Climate–Carbon Cycle Feedback Analysis: Results from the C4MIP Model Intercomparison

Abstract Eleven coupled climate–carbon cycle models used a common protocol to study the coupling between climate change and the carbon cycle. The models were forced by historical emissions and the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2 anthropogenic emissions of CO2 for the 1850–2100 time period. For each model, two simulations were performed in order to isolate the impact of climate change on the land and ocean carbon cycle, and therefore the climate feedback on the atmospheric CO2 concentration growth rate. There was unanimous agreement among the models that future climate change will reduce the efficiency of the earth system to absorb the anthropogenic carbon perturbation. A larger fraction of anthropogenic CO2 will stay airborne if climate change is accounted for. By the end of the twenty-first century, this additional CO2 varied between 20 and 200 ppm for the two extreme models, the majority of the models lying between 50 and 100 ppm. The higher CO2 levels led to an additional climate warming ranging between 0.1° and 1.5°C. All models simulated a negative sensitivity for both the land and the ocean carbon cycle to future climate. However, there was still a large uncertainty on the magnitude of these sensitivities. Eight models attributed most of the changes to the land, while three attributed it to the ocean. Also, a majority of the models located the reduction of land carbon uptake in the Tropics. However, the attribution of the land sensitivity to changes in net primary productivity versus changes in respiration is still subject to debate; no consensus emerged among the models.

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The Impact of Climate Change and Feedback Processes on the Ocean Carbon Cycle

Ocean Biogeochemistry ◽

10.1007/978-3-642-55844-3_8 ◽

2003 ◽

pp. 157-193 ◽

Cited By ~ 32

Author(s):

Philip W. Boyd ◽

Scott C. Doney

Keyword(s):

Climate Change ◽

Carbon Cycle ◽

Ocean Carbon Cycle ◽

Impact Of Climate Change ◽

Ocean Carbon ◽

The Impact

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Assessing the impact of historical and future climate change on potential natural vegetation types and net primary productivity in Australian grazing lands

The Rangeland Journal ◽

10.1071/rj17081 ◽

2017 ◽

Vol 39 (4) ◽

pp. 387 ◽

Cited By ~ 3

Author(s):

Xiaoni Liu ◽

Baisen Zhang ◽

Beverley Henry ◽

Jinglan Zhang ◽

Peter Grace

Keyword(s):

Climate Change ◽

Primary Productivity ◽

Net Primary Productivity ◽

Carbon Sink ◽

Natural Vegetation ◽

Future Climate ◽

Future Climate Change ◽

Change Scenario ◽

Potential Natural Vegetation ◽

The Impact

The study investigated the impact of historical and future climate changes on potential natural vegetation (PNV) types and net primary productivity (NPP) in Australia, using the Comprehensive and Sequential Classification System model and the Miami model coupled with climate of the 1931–70 and 1971–2010 periods and the projected climate in 2050. Twenty-eight vegetation classes were classified based on the key climate indicators with four of them being the major vegetation classes corresponding to Australian rangelands and accounting for 75% of total land area. There was a substantial shift in areas of vegetation classes from the 1931–70 period to the 1971–2010 period due to the increased rainfall over large areas across Australia. The modelling projected a range of changes in vegetation classes for 2050 depending on the climate-change scenario used. Many vegetation classes with more intense land use (e.g. steppe and forest) were projected to decrease in 2050, which may have significant impact on the grazing industry and biodiversity conservation. By 2050, NPP was projected to increase in central and northern Australia and to decrease in southern and eastern coastal areas and was projected to be higher on average than that of the 1931–70 period. The vegetation classes approximately corresponding to Australian rangelands mostly had increased NPP projections compared with the 1931–70 period. Although actual response will partially depend on human management activities, fire and extreme events, the projected increase in average NPP in 2050 indicates that Australian vegetation, particularly the rangeland vegetation, will likely be a net carbon sink rather than a carbon source by 2050, with the exception of a ‘warm-dry’ scenario.

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Impacts of climate change on net primary productivity of grasslands in Inner Mongolia

The Rangeland Journal ◽

10.1071/rj14022 ◽

2014 ◽

Vol 36 (5) ◽

pp. 493 ◽

Cited By ~ 8

Author(s):

Qiuyue Li ◽

Debao Tuo ◽

Lizhen Zhang ◽

Xiaoyu Wei ◽

Yurong Wei ◽

...

