Description and basic evaluation of simulated mean state, internal variability, and climate sensitivity in MIROC6

Abstract. The sixth version of the Model for Interdisciplinary Research on Climate (MIROC), called MIROC6, was cooperatively developed by a Japanese modeling community. In the present manuscript, simulated mean climate, internal climate variability, and climate sensitivity in MIROC6 are evaluated and briefly summarized in comparison with the previous version of our climate model (MIROC5) and observations. The results show that overall reproducibility of mean climate and internal climate variability in MIROC6 is better than that in MIROC5. The tropical climate systems (e.g., summertime precipitation in the western Pacific and the eastward propagating Madden-Julian Oscillation) and the mid-latitude atmospheric circulations (e.g., the westerlies, the polar night jet, and troposphere-stratosphere interactions) are significantly improved in MIROC6. These improvements can be attributed to the newly implemented parameterization for shallow convective processes and to the directly resolved stratosphere. While there are significant differences in climates and variabilities between the two models, the effective climate sensitivity of 2.5 K remains the same because the differences in radiative forcing and climate feedback tend to offset each other. With an aim towards contributing to the sixth phase of the Coupled Model Intercomparison Project, designated simulations tackling a wide range of climate science issues, as well as seasonal-to-decadal climate predictions and future climate projections, are currently ongoing using MIROC6.

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Description and basic evaluation of simulated mean state, internal variability, and climate sensitivity in MIROC6

Geoscientific Model Development ◽

10.5194/gmd-12-2727-2019 ◽

2019 ◽

Vol 12 (7) ◽

pp. 2727-2765 ◽

Cited By ~ 58

Author(s):

Hiroaki Tatebe ◽

Tomoo Ogura ◽

Tomoko Nitta ◽

Yoshiki Komuro ◽

Koji Ogochi ◽

...

Keyword(s):

Climate Variability ◽

Climate Sensitivity ◽

Radiative Forcing ◽

Climate Model ◽

Coupled Model ◽

Climate Feedback ◽

Climate Projections ◽

Internal Climate Variability ◽

Wide Range ◽

Mean Climate

Abstract. The sixth version of the Model for Interdisciplinary Research on Climate (MIROC), called MIROC6, was cooperatively developed by a Japanese modeling community. In the present paper, simulated mean climate, internal climate variability, and climate sensitivity in MIROC6 are evaluated and briefly summarized in comparison with the previous version of our climate model (MIROC5) and observations. The results show that the overall reproducibility of mean climate and internal climate variability in MIROC6 is better than that in MIROC5. The tropical climate systems (e.g., summertime precipitation in the western Pacific and the eastward-propagating Madden–Julian oscillation) and the midlatitude atmospheric circulation (e.g., the westerlies, the polar night jet, and troposphere–stratosphere interactions) are significantly improved in MIROC6. These improvements can be attributed to the newly implemented parameterization for shallow convective processes and to the inclusion of the stratosphere. While there are significant differences in climates and variabilities between the two models, the effective climate sensitivity of 2.6 K remains the same because the differences in radiative forcing and climate feedback tend to offset each other. With an aim towards contributing to the sixth phase of the Coupled Model Intercomparison Project, designated simulations tackling a wide range of climate science issues, as well as seasonal to decadal climate predictions and future climate projections, are currently ongoing using MIROC6.

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Incorrect Asian aerosols affecting the attribution and projection of regional climate change in CMIP6 models

npj Climate and Atmospheric Science ◽

10.1038/s41612-020-00159-2 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Zhili Wang ◽

Lei Lin ◽

Yangyang Xu ◽

Huizheng Che ◽

Xiaoye Zhang ◽

...

Keyword(s):

Climate Change ◽

Radiative Forcing ◽

Impact Analysis ◽

Climate Model ◽

Regional Climate ◽

Eastern China ◽

Coupled Model ◽

Regional Climate Change ◽

Anthropogenic Aerosol ◽

Wide Range

AbstractAnthropogenic aerosol (AA) forcing has been shown as a critical driver of climate change over Asia since the mid-20th century. Here we show that almost all Coupled Model Intercomparison Project Phase 6 (CMIP6) models fail to capture the observed dipole pattern of aerosol optical depth (AOD) trends over Asia during 2006–2014, last decade of CMIP6 historical simulation, due to an opposite trend over eastern China compared with observations. The incorrect AOD trend over China is attributed to problematic AA emissions adopted by CMIP6. There are obvious differences in simulated regional aerosol radiative forcing and temperature responses over Asia when using two different emissions inventories (one adopted by CMIP6; the other from Peking university, a more trustworthy inventory) to driving a global aerosol-climate model separately. We further show that some widely adopted CMIP6 pathways (after 2015) also significantly underestimate the more recent decline in AA emissions over China. These flaws may bring about errors to the CMIP6-based regional climate attribution over Asia for the last two decades and projection for the next few decades, previously anticipated to inform a wide range of impact analysis.

