Doubled CO2 Research Articles

New insights into the spatial variability of microbial diversity and density in peatlands exposed to various electron acceptors with an emphasis on methanogenesis and CO2 fluxes.

Peatlands are vital in the global carbon cycle, acting as significant sinks for carbon and releasing methane (CH4) and carbon dioxide (CO2) into the atmosphere. However, the complex interactions between environmental factors and the microbial communities responsible for these greenhouse gas emissions remain insufficiently understood. To address this knowledge gap, a pilot-scale mesocosm study was conducted to assess the impact of different terminal electron acceptors (TEAs), including sulfate (SO4 2-), humic acid (HA), and goethite, on CH4 and CO2 emissions and microbial community structures in peatlands. Our results revealed that the addition of TEAs significantly altered the CH4 and CO2 emissions. Specifically, the addition of SO4 2- nearly doubled CO2 production while substantially inhibiting CH4 emissions. The combined addition of SO4 2- and HA, as well as HA alone, followed a similar pattern, albeit with less pronounced effects on CH4. Goethite addition resulted in the highest inhibition of CH4 among all treatments but did not significantly increase CO2 production. Community composition and network analysis indicated that TEAs primarily determined the structure of microbial communities, with each treatment exhibiting distinct taxa networks. Proteobacteria, Acidobacteria, Chloroflexi, and Bacteroidetes were the most abundant phyla across all mesocosms. The presence of methanotrophs, including Methylomirabilales and Methylococcales, was linked to the inhibition of CH4 emissions in these mesocosms. This study provides novel insights into the spatial variability of microbial diversity and density in peatlands under various TEAs, emphasizing the role of methanogenesis and CO2 fluxes in carbon cycling. Our findings enhance the understanding of carbon cycling in microbe-rich environments exposed to TEAs and highlight the potential for future studies to investigate the long-term effects of TEAs on microbial communities, enzymes, and carbon storage.

Network-based constraint to evaluate climate sensitivity

The 2015 Paris agreement was established to limit Greenhouse gas (GHG) global warming below 1.5°C above preindustrial era values. Knowledge of climate sensitivity to GHG levels is central for formulating effective climate policies, yet its exact value is shroud in uncertainty. Climate sensitivity is quantitatively expressed in terms of Equilibrium Climate Sensitivity (ECS) and Transient Climate Response (TCR), estimating global temperature responses after an abrupt or transient doubling of CO2. Here, we represent the complex and highly-dimensional behavior of modelled climate via low-dimensional emergent networks to evaluate Climate Sensitivity (netCS), by first reconstructing meaningful components describing regional subprocesses, and secondly inferring the causal links between these to construct causal networks. We apply this methodology to Sea Surface Temperature (SST) simulations and investigate two different metrics in order to derive weighted estimates that yield likely ranges of ECS (2.35–4.81°C) and TCR (1.53-2.60°C). These ranges are narrower than the unconstrained distributions and consistent with the ranges of the IPCC AR6 estimates. More importantly, netCS demonstrates that SST patterns (at “fast” timescales) are linked to climate sensitivity; SST patterns over the historical period exclude median sensitivity but not low-sensitivity (ECS < 3.0°C) or very high sensitivity (ECS ≥ 4.5°C) models.

Role of the Antarctic Circumpolar Circulation in Current Asymmetric Arctic and Antarctic Warming

AbstractBoth historical observations and recent modeling studies reveal a faster warming in the Arctic compared to the Antarctic. To understand the role of the Antarctic Circumpolar Circulation (ACC) in this warming asymmetry, we simulate the climate mean state and climate response to doubled CO2 under different climate mean ACC states by closing or opening the Drake Passage (DP) with the Community Earth System Model. From closed to open DP, a stronger climate mean ACC leads to a stronger climate mean Atlantic Meridional Overturning Circulation (AMOC), as well as a colder Antarctic but a warmer Arctic in the climate mean state. The less climate mean sea ice coverage in a warmer Arctic implies less extensive sea ice melting under global warming. This causes a reduced asymmetry in warming between the two poles in response to the doubled CO2.

