Climate change impacts on sugarcane attainable yield in southern Brazil

This study evaluated the effects of climate change on sugarcane yield, water use efficiency, and irrigation needs in southern Brazil, based on downscaled outputs of two general circulation models (PRECIS and CSIRO) and a sugarcane growth model. For three harvest cycles every year, the DSSAT/CANEGRO model was used to simulate the baseline and four future climate scenarios for stalk yield for the 2050s. The model was calibrated for the main cultivar currently grown in Brazil based on five field experiments under several soil and climate conditions. The sensitivity of simulated stalk fresh mass (SFM) to air temperature, CO₂ concentration [CO₂] and rainfall was also analyzed. Simulated SFM responses to [CO₂], air temperature and rainfall variations were consistent with the literature. There were increases in simulated SFM and water usage efficiency (WUE) for all scenarios. On average, for the current sugarcane area in the State of São Paulo, SFM would increase 24 % and WUE 34 % for rainfed sugarcane. The WUE rise is relevant because of the current concern about water supply in southern Brazil. Considering the current technological improvement rate, projected yields for 2050 ranged from 96 to 129 t?ha^?1, which are respectively 15 and 59 % higher than the current state average yield.     

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.     

Estimates of Large-Scale Fluxes in High Latitudes from Terrestrial Biosphere Models and an Inversion of Atmospheric CO2 Measurements

It is important to improve estimates of large-scale carbon fluxes over the boreal forest because the responses of this biome to global change may influence the dynamics of atmospheric carbon dioxide in ways that may influence the magnitude of climate change. Two methods currently being used to estimate these fluxes are process-based modeling by terrestrial biosphere models (TBMs), and atmospheric inversions in which fluxes are derived from a set of observations on atmospheric CO₂ concentrations via an atmospheric transport model. Inversions do not reveal information about processes and therefore do not allow for predictions of future fluxes, while the process-based flux estimates are not necessarily consistent with atmospheric observations of CO₂. In this study we combine the two methods by using the fluxes from four TBMs as a priori fluxes for an atmospheric Bayesian Synthesis Inversion. By doing so we learn about both approaches. The results from the inversion indicate where the results of the TBMs disagree with the atmospheric observations of CO₂, and where the results of the inversion are poorly constrained by atmospheric data, the process-based estimates determine the flux results. The analysis indicates that the TBMs are modeling the spring uptake of CO₂ too early, and that the inversion shows large uncertainty and more dependence on the initial conditions over Europe and Boreal Asia than Boreal North America. This uncertainty is related to the scarcity of data over the continents, and as this problem is not likely to be solved in the near future, TBMs will need to be developed and improved, as they are likely the best option for understanding the impact of climate variability in these regions.     

The Potential Response of Terrestrial Carbon Storage to Changes in Climate and Atmospheric CO2

We use a georeferenced model of ecosystem carbon dynamics to explore the sensitivity of global terrestrial carbon storage to changes in atmospheric CO₂ and climate. We model changes in ecosystem carbon density, but we do not model shifts in vegetation type. A model of annual NPP is coupled with a model of carbon allocation in vegetation and a model of decomposition and soil carbon dynamics. NPP is a function of climate and atmospheric CO₂ concentration. The CO₂ response is derived from a biochemical model of photosynthesis. With no change in climate, a doubling of atmospheric CO₂ from 280 ppm to 560 ppm enhances equilibrium global NPP by 16.9%; equilibrium global terrestrial ecosystem carbon (TEC) increases by 14.9%. Simulations with no change in atmospheric CO₂ concentration but changes in climate from five atmospheric general circulation models yield increases in global NPP of 10.0–14.8%. The changes in NPP are very nearly balanced by changes in decomposition, and the resulting changes in TEC range from an increase of 1.1% to a decrease of 1.1%. These results are similar to those from analyses using bioclimatic biome models that simulate shifts in ecosystem distribution but do not model changes in carbon density within vegetation types. With changes in both climate and a doubling of atmospheric CO₂, our model generates increases in NPP of 30.2–36.5%. The increases in NPP and litter inputs to the soil more than compensate for any climate stimulation of decomposition and lead to increases in global TEC of 15.4–18.2%.     

