Doubling Of Atmospheric CO2 Concentration Research Articles

Comparison of Proxy-Shortwave Cloud Albedo from SBUV Observations with CMIP6 Models

Abstract We construct a long-term record of top of atmosphere (TOA) shortwave (SW) albedo of clouds and aerosols from 340-nm radiances observed by NASA and NOAA satellite instruments from 1980 to 2013. We compare our SW cloud+aerosol albedo with simulated cloud albedo from both AMIP and historical CMIP6 simulations from 47 climate models. While most historical runs did not simulate our observed spatial pattern of the trends in albedo over the Pacific Ocean, four models qualitatively simulate our observed patterns. Those historical models and the AMIP models collectively estimate an equilibrium climate sensitivity (ECS) of ∼3.5°C, with an uncertainty from 2.7° to 5.1°C. Our ECS estimates are sensitive to the instrument calibration, which drives the wide range in ECS uncertainty. We use instrument calibrations that assume a neutral change in reflectivity over the Antarctic ice sheet. Our observations show increasing cloudiness over the eastern equatorial Pacific and off the coast of Peru as well as neutral cloud trends off the coast of Namibia and California. To produce our SW cloud+aerosol albedo, we first retrieve a black-sky cloud albedo (BCA) and empirically correct the sampling bias from diurnal variations. Then, we estimate the broadband proxy albedo using multiple nonlinear regression along with several years of CERES cloud albedo to obtain the regression coefficients. We validate our product against CERES data from the years not used in the regression. Zonal mean trends of our SW cloud+aerosol albedo show reasonable agreement with CERES as well as the Pathfinder Atmospheres–Extended (PATMOS-x) observational dataset. Significance Statement Equilibrium climate sensitivity is a measure of the rise in global temperature over hundreds of years after a doubling of atmospheric CO2 concentration. Current state-of-the-art climate models forecast a wide range of equilibrium climate sensitivities (1.5°–6°C), due mainly to how clouds, aerosols, and sea surface temperatures are simulated within these models. Using data from NASA and NOAA satellite instruments from 1980 to 2013, we first construct a dataset that describes how much sunlight has been reflected by clouds over the 34 years and then we compare this data record to output from 47 climate models. Based on these comparisons, we conclude the best estimate of equilibrium climate sensitivity is about 3.5°C, with an uncertainty range of 2.7°–5.1°C.

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.

Muted extratropical low cloud seasonal cycle is closely linked to underestimated climate sensitivity in models

A large spread in model estimates of the equilibrium climate sensitivity (ECS), defined as the global mean near-surface air-temperature increase following a doubling of atmospheric CO2 concentration, leaves us greatly disadvantaged in guiding policy-making for climate change adaptation and mitigation. In this study, we show that the projected ECS in the latest generation of climate models is highly related to seasonal variations of extratropical low-cloud fraction (LCF) in historical simulations. Marked reduction of extratropical LCF from winter to summer is found in models with ECS > 4.75 K, in accordance with the significant reduction of extratropical LCF under a warming climate in these models. In contrast, a pronounced seasonal cycle of extratropical LCF, as supported by satellite observations, is largely absent in models with ECS < 3.3 K. The distinct seasonality in extratropical LCF in climate models is ascribed to their different prevailing cloud regimes governing the extratropical LCF variability.

Ways to Estimate Climate Sensitivity

This paper mainly explores the specific significance of climate sensitivity and the various methods to assess it. In this paper, three major methods to calculate climate sensitivity are evaluated, including direct observation, climate models, and paleoclimate dataset. Direct observation utilizes instrument records to obtain environment data since the mid-19thcentury. Climate models simulate physical processes in the environment to analyse the increase in temperature resulted from the doubling of atmospheric CO2 concentration. Paleoclimate dataset reconstructs past climate based on some natural resources, such as ocean sediments. Paleoclimate dataset and climate models often work together to calculate climate sensitivity.

