Comparison of Agricultural Impacts of Climate Change Calculated from High and Low Resolution Climate Change Scenarios: Part I. The Uncertainty Due to Spatial Scale

We investigated the effect of two different spatial scales of climate change scenarios on crop yields simulated by the EPIC crop model for corn, soybean, and wheat, in the central Great Plains of the United States. The effect of climate change alone was investigated in Part I. In Part II (Easterling et al., 2001) we considered the effects ofCO₂ fertilization effects and adaptation in addition to climate change. The scenarios were formed from five years of control and 2 ×CO₂ runs of a high resolution regional climate model (RegCM) and the same from an Australian coarse resolution general circulation model (GCM), which provided the initial and lateral boundary conditions for the regional model runs. We also investigated the effect of two different spatial resolutions of soil input parameters to the crop models. We found that for corn and soybean in the eastern part of the study area, significantly different mean yield changes were calculated depending on the scenario used. Changes in simulated dryland wheat yields in the western areas were very similar, regardless of the scale of the scenario. The spatial scale of soils had a strong effect on the spatial variance and pattern of yields across the study area, but less effect on the mean aggregated yields. We investigated what aspects of the differences in the scenarios were most important for explaining the different simulated yield responses. For instance, precipitation changes in June were most important for corn and soybean in the eastern CSIRO grid boxes. We establish the spatial scale of climate changescenarios as an important uncertainty for climate change impacts analysis.     

CLIMATE CHANGE DUE TO GREENHOUSE EFFECTS IN CHINA AS SIMULATED BY A REGIONAL CLIMATE MODEL-PART I:EVALUATION OF THE MODEL SIMULATIONS*

Impacts of greenhouse effects(2×CO₂) on climate change over China as simulated by a regional climate model have been investigated.The model was based on RegCM2 and is nested in one-way mode within a global coupled atmosphere-ocean model(CSIRO R₂₁L₉ AOGCM).Two multi-year simulations,the control run with normal CO₂ concentration and the sensitivity run with doubled CO₂ concentration are conducted. As Part I of the publications,results of control run of the CSIRO,i.e.its simulation of present climate in China,are analyzed briefly.It shows that the model can basically reproduce the surface air temperature and precipitation pattern over China.Therefore,its outputs can be used to drive the regional model. Analysis of control run of RegCM shows that with a high resolution,the model improves the simulations of surface air temperature and precipitation in China as compared to the CSIRO model, especially for the precipitation.The spatial correlation coefficient between simulated and observed annual temperature increased from 0.83 in the CSIRO to 0.92 in the RegCM and for annual precipitation from 0.48 in the CSIRO to 0.65 in the RegCM.A similar improvement in the RegCM compared to the CSIRO was found in all simulated months.The main improvement for surface temperature is that RegCM can simulate the fine scale structure of temperature caused by topography.RegCM greatly improved the spatial distribution of precipitation by eliminating the virtual precipitation center in central China,which was simulated by many other GCMs.The precipitation simulated by RegCM in North and Northwest China is smaller than that by CSIRO, which makes it closer to the observation.     

温室效应引起的中国区域气候变化的数值模拟Ⅰ:模式对中国气候模拟能力的检验

使用RegCM2区域气候模式单向嵌套澳大利亚CSIRO R21L9全球海-气耦合模式,进行了CO2加倍对中国区域气候变化影响的数值试验研究,分析了控制试验(1×CO2)即模式对中国当代气候的模拟情况.首先给出了全球模式控制试验在中国地区的结果,分析表明它对中国区域的地面气温和降水具有一定的模拟能力,其结果可以用来制作驱动区域气候模式的初始场和侧边界.对RegCM2 5 a时间长度控制试验积分结果的分析与检验表明,区域气候模式由于具有较高的分辨率和较完善的物理过程,它对中国区域地面气温和降水的模拟效果较全球模式有了较大提高,如它模拟的各月气温与实况的相关系数全年12个月的平均由全球模式的0.83提高到0.92,降水由0.48提高到0.65.     