Possible Impacts of Global Warming on the Hydrology of the Ogallala Aquifer Region

The Ogallala or High Plains aquifer provides water for about 20% of the irrigated land in the United States. About 20 km³ (16.6 million acre-feet) of water are withdrawn annually from this aquifer. In general, recharge has not compensated for withdrawals since major irrigation development began in this region in the 1940s. The mining of the Ogallala has been pictured as an analogue to climate change in that many GCMs predict a warmer and drier future for this region. In this paper we attempt to anticipate the possible impacts of climate change on the sustainability of the aquifer as a source of water for irrigation and other purposes in the region. We have applied HUMUS, the Hydrologic Unit Model of the U.S. to the Missouri and Arkansas-White-Red water resource regions that overlie the Ogallala. We have imposed three general circulation model (GISS, UKTR and BMRC) projections of future climate change on this region and simulated the changes that may be induced in water yields (runoff plus lateral flow) and ground water recharge. Each GCM was applied to HUMUS at three levels of global mean temperature (GMT) to represent increasing severity of climate change (a surrogate for time). HUMUS was also run at three levels of atmospheric CO₂ concentration (hereafter denoted by [CO₂]) in order to estimate the impacts of direct CO₂ effects on photosynthesis and evapotranspiration. Since the UKTR and GISS GCMs project increased precipitation in the Missouri basin, water yields increase there. The BMRC GCM predicts sharply decreased precipitation and, hence, reduced water yields. Precipitation reductions are even greater in the Arkansas basin under BMRC as are the consequent water yield losses. GISS and UKTR climates lead to only moderate yield losses in the Arkansas. CO₂-fertilization reverses these losses and yields increase slightly. CO₂ fertilization increases recharge in the base (no climate change) case in both basins. Recharge is reduced under all three GCMs and severities of climate change.     

Future cereal production in China: The interaction of climate change,water availability and socio-economic scenarios

Food production in China is a fundamental component of the national economy and driver of agricultural policy. Sustaining and increasing output to meet growing demand faces significant challenges including climate change, increasing population, agricultural land loss and competing demands for water. Recent warming in China is projected to accelerate by climate models with associated changes in precipitation and frequency of extreme events. How changes in cereal production and water availability due to climate change will interact with other socio-economic pressures is poorly understood. By linking crop and water simulation models and two scenarios of climate (derived from the Regional Climate Model PRECIS) and socio-economic change (downscaled from IPCC SRES A2 and B2) we demonstrate that by the 2040s the absolute effects of climate change are relatively modest. The interactive effects of other drivers are negative, leading to decreases in total production of ?18% (A2) and ?9% (B2). Outcomes are highly dependent on climate scenario, socio-economic development pathway and the effects of CO₂ fertilization on crop yields which may almost totally offset the decreases in production. We find that water availability plays a significant limiting role on future cereal production, due to the combined effects of higher crop water requirements (due to climate change) and increasing demand for non-agricultural use of water (due to socio-economic development). Without adaptation, per capita cereal production falls in all cases, by up to 40% of the current baseline.By simulating the effects of three adaptation scenarios we show that for these future scenarios China is able to maintain per capita cereal production, given reasonable assumptions about policies on land and water management and progress in agricultural technology. Our results are optimistic because PRECIS simulates much wetter conditions than a multi-model average, the CO₂ crop yield response function is highly uncertain and the effects of extreme events on crop growth and water availability are likely to be underestimated.     

Response of Soybean and Sorghum to Varying Spatial Scales of Climate Change Scenarios in the Southeastern United States

This study examines how uncertainty associated with the spatial scale of climate change scenarios influences estimates of soybean and sorghum yield response in the southeastern United States. We investigated response using coarse (300-km, CSIRO) and fine (50-km, RCM) scale climate change scenarios and considering climate changes alone, climate changes with CO₂ fertilization, and climate changes with CO₂ fertilization and adaptation. Relative to yields simulatedunder a current, control climate scenario, domain-wide soybean yield decreased by 49% with the coarse-scale climate change scenario alone, and by26% with consideration for CO₂ fertilization. By contrast, thefine-scale climate change scenario generally exhibited higher temperatures and lower precipitation in the summer months resulting in greater yield decreases (69% for climate change alone and 54% with CO₂fertilization). Changing planting date and shifting cultivars mitigated impacts, but yield still decreased by 8% and 18% respectively for the coarse andfine climate change scenarios. The results were similar for sorghum. Yield decreased by 51%, 42%, and 15% in response to fine-scaleclimate change alone, CO₂ fertilization, and adaptation cases, respectively– significantly worse than with the coarse-scale (CSIRO) scenarios. Adaptation strategies tempered the impacts of moisture and temperature stress during pod-fill and grain-fill periods and also differed with respect to the scale of the climate change scenario.     