Keyword(s):

Climate Change ◽

Primary Productivity ◽

Inner Mongolia ◽

Net Primary Productivity ◽

Emission Scenario ◽

Future Climate ◽

Future Climate Change ◽

Emission Scenarios ◽

The Impact ◽

A1b Scenario

Net primary productivity (NPP) of grasslands is a key variable for characterising carbon cycles in grassland ecosystems. The prediction of NPP in Inner Mongolia is important for adaptation to future climate change, food security and sustainable use of the grassland resources. The output from two models, potentially suitable for simulating NPP in response to climate change, was tested against observed aboveground forage mass of dry matter at eight sites in Inner Mongolia from 1995 to 2005. The Classification Indices-Based Model (CIBM) showed an acceptable agreement with field measurements. The impact of climate change on the NPP of grasslands was subsequently analysed by CIBM using future climate projections from a Global Circulation Model based on three greenhouse gas emission scenarios: A2 (medium-high emission), A1B (medium emission) and B2 (medium-low emission) differing in assumptions about patterns of global social and economic development. Generally, significant increases in NPP, compared with the baseline NPP of 3.6 tonnes ha–1 for 1961–90, were predicted. The magnitude of the increase in NPP depended on the emission scenario, as well as on the time frame and region considered. Overall the predicted NPP stimulation increased with the level of emissions assumed, being 4.8 tonnes ha–1 in the A2 scenario, 4.3 tonnes ha–1 in the B2 scenario and 4.5 tonnes ha–1 in the A1B scenario in the 2080s (2071–2100). The increase in NPP in response to climate change differed between regions and there was an interaction with emission scenario. For the A2 and the B2 emission scenarios, the western region of Inner Mongolia was predicted to exhibit the strongest NPP increases, but, under the A1B scenario for the 2050s, the south-eastern region exhibited the greatest increase in NPP. It is concluded that the productivity of grassland in Inner Mongolia is likely to increase in response to climate change but these predicted effects are sensitive to emission scenarios and differ regionally. This will provide opportunities but also challenges for herders and policy makers in adapting to this change.

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Dynamics of soil organic carbon in the steppes of Russia and Kazakhstan under past and future climate and land use

Regional Environmental Change ◽

10.1007/s10113-021-01799-7 ◽

2021 ◽

Vol 21 (3) ◽

Author(s):

Susanne Rolinski ◽

Alexander V. Prishchepov ◽

Georg Guggenberger ◽

Norbert Bischoff ◽

Irina Kurganova ◽

...

Keyword(s):

Climate Change ◽

Land Use ◽

Organic Carbon ◽

Land Use Change ◽

Soil Organic Carbon ◽

Arable Land ◽

Future Climate ◽

Future Climate Change ◽

Climate Scenarios ◽

The Impact

AbstractChanges in land use and climate are the main drivers of change in soil organic matter contents. We investigated the impact of the largest policy-induced land conversion to arable land, the Virgin Lands Campaign (VLC), from 1954 to 1963, of the massive cropland abandonment after 1990 and of climate change on soil organic carbon (SOC) stocks in steppes of Russia and Kazakhstan. We simulated carbon budgets from the pre-VLC period (1900) until 2100 using a dynamic vegetation model to assess the impacts of observed land-use change as well as future climate and land-use change scenarios. The simulations suggest for the entire VLC region (266 million hectares) that the historic cropland expansion resulted in emissions of 1.6⋅ 1015 g (= 1.6 Pg) carbon between 1950 and 1965 compared to 0.6 Pg in a scenario without the expansion. From 1990 to 2100, climate change alone is projected to cause emissions of about 1.8 (± 1.1) Pg carbon. Hypothetical recultivation of the cropland that has been abandoned after the fall of the Soviet Union until 2050 may cause emissions of 3.5 (± 0.9) Pg carbon until 2100, whereas the abandonment of all cropland until 2050 would lead to sequestration of 1.8 (± 1.2) Pg carbon. For the climate scenarios based on SRES (Special Report on Emission Scenarios) emission pathways, SOC declined only moderately for constant land use but substantially with further cropland expansion. The variation of SOC in response to the climate scenarios was smaller than that in response to the land-use scenarios. This suggests that the effects of land-use change on SOC dynamics may become as relevant as those of future climate change in the Eurasian steppes.

