Time lag between changes in global temperature and atmospheric CO2 content according to the results of numerical experiments with Earth system models

Author(s):  
Kirill Muryshev ◽  
Alexey Eliseev ◽  
Igor Mokhov ◽  
Maxim Arzhanov ◽  
Alexandr Timazhev ◽  
...  
2015 ◽  
Vol 12 (9) ◽  
pp. 2655-2694 ◽  
Author(s):  
E. S. Weng ◽  
S. Malyshev ◽  
J. W. Lichstein ◽  
C. E. Farrior ◽  
R. Dybzinski ◽  
...  

Abstract. The long-term and large-scale dynamics of ecosystems are in large part determined by the performances of individual plants in competition with one another for light, water, and nutrients. Woody biomass, a pool of carbon (C) larger than 50% of atmospheric CO2, exists because of height-structured competition for light. However, most of the current Earth system models that predict climate change and C cycle feedbacks lack both a mechanistic formulation for height-structured competition for light and an explicit scaling from individual plants to the globe. In this study, we incorporate height-structured competition for light, competition for water, and explicit scaling from individuals to ecosystems into the land model version 3 (LM3) currently used in the Earth system models developed by the Geophysical Fluid Dynamics Laboratory (GFDL). The height-structured formulation is based on the perfect plasticity approximation (PPA), which has been shown to accurately scale from individual-level plant competition for light, water, and nutrients to the dynamics of whole communities. Because of the tractability of the PPA, the coupled LM3-PPA model is able to include a large number of phenomena across a range of spatial and temporal scales and still retain computational tractability, as well as close linkages to mathematically tractable forms of the model. We test a range of predictions against data from temperate broadleaved forests in the northern USA. The results show the model predictions agree with diurnal and annual C fluxes, growth rates of individual trees in the canopy and understory, tree size distributions, and species-level population dynamics during succession. We also show how the competitively optimal allocation strategy – the strategy that can competitively exclude all others – shifts as a function of the atmospheric CO2 concentration. This strategy is referred to as an evolutionarily stable strategy (ESS) in the ecological literature and is typically not the same as a productivity- or growth-maximizing strategy. Model simulations predict that C sinks caused by CO2 fertilization in forests limited by light and water will be down-regulated if allocation tracks changes in the competitive optimum. The implementation of the model in this paper is for temperate broadleaved forest trees, but the formulation of the model is general. It can be expanded to include other growth forms and physiologies simply by altering parameter values.


2021 ◽  
Author(s):  
Paul Clements

Abstract The Intergovernmental Panel on Climate Change (IPCC), the authority for estimating a carbon budget for keeping to the Paris Agreement’s 1.5—2°C target for limiting global warming, has indicated a budget of 580—1170 gigatons (Gt) of carbon dioxide (CO2) from 2018. This budget is based largely on Earth system models using data from the instrumental record over the industrial period. During the prior 800,000 years, however, a range of 120 parts per million (ppm) in atmospheric CO2 was associated with about a 6°C change in temperature, while temperature has only risen about 1°C with the 130 ppm increase in atmospheric CO2 in the industrial period. The paleoclimate record indicates that the anthropogenic increase in CO2 up to the present commits Earth to significant additional warming, such as from reduced albedo as Arctic sea ice melts and further CO2 release from vegetative stores. Instrumental data and model updates also indicate greater warming from these sources than IPCC models predict. Additionally, reductions in CO2 emissions to meet the Paris warming target will also reduce cooling from aerosols, which the IPCC may also have underestimated. Together, these factors indicate that CO2 emissions consistent with the IPCC’s carbon budget are likely to lead to at least 2—2.5°C global warming. I draw on the sustained critique of IPCC findings by Hansen and his colleagues, who have argued that the paleoclimate should be considered on par with Earth system models in climate analysis, and for more ambitious targets for reducing CO2 emissions.


2014 ◽  
Vol 11 (12) ◽  
pp. 17757-17860 ◽  
Author(s):  
E. S. Weng ◽  
S. Malyshev ◽  
J. W. Lichstein ◽  
C. E. Farrior ◽  
R. Dybzinski ◽  
...  

