A transient climate change simulation with greenhouse gas and aerosol forcing: projected climate to the twenty-first century

 The potential climatic consequences of increasing atmospheric greenhouse gas (GHG) concentration and sulfate aerosol loading are investigated for the years 1900 to 2100 based on five simulations with the CCCma coupled climate model. The five simulations comprise a control experiment without change in GHG or aerosol amount, three independent simulations with increasing GHG and aerosol forcing, and a simulation with increasing GHG forcing only. Climate warming accelerates from the present with global mean temperatures simulated to increase by 1.7 °C to the year 2050 and by a further 2.7 °C by the year 2100. The warming is non-uniform as to hemisphere, season, and underlying surface. Changes in interannual variability of temperature show considerable structure and seasonal dependence. The effect of the comparatively localized negative radiative forcing associated with the aerosol is to retard and reduce the warming by about 0.9 °C at 2050 and 1.2 °C at 2100. Its primary effect on temperature is to counteract the global pattern of GHG-induced warming and only secondarily to affect local temperatures suggesting that the first order transient climate response of the system is determined by feedback processes and only secondarily by the local pattern of radiative forcing. The warming is accompanied by a more active hydrological cycle with increases in precipitation and evaporation rates that are delayed by comparison with temperature increases. There is an “El Nino-like” shift in precipitation and an overall increase in the interannual variability of precipitation. The effect of the aerosol forcing is again primarily to delay and counteract the GHG-induced increase. Decreases in soil moisture are common but regionally dependent and interannual variability changes show considerable structure. Snow cover and sea-ice retreat. A PNA-like anomaly in mean sea-level pressure with an enhanced Aleutian low in northern winter is associated with the tropical shift in precipitation regime. The interannual variability of mean sea-level pressure generally decreases with largest decreases in the tropical Indian ocean region. Changes to the ocean thermal structure are associated with a spin-down of the Atlantic thermohaline circulation together with a decrease in its variability. The effect of aerosol forcing, although modest, differs from that for most other quantities in that it does not act primarily to counteract the GHG forcing effect. The barotropic stream function in the ocean exhibits modest change in the north Pacific but accelerating changes in much of the Southern Ocean and particularly in the north Atlantic where the gyre spins down in conjunction with the decrease in the thermohaline circulation. The results differ in non-trivial ways from earlier equilibrium 2 × CO₂ results with the CCCma model as a consequence of the coupling to a fully three-dimensional ocean model and the evolving nature of the forcing. Received: 24 September 1998 / Accepted: 8 October 1999     

Multi-fingerprint detection and attribution analysis of greenhouse gas, greenhouse gas-plus-aerosol and solar forced climate change

 A multi-fingerprint analysis is applied to the detection and attribution of anthropogenic climate change. While a single fingerprint is optimal for the detection of climate change, further tests of the statistical consistency of the detected climate change signal with model predictions for different candidate forcing mechanisms require the simultaneous application of several fingerprints. Model-predicted climate change signals are derived from three anthropogenic global warming simulations for the period 1880 to 2049 and two simulations forced by estimated changes in solar radiation from 1700 to 1992. In the first global warming simulation, the forcing is by greenhouse gas only, while in the remaining two simulations the direct influence of sulfate aerosols is also included. From the climate change signals of the greenhouse gas only and the average of the two greenhouse gas-plus-aerosol simulations, two optimized fingerprint patterns are derived by weighting the model-predicted climate change patterns towards low-noise directions. The optimized fingerprint patterns are then applied as a filter to the observed near-surface temperature trend patterns, yielding several detection variables. The space-time structure of natural climate variability needed to determine the optimal fingerprint pattern and the resultant signal-to-noise ratio of the detection variable is estimated from several multi-century control simulations with different CGCMs and from instrumental data over the last 136 y. Applying the combined greenhouse gas-plus-aerosol fingerprint in the same way as the greenhouse gas only fingerprint in a previous work, the recent 30-y trends (1966–1995) of annual mean near surface temperature are again found to represent a significant climate change at the 97.5% confidence level. However, using both the greenhouse gas and the combined forcing fingerprints in a two-pattern analysis, a substantially better agreement between observations and the climate model prediction is found for the combined forcing simulation. Anticipating that the influence of the aerosol forcing is strongest for longer term temperature trends in summer, application of the detection and attribution test to the latest observed 50-y trend pattern of summer temperature yielded statistical consistency with the greenhouse gas-plus-aerosol simulation with respect to both the pattern and amplitude of the signal. In contrast, the observations are inconsistent with the greenhouse-gas only climate change signal at a 95% confidence level for all estimates of climate variability. The observed trend 1943–1992 is furthermore inconsistent with a hypothesized solar radiation change alone at an estimated 90% confidence level. Thus, in contrast to the single pattern analysis, the two pattern analysis is able to discriminate between different forcing hypotheses in the observed climate change signal. The results are subject to uncertainties associated with the forcing history, which is poorly known for the solar and aerosol forcing, the possible omission of other important forcings, and inevitable model errors in the computation of the response to the forcing. Further uncertainties in the estimated significance levels arise from the use of model internal variability simulations and relatively short instrumental observations (after subtraction of an estimated greenhouse gas signal) to estimate the natural climate variability. The resulting confidence limits accordingly vary for different estimates using different variability data. Despite these uncertainties, however, we consider our results sufficiently robust to have some confidence in our finding that the observed climate change is consistent with a combined greenhouse gas and aerosol forcing, but inconsistent with greenhouse gas or solar forcing alone. Received: 28 April 1996 / Accepted: 27 January 1997     