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Predicted Future Benefits for an Endemic Rodent in the Irano-Turanian Region

Climate ◽

10.3390/cli9010016 ◽

2021 ◽

Vol 9 (1) ◽

pp. 16

Author(s):

Suzanna Meeussen ◽

Anouschka Hof

Keyword(s):

Climate Change ◽

Climate Models ◽

Species Distribution Modelling ◽

Geographic Range ◽

Future Climate ◽

Future Climate Change ◽

Distribution Ranges ◽

Bioclimatic Variables ◽

Suitable Area ◽

The Impact

Climate change is expected to have an impact on the geographical distribution ranges of species. Endemic species and those with a restricted geographic range may be especially vulnerable. The Persian jird (Meriones persicus) is an endemic rodent inhabiting the mountainous areas of the Irano-Turanian region, where future desertification may form a threat to the species. In this study, the species distribution modelling algorithm MaxEnt was used to assess the impact of future climate change on the geographic distribution range of the Persian jird. Predictions were made under two Representative Concentration Pathways and five different climate models for the years 2050 and 2070. It was found that both bioclimatic variables and land use variables were important in determining potential suitability of the region for the species to occur. In most cases, the future predictions showed an expansion of the geographic range of the Persian jird which indicates that the species is not under immediate threat. There are however uncertainties with regards to its current range. Predictions may therefore be an over or underestimation of the total suitable area. Further research is thus needed to confirm the current geographic range of the Persian jird to be able to improve assessments of the impact of future climate change.

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Selection of models to describe the temperature-dependent development of Neoleucinodes elegantalis (Lepidoptera: Crambidae) and its application to predict the species voltinism under future climate conditions

Bulletin of Entomological Research ◽

10.1017/s0007485321000195 ◽

2021 ◽

pp. 1-9

Author(s):

Hevellyn Talissa dos Santos ◽

Cesar Augusto Marchioro

Keyword(s):

Climate Change ◽

Linear Model ◽

Future Climate ◽

Future Climate Change ◽

Climate Change Scenarios ◽

Temperature Dependent ◽

Dependent Development ◽

Degree Day ◽

Non Linear ◽

The Impact

Abstract The small tomato borer, Neoleucinodes elegantalis (Guenée, 1854) is a multivoltine pest of tomato and other cultivated solanaceous plants. The knowledge on how N. elegantalis respond to temperature may help in the development of pest management strategies, and in the understanding of the effects of climate change on its voltinism. In this context, this study aimed to select models to describe the temperature-dependent development rate of N. elegantalis and apply the best models to evaluate the impacts of climate change on pest voltinism. Voltinism was estimated with the best fit non-linear model and the degree-day approach using future climate change scenarios representing intermediary and high greenhouse gas emission rates. Two out of the six models assessed showed a good fit to the observed data and accurately estimated the thermal thresholds of N. elegantalis. The degree-day and the non-linear model estimated more generations in the warmer regions and fewer generations in the colder areas, but differences of up to 41% between models were recorded mainly in the warmer regions. In general, both models predicted an increase in the voltinism of N. elegantalis in most of the study area, and this increase was more pronounced in the scenarios with high emission of greenhouse gases. The mathematical model (74.8%) and the location (9.8%) were the factors that mostly contributed to the observed variation in pest voltinism. Our findings highlight the impact of climate change on the voltinism of N. elegantalis and indicate that an increase in its population growth is expected in most regions of the study area.

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Bayesian estimation of Earth's climate sensitivity and transient climate response from observational warming and heat content datasets

Earth System Dynamics ◽

10.5194/esd-12-709-2021 ◽

2021 ◽

Vol 12 (2) ◽

pp. 709-723

Author(s):

Philip Goodwin ◽

B. B. Cael

Keyword(s):

