Spatial Scale Effects of Climate Scenarios on Simulated Cotton Production in the Southeastern U.S.A.

We examine the effect of climate scenarios generated using results from climate models of different spatial resolution on yields simulated by the deterministic cotton model GOSSYM for the southeastern U.S.A. Two related climate change scenarios were used: a coarse-scale scenario produced from results of a general circulation model (GCM) which also provided the boundary conditions to a regional climate model (RCM), from which a fine-scale scenario was constructed. Cotton model simulations were performed for three cases: climate change alone; climate change and elevatedCO₂; climate change, elevated CO₂ and adaptations to climate change. In general, significant differences in state-average projected yield changes between the coarse and fine-scale scenarios are found for these three cases. In the first two cases, different directions of change are found in some sub-regions. With adaptation, yields substantially increase for both climate scenarios, but more so for the coarse-scale scenario (30%domain-average increase). Under irrigation, yield change differences between the two climate scenarios are small in all three cases, and yields are higher under irrigation ( 35% domain-average increase with adaptation case) compared to dryland conditions. For the climate change alone case, differences in summer water-stress levels explain the contrasts in dryland yield patterns between the coarse and fine-scale climate scenarios.     

U.S. Climate Sensitivity Simulated with the NCEP Regional Spectral Model

10-year continuous U.S. climate simulations were conducted with the Regional Spectral Model (RSM) using boundary conditions from the National Centers for Environmental Prediction/Dept. of Energy reanalyses and the global PCM (Parallel Climate Model) simulations for present day (1986–1996) andfuture (2040–2050) CO₂ concentrations (about a 36% increasedCO₂). In order to examine the influence of physical parameterization differences as well as grid-resolution, fine resolution RSM simulations (50 km) were compared to coarse resolution (180 and 250 km) RSM simulations, which had resolutions comparable to the T62 reanalysis and PCM simulations. During the winter, the fine resolution RSM simulations provided more realistic detail over the western mountains. During the summer, large differences between the RSM and driving PCM simulations were found. Our results with presentCO₂ suggest that most of the differences between the regionalclimate model simulations and the climate simulations driven by the global model used to drive the regional climate model were not due to the finer resolution of the regional climate model but to the different treatment of the physical processes in the two models, especially when the subgrid scale physics was important, like during summer. Compared to the coarse resolution RSM simulation results, on the other hand, the fine resolution RSM simulations did show improved simulation skills especially when a good boundary condition such as the reanalysis was used to drive the RSM. Under increased CO₂, the driving PCM and downscaled RSM simulations exhibitedwarming over all vertical layers and all regions. Both the RSM and PCM had increased precipitation during the winter, but during the summer, the PCM simulation had an overall precipitation increase mainly due to increased subgrid scale convective activity, whereas the RSM simulations exhibited precipitation decreases and the resulting RSM soil moisture became dryer, especially in the U.S. Southwest. Most of differences in the simulated climate change signals were produced by the distinct model physics rather than by differences in grid resolution.     

Regional Climate Change and Uncertainty Analysis based on Four Regional Climate Model Simulations over China

Four sets of climate change simulations at grid spacing of 50 km were conducted over East Asia with two regional climate models driven at the lateral boundaries by two global models for the period 1981–2050. The focus of the study was on the ensemble projection of climate change in the mid-21 st century(2031–50) over China. Validation of each simulation and the ensemble average showed good performances of the models overall, as well as advantages of the ensemble in reproducing present day(1981–2000) December–February(DJF), June–August(JJA), and annual(ANN) mean temperature and precipitation. Significant warming was projected for the mid-21 st century, with larger values of temperature increase found in the northern part of China and in the cold seasons. The ensemble average changes of precipitation in DJF, JJA, and ANN were determined, and the uncertainties of the projected changes analyzed based on the consistencies of the simulations. It was concluded that the largest uncertainties in precipitation projection are in eastern China during the summer season(monsoon precipitation).     

Future Precipitation Extremes in China under Climate Change and Their Physical Quantification Based on a Regional Climate Model and CMIP5 Model Simulations

