scholarly journals The influence of vegetation dynamics on anthropogenic climate change

2012 ◽  
Vol 3 (2) ◽  
pp. 233-243 ◽  
Author(s):  
U. Port ◽  
V. Brovkin ◽  
M. Claussen
Keyword(s):  
Climate Change ◽  
Vegetation Cover ◽  
Vegetation Dynamics ◽  
Global Climate ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Tree Cover ◽  
Earth System ◽  
Atmospheric Co2 Concentration ◽  
Global Mean

Abstract. In this study, vegetation–climate and vegetation–carbon cycle interactions during anthropogenic climate change are assessed by using the Earth System Model of the Max Planck Institute for Meteorology (MPI ESM) that includes vegetation dynamics and an interactive carbon cycle. We assume anthropogenic CO2 emissions according to the RCP 8.5 scenario in the time period from 1850 to 2120. For the time after 2120, we assume zero emissions to evaluate the response of the stabilising Earth System by 2300. Our results suggest that vegetation dynamics have a considerable influence on the changing global and regional climate. In the simulations, global mean tree cover extends by 2300 due to increased atmospheric CO2 concentration and global warming. Thus, land carbon uptake is higher and atmospheric CO2 concentration is lower by about 40 ppm when considering dynamic vegetation compared to the static pre-industrial vegetation cover. The reduced atmospheric CO2 concentration is equivalent to a lower global mean temperature. Moreover, biogeophysical effects of vegetation cover shifts influence the climate on a regional scale. Expanded tree cover in the northern high latitudes results in a reduced albedo and additional warming. In the Amazon region, declined tree cover causes a regional warming due to reduced evapotranspiration. As a net effect, vegetation dynamics have a slight attenuating effect on global climate change as the global climate cools by 0.22 K due to natural vegetation cover shifts in 2300.

scholarly journals The influence of vegetation dynamics on anthropogenic climate change

2012 ◽  
Vol 3 (2) ◽  
pp. 485-522 ◽  
Author(s):  
U. Port ◽  
V. Brovkin ◽  
M. Claussen
Keyword(s):  
Climate Change ◽  
Vegetation Cover ◽  
Vegetation Dynamics ◽  
Global Climate ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Tree Cover ◽  
Atmospheric Co2 Concentration ◽  
The Earth ◽  
Global Mean

Abstract. In this study, vegetation-climate and vegetation-carbon cycle interactions during anthropogenic climate change are assessed by using the Earth System Model MPI ESM including a module for vegetation dynamics. We assume anthropogenic CO2 emissions according to the RCP 8.5 scenario in the period from 1850 to 2120 and shut them down afterwards to evaluate the equilibrium response of the Earth System by 2300. Our results suggest that vegetation dynamics have a considerable influence on the changing global and regional climate. In the simulations, global mean tree cover extends by 2300 due to increased atmospheric CO2 concentration and global warming. Thus, land carbon uptake is higher and atmospheric CO2 concentration is lower by about 40 ppm when considering dynamic vegetation compared to a static pre-industrial vegetation cover. The reduced atmospheric CO2 concentration is equivalent to a lower global mean temperature. Moreover, biogeophysical effects of vegetation cover shifts influence the climate on a regional scale. Expanded tree cover in the northern high latitudes results in a reduced albedo and additional warming. In the Amazon region, declined tree cover causes a higher temperature as evapotranspiration is reduced. In total, we find that vegetation dynamics have a slight attenuating effect on global climate change as the global climate cools by 0.22 K in 2300 due to natural vegetation cover shifts.

scholarly journals Response of simulated burned area to historical changes in environmental and anthropogenic factors: a comparison of seven fire models

2019 ◽  
Vol 16 (19) ◽  
pp. 3883-3910 ◽  
Author(s):  
Lina Teckentrup ◽  
Sandy P. Harrison ◽  
Stijn Hantson ◽  
Angelika Heil ◽  
Joe R. Melton ◽  
...  
Keyword(s):  
Land Use ◽  
Co2 Concentration ◽  
Fire Regimes ◽  
Atmospheric Co2 ◽  
Anthropogenic Factors ◽  
Burned Area ◽  
Earth System ◽  
Atmospheric Co2 Concentration ◽  
Fire Models ◽  
The Impact

