Potential Role of Solar Variability as an Agent for Climate Change

Numerical experiments have been carried out with a two-dimensional sector averaged global climate model in order to assess the potential impact of solar variability on the Earth's surface temperature from 1700 to 1992. This was done by investigating the model response to the variations in solar radiation caused by the changes in the Earth's orbital elements, as well as by the changes intrinsic to the Sun. In the absence of a full physical theory able to explain the origin of the observed total solar irradiance variations, three different total solar irradiance reconstructions have been used. A total solar irradiance change due to the photospheric effects incorporated in the Willson and Hudson (1988) parameterization, and the newly reconstructed solar total irradiance variations from the solar models of Hoyt and Schatten (1993) and Lean et al. (1995). Our results indicate that while the influence of the orbital forcing on the annual and global mean surface temperature is negligible at the century time scale, the monthly mean response to this forcing can be quite different from one month to another. The modelled global warming due to the three investigated total solar irradiance reconstructions is insufficient to reproduce the observed 20th century warming. Nevertheless, our simulated surface temperature response to the changes in the Sun's radiant energy output suggests that the Gleissberg cycle (88 years) solar forcing should not be neglected in explaining the century-scale climate variations. Finally, spectral analysis seems to point out that the 10- to 12-year oscillations found in the recorded Northern Hemisphere temperature variations from 1700 to 1992 could be unrelated to the solar forcing. Such a result could indicate that the eleven-year period which is frequently found in climate data might be related to oscillations in the atmosphere or oceans, internal to the climate system.     

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.     

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.     

Variability and predictability of Northeast China climate during 1948–2012

In this work, authors examine the variabilities of precipitation and surface air temperature (T2m) in Northeast China during 1948–2012, and their global connection, as well as the predictability. It is noted that both the precipitation and T2m variations in Northeast China are dominated by interannual and higher frequency variations. However, on interdecadal time scales, T2m is shifted significantly from below normal to above normal around 1987/1988. Statistically, the seasonal mean precipitation and T2m are largely driven by local internal atmospheric variability rather than remote forcing. For the precipitation variation, circulation anomalies in the low latitudes play a more important role in spring and summer than in autumn and winter. For T2m variations, the associated sea surface pressure (SLP) and 850-hPa wind (uv850) anomalies are similar for all seasons in high latitudes with significantly negative correlations for SLP and westerly wind anomaly for uv850, suggesting that a strong zonal circulation in the high latitudes favors warming in Northeast China. The predictability of precipitation and T2m in Northeast China is assessed by using the Atmospheric Model Inter-comparison Project type experiments which are forced by observed sea surface temperature (SST) and time-evolving greenhouse gas (GHG) concentrations. Results suggest that T2m has slightly higher predictability than precipitation in Northeast China. To some extent, the model simulates the interdecadal shift of T2m around 1987/1988, implying a possible connection between SST (and/or GHG forcing) and surface air temperature variation in Northeast China on interdecadal time scales. Nevertheless, the precipitation and T2m variations are mainly determined by the unpredictable components which are caused by the atmospheric internal dynamic processes, suggesting low predictability for the climate variation in Northeast China.     

Application of solar max ACRIM data to analysis of solar-driven climatic variability on Earth

Climatic change caused by solar variability has been proposed for at least a century, but could not be assessed reliably in the past because the uncertainty in solar irradiance measured from the Earth's surface is too large. Now satellite measurements by such instruments as the Active Cavity Radiometer Irradiance Monitor (ACRIM) permit a preliminary assessment. The satellite data exhibit irradiance variations over a spectrum of shorter timescales, but the first 5-yr overall trend indicates slightly decreasing luminosity. The global temperature response to monthly-mean ACRIM-measured fluctuations from 1980–1984 was computed from the NYU 1D transient climate model - which includes thermal inertia effects of the world oceans - starting from an assumed pre-existing steady state, and the results compared with observations of recent global temperature trends. The modeled surface temperature evolution exhibited a complex history-dependent behavior whose fluctuations were an order of magnitude smaller than observed, primarily owing to oceanic thermal damping. Thus solar variability appears unlikely to have been an important factor in global-scale climate change over this period. The possibility of using the measurements to develop simple correlations for irradiance with longer term solar activity observable from the surface, and therefore to analyze historical effects, was considered, but is not supported by the satellite data. However, we have used a model of solar irradiance variation with time (Schatten, 1988), covering the period 1976–1997 in order to assess our model's response to forcing whose fluctuation timescale is comparable to the thermal relaxation time of the upper ocean. Continuous monitoring of solar flux by space-based instruments over timescales of 20 yr or more, comparable to timescales for thermal relaxation of the oceans, and of the solar cycle itself, is probably needed to resolve issues of long-term solar variation effects on climate.Presently at Lamont-Doherty Geological Observatory of Columbia University, Palisades, NY 10964.     