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.     

Climate Scenarios for the Southeastern U.S. Based on GCM and Regional Model Simulations

We analyze the control runs and 2 × CO₂ projections (5-yearlengths) of the CSIRO Mk 2 GCM and the RegCM2 regional climate model, which was nested in the CSIRO GCM, over the Southeastern U.S.; and we present the development of climate scenarios for use in an integrated assessment of agriculture. The RegCM exhibits smaller biases in both maximum and minimum temperature compared to the CSIRO. Domain average precipitation biases are generally negative and relatively small in winter, spring, and fall, but both models produce large positive biases in summer, that of the RegCM being the larger. Spatial pattern correlations of the model control runs and observations show that the RegCM reproduces better than the CSIRO the spatial patterns of precipitation, minimum and maximum temperature in all seasons. Under climate change conditions, the most salient feature from the point of view of scenarios for agriculture is the large decreases in summer precipitation, about 20% in the CSIRO and 30% in the RegCM. Increases in springprecipitation are found in both models, about 35% in the CSIRO and 25% in theRegCM. Precipitation decreases of about 20% dominate in winter in the CSIRO,while a more complex pattern of increases and decreases is exhibited by the regional model. Temperature increases by 3 to 5 °C in the CSIRO, the higher values dominating in winter and spring. In the RegCM, temperature increases are much more spatially and temporally variable, ranging from 1 to 7 °C acrossall months and grids. In summer large increases (up to 7 °C) in maximum temperature are found in the northeastern part of the domain where maximum drying occurs.     

区域气候模式对温室效应引起的中国地区气候变化的数值模拟

利用基于 ＲｅｇＣＭ２的区域气候模式并单向嵌套澳大利亚 ＣＳＩＲＯ Ｒ２１Ｌ９全球海－气耦合模式，进行了温室气体二氧化碳浓度倍增对中国气候变化影响的数值试验研究。控制试验结果表明：区域模式由于具有较高的分辨率，因而对中国区域地面气温和降水的模拟效果较全球模式有了较大提高；模式对 ２×ＣＯ２敏感性试验结果表明了在 ＣＯ２浓度倍增情况下，由于温室效应，中国区域的地面气温将有明显升高，降水也将呈增加趋势。     

An Overview of BCC Climate System Model Development and Application for Climate Change Studies

This paper reviews recent progress in the development of the Beijing Climate Center Climate System Model(BCC-CSM) and its four component models(atmosphere,land surface,ocean,and sea ice).Two recent versions are described:BCC-CSM1.1 with coarse resolution(approximately 2.8125°×2.8125°) and BCC-CSM1.1(m) with moderate resolution(approximately 1.125°×1.125°).Both versions are fully coupled climate-carbon cycle models that simulate the global terrestrial and oceanic carbon cycles and include dynamic vegetation.Both models well simulate the concentration and temporal evolution of atmospheric CO_2 during the 20th century with anthropogenic CO2 emissions prescribed.Simulations using these two versions of the BCC-CSM model have been contributed to the Coupled Model Intercomparison Project phase five(CMIP5) in support of the Intergovernmental Panel on Climate Change(IPCC) Fifth Assessment Report(AR5).These simulations are available for use by both national and international communities for investigating global climate change and for future climate projections.Simulations of the 20th century climate using BCC-CSMl.l and BCC-CSMl.l(m) are presented and validated,with particular focus on the spatial pattern and seasonal evolution of precipitation and surface air temperature on global and continental scales.Simulations of climate during the last millennium and projections of climate change during the next century are also presented and discussed.Both BCC-CSMl.l and BCC-CSMl.l(m) perform well when compared with other CMIP5 models.Preliminary analyses indicate that the higher resolution in BCC-CSM1.1(m) improves the simulation of mean climate relative to BCC-CSMl.l,particularly on regional scales.     

