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Changes in the Antarctic ice sheet play a critical role in the Southern Ocean and global climates. Although many studies have pointed out that enhanced ocean heat delivery onto the Antarctic continental shelf regions can cause significant changes in Antarctic ice-shelf basal melting, the associated physical mechanisms require further research. Here, we perform numerical experiments using an ocean–sea ice model with an ice-shelf component to simulate future projections in Antarctic ice-shelf basal melting in a warming climate, focusing on the driving mechanism and the physical linkages with the seasonal Antarctic sea ice fields and coastal water masses. The model projects a distinct superlinear response of ice-shelf basal melting to future atmospheric warming, demonstrating that future projections of the Antarctic and Southern Ocean climate bifurcate with the level of global warming. Detailed examinations of sea ice and water masses show that in an extreme warming scenario, a combination of enhanced intrusions of warm deep water and warm summertime surface water can cause the nonlinear response of Antarctic ice-shelf basal melting. A large reduction in Antarctic coastal sea ice and the associated ocean freshening by decreasing coastal sea ice production in winter provide favorable conditions for summertime warm surface water formation and warm deep water intrusions onto some continental shelves. The model results demonstrate that disappearing summertime sea ice along the Antarctic coastal margins in a warming climate heralds the nonlinear increase in Antarctic ice-shelf basal melting, presumably contributing to the negative mass balance of the Antarctic ice sheet and the sea level rise.

Nutrient inputs from the atmosphere and rivers to the ocean are increased substantially by human activities. These increasing inputs of nutrients from human activities promote oceanic NPP, potentially partially counteracting decreases caused by climate change. Then, increases in export of organic matter to the ocean interior and its decomposition consumes dissolved oxygen. Therefore, nutrient inputs to the ocean promote carbon uptake and amplify climate-driven ocean deoxygenation. However, the previous generation of Earth system models that participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5), which contributed substantially to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, did not account for anthropogenic nutrient inputs to the ocean. Several CMIP phase 6 (CMIP6) Earth system models do consider anthropogenic nutrient inputs to the ocean for the historical period, but their impact on ocean biogeochemical cycles has not been fully assessed, even for individual Earth system models. Therefore, our understanding of the impact of such perturbations on ocean biogeochemistry is even less complete than that associated with climate change. In particular, the quantitative relationship between the effects of climate change on ocean biogeochemical cycles and those of anthropogenic nutrient inputs remains poorly understood.In this study, using historical simulations by one of the CMIP6 models (MIROC-ES2L) that considers anthropogenic nutrient inputs, we demonstrate that the contribution of anthropogenic nutrient inputs to past changes in global oceanic productivity, carbon uptake, and deoxygenation is of similar magnitude to the effect of climate change. In particular, two noteworthy results are obtained: (1) that anthropogenic fertilization could more than counteract the expected decrease in NPP caused by ocean warming and stratification for the historical period, and (2) that it could accelerate climate-driven deoxygenation in the upper ocean, helping to close the gap between models and observations. Additionally, current estimation of the imbalance in the carbon budget could be explained partially by increase in oceanic carbon uptake associated with anthropogenic nutrient inputs to the ocean. These improvements provide support regarding the significant contribution of anthropogenic nutrient inputs to global changes in ocean biogeochemistry. Considering the effects of both nutrient inputs and climate change is crucial in assessing anthropogenic impacts on ocean biogeochemistry.

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Nutrient inputs from the atmosphere and rivers to the ocean are increased substantially by human activities. However, the effects of increased nutrient inputs are not included in the widely used CMIP5 Earth system models, which introduce bias into model simulations of ocean biogeochemistry. Here, using historical simulations by an Earth system model with perturbed atmospheric and riverine nutrient inputs, we show that the contribution of anthropogenic nutrient inputs to past global changes in ocean biogeochemistry is of similar magnitude to the effect of climate change. Anthropogenic nutrient inputs increase oceanic productivity and carbon uptake, offsetting climate-induced decrease and accelerating climate-driven deoxygenation in the upper ocean. Moreover, accounting for anthropogenic nutrient inputs improves the known carbon budget imbalance and model underestimation of the observed decrease in the global oxygen inventory. Considering the effects of both nutrient inputs and climate change is crucial in assessing anthropogenic impacts on ocean biogeochemistry.