Climate Sensitivity ◽

Future Climate ◽

Climate Feedback ◽

Future Climate Change ◽

Climate Projections ◽

Climate Response ◽

Ocean Heat Uptake ◽

Transient Climate Response ◽

Posterior Probability Distribution ◽

The Impact

Abstract. Future climate change projections, impacts, and mitigation targets are directly affected by how sensitive Earth's global mean surface temperature is to anthropogenic forcing, expressed via the climate sensitivity (S) and transient climate response (TCR). However, the S and TCR are poorly constrained, in part because historic observations and future climate projections consider the climate system under different response timescales with potentially different climate feedback strengths. Here, we evaluate S and TCR by using historic observations of surface warming, available since the mid-19th century, and ocean heat uptake, available since the mid-20th century, to constrain a model with independent climate feedback components acting over multiple response timescales. Adopting a Bayesian approach, our prior uses a constrained distribution for the instantaneous Planck feedback combined with wide-ranging uniform distributions of the strengths of the fast feedbacks (acting over several days) and multi-decadal feedbacks. We extract posterior distributions by applying likelihood functions derived from different combinations of observational datasets. The resulting TCR distributions when using two preferred combinations of historic datasets both find a TCR of 1.5 (1.3 to 1.8 at 5–95 % range) ∘C. We find the posterior probability distribution for S for our preferred dataset combination evolves from S of 2.0 (1.6 to 2.5) ∘C on a 20-year response timescale to S of 2.3 (1.4 to 6.4) ∘C on a 140-year response timescale, due to the impact of multi-decadal feedbacks. Our results demonstrate how multi-decadal feedbacks allow a significantly higher upper bound on S than historic observations are otherwise consistent with.

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Simulation of future climate scenarios and the impact on the water availability in southern Brazil

Acta Scientiarum Technology ◽

10.4025/actascitechnol.v43i1.56026 ◽

2021 ◽

Vol 43 ◽

pp. e56026

Author(s):

Gabriela Leite Neves ◽

Jorim Sousa das Virgens Filho ◽

Maysa de Lima Leite ◽

Frederico Fabio Mauad

Keyword(s):

Climate Change ◽

Water Balance ◽

Water Availability ◽

Meteorological Data ◽

Future Climate ◽

Climate Scenarios ◽

Southern Brazil ◽

Climate Data ◽

Intergovernmental Panel ◽

The Impact

Water is an essential natural resource that is being impacted by climate change. Thus, knowledge of future water availability conditions around the globe becomes necessary. Based on that, this study aimed to simulate future climate scenarios and evaluate the impact on water balance in southern Brazil. Daily data of rainfall and air temperature (maximum and minimum) were used. The meteorological data were collected in 28 locations over 30 years (1980-2009). For the data simulation, we used the climate data stochastic generator PGECLIMA_R. It was considered two scenarios of the fifth report of the Intergovernmental Panel on Climate Change (IPCC) and a scenario with the historical data trend. The water balance estimates were performed for the current data and the simulated data, through the methodology of Thornthwaite and Mather (1955). The moisture indexes were spatialized by the kriging method. These indexes were chosen as the parameters to represent the water conditions in different situations. The region assessed presented a high variability in water availability among locations; however, it did not present high water deficiency values, even with climate change. Overall, it was observed a reduction of moisture index in most sites and in all scenarios assessed, especially in the northern region when compared to the other regions. The second scenario of the IPCC (the worst situation) promoting higher reductions and dry conditions for the 2099 year. The impacts of climate change on water availability, identified in this study, can affect the general society, therefore, they must be considered in the planning and management of water resources, especially in the regional context

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An evaluation of the effect of future climate on runoff in the Dongjiang River basin, South China

Proceedings of the International Association of Hydrological Sciences ◽

10.5194/piahs-368-257-2015 ◽

2015 ◽

Vol 368 ◽

pp. 257-262

Author(s):

K. Lin ◽

W. Zhai ◽

S. Huang ◽

Z. Liu

Keyword(s):

Climate Change ◽

River Basin ◽

South China ◽

Annual Runoff ◽

Future Climate ◽

Weather Data ◽

Future Climate Change ◽

Dongjiang River ◽

The Future ◽

The Impact

Abstract. The impact of future climate change on the runoff for the Dongjiang River basin, South China, has been investigated with the Soil and Water Assessment Tool (SWAT). First, the SWAT model was applied in the three sub-basins of the Dongjiang River basin, and calibrated for the period of 1970–1975, and validated for the period of 1976–1985. Then the hydrological response under climate change and land use scenario in the next 40 years (2011–2050) was studied. The future weather data was generated by using the weather generators of SWAT, based on the trend of the observed data series (1966–2005). The results showed that under the future climate change and LUCC scenario, the annual runoff of the three sub-basins all decreased. Its impacts on annual runoff were –6.87%, –6.54%, and –18.16% for the Shuntian, Lantang, and Yuecheng sub-basins respectively, compared with the baseline period 1966–2005. The results of this study could be a reference for regional water resources management since Dongjiang River provides crucial water supplies to Guangdong Province and the District of Hong Kong in China.

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