Simulations of Water Resource Changes in Eastern and Central China in the Past 130 Years by a Regional Climate Model

Anthropogenic influences on regional climate and water resources over East Asia are simulated by using a regional model nested to a global model. The changes of land use/land cover (LULC) and CO₂ concentration are considered. The results show that variations of LULC and CO₂ concentration during the past 130 years caused a warming trend in many regions of East Asia. The most remarkable temperature increase occurred in Inner Mongolia, Northeast and North China, whereas temperature decreased in Gansu Province and north of Sichuan Province. LULC and CO₂ changes over the past 130 years resulted in a decreasing trend of precipitation in the Huaihe River valley, Shandong Byland, and Yunnan-Guizhou Plateau, but precipitation increased along the middle reaches of the Yangtze River, the middle reaches of the Yellow River, and parts of South China. This pattern of precipitation change with changes in surface evapotranspiration may have caused a more severe drought in the lower reaches of the Yellow River and the Huaihe River valley. The drought trend, however, weakened in the mid and upper reaches of the Yellow River valley, and the Yangtze River valley floods were increasing. In addition, changes in LULC and CO₂ concentration during the past 130 years led to adjustments in the East Asian monsoon circulation, which further affected water vapor transport and budget, making North China warm and dry, the Sichuan basin cold and wet, and East China warm and wet.     

Impact assessment of climate change,carbon dioxide fertilization and constant growing season on rice yields in China

Rice is the staple food in China, and the country’s enlarging population puts increasing pressure on its rice production as well as on that of the world. In this study, we estimate the impact of climate change, CO₂ fertilization, crop adaptation and the interactions of these three factors on the rice yields of China using model simulation with four hypothetical scenarios. According to the results of the model simulation, the rice yields without CO₂ fertilization are predicted to decrease by 3.3 % in the 2040s. Considering a constant rice-growing season (GS), the rice yields are predicted to increase by 3.2 %. When the effect of CO₂ fertilization is integrated into the Agro-C model, the expected rice yields increase by 20.9 %. When constant GS and CO₂ fertilization are both integrated into the model, the predicted rice yield increases by 28.6 %. In summary, the rice yields in China are predicted to decrease in the 2040s by 0.22 t/ha due to climate change, to increase by 0.44 t/ha due to a constant GS and to increase by 1.65 t/ha due to CO₂ fertilization. The benefits of crop adaptation would completely offset the negative impact of climate change. In the future, the most of the positive effects of climate change are expected to occur in northeastern and northwestern China, and the expansion of rice cultivation in northeastern China should further enhance the stability of rice production in China.     

A simple hydrologic framework for simulating wetlands in climate and earth system models

Wetlands are ecosystems of important functions in the earth??s climate system. Through relatively high evapotranspiration, they affect surface water and energy exchange with the atmosphere directly influencing the physical climate. Through CH₄, CO₂ and N₂O fluxes, they regulate the biogeochemical cycles, indirectly influencing the physical climate. However, current models do not explicitly include the water table, present under all large and stable wetlands; model wetlands are identified as flat land with wet soil resulting from precipitation events. That is, the wetlands are only ??wetted?? from above but not from below by the high water table. Furthermore, without the knowledge of the water table position, estimates of CH₄ and other gases (e.g., CO₂ and N₂O) are poorly constrained. We present a simple hydrologic framework for simulating wetlands based on water table depth. A synthesis of hydrologic controls on wetlands highlights the key role that groundwater plays. It directly feeds wetlands, supports surface-water fed wetlands by maintaining a saturated substrate, and links land drainage to sea level by impeding drainage in lowlands. Forced by routine climate model output (precipitation?Cevapotranspiration-surface runoff), land topography, and sea level, we simulate the present-day water table in North America at the 1?km scale. We validate the simulation with water table observations and compare regions of shallow water table to mapped wetlands. Our results show that the framework captures the salient features of wetland distribution and extent at regional and continental scales, a direct result of large-scale groundwater convergence that nourishes the lowlands even in arid climates. The low requirement of forcing and computation make the framework easy to adopt in climate and earth system models for simulating wetland responses to climate and sea level change for the present, paleo reconstructions, and future projections.     