Numerical Simulation of Global Temperature Change during the 20th Century with the IAP／LASG GOALS Model

The IAP/LASG GOALS coupled model is used to simulate the climate change during the 20th century using historical greenhouse gases concentrations, the mass mixing ratio of sulfate aerosols simulated by a CTM model, and reconstruction of solar variability spanning the period 1900 to 1997. Four simulations, including a control simulation and three forcing simulations, are conducted. Comparison with the observational record for the period indicates that the three forcing experiments simulate reasonable temporal and spatial distributions of the temperature change. The global warming during the 20th century is caused mainly by increasing greenhouse gas concentration especially since the late 1980s; sulfate aerosols offset a portion of the global warming and the reduction of global temperature is up to about 0.11℃ over the century; additionally, the effect of solar variability is not negligible in the simulation of climate change over the 20th century.     

Greenhouse-gas versus aerosol forcing and African climate response

There are many indicators that human activity may change climate conditions all around the globe through emissions of greenhouse gases. In addition, aerosol particles are emitted from various natural and anthropogenic sources. One important source of aerosols arises from biomass burning, particularly in low latitudes where shifting cultivation and land degradation lead to enhanced aerosol burden. In this study the counteracting effects of greenhouse gases and aerosols on African climate are compared using climate model experiments with fully interactive aerosols from different sources. The consideration of aerosol emissions induces a remarkable decrease in short-wave solar irradiation near the surface, especially in winter and autumn in tropical West Africa and the Congo Basin where biomass burning is mainly prevailing. This directly leads to a modification of the surface energy budget with reduced sensible heat fluxes. As a consequence, temperature decreases, compensating the strong warming signal due to enhanced trace gas concentrations. While precipitation in tropical Africa is less sensitive to the greenhouse warming, it tends to decrease, if the effect of aerosols from biomass burning is taken into account. This is partly due to the local impact of enhanced aerosol burden and partly to modifications of the large-scale monsoon circulation in the lower troposphere, usually lagging behind the season with maximum aerosol emissions. In the model equilibrium experiments, the greenhouse gas impact on temperature stands out from internal variability at various time scales from daily to decadaland the same holds for precipitation under the additional aerosol forcing. Greenhouse gases and aerosols exhibit an opposite effect on daily temperature extremes, resulting in an compensation of the individual responses under the combined forcing. In terms of precipitation, daily extreme events tend to be reduced under aerosol forcing, particularly over the tropical Atlantic and the Congo basin. These results suggest that the simulation of the multiple aerosol effects from anthropogenic sources represents an important factor in tropical climate change, hence, requiring more attention in climate modelling attempts.     

