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.     

Simple indices of global climate variability and change Part II: attribution of climate change during the twentieth century

Five simple indices of surface temperature are used to investigate the influence of anthropogenic and natural (solar irradiance and volcanic aerosol) forcing on observed climate change during the twentieth century. These indices are based on spatial fingerprints of climate change and include the global-mean surface temperature, the land-ocean temperature contrast, the magnitude of the annual cycle in surface temperature over land, the Northern Hemisphere meridional temperature gradient and the hemispheric temperature contrast. The indices contain information independent of variations in global-mean temperature for unforced climate variations and hence, considered collectively, they are more useful in an attribution study than global mean surface temperature alone. Observed linear trends over 1950–1999 in all the indices except the hemispheric temperature contrast are significantly larger than simulated changes due to internal variability or natural (solar and volcanic aerosol) forcings and are consistent with simulated changes due to anthropogenic (greenhouse gas and sulfate aerosol) forcing. The combined, relative influence of these different forcings on observed trends during the twentieth century is investigated using linear regression of the observed and simulated responses of the indices. It is found that anthropogenic forcing accounts for almost all of the observed changes in surface temperature during 1946–1995. We found that early twentieth century changes (1896–1945) in global mean temperature can be explained by a combination of anthropogenic and natural forcing, as well as internal climate variability. Estimates of scaling factors that weight the amplitude of model simulated signals to corresponding observed changes using a combined normalized index are similar to those calculated using more complex, optimal fingerprint techniques.     

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     

Testing for linear Granger causality from?natural/anthropogenic forcings to global temperature anomalies

In this paper, we analyze the Granger causality from natural or anthropogenic forcings to global temperature anomalies. The lag-augmented Wald test is performed, and its robustness is also evaluated considering bootstrap method. The results show there is no-evidence of Granger causality from natural forcings to global temperature. On the contrary, a detectable Granger causality is found from anthropogenic forcings to global temperature confirming that greenhouse gases have an important role on recent global warming.     

Impact of Direct Radiative Forcing of Anthropogenic Aerosols on Diurnal Temperature Range in January in Eastern China

This study investigates the changes in January diurnal temperature range(DTR) in China during 1961-2000.The observed DTR changes during 1981-2000 relative to 1961-80 are first analyzed based on the daily temperature data at 546 weather stations.These observed DTR changes are classified into six cases depending on the changes in daily maximum and minimum temperatures,and then the occurrence frequency and magnitude of DTR change in each case are presented.Three transient simulations are then performed to understand the impact of greenhouse gases(GHGs) and aerosol direct forcing on DTR change:one without anthropogenic radiative forcing,one with anthropogenic GHGs,and another one with the combined forcing of GHGs and five species of anthropogenic aerosols.The predicted daily DTR changes during the years 1981-2000 are also classified into six cases and are compared with the observations.Results show that the previously proposed reason for DTR reduction,a stronger nocturnal warming than a daytime warming,explains only 19.8%of the observed DTR reduction days.DTR reductions are found to generally occur in northeastern China,coinciding with significant regional warming.The simulation with GHG forcing alone reproduces this type of DTR reduction with an occurrence frequency of 32.9%,which is larger than the observed value.Aerosol direct forcing reduces DTR mainly by daytime cooling.Consideration of aerosol cooling improves the simulation of occurrence frequencies of different types of DTR changes as compared to the simulation with GHGs alone,but it cannot improve the prediction of the magnitude of DTR changes.     

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。     

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.     

Direct Radiative Forcing of Anthropogenic Aerosols over Oceans from Satellite Observations

Anthropogenic aerosols play an important role in the atmospheric energy balance. Anthropogenic aerosol optical depth (AOD) and its accompanying shortwave radiative forcing (RF) are usually simulated by nu- merical models. Recently, with the development of space-borne instruments and sophisticated retrieval algorithms, it has become possible to estimate aerosol radiative forcing based on satellite observations. In this study, we have estimated shortwave direct radiative forcing due to anthropogenic aerosols over oceans in all-sky conditions by combining clouds and the Single Scanner Footprint data of the Clouds and Earth’s Radiant Energy System (CERES/SSF) experiment, which provide measurements of upward shortwave fluxes at the top of atmosphere, with Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol and cloud products. We found that globally averaged aerosol radiative forcing over oceans in the clear-sky conditions and all-sky conditions were -1.03±0.48 W m-2 and -0.34 ±0.16 W m-2, respectively. Direct radiative forcing by anthropogenic aerosols shows large regional and seasonal variations. In some regions and in particular seasons, the magnitude of direct forcing by anthropogenic aerosols can be comparable to the forcing of greenhouse gases. However, it shows that aerosols caused the cooling effect, rather than warming effect from global scale, which is different from greenhouse gases.     