东亚地区小冰期气候的模拟

本文使用ECHO-G全球气候模式对1550～1850年的小冰期气候进行了300个模式年的模拟,着重分析了东亚地区小冰期的温度变化特征,并与目前所得到的小冰期气候重建结果进行了对比。结果表明,在考虑了太阳辐射、火山活动、CO2和CH4等主要气候影响驱动因子的条件下,较好地模拟出了东亚地区的小冰期气候特征,并与其它手段的气候重建结果相吻合,显示太阳活动和火山活动是小冰期气候形成的主要原因。     

Natural forcing of climate during the last millennium: fingerprint of solar variability

The variability of the climate during the last millennium is partly forced by changes in total solar irradiance (TSI). Nevertheless, the amplitude of these TSI changes is very small so that recent reconstruction data suggest that low frequency variations in the North Atlantic Oscillation (NAO) and in the thermohaline circulation may have amplified, in the North Atlantic sector and mostly in winter, the radiative changes due to TSI variations. In this study we use a state-of-the-art climate model to simulate the last millennium. We find that modelled variations of surface temperature in the Northern Hemisphere are coherent with existing reconstructions. Moreover, in the model, the low frequency variability of this mean hemispheric temperature is found to be correlated at 0.74 with the solar forcing for the period 1001?C1860. Then, we focus on the regional climatic fingerprint of solar forcing in winter and find a significant relationship between the low frequency TSI forcing and the NAO with a time lag of more than 40?years for the response of the NAO. Such a lag is larger than the around 20-year lag suggested in other studies. We argue that this lag is due, in the model, to a northward shift of the tropical atmospheric convection in the Pacific Ocean, which is maximum more than four decades after the solar forcing increase. This shift then forces a positive NAO through an atmospheric wave connection related to the jet-stream wave guide. The shift of the tropical convection is due to the persistence of anomalous warm SST forcing the anomalous precipitation, associated with the advection of warm SST by the North Pacific subtropical gyre in a few decades. Finally, we analyse the response of the Atlantic meridional overturning circulation to solar forcing and find that the former is weakened when the latter increases. Changes in wind stress, notably due to the NAO, modify the barotropic streamfunction in the Atlantic 50?years after solar variations. This implies a wind-driven modification of the oceanic circulation in the Atlantic sector in response to changes in solar forcing, in addition to the variations of the thermohaline circulation.     

Sea-Ice Concentration Multivariate Assimilation for the Canadian East Coast in a Coupled Sea Ice–Ocean Model

The present study focuses on the impact of ocean state (i.e., salinity and temperature) updates on the sea-ice analysis and short-term forecast in an assimilative sea ice–ocean coupled system. A relatively simple sea-ice assimilation scheme was applied to the sea ice–ocean coupled North Atlantic Nucleus for European Modelling of the Ocean (NEMO) system with a focus on the Canadian East Coast. In this assimilation scheme the ocean state was updated directly based on the correlations between the model's sea-ice concentration and the upper ocean salinity and temperature. These correlations were based on a limited time ensemble generated by applying random perturbations to the atmospheric forcing fields. High deviations in the sea-ice conditions were found along the ice edge, implying that the sea-ice edge position is sensitive to small atmospheric forcing variations. Assimilation runs with and without ocean state updates (i.e., sea-ice concentration nudging) were conducted and compared for the winter of 2002. Both continuous and intermittent assimilation schemes were examined. In a continuous sea-ice assimilation experiment, the ocean direct update is unnecessary. When the sea-ice updates are introduced intermittently the ocean state has to be altered to accommodate them, or they will be rapidly diminished by the model's dynamics. The correlations between sea-ice concentration and ocean salinity and temperature based on the first 15 days of January were used for corrections during the entire winter season when, in addition to thermodynamic processes, dynamic processes are responsible for, and even dominate, sea-ice evolution on the Labrador and Newfoundland shelves. This was an adequate choice as was demonstrated by the results of the study which showed that the experiments with ocean state adjustments generated more accurate short-term sea-ice forecasts.     