Impacts of atmospheric CO2 increase and Amazon deforestation on the regional climate: A water budget modelling study

AbstractGlobal air temperature increase has caused changes in the global climate such as droughts, floods and severe events. Land cover shifts and the increase in greenhouse gas emissions can intensify these impacts. Therefore, the application of Specific Warming Level 2 (SWL2) technique has been considered to evaluate the global warming issue in various climate scales, which may induce different responses in the climate system. The objective of this study is to evaluate the impacts of a doubling of current atmospheric CO2 concentrations as well as the influence of deforestation of the Amazon Forest on the climate of South America. In this study, the CPTEC‐BAM1.2 global model was used to simulate these processes. The first scenario of simulations considered doubled atmospheric CO2 concentration (2XCO2 = 776 ppm) and the second scenario is the total conversion of the Amazon Forest to pasture (DEF). In the third scenario both CO2 and deforestation are considered simultaneously (2XCO2 + DEF). A control simulation considers the natural Amazon Forest shape and a steady CO2 concentration of 388 ppm. Results suggest that the temperature increased in all scenarios, the highest increment in the 2XCO2 + DEF experiment (5.4°C in 2XCO2 + DEF, 5.1°C in DEF and 3.2°C in 2XCO2). The model simulated drastic negative rainfall anomalies in each of three scenarios (2XCO2 + DEF: −2.1 mm day−1, 2XCO2: −1.3 mm day−1 and DEF: −0.9 mm day−1). Besides less precipitation and evapotranspiration, shifts in moisture transport were identified in each of the three scenarios. The effect of doubled atmospheric CO2 produces results similar to deforestation for hydrological water budget changes, and total pasture conversion may intensify such changes.

Objectively combining climate sensitivity evidence

Recent assessments of climate sensitivity per doubling of atmospheric CO2 concentration have combined likelihoods derived from multiple lines of evidence. These assessments were very influential in the Intergovernmental Panel on Climate Change Sixth Assessment Report (AR6) assessment of equilibrium climate sensitivity, the likely range lower limit of which was raised to 2.5 °C (from 1.5 °C previously). This study evaluates the methodology of and results from a particularly influential assessment of climate sensitivity that combined multiple lines of evidence, Sherwood et al. (Rev Geophys 58(4):e2019RG000678, 2020). That assessment used a subjective Bayesian statistical method, with an investigator-selected prior distribution. This study estimates climate sensitivity using an Objective Bayesian method with computed, mathematical priors, since subjective Bayesian methods may produce uncertainty ranges that poorly match confidence intervals. Identical model equations and, initially, identical input values to those in Sherwood et al. are used. This study corrects Sherwood et al.'s likelihood estimation, producing estimates from three methods that agree closely with each other, but differ from those that they derived. Finally, the selection of input values is revisited, where appropriate adopting values based on more recent evidence or that otherwise appear better justified. The resulting estimates of long-term climate sensitivity are much lower and better constrained (median 2.16 °C, 17–83% range 1.75–2.7 °C, 5–95% range 1.55–3.2 °C) than in Sherwood et al. and in AR6 (central value 3 °C, very likely range 2.0–5.0 °C). This sensitivity to the assumptions employed implies that climate sensitivity remains difficult to ascertain, and that values between 1.5 °C and 2 °C are quite plausible.

Efficacy of black carbon aerosols: the role of shortwave cloud feedback

Using idealized climate model simulations, we investigate the effectiveness of black carbon (BC) aerosols in warming the planet relative to CO2 forcing. We find that a 60-fold increase in the BC aerosol mixing ratio from the present-day levels leads to the same equilibrium global mean surface warming (∼4.1 K) as for a doubling of atmospheric CO2 concentration. However, the radiative forcing is larger (∼5.5 Wm−2) in the BC case relative to the doubled CO2 case (∼3.8 Wm−2) for the same surface warming indicating the efficacy (a metric for measuring the effectiveness) of BC aerosols to be less than CO2. The lower efficacy of BC aerosols is related to the differences in the shortwave (SW) cloud feedback: negative in the BC case but positive in the CO2 case. In the BC case, the negative SW cloud feedback is related to an increase in the tropical low clouds which is associated with a northward shift (∼7°) of the Intertropical Convergence Zone (ITCZ). Further, we show that in the BC case fast precipitation suppression offsets the surface temperature mediated precipitation response and causes ∼8% net decline in the global mean precipitation. Our study suggests that a feedback between the location of ITCZ and the interhemispheric temperature could exist, and the consequent SW cloud feedback could be contributing to the lower efficacy of BC aerosols. Therefore, an improved representation of low clouds in climate models is likely the key to understand the global climate sensitivity to BC aerosols.