The atmospheric water holding capacity will increase with temperature according to Clausius-Clapeyron scaling and affects precipitation.The rates of change in future precipitation extremes are quantified with changes in surface air temperature.Precipitation extremes in China are determined for the 21st century in six simulations using a regional climate model,RegCM4,and 17 global climate models that participated in CMIP5.First,we assess the performance of the CMIP5 models and RCM runs in their simulation of extreme precipitation for the current period(RF:1982-2001).The CMIP5 models and RCM results can capture the spatial variations of precipitation extremes,as well as those based on observations:OBS and XPP.Precipitation extremes over four subregions in China are predicted to increase in the mid-future(MF:2039-58)and far-future(FF:2079-98)relative to those for the RF period based on both the CMIP5 ensemble mean and RCM ensemble mean.The secular trends in the extremes of the CMIP5 models are predicted to increase from 2008 to 2058,and the RCM results show higher interannual variability relative to that of the CMIP5 models.Then,we quantify the increasing rates of change in precipitation extremes in the MF and FF periods in the subregions of China with the changes in surface air temperature.Finally,based on the water vapor equation,changes in precipitation extremes in China for the MF and FF periods are found to correlate positively with changes in the atmospheric vertical wind multiplied by changes in surface specific humidity(significant at the p<0.1 level).     

基于一个不同网格相互嵌套的陆气耦合模式的气候模拟研究

将一个大气植被相互作用模式(AVIM)与大气所LASG的R15九层大气环流模式GOALS相耦合．用来模拟多年平均的全球气候状况。AVIM是一个陆地表面陆面和生理过程相互反馈的模型。作为陆气耦合的第一步,暂不考虑AVIM中的生理过程,而首光将其物理过程[相当于通常的SVAT(土壤—植被—大气—传输方案)模型]与大气所LASG的九层大气环流模式耦合起来．其中海洋模式部分不参与积分,海面温度是多年平均的气候伯。考虑到GCM的分辨率较低(7．5°×4．5°)而植被分布必须有较高的分辨率(1.5°×1.5°),采取广大气与地表面粗细网格的嵌套耦合。模式积分15年,取最后10年的平均值作分析。将模拟的气候要素场与观测值和NCEP再分析资料作了比较,气候模拟结果反映了全球环流与温湿场的主要特征,特别是降水和地面气温的模拟效果较好。这为今后气候模式与生物圈的耦合奠定广一个良好的基础。     

新疆地区未来气候变化的区域气候模式集合预估

本文基于一套在5个全球气候模式结果驱动下,RegCM4区域气候模式对东亚25km水平分辨率的集合预估,分析了中、高温室气体典型排放路径(RCP4.5和RCP8.5)下,21世纪不同时期新疆地区的未来气候变化.对模式当代气候模拟结果的检验表明,区域模式的模拟集合(ensR)总体上能够很好地再现当代新疆平均气温、降水和极端...     

一个水文模型与区域气候模式耦合的数值模拟研究(英)

在陆面过程方案中考虑精细的水文模型有助于改善对区域水文及气候的模拟。建立了一个考虑降水及入渗空间非均匀性的水文模型,并将其并入陆面过程方案BATS中。通过区域气候模式耦合模拟试验,得到如下主要结论:陆面水文的模拟对降水及入渗空间非均匀性的考虑非常敏感:考虑入渗非均匀性后,提高了径流系数,这与湿润地区水分平衡的观测结果更一致;入渗非均匀参数化方案的引入对区域水文及气候模拟的影响比降水非均匀参数化方案的引入要大:不透水面积在区域中的考虑所揭示的特征与我国北方干旱化趋势是一致的。     

一个水文模型与区域气候模式耦合的数值模拟研究

在陆面过程方案中考虑精细的水模型有助于改善对区域水及气候的模拟。建立了一个考虑降水及入诊空间非均匀性的水模型，并将其并入陆面过程方案BATS中。通过区域气候模式耦合模拟试验，得到如下主要结论：陆面水的模拟对降水及入渗空间非均匀性的考虑非常敏感；考虑入渗非均匀性后，提高了径流系数，这与湿润地区水分平衡的观测结果更一致；入渗非均匀参数化方案的引入对区域水及气候模拟的影响比降水非均匀参数化方案的引入要大；不透水面积在区域中的考虑所揭示的特征与我国北方干旱化趋势是一致的。     

Mid-Century Ensemble Regional Climate Change Scenarios for the Western United States