Solar Forcing of Global Climate Change Since The Mid-17th Century

Spacecraft measurements of the sun's total irradiance since 1980 have revealed a long-term variation that is roughly in phase with the 11-year solar cycle. Its origin is uncertain, but may be related to the overall level of solar magnetic activity as well as to the concurrent activity on the visible disk. A low-pass Gaussian filtered time series of the annual sunspot number has been developed as a suitable proxy for solar magnetic activity that contains a long-term component related to the average level of activity as well as a short-term component related to the current phase of the 11-year cycle. This time series is also assumed to be a proxy for solar total irradiance, and the irradiance is reconstructed for the period since 1617 based on the estimate from climatic evidence that global temperatures during the Maunder Minimum of solar activity, which coincided with one of the coldest periods of the Little Ice Age, were about 1 °C colder than modern temperatures. This irradiance variation is used as the variable radiative forcing function in a one-dimensional ocean–climate model, leading to a reconstruction of global temperatures over the same period, and to a suggestion that solar forcing and anthropogenic greenhouse-gas forcing made roughly equal contributions to the rise in global temperature that took place between 1900 and 1955. The importance of solar variability as a factor in climate change over the last few decades may have been underestimated in recent studies.     

Anthropogenic and natural causes of climate change

We test for causality between radiative forcing and temperature using multivariate time series models and Granger causality tests that are robust to the non-stationary (trending) nature of global climate data. We find that both natural and anthropogenic forcings cause temperature change and also that temperature causes greenhouse gas concentration changes. Although the effects of greenhouse gases and volcanic forcing are robust across model specifications, we cannot detect any effect of black carbon on temperature, the effect of changes in solar irradiance is weak, and the effect of anthropogenic sulfate aerosols may be only around half that usually attributed to them.     

Long-term patterns of solar irradiance forcing in model experiments and proxy based surface temperature reconstructions

Comparisons are made of long-term empirical and model-estimated patterns of solar irradiance forcing during a 200-year period (1650-1850), which precedes any apparent anthropogenic influence on climate. This interval encompasses a considerable range (approximately 4 W/m²) of estimated variation in solar output, including the "Maunder" and "Dalton" Minima of solar irradiance, and an intervening interval of relatively high values of irradiance, but does not encroach into the industrial era wherein it is difficult to separate solar and anthropogenic influences. Particular emphasis is placed on comparing empirical and modeled patterns of forced surface temperature variation. The empirical patterns bear a greater similarity to the pattern of forced response of a coupled ocean-atmosphere general circulation model (AOGCM) than with an independent model simulation result using an ocean with specified heat transport, both in terms of the spatial pattern of response and implied global mean sensitivity to forcing. Heightened sensitivity in the western Pacific warm pool apparent in the empirical response pattern, is not observed in the forced response of the coupled model. It is possible that this pattern is the result of feedback processes not currently reproduced in course-resolution coupled models. The greatest empirical response is found at the multidecadal-to-century (> 40 year period) time scale, for which the forcing is dominated by the roughly 90-year Gleissberg Cycle of irradiance. This indicates a global-mean sensitivity (approximately 0.3 K/W/m²), which is close to the coupled model result (approximately 0.4 K/W/m²). At decadal time scales (8-25 year period), for which the forcing is dominated by the 11-year and 22-year period solar cycles), the temperature sensitivity is moderately reduced, and its spatial pattern of response is dominated by an apparent resonance with known decadal modes of climate variability.     