Estimates of late Early Cretaceous atmospheric CO2 from Mongolia based on stomatal and isotopic analysis of Pseudotorellia.

The Aptian-Albian (121.4-100.5 Ma) was a greenhouse period with global temperatures estimated as 10-15°C warmer than pre-industrial conditions, so it is surprising that the most reliable CO2 estimates from this time are <1400 ppm. This low CO2 during a warm period implies a very high Earth-system sensitivity in the range of 6 to 9°C per CO2 doubling between the Aptian-Albian and today. We applied a well-vetted paleo-CO2 proxy based on leaf gas-exchange principles (Franks model) to two Pseudotorellia species from three stratigraphically similar samples at the Tevshiin Govi lignite mine in central Mongolia (~119.7-100.5 Ma). Our median estimated CO2 concentration from the three respective samples was 2132, 2405, and 2770 ppm. The primary reason for the high estimated CO2 but with relatively large uncertainties is the very low stomatal density in both species, where small variations propagate to large changes in estimated CO2. Indeed, we found that at least 15 leaves are required before the aggregate estimated CO2 approaches that of the full data set. Our three CO2 estimates all exceeded 2000 ppm, translating to an Earth-system sensitivity (~3-5°C/CO2 doubling) that is more in keeping with the current understanding of the long-term climate system. Because of our large sample size, the directly measured inputs did not contribute much to the overall uncertainty in estimated CO2; instead, the inferred inputs were responsible for most of the overall uncertainty and thus should be scrutinized for their value choices.

Modeling climate change impacts under future CCM3 scenario on sorghum (Sorghum bicolor) as an drought resilient crop in tropical arid Lombok Island, Indonesia

Abstract. Wibowo AA, Meylani V. 2024. Modeling climate change impacts under future CCM3 scenario on sorghum (Sorghum bicolor) as an drought resilient crop in tropical arid Lombok Island, Indonesia. Intl J Trop Drylands 8: 35-43. The arid ecosystems and drought conditions exacerbated by climate change and rising CO2 levels necessitate the identification of alternative drought-tolerant crops. Sorghum bicolor L. has emerged as a promising option due to its resilience to drought. However, there is dearth of information regarding its future potential distribution, particularly in arid regions like Lombok Island, Indonesia, where sorghum is being considered as a viable alternative to ensure food security. This study employs Maximum Entropy (MaxEnt) modeling, incorporating environmental and bioclimatic variables, along with the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM3) scenario reflecting doubled CO2 levels, to model the future potential distribution of S. bicolor. The model projects a total suitable habitat area of 1,875 km2, constituting 39.56% of Lombok Island’s land area. Notably, very high-suitability areas of 175 km2, and high-suitability areas of 200 km2 encompass 3.69% and 4.22% of the island’s territory, respectively, predominantly concentrated in the southern region of the island and characterized by low precipitation and high temperatures, particularly at altitudes ranging from 0 to 1,000 meters. The model's performance, evaluated using the Area Under the Curve (AUC), yields a score of 0.725, indicating a good level of accuracy. Key factors influencing sorghum distribution include annual precipitation (68.69%), isothermality (9.56%), temperature seasonality (9.56%), precipitation seasonality (8.69%), and annual mean temperature (3.47%). The CCM3 model forecasts an expansion of sorghum distribution toward the north, occupying approximately 6.25% of Lombok's total area. These findings highlight sorghum’s adaptability and resilience to future climate changes, positioning it as a valuable resource for sustainable agriculture in arid environments.