Improving the Realism of Modeling Agronomic Adaptation to Climate Change: Simulating Technological Substitution

The purpose of the paper is to propose and test a new approach to simulating farmers' agronomic adaptation to climate change based on the pattern of adoption of technological innovation/substitution over time widely described as a S-shaped (or logistic) curve, i.e., slow growth at the beginning followed by accelerating and then decelerating growth, ultimately leading to saturation. The approach we developed is tested using the Erosion Productivity Impact Calculator crop model applied to corn production systems in the southeastern U.S. using a high-resolution climate change scenario. Corn is the most extensively grown crop in the southeastern U.S. The RegCM limited area model nested within the CSIRO general circulation model generated the scenario. We compare corn yield outcomes using this new form of adaptation (logistic) with climatically optimized (clairvoyant) adaptation. The results show logistic adaptation to be less effective than clairvoyant adaptation in ameliorating climate change impacts on yields, although the differences between the two sets of yields are statistically significant in one case only. These results are limited by the reliance on a single scenario of climate change. We conclude that the logistic technique should be tested widely across climate change scenarios, crop species, and geographic areas before a full evaluation of its effect on outcomes is possible.     

Elevation Dependence of Winter Wheat Production in Eastern Washington State with Climate Change: A Methodological Study

Crop growth models, used in climate change impact assessments to project production on a local scale, can obtain the daily weather information to drive them from models of the Earth's climate. General Circulation Models (GCMs), often used for this purpose, provide weather information for the entire globe but often cannot depict details of regional climates especially where complex topography plays an important role in weather patterns. The U.S. Pacific Northwest is an important wheat growing region where climate patterns are difficult to resolve with a coarse scale GCM. Here, we use the PNNL Regional Climate Model (RCM) which uses a sub-grid parameterization to resolve the complex topography and simulate meteorology to drive the Erosion Productivity Impact Calculator (EPIC) crop model. The climate scenarios were extracted from the PNNL-RCM baseline and 2 × CO₂ simulationsfor each of sixteen 90 km² grid cells of the RCM, with differentiation byelevation and without correction for climate biases. The dominant agricultural soil type and farm management practices were established for each grid cell. Using these climate and management data in EPIC, we simulated winter wheat production in eastern Washington for current climate conditions (baseline) and a 2 × CO₂ `greenhouse' scenario of climate change.Dryland wheat yields for the baseline climate averaged 4.52 Mg ha^–1 across the study region. Yields were zero at high elevations where temperatures were too low to allow the crops to mature. The highest yields (7.32 Mgha^–1) occurred at intermediate elevations with sufficientprecipitation and mild temperatures. Mean yield of dryland winter wheat increased to 5.45 Mg ha^–1 for the 2 × CO₂ climate, which wasmarkedly warmer and wetter. Simulated yields of irrigated wheat were generally higher than dryland yields and followed the same pattern but were, of course, less sensitive to increases in precipitation. Increases in dryland and irrigated wheat yields were due, principally, to decreases in the frequency of temperature and water stress. This study shows that the elevation of a farm is a more important determinant of yield than farm location in eastern Washington and that climate changes would affect wheat yields at all farms in the study.     

Climate Change Impacts and Adaptation Strategies in Spring Barley Production in the Czech Republic