Adaptation, Spatial Heterogeneity, and the Vulnerability of Agricultural Systems to Climate Change and CO2 Fertilization: An Integrated Assessment Approach

In this paper we develop economic measures of vulnerability to climate change with and without adaptation in agricultural production systems. We implement these measures using coupled, site-specific ecosystem and economic simulation models. This modeling approach has two key features needed to study the response of agricultural production systems to climate change: it represents adaptation as an endogenous, non-marginal economic response to climate change; and it provides the capability to represent the spatial variability in bio-physical and economic conditions that interact with adaptive responses. We apply this approach to the dryland grain production systems of the Northern Plains region of the United States. The results support the hypothesis that the most adverse impacts on net returns distributions tend to occur in the areas with the poorest resource endowments and when mitigating effects of CO₂ fertilization and adaptation are absent. We find that relative and absolute measures of vulnerability depend on complex interactions between climate change, CO₂ level, adaptation, and economic conditions such as relativeoutput prices. The relationship between relative vulnerability and resource endowments varies with assumptions about climate change, adaptation, and economic conditions. Vulnerability measured with respect to an absolute threshold is inversely related to resource endowments in all cases investigated.     

Climate response to introduction of the ESA CCI land cover data to the NCAR CESM

The European Space Agency Climate Change Initiative Land Cover data (ESA CCI-LC, from 1992 to 2015) is introduced to the National Center for Atmospheric Research Community Earth System Model version 1.2.1 (NCAR CESM1.2.1). In comparison with the original land surface data in the Community Land Model version 4 (ORG), the new data features notable land use and land cover change (LULCC) with increased forests over northeastern Asia and Alaska by decreasing shrublands and grasslands. Overestimated bare land cover over the Tibetan Plateau (TP) and the Rocky Mountains in the ORG are corrected with the replacements by grasslands and shrublands respectively in the new data. The model simulation results show that with the introduction of the ESA CCI-LC, the simulated surface albedo, surface net radiation flux, sensible and latent heat fluxes are relatively improved over the regions where significant LULCC exists, such as northeastern Asia, Alaska, the TP, and Australia. Surface air temperature, precipitation, and atmospheric circulation are improved in boreal winter but degraded in summer. The winter warming over northeastern Asia results from increased longwave downwelling flux and adiabatic heating while the notable winter cooling over Alaska is attributed to strong cold advection followed by reduced longwave downwelling flux. LULCC alters precipitation by influencing water vapor content. In winter, LULCC affects atmospheric circulation via modulating baroclinicity while in summer, it influences land-sea thermal contrast, thus affecting the intensity of East Asian summer monsoon. LULCC also alters the simulated dust burden.

     

Impact of doubled CO2 on the interaction between the global and regional water cycles in four study regions

Results from a suite of 30-year simulations (after spin-up) of the fully coupled Community Climate System Model version 2.0.1 are analyzed to examine the impact of doubling CO₂ on interactions between the global water cycle and the regional water cycles of four similar-size, but hydrologically and thermally different study regions (the Yukon, Ob, St Lawrence, and Colorado river basins and their adjacent land). A heuristic evaluation based on published climatological data shows that the model generally produces acceptable results for the control 1× CO₂ concentration, except for mountainous regions where it performs like other modern climate models. After doubling CO₂, the Northern Hemisphere receives significantly (95% confidence level) more moisture from the Southern Hemisphere during the boreal summer than under 1× CO₂ conditions, and the phase of the annual cycle of net moisture transport to areas north of 60°N shifts to a month later than in the reference simulation. Precipitation and evapotranspiration in the doubled CO₂ simulation increase for the Yukon, Ob, and St Lawrence, but decrease, on average, for the Colorado region compared to the reference simulation. For all regions, interaction between global and regional water cycles increases under doubled CO₂, because the amount of moisture entering and leaving the regions increases in the warmer climate. The degree of change in this interaction depends on region and season, and is related to slight shifts in the position/strength of semi-permanent highs and lows for the Yukon, Ob, and St Lawrence; in the Colorado region, higher temperatures associated with doubling CO₂ and the anticyclone located over the region increase the persistence of dry conditions.     