Impact of the Montreal protocol and its amendments on the rate of change of global radiative forcing

Increases in chlorinated and brominated halocarbons are believed to be responsible for the depletion of stratospheric ozone observed over much of the globe in the past decade or so. Ozone depletion is in turn believed to lead to a negative radiative forcing, tending to cool the stratosphere and the surface. We show that the increasing atmospheric concentrations of ozone-depleting halocarbons and onset of related ozone depletion likely led to a negative forcing of the climate system in the 1980s that slowed significantly the rate of change of total anthropogenic radiative forcing due to the combined effect of all greenhouse gases over that decade. Within the next decade, emissions of these halocarbons are expected to rapidly decrease, with corresponding impacts on ozone and radiative forcing. As the emissions of ozone-depleting gases are reduced and eventually phased out, the rate of ozone depletion is expected to decrease and eventually reverse. All other things being equal, we show that the change from deepening ozone depletion in the 1980s to ozone increases in the future should lead to a pronounced increase in the decadal rate of change of anthropogenic greenhouse forcing of the next few decades, perhaps to levels unprecedented in this century.     

Contributions of solar and greenhouse gases forcing during the present warm period

Due to the dramatic increase in the global mean surface temperature (GMST) during the twentieth century, the climate science community has endeavored to determine which mechanisms are responsible for global warming. By analyzing a millennium simulation (the period of 1000–1990 ad) of a global climate model and global climate proxy network dataset, we estimate the contribution of solar and greenhouse gas forcings on the increase in GMST during the present warm period (1891–1990 ad). Linear regression analysis reveals that both solar and greenhouse gas forcing considerably explain the increase in global mean temperature during the present warm period, respectively, in the global climate model. Using the global climate proxy network dataset, on the other hand, statistical approach suggests that the contribution of greenhouse gas forcing is slightly larger than that of solar forcing to the increase in global mean temperature during the present warm period. Overall, our result indicates that the solar forcing as well as the anthropogenic greenhouse gas forcing plays an important role to increase the global mean temperature during the present warm period.     

A probabilistic quantification of the anthropogenic component of twentieth century global warming

This paper examines in detail the statement in the 2007 IPCC Fourth Assessment Report that “Most of the observed increase in global average temperatures since the mid-twentieth century is very likely due to the observed increase in anthropogenic greenhouse gas concentrations”. We use a quantitative probabilistic analysis to evaluate this IPCC statement, and discuss the value of the statement in the policy context. For forcing by greenhouse gases (GHGs) only, we show that there is a greater than 90 % probability that the expected warming over 1950–2005 is larger than the total amount (not just “most”) of the observed warming. This is because, following current best estimates, negative aerosol forcing has substantially offset the GHG-induced warming. We also consider the expected warming from all anthropogenic forcings using the same probabilistic framework. This requires a re-assessment of the range of possible values for aerosol forcing. We provide evidence that the IPCC estimate for the upper bound of indirect aerosol forcing is almost certainly too high. Our results show that the expected warming due to all human influences since 1950 (including aerosol effects) is very similar to the observed warming. Including the effects of natural external forcing factors has a relatively small impact on our 1950–2005 results, but improves the correspondence between model and observations over 1900–2005. Over the longer period, however, externally forced changes are insufficient to explain the early twentieth century warming. We suggest that changes in the formation rate of North Atlantic Deep Water may have been a significant contributing factor.     

气候变化和人类活动对中国东部季风区水循环影响的检测和归因

水文循环过程受气候变化与人类活动的共同作用,区分气候内部自然变率与人类活动作用于水循环贡献对于增加气候变化的理解非常重要。本研究利用近期发展的考虑地下水取用水与灌溉影响的全球陆气耦合模式进行数值模拟,基于最优指纹法分析探讨中国东部季风区黄河、淮河、海河、珠江、长江、松花江流域水循环变化(地表温度、降水、径流、蒸散发)及归因。结果表明:大部分流域的地表温度年际变化在1965~2005年间检测到包括温室气体气溶胶人为排放、臭氧与土地利用变化产生的外强迫效应,显示在长期对于地表温度起主要作用的可能为上述强迫;1965~2005年降水年际变化仅在淮河及长江下游检测到上述强迫效应,且在长江下游效应占主导。在1965~1984年间,地表温度的年际变化在海河流域检测到由于地下水取水灌溉产生的外强迫效应,并且该效应占主导。在1982~2005年径流年际变化中,在淮河、长江下游及黄河下游处检测到了由于温室气体排放、气溶胶人为排放、臭氧变化及土地利用变化等产生的外强迫效应但无法有效分离,显示该信号在这些地区可能不为主导效应;1982~2005年间的蒸散发年际变化在珠江、长江下游同样检测到了上述强迫效应,并且该效应在长江下游占主导效应。     