Assessment of CMIP5 global model simulations over the subset of CORDEX domains used in the Phase I CREMA

We present an assessment of the CMIP5 global model simulations over a subset of CORDEX domains used in the Phase I CREMA (CORDEX RegCM hyper-MAtrix) experiment (Africa, HYMEX-MED (Mediterranean), South America, Central America and West Asia). Three variants of the transformed Mielke measure are used to assess (1) the model skill in simulating surface temperature and precipitation historical climatology, (2) the degree of surface temperature and precipitation change occurring under greenhouse gas forcing, and (3) the consistency of a model’s projected change with that of the Multi Model Ensemble (MME) mean. The majority of models exhibit varying degrees of skill depending on the region and season; however, a few models are identified as performing well globally. We find that resolution improves the model skill in most regional and seasonal cases, especially for temperature. Models with the highest and lowest climate sensitivity, as well as those whose change most resembles the ensemble mean are also discussed. Although the higher resolution models perform better, we find that resolution does not have a statistically significant impact on the models’ response to GHG forcing, indicating that model biases do not play a primary role in affecting the model response to GHG forcing. We also assess the three selected models for the CREMA Phase I experiment (HADGEM2ES, MPI-ESMMR and GFDL-ESM2M) and find that they are characterized by a relatively good level of performance, a range of high to low climate sensitivities and a good consistency with the MME changes, thereby providing a reasonably representative sample of the CMIP5 ensemble.     

Future impact of anthropogenic sulfate aerosol on North Atlantic climate

We examine the simulated future change of the North Atlantic winter climate influenced by anthropogenic greenhouses gases and sulfate aerosol. Two simulations performed with the climate model ECHAM4/OPYC3 are investigated: a simulation forced by greenhouse gases and a simulation forced by greenhouse gases and sulfate aerosol. Only the direct aerosol effect on the clear-sky radiative fluxes is considered. The sulfate aerosol has a significant impact on temperature, radiative quantities, precipitation and atmospheric dynamics. Generally, we find a similar, but weaker future climate response if sulfate aerosol is considered additionally. Due to the induced negative top-of-the-atmosphere radiative forcing, the future warming is attenuated. We find no significant future trends in North Atlantic Oscillation (NAO) index in both simulations. However, the aerosol seems to have a balancing effect on the occurence of extreme NAO events. The simulated correlation patterns of the NAO index with temperature and precipitation, respectively, agree well with observations up to the present. The extent of the regions influenced by the NAO tends to be reduced under strong greenhouse gas forcing. If sulfate is included and the warming is smaller, this tendency is reversed. Also, the future decrease in baroclinicity is smaller due to the aerosols’ cooling effect and the poleward shift in track density is partly offset. Our findings imply that in simulations where aerosol cooling is neglected, the magnitude of the future warming over the North Atlantic region is overestimated, and correlation patterns differ from those based on the future simulation including aerosols.     

Quantifying the contributions of anthropogenic and natural forcings to climate changes over arid-semiarid areas during 1946–2005

In this study, the contributions from changes in man-made greenhouse gases (GHG), anthropogenic aerosols (AA), and land use (LU), as well as natural solar and volcanic (NAT) forcing changes, to observed changes in surface air temperature (T) and precipitation (P) over global land, especially over arid-semiarid areas, during 1946–2005 are quantified using observations and climate model simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Results show that the anthropogenic (ANT) forcings dominate the ubiquitous surface warming seen in observations and lead to slight increases in precipitation over most land areas, while the NAT forcing leads to small cooling over land. GHG increases are the primary factor responsible for the anthropogenic climate change, while the AA forcing offsets a large part of the GHG-induced warming and P changes. The LU forcing generally contributes little to the T and P changes from 1946 to 2005 over most land areas. Unlike the consistent temperature changes among most model simulations, precipitation changes display a large spread among the models and are incomparable with the observations in spatial distributions and magnitude, mainly due to its large internal variability that varies among individual model runs. Using an optimal fingerprinting method, we find that the observed warming over land during 1946–2005 can be largely attributed to the ANT forcings, and the combination of the ANT and NAT forcings can explain about 85~95% of the observed warming trend over global land as well as over most arid-semiarid regions such as Northern China. However, the anthropogenic influences on precipitation over the past 60 years are generally undetectable over most land areas, including most arid-semiarid regions. This indicates that internal variability is still larger than the forced change for land precipitation.     