Soil organic carbon in savannas decreases with anthropogenic climate change

Climate models indicate that climate change is likely to affect carbon (C) cycling in drylands, particularly savannas, but the magnitude and direction of change are not fully understood. In this study, we used the Century model to analyze how net primary productivity (NPP), soil respiration and soil C sequestration would respond to an increase in atmospheric CO2 and soil temperature. We also assessed the coupled effects of precipitation and temperature change on C dynamics under future climatic conditions, as well as the decoupled effects of each of the climate variables under three IPCC climate scenarios; historical, Representative Concentration Pathway 2.6 (RCP2.6) and RCP8.5. An increase in soil temperature results in loss of soil organic C (SOC), whereas doubling atmospheric CO2 concentration causes an increase in SOC. The increase in air temperature causes soil respiration to increase, while it causes NPP to decrease. We calculated the total SOC in the Kalahari savannas to be 0.9 Pg C (1Pg=1015g) in the top meter, and the rate of SOC loss due to anthropogenic climate change to be ~1.1TgCyr−1 (1Tg=1012g) and ~2.0TgCyr−1 under RCP2.6 and RCP8.5, respectively until the end of this century. If extrapolated to the global extent of savannas, our results imply net SOC loss of at least ~28.4TgCy−1 and 64.1TgCyr−1 under RCP2.6 and RCP8.5, respectively. The rapid loss of C from dryland soils predicted by Century could accelerate global warming and strengthen positive feedback mechanisms between climate change and processes controlling SOC. Our results vividly support the positive feedback between the SOC and atmospheric C cycles and further indicate that these feedbacks are not adequately accounted for in existing Earth System Models (ESM) that are part of CMIP5. Revisions to these ESM would appear necessary to adequately account for this positive feedback.

Projected land photosynthesis constrained by changes in the seasonal cycle of atmospheric CO2.

Uncertainties in the response of vegetation to rising atmospheric CO2 concentrations contribute to the large spread in projections of future climate change. Climate-carbon cycle models generally agree that elevated atmospheric CO2 concentrations will enhance terrestrial gross primary productivity (GPP). However, the magnitude of this CO2 fertilization effect varies from a 20 per cent to a 60 per cent increase in GPP for a doubling of atmospheric CO2 concentrations in model studies. Here we demonstrate emergent constraints on large-scale CO2 fertilization using observed changes in the amplitude of the atmospheric CO2 seasonal cycle that are thought to be the result of increasing terrestrial GPP. Our comparison of atmospheric CO2 measurements from Point Barrow in Alaska and Cape Kumukahi in Hawaii with historical simulations of the latest climate-carbon cycle models demonstrates that the increase in the amplitude of the CO2 seasonal cycle at both measurement sites is consistent with increasing annual mean GPP, driven in part by climate warming, but with differences in CO2 fertilization controlling the spread among the model trends. As a result, the relationship between the amplitude of the CO2 seasonal cycle and the magnitude of CO2 fertilization of GPP is almost linear across the entire ensemble of models. When combined with the observed trends in the seasonal CO2 amplitude, these relationships lead to consistent emergent constraints on the CO2 fertilization of GPP. Overall, we estimate a GPP increase of 37 ± 9 per cent for high-latitude ecosystems and 32 ± 9 per cent for extratropical ecosystems under a doubling of atmospheric CO2 concentrations on the basis of the Point Barrow and Cape Kumukahi records, respectively.