Abstract. Understanding how fire regimes change over time is of major importance for understanding their future impact on the Earth system, including society. Large differences in simulated burned area between fire models show that there is substantial uncertainty associated with modelling global change impacts on fire regimes. We draw here on sensitivity simulations made by seven global dynamic vegetation models participating in the Fire Model Intercomparison Project (FireMIP) to understand how differences in models translate into differences in fire regime projections. The sensitivity experiments isolate the impact of the individual drivers on simulated burned area, which are prescribed in the simulations. Specifically these drivers are atmospheric CO2 concentration, population density, land-use change, lightning and climate. The seven models capture spatial patterns in burned area. However, they show considerable differences in the burned area trends since 1921. We analyse the trajectories of differences between the sensitivity and reference simulation to improve our understanding of what drives the global trends in burned area. Where it is possible, we link the inter-model differences to model assumptions. Overall, these analyses reveal that the largest uncertainties in simulating global historical burned area are related to the representation of anthropogenic ignitions and suppression and effects of land use on vegetation and fire. In line with previous studies this highlights the need to improve our understanding and model representation of the relationship between human activities and fire to improve our abilities to model fire within Earth system model applications. Only two models show a strong response to atmospheric CO2 concentration. The effects of changes in atmospheric CO2 concentration on fire are complex and quantitative information of how fuel loads and how flammability changes due to this factor is missing. The response to lightning on global scale is low. The response of burned area to climate is spatially heterogeneous and has a strong inter-annual variation. Climate is therefore likely more important than the other factors for short-term variations and extremes in burned area. This study provides a basis to understand the uncertainties in global fire modelling. Both improvements in process understanding and observational constraints reduce uncertainties in modelling burned area trends.

Responses of woody Cerrado species to rising atmospheric CO2 concentration and water stress: gains and losses

2016 ◽  
Vol 43 (12) ◽  
pp. 1183 ◽  
Author(s):  
João Paulo Souza ◽  
Nayara M. J. Melo ◽  
Eduardo G. Pereira ◽  
Alessandro D. Halfeld ◽  
Ingrid N. Gomes ◽  
...  
Keyword(s):  
Water Stress ◽  
Elevated Co2 ◽  
Global Climate ◽  
Net Photosynthesis ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Ecosystem Functions ◽  
Total Biomass ◽  
High Co2 ◽  
Atmospheric Co2 Concentration

The rise in atmospheric CO2 concentration ([CO2]) has been accompanied by changes in other environmental factors of global climate change, such as drought. Tracking the early growth of plants under changing conditions can determine their ecophysiological adjustments and the consequences for ecosystem functions. This study investigated long-term ecophysiological responses in three woody Cerrado species: Hymenaea stigonocarpa Mart. ex Hayne, Solanum lycocarpum A. St.-Hil. and Tabebuia aurea (Silva Manso) Benth. and Hook. f. ex S. Moore, grown under ambient and elevated [CO2]. Plants were grown for 515 days at ambient (430 mg dm–3) or elevated [CO2] (700 mg dm–3). Some plants were also subjected to water stress to investigate the synergy between atmospheric [CO2] and soil water availability, and its effect on plant growth. All three species showed an increase in maximum net photosynthesis (PN) and chlorophyll index under high [CO2]. Transpiration decreased in some species under high [CO2] despite daily watering and a corresponding increase in water use efficiency was observed. Plants grown under elevated [CO2] and watered daily had greater leaf area and total biomass production than plants under water stress and ambient [CO2]. The high chlorophyll and PN in cerrado plants grown under elevated [CO2] are an investment in light use and capture and higher Rubisco carboxylation rate, respectively. The elevated [CO2] had a positive influence on biomass accumulation in the cerrado species we studied, as predicted for plants under high [CO2]. So, even with water stress, Cerrado species under elevated [CO2] had better growth.

scholarly journals Limitations of the 1 % experiment as the benchmark idealized experiment for carbon cycle intercomparison in C<sup>4</sup>MIP

2019 ◽  
Vol 12 (2) ◽  
pp. 597-611 ◽  
Author(s):  
Andrew Hugh MacDougall
Keyword(s):  
Climate Change ◽  
Carbon Cycle ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Smooth Transition ◽  
Model Intercomparison ◽  
Carbon Cycle Model ◽  
Atmospheric Co2 Concentration ◽  
Benchmark Experiment ◽  
Intercomparison Project