To study the impacts of climate change on water resources in the western U.S., global climate simulations were produced using the National Center for Atmospheric Research/Department of Energy (NCAR/DOE) Parallel Climate Model (PCM). The Penn State/NCAR Mesoscale Model (MM5) was used to downscale the PCM control (20 years) and three future(2040–2060) climate simulations to yield ensemble regional climate simulations at 40 km spatial resolution for the western U.S. This paper describes the regional simulations and focuses on the hydroclimate conditions in the Columbia River Basin (CRB) and Sacramento-San Joaquin River (SSJ) Basin. Results based on global and regional simulations show that by mid-century, the average regional warming of 1 to 2.5 °C strongly affects snowpack in the western U.S. Along coastal mountains, reduction in annual snowpack was about70% as indicated by the regional simulations. Besides changes in mean temperature, precipitation, and snowpack, cold season extreme daily precipitation increased by 5 to 15 mm/day (15–20%) along theCascades and the Sierra. The warming resulted in increased rainfall at the expense of reduced snowfall, and reduced snow accumulation (or earlier snowmelt) during the cold season. In the CRB, these changes were accompanied by more frequent rain-on-snow events. Overall, they induced higher likelihood of wintertime flooding and reduced runoff and soil moisture in the summer. Changes in surface water and energy budgets in the CRB and SSJ basin were affected mainly by changes in surface temperature, which were statistically significant at the 0.95 confidence level. Changes in precipitation, while spatially incoherent, were not statistically significant except for the drying trend during summer. Because snow and runoff are highly sensitive tospatial distributions of temperature and precipitation, this study shows that (1) downscaling provides more realistic estimates of hydrologic impacts in mountainous regions such as the western U.S., and (2) despite relatively small changes in temperature and precipitation, changes in snowpack and runoff can be much larger on monthly to seasonal time scales because the effects of temperature and precipitation are integrated over time and space through various surface hydrological and land-atmosphere feedback processes. Although the results reported in this study were derived from an ensemble of regional climate simulations driven by a global climate model that displays low climate sensitivity compared with most other models, climate change was found to significantly affect water resources in the western U.S. by the mid twenty-first century.     

The Effects of Spatial Scale of Climate Scenarios on Economic Assessments: An Example from U.S. Agriculture

The appropriate level of spatial resolution for climate scenarios is a key uncertainty in climate impact studies and regional integrated assessments. To the extent that such uncertainty may affect the magnitude of economic estimates of climate change, it has implications for the public policy debates concerning the efficiency of CO₂ control options. In this article, we investigate the effects that different climate scenario resolutions have on economic estimates of the impacts of future climate changeon agriculture in the United States. These results are derived via a set of procedures and an analytical model that has been used previously in climate change assessments. The results demonstrate that the spatial scale of climate scenarios affects the estimates of both regional changes in crop yields and the economic impact on the agricultural sector as a whole. An assessment based on the finer scale climatological information consistently yielded a less favorable assessment of the implications of climate change. Regional indicators of economic activity were of opposite sign in some regions, based on the scenario scale. Such differences in economic magnitudes or signs are potentially important in examining whether past climate change assessments may misstate the economic consequences of such changes. The results reported here suggest that refinement of the spatial scale of scenarios should be carefully considered in future impacts research.     

区域和全球模式的嵌套技术 及其长期积分试验

将区域模式嵌入澳大利亚CSIRO (Commonwealth Scientific and Industrial Research Organization）的全球模式中,并将其应用于区域模式的长期气候积分试验。模拟结果表明,当区域与全球模式嵌套时,边界吸收问题十分重要,由区域模式得到的高分辨率大尺度环流形式在边界上必须与全球模式提供的强迫一致,同时区域模式必须给出基于模式内部物理过程产生的高分辨信息。因此,在嵌套过程中,必须仔细考虑缓冲区的设置,使大尺度强迫与中尺度特征充分混合,既保持区域模式内外的一致性,又使区域内部中尺度强迫物理过程得到充分发展。将区域模式与澳大利亚CSIRO的9层21波三角形截断谱模式嵌套后,完成了连续3年的区域气候模式积分。模拟结果表明,由于区域模式较好地刻划了区域尺度的地形、下垫面和海岸线分布等的细节特征,模拟的区域气候特征比全球模式有较大的改进,尤其是对季风降水的模拟,区域模式明显改进了全球模式的模拟结果。     

P-σ坐标系区域气候模式与GCM的嵌套试验

将P-σ坐标系区域气候模式与大气环流模式（GCM）单向嵌套，对我国1998年夏季长江流域严重洪涝进行模拟试验，并与GCM的模拟结果进行了比较。试验表明，嵌套的区域气候模式对降水场的模拟结果较GCM的结果有明显的改进，这是由于P-σ坐标系区域气候模式能够更真实地描述地形的动力和热力作用，因而能更准确地模拟青藏高原及其邻近地区的气压系统，在一定程度上弥补了低分辨率的GCM模拟在高原地区的不足，文中指出，与GCM嵌套的区域气候模式比GCM能够更有效地模拟区域气候的变化，尤其是对区域气候性特征比较明显的地区。     

Assessing Winter Wheat Responses to Climate Change Scenarios: A Simulation Study in the U.S. Great Plains