Following the protocol of the fourth phase of the Paleoclimate Modelling Intercomparison Project (PMIP4), we performed numerical experiments targeting distinctive past time periods using the Model for Interdisciplinary Research on Climate, Earth System version 2 for Long-term simulations (MIROC-ES2L), which is an Earth system model. Setup and basic performance of the experiments are presented. The Last Glacial Maximum was one of the most extreme climate states during the Quaternary and conducting numerical modeling experiments of this period has long been a challenge for the paleoclimate community. We conducted a Last Glacial Maximum experiment with a long spin-up of nearly 9000 years. Globally, there was reasonable agreement between the anomalies relative to the present day derived from model climatology and those derived from proxy data archives, while some regional discrepancies remained. By changing orbital and greenhouse gas forcings, we conducted experiments for two interglacial periods: 6000 and 127 000 years before present. Model anomalies relative to the present day were qualitatively consistent with variations in solar forcing. However, anomalies in the model were smaller than those derived from proxy data archives, suggesting that processes that play a role in past interglacial climates remain lacking in this state-of-the-art model. We conducted transient simulations from 850 to 1850 CE and from 1850 to 2014 CE. Cooling in the model indicated a clear response to huge volcanic eruptions, consistent with paleo-proxy data. The contrast between cooling during the Little Ice Age and warming during the 20th to 21st centuries was represented well at the multidecadal timescale.

The IPCC Task Group on Data Support for Climate Change Assessments (TG-Data) recommends the implementation of FAIR (Findable, Accessible, Interoperable, Reusable) data principles and best practices for the documentation and curation of data that is assessed by the IPCC. The motivation to implement FAIR in the IPCC is to increase transparency and accessibility of the assessment, the implementation of the IPCC Error Protocol, and the long-term curation of the assessed digital information. This document introduces the implementation of FAIR data principles into the IPCC process and reflects the four elements of FAIR to find the data, produce and reproduce figures and, finally, to document the provenance for reusability. It presents standard (basic) measures that are recommended for all digital data that is assessed, intermediate measures that achieve reproducibility of assessed digital information, for example through the use of collaborative platforms for figure development, and also full (advanced) measures to achieve reusability of digital products with complete provenance documentation.

Many nations responded to the corona virus disease‐2019 (COVID‐19) pandemic by restricting travel and other activities during 2020, resulting in temporarily reduced emissions of CO2, other greenhouse gases and ozone and aerosol precursors. We present the initial results from a coordinated Intercomparison, CovidMIP, of Earth system model simulations which assess the impact on climate of these emissions reductions. 12 models performed multiple initial‐condition ensembles to produce over 300 simulations spanning both initial condition and model structural uncertainty. We find model consensus on reduced aerosol amounts (particularly over southern and eastern Asia) and associated increases in surface shortwave radiation levels. However, any impact on near‐surface temperature or rainfall during 2020–2024 is extremely small and is not detectable in this initial analysis. Regional analyses on a finer scale, and closer attention to extremes (especially linked to changes in atmospheric composition and air quality) are required to test the impact of COVID‐19‐related emission reductions on near‐term climate., Key Points Lockdown restrictions during COVID‐19 have reduced emissions of aerosols and greenhouse gases12 CMIP6 Earth system models have performed coordinated experiments to assess the impact of this on climateAerosol amounts are reduced over southern and eastern Asia but there is no detectable change in annually averaged temperature or precipitation

The measurements of one of the major greenhouse gases, carbon dioxide (CO2), are being made using dedicated satellite remote sensing since the launch of the greenhouse gases observing satellite (GOSAT) by a three-way partnership between the Japan Aerospace Exploration Agency (JAXA), the Ministry of Environment (MoE) and the National Institute for Environmental Studies (NIES), and the National Aeronautics and Space Administration (NASA) Orbiting Carbon Observatory-2 (OCO-2). In the past 10 years, estimation of CO2 fluxes from land and ocean using the earth system models (ESMs) and inverse modelling of in situ atmospheric CO2 data have also made significant progress. We attempt, for the first time, to evaluate the CO2 fluxes simulated by an earth system model (MIROC-ES2L) and the fluxes estimated by an inverse model (MIROC4-Inv) using in situ data by comparing with GOSAT and OCO-2 observations. Both MIROC-ES2L and MIROC4-Inv fluxes are used in the MIROC4-atmospheric chemistry transport model (referred to as ACTM_ES2LF and ACTM_InvF, respectively) for calculating total column CO2 mole fraction (XCO2) that are sampled at the time and location of the satellite measurements. Both the ACTM simulations agreed well with the GOSAT and OCO-2 satellite observations, within 2 ppm for the spatial maps and time evolutions of the zonal mean distributions. Our results suggest that the inverse model using in situ data is more consistent with the OCO-2 retrievals, compared with those of the GOSAT XCO2 data due to the higher accuracy of the former. This suggests that the MIROC4-Inv fluxes are of sufficient quality to evaluate MIROC-ES2L simulated fluxes. The ACTM_ES2LF simulation shows a slightly weaker seasonal cycle for the meridional profiles of CO2 fluxes, compared with that from the ACTM_InvF. This difference is revealed by greater XCO2 differences for ACTM_ES2LF vs GOSAT, compared with those of ACTM_InvF vs GOSAT. Using remote sensing–based global products of leaf area index (LAI) and gross primary productivity (GPP) over land, we show a weaker sensitivity of MIROC-ES2L biospheric activities to the weather and climate in the tropical regions. Our results clearly suggest the usefulness of XCO2 measurements by satellite remote sensing for evaluation of large-scale ESMs, which so far remained untested by the sparse in situ data.