The Canadian Centre for Climate Modelling and Analysis global coupled model and its climate

 A global, three-dimensional climate model, developed by coupling the CCCma second-generation atmospheric general circulation model (GCM2) to a version of the GFDL modular ocean model (MOM1), forms the basis for extended simulations of past, current and projected future climate. The spin-up and coupling procedures are described, as is the resulting climate based on a 200 year model simulation with constant atmospheric composition and external forcing. The simulated climate is systematically compared to available observations in terms of mean climate quantities and their spatial patterns, temporal variability, and regional behavior. Such comparison demonstrates a generally successful reproduction of the broad features of mean climate quantities, albeit with local discrepancies. Variability is generally well-simulated over land, but somewhat underestimated in the tropical ocean and the extratropical storm-track regions. The modelled climate state shows only small trends, indicating a reasonable level of balance at the surface, which is achieved in part by the use of heat and freshwater flux adjustments. The control simulation provides a basis against which to compare simulated climate change due to historical and projected greenhouse gas and aerosol forcing as described in companion publications. Received: 24 September 1998 / Accepted: 8 October 1999     

A GCM study of future climate response to aerosol pollution reductions

We use the global atmospheric GCM aerosol model ECHAM5-HAM to asses possible impacts of future air pollution mitigation strategies on climate. Air quality control strategies focus on the reduction of aerosol emissions. Here we investigate the extreme case of a maximum feasible end-of-pipe abatement of aerosols in the near term future (2030) in combination with increasing greenhouse gas (GHG) concentrations. The temperature response of increasing GHG concentrations and reduced aerosol emissions leads to a global annual mean equilibrium temperature response of 2.18 K. When aerosols are maximally abated only in the Industry and Powerplant sector, while other sectors stay with currently enforced regulations, the temperature response is 1.89 K. A maximum feasible abatement applied in the Domestic and Transport sector, while other sectors remain with the current legislation, leads to a temperature response of 1.39 K. Increasing GHG concentrations alone lead to a temperature response of 1.20 K. We also simulate 2–5% increases in global mean precipitation among all scenarios considered, and the hydrological sensitivity is found to be significantly higher for aerosols than for GHGs. Our study, thus highlights the huge potential impact of future air pollution mitigation strategies on climate and supports the need for urgent GHG emission reductions. GHG and aerosol forcings are not independent as both affect and are influenced by changes in the hydrological cycle. However, within the given range of changes in aerosol emissions and GHG concentrations considered in this study, the climate response towards increasing GHG concentrations and decreasing aerosols emissions is additive.     

Competition of NAO regime changes and increasing greenhouse gases and aerosols with respect to Arctic climate projections

Regional magnitudes and patterns of Arctic winter climate changes in consequence of regime changes of the North Atlantic Oscillation (NAO) are analyzed using a regional atmospheric climate model. The regional model has been driven with data of positive and negative NAO phases from a control simulation as well as from a time-dependent greenhouse gas and aerosol scenario simulation. Both global model simulations include a quite realistic interannual variability of the NAO with pronounced decadal regime changes and no or rather weak long-term NAO trends. The results indicate that the effects of NAO regime changes on Arctic winter temperatures and precipitation are regionally significant over most of northwestern Eurasia and parts of Greenland. In this regard, mean winter temperature variations of up to 6 K may occur over northern Europe. Precipitation and synoptic variability are also regionally modified by NAO regime changes, but not as significantly as temperatures. However, the climate changes associated with the NAO are in some regions clearly stronger than those attributed to enhanced greenhouse gases and aerosols, indicating that projected global changes of the atmospheric composition and internal circulation changes are competing with each other in their importance for the Arctic climate evolution in the near future. The knowledge of the future NAO trend on decadal and longer time scales appears to be vitally important in terms of a regional assessment of climate scenarios for the Arctic.     

