近地层O3和CO2浓度变化对冬小麦影响的数值模拟：Ⅰ模型结构

在试验研究的基础上,文中尝试利用数值模拟方法评估O3和CO2浓度变化对作物的影响.以农田生态系统碳氮生物化学模型(DNDC)为基础,对其中的作物子模型进行改进,加入O3对冬小麦光合作用和叶片生长影响的模拟,结合原模型中有关CO2对冬小麦光合作用影响的模拟,建立反映O3和CO2浓度变化对冬小麦生长发育和产量形成影响的作物模型.文章对DNDC模型进行了参数修正以适用于中国华北地区;文章参考前人的工作,引用了两种O3对作物光合作用影响的模拟方法进行比较,分别是O3对初始光利用率的影响和O3对叶片光合作用的直接影响;在此基础上,进一步考虑O3对冬小麦叶片生长的影响,根据试验资料,建立了O3对叶片生长影响系数.     

近地层O3和CO2浓度变化对冬小麦影响的数值模拟：Ⅱ模拟结果和分析

针对CO2和O3浓度变化对冬小麦影响,改进了农田生态系统碳氮生物化学模型(DNDC),并利用模型模拟了O3和CO2浓度变化对冬小麦生长发育和产量的影响,检验了模型的模拟效果.通过对原DNDC模型适用性的调整,使之适用于固城站,为进一步改进作物模型打下了可靠的基础.通过试验资料验证表明,模型较好地反映了O3和CO2浓度变化对冬小麦生长发育和产量形成的影响.通过敏感性分析得出,模型对温度变化反映灵敏;在CO2浓度倍增情况下,O3浓度变化对冬小麦的复合影响分析看出,一定浓度范围内,CO2可缓解O3对作物影响的负效应,O3对CO2带来的正效应有削弱作用.     

基于遥感信息的华北冬小麦区域生长模型及模拟研究

卫星遥感估产和作物生长模拟在作物监测和产量预测方面有各自不可替代的优势。但是,遥感估产难以揭示作物生长发育和产量形成的内在机理,作物模拟在区域应用时初始值的获取和参数的区域化遇到很多困难。如何利用二者的互补性使其相互结合受到人们关注。该文在Wofost模型本地化和区域化的基础上,首次利用同化法的思路探讨了MODIS遥感信息与华北冬小麦生长模拟模型结合的可行性和方法,初步建立了潜在生产水平(水分适宜条件)下区域遥感-作物模拟框架模型(WSPFRS模型)。模拟结果显示:WSPFRS模型对区域尺度的出苗期重新初始化后,模拟的开花期、成熟期空间分布的准确性比Wofost模拟结果有所改进;利用遥感信息对区域尺度上返青期生物量重新初始化后,模拟贮存器官干重的空间分布更接近实际单产的分布,贮存器官干重的高值区与实际高产区基本相符。该研究将为下一步实际水分供应条件下基于遥感信息的冬小麦区域生长模拟研究奠定了基础。     

CO2和O3浓度倍增对作物影响的研究进展

文中利用自行设计的OTC - 1型开顶式气室进行了 9a的田间试验 ,取得了一批质量可靠的试验数据 ,分析了CO2 浓度倍增对大豆、冬小麦、棉花、玉米、春小麦和谷子的生物量、产量及品质的影响 ,结果表明CO2 浓度倍增对上述 6种作物的生物量及产量的影响均是正效应 ,对冬小麦、棉花和谷子品质的影响可能是有利的 ,对玉米品质的影响可能是不利的 ,对大豆的影响不大 ;分析了O3 浓度倍增对冬小麦、水稻、油菜和菠菜生物量、产量及品质的影响 ,结果表明O3 浓度倍增对上述 4种作物生物量的影响均是负效应 ,对冬小麦和水稻的产量影响是负效应 ,但是冬小麦和水稻籽粒中粗蛋白和 17种氨基酸含量都有所增加 ;分析了CO2 和O3 浓度复合倍增对大豆生物量、产量及品质的影响 ,结果是生物量和产量呈增加趋势 ,说明了CO2 的正效应大于O3 的负效应。采用作物模型数值模拟方法 ,分析了CO2 和O3 浓度倍增对冬小麦生物量及产量的影响。     