Abstract. Idealized climate change simulations are used as benchmark experiments to facilitate the comparison of ensembles of climate models. In the fifth phase of the Coupled Model Intercomparison Project (CMIP5), the 1 % per yearly compounded change in atmospheric CO2 concentration experiment was used to compare Earth system models with full representations of the global carbon cycle in the Coupled Climate–Carbon Cycle Model Intercomparison Project (C4MIP). However, this “1 % experiment” was never intended for such a purpose and implies a rise in atmospheric CO2 concentration at double the rate of the instrumental record. Here, we examine this choice by using an intermediate complexity climate model to compare the 1 % experiment to an idealized CO2 pathway derived from a logistic function. The comparison shows three key differences in model output when forcing the model with the logistic experiment. (1) The model forced with the logistic experiment exhibits a transition of the land biosphere from a carbon sink to a carbon source, a feature absent when forcing the model with the 1 % experiment. (2) The ocean uptake of carbon comes to dominate the carbon cycle as emissions decline, a feature that cannot be captured when forcing a model with the 1 % experiment, as emissions always increase in that experiment. (3) The permafrost carbon feedback to climate change under the 1 % experiment forcing is less than half the strength of the feedback seen under logistic experiment forcing. Using the logistic experiment also allows smooth transition to zero or negative emissions states, allowing these states to be examined without sharp discontinuities in CO2 emissions. The protocol for the CMIP6 iteration of C4MIP again sets the 1 % experiment as the benchmark experiment for model intercomparison; however, clever use of the Tier 2 experiments may alleviate some of the limitations outlined here. Given the limitations of the 1 % experiment as the benchmark experiment for carbon cycle intercomparisons, adding a logistic or similar idealized experiment to the protocol of the CMIP7 iteration of C4MIP is recommended.

scholarly journals A model-based constraint of CO<sub>2</sub> fertilisation

2012 ◽  
Vol 9 (7) ◽  
pp. 9425-9451 ◽  
Author(s):  
P. B. Holden ◽  
N. R. Edwards ◽  
D. Gerten ◽  
S. Schaphoff
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Co2 Concentration ◽  
Earth System Model ◽  
Atmospheric Co2 ◽  
System Model ◽  
Model Parameters ◽  
Earth System ◽  
Atmospheric Co2 Concentration ◽  
Post Industrial

Abstract. We derive a constraint on the strength of CO2 fertilisation of the terrestrial biosphere through a "top-down" approach, calibrating Earth System Model parameters constrained only by the post-industrial increase of atmospheric CO2 concentration. We derive a probabilistic prediction for the globally averaged strength of CO2 fertilisation in nature, implicitly net of other limiting factors such as nutrient availability. The approach yields an estimate that is independent of CO2 enrichment experiments and so provides a new constraint that can in principal be combined with data-driven priors. To achieve this, an essential requirement was the incorporation of a Land Use Change (LUC) scheme into the GENIE earth system model, which we describe in full. Using output from a 671-member ensemble of transient GENIE simulations we build an emulator of the change in atmospheric CO2 concentration change over the preindustrial period (1850 to 2000). We use this emulator to sample the 28-dimensional input parameter space. A Bayesian calibration of the emulator output suggests that the increase in Gross Primary Productivity in response of a doubling of CO2 from preindustrial values is likely to lie in the range 11 to 53%, with a most likely value of 28%. The present-day land-atmosphere flux (1990–2000) is estimated at −0.6 GTC yr−1 (likely in the range 0.9 to −2.0 GTC yr−1). The present-day land-ocean flux (1990–2000) is estimated at −2.2 GTC yr−1 (likely in the range −1.6 to −2.8 GTC yr−1). We estimate cumulative net land emissions over the post-industrial period (land use change emissions net of the CO2 fertilisation sink) to be 37 GTC, likely to lie in the range 130 to −20 GTC.

scholarly journals Climate, ocean circulation, and sea level changes under stabilization and overshoot pathways to 1.5 K warming

2018 ◽  
Vol 9 (2) ◽  
pp. 817-828 ◽  
Author(s):  
Jaime B. Palter ◽  
Thomas L. Frölicher ◽  
David Paynter ◽  
Jasmin G. John
Keyword(s):  
Sea Ice ◽  
Sea Level Rise ◽  
Sea Level ◽  
Ocean Circulation ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Carbon Removal ◽  
Surface Warming ◽  
Atmospheric Co2 Concentration ◽  
Global Mean

