Multi-Year Simulations and Experimental Seasonal Predictions for Rainy Seasons in China by Using a Nested Regional Climate Model (RegCM_NCC) Part Ⅱ:The Experimental Seasonal Prediction

A nested regional climate model has been experimentally used in the seasonal prediction at the China National Climate Center （NCC） since 2001. The NCC/IAP （Institute of Atmospheric Physics） T63 coupled GCM （CGCM） provides the boundary and initial conditions for driving the regional climate model （RegCM_NCC）. The latter has a 60-km horizontal resolution and improved physical parameterization schemes including the mass flux cumulus parameterization scheme, the turbulent kinetic energy closure scheme （TKE） and an improved land process model （LPM）. The large-scale terrain features such as the Tibetan Plateau are included in the larger domain to produce the topographic forcing on the rain-producing systems. A sensitivity study of the East Asian climate with regard to the above physical processes has been presented in the first part of the present paper. This is the second part, as a continuation of Part Ⅰ. In order to verify the performance of the nested regional climate model, a ten-year simulation driven by NCEP reanalysis datasets has been made to explore the performance of the East Asian climate simulation and to identify the model＇s systematic errors. At the same time, comparative simulation experiments for 5 years between the RegCM2 and RegCM_NCC have been done to further understand their differences in simulation performance. Also, a ten-year hindcast （1991-2000） for summer （June-August）, the rainy season in China, has been undertaken. The preliminary results have shown that the RegCM_NCC is capable of predicting the major seasonal rain belts. The best predicted regions with high anomaly correlation coefficient （ACC） are located in the eastern part of West China, in Northeast China and in North China, where the CGCM has maximum prediction skill as well. This fact may reflect the importance of the largescale forcing. One significant improvement of the prediction derived from RegCM_NCC is the increase of ACC in the Yangtze River valley where the CGCM has a very low, even a negative, ACC. The reason behind this improvement is likely to be related to the more realistic representation of the large-scale terrain features of the Tibetan Plateau. Presumably, many rain-producing systems may be generated over or near the Tibetan Plateau and may then move eastward along the Yangtze River basin steered by upper-level westerly airflow, thus leading to enhancement of rainfalls in the mid and lower basins of the Yangtze River. The real-time experimental predictions for summer in 2001, 2002, 2003 and 2004 by using this nested RegCM-NCC were made. The results are basically reasonable compared with the observations.

SIMULATION OF PRESENT CLIMATE OVER EAST ASIA BY A REGIONAL CLIMATE MODEL

A 15-year simulation of climate over East Asia is conducted with the latest version of a regional climate model RegCM3 nested in one-way mode to the ERA40 Re-analysis data. The performance of the model in simulating present climate over East Asia and China is investigated. Results show that RegCM3 can reproduce well the atmospheric circulation over East Asia. The simulation of the main distribution patterns of surface air temperature and precipitation over China and their seasonal cycle/evolution, are basically agree with that of the observation. Meanwhile a general cold bias is found in the simulation. As for the precipitation, the model tends to overestimate the precipitation in northern China while underestimate it in southern China, particularly in winter. In general, the model has better performance in simulating temperature than precipitation.

Global Climate Internal Variability in a 2000-year Control Simulation with Community Earth System Model(CESM)

Using the low-resolution （T31, equivalent to 3.75°× 3.75°） version of the Community Earth System Model （CESM） from the National Center for Atmospheric Research （NCAR）, a global climate simulation was carried out with fixed external forcing factors （1850 Common Era. （C.E.） conditions） for the past 2000 years. Based on the simulated results, spatio-temporal structures of surface air temperature, precipitation and internal variability, such as the E1 Nifio-Southem Oscillation （ENSO）, the Atlantic Multi-decadal Oscilla- tion （AMO）, the Pacific Decadal Oscillation （PDO）, and the North Atlantic Oscillation （NAO）, were compared with reanalysis datasets to evaluate the model performance. The results are as follows： 1） CESM showed a good performance in the long-term simulation and no significant climate drift over the past 2000 years; 2） climatological patterns of global and regional climate changes simulated by the CESM were reasonable compared with the reanalysis datasets; and 3） the CESM simulated internal natural variability of the climate system performs very well. The model not only reproduced the periodicity of ENSO, AMO and PDO events but also the 3-8 years vari- ability of the ENSO. The spatial distribution of the CESM-simulated NAO was also similar to the observed. However, because of weaker total irradiation and greenhouse gas concentration forcing in the simulation than the present, the model performances had some differences from the observations. Generally, the CESM showed a good performance in simulating the global climate and internal natu- ral variability of the climate system. This paves the way for other forced climate simulations for the past 2000 years by using the CESM.