Climate-induced reduction in metabolically suitable habitat for U.S. northeast shelf marine species

The U.S. northeast shelf (USNES) has been experiencing rapid ocean warming, which is changing the thermal environment that marine species inhabit. To determine the effect of current and future ocean warming on the distribution of five important USNES fish species (Atlantic cod [Gadus morhua], black sea bass [Centropristis striata], cunner [Tautogolabrus adspersus], spiny dogfish [Squalus acanthias], summer flounder [Paralichthys dentatus]), we applied species-specific physiological parameters from laboratory studies to calculate the Metabolic Index (MI). The MI for each species was calculated across a historical (1972–2019) and contemporary (2010–2019) climatology for each season. Broadly, the oceanic conditions in the winter and spring seasons did not limit metabolically suitable habitat for all five species, while portions of the USNES in the summer and fall seasons were metabolically unsuitable for the cold water species (Atlantic cod, cunner, spiny dogfish). The warmer water species (black sea bass, summer flounder) experienced little metabolically suitable habitat loss, which was restricted to the most southern portion of the distribution. Under a doubling of atmospheric CO2, metabolically suitable habitat is projected to decrease substantially for Atlantic cod, restricting them to the Gulf of Maine. Cunner are projected to experience similar habitat loss as Atlantic cod, with some refugia in the New York Bight, and spiny dogfish may experience habitat loss in the Southern Shelf and portions of Georges Bank. In contrast, black sea bass and summer flounder are projected to experience minimal habitat loss restricted to the southern inshore portion of the USNES. The utility of using MI for co-occurring fish species in the USNES differed, likely driven by species-specific physiology and whether the southern edge of a population occurred within the USNES.

Mid-Pliocene not analogous to high-CO2 climate when considering Northern Hemisphere winter variability

Abstract. In this study, we address the question of whether the mid-Pliocene climate can act as an analogue for a future warm climate with elevated CO2 concentrations, specifically regarding Northern Hemisphere winter variability. We use a set of sensitivity simulations with the global coupled climate model CESM1.0.5 (CCSM4-Utr), which is part of the PlioMIP2 model ensemble, to separate the response to a CO2 doubling and to mid-Pliocene boundary conditions other than CO2. In the CO2 doubling simulation, the Aleutian low deepens, and the Pacific–North American pattern (PNA) strengthens. In response to the mid-Pliocene boundary conditions, sea-level pressure variance decreases over the North Pacific, the PNA becomes weaker and the North Pacific Oscillation (NPO) becomes the dominant mode of variability. The mid-Pliocene simulation shows a weak North Pacific jet stream that is less variable in intensity but has a high level of variation in jet latitude, consistent with a dominant NPO and indicating that North Pacific atmospheric dynamics become more North Atlantic-like. We demonstrate that the weakening of the Aleutian low, and subsequent relative dominance of the NPO over the PNA, is related to shifts in tropical Pacific convection. Variability in the North Atlantic shows little variation between all simulations. The opposite response in North Pacific winter variability to elevated CO2 or mid-Pliocene boundary conditions demonstrates that the mid-Pliocene climate cannot serve as a future analogue in this regard.

Connectivity of floodplain influences riverine carbon outgassing and dissolved carbon transport

Rivers not only function as a conduit for the delivery of terrestrial constituents to oceans, but they also serve as an essential medium for biogeochemical processing of the constituents. While extensive research has been conducted on carbon transport in many rivers, little is known about carbon transformation in engineered rivers reconnected with their floodplain network. Being the largest distributary of the levee-confined Mississippi River (MR), the Atchafalaya River (AR) carries 25 % of the MR water, flowing through North America's largest freshwater swamp basin and emptying into the Gulf of Mexico. Previous studies reported that this 200-km long, 5–30-km wide river basin can remove a substantial amount of riverine nutrients and organic carbon. This study aimed to test the hypothesis that the AR emits significantly higher CO2 into the atmosphere as it flows through its extensive floodplain network than the levee-confined MR does. From January 2019 to December 2021, we conducted biweekly – monthly in-situ measurements in the lower AR at Morgan City and in the lower Mississippi River at Baton Rouge. Field measurements included partial pressure of dissolved CO2 (pCO2), water temperature, chlorophyll a, colored dissolved organic matter, dissolved oxygen, pH, and turbidity. During each field sampling, water samples were collected and analyzed for concentrations of dissolved organic and inorganic carbon (DOC and DIC). Mass transport of DOC and DIC and outgassing of CO2 were quantified for the two rivers. We found that pCO2 levels were significantly higher in the AR (mean: 3563 μatm; min-max: 1130–8650 μatm) than those in the MR (1931 μatm, 836–3501 μatm), resulting in a doubled CO2 outgassing rate in the AR (486 mmol m2 d−1) than in the MR (241 mmol m2 d−1). The AR had higher DOC (8.5 mg L−1) but lower chlorophyll a (153.9 AFU) when compared with the MR (7.5 mg L−1 and 164.0 AFU). Water temperature was constantly higher in the AR than in the MR, especially during the wintertime. Since the Mississippi-Atchafalaya River system is among the world's largest and most engineered river systems, our assessment offers a field case study to inform on the potential implications of reconnecting rivers with their floodplains networks.