The crop model CERES-Barley was used to assess the impacts of increased concentration of atmospheric CO₂ on growth and development of the most important spring cereal in Central and Western Europe, i.e., spring barley, and to examine possible adaptation strategies. Three experimental regions were selected to compare the climate change impacts in various climatic and pedological conditions. The analysis was based on multi-year crop model simulations run with daily weather series obtained by stochastic weather generator and included two yield levels: stressed yields and potential yields. Four climate change scenarios based on global climate models and representing 2 × CO₂ climate were applied. Results: (i) The crop model is suitable for use in the given environment, e.g., the coefficient of determination between the simulated and experimental yields equals 0.88. (ii) The indirect effect related to changed weather conditions is mostly negative. Its magnitude ranges from ?19% to +5% for the four scenarios applied at the three regions. (iii) The magnitude of the direct effect of doubled CO₂ on the stressed yields for the three test sites is 35–55% in the present climate and 25–65% in the 2 × CO₂ climates. (iv) The stressed yields would increase in 2 × CO₂ conditions by 13–52% when both direct and indirect effects were considered. (v) The impacts of doubled CO₂ on potential yields are more uniform throughout the localities in comparison with the stressed yields. The magnitude of the indirect and direct effects ranges from ?1 to ?9% and from +31 to +33%, respectively. Superposition of both effects results in 19–30% increase of the potential yields. (vi) Application of the earlier planting date (up to 60 days) would result in 15–22% increase of the yields in 2 × CO₂ conditions. (vii) Use of a cultivar with longer vegetation duration would bring 1.5% yield increase per one extra day of the vegetation season. (viii) The initial water content in the soil water profile proved to be one of the key elements determining the spring barley yield. It causes the yields to increase by 54–101 kg.ha^?1 per 1% increase of the available soil water content on the sowing day.     

The Sensitivity of Australian Fire Danger to Climate Change

Global climate change, such as that due to the proposed enhanced greenhouseeffect, is likely tohave a significant effect on biosphere-atmosphere interactions, includingbushfire regimes. Thisstudy quantifies the possible impact of climate change on fire regimes byestimating changes infire weather and the McArthur Forest Fire Danger Index (FDI), an index thatis used throughoutAustralia to estimate fire danger. The CSIRO 9-level general circulation model(CSIRO9 GCM)is used to simulate daily and seasonal fire danger for the present Australianclimate and for adoubled-CO₂ climate. The impact assessment includes validation ofthe GCMs daily controlsimulation and the derivation of correction factors which improve theaccuracy of the firedanger simulation. In summary, the general impact of doubled-CO₂is to increase firedanger at all sites by increasing the number of days of very high and extremefire danger.Seasonal fire danger responds most to the large CO₂-induced changesin maximumtemperature.     

Climate Change in Northern Africa: The Past is Not the Future

By using a climate system model of intermediate complexity, we have simulated long-term natural climate changes occurring over the last 9000 years. The paleo-simulations in which the model is driven by orbital forcing only, i.e., by changes in insolation caused by changes in the Earth's orbit, are compared with sensitivity simulations in which various scenarios of increasing atmospheric CO₂ concentration are prescribed. Focussing on climate and vegetation change in northern Africa, we recapture the strong greening of the Sahara in the early and mid-Holocene (some 9000–6000 years ago), and we show that some expansion of grasslandinto the Sahara is theoretically possible, if the atmospheric CO₂ concentration increases well above pre-industrial values and if vegetation growth is not disturbed. Depending on the rate of CO₂ increase, vegetation migration into the Sahara can be rapid, up to 1/10th of the Saharan area per decade, but could not exceed a coverage of 45%. In ourmodel, vegetation expansion into today's Sahara is triggered by an increase in summer precipitation which is amplified by a positive feedback between vegetation and precipitation. This is valid for simulations with orbital forcing and greenhouse-gas forcing. However, we argue that the mid-Holocene climate optimum some 9000 to 6000 years ago with its marked reduction of deserts in northern Africa is not a direct analogue for future greenhouse-gas induced climate change, as previously hypothesized. Not only does the global pattern of climate change differ between the mid-Holocene model experiments and the greenhouse-gas sensitivity experiments, but the relative role of mechanisms which lead to a reduction of the Sahara also changes. Moreover, the amplitude of simulated vegetation cover changes in northern Africa is less than is estimated for mid-Holocene climate.     

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.     