The CMIP6 Historical Simulation Datasets Produced by the Climate System Model CAMS-CSM

This paper describes the historical simulations produced by the Chinese Academy of Meteorological Sciences(CAMS)climate system model(CAMS-CSM),which are contributing to phase 6 of the Coupled Model Intercomparison Project(CMIP6).The model description,experiment design and model outputs are presented.Three members’historical experiments are conducted by CAMS-CSM,with two members starting from different initial conditions,and one excluding the stratospheric aerosol to identify the effect of volcanic eruptions.The outputs of the historical experiments are also validated using observational data.It is found that the model can reproduce the climatological mean states and seasonal cycle of the major climate system quantities,including the surface air temperature,precipitation,and the equatorial thermocline.The long-term trend of air temperature and precipitation is also reasonably captured by CAMS-CSM.There are still some biases in the model that need further improvement.This paper can help the users to better understand the performance and the datasets of CAMS-CSM.

Simulation of Climate Change Induced by CO_2 Increasing for East Asia with IAP/ LASG GOALS Model

Two simulations, one for the control run and another for the perturbation run, with a global coupled ocean-atmosphere-land system model (IAP/LASG GOALS version 4) have been carried out to study the global warming, with much detailed emphasis on East Asia. Results indicate that there is no climate drift in the control run and at the time of CO, doubling the global temperature increases about 1.65 degreesC. The GOALS model is able to simulate the observed spatial distribution and annual cycles of temperature and precipitation for East Asia quite well. But, in general, the model underestimates temperature and overestimates rainfall amount for regional annual average. For the climate change in East Asia, the temperature and precipitation in East Asia increase 2.1 degreesC and 5% respectively, and the maximum warming occurs at middle-latitude continent and the maximum precipitation increase occurs around 25 degreesN with reduced precipitation in the tropical western Pacific.

Steric Sea Level Change in Twentieth Century Historical Climate Simulation and IPCC-RCP8.5 Scenario Projection: A Comparison of Two Versions of FGOALS Model

To reveal the steric sea level change in 20th century historical climate simulations and future climate change projections under the IPCC＇s Representative Concentration Pathway 8.5 （RCP8.5） scenario, the results of two versions of LASG/IAP＇s Flexible Global Ocean-Atmosphere-Land System model （FGOALS） are analyzed. Both models reasonably reproduce the mean dynamic sea level features, with a spatial pattern correlation coefficient of 0.97 with the observation. Characteristics of steric sea level changes in the 20th century historical climate simulations and RCPS.5 scenario projections are investigated. The results show that, in the 20th century, negative trends covered most parts of the global ocean. Under the RCPS.5 scenario, global-averaged steric sea level exhibits a pronounced rising trend throughout the 21st century and the general rising trend appears in most parts of the global ocean. The magnitude of the changes in the 21st century is much larger than that in the 20th century. By the year 2100, the global-averaged steric sea level anomaly is 18 cm and 10 cm relative to the year 1850 in the second spectral version of FGOALS （FGOALS-s2） and the second grid-point version of FGOALS （FGOALS-g2）, respectively. The separate contribution of the thermosteric and halosteric components from various ocean layers is further evaluated. In the 20th century, the steric sea level changes in FGOALS-s2 （FGOALS-g2） are largely attributed to the thermosteric （halosteric） component relative to the pre-industrial control run. In contrast, in the 21st century, the thermosteric component, mainly from the upper 1000 m, dominates the steric sea level change in both models under the RCPS.5 scenario. In addition, the steric sea level change in the marginal sea of China is attributed to the thermosteric component.

Applications and verification of a computational energy dynamics model for mine climate simulations

A complete thermodynamic model is described for temperature and heat flow distribution simulation for ventilation networks in underground mines.The method is called the Computational Energy Dynamics(CED)model of the heat,mass,and energy transport.The Thermal and Humidity(TH)transport elements of the full model are described for advection,convection,and accumulation,encompassing heat capacity,radiation,latent heat for evaporation,and condensation in the airways,as well as variable heat conduction and accumulation in the rock strata.The thermal flywheel effect for time-dependent temperature field applications is included in the model solution.A CED model validation exercise is described,directly evaluating the iterated,minimized energy balance errors for the mechanical and thermal energy components for each network branch after a converged solution is determined.A simulation example relevant to mine safety and health is shown with the CED-TH model,demonstrating its capabilities in efficiency and accuracy in comparison with measurement results.

