scholarly journals GIR v1.0.0: a generalised impulse-response model for climate uncertainty and future scenario exploration

2020 ◽  
Author(s):  
Nicholas James Leach ◽  
Zebedee Nicholls ◽  
Stuart Jenkins ◽  
Christopher J. Smith ◽  
John Lynch ◽  
...  
Keyword(s):  
Greenhouse Gas ◽  
Impulse Response ◽  
Radiative Forcing ◽  
Climate Models ◽  
Temperature Response ◽  
Structural Complexity ◽  
Common Denominator ◽  
Response Model ◽  
State Dependent ◽  
Effective Radiative Forcing

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.

scholarly journals FaIRv2.0.0: a generalized impulse response model for climate uncertainty and future scenario exploration

2021 ◽  
Vol 14 (5) ◽  
pp. 3007-3036
Author(s):  
Nicholas J. Leach ◽  
Stuart Jenkins ◽  
Zebedee Nicholls ◽  
Christopher J. Smith ◽  
John Lynch ◽  
...  
Keyword(s):  
Greenhouse Gas ◽  
Impulse Response ◽  
Climate Models ◽  
Global Climate ◽  
Climate System ◽  
System Response ◽  
Common Denominator ◽  
Response Model ◽  
Wide Range ◽  
Complex Models

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.

scholarly journals FaIRv2.0.0: a generalised impulse-response model for climate uncertainty and future scenario exploration

2020 ◽  
Author(s):  
Nicholas J. Leach ◽  
Stuart Jenkins ◽  
Zebedee Nicholls ◽  
Christopher J. Smith ◽  
John Lynch ◽  
...  
Keyword(s):  
Greenhouse Gas ◽  
Impulse Response ◽  
Climate Models ◽  
Climate System ◽  
System Response ◽  
Common Denominator ◽  
Response Model ◽  
Wide Range ◽  
Complex Models ◽  
Additional Equation

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.

scholarly journals HIRM v1.0: A hybrid impulse response model for climate modeling and uncertainty analyses

2020 ◽  
Author(s):  
Kalyn Dorheim ◽  
Steven Smith ◽  
Ben Bond-Lamberty
Keyword(s):  
Impulse Response ◽  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Computational Cost ◽  
Global Temperature ◽  
Impulse Response Functions ◽  
Response Model ◽  
Modeling Framework ◽  
Uncertainty Analyses

Abstract. Simple climate models (SCMs) are frequently used in research and decision-making communities because of their flexibility, tractability, and low computational cost. SCMs can be idealized, flexibly representing major climate dynamics as impulse response functions, or process-based, using explicit equations to model possibly nonlinear climate and earth system dynamics. Each of these approaches has strengths and limitations. Here we present and test a hybrid impulse response modeling framework (HIRM) that combines the strengths of process-based SCMs in an idealized impulse response model, with HIRM’s input derived from the output of a process-based model. This structure allows it to capture the crucial nonlinear dynamics frequently encountered in going from greenhouse gas emissions to atmospheric concentration to radiative forcing to climate change. As a test, the HIRM framework was configured to emulate total temperature of the simple climate model Hector 2.0 under the four Representative Concentration Pathways and the temperature response of an abrupt four times CO2 concentration step. HIRM was able to reproduce near-term and long-term Hector global temperature with a high degree of fidelity. Additionally, we conducted two case studies to demonstrate potential applications for this hybrid model: examining the effect of aerosol forcing uncertainty on global temperature, and incorporating more process-based representations of black carbon into a SCM. The open-source HIRM framework has a range of applications including complex climate model emulation, uncertainty analyses of radiative forcing, attribution studies, and climate model development.

scholarly journals HIRM v1.0: a hybrid impulse response model for climate modeling and uncertainty analyses

2021 ◽  
Vol 14 (1) ◽  
pp. 365-375
Author(s):  
Kalyn Dorheim ◽  
Steven J. Smith ◽  
Ben Bond-Lamberty
Keyword(s):  
Impulse Response ◽  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Computational Cost ◽  
Global Temperature ◽  
Impulse Response Functions ◽  
Response Model ◽  
Modeling Framework ◽  
Uncertainty Analyses