Hard red winter wheat (Triticum aestivum L.) is a major crop in the Great Plains region of the U.S. The goal of this assessment effort was to investigate the influence of two contrasting global climate change projections (U.K. Hadley Center for Climate Prediction and Research and Canadian Centre for Climate Modelling and Analysis) on the yield and percent kernel nitrogen content of winter wheat at three locations in Nebraska. These three locations represent sub-humid and semi arid areas and the transition between these areas and are also representative of major portions of the winter wheat growing areas of the central Great Plains. Climate scenarios based on each of the projections for each location were developed using the LARS-WG weather generator along with data from automated weather stations. CERES-Wheat was used to simulate the responses for two contrasting cultivars of wheat using two sowing dates. The first sowing date represented current sowing dates appropriate for each location. The second sowing date was later and represents the approximate date when the mean air temperature from the climate scenarios is the same as the mean air temperature from the actual climate data at the current sowing dates. The yield and percent kernel nitrogen content using the two climate scenarios generally decrease going from the sub-humid eastern to the semi arid western parts of Nebraska. Results from these simulations indicate that yield and percent kernel nitrogen content using the two climate scenarios could not both be maintained at levels currently simulated. Protein content (directly related to kernel nitrogen content) and end-use quality are the primary determinants for the use of hard red winter wheat in baked goods. Nitrogen management and new cultivars, which can enhance the uptake and translocation of nitrogen, will be proactive steps to meet the challenges of global climate change as represented by these climate scenarios.     

Cluster analysis of Southeastern U.S. climate stations

Summary A two-step cluster analysis of 449 Southeastern climate stations is used to objectively determine general climate clusters (groups of climate stations) for eight southeastern states. The purpose is objectively to define regions of climatic homogeneity that should perform more robustly in subsequent climatic impact models. This type of analysis has been successfully used in many related climate research problems including the determination of corn/climate districts in Iowa (Ortiz-Valdez, 1985) and the classification of synoptic climate types (Davis, 1988).These general climate clusters may be more appropriate for climate research than the standard climate divisions (CD) groupings of climate stations, which are modifications of the agro-economic United States Department of Agriculture crop reporting districts. Unlike the CD's, these objectively determined climate clusters are not restricted by state borders and thus have reduced multicollinearity which makes them more appropriate for the study of the impact of climate and climatic change.With 5 Figures     

Projected Climate Change in the Northwestern Arid Regions of China: An Ensemble of Regional Climate Model Simulations

The projected temperature and precipitationchange under different emissions scenarios using Coupled Model Intercomparison Project Phase 5 models over the northwestern arid regions of China(NWAC) were analyzed using the ensemble of three high-resolution dynamical downscaling simulations: the simulation of the Regional Climate Model version 4.0(Reg CM4) forced by the Beijing Climate Center Climate System Model version 1.1(BCC_CSM1.1); the Hadley Centre Global Environmental Model version 3 regional climate model(Had GEM3-RA) forced by the Atmosphere-Ocean coupled Had GEM version 2(Had GEM2-AO); and the Weather Research and Forecasting(WRF) model forced by the Norwegian community Earth System Model(Nor ESM1-M). Model validation indicated that the multimodel simulations reproduce the spatial and temporal distribution of temperature and precipitation well. The temperature is projected to increase over NWAC under both the 4.5 and 8.5 Representative Concentration Pathways scenarios(RCP4.5 and RCP8.5, respectively) in the middle of the 21 st century, but the warming trend is larger under the RCP8.5 scenario. Precipitation shows a significant increasing trend in spring and winter under both RCP4.5 and RCP8.5; but in summer, precipitation is projected to decrease in the Tarim Basin and Junggar Basin. The regional averaged temperature and precipitation show increasing trends in the future over NWAC; meanwhile, the large variability of the winter mean temperature and precipitation may induce more extreme cold events and intense snowfall events in these regions in the future.     

全球和区域气候模式对中国东部夏季降水季节演变模拟的比较

本文利用全球海气耦合模式(MIRO3.2_hires)和区域气候模式(RegCM3)的模拟结果,分析了东亚地区夏季降水和大气环流的季节演变特征,并与NCEP/DOE再分析资料和降水观测资料进行了对比分析.结果表明,全球和区域气候模式都能反映出中国东部地区夏季平均环流场和降水场气候态分布的基本特征,但全球模式模拟的雨带范...     