Simulation of Climate Change Induced by CO2 Increasing for East Asia with IAP/ LASG GOALS Model

Two simulations, one for the control run and another for the perturbation run, with a global coupled ocean-atmosphere-land system model(IAP / LASG GOALS version 4) have been carried out to study the global warming, with much detailed emphasis on East Asia. Results indicate that there is no climate drift in the control run and at the time of CO2 doubling the global temperature increases about 1.65℃. The GOALS model is able to simulate the observed spatial distribution and annual cycles of temperature and precipitation for East Asia quite well. But, in general, the model underestimates temperature and overestimates rainfall amount for regional annual average. For the climate change in East Asia, the temperature and precipitation in East Asia increase 2.1 ℃ and 5% respectively, and the maximum warming occurs at middle-latitude continent and the maximum precipitation increase occurs around 25°N with reduced precipitation in the tropical western Pacific.

Antarctic Sea Ice Concentration in the Brazilian Earth System Model Simulations

Sea ice is an important and complex component of the Earth’s system, acting as both an indicator and an amplifier of climate change. Here, we investigated the ability of the Brazilian Earth System Model (BESM-OA2.5) and four state-of-the-art climate models participating in the fifth phase of the Coupled Model Intercomparison Project, Version 5 (CMIP5) to represent the Antarctic Sea Ice Concentration (SIC) seasonal cycle. We validated the sea ice model’s performance using satellite data from 1980 to 2005 and calculated the skill and RMSE of each model. BESM-OA2.5 results for melt-freeze transitions in the Southern Ocean are consistent with CMIP5 models and satellite data. In February, when the sea ice reaches its annual minimum, the BESM-OA2.5 has the best fit among the models. However, in September, when the Antarctic sea ice reaches its annual maximum, the SIC simulated by BESM-OA2.5 indicated the largest area covered by ice compared to satellite, particularly on the Polar Front. Similar results were found in the CMIP5 models evaluated here. We suggest that the large bias simulated in the Polar Front is related to the inability of the sea ice model to represent the complex ocean-atmosphere-sea ice interactions. The subject is considered a hot topic in climate change studies and lacks conclusive answers.

Rainfall-Runoff Modeling and Hydrological Responses to the Projected Climate Change for Upper Baro Basin, Ethiopia

This paper presents the results of Rainfall-Runoff modeling and simulation of hydrological responses under changing climate using HEC-HMS model. The basin spatial data was processed by HEC-GeoHMS and imported to HEC-HMS. The calibration and validation of the HEC-HMS model was done using the observed hydrometeorological data (1989-2018) and HEC-GeoHMS output data. The goodness-of-fit of the model was measured using three performance indices: Nash and Sutcliffe coefficient (NSE) = 0.8, Coefficient of Determination (R2) = 0.8, and Percent Difference (D) = 0.03, with values showing very good performance of the model. Finally, the optimized HEC-HMS model has been applied to simulate the hydrological responses of Upper Baro Basin to the projected climate change for mid-term (2040s) and long-term (2090s) A1B emission scenarios. The simulation results have shown a mean annual percent decrease of 3.6 and an increase of 8.1 for Baro River flow in the 2040s and 2090s scenarios, respectively, compared to the baseline period (2000s). A pronounced flow variation is rather observed on a seasonal basis, reaching a reduction of 50% in spring and an increase of 50% in autumn for both mid-term and long-term scenarios with respect to the base period. Generally, the rainfall-runoff model is developed to solve, in a complementary way, the two main problems in water resources management: the lack of gauged sites and future hydrological response to climate change data of the basin and the region in general. The study results imply that seasonal and time variation in the hydrologic cycle would most likely cause hydrologic extremes. And hence, the developed model and output data are of paramount importance for adaptive strategies and sustainable water resources development in the basin.