Abstract. The Paris Agreement has initiated a scientific debate on the role that carbon removal – or net negative emissions – might play in achieving less than 1.5 K of global mean surface warming by 2100. Here, we probe the sensitivity of a comprehensive Earth system model (GFDL-ESM2M) to three different atmospheric CO2 concentration pathways, two of which arrive at 1.5 K of warming in 2100 by very different pathways. We run five ensemble members of each of these simulations: (1) a standard Representative Concentration Pathway (RCP4.5) scenario, which produces 2 K of surface warming by 2100 in our model; (2) a “stabilization” pathway in which atmospheric CO2 concentration never exceeds 440 ppm and the global mean temperature rise is approximately 1.5 K by 2100; and (3) an “overshoot” pathway that passes through 2 K of warming at mid-century, before ramping down atmospheric CO2 concentrations, as if using carbon removal, to end at 1.5 K of warming at 2100. Although the global mean surface temperature change in response to the overshoot pathway is similar to the stabilization pathway in 2100, this similarity belies several important differences in other climate metrics, such as warming over land masses, the strength of the Atlantic Meridional Overturning Circulation (AMOC), ocean acidification, sea ice coverage, and the global mean sea level change and its regional expressions. In 2100, the overshoot ensemble shows a greater global steric sea level rise and weaker AMOC mass transport than in the stabilization scenario, with both of these metrics close to the ensemble mean of RCP4.5. There is strong ocean surface cooling in the North Atlantic Ocean and Southern Ocean in response to overshoot forcing due to perturbations in the ocean circulation. Thus, overshoot forcing in this model reduces the rate of sea ice loss in the Labrador, Nordic, Ross, and Weddell seas relative to the stabilized pathway, suggesting a negative radiative feedback in response to the early rapid warming. Finally, the ocean perturbation in response to warming leads to strong pathway dependence of sea level rise in northern North American cities, with overshoot forcing producing up to 10 cm of additional sea level rise by 2100 relative to stabilization forcing.

GFDL's CM2 Global Coupled Climate Models. Part IV: Idealized Climate Response

2006 ◽  
Vol 19 (5) ◽  
pp. 723-740 ◽  
Author(s):  
R. J. Stouffer ◽  
A. J. Broccoli ◽  
T. L. Delworth ◽  
K. W. Dixon ◽  
R. Gudgel ◽  
...  
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Climate Models ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Climate Response ◽  
Atmospheric Co2 Concentration ◽  
Group I

Abstract The climate response to idealized changes in the atmospheric CO2 concentration by the new GFDL climate model (CM2) is documented. This new model is very different from earlier GFDL models in its parameterizations of subgrid-scale physical processes, numerical algorithms, and resolution. The model was constructed to be useful for both seasonal-to-interannual predictions and climate change research. Unlike previous versions of the global coupled GFDL climate models, CM2 does not use flux adjustments to maintain a stable control climate. Results from two model versions, Climate Model versions 2.0 (CM2.0) and 2.1 (CM2.1), are presented. Two atmosphere–mixed layer ocean or slab models, Slab Model versions 2.0 (SM2.0) and 2.1 (SM2.1), are constructed corresponding to CM2.0 and CM2.1. Using the SM2 models to estimate the climate sensitivity, it is found that the equilibrium globally averaged surface air temperature increases 2.9 (SM2.0) and 3.4 K (SM2.1) for a doubling of the atmospheric CO2 concentration. When forced by a 1% per year CO2 increase, the surface air temperature difference around the time of CO2 doubling [transient climate response (TCR)] is about 1.6 K for both coupled model versions (CM2.0 and CM2.1). The simulated warming is near the median of the responses documented for the climate models used in the 2001 Intergovernmental Panel on Climate Change (IPCC) Working Group I Third Assessment Report (TAR). The thermohaline circulation (THC) weakened in response to increasing atmospheric CO2. By the time of CO2 doubling, the weakening in CM2.1 is larger than that found in CM2.0: 7 and 4 Sv (1 Sv ≡ 106 m3 s−1), respectively. However, the THC in the control integration of CM2.1 is stronger than in CM2.0, so that the percentage change in the THC between the two versions is more similar. The average THC change for the models presented in the TAR is about 3 or 4 Sv; however, the range across the model results is very large, varying from a slight increase (+2 Sv) to a large decrease (−10 Sv).

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