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Setup of the PMIP3 paleoclimate experiments conducted using an Earth System Model, MIROC-ESM

Geoscientific Model Development Discussions ◽

10.5194/gmdd-5-2527-2012 ◽

2012 ◽

Vol 5 (3) ◽

pp. 2527-2569 ◽

Cited By ~ 1

Author(s):

T. Sueyoshi ◽

R. Ohgaito ◽

A. Yamamoto ◽

M. O. Chikamoto ◽

T. Hajima ◽

...

Keyword(s):

Climate Model ◽

Coupled Model ◽

Earth System Model ◽

Future Climate ◽

System Model ◽

Climate Feedback ◽

Climate Projections ◽

Earth System ◽

Intergovernmental Panel ◽

Intercomparison Project

Abstract. The importance of climate model evaluation using paleoclimate simulations for better future climate projections has been recognized by the Intergovernmental Panel on Climate Change. In recent years, Earth System Models (ESMs) were developed to investigate carbon-cycle climate feedback, as well as to project the future climate. Paleoclimate events, especially those associated with the variations in atmospheric CO2 level or land vegetation, provide suitable benchmarks to evaluate ESMs. Here we present implementations of the paleoclimate experiments proposed by the Coupled Model Intercomparison Project phase 5/Paleoclimate Modelling Intercomparison Project phase 3 (CMIP5/PMIP3) using an Earth System Model, MIROC-ESM. In this paper, experimental settings and procedures of the mid-Holocene, the Last Glacial Maximum, and the Last Millennium experiments are explained. The first two experiments are time slice experiments and the last one is a transient experiment. The complexity of the model requires various steps to correctly configure the experiments. Several basic outputs are also shown.

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Incorrect Asian aerosols affecting the attribution and projection of regional climate change in CMIP6 models

10.5194/egusphere-egu21-8421 ◽

2021 ◽

Author(s):

Lei Lin ◽

Zhili Wang ◽

Yangyang Xu ◽

Huizheng Che ◽

Xiaoye Zhang ◽

...

Keyword(s):

Climate Change ◽

Radiative Forcing ◽

Impact Analysis ◽

Climate Model ◽

Regional Climate ◽

Eastern China ◽

Coupled Model ◽

Regional Climate Change ◽

Anthropogenic Aerosol ◽

Wide Range

Anthropogenic aerosol (AA) forcing has been shown as a critical driver of climate change over Asia since the mid-20th century. Here we show that almost all Coupled Model Intercomparison Project Phase 6 (CMIP6) models fail to capture the observed dipole pattern of aerosol optical depth (AOD) trends over Asia during 2006&#8211;2014, last decade of CMIP6 historical simulation, due to an opposite trend over eastern China compared with observations. The incorrect AOD trend over China is attributed to problematic AA emissions adopted by CMIP6. There are obvious differences in simulated regional aerosol radiative forcing and temperature responses over Asia when using two different emissions inventories (one adopted by CMIP6; the other from Peking university, a more trustworthy inventory) to driving a global aerosol-climate model separately. We further show that some widely adopted CMIP6 pathways (after 2015) also significantly underestimate the more recent decline in AA emissions over China. These flaws may bring about errors to the CMIP6-based regional climate attribution over Asia for the last two decades and projection for the next few decades, previously anticipated to inform a wide range of impact analysis.

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Changing the Climate Sensitivity of an Atmospheric General Circulation Model through Cloud Radiative Adjustment

Journal of Climate ◽

10.1175/jcli-d-11-00590.1 ◽

2012 ◽

Vol 25 (19) ◽

pp. 6567-6584 ◽

Cited By ~ 15

Author(s):

Andrei P. Sokolov ◽

Erwan Monier

Keyword(s):

Climate Change ◽

Climate Sensitivity ◽

General Circulation ◽

Climate Model ◽

Circulation Model ◽

Climate Projections ◽

Regional Patterns ◽

Adjustment Method ◽

Wide Range ◽

Perturbed Physics

Abstract Conducting probabilistic climate projections with a particular climate model requires the ability to vary the model’s characteristics, such as its climate sensitivity. In this study, the authors implement and validate a method to change the climate sensitivity of the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, version 3 (CAM3), through cloud radiative adjustment. Results show that the cloud radiative adjustment method does not lead to physically unrealistic changes in the model’s response to an external forcing, such as doubling CO2 concentrations or increasing sulfate aerosol concentrations. Furthermore, this method has some advantages compared to the traditional perturbed physics approach. In particular, the cloud radiative adjustment method can produce any value of climate sensitivity within the wide range of uncertainty based on the observed twentieth century climate change. As a consequence, this method allows Monte Carlo–type probabilistic climate forecasts to be conducted where values of uncertain parameters not only cover the whole uncertainty range, but cover it homogeneously. Unlike the perturbed physics approach that can produce several versions of a model with the same climate sensitivity but with very different regional patterns of change, the cloud radiative adjustment method can only produce one version of the model with a specific climate sensitivity. As such, a limitation of this method is that it cannot cover the full uncertainty in regional patterns of climate change.