Recent progress toward reducing the uncertainty in tropical low cloud feedback and climate sensitivity: a review

Equilibrium climate sensitivity (ECS) to doubling of atmospheric CO2 concentration is a key index for understanding the Earth’s climate history and prediction of future climate changes. Tropical low cloud feedback, the predominant factor for uncertainty in modeled ECS, diverges both in sign and magnitude among climate models. Despite its importance, the uncertainty in ECS and low cloud feedback remains a challenge. Recently, researches based on observations and climate models have demonstrated a possibility that the tropical low cloud feedback in a perturbed climate can be constrained by the observed relationship between cloud, sea surface temperature and atmospheric dynamic and thermodynamic structures. The observational constraint on the tropical low cloud feedback suggests a higher ECS range than raw range obtained from climate model simulations. In addition, newly devised modeling frameworks that address both spreads among different model structures and parameter settings have contributed to evaluate possible ranges of the uncertainty in ECS and low cloud feedback. Further observational and modeling approaches and their combinations may help to advance toward dispelling the clouds of uncertainty.

Longevity of animals under reactive oxygen species stress and disease susceptibility due to global warming.

The world is projected to experience an approximate doubling of atmospheric CO2 concentration in the next decades. Rise in atmospheric CO2 level as one of the most important reasons is expected to contribute to raise the mean global temperature 1.4 °C-5.8 °C by that time. A survey from 128 countries speculates that global warming is primarily due to increase in atmospheric CO2 level that is produced mainly by anthropogenic activities. Exposure of animals to high environmental temperatures is mostly accompanied by unwanted acceleration of certain biochemical pathways in their cells. One of such examples is augmentation in generation of reactive oxygen species (ROS) and subsequent increase in oxidation of lipids, proteins and nucleic acids by ROS. Increase in oxidation of biomolecules leads to a state called as oxidative stress (OS). Finally, the increase in OS condition induces abnormality in physiology of animals under elevated temperature. Exposure of animals to rise in habitat temperature is found to boost the metabolism of animals and a very strong and positive correlation exists between metabolism and levels of ROS and OS. Continuous induction of OS is negatively correlated with survivability and longevity and positively correlated with ageing in animals. Thus, it can be predicted that continuous exposure of animals to acute or gradual rise in habitat temperature due to global warming may induce OS, reduced survivability and longevity in animals in general and poikilotherms in particular. A positive correlation between metabolism and temperature in general and altered O2 consumption at elevated temperature in particular could also increase the risk of experiencing OS in homeotherms. Effects of global warming on longevity of animals through increased risk of protein misfolding and disease susceptibility due to OS as the cause or effects or both also cannot be ignored. Therefore, understanding the physiological impacts of global warming in relation to longevity of animals will become very crucial challenge to biologists of the present millennium.

Simulation of CO2 enrichment and climate change impacts on soybean production

Abstract The potential doubling of atmospheric CO2 concentration and associated changes in temperature and precipitation are crucial issues for agricultural productivity. The CROPGRO-Soybean model in decision support system for agro-technology transfer v4.5 to simulate soybean (Glycine max cv. Pioneer 93B15) grown in an elevated CO2 environment was calibrated and validated. Crop growth and yield data were obtained from a series of experiments conducted in central Illinois at the soybean free air CO2 enrichment facility from 2002 to 2006. The model was applied to simulate the possible impacts of climate change on soybean yield in the region for the future years of 2080-2100, centred on 2090. The model reproduced the measured soybean growth and yield well under ambient and elevated CO2 conditions. For the period from 2081 to 2100, soybean yield was projected to decrease due to elevated temperature but to increase due to elevated precipitation and CO2 concentration, achieving counterbalance. The adverse impacts of the warming conditions on soybean yield can be mitigated by late planting within an optimum planting range (day of year 145 to 152) as a management option, as well as by controlling genetic responses to thermal days in the reproductive stage.