土地利用变化对我国区域气候影响的数值试验

使用RegCM2区域气候模式单向嵌套澳大利亚CSIRO R21L9全球海-气耦合模式,通过将中国区域植被覆盖由理想状况改变为实际状况的数值试验对比分析,探讨了当代中国土地利用变化对中国区域气候的影响,并对结果进行了统计显著性检验。研究表明,土地利用的变化,会导致我国西北等地区年平均降水减少,导致年平均气温在内陆部分地区升高和在沿海个别地区降低,引起许多地方夏季日平均最高气温升高,而冬季日平均最低气温则在我国东部部分地区降低的同时在西北地区升高,土壤湿度的变化表现为大范围的降低。研究同时表明,相同的土地变化在不同的地理环境下引起的气候要素变化有一定的不一致性。     

Simulated Climate Change Effects on Year-Round Water Temperatures in Temperate Zone Lakes

A deterministic, one-dimensional model is presented to simulate daily water temperature profiles and associated ice and snow covers for dimictic and polymictic lakes of the temperate zone. The lake parameters required as model input are surface area (A_s), maximum depth (H_MAX), and Secchi depth (z_s), the latter, used as a measure of light attenuation and trophic state. The model is driven by daily weather data and operates year-round over multiple years. The model has been tested with extensive data (over 5,000 temperature points). Standard error between simulated and measured water temperatures is 1.4°C in the open water season and 0.5°C in the ice cover season. The model is applied to simulate the sensitivity of Minnesota lake water temperature characteristics to climate change. The projected climate changes due to a doubling of atmospheric CO₂ are obtained from the output of the Canadian Climate Center General Circulation Model (CCC GCM) and the Goddard Institute of Space Studies General Circulation Model (GISS GCM). Simulated lake temperature characteristics have been plotted in a coordinate system with a lake geometry ratio (A _s ^0.25 /H_MAX) on one axis and Secchi depth on the other. The lake geometry ratio expresses a lake's susceptibility to stratification. By interpolation, the sensitivity of lake temperature characteristics to changes of water depth and Secchi depth under the projected climate scenarios can therefore be obtained. Selected lake temperature characteristics simulated with past climate conditions (1961–1979) and with a projected 2 × CO₂ climate scenario as input are presented herein in graphical form. The simulation results show that under the 2 × CO₂ climate scenario ice formation is delayed and ice cover period is shortened. These changes cause water temperature modifications throughout the year.     

On the role of resolution and topography in the simulation of East Asia precipitation

Summary In this paper, we investigate the role that horizontal resolution plays in the simulation of East Asia precipitation. Two sets of numerical experiments are performed using the Regional Climate Model (RegCM2) nested in one-way mode within the CSIRO global coupled atmosphere-ocean model. In the first set we use the actual RegCM2 topography at the selected model resolutions, which are 45, 60, 90, 120, 180, 240 and 360 km. In the second set of the experiments, the same coarse CSIRO model topography is used in all simulations using the different resolutions of the first set. The results demonstrate that the simulation of East Asian precipitation improves as the horizontal resolution is increased. Moreover, it is shown that the simulations using a higher resolution along with the coarse CSIRO topography perform better than the simulations using a coarser model resolution with corresponding model topography. This suggests that over East Asia adequate spatial resolution to resolve the physical and dynamical processes is more important than topography. Lastly, the results indicate that model resolutions of 60 km or higher are needed to accurately simulate the distribution of precipitation over China and East Asia.     

Climate Change and Winter Wheat Management: A Modelling Scenario for South-Eastern England

Crop models are useful tools for assessing the impact of climate change on crop production. The dynamic crop-growth model, CERES-Wheat is used to examine crop management responses, including yield, under six climate change scenarios for the years 2025 and 2050 on the Estate of Imperial College at Wye, Kent, U.K. Sensitivity analysis shows a dry matter yield decrease in response to increases in temperature alone. CERES-Wheat was then constrained to assess the crop performance under water-limited production scenarios with different soils, and the results show that crop grain yield actually increases, largely due to CO₂ fertilisation leading to increased rates of photosynthesis. Different management practices (planting dates and nitrogen application) were applied to find the best adaptation strategies. In general, `early' sowing (10th September) had the highest simulated yield, and `late' sowing (10th November) the lowest. For the soils tested, the highest and sustained crop production was obtained from Hamble soils (silt loam) compared with either the Fyfield (sandy) or Denchworth (clay). Adding nitrogen and other fertilisers would likely be necessary to take full advantage of the CO₂ fertilisationeffect and to compensate, in some cases, for yield losses caused by climate change where water shortage becomes serious.     