It is important to understand how the emissions of different regions, sectors, or climate forcers play a role on pathways toward the Paris Agreement temperature targets. There are however methodological challenges for attributing individual contributions due to complexities associated with a variety of climate forcers affecting the climate system on different spatial and temporal scales. Here, we use the latest historical and future emissions data for a comprehensive set of climate forcers as well as land-use datasets and apply the normalized marginal approach to quantify the forcing contributions of regions, sectors and forcing agents toward the 2C and 1.5C targets. We show that most of the worldwide regions and sectors need to maintain forcing levels not higher than present levels to attain the 1.5C target of the Paris Agreement, while slightly higher future forcing levels than present levels are allowed for the 2C target. Our results illustrate the importance of negative CO2 emissions, which contribute -0.75+/-0.44 Wm-2 and -0.42+/-0.27 Wm-2 to the 2C and 1.5C targets. Less negative forcings, or more positive forcings are also identified for the land-use albedo for the 2C and 1.5C scenarios compared to existing studies., 53 pages, 19 figures

The past 20 years of research using Earth system models (ESMs) is reviewed with an emphasis on results from the ESM based on MIROC (Model for Interdisciplinary Research on Climate) developed in Japan. Earth system models are climate models incorporating biogeochemical processes such as the carbon cycle. The development of ESM was triggered by studies of the feedback between climate change and the carbon cycle. State-of-the-art ESMs are much more realistic than the first ESMs. They now include various biogeochemical processes other than carbon, such as atmospheric chemistry and the nitrogen and iron cycles as well as nutrient transport by atmospheric dust and rivers. They are used to address many practical issues, such as evaluating the amount of carbon dioxide emissions that is consistent with climate change mitigation targets, and are indispensable tools for the development of climate change mitigation policies. Novel, ambitious attempts to use ESMs include coupling socioeconomics with Earth systems, and projecting the carbon cycle on decadal timescales. Development of ESMs requires ongoing integration of multiple aspects of climate science. Emerging applications of ESMs can bring forth meaningful insights, and should be directed toward expanding connections with fields outside climate science, e.g., socioeconomics.

Earth system models (ESMs) are commonly used for simulating the climate–carbon (C) cycle and for projecting future global warming. While ESMs are most often applied to century-long climate simulations, millennium-long simulations, which have been conducted by other types of models but not by ESM because of the computational cost, can provide basic fundamental properties of climate–C cycle models and will be required for estimating the carbon dioxide (CO2) concentration and subsequent climate stabilization in the future. This study used two ESMs (the Model for Interdisciplinary Research on Climate, the Earth system model version (MIROC-ESM) and the MIROC Earth system version 2 for long-term simulation (MIROC-ES2L)) to investigate millennium-scale climate and C cycle adjustment to external forcing. The CO2 concentration was doubled abruptly at the beginning of the model simulations and kept at that level for the next 1000 or 2000 years; these model simulations were compared with transient simulations where the CO2 was increased at the rate of 1% year−1 for up to 140 years (1pctCO2). Model simulations to separate and evaluate the C cycle feedbacks were also performed. Unlike the 1pctCO2 experiment, the change in temperature–cumulative anthropogenic C emission (∆T–CE) relationship was non-linear over the millennium time-scales; there were differences in this nonlinearity between the two ESMs. The differences in ∆T–CE among existing models suggest large uncertainty in the ∆T and CE in the millennium-long climate-C simulations. Ocean C and heat transport were found to be disconnected over millennium time-scales, leading to longer time-scale of ocean C accumulation than heat uptake. Although the experimental design used here was highly idealized, this long-lasting C uptake by the ocean should be considered as part of the stabilization of CO2 concentration and global warming. Future studies should perform millennium time-scale simulations using a hierarchy of models to clarify climate-C cycle processes and to understand the long-term response of the Earth system to anthropogenic perturbations.