Equilibrium climate sensitivity in light of observations over the warming hiatus

A key uncertainty in projecting future climate change is the magnitude of equilibrium climate sensitivity (ECS), that is, the eventual increase in global annual average surface temperature in response to a doubling of atmospheric CO2 concentration. The lower bound of the likely range for ECS given in the IPCC Fifth Assessment Report (AR5; refs 1,2) was revised downwards to 1.5 degrees C, from 2 degrees C in its previous report(3), mainly as an effect of considering observations over the warming hiatus-the period of slowdown of global average temperature increase since the early 2000s. Here we analyse how estimates of ECS change as observations accumulate over time and estimate the contribution of potential causes to the hiatus. We find that including observations over the hiatus reduces the most likely value for ECS from 2.8 degrees C to 2.5 degrees C, but that the lower bound of the 90% range remains stable around 2 degrees C. We also find that the hiatus is primarily attributable to El Nino/Southern Oscillation-related variability and reduced solar forcing.

Photoperiod and Nitrogen Supply Limit the Scope of Northward Migration and Seed Transfer of Black Spruce in a Future Climate Associated with Doubled Atmospheric CO2 Concentration

The predicated changes in precipitation and temperature associated with the continued elevation of atmospheric CO2 concentration will trigger the northward shift of the Climate Envelopes for 130 North America tree species by as much as 10 degrees. However, climate envelope models do not take into account changes in other factors that may also influence the survival and growth of plants at the predicted new locations, such as photoperiod and nutrient regimes. This study investigated how photoperiod and nitrogen supply would affect the ecophysiological traits of black spruce (Picea mariana (Mill) B. S. P.) that are critical for survival and growth at new locations predicted by climate envelope models. We exposed black spruce seedlings to the photoperiod regime at the seed origin (PS) and that 10° north of the seed origin (PNM) as predicted by climate envelope models under the current and doubled atmospheric CO2 concentration and different levels of N supply (30 vs. 300 μmol·mol-1 N). We found that the PNM and the 30 μmol·mol-1 N supply both had negative impact on the development of seedling cold hardiness in the fall, and led to earlier burst of the terminal bud and greater rate of mortality in the following growing season. While the PNM stimulated seedling growth in the first growing season, the effect was not sustained in the second growing season. Our results suggest that the photoperiod regimes and poor nutrient conditions at higher latitudes will likely constrain the scope of the northward migration or seed transfer of black spruce.