气候模式分辨率对气溶胶气候效应模拟结果的影响

气候模式分辨率作为影响模式模拟结果的重要因素,其对气溶胶与云相互作用的影响尚未全面认识。利用公共大气模型CAM5.3在3种分辨率（2°、1°、0.5°）下,分别采用2000年和1850年气溶胶排放情景进行试验,检验提高分辨率是否能改进气候模式的模拟能力,分析不同分辨率下气溶胶气候效应的异同,探索模式分辨率对气溶胶气候效应数值模拟结果的影响。通过观测资料与模式结果对比发现,提高分辨率可以明显改进模式对总云量、云短波辐射强迫的模拟能力,0.5°分辨率下模拟结果与观测更接近,其他变量并无明显改善。在不同分辨率下,全球平均的气溶胶气候效应较为一致,总云量、云水路径均增加,云短波和长波辐射强迫均加强,而云顶的云滴有效半径和降水均减小,地面气温降低。不同分辨率下,气溶胶增加引起的气溶胶光学厚度、云水路径、地面温度、云短波和长波辐射强迫变化的纬向平均分布相似但大小存在差异;而降水和云量变化的纬向分布与大小均存在较大差异,在区域尺度上还存在较大的不确定性。全球平均而言, 0.5°分辨率下气溶胶的间接辐射强迫相比1°分辨率下的结果降低了2.5%,相比2°分辨率下的结果降低了6.4%。提高模式分辨率可以部分改进模式模拟能力,同时,气溶胶的间接效应随着模式分辨率的提高而减弱。但气溶胶引起的云量、降水的变化在不同分辨率下差异较大,存在较大的不确定性。      

The Climate Response to Global Forest Area Changes under Different Warming Scenarios in China

Human activities have notably affected the Earth’s climate through greenhouse gases(GHG), aerosol, and land use/land cover change(LULCC). To investigate the impact of forest changes on regional climate under different shared socioeconomic pathways(SSPs), changes in surface air temperature and precipitation over China under low and medium/high radiative forcing scenarios from 2021 to 2099 are analyzed using multimodel climate simulations from the Coupled Model Intercomparison Project Phase 6(CMIP...     

Optimal detection and attribution of climate change: sensitivity of results to climate model differences

Fingerprint techniques for the detection of anthropogenic climate change aim to distinguish the climate response to anthropogenic forcing from responses to other external influences and from internal climate variability. All these responses and the characteristics of internal variability are typically estimated from climate model data. We evaluate the sensitivity of detection and attribution results to the use of response and variability estimates from two different coupled ocean atmosphere general circulation models (HadCM2, developed at the Hadley Centre, and ECHAM3/LSG from the MPI für Meteorologie and Deutsches Klimarechenzentrum). The models differ in their response to greenhouse gas and direct sulfate aerosol forcing and also in the structure of their internal variability. This leads to differences in the estimated amplitude and the significance level of anthropogenic signals in observed 50-year summer (June, July, August) surface temperature trends. While the detection of anthropogenic influence on climate is robust to intermodel differences, our ability to discriminate between the greenhouse gas and the sulfate aerosol signals is not. An analysis of the recent warming, and the warming that occurred in the first half of the twentieth century, suggests that simulations forced with combined changes in natural (solar and volcanic) and anthropogenic (greenhouse gas and sulfate aerosol) forcings agree best with the observations.     

不同辐射强迫对暖干复合事件强度长期趋势信号检测的影响

本文基于Copula联合概率建立表征暖干复合事件强度的指数,基于单个辐射强迫的地球系统模式大样本模拟试验的结果,使用4种场显著性检验的方法分析了不同辐射强迫下中国区域整体暖干事件强度长期趋势信号的可检测性。结果表明,4种方法得到的结论较为一致,均表明全强迫(自然外强迫和人为外强迫)下中国大部分区域复合事件的强度显著增强,不同集合成员之间的趋势较为一致,表明长期趋势主要受外强迫而非气候系统内部变率影响,其长期趋势的外强迫信号大约出现在2005年。在单个温室气体强迫的模拟试验下,复合事件强度的长期趋势更为明显,主要体现在强度更强并且长期趋势中外强迫信号出现的时间更早(约2000年)。但是在单个气溶胶强迫下,尚检测不到暖干事件强度长期趋势的外强迫信号。进一步分析表明,温度变化是暖干事件强度长期趋势变化的主要贡献因素。温室气体强迫下温度的贡献更大,尤其是在我国西部地区。     