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Aerosol lifetime and climate change

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-12-16493-2012 ◽

2012 ◽

Vol 12 (7) ◽

pp. 16493-16514 ◽

Cited By ~ 3

Author(s):

G.-J. Roelofs

Keyword(s):

Climate Change ◽

Water Vapor ◽

Climate Sensitivity ◽

Radiative Forcing ◽

Climate Models ◽

Climate Model ◽

Hydrological Cycle ◽

Lapse Rate ◽

Fundamental Relation ◽

Wide Range

Abstract. The dominant removal mechanism for atmospheric aerosol is activation of particles to cloud droplets and subsequent wet deposition in precipitation. The atmospheric lifetime of aerosol is thus closely coupled to the atmospheric cycling time of water vapor. Changes of hydrological cycle characteristics resulting from climate change therefore directly affect aerosol lifetime, and thus the radiative forcing exerted by aerosol. This study expresses the coupling between water vapor and aerosol lifetimes and their temperature sensitivities in fundamental equations and in terms of the efficiency of processing of air by precipitating clouds. Based on climate model simulations these temperature sensitivities are estimated to be on the order of +5.3% K−1, but this may be an overestimation. Generally, shifting spatial and temporal patterns of aerosol (precursor) emissions and precipitation, and changes in aerosol activation efficiency probably influence aerosol lifetimes more than climate change itself, resulting in a wide range of simulated aerosol lifetime sensitivities between aerosol-climate models. It is possible that the climate sensitivity of models plays a role. It can be argued that climate sensitivity is intrinsically coupled with the simulated (temperature sensitivity of the) aerosol lifetime through the distribution of water vapor and aerosol between the lower and upper troposphere. This implies a fundamental relation between various feedback forcings (water vapor, lapse rate, cloud) and the aerosol forcing, illustrating the key role of the hydrological cycle in different aspects of the climate system.

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Estimating the Contribution of Sea Ice Response to Climate Sensitivity in a Climate Model

Journal of Climate ◽

10.1175/jcli-d-14-00042.1 ◽

2014 ◽

Vol 27 (22) ◽

pp. 8597-8607 ◽

Cited By ~ 10

Author(s):

Ken Caldeira ◽

Ivana Cvijanovic

Keyword(s):

Climate Change ◽

Sea Ice ◽

Climate Sensitivity ◽

Radiative Forcing ◽

Climate Model ◽

Ocean Model ◽

Radiative Properties ◽

Climate Feedback ◽

Climate Effect ◽

Feedback Parameter

Abstract The response of sea ice to climate change affects Earth’s radiative properties in ways that contribute to yet more climate change. Here, a configuration of the Community Earth System Model, version 1.0.4 (CESM 1.0.4), with a slab ocean model and a thermodynamic–dynamic sea ice model is used to investigate the overall contribution to climate sensitivity of feedbacks associated with the sea ice loss. In simulations in which sea ice is not present and ocean temperatures are allowed to fall below freezing, the climate feedback parameter averages ~1.31 W m−2 K−1; the value obtained for control simulations with active sea ice is ~1.05 W m−2 K−1, indicating that, in this configuration of CESM1.0.4, sea ice response accounts for ~20% of climate sensitivity to an imposed change in radiative forcing. In this model, the effect of sea ice response on the longwave climate feedback parameter is nearly half as important as its effect on the shortwave climate feedback parameter. Further, it is shown that the strength of the overall sea ice feedback can be related to 1) the sensitivity of sea ice area to changes in temperature and 2) the sensitivity of sea ice radiative forcing to changes in sea ice area. An alternative method of disabling sea ice response leads to similar conclusions. It is estimated that the presence of sea ice in the preindustrial control simulation has a climate effect equivalent to ~3 W m−2 of radiative forcing.