The measurements of one of the major greenhouse gases, carbon dioxide (CO 2 ), are being made using dedicated satellite remote sensing since the launch of the greenhouse gases observing satellite (GOSAT) by JAXA in 2009 and NASA’s Orbiting Carbon Observatory-2 (OCO-2). In the past 10 years, estimation of CO 2 fluxes from land and ocean using the earth system models (ESMs) and inverse modelling of in situ atmospheric CO 2 data have also made significant progress. In this article, we attempt, for the first time, to evaluate the CO 2 fluxes simulated by an earth system model (MIROC-ES2L) using GOSAT observations and the fluxes estimated by an inverse model (MIROC4-Inv) for the period 2009-2014. Further, we use the OCO-2 measurements for testing the consistency of inversion results for the period 2014-2018, along with the GOSAT data. Both MIROC-ES2L and MIROC4-Inv fluxes are used in the MIROC4-atmospheric chemistry transport model (referred to as ACTM_ES2LF and ACTM_InvF, respectively) for calculating CO 2 concentrations that are sampled at the time and location of the satellite measurements. Our results suggest the inverse model using in situ data are more consistent with the OCO-2 retrievals, compared to those of the GOSAT XCO 2 data, suggesting possible improvements in the present GOSAT retrieval system by better accounting for the degradation correction of the TANSO-FTS. The ACTM_ES2LF simulation shows a slightly weaker seasonal cycle for the meridional profiles of CO 2 fluxes, compared to that from the ACTM_InvF. This difference is revealed by greater ACTM_ES2LF vs GOSAT differences, compared to those of ACTM_InvF vs GOSAT. We also find that the simulated seasonal cycle amplitude of XCO 2 by ACTM_ES2LF are slightly weaker compared to those observed by GOSAT or ACTM_InvF. Using remote sensing based global products of leaf area index (LAI) and gross primary productivity (GPP) over land, we show a weaker sensitivity of MIROC-ES2L biospheric activities to the weather and climate in the tropical regions. Our results clearly suggest the usefulness of XCO 2 measurements by satellite remote sensing for evaluation of large-scale ESMs, which so far remained untested by the sparse in situ data.

Following the protocol of the fourth phase of the Paleoclimate Modeling Intercomparison Project (PMIP4), we performed numerical experiments targeting distinctive past time periods using the Model for Interdisciplinary Research on Climate Earth System Model (MIROC-ES2L), which is an Earth System Model. Setup and basic performance of the experiments are presented. The Last Glacial Maximum was one of the most extreme climate states during the Quaternary and conducting numerical modeling experiments of this period has long been a challenge for the paleoclimate community. We conducted a Last Glacial Maximum experiment with a long spin-up of nearly 9,000 years. Globally, there is reasonable agreement between the anomalies relative to present day derived from model climatology and those derived from proxy data archives while some regional discrepancies remain. By changing orbital and greenhouse gas forcings, we conducted experiments for two interglacial periods: 6,000 and 127,000 years before present. Model anomalies relative to present day are qualitatively consistent with variations in solar forcing. However, anomalies in the model are smaller than those derived from proxy data archives, suggesting that processes that play a role in past interglacial climates are still missing in this state-of-the-art model. We conducted transient simulations from 850 CE to 1850 CE and from 1850 CE to 2014 CE. Cooling in the model indicates clear responses to huge volcanic eruptions, which are consistent with paleo-proxy data. The contrast between cooling during the Little Ice Age and warming during the 20th to 21st centuries is well represented at the multi-decadal time scale.

Based on a set of climate simulations utilizing two kinds of Earth system models (ESMs) in which observed ocean hydrographic data are assimilated using exactly the same data assimilation procedure, we have clarified that the successful simulation of the observed air–sea CO2 flux variations in the equatorial Pacific is tightly linked to the reproducibility of coupled physical air–sea processes. When an ESM with a weaker ENSO (El Niño–Southern Oscillations) amplitude than that of the observations was used for historical simulations with ocean data assimilation, the observed equatorial anticorrelated relationship between the sea surface temperature (SST) and the air–sea CO2 flux on interannual to decadal timescales could not be represented. The simulated CO2 flux anomalies were upward (downward) during El Niño (La Niña) periods in the equatorial Pacific. The reason for this was that the non-negligible correction term in the governing equation of ocean temperature, which was added via the ocean data assimilation procedure, caused an anomalous, spurious equatorial upwelling (downwelling) during El Niño (La Niña) periods, which brought more (less) subsurface layer water rich in dissolved inorganic carbon (DIC) to the surface layer. On the other hand, in the historical simulations where the observational data were assimilated into the other ESM with a more realistic ENSO representation, the correction term associated with the assimilation procedure remained small enough so as not to disturb an anomalous advection–diffusion balance for the equatorial ocean temperature. Consequently, spurious vertical transport of DIC and the resultant positively correlated SST and air–sea CO2 flux variations did not occur. Thus, the reproducibility of the tropical air–sea CO2 flux variability with data assimilation can be significantly attributed to the reproducibility of ENSO in an ESM. Our results suggest that, when using data assimilation to initialize ESMs for carbon cycle predictions, the reproducibility of the internal climate variations in the model itself is of great importance.