Study on the Effects of Land Surface Heterogeneities in Temperature and Moisture on Annual Scale Regional Climate Simulation

The ＂combined approach＂, which is suitable to represent subgrid land surface heterogeneity in both interpatch and intra-patch variabilities, is employed in the BiOsphere/Atmosphere Transfer Scheme （BATS） as a land surface component of the regional climate model RegCM3 to consider the heterogeneities in temperature and moisture at the land surface, and then annual-scale simulations for 5 years （1988-1992） were conducted. Results showed that on the annual scale, the model＇s response to the heterogeneities is quite sensitive, and that the effect of the temperature heterogeneity （TH） is more pronounced than the moisture heterogeneity （MH）. On the intraannual scale, TH may lead to more （less） precipitation in warm （cold） seasons, and hence lead to larger intraannual variability in precipitation; the major MH effects may be lagged by about 1 month during the warm, rainy seasons, inducing -6% more precipitation for some sub-regions. Additionally, the modeled climate for the northern sub-regions shows larger sensitivities to the land surface heterogeneities than those for the southern sub-regions. Since state-of-art land surface models seldom account for surface intra-patch variabilities, this study emphasizes the importance of including this kind of variability in the land surface models.

Numerical Simulation for the Impact of Deforestation on Climate in China and Its Neighboring Regions

In this paper, the CCMOB model is used to study the effect of the deforestation on the climate of China and its neighboring regions. On the assumption that the forest in China would be replaced by the vegetation(such as grassland), the distribution of the albedo changed was calculated. The initial fields used were taken from the FGGE zonal mean data on 16 July, 1979. In the control simulation, the observed albedo data were used to modify the physical parameters of the original model. The control and sensitive experiments were run each for 210 days, in which the external forcing fields were fixed in July. As a result, we find that the East Asian Monsoon, Hadley cell and troposphere easterly jet are weakened for the deforestation in China. The precipitation and cloud amount over China are also decreased. The changes in evaporation and surface temperature are small. The results also show that the deforestation in China exerts a remarkable effect on the climate in the neighboring regions of China.

Simulation of Climate over Xinjiang with RegCM3

To verify the simulating ability of high-resolution regional climate model RegCM3 in Xinjiang,the climate of summer in 2005 was simulated.The specific analysis was directed against simulated temperature and precipitation fields,which were conducted the check analysis by use of the daily data from 102 meteorological stations in Xinjiang.The simulation results of temperature fields showed that RegCM3 model had ability to reflect the spatial distribution characteristics of temperature fields in Xinjiang.However,the regional average temperature had numerically significant 'cold bias' of 4-7 ℃ on the low side on the whole.The model simulated well the features of summer precipitation in Xinjiang.The area of high precipitation was located in Tianshan Mountains.The precipitation simulation of the model was in closer proximity to the measured value in plain areas,but the simulation effect was not so good in mountain areas.

Ventilation and climate simulation with the Multiflux code

Multiflux, a new thermal, hydrologic, and airflow model and software was being employed to solve the flow of heat, moisture, and air in and around an underground opening. The airway domain was solved with an integrated-parameter Computational Fluid Dynamic （CFD） module, which is an embedded part of the Multiflux code. The CFD model includes convection, conduction, and radiation for heat, as well as convection and diffusion for moist-ure transport in an air-filled opening. The surrounding rockmass model may be from any analytical solution, or from a complex thermal-hydrologic numerical model such as NUFT or TOUGH2. The rockmass model is interfaced to Multiflux using a novel technique called Numerical Transport Code Functionalization （NTCF）. The purpose was to briefly describe the Multiflux model and show four example applications. The first example reports the results of Multiflux simulations for a mine drift, comparing calculations with CLIMSIM, a well known mine climate software, and with measured data. The second and third examples involve development ends in two coal mines. Another development-end ventilation model in Multiflux is also shown as the 4th example compared with field measurements from the Lucky Friday Mine in Idaho, USA for comparison.The results of the study show very good agreement between the Multiflux model and the available measured field results.

Simulation of Deep Water Wave Climate for the Indian Seas

The ocean wave climate has a variety of applications in Naval defence.However,a long-term and reliable wave climate for the Indian Seas(The Arabian Sea and The Bay of Bengal)over a desired grid resolution could not be established so far due to several constraints.In this study,an attempt was made for the simulation of wave climate for the Indian Seas using the third-generation wave model(3g-WAM)developed by WAMDI group.The 3g-WAM as such was implemented at NPOL for research applications.The specific importance of this investigation was that,the model utilized a“mean climatic year of winds”estimated using historical wind measurements following statistical and probabilistic approaches as the winds which were considered for this purpose were widely scattered in space and time.Model computations were carried out only for the deep waters with current refraction.The gridded outputs of various wave parameters were stored at each grid point and the spectral outputs were stored at selected locations.Monthly,seasonal and annual distributions of significant wave parameters were obtained by post-processing some of the model outputs.A qualitative validation of simulated wave height and period parameters were also carried out by comparing with the observed data.The study revealed that the results of the wave climate simulation were quite promising and they can be utilized for various operational and ocean engineering applications.Therefore,this study will be a useful reference/demonstration for conducting such experiments in the areas where wind as well as wave measurements are insufficient.