外来入侵植物飞机草和本地植物异叶泽兰对大气CO2升高的响应

PDF HTML阅读 XML下载 导出引用 引用提醒 外来入侵植物飞机草和本地植物异叶泽兰对大气CO2浓度升高的响应 DOI: 10.5846/stxb201211101581 作者: 作者单位: 中国科学院西双版纳热带植物园,中国科学院西双版纳热带植物园,中国科学院西双版纳热带植物园,中国科学院西双版纳热带植物园,沈阳农业大学生物科学技术学院 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（30830027，31270582）；中国科学院知识创新工程重要方向性项目（KSCX2-YW-Z-1019） Responses of invasive Chromolaena odorata and native Eupatorium heterophyllum to atmospheric CO2 enrichment Author: Affiliation: Key Laboratory of Tropical Forest Ecology,Xishuangbanna Tropical Botanical Garden,Chinese Academy of Sciences,Mengla,Key Laboratory of Tropical Forest Ecology,Xishuangbanna Tropical Botanical Garden,Chinese Academy of Sciences,Mengla,Key Laboratory of Tropical Forest Ecology,Xishuangbanna Tropical Botanical Garden,Chinese Academy of Sciences,Mengla,Key Laboratory of Tropical Forest Ecology,Xishuangbanna Tropical Botanical Garden,Chinese Academy of Sciences,Mengla,College of Bioscience and Biotechnology,Shenyang Agricultural University Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:大气CO2浓度升高影响外来植物入侵，研究外来入侵植物和本地植物对大气CO2浓度升高响应的差异，有助于准确预测和管理外来植物入侵。基于封顶式CO2生长室，模拟大气CO2浓度变化（对照和700 μmol/mol），比较研究了外来入侵植物飞机草（Chromolaena odorata）和本地植物异叶泽兰（Eupatorium heterophyllum）形态、生长、生物量分配和光合特性对大气CO2浓度升高响应的差异。结果表明：（1）在当前大气CO2浓度下，飞机草总生物量、株高、基径和总叶面积高于异叶泽兰，分枝数低于异叶泽兰；CO2浓度升高，飞机的总生物量、株高、基径、分枝数和总叶面积分别增加了92%、41%、60%、325%和148%，高于异叶泽兰的32%、14%、30%、64%和79%，飞机草生长优势进一步提高。（2）无论在高或低CO2浓度下，飞机草根生物量分数（RMF）都低于异叶泽兰，叶生物量分数（LMF）和茎生物量分数（SMF）都高于异叶泽兰；CO2倍增两种植物RMF均降低，LMF和SMF均升高，但这2个参数对CO2倍增响应的种间差异不显著。（3）无论在高或低CO2浓度下，飞机草和异叶泽兰的净光合速率差异均不显著，CO2倍增对两种植物的净光合速率的促进作用相似。上述结果表明，在未来大气CO2浓度升高的条件下，飞机草的入侵性可能提高，入侵危害将加剧。 Abstract:Atmospheric CO2 concentration had increased from a pre-industrial level of 270 μmol/mol to 350 μmol/mol in 2005 and continues to increase at 1.9 μmol/mol per year on average. It is well known that atmospheric CO2 enrichment may influence the invasiveness of introduced plant species. Identifying the effects of elevated CO2 on invasiveness of exotic plants is very important for improving our ability to predict and control potentially invasive species. Four closed-top chambers were used to control CO2 concentration, ambient atmospheric CO2 concentration (control) and doubled atmospheric CO2 concentration (700 μmol/mol). To determine the effects of atmospheric CO2 enrichment on invasiveness of Chromolaena odorata, a noxious invasive perennial herb or subshrub in many countries of Asia, Oceania and Africa, we compared C. odorata and its phylogenetically related indigenous plant Eupatorium heterophyllum in terms of morphology, growth, biomass allocation, and photosynthesis at two CO2 concentrations. Fourteen traits related to morphology, growth, biomass allocation, and photosynthesis were measured when C. odorata and E. heterophyllum were treated for nearly three months.At ambient CO2 concentration, total biomass, height, stem diameter, and total leaf area were significantly higher and branch number were lower for invasive C. odorata than for native E. heterophyllum, which contribute to form dense monoculture for the invader, outshading native plant species. CO2 enrichment significantly increased total biomass, height, stem diameter, branch number, and total leaf area in both species. For C. odorata, total biomass, height, stem diameter, branch number and total leaf area were increased by 92%, 41%, 60%, 325%, and 148%, respectively, much higher than 32%, 14%, 30%, 64%, and 79% for E. heterophyllum. Consistently, growth advantage of the invader over the native became more evident at doubled atmospheric CO2 concentration.CO2 enrichment decreased root mass fraction (RMF) and increased stem mass fraction (SMF) and leaf mass fraction (LMF) for both the invasive and native species. However, the responses of these traits to CO2 enrichment were not significantly different between C. odorata and E. heterophyllum. C. odorata allocated more biomass to stems and leaves and less to roots than E. heterophyllum at either ambient CO2 concentration or doubled atmospheric CO2 concentration. Higher LMF and SMF may help C. odorata to increase carbon assimilation, and lower RMF may help C. odorata to reduce respiratory carbon loss, facilitating biomass accumulation. The more efficient strategy of biomass accumulation adopted by the invader might still provide stronger competitive ability against the native. In addition, atmospheric CO2 enrichment significantly increased net photosynthetic rate (Pmax) for both species, and the increases were not significantly different between C. odorata and E. heterophyllum. At both low and high CO2 concentration, Pmax was not significantly different between two species. This indicates that higher biomass accumulation of C. odorata may not be associated with photosynthesis, and benefit from other aspects at doubled atmospheric CO2 concentration.In conclusion, our results indicate that CO2 enrichment stimulates growth more greatly for invasive C. odorata than for native E. heterophyllum, and that in the future with high atmospheric CO2 concentration invasions by C. odorata may become more serious. 参考文献 相似文献 引证文献

Do probabilistic expert elicitations capture scientists’ uncertainty about climate change?