Abstract. The long-term and large scale dynamics of ecosystems are in large part determined by the performances of individual plants in competition with one another for light, water and nutrients. Woody biomass, a pool of carbon (C) larger than 50% of atmospheric CO2, exists because of height-structured competition for light. However, most of the current Earth System Models that predict climate change and C cycle feedbacks lack both a mechanistic formulation for height-structured competition for light and an explicit scaling from individual plants to the globe. In this study, we incorporate height-structured competition and explicit scaling from individuals to ecosystems into the land model (LM3) currently used in the Earth System Models developed by the Geophysical Fluid Dynamics Laboratory (GFDL). The height-structured formulation is based on the Perfect Plasticity Approximation (PPA), which has been shown to accurately scale from individual-level plant competition for light, water and nutrients to the dynamics of whole communities. Because of the tractability of the PPA, the coupled LM3–PPA model is able to include a large number of phenomena across a range of spatial and temporal scales, and still retain computational tractability, as well as close linkages to mathematically tractable forms of the model. We test a range of predictions against data from temperate broadleaved forests in the northern USA. The results show the model predictions agree with diurnal and annual C fluxes, growth rates of individual trees in the canopy and understory, tree size distributions, and species-level population dynamics during succession. We also show how the competitively optimal allocation strategy – the strategy that can competitively exclude all others – shifts as a function of the atmospheric CO2 concentration. This strategy is referred as an evolutionary stable strategy (ESS) in the ecological literature and is typically not the same as a productivity- or growth-maximizing strategy. Model simulations predict that C sinks caused by CO2 fertilization in forests limited by light and water will be down-regulated if allocation tracks changes in the competitive optimum. The implementation of the model in this paper is for temperate broadleaved forest trees, but the formulation of the model is general. It can be expanded to include other growth forms and physiologies simply by altering parameter values.


2014 ◽  
Vol 27 (9) ◽  
pp. 3425-3445 ◽  
Author(s):  
Tomohiro Hajima ◽  
Kaoru Tachiiri ◽  
Akihiko Ito ◽  
Michio Kawamiya

Abstract 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.


2014 ◽  
Vol 27 (2) ◽  
pp. 511-526 ◽  
Author(s):  
Pierre Friedlingstein ◽  
Malte Meinshausen ◽  
Vivek K. Arora ◽  
Chris D. Jones ◽  
Alessandro Anav ◽  
...  

Abstract In the context of phase 5 of the Coupled Model Intercomparison Project, most climate simulations use prescribed atmospheric CO2 concentration and therefore do not interactively include the effect of carbon cycle feedbacks. However, the representative concentration pathway 8.5 (RCP8.5) scenario has additionally been run by earth system models with prescribed CO2 emissions. This paper analyzes the climate projections of 11 earth system models (ESMs) that performed both emission-driven and concentration-driven RCP8.5 simulations. When forced by RCP8.5 CO2 emissions, models simulate a large spread in atmospheric CO2; the simulated 2100 concentrations range between 795 and 1145 ppm. Seven out of the 11 ESMs simulate a larger CO2 (on average by 44 ppm, 985 ± 97 ppm by 2100) and hence higher radiative forcing (by 0.25 W m−2) when driven by CO2 emissions than for the concentration-driven scenarios (941 ppm). However, most of these models already overestimate the present-day CO2, with the present-day biases reasonably well correlated with future atmospheric concentrations’ departure from the prescribed concentration. The uncertainty in CO2 projections is mainly attributable to uncertainties in the response of the land carbon cycle. As a result of simulated higher CO2 concentrations than in the concentration-driven simulations, temperature projections are generally higher when ESMs are driven with CO2 emissions. Global surface temperature change by 2100 (relative to present day) increased by 3.9° ± 0.9°C for the emission-driven simulations compared to 3.7° ± 0.7°C in the concentration-driven simulations. Although the lower ends are comparable in both sets of simulations, the highest climate projections are significantly warmer in the emission-driven simulations because of stronger carbon cycle feedbacks.


2011 ◽  
Vol 6 ◽  
pp. 216-221
Author(s):  
Sönke Zaehle ◽  
Colin Prentice ◽  
Sarah Cornell

2015 ◽  
Vol 8 (4) ◽  
pp. 3235-3292 ◽  
Author(s):  
A. L. Atchley ◽  
S. L. Painter ◽  
D. R. Harp ◽  
E. T. Coon ◽  
C. J. Wilson ◽  
...  