Abstract. Simple climate models (SCMs) are frequently used in research and decision-making communities because of their flexibility, tractability, and low computational cost. SCMs can be idealized, flexibly representing major climate dynamics as impulse response functions, or process-based, using explicit equations to model possibly nonlinear climate and Earth system dynamics. Each of these approaches has strengths and limitations. Here we present and test a hybrid impulse response modeling framework (HIRM) that combines the strengths of process-based SCMs in an idealized impulse response model, with HIRM's input derived from the output of a process-based model. This structure enables the model to capture some of the major nonlinear dynamics that occur in complex climate models as greenhouse gas emissions transform to atmospheric concentration to radiative forcing to climate change. As a test, the HIRM framework was configured to emulate the total temperature of the simple climate model Hector 2.0 under the four Representative Concentration Pathways and the temperature response of an abrupt 4 times CO2 concentration step. HIRM was able to reproduce near-term and long-term Hector global temperature with a high degree of fidelity. Additionally, we conducted two case studies to demonstrate potential applications for this hybrid model: examining the effect of aerosol forcing uncertainty on global temperature and incorporating more process-based representations of black carbon into a SCM. The open-source HIRM framework has a range of applications including complex climate model emulation, uncertainty analyses of radiative forcing, attribution studies, and climate model development.

scholarly journals Changes in the width of the tropical belt due to simple radiative forcing changes in the GeoMIP simulations

2016 ◽  
Vol 16 (15) ◽  
pp. 10083-10095 ◽  
Author(s):  
Nicholas A. Davis ◽  
Dian J. Seidel ◽  
Thomas Birner ◽  
Sean M. Davis ◽  
Simone Tilmes
Keyword(s):  
Carbon Dioxide ◽  
Radiative Forcing ◽  
General Circulation ◽  
Climate Models ◽  
Temperature Response ◽  
Austral Summer ◽  
Hadley Cell ◽  
Solar Constant ◽  
Cell Width ◽  
Climate Forcings

Abstract. Model simulations of future climates predict a poleward expansion of subtropical arid climates at the edges of Earth's tropical belt, which would have significant environmental and societal impacts. This expansion may be related to the poleward shift of the Hadley cell edges, where subsidence stabilizes the atmosphere and suppresses precipitation. Understanding the primary drivers of tropical expansion is hampered by the myriad forcing agents in most model projections of future climate. While many previous studies have examined the response of idealized models to simplified climate forcings and the response of comprehensive climate models to more complex climate forcings, few have examined how comprehensive climate models respond to simplified climate forcings. To shed light on robust processes associated with tropical expansion, here we examine how the tropical belt width, as measured by the Hadley cell edges, responds to simplified forcings in the Geoengineering Model Intercomparison Project (GeoMIP). The tropical belt expands in response to a quadrupling of atmospheric carbon dioxide concentrations and contracts in response to a reduction in the solar constant, with a range of a factor of 3 in the response among nine models. Models with more surface warming and an overall stronger temperature response to quadrupled carbon dioxide exhibit greater tropical expansion, a robust result in spite of inter-model differences in the mean Hadley cell width, parameterizations, and numerical schemes. Under a scenario where the solar constant is reduced to offset an instantaneous quadrupling of carbon dioxide, the Hadley cells remain at their preindustrial width, despite the residual stratospheric cooling associated with elevated carbon dioxide levels. Quadrupled carbon dioxide produces greater tropical belt expansion in the Southern Hemisphere than in the Northern Hemisphere. This expansion is strongest in austral summer and autumn. Ozone depletion has been argued to cause this pattern of changes in observations and model experiments, but the results here indicate that seasonally and hemispherically asymmetric tropical expansion can be a basic response of the general circulation to climate forcings.

scholarly journals Observational Constraint on Greenhouse Gas and Aerosol Contributions to Global Ocean Heat Content Changes

2020 ◽  
Vol 33 (24) ◽  
pp. 10579-10591
Author(s):  
Elodie Charles ◽  
Benoit Meyssignac ◽  
Aurélien Ribes
Keyword(s):  
Greenhouse Gas ◽  
Radiative Forcing ◽  
Climate Models ◽  
Ghg Emissions ◽  
Heat Content ◽  
Ocean Heat Content ◽  
Global Ocean ◽  
Detection And Attribution ◽  
Aerosol Forcing ◽  
Bivariate Method

AbstractObservations and climate models are combined to identify an anthropogenic warming signature in the upper ocean heat content (OHC) changes since 1971. We apply a new detection and attribution analysis developed by Ribes et al. that uses a symmetric treatment of the magnitude and the pattern of the climate response to each radiative forcing. A first estimate of the OHC response to natural, anthropogenic, greenhouse gas, and other forcings is derived from a large ensemble of CMIP5 simulations. Observational datasets from historical reconstructions are then used to constrain this estimate. A spatiotemporal observational mask is applied to compare simulations with actual observations and to overcome reconstruction biases. Results on the 0–700-m layer from 1971 to 2005 show that the global OHC would have increased since 1971 by 2.12 ± 0.21 × 107 J m−2 yr−1 in response to GHG emissions alone. But this has been compensated for by other anthropogenic influences (mainly aerosol), which induced an OHC decrease of 0.84 ± 0.18 × 107 J m−2 yr−1. The natural forcing has induced a slight global OHC decrease since 1971 of 0.13 ± 0.09 × 107 J m−2 yr−1. Compared to previous studies we have separated the effect of the GHG forcing from the effect of the other anthropogenic forcing on OHC changes. This has been possible by using a new detection and attribution (D&A) method and by analyzing simultaneously the global OHC trends over 1957–80 and over 1971–2005. This bivariate method takes advantage of the different time variation of the GHG forcing and the aerosol forcing since 1957 to separate both effects and reduce the uncertainty in their estimates.