水分和氮素营养胁迫下春小麦生长模拟模式的研究

根据田间试验资料，在前人工作基础上进一步探讨了水分和氮素营养胁迫对作物生长的影响，并建立了大田生产实际条件下春小麦生长模式。经初步检验，模式对总干重的模拟相对误差小于5%，穗重模拟小于10%，根、茎、叶等器官重、根层土壤水分含量、作物总耗氮量和籽粒氮浓度以及叶面积指数等的模拟也取得了较好的结果。     

作物长势评估指数的设计与应用

合理有效地开展作物长势评估,可以及时反映作物生长状况及其对天气气候条件的响应。由于WOFOST模型、ORYZA2000模型在模拟冬小麦、玉米和水稻生长发育过程具备较强机理性,研究基于2001年以来全国冬小麦、玉米、水稻主产区逐日模拟的作物发育进程、叶面积指数和地上总生物量,通过隶属函数构建评估指数,开展高时空分辨率的作物长势评估。结果表明:长势综合评估指数在作物生长前期以发育进程、叶面积指数和地上总生物量三要素加权集合表征,中后期以发育进程和地上总生物量与穗重相关性的加权集合表征;长势评估指数与常规地面观测和遥感长势监测一致性较好,可以反映天气气候条件影响。在作物生长季内,以日为单位构建了作物长势评估指数数据库;根据长势评估指数将作物长势分为长势好、长势偏好、长势持平、长势偏差、长势差,实现空间上的长势监测、对比;以空间集成的方式,开展省级作物长势对比分析;利用长势评估指数变化反映典型天气气候条件对作物生长发育的影响。上述基于作物模型的作物长势评估指数符合现代化农业气象科研与业务服务发展的需求。     

冠层CO2分布廊线的农业气象数值模拟研究

本文将农田微气象模式与冬小麦冠层光合模式进行耦合，建立了一个具有较强机理的冬小麦冠层CO2分布廓线模式，冠层光合模式中考虑了气孔对叶片光合的调节作用，具有明确的生物学意义，实测资料验证表明，模式可以较准确地模拟拔节期冬小麦冠层CO2分布状况，平均相对误差为6．47％，数值分析表明：当冬小麦冠层风速为1m/s时，CO2廓线弯曲最为明显，随着风速加大，CO2廓线弯曲程度变小，CO2浓度升高后风速对廓线影响的基本规律没有发生改变，但是冠层中CO2浓度差将进一步加大。     

大气CO2浓度升高及气候变化对作物冠层光合影响的数值模拟

利用美国Licor-6200光合作用测定仪,对黄淮海地区代表性冬小麦品种鲁麦23号叶片光合作用速率进行了较为全面的测定,分别确定了冬小麦叶片光-光合作用响应曲线和CO2-光合作用响应曲线,在此基础上,建立了叶片光合作用模式,并进而建立了一个具有瞬时时间尺度,空间积分为叶片尺度的冬小麦冠层模式,利用模式分别分析了大气中CO2浓度升高和温度变化对冠层光合作用的不同影响,并在此基础上进一步进行了综合数值分析.单因子分析表明晴天状况下,冠层光合速率随CO2浓度升高而上升,当CO2浓度由330×10-6上升至660×10-6时,冠层光合日总量可增加19.7 %;冠层光合速率随辐射增加而增大,辐射量增加10.0 %,冠层光合日总量可增加6.7 %;冠层光合速率随温度升高而下降,温度升高1 ℃,冠层光合日总量减少2.9 %.多因子综合数值分析表明在辐射量较大的气候背景下,冠层光合日总量对温度和CO2变化响应更加敏感.本文的实测数据为研究气候变化对中国农业影响提供了最基本的可靠模型参数,冠层光合模型为未来改进作物模型提供了理论基础.     

遥感信息与作物模型结合在冬小麦区域模拟中的应用

遥感数据与作物模型结合是当前农业信息技术应用研究的重要内容和发展趋势之一,能够解决单独利用遥感或作物模型无法解决的问题。为了开展大范围、区域性作物生长过程的模拟和产量预测,首先对作物模型WOFOST进行了订正和验证,使得调整后的模型适于模拟河南新乡县冬小麦生长;根据实际生产分三类情形模拟新乡县2002—2003年度冬小麦的生长发育状况;利用全生育期内能获取的Landsat-7 ETM+数据反演叶面积指数,结合WOFOST模型的模拟情况,确定每个像元对应的冬小麦的生长状况,从而在像元上实现了WOFOST模型对冬小麦生长的模拟;最后对照比较本研究方法的结果与当年新乡县冬小麦的统计情况,结果相近,验证了本文研究方法的技术可行性。     