Abstract. Climate change is profoundly transforming the carbon-rich Arctic tundra landscape, potentially moving it from a carbon sink to a carbon source by increasing the thickness of soil that thaws on a seasonal basis. However, the modeling capability and precise parameterizations of the physical characteristics needed to estimate projected active layer thickness (ALT) are limited in Earth System Models (ESMs). In particular, discrepancies in spatial scale between field measurements and Earth System Models challenge validation and parameterization of hydrothermal models. A recently developed surface/subsurface model for permafrost thermal hydrology, the Advanced Terrestrial Simulator (ATS), is used in combination with field measurements to calibrate and identify fine scale controls of ALT in ice wedge polygon tundra in Barrow, Alaska. An iterative model refinement procedure that cycles between borehole temperature and snow cover measurements and simulations functions to evaluate and parameterize different model processes necessary to simulate freeze/thaw processes and ALT formation. After model refinement and calibration, reasonable matches between simulated and measured soil temperatures are obtained, with the largest errors occurring during early summer above ice wedges (e.g. troughs). The results suggest that properly constructed and calibrated one-dimensional thermal hydrology models have the potential to provide reasonable representation of the subsurface thermal response and can be used to infer model input parameters and process representations. The models for soil thermal conductivity and snow distribution were found to be the most sensitive process representations. However, information on lateral flow and snowpack evolution might be needed to constrain model representations of surface hydrology and snow depth.


Climate ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 72
Author(s):  
Xing Yi ◽  
Birgit Hünicke ◽  
Eduardo Zorita

Arabian Sea upwelling in the past has been generally studied based on the sediment records. We apply two earth system models and analyze the simulated water vertical velocity to investigate coastal upwelling in the western Arabian Sea over the last millennium. In addition, two models with slightly different configurations are also employed to study the upwelling in the 21st century under the strongest and the weakest greenhouse gas emission scenarios. With a negative long-term trend caused by the orbital forcing of the models, the upwelling over the last millennium is found to be closely correlated with the sea surface temperature, the Indian summer Monsoon and the sediment records. The future upwelling under the Representative Concentration Pathway (RCP) 8.5 scenario reveals a negative trend, in contrast with the positive trend displayed by the upwelling favorable along-shore winds. Therefore, it is likely that other factors, like water stratification in the upper ocean layers caused by the stronger surface warming, overrides the effect from the upwelling favorable wind. No significant trend is found for the upwelling under the RCP2.6 scenario, which is likely due to a compensation between the opposing effects of the increase in upwelling favorable winds and the water stratification.


2012 ◽  
Vol 25 (19) ◽  
pp. 6646-6665 ◽  
Author(s):  
John P. Dunne ◽  
Jasmin G. John ◽  
Alistair J. Adcroft ◽  
Stephen M. Griffies ◽  
Robert W. Hallberg ◽  
...  

Abstract The physical climate formulation and simulation characteristics of two new global coupled carbon–climate Earth System Models, ESM2M and ESM2G, are described. These models demonstrate similar climate fidelity as the Geophysical Fluid Dynamics Laboratory’s previous Climate Model version 2.1 (CM2.1) while incorporating explicit and consistent carbon dynamics. The two models differ exclusively in the physical ocean component; ESM2M uses Modular Ocean Model version 4p1 with vertical pressure layers while ESM2G uses Generalized Ocean Layer Dynamics with a bulk mixed layer and interior isopycnal layers. Differences in the ocean mean state include the thermocline depth being relatively deep in ESM2M and relatively shallow in ESM2G compared to observations. The crucial role of ocean dynamics on climate variability is highlighted in El Niño–Southern Oscillation being overly strong in ESM2M and overly weak in ESM2G relative to observations. Thus, while ESM2G might better represent climate changes relating to total heat content variability given its lack of long-term drift, gyre circulation, and ventilation in the North Pacific, tropical Atlantic, and Indian Oceans, and depth structure in the overturning and abyssal flows, ESM2M might better represent climate changes relating to surface circulation given its superior surface temperature, salinity, and height patterns, tropical Pacific circulation and variability, and Southern Ocean dynamics. The overall assessment is that neither model is fundamentally superior to the other, and that both models achieve sufficient fidelity to allow meaningful climate and earth system modeling applications. This affords the ability to assess the role of ocean configuration on earth system interactions in the context of two state-of-the-art coupled carbon–climate models.


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