Climate change mitigation: trade-offs between delay and strength of action required

Climate change mitigation via a reduction in the anthropogenic emissions of carbon dioxide (CO₂) is the principle requirement for reducing global warming, its impacts, and the degree of adaptation required. We present a simple conceptual model of anthropogenic CO₂ emissions to highlight the trade off between delay in commencing mitigation, and the strength of mitigation then required to meet specific atmospheric CO₂ stabilization targets. We calculate the effects of alternative emission profiles on atmospheric CO₂ and global temperature change over a millennial timescale using a simple coupled carbon cycle-climate model. For example, if it takes 50 years to transform the energy sector and the maximum rate at which emissions can be reduced is ?2.5% $\text{year}^{-1}$ , delaying action until 2020 would lead to stabilization at 540 ppm. A further 20 year delay would result in a stabilization level of 730 ppm, and a delay until 2060 would mean stabilising at over 1,000 ppm. If stabilization targets are met through delayed action, combined with strong rates of mitigation, the emissions profiles result in transient peaks of atmospheric CO₂ (and potentially temperature) that exceed the stabilization targets. Stabilization at 450 ppm requires maximum mitigation rates of ?3% to ?5% $\text{year}^{-1}$ , and when delay exceeds 2020, transient peaks in excess of 550 ppm occur. Consequently tipping points for certain Earth system components may be transgressed. Avoiding dangerous climate change is more easily achievable if global mitigation action commences as soon as possible. Starting mitigation earlier is also more effective than acting more aggressively once mitigation has begun.     

Effects of Climate Change on Carbon Storage in Boreal Forests of China: A Local Perspective

The BIOME3 model was used to simulate the distribution patterns and carbon storage of the horizontal, zonal boreal forests in northeast and northwest China using a mapping system for vegetation patterns combined with carbon density estimates from vegetation and soils. The BIOME3 prediction is in reasonable good agreement with the potential distribution of Chinese boreal forests. The effects of changing atmospheric CO₂ concentration had a nonlinear effect on boreal forest distribution, with 3.5–10.8% reduced areas for both increasing and decreasing CO₂. In contrast, the increased climate together with and without changing CO₂ concentration showed dramatic changes in geographic patterns, with 70% reduction in area and disappearance of almost boreal forests in northeast China. The baseline carbon storage in boreal forests of China is 4.60 PgC (median estimate) based on the vegetation area of actual boreal forest distribution. If taking the large area of agricultural crops into account, the median value of potential carbon storage is 6.92 PgC. The increasing (340–500 ppmv) and decreasing CO₂ concentration (340–200 ppmv) led to decrease of carbon storage, 0.33 PgC and 1.01 PgC respectively compared to BIOME3 potential prediction under present climate and CO₂ conditions. Both climate change alone and climate change with CO₂ enrichment (340–500 ppmv) reduced largely the carbon stored in vegetation and soils by ca. 6.5 PgC. The effect of climate change is more significant than the direct physiological effect of CO₂ concentration on the boreal forests of China, showing a large reduction in both distribution area and carbon storage.     

用区域气候模式模拟人为硫酸盐气溶胶在气候变化中的作用

使用新版RegCM2区域气候模式，单向嵌套澳大利亚CSIROR21L9全球海-气耦合模式，在C02加倍情况下引人人为硫酸盐气溶胶直接气候效应，进行了其对中国气候变化影响的试验。结果表明，硫酸盐气溶胶的直接气候效应，对地面气温为降温作用，其中在冬半年和在南方更明显；对降水的影响为全国各月平均降水将以减少为主，年平均降水变化的基本特点为在中国东部以减少为主，西部以增加为主。但无论温度还是降水变化的数值都很小。