a rate of 18 % per decade. The corresponding values for methane are +0.46 (0.36 to 0.56) W m−2 and 4 % per decade but with a clear acceleration since 2007. Ozone radiative-forcing averages +0.32 (0 to 0.64) W m−2, almost entirely contributed by tropospheric ozone since stratospheric ozone radiative forcing is only +0.003 W m−2. Aerosol radiative-forcing averages −1.25 (−1.98 to −0.52) W m−2, with aerosol–radiation interactions contributing −0.56 W m−2 and aerosol–cloud interactions contributing −0.69 W m−2 to the global average. Both have been relatively stable since 2003. Taking the six forcing agents together, there is no indication of a sustained slowdown or acceleration in the rate of increase in anthropogenic radiative forcing over the period. These ongoing radiative-forcing estimates will monitor the impact on the Earth's energy budget of the dramatic emission reductions towards net-zero that are needed to limit surface temperature warming to the Paris Agreement temperature targets. Indeed, such impacts should be clearly manifested in radiative forcing before being clear in the temperature record. In addition, this radiative-forcing dataset can provide the input distributions needed by researchers involved in monitoring of climate change, detection and attribution, interannual to decadal prediction, and integrated assessment modelling. The data generated by this work are available at 0.24380/ads.1hj3y896 (Bellouin et al., 2020b).
pyam: Analysis and visualisation of integrated assessment and macro-energy scenarios
Publisher: F1000 Research Ltd
Date: 09-2021
DOI: 10.12688/OPENRESEUROPE.13633.2
Abstract: The open-source Python package pyam provides a suite of features and methods for the analysis, validation and visualization of reference data and scenario results generated by integrated assessment models, macro-energy tools and other frameworks in the domain of energy transition, climate change mitigation and sustainable development. It bridges the gap between scenario processing and visualisation solutions that are "hard-wired" to specific modelling frameworks and generic data analysis or plotting packages. The package aims to facilitate reproducibility and reliability of scenario processing, validation and analysis by providing well-tested and documented methods for working with timeseries data in the context of climate policy and energy systems. It supports various data formats, including sub-annual resolution using continuous time representation and "representative timeslices". The pyam package can be useful for modelers generating scenario results using their own tools as well as researchers and analysts working with existing scenario ensembles such as those supporting the IPCC reports or produced in research projects. It is structured in a way that it can be applied irrespective of a user's domain expertise or level of Python knowledge, supporting experts as well as novice users. The code base is implemented following best practices of collaborative scientific-software development. This manuscript describes the design principles of the package and the types of data which can be handled. The usefulness of pyam is illustrated by highlighting several recent applications.
Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response
Publisher: Copernicus GmbH
Date: 31-10-2020
Abstract: Abstract. Reduced-complexity climate models (RCMs) are critical in the policy and decision making space, and are directly used within multiple Intergovernmental Panel on Climate Change (IPCC) reports to complement the results of more comprehensive Earth system models. To date, evaluation of RCMs has been limited to a few independent studies. Here we introduce a systematic evaluation of RCMs in the form of the Reduced Complexity Model Intercomparison Project (RCMIP). We expect RCMIP will extend over multiple phases, with Phase 1 being the first. In Phase 1, we focus on the RCMs' global-mean temperature responses, comparing them to observations, exploring the extent to which they emulate more complex models and considering how the relationship between temperature and cumulative emissions of CO2 varies across the RCMs. Our work uses experiments which mirror those found in the Coupled Model Intercomparison Project (CMIP), which focuses on complex Earth system and atmosphere–ocean general circulation models. Using both scenario-based and idealised experiments, we examine RCMs' global-mean temperature response under a range of forcings. We find that the RCMs can all reproduce the approximately 1 ∘C of warming since pre-industrial times, with varying representations of natural variability, volcanic eruptions and aerosols. We also find that RCMs can emulate the global-mean temperature response of CMIP models to within a root-mean-square error of 0.2 ∘C over a range of experiments. Furthermore, we find that, for the Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP)-based scenario pairs that share the same IPCC Fifth Assessment Report (AR5)-consistent stratospheric-adjusted radiative forcing, the RCMs indicate higher effective radiative forcings for the SSP-based scenarios and correspondingly higher temperatures when run with the same climate settings. In our idealised setup of RCMs with a climate sensitivity of 3 ∘C, the difference for the ssp585–rcp85 pair by 2100 is around 0.23∘C(±0.12 ∘C) due to a difference in effective radiative forcings between the two scenarios. Phase 1 demonstrates the utility of RCMIP's open-source infrastructure, paving the way for further phases of RCMIP to build on the research presented here and deepen our understanding of RCMs.
Related Organisations
Met Office
Location: United Kingdom of Great Britain and Northern Ireland
International Institute For Applied Systems Analysis
Location: Austria
University Of Leeds
Location: United Kingdom of Great Britain and Northern Ireland
Related Funding Activities
No related grants have been discovered for Christopher Smith.