Changes in Soybean Yields in the Midwestern United States as a Result of Future Changes in Climate, Climate Variability, and CO2 Fertilization

This modeling study addresses the potential impacts of climate change and changing climate variability due to increased atmospheric CO₂ concentration on soybean (Glycine max (L.) Merrill) yields in theMidwestern Great Lakes Region. Nine representative farm locations and six future climate scenarios were analyzed using the crop growth model SOYGRO. Under the future climate scenarios earlierplanting dates produced soybean yield increases of up to 120% above current levels in the central and northern areas of the study region. In the southern areas, comparatively small increases (0.1 to 20%) and small decreases (–0.1 to–25%) in yield are found. The decreases in yield occurred under the Hadley Center greenhouse gas run (HadCM2-GHG), representing a greater warming, and the doubled climate variability scenario – a more extreme and variableclimate. Optimum planting dates become later in the southern regions. CO₂fertilization effects (555 ppmv) are found to be significant for soybean, increasing yields around 20% under future climate scenarios.For the study region as a whole the climate changes modeled in this research would have an overall beneficial effect, with mean soybean yield increases of 40% over current levels.     

Climate response to the physiological impact of carbon dioxide on plants in the Met Office Unified Model HadCM3

The concentration of carbon dioxide in the atmosphere acts to control the stomatal conductance of plants. There is observational and modelling evidence that an increase in the atmospheric concentration of CO₂ would suppress the evapotranspiration (ET) rate over land. This process is known as CO₂ physiological forcing and has been shown to induce changes in surface temperature and continental runoff. We analyse two transient climate simulations for the twenty-first century to isolate the climate response to the CO₂ physiological forcing. The land surface warming associated with the decreased ET rate is accompanied by an increase in the atmospheric lapse rate, an increase in specific humidity, but a decrease in relative humidity and stratiform cloud over land. We find that the water vapour feedback more than compensates for the decrease in latent heat flux over land as far as the budget of atmospheric water vapour is concerned. There is evidence that surface snow, water vapour and cloudiness respond to the CO₂ physiological forcing and all contribute to further warm the climate system. The climate response to the CO₂ physiological forcing has a quite different signature to that from the CO₂ radiative forcing, especially in terms of the changes in the temperature vertical profile and surface energy budget over land.     

A nonlinear impulse response model of the coupled carbon cycle-climate system (NICCS)

 Impulse-response-function (IRF) models are designed for applications requiring a large number of climate change simulations, such as multi-scenario climate impact studies or cost-benefit integrated-assessment studies. The models apply linear response theory to reproduce the characteristics of the climate response to external forcing computed with sophisticated state-of-the-art climate models like general circulation models of the physical ocean-atmosphere system and three-dimensional oceanic-plus-terrestrial carbon cycle models. Although highly computer efficient, IRF models are nonetheless capable of reproducing the full set of climate-change information generated by the complex models against which they are calibrated. While limited in principle to the linear response regime (less than about 3 ^∘C global-mean temperature change), the applicability of the IRF model presented has been extended into the nonlinear domain through explicit treatment of the climate system's dominant nonlinearities: CO₂ chemistry in ocean water, CO₂ fertilization of land biota, and sublinear radiative forcing. The resultant nonlinear impulse-response model of the coupled carbon cycle-climate system (NICCS) computes the temporal evolution of spatial patterns of climate change for four climate variables of particular relevance for climate impact studies: near-surface temperature, cloud cover, precipitation, and sea level. The space-time response characteristics of the model are derived from an EOF analysis of a transient 850-year greenhouse warming simulation with the Hamburg atmosphere-ocean general circulation model ECHAM3-LSG and a similar response experiment with the Hamburg carbon cycle model HAMOCC. The model is applied to two long-term CO₂ emission scenarios, demonstrating that the use of all currently estimated fossil fuel resources would carry the Earth's climate far beyond the range of climate change for which reliable quantitative predictions are possible today, and that even a freezing of emissions to present-day levels would cause a major global warming in the long term. Received: 28 January 2000 / Accepted: 9 March 2001     