The expectation of future precipitation change over the Mediterranean region is different from what we observe

In this study we assess the role of anthropogenic forcing (greenhouse gases and sulphate aerosols, GS) in recently observed precipitation trends over the Mediterranean region. We investigate whether the observed precipitation trends (1966–2005 and 1979–2008) are consistent with what 22 models project as response of precipitation to GS forcing. Significance is estimated using 9,000-year control runs derived from the CMIP3 archive. The results indicate that externally forced changes are detectable in observed precipitation trends in winter, late summer and in autumn. Natural internal climate variability cannot explain these changes. However, the observed trends (derived from 3 sources) are markedly inconsistent with expected changes due to GS forcing. While the influence of GS signal is detectable in winter and early spring, observed changes are several times larger than the projected response to GS forcing. The most striking inconsistency, however, is the contradiction between projected drying and the observed increase in precipitation in late summer and autumn, irrespective of the data set used. Natural (internal) variability as estimated from the models cannot account for these inconsistencies, which are already present in the large scale circulation patterns (Geopotential height at 500 hPa). The obtained results are robust to the removal of the fingerprint of the North Atlantic Oscillation. The detection of an outright sign mismatch of observed and projected trends in autumn and late summer, leads us to conclude that the recently observed trends can not be used as an illustration of plausible future expected change in the Mediterranean region. These significant shortcomings in our understanding of recent observed changes complicate communication of future expected changes in Mediterranean precipitation.     

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.     

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.     

Natural and anthropogenic climate change: incorporating historical land cover change,vegetation dynamics and the global carbon cycle

This study explores natural and anthropogenic influences on the climate system, with an emphasis on the biogeophysical and biogeochemical effects of historical land cover change. The biogeophysical effect of land cover change is first subjected to a detailed sensitivity analysis in the context of the UVic Earth System Climate Model, a global climate model of intermediate complexity. Results show a global cooling in the range of –0.06 to –0.22 °C, though this effect is not found to be detectable in observed temperature trends. We then include the effects of natural forcings (volcanic aerosols, solar insolation variability and orbital changes) and other anthropogenic forcings (greenhouse gases and sulfate aerosols). Transient model runs from the year 1700 to 2000 are presented for each forcing individually as well as for combinations of forcings. We find that the UVic Model reproduces well the global temperature data when all forcings are included. These transient experiments are repeated using a dynamic vegetation model coupled interactively to the UVic Model. We find that dynamic vegetation acts as a positive feedback in the climate system for both the all-forcings and land cover change only model runs. Finally, the biogeochemical effect of land cover change is explored using a dynamically coupled inorganic ocean and terrestrial carbon cycle model. The carbon emissions from land cover change are found to enhance global temperatures by an amount that exceeds the biogeophysical cooling. The net effect of historical land cover change over this period is to increase global temperature by 0.15 °C.     

Projected 21st century snowfall changes over the French Alps and related uncertainties

Snowfall changes in mountain areas in response to anthropogenic forcing could have widespread hydrological, ecological and economic impacts. In this paper, the robustness of snowfall changes over the French Alps projected during the 21st century and the associated uncertainties are studied. In particular, the role of temperature changes on snowfall changes is investigated. Those issues are tackled through the analysis of the results of a very large ensemble of high-resolution regional climate projections, obtained either through dynamical or statistical downscaling. We find that, at the beginning and at the end of the cold season extending from November to March (included), temperature change is an important source of spread in snowfall changes. However, no link is found between temperature and snowfall changes in January and February. At the beginning and at the end of the cold season, the rate of change in snowfall per Kelvin does not depend much on the bias correction step, the period or the greenhouse gas scenario but mostly on the downscaling method and the climate models, the latter uncertainty source being dominant.     