Evaporation from Irrigated Lands in Arid Regions as Inferred from the Regional Climate Model and Atmospheric Boundary Layer Model Simulations

The applicability is analyzed of the modeling system consisting of the MGO regional climate model and multilevel atmospheric boundary layer model for the mesoscale climate change evaluation in the regions with irrigated land use. Based on these models, the Aral Sea evolution impact on the spatial distribution of temperature and humidity in the vicinity of irrigated land is assessed. Numerical experiments cover climate evolution during 1979–2011. It is shown that in the middle of the 20th century the Aral Sea impact was manifested in the temperature and humidity distributions up to the altitude of 200–300 m at the distance of about 40 km off the seashore. The effect of advection on the calculated values of evapotranspiration in irrigated areas located at different distances from the sea is also investigated. Different methods for the determination of evapotranspiration over the irrigated cotton fields are intercompared. The influence of different resolution of surface temperature distribution on total evapotranspiration estimates is analyzed.     

MM5 Simulations of the China Regional Climate During the Mid-Holocene

Using a regional climate model MM5 nested with an atmospheric global climate model CCM3, a series of simulations and sensitivity experiments have been performed to investigate responses of the mid-Holocene climate to different factors over China. Model simulations of the mid-Holocene climate change, especially the precipitation change, are in good agreement with the geologic records. Model results show that relative to the present day (PD) climate, the temperature over China increased in the mid-Holocene, and the increase in summer is more than that in winter. The summer monsoon strengthened over the eastern China north of 30°N, and the winter monsoon weakened over the whole eastern China; the precipitation increased over the west part of China, North China, and Northeast China, and decreased over the south part of China.The sensitive experiments indicate that changes in the global climate (large-scale circulation background),vegetation, earth orbital parameter, and CO2 concentration led to the mid-Holocene climate change relative to the PD climate, and changes in precipitation, temperature and wind fields were mainly affected by change of the large-scale circulation background, especially with its effect on precipitation exceeding 50%. Changes in vegetation resulted in increasing of temperature in both winter and summer over China, especially over eastern China; furthermore, its effect on precipitation in North China accounts for 25% of the total change.Change in the orbital parameter produced the larger seasonal variation of solar radiation in the mid-Holocene than the PD, which resulted in declining of temperature in winter and increasing in summer; and also had an important effect on precipitation with an effect equivalent to vegetation in Northeast China and North China. During the mid-Holocene, CO2 content was only 280×10-6, which reduced temperature in a very small magnitude. Therefore, factors affecting the mid-Holocene climate change over China from strong to weak are large-scale circulation pattern, vegetation, earth orbital parameter, and CO2 concentration.     

初、边值条件对区域气候模拟的影响

利用区域气候模式(RegCM2)对1998年夏季风气候进行了模拟,并就初、边值条件对模拟结果的影响情况进行了讨论,结果表明:该模式可以较好地模拟出月际尺度的气候变化,但对降水异常的模拟还需作进一步完善.通过在几个季节采用不同初始场进行的数值模拟发现,从春季开始的积分其结果对初始场的敏感性较高,初始场的差别会对后期模拟产生明显影响.相对来说,从冬季开始的积分,其对初始场的依赖性较小,初始场的差别会在积分过程中逐渐减小,因而在利用RegCM2进行区域气候模拟时宜从冬季开始.另外,通过对采用不同侧边界嵌套方案的模拟效果进行简单讨论,发现当采用较少的缓冲区(5圈)时,海绵边界对温度、比湿及位势高度的模拟要比指数松弛及流入流出边界好,降水的模拟也要比其他方案好一些,但对风场的模拟则不如指数松弛方案.     

U.S. Agriculture and Climate Change: New Results

We examined the impacts on U.S. agriculture of transient climate change assimulated by 2 global general circulation models focusing on the decades ofthe 2030s and 2090s. We examined historical shifts in the location of cropsand trends in the variability of U.S. average crop yields, finding thatnon-climatic forces have likely dominated the north and westward movement ofcrops and the trends in yield variability. For the simulated future climateswe considered impacts on crops, grazing and pasture, livestock, pesticide use,irrigation water supply and demand, and the sensitivity to international tradeassumptions, finding that the aggregate of these effects were positive for theU.S. consumer but negative, due to declining crop prices, for producers. Weexamined the effects of potential changes in El Niño/SouthernOscillation (ENSO) and impacts on yield variability of changes in mean climateconditions. Increased losses occurred with ENSO intensity and frequencyincreases that could not be completely offset even if the events could beperfectly forecasted. Effects on yield variability of changes in meantemperatures were mixed. We also considered case study interactions ofclimate, agriculture, and the environment focusing on climate effects onnutrient loading to the Chesapeake Bay and groundwater depletion of theEdward's Aquifer that provides water for municipalities and agriculture to theSan Antonio, Texas area. While only case studies, these results suggestenvironmental targets such as pumping limits and changes in farm practices tolimit nutrient run-off would need to be tightened if current environmentalgoals were to be achieved under the climate scenarios we examined