非对称性增温对农业生态系统影响研究进展

该文概述了北半球和我国气候变暖中增温的非对称性特征:北半球气候变暖存在明显的季节差异和昼夜不同步性, 大部分地区冬、春季升温高于夏、秋季, 日最低气温升幅是日最高气温升幅的2~3倍; 近50年我国近地表气温升高主要是最低气温明显上升的结果, 日最低气温升幅是日最气高温升幅的2~3倍, 与北半球基本一致; 升温最显著的季节为冬季和春季。在此基础上概述了非对称性增温对农业生态系统的影响, 论述了非对称性增温对农作物物候和农作物产量的影响, 得出最低气温升高促使整个生长季延长, 促使早春作物物候期提前, 但最低气温和最高气温对不同作物的物候以及同一作物的不同发育阶段影响不同。现有研究多采用模型或统计的方法研究气候变暖对作物生长的影响, 认为温度升高对作物有“强迫成熟”效应; 而现有的最低气温升高和最高气温升高对作物生长影响的研究结果并不一致。非对称性增温对农作物影响的实验研究极少, 且缺乏对模型模拟结果的实验验证。     

Numerical Simulation Study on the Impacts of Tropospheric O_3 and CO_2 Concentration Changes on Winter Wheat. Part Ⅱ: Simulation Results and Analyses

With the rapid development of industrialization and urbanization, the enrichment of tropospheric ozone and carbon dioxide concentration at striking rates has caused effects on biosphere, especially on crops. It is generally accepted that the increase of CO2 concentration will have obverse effects on plant productivity while ozone is reported as the air pollutant most damaging to agricultural crops and other plants. The Model of Carbon and Nitrogen Biogeochemistry in Agroecosystems (DNDC) was adapted to evaluate simultaneously impacts of climate change on winter wheat. Growth development and yield formation of winter wheat under different O3 and CO2 concentration conditions are simulated with the improved DNDC model whose structure has been described in another paper. Through adjusting the DNDC model applicability, winter wheat growth and development in Gucheng Station were simulated well in 1993 and 1999, which is in favor of modifying the model further. The model was validated against experiment observation, including development stage data, leaf area index, each organ biomass, and total aboveground biomass. Sensitivity tests demonstrated that the simulated results in development stage and biomass were sensitive to temperature change. The main conclusions of the paper are the following: 1) The growth and yield of winter wheat under CO2 concentration of 500 ppmv, 700 ppmv and the current ozone concentration are simulated respectively by the model. The results are well fitted with the observed data of OTCs experiments. The results show that increase of CO2 concentration may improve the growth of winter wheat and elevate the yield. 2) The growth and yield of winter wheat under O3 concentration of 50 ppbv, 100 ppbv, 200 ppbv and the based concentration CO2 are simulated respectively by the model. The simulated curves of stem, leaf, and spike organs growth as well as leaf area index are well accounted with the observed data. The results reveal that ozone has negative effects on the growth and yield of winter wheat. Ozone accelerates the process of leaf senescence and causes yield loss. Under very high ozone concentration, crops are damaged dramatically and even dead. 3) At last, by the model possible effects of air temperature change and combined effects of O3 and CO2 are estimated respectively. The results show that doubled CO2 concentration may alleviate negative effect of O3 on biomass and yield of winter wheat when ozone concentration is about 70-80 ppbv. The obverse effects of CO2 are less than the adverse effects of O3 when the concentration of ozone is up to 100 ppbv. Future work should determine whether it can be applied to other species by adjusting the values of related parameters, and whether the model can be adapted to predict ozone effects on crops in farmland environment.     

Numerical Simulation Study on the Impacts of Tropospheric O3 and CO2 Concentration Changes on Winter Wheat. Part II: Simulation Results and Analyses