An investigation into the mechanisms of changes in mid-latitude mean sea level pressure as greenhouse gases are increased

When greenhouse gases are increased in coupled GCM experiments there is both a direct effect and an indirect effect due to changes in the surface conditions. In this study we carry out experiments with a perpetual winter atmosphere only model in order to investigate the influence of changes to the surface conditions (sea surface temperatures, sea-ice and snow amount) on the Northern Hemisphere winter mid-latitude mean sea level pressure response. The surface conditions for the perpetual winter model experiments are prescribed from time averages of the HadCM2 control and greenhouse gas experiments. Forcing the perpetual winter model with the HadCM2 greenhouse gas surface conditions produces a negative mean sea level pressure (MSLP) response across both Northern Hemisphere ocean basins, as was found in the coupled model HadCM2 experiment. Additional PW model experiments show that the sea surface temperature forcing from the HadCM2 greenhouse gas experiment dominates the snow and soil moisture content forcings. The sea-ice forcing from the HadCM2 greenhouse gas experiment reduces MSLP at high latitudes. In the north Pacific region MSLP decreases when the global mean warming is applied to the sea surface temperature forcing field at all open sea points. In the north Atlantic region the increased tropics to mid-latitude meridional sea surface temperature gradient is required for MSLP to decrease. These experiments show that the MSLP response in the Northern Hemisphere mid-latitude storm track regions is sensitive to the non-local sea surface temperature anomaly pattern.     

Evaluation of the North Atlantic Oscillation as simulated by a coupled climate model

 The realism of the Hadley Centre’s coupled climate model (HadCM2) is evaluated in terms of its simulation of the winter North Atlantic Oscillation (NAO), a major natural mode of the Northern Hemisphere atmosphere that is currently the subject of considerable scientific interest. During 1400 y of a control integration with present-day radiative forcing levels, HadCM2 exhibits a realistic NAO associated with spatial patterns of sea level pressure, synoptic activity, temperature and precipitation anomalies that are very similar to those observed. Spatially, the main model deficiency is that the simulated NAO has a teleconnection with the North Pacific that is stronger than observed. In a temporal sense the simulation is compatible with the observations if the recent observed trend (from low values in the 1960s to high values in the early 1990s) in the winter NAO index (the pressure difference between Gibraltar and Iceland) is ignored. This recent trend is, however, outside the range of variability simulated by the control integration of HadCM2, implying that either the model is deficient or that external forcing is responsible for the variation. It is shown, by analysing two ensembles, each of four HadCM2 integrations that were forced with historic and possible future changes in greenhouse gas and sulphate aerosol concentrations, that a small part of the recent observed variation may be a result of anthropogenic forcing. If so, then the HadCM2 experiments indicate that the anthropogenic effect should reverse early next century, weakening the winter pressure gradient between Gibraltar and Iceland. Even combining this anthropogenic forcing and internal variability cannot explain all of the recent observed variations, indicating either some model deficiency or that some other external forcing is partly responsible. Received: 20 August 1998 / Accepted: 12 May 1999     

Detecting a Global Warming Signal in Hemispheric Temperature Series: AStructural Time Series Analysis

Non-stationary time series such as global andhemispheric temperatures, greenhouse gasconcentrations, solar irradiance, and anthropogenicsulfate aerosols, may contain stochastic trends (thesimplest stochastic trend is a random walk) which, dueto their unique patterns, can act as a signal of theinfluence of other variables on the series inquestion. Two or more series may share a commonstochastic trend, which indicates that either oneseries causes the behavior of the other or that thereis a common driving variable. Recent developments ineconometrics allow analysts to detect and classifysuch trends and analyze relationships among seriesthat contain stochastic trends. We apply someunivariate autoregression based tests to evaluate thepresence of stochastic trends in several time seriesfor temperature and radiative forcing. The temperatureand radiative forcing series are found to be ofdifferent orders of integration which would cast doubton the anthropogenic global warming hypothesis.However, these tests can suffer from size distortionswhen applied to noisy series such as hemispherictemperatures. We, therefore, use multivariatestructural time series techniques to decomposeNorthern and Southern Hemisphere temperatures intostochastic trends and autoregressive noise processes. These results show that there are two independentstochastic trends in the data. We investigate thepossible origins of these trends using a regressionmethod. Radiative forcing due to greenhouse gases andsolar irradiance can largely explain the common trend.The second trend, which represents the non-scalarnon-stationary differences between the hemispheres,reflects radiative forcing due to tropospheric sulfateaerosols. We find similar results when we use the sametechniques to analyze temperature data generated bythe Hadley Centre GCM SUL experiment.