Expert elicitation studies have become important barometers of scientific knowledge about future climate change (Morgan and Keith, Environ Sci Technol 29(10), 1995; Reilly et al., Science 293(5529):430–433, 2001; Morgan et al., Climate Change 75(1–2):195–214, 2006; Zickfeld et al., Climatic Change 82(3–4):235–265, 2007, Proc Natl Acad Sci 2010; Kriegler et al., Proc Natl Acad Sci 106(13):5041–5046, 2009). Elicitations incorporate experts’ understanding of known flaws in climate models, thus potentially providing a more comprehensive picture of uncertainty than model-driven methods. The goal of standard elicitation procedures is to determine experts’ subjective probabilities for the values of key climate variables. These methods assume that experts’ knowledge can be captured by subjective probabilities—however, foundational work in decision theory has demonstrated this need not be the case when their information is ambiguous (Ellsberg, Q J Econ 75(4):643–669, 1961). We show that existing elicitation studies may qualitatively understate the extent of experts’ uncertainty about climate change. We designed a choice experiment that allows us to empirically determine whether experts’ knowledge about climate sensitivity (the equilibrium surface warming that results from a doubling of atmospheric CO2 concentration) can be captured by subjective probabilities. Our results show that, even for this much studied and well understood quantity, a non-negligible proportion of climate scientists violate the choice axioms that must be satisfied for subjective probabilities to adequately describe their beliefs. Moreover, the cause of their violation of the axioms is the ambiguity in their knowledge. We expect these results to hold to a greater extent for less understood climate variables, calling into question the veracity of previous elicitations for these quantities. Our experimental design provides an instrument for detecting ambiguity, a valuable new source of information when linking climate science and climate policy which can help policy makers select decision tools appropriate to our true state of knowledge.

Examining vegetation feedbacks on global warming in the Community Earth System Model

Leaves close their stomates in response to increases of CO2. Such a rapid physiological response is included in the land component of comprehensive climate models. However, observational studies have shown that they can further close their stomates as a consequence of “down‐regulation,” further reducing canopy conductance. However, they may also increase the area of their leaves, hence increasing their canopy conductance. Changes of canopy conductance change surface ET, a reduction leading to surface warming. A simulation considering these mechanisms of modifying canopy conductance is carried out for the assumption of a doubled atmospheric CO2concentration, using the Community Earth System model. It finds that down‐regulation as formulated in previous studies could have as large a warming impact on land temperatures as the standard leaf physiological response. Increases in LAI, if they were to occur, appear to have but a small cooling effect. The reduction of latent cooling in the model is amplified by a reduction of low‐level cloud cover, hence enhanced net absorption of solar radiation. Reduction of low level cloudiness appears to be necessary to maintain global radiation balance as reported in a previous study. Over mid to high latitudes, decreases in surface albedo associated with reduced snow cover also contribute to amplifying the warming. The physiological feedbacks of leaf stomates in the simulation increase warming by 0.6 ± 0.2°C over land and 0.3 ± 0.1°C globally, not inconsistent with previous studies. Enhanced interhemispheric temperature differences weaken the southward shift of the ITCZ associated with CO2radiative warming. Regions with relatively high LAI tend to have greater vegetation feedback; but increases in large‐scale precipitation may weaken this local warming effect.