土地利用模式比较计划(LUMIP)简评

为进一步促进土地利用和土地覆盖变化（Land-Use and Land-Cover Change,LULCC）以及土地管理对气候影响的理解,第六次国际耦合模式比较计划（CMIP6）设立了土地利用模式比较计划（LUMIP）。该计划主要包括两个阶段的试验设计：第一阶段涉及理想的毁林情景耦合试验和陆面模式模拟试验,旨在促进LULCC对气候影响过程的理解,并量化模式对LULCC的敏感性。第二阶段的试验重点关注土地利用变化的历史影响,以及未来土地管理决策在减缓气候变化方面的潜力。本文概述了其科学背景、试验设计和方案、参与模式情况等,并简评了该计划的研究意义和特色,以期读者迅速了解其相关的研究要点和发展方向。     

Influence of dynamic vegetation on climate change arising from increasing CO<Subscript>2</Subscript>

A dynamic global vegetation model (DGVM) is coupled to an atmospheric general circulation model (AGCM) to investigate the influence of vegetation dynamics on climate change under conditions of global warming. The model results are largely in agreement with observations and the results of previous studies in terms of the present climate, present potential vegetation, present net primary productivity (NPP), and pre-industrial carbon budgets. The equilibrium state of climate properties are compared among pre-industrial, doubled, and quadrupled atmospheric CO₂ values using DGVM–AGCM and current AGCM with fixed vegetation to evaluate the influence of dynamic vegetation change. We also separated the contributions of temperature, precipitation and CO₂ fertilization on vegetation change. The results reveal an amplification of global warming climate sensitivity by 10% due to the inclusion of dynamic vegetation. The total effects of elevated CO₂ and climate change also lead to an increase in NPP and vegetation coverage globally. The reduction of albedo associated with this greening results in enhanced global warming. Our separation analysis indicates that temperature alters vegetation at high latitudes such as Siberia or Alaska, where there is a switch from tundra to forest. On the other hand, CO₂ fertilization provides the largest contribution to greening in arid/semi-arid region. Precipitation change did not cause any drastic vegetation shift.     

Can ocean iron fertilization mitigate ocean acidification?

Ocean iron fertilization has been proposed as a method to mitigate anthropogenic climate change, and there is continued commercial interest in using iron fertilization to generate carbon credits. It has been further speculated that ocean iron fertilization could help mitigate ocean acidification. Here, using a global ocean carbon cycle model, we performed idealized ocean iron fertilization simulations to place an upper bound on the effect of iron fertilization on atmospheric CO₂ and ocean acidification. Under the IPCC A2 CO₂ emission scenario, at year 2100 the model simulates an atmospheric CO₂ concentration of 965 ppm with the mean surface ocean pH 0.44 units less than its pre-industrial value of 8.18. A globally sustained ocean iron fertilization could not diminish CO₂ concentrations below 833 ppm or reduce the mean surface ocean pH change to less than 0.38 units. This maximum of 0.06 unit mitigation in surface pH change by the end of this century is achieved at the cost of storing more anthropogenic CO₂ in the ocean interior, furthering acidifying the deep-ocean. If the amount of net carbon storage in the deep ocean by iron fertilization produces an equivalent amount of emission credits, ocean iron fertilization further acidifies the deep ocean without conferring any chemical benefit to the surface ocean.     

Modelling China’s potential maize production at regional scale under climate change

With the continuing warming due to greenhouse gases concentration, it is important to examine the potential impacts on regional crop production spatially and temporally. We assessed China’s potential maize production at 50 × 50 km grid scale under climate change scenarios using modelling approach. Two climate changes scenarios (A2 and B2) and three time slices (2011–2040, 2041–2070, 2071–2100) produced by the PRECIS Regional Climate Model were used. Rain-fed and irrigated maize yields were simulated with the CERES-Maize model, with present optimum management practices. The model was run for 30 years of baseline climate and three time slices for the two climate change scenarios, without and with simulation of direct CO₂ fertilization effects. Crop simulation results under climate change scenarios varied considerably between regions and years. Without the CO₂ fertilization effect, China’s maize production was predicted to suffer a negative effect under both A2 and B2 scenarios for all time slices, with greatest production decreases in today’s major maize planting areas. When the CO₂ fertilization effect is taken into account, production was predicted to increase for rain-fed maize but decrease for irrigated maize, under both A2 and B2 scenarios for most time periods.