scholarly journals Effective radiative forcing and adjustments in CMIP6 models

2020 ◽  
Vol 20 (16) ◽  
pp. 9591-9618 ◽  
Author(s):  
Christopher J. Smith ◽  
Ryan J. Kramer ◽  
Gunnar Myhre ◽  
Kari Alterskjær ◽  
William Collins ◽  
...  
Keyword(s):  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Climate Models ◽  
Coupled Model ◽  
Internal Variability ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Aerosol Forcing ◽  
Intercomparison Project ◽  
Effective Radiative Forcing

Abstract. The effective radiative forcing, which includes the instantaneous forcing plus adjustments from the atmosphere and surface, has emerged as the key metric of evaluating human and natural influence on the climate. We evaluate effective radiative forcing and adjustments in 17 contemporary climate models that are participating in the Coupled Model Intercomparison Project (CMIP6) and have contributed to the Radiative Forcing Model Intercomparison Project (RFMIP). Present-day (2014) global-mean anthropogenic forcing relative to pre-industrial (1850) levels from climate models stands at 2.00 (±0.23) W m−2, comprised of 1.81 (±0.09) W m−2 from CO2, 1.08 (± 0.21) W m−2 from other well-mixed greenhouse gases, −1.01 (± 0.23) W m−2 from aerosols and −0.09 (±0.13) W m−2 from land use change. Quoted uncertainties are 1 standard deviation across model best estimates, and 90 % confidence in the reported forcings, due to internal variability, is typically within 0.1 W m−2. The majority of the remaining 0.21 W m−2 is likely to be from ozone. In most cases, the largest contributors to the spread in effective radiative forcing (ERF) is from the instantaneous radiative forcing (IRF) and from cloud responses, particularly aerosol–cloud interactions to aerosol forcing. As determined in previous studies, cancellation of tropospheric and surface adjustments means that the stratospherically adjusted radiative forcing is approximately equal to ERF for greenhouse gas forcing but not for aerosols, and consequentially, not for the anthropogenic total. The spread of aerosol forcing ranges from −0.63 to −1.37 W m−2, exhibiting a less negative mean and narrower range compared to 10 CMIP5 models. The spread in 4×CO2 forcing has also narrowed in CMIP6 compared to 13 CMIP5 models. Aerosol forcing is uncorrelated with climate sensitivity. Therefore, there is no evidence to suggest that the increasing spread in climate sensitivity in CMIP6 models, particularly related to high-sensitivity models, is a consequence of a stronger negative present-day aerosol forcing and little evidence that modelling groups are systematically tuning climate sensitivity or aerosol forcing to recreate observed historical warming.

scholarly journals Anthropogenic aerosol forcing – insights from multiple estimates from aerosol-climate models with reduced complexity

2019 ◽  
Vol 19 (10) ◽  
pp. 6821-6841 ◽  
Author(s):  
Stephanie Fiedler ◽  
Stefan Kinne ◽  
Wan Ting Katty Huang ◽  
Petri Räisänen ◽  
Declan O'Donnell ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Coupled Model ◽  
Cloud Droplet ◽  
Internal Variability ◽  
Anthropogenic Aerosol ◽  
Aerosol Forcing ◽  
Effective Radiative Forcing ◽  
Absolute Magnitudes ◽  
Natural Aerosols

Abstract. This study assesses the change in anthropogenic aerosol forcing from the mid-1970s to the mid-2000s. Both decades had similar global-mean anthropogenic aerosol optical depths but substantially different global distributions. For both years, we quantify (i) the forcing spread due to model-internal variability and (ii) the forcing spread among models. Our assessment is based on new ensembles of atmosphere-only simulations with five state-of-the-art Earth system models. Four of these models will be used in the sixth Coupled Model Intercomparison Project (CMIP6; Eyring et al., 2016). Here, the complexity of the anthropogenic aerosol has been reduced in the participating models. In all our simulations, we prescribe the same patterns of the anthropogenic aerosol optical properties and associated effects on the cloud droplet number concentration. We calculate the instantaneous radiative forcing (RF) and the effective radiative forcing (ERF). Their difference defines the net contribution from rapid adjustments. Our simulations show a model spread in ERF from −0.4 to −0.9 W m−2. The standard deviation in annual ERF is 0.3 W m−2, based on 180 individual estimates from each participating model. This result implies that identifying the model spread in ERF due to systematic differences requires averaging over a sufficiently large number of years. Moreover, we find almost identical ERFs for the mid-1970s and mid-2000s for individual models, although there are major model differences in natural aerosols and clouds. The model-ensemble mean ERF is −0.54 W m−2 for the pre-industrial era to the mid-1970s and −0.59 W m−2 for the pre-industrial era to the mid-2000s. Our result suggests that comparing ERF changes between two observable periods rather than absolute magnitudes relative to a poorly constrained pre-industrial state might provide a better test for a model's ability to represent transient climate changes.