气候变化对东亚沙尘气溶胶影响的数值模拟

使用RegCM3-dust区域气候模式,单向嵌套MIROC3．2-hires全球模式输出结果,在IPCCA1B温室气体排放情景下,对中国及东亚地区进行了当代（1991年-2000年）和未来（2091年-2100年）水平分辨率为50km的气候以及沙尘气溶胶数值模拟试验。结果表明,模式对中国地区地面气温、降水和东亚沙尘气溶胶空间分布模拟较好。未来东亚沙尘气溶胶年平均起沙通量增加2％,其中12月-3月由于地表积雪量的减少而增加,4月-11月由于10m风速的减小而减少,不同强度的强起沙事件同样12月-3月增加,4月-11月减少。年平均沙尘气溶胶柱含量增加14％,其中3月-5月和8月略减少,其它月份增加。沙尘气溶胶引起地面（SRF）负辐射强迫和沙尘源区大气顶（TOA）正辐射强迫、下游地区TOA负辐射强迫,受沙尘气溶胶辐射强迫的影响,地面起沙通量和柱含量减少。     

Projection of future climate change conditions using IPCC simulations, neural networks and Bayesian statistics. Part 2: Precipitation mean state and seasonal cycle in South America

Evaluating the response of climate to greenhouse gas forcing is a major objective of the climate community, and the use of large ensemble of simulations is considered as a significant step toward that goal. The present paper thus discusses a new methodology based on neural network to mix ensemble of climate model simulations. Our analysis consists of one simulation of seven Atmosphere–Ocean Global Climate Models, which participated in the IPCC Project and provided at least one simulation for the twentieth century (20c3m) and one simulation for each of three SRES scenarios: A2, A1B and B1. Our statistical method based on neural networks and Bayesian statistics computes a transfer function between models and observations. Such a transfer function was then used to project future conditions and to derive what we would call the optimal ensemble combination for twenty-first century climate change projections. Our approach is therefore based on one statement and one hypothesis. The statement is that an optimal ensemble projection should be built by giving larger weights to models, which have more skill in representing present climate conditions. The hypothesis is that our method based on neural network is actually weighting the models that way. While the statement is actually an open question, which answer may vary according to the region or climate signal under study, our results demonstrate that the neural network approach indeed allows to weighting models according to their skills. As such, our method is an improvement of existing Bayesian methods developed to mix ensembles of simulations. However, the general low skill of climate models in simulating precipitation mean climatology implies that the final projection maps (whatever the method used to compute them) may significantly change in the future as models improve. Therefore, the projection results for late twenty-first century conditions are presented as possible projections based on the “state-of-the-art” of present climate modeling. First, various criteria were computed making it possible to evaluate the models’ skills in simulating late twentieth century precipitation over continental areas as well as their divergence in projecting climate change conditions. Despite the relatively poor skill of most of the climate models in simulating present-day large scale precipitation patterns, we identified two types of models: the climate models with moderate-to-normal (i.e., close to observations) precipitation amplitudes over the Amazonian basin; and the climate models with a low precipitation in that region and too high a precipitation on the equatorial Pacific coast. Under SRES A2 greenhouse gas forcing, the neural network simulates an increase in precipitation over the La Plata basin coherent with the mean model ensemble projection. Over the Amazonian basin, a decrease in precipitation is projected. However, the models strongly diverge, and the neural network was found to give more weight to models, which better simulate present-day climate conditions. In the southern tip of the continent, the models poorly simulate present-day climate. However, they display a fairly good convergence when simulating climate change response with a weak increase south of 45°S and a decrease in Chile between 30 and 45°S. Other scenarios (A1B and B1) strongly resemble the SRES A2 trends but with weaker amplitudes.     

欧洲地区不同温室气体背景下土地利用/覆盖变化的气候效应

通过温室气体排放和土地利用/覆盖变化,人类活动对气候变化产生显著影响。为了探究在不同温室气体浓度（Greenhouse gas concentration,GHG）背景下,相同的土地利用/覆盖变化（Land Use and Land Cover Change,LULCC）对于欧洲区域气候的影响差异,采用CESM（Community Earth System Model）耦合模式进行了模拟研究。研究发现,在1850年温室气体浓度背景下,土地利用/覆盖变化导致欧洲中东部地区降水显著增加,而在2000年温室气体浓度背景下,土地利用/覆盖变化导致欧洲中东部地区降水减少。温室气体增加后,LULCC导致该地区对流层低层大气环流由辐合变为辐散,气温以及大气水汽含量降低,这些变化能较大程度的改变LULCC对区域降水的净影响力。     

Climate simulations of major estuarine watersheds in the Mid-Atlantic region of the US