Sensitivity of the WRF-Chem v4.4 simulations of ozone and formaldehyde and their precursors to multiple bottom-up emission inventories over East Asia during the KORUS-AQ 2016 field campaign

Abstract. In this study, the WRF-Chem v4.4 model was utilized to evaluate the sensitivity of O3 simulations with three bottom-up emission inventories (EDGAR-HTAP v2 and v3 and KORUS v5) using surface and aircraft data in East Asia during the Korea-United States Air Quality (KORUS-AQ) campaign period in 2016. All emission inventories were found to reproduce the diurnal variations of O3 and its main precursor NO2 as compared to the surface monitor data. However, the spatial distributions of the daily maximum 8 h average (MDA8) O3 in the model do not completely align with the observations. The model MDA8 O3 had a negative (positive) bias north (south) of 30° N over China. All simulations underestimated the observed CO by 50 %–60 % over China and South Korea. In the Seoul Metropolitan Area (SMA), EDGAR-HTAP v2 and v3 and KORUS v5 simulated the vertical shapes and diurnal patterns of O3 and other precursors effectively, but the model underestimated the observed O3, CO, and HCHO concentrations. Notably, the model aromatic volatile organic compounds (VOCs) were significantly underestimated with the three bottom-up emission inventories, although the KORUS v5 shows improvements. The model isoprene estimations had a positive bias relative to the observations, suggesting that the Model of Emissions of Gases and Aerosols from Nature (MEGAN) version 2.04 overestimated isoprene emissions. Additional model simulations were conducted by doubling CO and VOC emissions over China and South Korea to investigate the causes of the model O3 biases and the effects of the long-range transport on the O3 over South Korea. The doubled CO and VOC emission simulations improved the model O3 simulations for the local-emission-dominant case but led to the model O3 overestimations for the transport-dominant case, which emphasizes the need for accurate representations of the local VOC emissions over South Korea.

The Cause of Negative CO2 Forcing at the Top‐Of‐Atmosphere: The Role of Stratospheric Versus Tropospheric Temperature Inversions

AbstractIncreasing carbon dioxide (CO2) in the atmosphere usually reduces Earth's outgoing longwave radiation (OLR). The unusual case of Antarctica, where CO2 enhances OLR and implies a negative forcing, has previously been explained by the strong near‐surface inversion or extremely low surface temperature. However, negative forcing can occasionally be found in the Arctic and tropics where neither of these explanations applies. Here, we examine the changes in infrared opacity from CO2 doubling in these low or negative forcing climate states, which shows the predominant role of the stratospheric contribution to the broadband forcing. Negative forcing in today's climate demands a combination of strong negative forcing caused by a steep stratospheric temperature inversion and a weaker positive forcing in the atmospheric window, which can be caused by a low surface temperature or a strong high cloud masking effect. Contrary to conventional wisdom, the near‐surface inversion has little impact on the forcing.