With the rapid development of industrialization and urbanization, the enrichment of tropospheric ozone and carbon dioxide concentration at striking rates has caused effects on biosphere, especially on crops. It is generally accepted that the increase of CO2 concentration will have obverse effects on plant productivity while ozone is reported as the air pollutant most damaging to agricultural crops and other plants. The Model of Carbon and Nitrogen Biogeochemistry in Agroecosystems (DNDC) was adapted to evaluate simultaneously impacts of climate change on winter wheat. Growth development and yield formation of winter wheat under different O3 and CO2 concentration conditions are simulated with the improved DNDC model whose structure has been described in another paper. Through adjusting the DNDC model applicability, winter wheat growth and development in Gucheng Station were simulated well in 1993 and 1999, which is in favor of modifying the model further. The model was validated against experiment observation, including development stage data, leaf area index, each organ biomass, and total aboveground biomass. Sensitivity tests demonstrated that the simulated results in development stage and biomass were sensitive to temperature change. The main conclusions of the paper are the following: 1) The growth and yield of winter wheat under CO2 concentration of 500 ppmv, 700 ppmv and the current ozone concentration are simulated respectively by the model. The results are well fitted with the observed data of OTCs experiments. The results show that increase of CO2 concentration may improve the growth of winter wheat and elevate the yield. 2) The growth and yield of winter wheat under O3 concentration of 50 ppbv, 100 ppbv, 200 ppbv and the based concentration CO2 are simulated respectively by the model. The simulated curves of stem, leaf, and spike organs growth as well as leaf area index are well accounted with the observed data. The results reveal that ozone has negative e ects on the growth and yield of winter wheat. Ozone accelerates the process of leaf senescence and causes yield loss. Under very high ozone concentration, crops are damaged dramatically and even dead. 3) At last, by the model possible effects of air temperature change and combined effects of O3 and CO2 are estimated respectively. The results show that doubled CO2 concentration may alleviate negative effect of O3 on biomass and yield of winter wheat when ozone concentration is about 70-80 ppbv. The obverse effects of CO2 are less than the adverse effects of O3 when the concentration of ozone is up to 100 ppbv. Future work should determine whether it can be applied to other species by adjusting the values of related parameters, and whether the model can be adapted to predict ozone e ects on crops in farmland environment.     

Numerical Simulation Study on the Impacts of Tropospheric O3 and CO2 Concentration Changes on Winter Wheat.Part I: Model Description

Ozone is well documented as the air pollutant most damaging to agricultural crops and other plants.It is reported that tropospheric O3 concentration increases rapidly in recent 20 years. Evaluating and predicting impacts of ozone concentration changes on crops are drawing great attention in the scientific community. In China, main study method about this filed is controlled experiments, for example, Open Top Chambers. But numerical simulation study about impacts of ozone on crops with crop model was developed slowly, what is more, the study about combined impacts of ozone and carbon dioxide has not been reported.The improved agroecosystem model is presented to evaluate simultaneously impacts of tropospheric O3 and CO2 concentration changes on crops in the paper by integrating algorithms about impacts of ozone on photosynthesis with an existing agroecosystem biogeochemical model (named as DNDC). The main physiological processes of crop growth (phenology, leaf area index, photosynthesis, respiration, assimilated allocation and so on) in the former DNDC are kept. The algorithms about impacts of ozone on photosynthesis and winter wheat leaf are added in the modified DNDC model in order to reveal impacts of ozone and carbon dioxide on growth, development, and yield formation of winter wheat by coupling the simulation about impacts of carbon dioxide on photosynthesis of winter wheat which exists in the former DNDC. In the paper, firstly assimilate allocation algorithms and some genetic parameters (such as daily thermal time of every development stage) were modified in order that DNDC can be applicable in North China. Secondly impacts of ozone on crops were simulated with two different methods-one was impacts of ozone on light use efficiency , and the other was direct effects of ozone on leaves photosynthesis. The latter simulated results are closer to experiment measurements through comparing their simulating results. At last the method of direct impacts of ozone on leaf growth is adopted and the coe cients about impacts of ozone on leaf growth and death are ascertained. Effects of climate changes, increasing ozone, and carbon dioxide concentration on agroecosystem are tried to be simulated numerically in the study which is considered to be advanced and credible.     

Numerical Simulation Study on the Impacts of Tropospheric and CO_2 Concentration Changes on Winter Wheat. Part I: Model Description

