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The world climate research centres are currently running Earth System
Models (ESMs) forced by Representative Concentration Pathways (RCP)
scenarios. Based on these future pathways in atmospheric greenhouse gas
concentrations, the emphasis has been mainly on estimating the
associated levels of global warming that might be expected. There is
also the...
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Citations
... The ranges of the parameters perturbed were selected on the basis of the original ranges given in Table B1 of Tachiiri et al. (2013) rather than the final range in Table 1 of the same work. Whereas Tachiiri et al. (2013) considered the representability of the Coupled Climate Carbon Cycle Model Inter-comparison Project (C4MIP) models (Friedlingstein et al. 2006), the ranges of parameter perturbation in the present work are based on previous studies. ...
... The ranges of the parameters perturbed were selected on the basis of the original ranges given in Table B1 of Tachiiri et al. (2013) rather than the final range in Table 1 of the same work. Whereas Tachiiri et al. (2013) considered the representability of the Coupled Climate Carbon Cycle Model Inter-comparison Project (C4MIP) models (Friedlingstein et al. 2006), the ranges of parameter perturbation in the present work are based on previous studies. In particular, the range of horizontal diffusivity is determined on the basis of Collins et al. (2007) and Roach et al. (2018), and is significantly narrowed. ...
The transient climate response to cumulative carbon emissions (TCRE) is a key metric in estimating the remaining carbon budget for given temperature targets. However, the TCRE has a small scenario dependence that can be non-negligible for stringent temperature targets. To investigate the parametric correlations and scenario dependence of the TCRE, the present study uses a 512-member ensemble of an Earth system model of intermediate complexity (EMIC) perturbing 11 physical and biogeochemical parameters under scenarios with steady increases of 0.25%, 0.5%, 1%, 2%, or 4% per annum (ppa) in the atmospheric CO 2 concentration (pCO 2 ), or an initial increase of 1% followed by an annual decrease of 1% thereafter. Although a small difference of 5% (on average) in the TCRE is observed between the 1-ppa and 0.5-ppa scenarios, a significant scenario dependence is found for the other scenarios, with a tendency toward large values in gradual or decline-after-a-peak scenarios and small values in rapidly increasing scenarios. For all scenarios, correlation analysis indicates a remarkably large correlation between the equilibrium climate sensitivity (ECS) and the relative change in the TCRE, which is attributed to the longer response time of the high ECS model. However, the correlations of the ECS with the TCRE and its scenario dependence for scenarios with large pCO 2 increase rates are slightly smaller, and those of biogeochemical parameters such as plant respiration and the overall pCO 2 –carbon cycle feedback are larger, than in scenarios with gradual increases. The ratio of the TCREs under the overshooting (i.e., 1-ppa decrease after a 1-ppa increase) and 1-ppa increase only scenarios had a clear positive relation with zero-emission commitments. Considering the scenario dependence of the TCRE, the remaining carbon budget for the 1.5 °C target could be reduced by 17 or 22% (before and after considering the unrepresented Earth system feedback) for the most extreme case (i.e., the 67 th percentile when using the 0.25-ppa scenario as compared to the 1-ppa increase scenario). A single ensemble EMIC is also used to indicate that, at least for high ECS (high percentile) cases, the scenario dependence of the TCRE should be considered when estimating the remaining carbon budget.
... However, Hajima et al (2012) reported some increase in TCRE using the MIROC-ESM (with large climate sensitivity of 4.7 K), implying significant model dependence of TCRE during the final parts, i.e. when pCO 2 is stabilized or decreasing, of the two scenarios. Using a large perturbed parameter ensemble and a type of EMIC, Tachiiri et al (2013) showed that the TCRE ensemble mean remained constant throughout an experiment with the RCP2.6 and RCP4.5 scenarios and during the transition from RCP4.5 to RCP2.6. ...
... In the present study, which focused on the uncertainty of TCRE after stabilization, we reanalyzed the results of Tachiiri et al (2013) and performed an experiment to assess the equilibrium states. By analyzing large ensemble datasets, we filled the gap not covered by the limited number of comprehensive models. ...
... The experiment (Tachiiri et al 2013) was performed using an EMIC called the Japan Uncertainty Modelling Project-Loosely Coupled Model (JUMP-LCM; Tachiiri et al 2010), which has a two-dimensional energy-moisture balance atmosphere, coupled with an ocean general circulation model. In addition, a process-based land ecosystem model is 'loosely coupled'. ...
We analyzed a dataset from an experiment of an earth system model of intermediate complexity, focusing on the change in transient climate response to cumulative carbon emissions (TCRE) after atmospheric CO2 concentration was stabilized in the Representative Concentration Pathway (RCP) 4.5. We estimated the TCRE in 2005 at 0.3-2.4 K/TtC for an unconstrained case and 1.1-1.7 K/TtC when constrained with historical and present-day observational data, the latter result being consistent with other studies. The range of TCRE increased when the increase of CO2 concentration was moderated and then stabilized. This is because the larger (smaller) TCRE members yield even greater (less) TCRE. An additional experiment to assess the equilibrium state revealed significant changes in temperature and cumulative carbon emissions after 2300. We also found that variation of land carbon uptake is significant to the total allowable carbon emissions and subsequent change of the TCRE. Additionally, in our experiment, we revealed that equilibrium climate sensitivity (ECS), one of the 12 parameters perturbed in the ensemble experiment, has a strong positive relationship with the TCRE at the beginning of the stabilization and its subsequent change. We confirmed that for participant models in the Coupled Model Intercomparison Project Phase 5, ECS has a strong positive relationship with TCRE. For models using similar experimental settings, there is a positive relationship with TCRE for the start of the period of stabilization in CO2 concentration, and rate of change after stabilization. The results of this study are influential regarding the total allowable carbon emissions calculated from the TCRE and the temperature increase set as the mitigation target.