Sensitivity Study of the RegCM4’s Surface Schemes in the Simulations of West Africa Climate

Two simulations of five years (2003-2007) were conducted with the Regional Climate models RegCM4, one coupled with Land surface models BATS and the other with CLM4.5 over West Africa, where simulated air temperature and precipitation were analyzed. The purpose of this study is to assess the performance of RegCM4 coupled with the new CLM4.5 Land surface scheme and the standard one named BATS in order to find the best configuration of RegCM4 over West African. This study could improve our understanding of the sensitivity of land surface model in West Africa climate simulation, and provide relevant information to RegCM4 users. The results show fairly realistic restitution of West Africa’s climatology and indicate correlations of 0.60 to 0.82 between the simulated fields (BATS and CLM4.5) for precipitation. The substitution of BATS surface scheme by CLM4.5 in the model configuration, leads mainly to an improvement of precipitation over the Atlantic Ocean, however, the impact is not sufficiently noticeable over the continent. While the CLM4.5 experiment restores the seasonal cycles and spatial distribution, the biases increase for precipitation and temperature. Positive biases already existing with BATS are amplified over some sub-regions. This study concludes that temporal localization (seasonal effect), spatial distribution (grid points) and magnitude of precipitation and temperature (bias) are not simultaneously improved by CLM4.5. The introduction of the new land surface scheme CLM4.5, therefore, leads to a performance of the same order as that of BATS, albeit with a more detailed formulation.

Zero-Energy-Buildings in Different Climates： Design Strategies, Simulation and Prognosis METHOD for Energy Demand

The European Directive 2010/31 claims that by 2020 only （nearly-） ZEB （zero-energy-buildings） may be built. To reach this goal, it is pertinent for buildings to be energetically optimized first. The remaining energy demand must then be covered by on-site renewable energies （PV, geothermal, etc.）. With the area of use （energy demand） and the size of the building envelope/estate （renewable energy supply） in competition with each other, the maximum number of building stories will be most likely limited. For 15 different climatic locations worldwide, the energy demand of optimised office rooms has been simulated and compared with the possible renewable energy production on site. For every location, a good correlation has been found between the simulated energy demand and data like heating and cooling degree hours. Correspondent linear equations are given here. As another result, the maximum numbers of possible stories for ZEBS have been derived, being between 3 and 10 depending on the location.

Biases of the Arctic climate in a regional ocean-sea iceatmosphere coupled model: an annual validation

The Coupling of three model components, WRF/PCE （polar climate extension version of weather research and forecasting model （WRF））, ROMS （regional ocean modeling system）, and CICE （community ice code）, has been implemented, and the regional atmosphere-ocean-sea ice coupled model named WRF/PCE- ROMS-CICE has been validated against ERA-interim reanalysis data sets for 1989. To better understand the reasons that generate model biases, the WRF/PCE-ROMS-CICE results were compared with those of its components, the WRF/PCE and the ROMS-CICE. There are cold biases in surface air temperature （SAT） over the Arctic Ocean, which contribute to the sea ice concentration （SIC） and sea surface temperature （SST） biases in the results of the WRF/PCE-ROMS-CICE. The cold SAT biases also appear in results of the atmo- spheric component with a mild temperature in winter and similar temperature in summer. Compared to results from the WRF/PCE, due to influences of different distributions of the SIC and the SST and inclusion of interactions of air-sea-sea ice in the WRF/PCE-ROMS-CICE, the simulated SAT has new features. These influences also lead to apparent differences at higher levels of the atmosphere, which can be thought as responses to biases in the SST and sea ice extent. There are similar atmospheric responses in feature of distribution to sea ice biases at 700 and 500 hPa, and the strength of responses weakens when the pressure decreases in January. The atmospheric responses in July reach up to 200 hPa. There are surplus sea ice ex- tents in the Greenland Sea, the Barents Sea, the Davis Strait and the Chukchi Sea in winter and in the Beau- fort Sea, the Chukchi Sea, the East Siberian Sea and the Laptev Sea in summer in the ROMS-CICE. These differences in the SIC distribution can all be explained by those in the SST distributions. These features in the simulated SST and SIC from ROMS-CICE also appear in the WRF/PCE-ROMS-CICE. It is shown that the performance of the WRF/PCE-ROMS-CICE is determined to a large extent by its components, the WRF/PCE and the ROMS-CICE.