Ozone is well documented as the air pollutant most damaging to agricultural crops and other plants. It is reported that tropospheric O3 concentration increases rapidly in recent 20 years. Evaluating and predicting impacts of ozone concentration changes on crops are drawing great attention in the scientific community. In China, main study method about this filed is controlled experiments, for example, Open Top Chambers. But numerical simulation study about impacts of ozone on crops with crop model was developed slowly, what is more, the study about combined impacts of ozone and carbon dioxide has not been reported. The improved agroecosystem model is presented to evaluate simultaneously impacts of tropospheric O3 and CO2 concentration changes on crops in the paper by integrating algorithms about impacts of ozone on photosynthesis with an existing agroecosystem biogeochemical model (named as DNDC). The main physiological processes of crop growth (phenology, leaf area index, photosynthesis, respiration, assimilated allocation and so on) in the former DNDC are kept. The algorithms about impacts of ozone on photosynthesis and winter wheat leaf are added in the modified DNDC model in order to reveal impacts of ozone and carbon dioxide on growth, development, and yield formation of winter wheat by coupling the simulation about impacts of carbon dioxide on photosynthesis of winter wheat which exists in the former DNDC. In the paper, firstly assimilate allocation algorithms and some genetic parameters (such as daily thermal time of every development stage) were modified in order that DNDC can be applicable in North China. Secondly impacts of ozone on crops were simulated with two different methods- one was impacts of ozone on light use efficiency, and the other was direct effects of ozone on leaves photosynthesis. The latter simulated results are closer to experiment measurements through comparing their simulating results. At last the method of direct impacts of ozone on leaf growth is adopted and the coefficients about impacts of ozone on leaf growth and death are ascertained. Effects of climate changes, increasing ozone, and carbon dioxide concentration on agroecosystem are tried to be simulated numerically in the study which is considered to be advanced and credible.     

MM5 Simulations of the China Regional Climate During the LGM.Ⅰ: Influence of CO2 and Earth Orbit Change

Using a regional climate model MM5 nested to an atmospheric global climate model CCM3, a series of simulations and sensitivity experiments have been performed to investigate the relative Last Glacial Maximum (LGM) climate response to different mechanisms over China. Model simulations of the present day (PD) climate and the LGM climate change are in good agreement with the observation data and geological records, especially in the simulation of precipitation change. Under the PD and LGM climate, changes of earth orbital parameters have a small influence on the annual mean temperature over China.However, the magnitude of the effect shows a seasonal pattern, with a significant response in winter. Thus,this influence cannot be neglected. During the LGM, CO2 concentration reached its lowest point to 200 ppmv. This results in a temperature decrease over China. The influences of CO2 concentration on climate show seasonal and regional patterns as well, with a significant influence in winter. On the contrary, CO2concentration has less impact in summer season. In some cases, temperature even increases with decreasing in CO2 concentration. This temperature increase is the outcome of decrease in cloud amount; hence increase the solar radiation that reached the earth's surface. This result suggests that cloud amount plays a very important role in climate change and could direct the response patterns of some climate variables such as temperature during certain periods and over certain regions. In the Tibetan Plateau, the temperature responses to changes of the above two factors are generally weaker than those in other regions because the cloud amount in this area is generally more than in the other areas. Relative to the current climate, changes in orbital parameters have less impact on the LGM climate than changes in CO2 concentration. However,both factors have rather less contributions to the climate change in the LGM. About 3%-10% changes in the annual mean temperature are contributed by CO2.     

MM5 Simulations of the China Regional Climate During the LGM.I: In uence of CO2 and Earth Orbit Change

Using a regional climate model MM5 nested to an atmospheric global climate model CCM3, a series of simulations and sensitivity experiments have been performed to investigate the relative Last Glacial Maximum (LGM) climate response to different mechanisms over China. Model simulations of the present day (PD) climate and the LGM climate change are in good agreement with the observation data and geological records, especially in the simulation of precipitation change. Under the PD and LGM climate,changes of earth orbital parameters have a small influence on the annual mean temperature over China.However, the magnitude of the effect shows a seasonal pattern, with a significant response in winter. Thus,this influence cannot be neglected. During the LGM, CO2 concentration reached its lowest point to 200 ppmv. This results in a temperature decrease over China. The influences of CO2 concentration on climate show seasonal and regional patterns as well, with a signi cant influence in winter. On the contrary, CO2 concentration has less impact in summer season. In some cases, temperature even increases with decreasing in CO2 concentration. This temperature increase is the outcome of decrease in cloud amount; hence increase the solar radiation that reached the earth's surface. This result suggests that cloud amount plays a very important role in climate change and could direct the response patterns of some climate variables such as temperature during certain periods and over certain regions. In the Tibetan Plateau, the temperature responses to changes of the above two factors are generally weaker than those in other regions because the cloud amount in this area is generally more than in the other areas. Relative to the current climate, changes in orbital parameters have less impact on the LGM climate than changes in CO2 concentration. However,both factors have rather less contributions to the climate change in the LGM. About 3%-10% changes in the annual mean temperature are contributed by CO2.     