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The Structure of Millennial Scale Glacial Climate Variability

10.5194/egusphere-egu21-4264 ◽

2021 ◽

Author(s):

Guido Vettoretti ◽

Peter Ditlevsen ◽

Markus Jochum ◽

Sune Rasmussen

Keyword(s):

Climate Variability ◽

Radiative Forcing ◽

Climate Model ◽

Ice Cores ◽

Internal Climate Variability ◽

Isotopic Analyses ◽

Different Levels ◽

Glacial Climate ◽

Intrinsic Characteristic ◽

Millennial Scale

The Dansgaard-Oeschger (D-O) oscillation recorded in isotopic analyses of Greenland ice cores is a climate oscillation with millennial scale variability alternating between cold stadial climate and warm interstadial climate states. Using a series of long comprehensive climate model integrations of the glacial climate system under different levels of radiative forcing, we formulate a simple heuristic model to emulate the D-O oscillation. We demonstrate that the D-O oscillation has properties that are consistent with an internal unforced oscillation as well as displaying interesting behaviour that is consistent with noise induced transitions. Therefore, the D-O oscillation is more aptly characterized as a stochastic oscillator with stadial and interstadial durations that are more dependent upon a control parameter and internal climate variability rather than an intrinsic characteristic timescale.

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Large ensemble assessment of how the global surface warming response to cumulative carbon differs for negative and positive carbon emissions

10.5194/egusphere-egu21-12718 ◽

2021 ◽

Author(s):

Negar Vakilifard ◽

Katherine Turner ◽

Ric Williams ◽

Philip Holden ◽

Neil Edwards ◽

...

Keyword(s):

Carbon Emissions ◽

Radiative Forcing ◽

Climate Model ◽

Climate Feedback ◽

Climate Response ◽

Ocean Heat Uptake ◽

Transient Climate Response ◽

Surface Warming ◽

Radiative Processes ◽

Negative Emission

The controls of the effective transient climate response (TCRE), defined in terms of the dependence of surface warming since the pre-industrial to the cumulative carbon emission, is explained in terms of climate model experiments for a scenario including positive emissions and then negative emission over a period of 400 years. We employ a pre-calibrated ensemble of GENIE, grid-enabled integrated Earth system model, consisting of 86 members to determine the process of controlling TCRE in both CO2 emissions and drawdown phases. Our results are based on the GENIE simulations with historical forcing from AD 850 including land use change, and the future forcing defined by CO2 emissions and a non-CO2 radiative forcing timeseries. We present the results for the point-source carbon capture and storage (CCS) scenario as a negative emission scenario, following the medium representative concentration pathway (RCP4.5), assuming that the rate of emission drawdown is 2 PgC/yr CO2 for the duration of 100 years. The climate response differs between the periods of positive and negative carbon emissions with a greater ensemble spread during the negative carbon emissions. The controls of the spread in ensemble responses are explained in terms of a combination of thermal processes (involving ocean heat uptake and physical climate feedback), radiative processes (saturation in radiative forcing from CO2 and non-CO2 contributions) and carbon dependences (involving terrestrial and ocean carbon uptake).&#160;&#160;

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Bayesian estimation of Earth's climate sensitivity and transient climate response from observational warming and heat content datasets

Earth System Dynamics ◽

10.5194/esd-12-709-2021 ◽

2021 ◽

Vol 12 (2) ◽

pp. 709-723

Author(s):

Philip Goodwin ◽

B. B. Cael

Keyword(s):

Climate Sensitivity ◽

Future Climate ◽

Climate Feedback ◽

Future Climate Change ◽

Climate Projections ◽

Climate Response ◽

Ocean Heat Uptake ◽

Transient Climate Response ◽

Posterior Probability Distribution ◽

The Impact

Abstract. Future climate change projections, impacts, and mitigation targets are directly affected by how sensitive Earth's global mean surface temperature is to anthropogenic forcing, expressed via the climate sensitivity (S) and transient climate response (TCR). However, the S and TCR are poorly constrained, in part because historic observations and future climate projections consider the climate system under different response timescales with potentially different climate feedback strengths. Here, we evaluate S and TCR by using historic observations of surface warming, available since the mid-19th century, and ocean heat uptake, available since the mid-20th century, to constrain a model with independent climate feedback components acting over multiple response timescales. Adopting a Bayesian approach, our prior uses a constrained distribution for the instantaneous Planck feedback combined with wide-ranging uniform distributions of the strengths of the fast feedbacks (acting over several days) and multi-decadal feedbacks. We extract posterior distributions by applying likelihood functions derived from different combinations of observational datasets. The resulting TCR distributions when using two preferred combinations of historic datasets both find a TCR of 1.5 (1.3 to 1.8 at 5–95 % range) ∘C. We find the posterior probability distribution for S for our preferred dataset combination evolves from S of 2.0 (1.6 to 2.5) ∘C on a 20-year response timescale to S of 2.3 (1.4 to 6.4) ∘C on a 140-year response timescale, due to the impact of multi-decadal feedbacks. Our results demonstrate how multi-decadal feedbacks allow a significantly higher upper bound on S than historic observations are otherwise consistent with.

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