The effect of aerosols is one of many uncertain factors in projections of future climate. However, the behaviour of mineral dust aerosols (dust) can be investigated within the context of past climate change. The Last Glacial Maximum (LGM) is known to have had enhanced dust deposition in comparison with the present, especially over polar regions. Using the Model for Interdisciplinary Research on Climate Earth System Model (MIROC-ESM), we conducted a standard LGM experiment following the protocol of the Paleoclimate Modelling Intercomparison Project phase 3 and sensitivity experiments. We imposed glaciogenic dust on the standard LGM experiment and investigated the impacts of glaciogenic dust and non-glaciogenic dust on the LGM climate. Global mean radiative perturbations by glaciogenic and non-glaciogenic dust were both negative, consistent with previous studies. However, glaciogenic dust behaved differently in specific regions; e.g. it resulted in less cooling over the polar regions. One of the major reasons for reduced cooling is the ageing of snow or ice, which results in albedo reduction via high dust deposition, especially near sources of high glaciogenic dust emission. Although the net radiative perturbations in the lee of high glaciogenic dust provenances are negative, warming by the ageing of snow overcomes this radiative perturbation in the Northern Hemisphere. In contrast, the radiative perturbation due to high dust loading in the troposphere acts to warm the surface in areas surrounding Antarctica, primarily via the longwave aerosol–cloud interaction of dust, and it is likely the result of the greenhouse effect attributable to the enhanced cloud fraction in the upper troposphere. Although our analysis focused mainly on the results of experiments using the atmospheric part of the MIROC-ESM, we also conducted full MIROC-ESM experiments for an initial examination of the effect of glaciogenic dust on the oceanic general circulation module. A long-term trend of enhanced warming was observed in the Northern Hemisphere with increased glaciogenic dust; however, the level of warming around Antarctica remained almost unchanged, even after extended coupling with the ocean.

The Earth system model, Model for Interdisciplinary Research on Climate-Earth system model (MIROC-ESM), in which the leaf area index (LAI) is calculated interactively with an ecological land model, simulated future changes in the snow water equivalent under the scenario of global warming. Using MIROC-ESM, the effects of the snow albedo feedback (SAF) in a boreal forest region of northern Eurasia were examined under the possible climate future scenario RCP8.5. The simulated surface air temperature (SAT) in spring greatly increases across Siberia and the boreal forest region, whereas the snow cover decreases remarkably only in western Eurasia. The large increase in SAT across Siberia is attributed to strong SAF, which is caused by both the reduced snow-covered fraction and the reduced surface albedo of the snow-covered portion due to the vegetation masking effect in those grid cells. A comparison of the future changes with and without interactive LAI changes shows that in Siberia, the vegetation masking effect increases the spring SAF by about two or three times and enhances the spring warming by approximately 1.5 times. This implies that increases in vegetation biomass in the future are a potential contributing factor to warming trends and that further research on the vegetation masking effect is needed for reliable future projection.

Using the outputs of projections under the highest emission scenario of the representative concentration pathways performed by Earth system models (ESMs), we evaluate the ocean acidification rates of subsurface layers of the western North Pacific, where the strongest sink of atmospheric CO2 is found in the mid-latitudes. The low potential vorticity water mass called the North Pacific Subtropical Mode Water (STMW) shows large dissolved inorganic carbon (DIC) concentration increase, and is advected southwestward, so that, in the sea to the south of Japan, DIC concentration increases and ocean acidification occurs faster than in adjacent regions. In the STMW of the Izu-Ogasawara region, the ocean acidification occurs with a pH decrease of ~0.004 year−1 , a much higher rate than the previously estimated global average (0.0023 year−1), so that the pH decreases by 0.3–0.4 during the twenty-first century and the saturation state of calcite (ΩCa) decreases from ~4.8 down to ~2.4. We find that the ESMs with a deeper mixed layer in the Kuroshio Extension region show a larger increase in DIC concentration within the Izu-Ogasawara region and within the Ryukyu Islands region. Comparing model results with the mixed layer depth obtained from the Argo dataset, we estimate that DIC concentration at a depth of ~200 m increases by 1.4–1.6 μmol kg−1 year−1 in the Izu-Ogasawara region and by 1.1–1.4 μmol kg−1 year−1 in the Ryukyu Islands region toward the end of this century.