First-order impacts on winter and summer crops assessed with various high-resolution climate models in the Iberian Peninsula

The first-order or initial agricultural impacts of climate change in the Iberian Peninsula were evaluated by linking crop simulation models to several high-resolution climate models (RCMs). The RCMs provided the daily weather data for control, and the A2 and B2 IPCC scenarios. All RCMs used boundary conditions from the atmospheric general circulation model (AGCM) HadAM3 while two were also bounded to two other AGCMs. The analyses were standardised to control the sources of variation and uncertainties that were added in the process. Climatic impacts on wheat and maize of climate were derived from the A2 scenario generated by RCMs bounded to HadAM3. Some results derived from B2 scenarios are included for comparisons together with impacts derived from RCMs using different boundary conditions. Crop models were used as impact models and yield was used as an indicator that summarised the effects of climate to quantify initial impacts and differentiate among regions. Comparison among RCMs was made through the choice of different crop management options. All RCM-crop model combinations detected crop failures for winter wheat in the South under control and future scenarios, and projected yield increases for spring wheat in northern and high altitude areas. Although projected impacts differed among RCMs, similar trends emerged for relative yields for some regions. RCM-crop model outputs compared favourably to others using European Re-Analysis data (ERA-15), establishing the feasibility of using direct daily outputs from RCM for impact analysis. Uncertainties were quantified as the standard deviation of the mean obtained for all RCMs in each location and differed greatly between winter (wheat) and summer (maize) seasons, being smaller in the latter.     

气候变化对我国小麦发育及产量可能影响的模拟研究

利用随机天气模型, 将气候模式对大气中CO₂倍增时预测的气候情景与CERES-小麦模式相连接, 研究了气候变化对我国冬小麦和春小麦生产的可能影响.结果表明, 气候变化后小麦发育将加快, 生育期缩短, 冬小麦平均缩短7.3天, 春小麦平均缩短10.5天, 春小麦生育期缩短的绝对数和相对数均大于冬小麦.籽粒产量呈下降趋势, 冬小麦平均减产7%~8%, 雨养条件下比水分适宜时减产幅度略大.春小麦的减产幅度大于冬小麦, 水分适宜时平均减产17.7%, 雨养时平均减产31.4%.     

Climate Change Impacts on the Potential Productivity of Corn and Winter Wheat in Their Primary United States Growing Regions

We calculate the impacts of climate effects inferred from three atmospheric general circulation models (GCMs) at three levels of climate change severity associated with change in global mean temperature (GMT) of 1.0, 2.5 and 5.0 °C and three levels of atmospheric CO2 concentration ([CO2]) – 365 (no CO2 fertilization effect), 560 and 750 ppm – on the potential production of dryland winter wheat (Triticum aestivum L.) and corn (Zea mays L.) for the primary (current) U.S. growing regions of each crop. This analysis is a subset of the Global Change Assessment Model (GCAM) which has the goal of integrating the linkages and feedbacks among human activities and resulting greenhouse gas emissions, changes in atmospheric composition and resulting climate change, and impacts on terrestrial systems. A set of representative farms was designed for each of the primary production regions studied and the Erosion Productivity Impact Calculator (EPIC) was used to simulate crop response to climate change. The GCMs applied were the Goddard Institute of Space Studies (GISS), the United Kingdom Meteorological Transient (UKTR) and the Australian Bureau of Meteorological Research Center (BMRC), each regionalized by means of a scenario generator (SCENGEN). The GISS scenarios have the least impact on corn and wheat production, reducing national potential production for corn by 6% and wheat by 7% at a GMT of 2.5 °C and no CO2 fertilization effect; the UKTR scenario had the most severe impact on wheat, reducing production by 18% under the same conditions; BMRC had the greatest negative impact on corn, reducing production by 20%. A GMT increase of 1.0°C marginally decreased corn and wheat production. Increasing GMT had a detrimental impact on both corn and wheat production, with wheat production suffering the greatest losses. Decreases for wheat production at GMT 5.0 and [CO2] = 365 ppm range from 36% for the GISS to 76% for the UKTR scenario. Increases in atmospheric [CO2] had a positive impact on both corn and wheat production. AT GMT 1.0, an increase in [CO2] to 560 ppm resulted in a net increase in corn and wheat production above baseline levels (from 18 to 29% for wheat and 2 to 5% for corn). Increases in [CO2] help to offset yield reductions at higher GMT levels; in most cases, however, these increases are not sufficient to return crop production to baseline levels.