Last Glacial to present-day variability of surface climate from oxygen isotope signatures in speleothems and model simulations

2021 ◽  
Author(s):  
Janica Buehler ◽  
Nils Weitzel ◽  
Jean-Philippe Baudouin ◽  
Martin Werner ◽  
Kira Rehfeld
Keyword(s):  
Climate Variability ◽  
Oxygen Isotope ◽  
Radiative Forcing ◽  
Late Holocene ◽  
Climate Models ◽  
Science Data ◽  
Past Climate ◽  
Last Glacial ◽  
State Dependent ◽  
Instrumental Period

<p>Comparing simulations and data from paleoclimate archives such as speleothems can test the capability of climate models to capture past climate changes. In past, present, and future, the hydrologic response to radiative forcing changes is far less understood and more uncertain than thermal changes.<br> <br>Speleothems store terrestrial climate information in the form of isotopic oxygen in mineral and are found mostly in the low-to mid-latitudes of the landmasses. Their usually well preserved (semi-)continuous time series of oxygen isotope ratio δ<sup>18</sup>O can cover full Glacial-Interglacial cycles and are used for past climate reconstructions. However, the measured δ<sup>18</sup>O in the mineral is influenced by multiple climate and cave-related variables and does, therefore, not directly represent past temperature or precipitation. </p><p>We assess the capability of the isotope-enabled models HadCM3 and ECHAM5-MPI/OM to simulate decadal to centennial climate variability beyond the instrumental period. In particular, we investigate the relationship between simulated δ<sup>18</sup>O and precipitation variability under different background conditions. By comparing simulated δ<sup>18</sup>O values at cave locations to the large global speleothem database SISALv2 (Comas-Bru et al. 2020), we also examine the consistency between modeled and archived temporal changes in δ<sup>18</sup>O in the mean state and variability. Our strategy involves forward-modeling of cave processes such as temperature-dependent fractionation and transit times to constrain a simple speleothem proxy model for the simulation output. For the late Holocene, we observe a strongly underestimated simulated isotopic variability on decadal to centennial timescales. We further test how much this underestimation depends on the background radiative forcing conditions by comparing the Last Glacial Maximum, the mid-Holocene, and the late Holocene. This provides deeper insight on low to mid-latitude state-dependent climate variability on decadal to centennial time scales. </p><p>Reference:</p><p>Comas-Bru, L., et. al. SISALv2: a comprehensive speleothem isotope database with multiple age-depth models. Earth System Science Data 12, 2579-2606 (2020) https://essd.copernicus.org/articles/12/2579/2020/</p>

Warmer climate projections in CMIP6: the role of changes in the greenhouse gas concentrations from CMIP5 to CMIP6

2020 ◽  
Author(s):  
Klaus Wyser ◽  
Erik Kjellström ◽  
Torben Koenigk ◽  
Helena Martins ◽  
Ralf Döscher
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Climate Impact ◽  
Earth Model ◽  
Minor Role ◽  
Climate Projections ◽  
First Results ◽  
Effective Radiative Forcing ◽  
A Minor ◽  
New Generation

<p>Many modelling groups have contributed with CMIP6 scenario experiments to the CMIP6 archive. The analysis of CMIP6 future projections has started and first results indicate that CMIP6 projections are warmer than their counterparts from CMIP5. To some extent this is explained with the higher climate sensitivity of many of the new generation of climate models. However, not only have models been updated since CMIP5 but also the forcings have changed from RCPs to SSPs. The new SSPs have been designed to have the same instantaneous radiative forcing at the end of the 21st century. However, we find that in the EC-Earth3 model the effective radiative forcing differs substantially when the GHG concentrations from the SSP are replaced by those from the corresponding RCP with the same nameplate RF. We estimate that for the SSP5-8.5 and SSP2-4.5 scenarios 50% or more of the stronger warming in CMIP6 than CMIP5 for the EC-Earth model can be explained by changes in GHG gas concentrations. Other changes in the forcing datasets such as aerosols only play a minor role for the additional warming. The discrepancy between RCP and SSP forcing datasets needs to be accounted for when comparing CMIP5 and CMIP6 climate projections and should be properly conveyed to the climate impact, adaptation and mitigation communities.</p>

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