This study developed a new Model for Interdisciplinary Research on Climate, Earth System version2 for Long-term simulations (MIROC-ES2L) Earth system model (ESM) using a state-of-the-art climate model as the physical core. This model embeds a terrestrial biogeochemical component with explicit carbon–nitrogen interaction to account for soil nutrient control on plant growth and the land carbon sink. The model’s ocean biogeochemical component is largely updated to simulate biogeochemical cycles of carbon, nitrogen, phosphorus, iron, and oxygen such that oceanic primary productivity can be controlled by multiple nutrient limitations. The ocean nitrogen cycle is coupled with the land component via river discharge processes, and external inputs of iron from pyrogenic and lithogenic sources are considered. Comparison of a historical simulation with observation studies showed the model could reproduce reasonable historical changes in climate, the carbon cycle, and other biogeochemical variables together with reasonable spatial patterns of distribution of the present-day condition. The model demonstrated historical human perturbation of the nitrogen cycle through land use and agriculture, and it simulated the resultant impact on the terrestrial carbon cycle. Sensitivity analyses in preindustrial conditions revealed modeled ocean biogeochemistry could be changed regionally (but substantially) by nutrient inputs from the atmosphere and rivers. Through an idealized experiment of a 1 %CO2 increase scenario, we found the transient climate response (TCR) in the model is 1.5 K, i.e., approximately 70 % that of our previous model. The cumulative airborne fraction (AF) is also reduced by 15 % because of the intensified land carbon sink, resulting in an AF close to the multimodel mean of the Coupled Model Intercomparison Project Phase 5 (CMIP5) ESMs. The transient climate response to cumulative carbon emission (TCRE) is 1.3 K EgC−1, i.e., slightly smaller than the average of the CMIP5 ESMs, suggesting optimistic model performance in future climate projections. This model and the simulation results are contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). The ESM could help further understanding of climate–biogeochemical interaction mechanisms, projections of future environmental changes, and exploration of our future options regarding sustainable development by evolving the processes of climate, biogeochemistry, and human activities in a holistic and interactive manner.

Recent climate modeling studies have concluded that cumulative carbon emissions determine temperature increase, regardless of emission pathways. Accordingly, the optimal emission pathway can be determined from a socioeconomic standpoint. To access the path dependence of socioeconomic impacts for cumulative carbon emissions, we used a computable general equilibrium model to analyze impacts on major socioeconomic indicators on a global scale for 30–50 pathways with different emission reduction starting years, different subsequent emission pathways, and three different cumulative 2100 emission scenarios (emissions that meet the 2 °C target, the 2 °C target emissions plus 10 %, and emissions producing radiative forcing of 4.5 W/m2). The results show that even with identical cumulative emission figures, the resulting socioeconomic impacts vary by the pathway realized. For the United Nations 2 °C target, for example, (a) the 95 % confidence interval of cumulative global gross domestic product (GDP) is 1355–1363 trillion US dollars (2010–2100, discount rate = 5 %), (b) the cumulative GDP of pathways with later emission reduction starting years grows weaker (5 % significance level), and (c) emissions in 2100 have a moderate negative correlation with cumulative GDP. These results suggest that GDP loss is minimized with pathways with earlier emission reduction followed by more moderate reduction rates to achieve lower emission levels. Consequently, we suggest an early emission peak to meet the stringent target. In our model setting, it is desirable for emissions to peak by 2020 to reduce mitigation cost and by 2030 at the latest to meet the 2 °C target.

Carbon dioxide (CO2) emissions are strongly associated with economy. The amount of CO2 that human society can emit in order to achieve a climate target depends on physical and biogeochemical properties in the climate system; these vary among climate models or earth system models (ESMs). Thus, uncertainties in such models, the spread remained when we both consider the range of existing models and observational data for key variables, can affect analysis of future global economy. In this study, using a computable general equilibrium model, we analyze the impacts on socioeconomics under a medium climate mitigation scenario by following three emission pathways considering uncertainties in existing ESMs (the lower and upper bounds as well as the mean). The results indicate that the impacts are larger in the lower bound case, despite the fact that economic and energy demands will increase continuously. In a comparison between the upper and lower bound cases, the carbon price of the latter case is approximately three times higher than that of the former case in 2100. Consequently, primary/final energy demand in the lower bound case becomes 1.0%/14% lower, and more renewables and carbon capture and storage are required to be used. Furthermore, the gross domestic product in the lower bound case is 4.1% smaller. Thus, within the scenario, the socioeconomic impacts caused by ESM uncertainties are not insignificant, but are smaller than the differences in annual and cumulative emissions.

The Ninth Symposium on Polar Science/Special session: [S] Antarctic ice-ocean interaction ～observation, reconstruction, and modeling～, Tue. 4 Dec. / Entrance Hall (1st floor) at National Institute of Polar Research

The effect of aerosols is one of the many uncertain factors in projections of the future climate. However, the behaviour of mineral dust aerosol (dust) can be investigated in the context of past climate changes. The Last Glacial Maximum (LGM) is known to have resulted in an enhancement of the dust deposition, especially over the polar regions. Using the Model for Interdisciplinary Research on Climate Earth System Model (MIROC-ESM), we investigated the impact of glaciogenic dust on the climate of the LGM and found that the effect of the enhancement of dust results in less cooling over the polar regions. One of the major reasons of the reduced cooling is the ageing of snow or ice, resulting in the reduction of the albedo by a high dust deposition, especially in the vicinity of high glaciogenic dust emissions. Although the net radiative perturbations in the lee of high glaciogenic dust provenances are negative, warming by ageing of snow overcomes this radiative perturbation in the Northern Hemisphere. In contrast, the radiative perturbation by the high dust loading in the troposphere acts to warm the surface surrounding Antarctica, which is mainly caused by the longwave aerosol–cloud interaction of dust and is likely the result of the greenhouse effect of the enhanced cloud fraction in the upper troposphere. Although our analysis mainly focused on the results of the experiments using the atmospheric part of the MIROC-ESM, we also conducted full MIROC-ESM experiments for a first trial of glacial dust modelling. The long-term trend to enhance warming in the Northern Hemisphere with the increase of glaciogenic dust was observed, whereas the warming level around Antarctica is almost unchanged, even after an extended interaction with the ocean.