... The 11 ESMs whose results are taken for this study were all used in the IPCC Fifth Assessment Report 5 . JUMP-LCM is an Earth system model of intermediate complexity built to mimic the full ESM MIROC3, of which key parameters (such as climate sensitivity, diffusivity in the ocean, maximum photosynthetic rate and so on) were varied to represent the behaviour of C 4 MIP models as much as possible 13 . OSCAR v2.1 is a simple carbon-climate model whose modules are designed to emulate a range of sensitivities derived from model intercomparisons such as C 4 MIP or CMIP5 (refs 14,40). ...
... OSCAR v2.1 is a simple carbon-climate model whose modules are designed to emulate a range of sensitivities derived from model intercomparisons such as C 4 MIP or CMIP5 (refs 14,40). For the last two models, we take 'constrained' ensembles of compatible emissions that were compared and rated against observations of various climate variables 13,14 . The global mean temperature projections by the models are shown in Supplementary Fig. 10, and their transient climate response to (cumulative) emissions are shown in Supplementary Fig. 11. ...
... To estimate the change in carbon stocks of ocean and land, models were prescribed atmospheric CO 2 concentration following historical estimates up to 2005 and the RCP2.6 scenario and its extension afterwards 2 . Depending on the study [12][13][14] , however, other climate forcings (other greenhouse gases, short-lived species and natural forcings) were prescribed as concentrations or directly as radiative forcing, which is thus a source of discrepancy among the estimates of compatible emissions. Note that these non-CO 2 forcings do impact the estimates of compatible emissions through their effect on climate change, which then feeds back on the carbon cycle. ...
To limit global warming to <2 °C we must reduce the net amount of CO2 we release into the atmosphere, either by producing less CO2 (conventional mitigation) or by capturing more CO2 (negative emissions). Here, using state-of-the-art carbon-climate models, we quantify the trade-off between these two options in RCP2.6: an Intergovernmental Panel on Climate Change scenario likely to limit global warming below 2 °C. In our best-case illustrative assumption of conventional mitigation, negative emissions of 0.5-3 Gt C (gigatonnes of carbon) per year and storage capacity of 50-250 Gt C are required. In our worst case, those requirements are 7-11 Gt C per year and 1,000-1,600 Gt C, respectively. Because these figures have not been shown to be feasible, we conclude that development of negative emission technologies should be accelerated, but also that conventional mitigation must remain a substantial part of any climate policy aiming at the 2-°C target.
... Through this, we can assess the effect of uncertainty in climate sensitivity on ecosystems and then on the amount of emission following given concentration pathways. An example is Tachiiri et al. (2013) who presented the potential of constraining physical properties of Earth systems using carbon-cycle related observations (in their case, carbon emission). However, they stated that this should be done very carefully because the posterior probability distribution function of physical parameters is sensitive to the characteristics of ecosystem components. ...
[Comment form the 1st author]
This review article summarize the findings on climate projection, its interaction with biogeochemistry and atmospheric chemistry, and other important topics such as geo-engineering etc, in terms of the earth system modeling. We briefly summarized the new findings up to AR5, and suggest new issues we have to tackle with in the next phase of earth system modeling. By following the journal's instruction, this article will be suitable in particular for the people who begin to join this science region.
[Formal abstract]
Changes in the natural environment that are the result of human activities are becoming evident. Since these changes are interrelated and can not be investigated without interdisciplinary collaboration between scientific fields, Earth system science (ESS) is required to provide a framework for recognizing anew the Earth system as one composed of its interacting subsystems. The concept of ESS has been partially realized by Earth system models (ESMs). In this paper, we focus on modeling in ESS, review related findings mainly from the latest assessment report of the Intergovernmental Panel on Climate Change, and introduce tasks under discussion for the next phases of the following areas of science: the global nitrogen cycle, ocean acidification, land-use and land-cover change, ESMs of intermediate complexity, climate geoengineering, ocean CO 2 uptake, and deposition of bioavailable iron in marine ecosystems. Since responding to global change is a pressing mission in Earth science, modeling will continue to contribute to the cooperative growth of diversifying disciplines and expanding ESS, because modeling connects traditional disciplines through explicit interaction between them.
Although the effectiveness of best management practices (BMPs) in reducing urban flooding is widely recognized, the improved sustainability achieved by implementing BMPs in upstream suburban areas, reducing downstream urban floods, is debated. This study introduces a new definition of urban drainage system (UDS) sustainability, focusing on BMP usage to enhance system performance after adaptation to climate change. Three types of hydraulic reliability index (HRI) plus robustness and improvability indices were used to quantify the potential enhanced sustainability of the system in a changing climate, together with a climate change adaptability index (CCAI). The sustainability of UDS for the safe conveyance of stormwater runoff is investigated under different land-use scenarios: No BMP, BMP in urban areas, and BMP inside and upstream of urban areas, considering climate change impacts. Rainfall–runoff simulation alongside drainage network modelling is conducted using a stormwater management model (US EPA SWMM) to determine the inundation areas for both baseline and future climatic conditions. A new method for disaggregating daily rainfall to hourly, proposed to provide a finer resolution of input rainfall to SWMM, was applied to a semi-urbanized catchment whose upstream runoff from mountainous areas may contribute to the stormwater runoff in downstream urban parts. Our findings confirm an increase in the number of inundation points and reduction in sustainability indices of UDS due to climate change. The results present an increase in UDS reliability from 4% to 16% and improvements in other sustainability indicators using BMPs in upstream suburban areas compared to implementing them in urban areas.
