scholarly journals An energy budget framework to understand mechanisms of land–ocean warming contrast induced by increasing greenhouse gases Part I: Near-equilibrium state

2021 ◽  
pp. 1-63
Author(s):  
Masaki Toda ◽  
Masahiro Watanabe ◽  
Masakazu Yoshimori
Keyword(s):  
Heat Capacity ◽  
Equilibrium State ◽  
Radiative Forcing ◽  
Energy Transport ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Ocean Warming ◽  
Climate Feedback ◽  
Energy Budgets ◽  
Effective Radiative Forcing

AbstractModeling studies have shown that surface air temperature (SAT) increase in response to an increase in the atmospheric CO2 concentration is larger over land than over ocean. This so-called land–ocean warming contrast, φ, defined as the land–mean SAT change divided by the ocean-mean SAT change, is a striking feature of global warming. Small heat capacity over land is unlikely the sole cause because the land-ocean warming contrast is found in the equilibrium state of CO2 doubling experiments.Several different mechanisms have been proposed to explain the land–ocean warming contrast, but the comprehensive understanding has not yet been obtained. In Part I of this study, we propose a framework to diagnose φ based on energy budgets at the top of atmosphere and for the atmosphere, which enables the decomposition of contributions from effective radiative forcing (ERF), climate feedback, heat capacity, and atmospheric energy transport anomaly to φ. Using this framework, we analyzed the SAT response to an abrupt CO2 quadrupling using 15 Coupled Model Intercomparison Project Phase 6 (CMIP6) Earth system models. In the near-equilibrium state (years 121-150), φ is 1.49 ± 0.11, which is primarily induced by the land–ocean difference in ERF and heat capacity. We found that contributions from ERF, feedback, and energy transport anomaly tend to cancel each other, leading to a small inter-model spread of φ compared to the large spread of individual components. In the equilibrium state without heat capacity contribution, ERF and energy transport anomaly are the major contributors to φ, which shows a weak negative correlation with the equilibrium climate sensitivity.

scholarly journals The inconstancy of the transient climate response parameter under increasing CO 2

2015 ◽  
Vol 373 (2054) ◽  
pp. 20140417 ◽  
Author(s):  
J. M. Gregory ◽  
T. Andrews ◽  
P. Good
Keyword(s):  
Radiative Forcing ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Deep Ocean ◽  
Climate Feedback ◽  
Climate Response ◽  
Ocean Heat Uptake ◽  
Transient Climate Response ◽  
Feedback Parameter ◽  
Response Parameter

In the Coupled Model Intercomparison Project Phase 5 (CMIP5), the model-mean increase in global mean surface air temperature T under the 1pctCO2 scenario (atmospheric CO 2 increasing at 1% yr −1 ) during the second doubling of CO 2 is 40% larger than the transient climate response (TCR), i.e. the increase in T during the first doubling. We identify four possible contributory effects. First, the surface climate system loses heat less readily into the ocean beneath as the latter warms. The model spread in the thermal coupling between the upper and deep ocean largely explains the model spread in ocean heat uptake efficiency. Second, CO 2 radiative forcing may rise more rapidly than logarithmically with CO 2 concentration. Third, the climate feedback parameter may decline as the CO 2 concentration rises. With CMIP5 data, we cannot distinguish the second and third possibilities. Fourth, the climate feedback parameter declines as time passes or T rises; in 1pctCO2, this effect is less important than the others. We find that T projected for the end of the twenty-first century correlates more highly with T at the time of quadrupled CO 2 in 1pctCO2 than with the TCR, and we suggest that the TCR may be underestimated from observed climate change.

Tropospheric Adjustment Induces a Cloud Component in CO2 Forcing

2008 ◽  
Vol 21 (1) ◽  
pp. 58-71 ◽  
Author(s):  
Jonathan Gregory ◽  
Mark Webb
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Surface Air Temperature ◽  
Co2 Concentration ◽  
Climate Feedback ◽  
Climate Projections ◽  
Feedback Parameter ◽  
Tropospheric Adjustment ◽  
Effective Radiative Forcing ◽  
Global Mean

Abstract The radiative forcing of CO2 and the climate feedback parameter are evaluated in several climate models with slab oceans by regressing the annual-mean global-mean top-of-atmosphere radiative flux against the annual-mean global-mean surface air temperature change ΔT following a doubling of atmospheric CO2 concentration. The method indicates that in many models there is a significant rapid tropospheric adjustment to CO2 leading to changes in cloud, and reducing the effective radiative forcing, in a way analogous to the indirect and semidirect effects of aerosol. By contrast, in most models the cloud feedback is small, defined as the part of the change that evolves with ΔT. Comparison with forcing evaluated by fixing sea surface conditions gives qualitatively similar results for the cloud components of forcing, both globally and locally. Tropospheric adjustment to CO2 may be responsible for some of the model spread in equilibrium climate sensitivity and could affect time-dependent climate projections.

scholarly journals Effects of Ocean Slow Response under Low Warming Targets

2020 ◽  
Vol 33 (2) ◽  
pp. 477-496 ◽  
Author(s):  
Shang-Min Long ◽  
Shang-Ping Xie ◽  
Yan Du ◽  
Qinyu Liu ◽  
Xiao-Tong Zheng ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Coupled Model ◽  
Deep Ocean ◽  
Ocean Warming ◽  
Meridional Overturning Circulation ◽  
Slow Response ◽  
Intercomparison Project ◽  
Meridional Overturning ◽  
Near Future