Existing Lambertian equivalent reflectivity (LER) ultraviolet (UV) data for the west region of the Southern Ocean indicate a decreasing trend. Since the area surrounding Antarctica is largely unpolluted, LER changes can only be due to variations in the cloud cover and/or in the sea ice extension. In order to evaluate their influence on LER and assess the trend of the UV reflectivity under ice-free and various sea ice concentration (SIC) levels, we compared a multi-satellite-based LER dataset with different satellite observations of cloud cover and SIC for October to March from 1979 to 2012. Despite the high cloud fraction for most of this period, sea ice was found to be the main driver of LER variability and had a greater influence on LER variability than cloud cover. The cloud cover was lower in spring than in summer for all datasets, and this difference appears to be primarily associated with the sea ice extent. While an increment of the cloud fraction of 20% has been found to cause an increase in LER of up to 13 reflectivity units (RU) under ice-free conditions, this increase is halved under low SIC. In contrast, no significant changes in LER data were found under high SIC levels. The correlation between LER and SIC is evident when the latter is higher than approximately 30%. The best correlations (r) between LER and SIC were found for the Weddell Sea (r = 0.87), the Ross Sea (r = 0.85), and the Indian Ocean (r = 0.90) for November, and for the Bellingshausen/Amundsen Seas (r = 0.86) and the Pacific Ocean (r = 0.83) for February and October, respectively. In contrast, no correlation was found in the proximity of the coastlines of west Antarctica in October. Overall, an enhancement of SIC from 0% to 100% results in a LER increase of 44 RU. This value is larger than the corresponding sea ice-induced increase computed for the observed and modeled shortwave albedos at the top of the atmosphere (21 and 13 RU, respectively). The LER data distributions for different regions and months show a marked seasonal double peak in reflectivity. The highest relative frequency is driven by the sea ice and peaks at approximately 90 RU, whereas the secondary peak of approximately 50 RU is dominated by cloudiness. Negative trends in the UV reflectivity of the grid cells characterized by a SIC greater than 30% were found for the Bellingshausen/Amundsen Seas (up to − 3.6 ± 1.0 per decade in March). Trends computed over the entire Southern Ocean for mid/high SIC bins are mostly negative, although are often not statistically significant. However, the trend in the reflectivity of the ice-free grid cells was generally positive, probably due to changes in the cloud amount/opacity.

Global warming effects on seaweed beds are already perceptible. Their geographical distributions greatly depend on water temperatures. To predict future geographical distributions of brown alga, Sargassum horneri, forming large beds in the northwestern Pacific, we referred to future monthly surface water temperatures at about 1.1° of longitude and 0.6° of latitude in February and August in 2050 and 2100 simulated by 12 organizations under an A2 scenario of global warming. The southern limit of S. horneri distribution is expected to keep moving northward such that it may broadly disappear from Honshu Island, the Chinese coast, and Korean Peninsula in 2100, when tropical Sargassum species such as Sargassum tenuifolium may not completely replace S. horneri. Thus, their forests in 2100 do not substitute those of S. horneri in 2000. Fishes using the beds and seaweed rafts consisting of S. horneri in East China Sea suffer these disappearances.

Carbon uptake by land and ocean as a biogeochemical response to increasing atmospheric CO2 concentration is called concentration–carbon feedback and is one of the carbon cycle feedbacks of the global climate. This feedback can have a major impact on climate projections with an uncertain magnitude. This paper focuses on the concentration–carbon feedback in terrestrial ecosystems, analyzing the mechanisms and strength of the feedback reproduced by Earth system models (ESMs) participating in phase 5 of the Coupled Model Intercomparison Project. It is confirmed that multiple ESMs driven by a common scenario show a large spread of concentration–carbon feedback strength among models. Examining the behavior of the carbon fluxes and pools of the models showed that the sensitivity of plant productivity to elevated CO2 is likely the key to reduce the spread, although increasing CO2 stimulates other carbon cycle processes. Simulations with a single ESM driven by different CO2 pathways demonstrated that carbon accumulation increases in scenarios with slower CO2 increase rates. Using both numerical and analytical approaches, the study showed that the difference among CO2 scenarios is a time lag of terrestrial carbon pools in response to atmospheric CO2 increase—a high rate of CO2 increase results in smaller carbon accumulations than that in an equilibrium state of a given CO2 concentration. These results demonstrate that the current quantities for concentration–carbon feedback are incapable of capturing the feedback dependency on the carbon storage state and suggest that the concentration feedback can be larger for future scenarios where the CO2 growth rate is reduced.