Future changes in Antarctic coastal polynyas and bottom water formation simulated by a high-resolution coupled model

Antarctic coastal polynyas produce Dense Shelf Water, a precursor to Antarctic Bottom Waters that supply the global abyssal circulation. Future projections of Dense Shelf Water formation are hindered by unresolved small-scale atmosphere-sea ice-ocean interactions in polynyas. Here, we investigate the future evolution of Antarctic coastal polynyas using a high-resolution ocean-ice-atmosphere model. We find that wintertime sea ice production rates remain active even under elevated atmospheric CO2 concentrations. Antarctic winter sea ice production rates are sensitive to atmospheric CO2 concentrations: doubling CO2 (734 ppm) decreases sea ice production by only 6–8%, versus 10–30% under CO2 quadrupling (1468 ppm). While considerable uncertainty remains in future ice-shelf basal melting, which is not accounted for in this study, doubling or quadrupling CO2 substantially freshens Dense Shelf Water due to increased precipitation. Consequently, doubling CO2 weakens Dense Shelf Water formation by ~ 75%, while CO2 quadrupling shuts down Dense Shelf Water formation.

State dependence of CO2 forcing and its implications for climate sensitivity.

When evaluating the effect of carbon dioxide (CO2) changes on Earth's climate, it is widely assumed that instantaneous radiative forcing from a doubling of a given CO2 concentration (IRF2×CO2) is constant and that variances in climate sensitivity arise from differences in radiative feedbacks or dependence of these feedbacks on the climatological base state. Here, we show that the IRF2×CO2 is not constant, but rather depends on the climatological base state, increasing by about 25% for every doubling of CO2, and has increased by about 10% since the preindustrial era primarily due to the cooling within the upper stratosphere, implying a proportionate increase in climate sensitivity. This base-state dependence also explains about half of the intermodel spread in IRF2×CO2, a problem that has persisted among climate models for nearly three decades.

BIOCLIM Modeling for Predicting Suitable Habitat for Endangered Tree Tapiscia sinensis (Tapisciaceae) in China

Climate change jeopardizes species survival, particularly for endangered species. This risk extends to the endangered Chinese endemic tree Tapiscia sinensis. The factors underpinning T. sinensis’s habitat distribution are poorly understood, and its potential response to future climate scenarios remains unclear. With six shortlisted climate factors and 117 occurrence records, we modeled T. sinensis’s potential distribution across China using the BIOCLIM model. We applied principal component analysis to examine the primary climate factors restricting its geographical range. The findings indicate that T. sinensis’ range is principally located in China’s middle subtropical climatic zone at low–mid altitudes. The principal component analysis identified two critical factors representing temperature and precipitation. Temperature was the most critical factor limiting T. sinensis distribution, especially the effect of temperature seasonality and isothermality. The habitat suitability model generated by BIOCLIM under current climate conditions demonstrated strong concordance between the predicted suitable areas and the present actual distribution range. These results verify that the model can reliably identify habitats conducive to T. sinensis growth and survival. However, under a hypothetical future climate scenario of doubled atmospheric CO2 concentrations for 2100, the model indicates a precipitous reduction and fragmentation in the areas with excellent suitability conditions. This predicted decline highlights the considerable threats posed by climate change to the long-term survival of this endangered species in China. Our habitat modeling yields critical insights that inform the development of science-based strategies and best practices to improve conservation management plans for research, protection, nursery cultivation, and sustainable planting in China. Habitat suitability knowledge could aid introduction and cultivation efforts for T. sinensis globally in places with analogous climates.

