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     

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.     

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.     

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.     

Towards the detection and attribution of an anthropogenic effect on climate

It has been hypothesized recently that regional-scale cooling caused by anthropogenic sulfate aerosols may be partially obscuring a warming signal associated with changes in greenhouse gas concentrations. Here we use results from model experiments in which sulfate and carbon dioxide have been varied individually and in combination in order to test this hypothesis. We use centered [R (t)] and uncentered [C (t)] pattern similarity statistics to compare observed time-evolving surface temperature change patterns with the model-predicted equilibrium signal patterns. We show that in most cases, the C (t) statistic reduces to a measure of observed global-mean temperature changes, and is of limited use in attributing observed climate changes to a specific causal mechanism. We therefore focus on R (t), which is a more useful statistic for discriminating between forcing mechanisms with different pattern signatures but similar rates of global mean change. Our results indicate that over the last 50 years, the summer (JJA) and fall (SON) observed patterns of near-surface temperature change show increasing similarity to the model-simulated response to combined sulfate aerosol/CO₂ forcing. At least some of this increasing spatial congruence occurs in areas where the real world has cooled. To assess the significance of the most recent trends in R (t) and C (t), we use data from multi-century control integrations performed with two different coupled atmosphere-ocean models, which provide information on the statistical behavior of 'unforced' trends in the pattern correlation statistics. For the combined sulfate aerosol/CO₂ experiment, the 50-year R (t) trends for the JJA and SON signals are highly significant. Results are robust in that they do not depend on the choice of control run used to estimate natural variability noise properties. The R (t) trends for the CO₂-only signal are not significant in any season. C (t) trends for signals from both the CO₂-only and combined forcing experiments are highly significant in all seasons and for all trend lengths (except for trends over the last 10 years), indicating large global-mean changes relative to the two natural variability estimates used here. The caveats regarding the signals and natural variability noise which form the basis of this study are numerous. Nevertheless, we have provided first evidence that both the largest-scale (global-mean) and smaller-scale (spatial anomalies about the global mean) components of a combined CO₂/anthropogenic sulfate aerosol signal are identifiable in the observed near-surface air temperature data. If the coupled-model noise estimates used here are realistic, we can be highly confident that the anthropogenic signal that we have identified is distinctly different from internally generated natural variability noise. The fact that we have been able to detect the detailed spatial signature in response to combined CO₂ and sulfate aerosol forcing, but not in response to CO₂ forcing alone, suggests that some of the regional-scale background noise (against which we were trying to detect a CO₂-only signal) is in fact part of the signal of a sulfate aerosol effect on climate. The large effect of sulfate aerosols found in this study demonstrates the importance of their inclusion in experiments designed to simulate past and future climate change. Received: 10 November 1994 / Accepted: 19 July 1995     

Analytical estimations of the efficiency of climate warming prevention by controlled aerosol emissions into the stratosphere

Analytical solutions of globally averaged energy-balance model to estimate the efficiency of controlled forcing on the climate in the result of sulfate aerosol emissions into the stratosphere are obtained. According to obtained results, the sulfate aerosol emissions, needed to prevent the warming, make up from 2 to 12 Mt S/year in the end of the 21st century depending on the anthropogenic impact scenario and aerosol parameters. In the case of the cessation of such compensative emissions of sulfate aerosols, the global temperature increase rate may reach 3 K per decade, that is several times more than values, derived when taking account of greenhouse effect only.     

Shortened Duration of Global Warming Slowdowns with Elevated Greenhouse Gas Emissions

Continuous emissions of anthropogenic greenhouse gases(GHGs) and aerosols in the last 160 years have resulted in an increasing trend of global mean surface temperatures(GMSTs). Due to interactions with natural variability,rates of the combined anthropogenically and naturally induced warming trends are characterized by significant slowdowns and speedups on decadal timescales. Here, by analyzing observed and model-simulated data, we investigate how the duration of these episodes will change with different strengths of GHG and aerosol forcing. We found that the duration of warming slowdowns can be more than 30 yr with a slower rate of anthropogenic emissions but would shorten to about 5 yr with a higher one. This duration reduction depends on both the magnitude of the climate response to anthropogenic forcing and the strength of the internal variability. Moreover, the warming slowdowns can still occur even towards the end of this century under high emissions scenarios but with significantly shortened duration.     