European climate of the past 500 years: new challenges for historical climatology

Temperature reconstructions from Europe for the past 500 years based on documentary and instrumental data are analysed. First, the basic documentary data sources, including information about climate and weather-related extremes, are described. Then, the standard palaeoclimatological reconstruction method adopted here is discussed with a particular application to temperature reconstructions from documentary-based proxy data. The focus is on two new reconstructions; January–April mean temperatures for Stockholm (1502–2008), based on a combination of data for the sailing season in the Stockholm harbour and instrumental temperature measurements, and monthly Central European temperature (CEuT) series (1500–2007) based on documentary-derived temperature indices of the Czech Republic, Germany and Switzerland combined with instrumental records from the same countries. The two series, both of which are individually discussed in greater detail in subsequent papers in this special edition, are here compared and analysed using running correlations and wavelet analysis. While the Stockholm series shows a pronounced low-frequency component, the CEuT series indicates much weaker low-frequency variations. Both series are analysed with respect to three different long-period reconstructions of the North Atlantic Oscillation (NAO) and are compared with other European temperature reconstructions based on tree-rings, wine-harvest data and various climate multiproxies. Correlation coefficients between individual proxy-based series show weaker correlations compared to the instrumental data. There are also indications of temporally varying temperature cross-correlations between different areas of Europe. The two temperature reconstructions have also been compared to geographically corresponding temperature output from simulations with global and regional climate models for the past few centuries. The findings are twofold: on the one hand, the analysis reinforces the hypothesis that the index-data based CEuT reconstruction may not appropriately reflect the centennial scale variations. On the other hand, it is possible that climate models may underestimate regional decadal variability. By way of a conclusion, the results are discussed from a broader point of view and attention is drawn to some new challenges for future investigations in the historical climatology in Europe.     

Volcanic and solar impacts on climate since 1700

 Numerical experiments have been carried out with a two-dimensional sector averaged global climate model with a detailed radiative scheme in order to assess the possible impact of solar and volcanic activities on the Earth’s surface temperature at the secular time scale from 1700 to 1992. Our results indicate that while the general trend of the observed temperature variations on the century time scale can be generated in response to both the solar and volcanic forcings, these are clearly not sufficient to explain the observed 20th century warming and more specifically the warming trend which started at the beginning of the 1970s. However, the lack of volcanism during the period 1925–1960 could account, at least partly, for the observed warming trend in this period. Finally, while Schlesinger and Ramankutty (1994) assumed that random forcing could not be a possible source of the 65–70 year oscillation they detected in the global climate system, our results indicate that the volcanic forcing over the past 150 years could have introduced an oscillation of around 70 years in the Earth’s surface temperature. Received: 25 August 1997/Accepted: 27 November 1998     

Past millennial solar forcing magnitude

A set of global climate model simulations for the last thousand years developed by the Max Planck Institute is compared with paleoclimate proxy data and instrumental data, focusing on surface temperatures for land areas between 30° and 75°N. The proxy data are obtained from six previously published Northern Hemispheric-scale temperature reconstructions, here re-calibrated for consistency, which are compared with the simulations utilizing a newly developed statistical framework for ranking several competing simulations by means of their statistical distance against past climate variations. The climate model simulations are driven by either “low” or “high” solar forcing amplitudes (0.1 and 0.25 % smaller total solar irradiance in the Maunder Minimum period compared to the present) in addition to several other known climate forcings of importance. Our results indicate that the high solar forcing amplitude results in a poorer match with the hemispheric-scale temperature reconstructions and lends stronger statistical support for the low-amplitude solar forcing. However, results are likely conditional upon the sensitivity of the climate model used and strongly dependent on the choice of temperature reconstruction, hence a greater consensus is needed regarding the reconstruction of past temperatures as this currently provides a great source of uncertainty.     

Northern Hemisphere Temperature Variability for the Past Three Centuries: Tree-Ring and Model Estimates

We compare Northern Hemisphere energy-balance-model temperature calculations to an annual temperature reconstruction based on 20 tree-ring width records from latitudinal and elevational treeline sites in northern North America, Scandinavia, Siberia and Mongolia for the past three centuries. The energy-balance model uses three primary forcings; solar, volcanic, and anthropogenic trace gas and aerosol variations. Several different parameterizations of the forcings are compared. The best agreement (r = 0.8) is found when the annual reconstruction is compared to a version of the model using (1) the Dust Veil Index of Lamb, (2) a solar parameterization which includes the length of the solar cycle, and (3) anthropogenic forcing. The implication is that all three forcings are important in explaining the temperature variations. The general similarity in low-frequency trends between the two independently-derived time series supports the validity of both the model estimates and the tree-ring reconstruction.     