Enhancing school buildings energy efficiency under climate change: A comprehensive analysis of energy, cost, and comfort factors

Incorporating future weather predictions into building assessments is essential for enhancing resilience, energy efficiency, cost savings, comfort, and sustainable infrastructure development in response to climate change. This study investigates the interplay between climate change and building performance, primarily focusing on energy usage, cost implications, and occupant comfort. It examines how future weather conditions impact school buildings in different climates, analyzing energy, cost, and comfort aspects. The research underscores the significance of tailored climate adaptation strategies for various regions and emphasizes considering future performance, even for highly energy-efficient buildings. Employing a comprehensive simulation-based approach, the study implements and validates future weather data in a Turkish school building, incorporating envelope improvements and photovoltaic applications to boost energy efficiency. A distinctive feature is the rigorous validation of future weather predictions against current measured data, facilitating a regional-level assessment of climate change effects on building energy consumption. The study's novelty lies in its detailed evaluation of climate change's multifaceted impacts on buildings, innovative future climate data validation, and contribution to a more localized and climate-specific approach to addressing building energy-cost-comfort performance. Findings reveal that in hot climates, there is a potential for nearly doubling primary energy consumption, global costs, and CO2 emissions in the future for both cost-optimal and nearly zero-energy scenarios. Consequently, the savings would decrease from 53-63 % to 13–30 %. In contrast, in cold climates, the impact on these parameters differs slightly, with reduced primary energy consumption and CO2 emissions but higher global costs. Notably, a building retrofitted to a high energy efficiency level may experience a substantial increase in future energy consumption and global costs, approaching the levels of currently inefficient buildings.

Moisture control of tropical cyclones in high-resolution simulations of paleoclimate and future climate

The intensity of tropical cyclones (TCs) is expected to increase in response to greenhouse warming. However, how future climate change will affect TC frequencies and tracks is still under debate. Here, to further elucidate the underlying sensitivities and mechanisms, we study TCs response to different past and future climate forcings. Using a high-resolution TC-resolving global Earth system model with 1/4° atmosphere and 1/10° ocean resolution, we conducted a series of paleo-time-slice and future greenhouse warming simulations targeting the last interglacial (Marine Isotope Stage (MIS) 5e, 125 ka), glacial sub-stage MIS5d (115 ka), present-day (PD), and CO2 doubling (2×CO2) conditions. Our analysis reveals that precessional forcing created an interhemispheric difference in simulated TC densities, whereas future CO2 forcing impacts both hemispheres in the same direction. In both cases, we find that TC genesis frequency, density, and intensity are primarily controlled by changes in tropospheric thermal and moisture structure, exhibiting a clear reduction in TC genesis density in warmer hemispheres.

The Role of Bjerknes and Shortwave Feedbacks in the Tropical Pacific SST Response to Global Warming

AbstractThe evolution of tropical sea surface temperatures (SSTs) in response to greenhouse warming is of great societal and scientific interest. Most state‐of‐the‐art climate models predict a mean “El Niño‐like” warming pattern by century‐end, characterized by greater warming over the Pacific cold tongue compared to the western warm pool. However, it is unclear which proposed mechanism dominates in this response. Here, we present partially coupled abrupt CO2 doubling experiments in which surface wind stress and shortwave heating are overridden to values from a control simulation. Contrary to previous studies, we find that experiments with overriding of surface wind stress exhibit only 58% of the full reduction in east‐west SST contrast. When both surface wind stress and shortwave flux are overridden, only 34% of the full reduction remains, controlled by spatially‐varying evaporative cooling. These results underscore the importance of Bjerknes and shortwave feedbacks in the tropical Pacific SST response to global warming.

Increase in Indian summer monsoon precipitation as a response to doubled atmospheric CO2: CMIP6 simulations and projections

Increase in Indian summer monsoon precipitation as a response to doubled atmospheric CO2: CMIP6 simulations and projections

Spatial–Temporal Distribution Pattern of Ormosia hosiei in Sichuan under Different Climate Scenarios