To better understand the implications of anthropogenic climate change for three major Mid-Atlantic estuaries (the Chesapeake Bay, the Delaware Bay, and the Hudson River Estuary), we analyzed the regional output of seven global climate models. The simulation given by the average of the models was generally superior to individual models, which differed dramatically in their ability to simulate twentieth-century climate. The model average had little bias in its mean temperature and precipitation and, except in the Lower Chesapeake Watershed, was able to capture the twentieth-century temperature trend. Weaknesses in the model average were too much seasonality in temperature and precipitation, a shift in precipitation’s summer maximum to spring and winter minimum to fall, interannual variability that was too high in temperature and too low in precipitation, and inability to capture the twentieth-century precipitation increase. There is some evidence that model deficiencies are related to land surface parameterizations. All models warmed over the twenty-first century under the six greenhouse gas scenarios considered, with an increase of 4.7 ± 2.0°C (model mean ± 1 standard deviation) for the A2 scenario (a medium-high emission scenario) over the Chesapeake Bay Watershed by 2070–2099. Precipitation projections had much weaker consensus, with a corresponding increase of 3 ± 12% for the A2 scenario, but in winter there was a more consistent increase of 8 ± 7%. The projected climate averaged over the four best-performing models was significantly cooler and wetter than the projected seven-model-average climate. Precipitation projections were within the range of interannual variability but temperature projections were not. The implied research needs are for improvements in precipitation projections and a better understanding of the impacts of warming on streamflow and estuarine ecology and biogeochemistry.     

The modification of greenhouse gas warming by the direct effect of sulphate aerosols

 The Canadian Centre for Climate Modelling and Analysis (CCCma) second generation climate model (GCMII) consists of an atmospheric GCM coupled to mixed layer ocean. It is used to investigate the climate response to a doubling of the CO₂ concentration together with the direct effect of scattering by sulphate aerosols. As expected, the aerosols offset some of the greenhouse gas (GHG) warming; the global annual mean screen temperature change due to doubled CO₂ is 3.4 °C in this model and this is reduced to 2.7 °C when an estimate of the direct effect of anthropogenic sulphate aerosols is included. The pattern of climate response to the comparatively localized aerosol forcing is not itself localized, and it bears a striking resemblance to the response pattern that arises from the globally distributed change in GHG forcing. This “non-local” response to “localized” forcing indicates that the pattern of climate response is determined, to first order, by the overall magnitude of the change in forcing rather than its detailed nature or structure. Feedback processes operating in the system apparently determine this pattern by locally amplifying and suppressing the response to the magnitude of the change in forcing. The influence of the location of the change in forcing is relatively small. These “non-local” and “local” effects of aerosol forcing are characterized and displayed and some of their consequences discussed. Effects on the moisture budget and on the energetics of the global climate are also examined. Received: 10 June 1997 / Accepted: 8 January 1998     

Process, Forcing, and Signal Analysis of Global Mean TemperatureVariations by Means of a Three-Box Energy Balance Model

An analytic solution of an energy balance model (EBM) is presented which can beused as a recursive filter for time series analysis. It is shown that the EBM can reproduce the solution of a coupled atmosphere-ocean general circulation model (AOGCM) experiment. Contrary to the AOGCM, the EBM easily allows for variations in climate sensitivity to satisfy the full range of uncertainty concerned with this parameter. The recursive filter is applied to two natural and two anthropogenic forcing mechanisms which are expressed in terms of heating rate anomaly time series: volcanism, solar activity, greenhouse gases (GHG), and anthropogenic tropospheric aerosols. Thus, we obtain modelled global mean temperature variations as a response to the different forcings and with respect to the uncertainty in the forcing approximations and climate sensitivity. In addition, it is shown that the observed (ENSO-corrected) global mean temperature time series within the period from 1866 to 1997 can be explained by the external forcings which have been considered and an additional white noise forcing. In this way we are able to separate different signals and compare them. As a result, global anthropogenic climate change due to GHG forcing can be detected at a high level of significance without considering spatial patterns of climate change but including natural forcing, which is usually not done. Furthermore, it is shown that solar forcing alone does not lead to significantclimate change, whereas solar and volcanic forcing together lead to a significant natural climate change signal. Anthropogenic climate change due to GHG forcing may partly be masked by anthropogenic aerosol cooling.