Direct Climatic Effect of Aerosols and Interdecadal Variations over East Asia Investigated by a Regional Coupled Climate-Chemistry/Aerosol Model

The direct climatic effect of aerosols for the 1980-2000 period over East Asia was numerically investigated by a regional scale coupled climate-chemistry/ aerosol model, which includes major anthropogenic aerosols （sulfate, black carbon, and organic carbon） and natural aerosols （soil dust and sea salt）. Anthropogenic emissions used in model simulation are from a global emission inventory prepared for the Intergovernmental Panel on Climate Change Fifth Assessment Report （IPCC AR5）, whereas natural aerosols are calculated online in the model. The simulated 20-year average direct solar radiative effect due to aerosols at the surface was estimated to be in a range of-9- -33 W m-2 over most areas of China, with maxima over the Gobi desert of West China, and-12 W m-2 to -24 W m-2 over the Sichuan Basin, the middle and lower reaches of the Yellow River and the Yangtze River. Aerosols caused surface cooling in most areas of East Asia, with maxima of-0.8℃ to -1.6℃ over the deserts of West China, the Sichuan Basin, portions of central China, and the middle reaches of the Yangtze River. Aerosols induced a precipitation decrease over almost the entire East China, with maxima of-90 mm/year to -150 mm/year over the Sichuan Basin, the middle reaches of the Yangtze River and the lower reaches of the Yellow River. Interdecadal variation of the climate response to the aerosol direct radiative effect is evident, indicating larger decrease in surface air temperature and stronger per- turbation to precipitation in the 1990s than that in the 1980s, which could be due to the interdecadal variation of anthropogenic emissions.

Quantifying major sources of uncertainty in projecting the impact of climate change on wheat grain yield in dryland environments

Modelling the impact of climate change on cropping systems is crucial to support policy-making for farmers and stakeholders.Nevertheless,there exists inherent uncertainty in such cases.General Circulation Models(GCMs)and future climate change scenarios(different Representative Concentration Pathways(RCPs)in different future time periods)are among the major sources of uncertainty in projecting the impact of climate change on crop grain yield.This study quantified the different sources of uncertainty associated with future climate change impact on wheat grain yield in dryland environments(Shiraz,Hamedan,Sanandaj,Kermanshah and Khorramabad)in eastern and southern Iran.These five representative locations can be categorized into three climate classes:arid cold(Shiraz),semi-arid cold(Hamedan and Sanandaj)and semi-arid cool(Kermanshah and Khorramabad).Accordingly,the downscaled daily outputs of 29 GCMs under two RCPs(RCP4.5 and RCP8.5)in the near future(2030s),middle future(2050s)and far future(2080s)were used as inputs for the Agricultural Production Systems sIMulator(APSIM)-wheat model.Analysis of variance(ANOVA)was employed to quantify the sources of uncertainty in projecting the impact of climate change on wheat grain yield.Years from 1980 to 2009 were regarded as the baseline period.The projection results indicated that wheat grain yield was expected to increase by 12.30%,17.10%,and 17.70%in the near future(2030s),middle future(2050s)and far future(2080s),respectively.The increases differed under different RCPs in different future time periods,ranging from 11.70%(under RCP4.5 in the 2030s)to 20.20%(under RCP8.5 in the 2080s)by averaging all GCMs and locations,implying that future wheat grain yield depended largely upon the rising CO2 concentrations.ANOVA results revealed that more than 97.22% of the variance in future wheat grain yield was explained by locations,followed by scenarios,GCMs,and their interactions.Specifically,at the semi-arid climate locations(Hamedan,Sanandaj,Kermanshah and Khorramabad),most of the variations arose from the scenarios(77.25%),while at the arid climate location(Shiraz),GCMs(54.00%)accounted for the greatest variation.Overall,the ensemble use of a wide range of GCMs should be given priority to narrow the uncertainty when projecting wheat grain yield under changing climate conditions,particularly in dryland environments characterized by large fluctuations in rainfall and temperature.Moreover,the current research suggested some GCMs(e.g.,the IPSL-CM5B-LR,CCSM4,and BNU-ESM)that made moderate effects in projecting the impact of climate change on wheat grain yield to be used to project future climate conditions in similar environments worldwide.