Ormosia hosiei is an endemic plant in China listed as a national grade II key protected wild plant with important scientific, economic, and cultural values. This study was designed to predict the potential suitable distribution areas for O. hosiei under current and future climate change and to provide a reference to enhance the species’ conservation and utilization. Based on the actual geographical locations of O. hosiei in Sichuan, we applied two species distribution models (BIOCLIM and DOMAIN) to predict its current and future potential suitable areas and future change patterns. We also analyzed the major climatic variables limiting its geographical distribution with principal component analysis. The results indicated that O. hosiei was mainly distributed in the eastern region of Sichuan and concentrated in the middle subtropical climate zone at relatively low elevations. The principal component analysis identified two critical factors representing temperature and moisture. The temperature was the most critical factor limiting O. hosiei distribution in Sichuan, especially the effect of extreme low temperatures. Both models’ simulation results of potential suitable areas under the current climate scenario showed that the excellent suitable habitat was consistent with the current actual distribution, remaining in the eastern region of Sichuan. Under the future climate scenario with doubled CO2 concentration (2100), both models predicted a sharp decrease in the areas of excellent and very high suitable habitats. The findings can inform strategies and guidelines for O. hosiei research, conservation, nursery production, and cultivation in Sichuan.

Rectifying low-frequency variability in future climate sea surface temperature simulations: are corrections for extreme change scenarios realistic?

Most procedures for redressing systematic bias in climate modeling are calibrated using current climate observations, and perform well. However, their performance in the future climate remains uncertain as no observations exist to compare against. In this context, we use the current and future climate outputs of an ultra-high resolution of Community Earth System Model (UHR-CESM) as the representative truth and bias correct monthly sea surface temperature (SST) simulations of eight Coupled Model Intercomparison Project 6 models over the Niño 3.4 region. A time-frequency bias correction approach is used to correct for bias in distributional, trend, and spectral attributes present in the models. This results in a near perfect power spectrum of the bias corrected current climate model simulations. Considering all correction procedures remain unchanged into the future, the overall representation of the corrected SST simulations shows improvement with consistency across models for the doubled CO2 scenario, but higher variability and lower consistency in the quadrupled CO2 concentration scenario.

Potential impacts of climate change on the productivity and soil carbon stocks of managed grasslands.

Rain-fed pastoral systems are tightly connected to meteorological conditions. It is, therefore, likely that climate change, including changing atmospheric CO2 concentration, temperature, precipitation and patterns of climate extremes, will greatly affect pastoral systems. However, exact impacts on the productivity and carbon dynamics of these systems are still poorly understood, particularly over longtime scales. The present study assesses the potential effects of future climatic conditions on productivity and soil organic carbon (SOC) stocks of mowed and rotationally grazed grasslands in France. We used the CenW ecosystem model to simulate carbon, water, and nitrogen cycles in response to changes in environmental drivers and management practices. We first evaluated model responses to individual changes in each key meteorological variable to get better insights into the role and importance of each individual variable. Then, we used 3 sets of meteorological variables corresponding to 3 Representative Concentration Pathways (RCP 2.6, RCP 4.5 and RCP 8.5) for long-term model runs from 1975 to 2100. Finally, we used the same three RCPs to analyze the responses of modelled grasslands to extreme climate events. We found that increasing temperature slightly increased grasslands productivities but strongly reduced SOC stocks. A reduction in precipitation led to reductions of biomass and milk production but increased SOC. Conversely, doubling CO2 concentration strongly increased biomass and milk production and marginally reduced SOC. These SOC trends were unexpected. They arose because both increasing precipitation and CO2 increased photosynthetic carbon gain, but they had an even greater effect on the proportion of biomass that could be grazed. The amount of carbon remaining on site and able to contribute to SOC formation was actually reduced under both higher precipitation and CO2. The simulations under the three RCPs indicated that grassland productivity was increased, but that required higher N fertilizer application rates and also led to substantial SOC losses. We thus conclude that, while milk productivity may continue at current rates under climate change, or even increase slightly, there could be some soil C losses over the 21st century. In addition, under the highest-emission scenario, the increasing importance of extreme climate conditions (heat waves and droughts) might render conditions at our site in some years as unsuitable for milk production. It highlights the importance of tailoring farming practices to achieve the dual goals of maintaining agricultural production while safeguarding soil C stocks.