AbstractThe 2015 Paris Agreement proposed targets to limit global-mean surface temperature (GMST) rise well below 2°C relative to preindustrial level by 2100, requiring a cease in the radiative forcing (RF) increase in the near future. In response to changing RF, the deep ocean responds slowly (ocean slow response), in contrast to the fast ocean mixed layer adjustment. The role of the ocean slow response under low warming targets is investigated using representative concentration pathway (RCP) 2.6 simulations from phase 5 of the Coupled Model Intercomparison Project. In RCP2.6, the deep ocean continues to warm while RF decreases after reaching a peak. The deep ocean warming helps to shape the trajectories of GMST and fuels persistent thermosteric sea level rise. A diagnostic method is used to decompose further changes after the RF peak into a slow warming component under constant peak RF and a cooling component due to the decreasing RF. Specifically, the slow warming component amounts to 0.2°C (0.6°C) by 2100 (2300), raising the hurdle for achieving the low warming targets. When RF declines, the deep ocean warming takes place in all basins but is the most pronounced in the Southern Ocean and Atlantic Ocean where surface heat uptake is the largest. The climatology and change of meridional overturning circulation are both important for the deep ocean warming. To keep the GMST rise at a low level, substantial decrease in RF is required to offset the warming effect from the ocean slow response.

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

2019 ◽  
Vol 12 (7) ◽  
pp. 2727-2765 ◽  
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.

scholarly journals Reduced complexity model intercomparison project phase 1: Protocol, results and initial observations

2020 ◽  
Author(s):  
Zebedee R. J. Nicholls ◽  
Malte Meinshausen ◽  
Jared Lewis ◽  
Robert Gieseke ◽  
Dietmar Dommenget ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Phase 1 ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Internal Variability ◽  
Second Phase ◽  
Model Intercomparison ◽  
Intercomparison Project ◽  
Reduced Complexity

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.

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.

scholarly journals Revisiting the Northern Mode of East Asian Winter Monsoon Variation and Its Response to Global Warming

2018 ◽  
Vol 31 (21) ◽  
pp. 9001-9014 ◽  
Author(s):  
Hainan Gong ◽  
Lin Wang ◽  
Wen Zhou ◽  
Wen Chen ◽  
Renguang Wu ◽  
...  
Keyword(s):  
Global Warming ◽  
Radiative Forcing ◽  
East Asian Winter Monsoon ◽  
East Asian ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Winter Monsoon ◽  
Cmip5 Models ◽  
Boreal Winter ◽  
Asian Winter Monsoon

This study revisits the northern mode of East Asian winter monsoon (EAWM) variation and investigates its response to global warming based on the ERA dataset and outputs from phase 5 of the Coupled Model Intercomparison Project (CMIP5) models. Results show that the observed variation in East Asian surface air temperature (EAT) is tightly coupled with sea level pressure variation in the expanded Siberian high (SH) region during boreal winter. The first singular value decomposition (SVD) mode of the EAT and SH explains 95% of the squared covariance in observations from 1961 to 2005, which actually represents the northern mode of EAWM variation. Meanwhile, the first SVD mode of the EAT and SH is verified to be equivalent to the first empirical orthogonal function mode (EOF1) of the EAT and SH, respectively. Since the leading mode of the temperature variation is significantly influenced by radiative forcing in a rapidly warming climate, for reliable projection of long-term changes in the northern mode of the EAWM, we further employ the EOF1 mode of the SH to represent the northern mode of EAWM variation. The models can well reproduce this coupling between the EAT and SH in historical simulations. Meanwhile, a robust weakening of the northern mode of the EAWM is found in the RCP4.5 scenario, and with stronger warming in the RCP8.5 scenario, the weakening of the EAWM is more pronounced. It is found that the weakening of the northern mode of the EAWM can contribute 6.7% and 9.4% of the warming trend in northern East Asian temperature under the RCP4.5 and RCP8.5 scenarios, respectively.

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

2018 ◽  
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 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.

scholarly journals Aerosol Effective Radiative Forcing in the Online Aerosol Coupled CAS-FGOALS-f3-L Climate Model

Atmosphere ◽  
2020 ◽  
Vol 11 (10) ◽  
pp. 1115
Author(s):  
Hao Wang ◽  
Tie Dai ◽  
Min Zhao ◽  
Daisuke Goto ◽  
Qing Bao ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Climate Model ◽  
Transport Model ◽  
Radiation Transport ◽  
Coupled Model ◽  
Global Ocean ◽  
Spectral Radiation ◽  
Anthropogenic Aerosol ◽  
Aerosol Cloud ◽  
Effective Radiative Forcing

The effective radiative forcing (ERF) of anthropogenic aerosol can be more representative of the eventual climate response than other radiative forcing. We incorporate aerosol–cloud interaction into the Chinese Academy of Sciences Flexible Global Ocean–Atmosphere–Land System (CAS-FGOALS-f3-L) by coupling an existing aerosol module named the Spectral Radiation Transport Model for Aerosol Species (SPRINTARS) and quantified the ERF and its primary components (i.e., effective radiative forcing of aerosol-radiation interactions (ERFari) and aerosol-cloud interactions (ERFaci)) based on the protocol of current Coupled Model Intercomparison Project phase 6 (CMIP6). The spatial distribution of the shortwave ERFari and ERFaci in CAS-FGOALS-f3-L are comparable with that of most available CMIP6 models. The global mean 2014–1850 shortwave ERFari in CAS-FGOALS-f3-L (−0.27 W m−2) is close to the multi-model means in 4 available models (−0.29 W m−2), whereas the assessing shortwave ERFaci (−1.04 W m−2) and shortwave ERF (−1.36 W m−2) are slightly stronger than the multi-model means, illustrating that the CAS-FGOALS-f3-L can reproduce the aerosol radiation effect reasonably well. However, significant diversity exists in the ERF, especially in the dominated component ERFaci, implying that the uncertainty is still large.

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