An estimate of equilibrium sensitivity of global terrestrial carbon cycle using NCAR CCSM4

Increasing concentrations of atmospheric CO2 influence climate, terrestrial biosphere productivity and ecosystem carbon storage through its radiative, physiological and fertilization effects. In this paper, we quantify these effects for a doubling of CO2 using a low resolution configuration of the coupled model NCAR CCSM4. In contrast to previous coupled climate-carbon modeling studies, we focus on the near-equilibrium response of the terrestrial carbon cycle. For a doubling of CO2, the radiative effect on the physical climate system causes global mean surface air temperature to increase by 2.14 K, whereas the physiological and fertilization on the land biosphere effects cause a warming of 0.22 K, suggesting that these later effects increase global warming by about 10 % as found in many recent studies. The CO2-fertilization leads to total ecosystem carbon gain of 371 Gt-C (28 %) while the radiative effect causes a loss of 131 Gt-C (~10 %) indicating that climate warming damps the fertilization-induced carbon uptake over land. Our model-based estimate for the maximum potential terrestrial carbon uptake resulting from a doubling of atmospheric CO2 concentration (285–570 ppm) is only 242 Gt-C. This highlights the limited storage capacity of the terrestrial carbon reservoir. We also find that the terrestrial carbon storage sensitivity to changes in CO2 and temperature have been estimated to be lower in previous transient simulations because of lags in the climate-carbon system. Our model simulations indicate that the time scale of terrestrial carbon cycle response is greater than 500 years for CO2-fertilization and about 200 years for temperature perturbations. We also find that dynamic changes in vegetation amplify the terrestrial carbon storage sensitivity relative to a static vegetation case: because of changes in tree cover, changes in total ecosystem carbon for CO2-direct and climate effects are amplified by 88 and 72 %, respectively, in simulations with dynamic vegetation when compared to static vegetation simulations.

The potential of vegetation feedback to alleviate climate aridity over the United States associated with a 2×CO2 climate condition

This study examines the potential impact of vegetation feedback on changes in summer climate aridity over the contiguous United States (US) due to the doubling of atmospheric CO2 concentration using a set of 100-year-long climate simulations made by a global climate model interactively coupled with a dynamic vegetation model. The Thornthwaite moisture index (Im), which quantifies climate aridity on the basis of atmospheric water supply (i.e., precipitation) and atmospheric water demand (i.e., potential evapotranspiration, PET), is used to measure climate aridity. Warmer atmosphere and drier surface resulting from increased CO2 concentration increase climate aridity over most of the contiguous US. This phenomenon is due to larger increments in PET than in precipitation, regardless of the presence or absence of vegetation feedback. Compared to simulations without active dynamic vegetation feedback, the presence of vegetation feedback significantly alleviates the increase in aridity. This vegetation-feedback effect is most noticeable in the subhumid regions such as southern, midwestern and northwestern US, primarily by the increasing vegetation greenness. In these regions, the greening in response to warmer temperatures enhances moisture transfer from soil to atmosphere by evapotranspiration (ET). The increased ET and subsequent moistening over land areas result in weaker surface warming (1–2 K) and PET (3–10 mm month−1), and greater precipitation (4–10 mm month−1). Collectively, they result in moderate increases in Im. Our results suggest that moistening by enhanced vegetation feedback may prevent aridification under climatic warming especially in areas vulnerable to climate change, with consequent implications for mitigation strategies.

Stomatal numbers, leaf and canopy conductance, and the control of transpiration

De Boer et al. (1) concluded that doubled atmospheric CO2 concentration ([CO2]), by reducing both leaf stomatal density and conductance, would decrease modeled annual transpiration by approximately 60 W m−2 in Florida's subtropical vegetation. This remarkable result was accompanied by statements that current Floridian annual evapotranspiration (ET) is approximately 120 W m−2 and that transpiration is approximately 50% of current ET (i.e., ∼60 W m−2). (The remainder of ET is accounted for by evaporation from soil and interception water.) Because 60 minus 60 W m−2 equals 0 W m−2, modeled transpiration in subtropical Florida would therefore cease with CO2 doubling, implying …