Potential impacts of East Asian winter monsoon on climate variability and predictability in the Australian summer monsoon region

This study explores potential impacts of the East Asian winter monsoon (EAWM) on summer climate variability and predictability in the Australia–Asian region through Australia–Asia (A-A) monsoon interactions. Observational analysis is conducted for the period of 1959 to 2001 using ERA-40 wind reanalysis and Climate Research Unit rainfall and surface temperature monthly datasets. Statistically significant correlations are established between the Australian summer monsoon and its rainfall variations with cross-equatorial flows penetrating from South China Sea region and northerly flow in the EAWM. The underlying mechanism for such connections is the response of the position and intensity of Hardley circulation to strong/weak EAWM. A strong EAWM is associated with an enhanced cross-equatorial flow crossing the maritime continent and a strengthened Australia summer monsoon westerlies which affect rainfall and temperature variations in northern and eastern part of the Australian continent. Furthermore, partial correlation analysis, which largely excludes El Niño-Southern Oscillation (ENSO) effects, suggests that these connections are the inherent features in the monsoon system. This is further supported by analyzing a global model experiment using persistent sea surface temperatures (SSTs) which, without any SST interannual variations, shows similar patterns as in the observational analysis. Furthermore, such interaction could potentially affect climate predictability in the region, as shown by some statistically significant lag correlations at monthly time scale. Such results are attributed to the impacts of EAWM on regional SST variations and its linkage to surface conditions in the Eurasian continent. Finally, such impacts under global warmed climate are discussed by analyzing ten IPCC AR4 models and results suggest they still exist in the warmed climate even though the EAWM tends to be weaker.     

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.     

What happened to surface temperature with sunspot activity in the past 130 years?

Based on composite analysis using categories of solar inactivity and activity, the responses of surface temperature to different categorized solar activity and a plausible mechanism have been discussed. The results show the increasing solar sunspot activity during solar cycles 13 to 24 (1880–2010) and it seemed to make a positive contribution to rising global temperature. However, the sunspots were fewer in number, if we focused on the most recent 60 years (1950–2010), and the decreasing solar activity did not contribute to a cooler Earth. This result indicates that the connection between sunspots and the Earth’s climate is sensitive to the study period. An extreme analysis was performed in an attempt to gain a better understanding of solar impacts. The extreme top 10 composite analysis demonstrated that the surface temperature response to solar activity is spatially different and is highly sensitive to El Niño–Southern Oscillation (ENSO) events. The most sensitive areas in the Pacific sector revealed a significant difference between including and excluding ENSO years. During the solar inactive years, the tropical eastern Pacific was observed as a weak El Niño-like (strong La Niña-like) pattern in the composite including (excluding) ENSO events. Another interesting feature is the strong similarity in the composites which include or exclude ENSO events during the sunspot active years, but it differs from the La Niña-like pattern observed in previous studies. The bottom-up mechanism associated with the response of the surface dynamical circulation and the heat balance when compared to the total solar irradiance forcing partially explains the connection.     

Solar irradiance forcing of centennial climate variability during the Holocene

Centennial climate variability during the Holocene has been simulated in two 10,000 year experiments using the intermediate-complexity ECBilt model. ECBilt contains a dynamic atmosphere, a global 3-D ocean model and a thermodynamic sea-ice model. One experiment uses orbital forcing and solar irradiance forcing, which is based on the Stuiver et al. residual ¹⁴C record spliced into the Lean et al. reconstruction. The other experiment uses orbital forcing alone. A glacier model is coupled off-line to the climate model. A time scale analysis shows that the response in atmospheric parameters to the irradiance forcing can be characterised as the direct response of a system with a large thermal inertia. This is evident in parameters like surface air temperature, monsoon precipitation and glacier length, which show a stronger response for longer time scales. The oceanic response, on the other hand, is strongly modified by internal feedback processes. The solar irradiance forcing excites a (damped) mode of the thermohaline circulation (THC) in the North Atlantic Ocean, similar to the loop-oscillator modes associated with random-noise freshwater forcing. This results in a significant peak (at time scales 200–250 year) in the THC spectrum which is absent in the reference run. The THC response diminishes the sea surface temperature response at high latitudes, while it gives rise to a signal in the sea surface salinity. A comparison of the model results with observations shows a number of encouraging similarities.     

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.