Near-constancy of the transient climate response to cumulative carbon emissions (TCRE) facilitates the development of future emission pathways compatible with temperature targets. However, most studies have explored TCRE under scenarios of temperature increase. We used an Earth system model (MIROC-ESM) to examine TCRE in scenarios with increasing and stable CO2 concentrations, as well as overshoot pathways in which global mean temperatures peak and decline. Results showed that TCRE is stable under scenarios of increasing or stable CO2 concentration at an atmospheric CO2 concentration (pCO2) double the pre-industrial level. However, in the case of overshoot pathways and a stable pCO2 scenario at a quadrupled pCO2 level, the TCRE increases by 10%–50%, with large increases over a short period just after pCO2 starts to decrease. During the period of pCO2 increase, annual ocean heat uptake (OHU) and ocean carbon storage (CO) (or cumulative ocean carbon uptake from the start of the experiment) exhibit similar changes, resulting in a stable TCRE. During the pCO2 decrease period, after a sudden TCRE increase when pCO2 starts to decrease, the OHU decreases and CO increases (relative to the pCO2 increase period) balance each other out, resulting in a stable TCRE. In overshoot pathways, the temperature distribution when the global mean temperature anomaly cools to 1.5 °C reveals small warming over land and large warming over the oceans relative to the 1% per annum pCO2 increasing scenario, particularly in some high-latitude areas of both hemispheres. The increase in TCRE with overshoot pathways decreases the carbon budget for the temperature anomaly targets in such scenarios. Our analysis showed a 16%–35% decrease in the remaining carbon budget for the 1.5 °C global warming target, in comparison with the reference scenario with a 1% per year pCO2 increase, for pathways peaking at the doubled pCO2 level followed by decline to the pre-industrial level.

An Earth system model (ESM) was used to investigate the effect of reaching the target of 1.5 °C warming (relative to preindustrial levels) after overshooting to the 2 °C level with respect to selected global environment indicators. Two scenarios were compared that diverged after reaching the 2 °C level: one stayed at the 2 °C level, and the other cooled to the 1.5 °C level. Unlike the internationally coordinated model intercomparison projects, the scenarios were developed for a specific climatic model with emissions and land use scenarios consistent with socioeconomic projections from an integrated assessment model. The ESM output resulted in delayed realization of the 1.5 °C and 2 °C targets expected for 2100. The cumulative CO2 emissions for 2010−2100 (2300) were 358 (−53) GtCO2 in the 2 °C scenario and −337 (−936) GtCO2 in the 1.5 °C scenario. We examined the effect of overshooting on commonly used indicators related to surface air temperature, sea surface temperature and total ocean heat uptake. Global vegetation productivity at 2100 showed around a 5% increase in the 2 °C scenario without overshooting compared with the 1.5 °C scenario with overshooting, considered to be caused by more precipitation and stronger CO2 fertilization. A considerable difference was found between the two scenarios in terms of Arctic sea ice, whereas both scenarios indicated few corals would survive past the 21st century. The difference in steric sea level rise, reflecting total cumulative ocean heat uptake, between the two scenarios was

The importance of evaluating models through paleoclimate simulations is becoming more recognized in efforts to improve climate projection. To evaluate an integrated Earth System Model, MIROC-ESM, we performed simulations in time-slice experiments for the mid-Holocene (6000 yr before present, 6 ka) and preindustrial (1850 AD, 0 ka) periods under the protocol of the Coupled Model Intercomparison Project 5/Paleoclimate Modelling Intercomparison Project 3. We first give an overview of the simulated global climates by comparing with simulations using a previous version of the MIROC model (MIROC3), which is an atmosphere–ocean coupled general circulation model. We then comprehensively discuss various aspects of climate change with 6 ka forcing and how the differences in the models can affect the results. We also discuss the representation of the precipitation enhancement at 6 ka over northern Africa. The precipitation enhancement at 6 ka over northern Africa according to MIROC-ESM does not differ greatly from that obtained with MIROC3, which means that newly developed components such as dynamic vegetation and improvements in the atmospheric processes do not have significant impacts on the representation of the 6 ka monsoon change suggested by proxy records. Although there is no drastic difference between the African monsoon representations of the two models, there are small but significant differences in the precipitation enhancement over the Sahara in early summer, which can be related to the representation of the sea surface temperature rather than the vegetation coupling in MIROC-ESM. Because the oceanic parts of the two models are identical, the difference in the sea surface temperature change is ultimately attributed to the difference in the atmospheric and/or land modules, and possibly the difference in the representation of low-level clouds.