Signal analysis of the atmospheric mean 500/1000 hPa temperature north of 55°N between 1949 and 1994

 The lower tropospheric mean temperature 500/1000 hPa is examined in the Northern Hemisphere high-latitude region north of 55°N with regard to a climate change signal due to anthropogenic climate forcing as a supplement to previous studies which concentrated on near surface temperatures. An observational data set of the German Weather Service is compared with several model simulations including different scenarios of greenhouse gas and sulfate aerosol forcing derived from the two recent versions of the coupled climate model in Hamburg, ECHAM-3/LSG and ECHAM-4/OPYC. The signal analysis is based on the optimal fingerprint method, which supplies a detection variable with optimal signal-to-noise ratio. The natural variability measures are derived from the corresponding long-term control experiments. From 1970 onward, we find high trend pattern analogies between the observational data and the greenhouse-gas induced model simulations. The fingerprint of this common temperature signal consists of a predominate warming with maximum over Siberia and a weak cooling over the North Atlantic reaching an estimated significance level of about 1%. A non-optimized approach has also been examined, leading to even closer trend pattern correlations. The additional forcing by sulfate aerosols decreases the correlation of this climate change simulation with the observations. The natural variability constitutes about 50% of the conforming trend patterns. The signal-to-noise ratio is best over the oceans while the tropospheric temperatures over the land masses are contaminated by strong noise. The trend pattern correlations look the same for both model versions and several ensemble members with different noise realizations. Received: 4 January 1999 / Accepted: 11 April 2001     

20世纪中国气候变暖的归因分析

Progress in the attribution of climate warming in China for the 20th century is summarized. Three sets of climate model experiments including both coupled and uncoupled runs have been used in the attribution analyses. Comparison of climate model results with the observations proves that in the 20th century, especially in the recent half century, climate warming in China is closely related to the increasing of the anthropogenic emissions of greenhouse gases, while sulfate aerosol should also have contributions. When both external forcing and natural forcing agents are prescribed, coupled climate models have better results in producing the observed variation of temperature in China. The role of oceanic forcing is also emphasized in the attribution analyses. The observed climate warming of China in the 1920s could not be reproduced in any set of climate model simulations.     

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     

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.     

A transient climate change simulation with greenhouse gas and aerosol forcing: experimental design and comparison with the instrumental record for the twentieth century

 The Canadian Centre for Climate Modelling and Analysis (CCCma) global coupled model is used to investigate the potential climate effects of increasing greenhouse gas (GHG) concentrations and changes in sulfate aerosol loadings. The forcing scenario adopted closely resembles that of Mitchell et al. for both the greenhouse gas and aerosol components. Its implementation in the model and the resulting changes in forcing are described. Five simulations of 200 years in length, nominally for the years 1900 to 2100, are available for analysis. They consist of a control simulation without change in forcing, three independent simulations with the same greenhouse gas and aerosol changes, and a single simulation with greenhouse gas only forcing. Simulations of the evolution of temperature and precipitation from 1900 to the present are compared with available observations. Temperature and precipitation are primary climate variables with reasonable temporal and spatial coverage in the observational record for the period. The simulation of potential climate change from the present to the end of the twenty-first century, based on projected GHG and aerosol forcing changes, is discussed in a companion paper. For the historical period dealt with here, the GHG and aerosol forcing has changed relatively little compared to the forcing changes projected to the end of the twenty-first century. Nevertheless, the forced climate signal for temperature in the model is reasonably consistent with the observed global mean temperature from the instrumental record. This is true also for the trend in zonally averaged temperature as a function of latitude and for some aspects of the geographical and regional distributions of temperature. Despite the modest change in overall forcing, the difference between GHG+aerosol and GHG-only forcing is discernible in the temperature response for this period. Changes in precipitation, on the other hand, are much less evident in both the instrumental and simulated record. There is an apparent increasing trend in average precipitation in both the observations and the model results over that part of the land for which observations are available. Regional and geographical changes and trends (which are less affected by sampling considerations), if they exist, are masked by the large natural variability of precipitation in both model and observations. Received: 24 September 1998 / Accepted: 8 October 1999     

The impact of natural and anthropogenic forcings on climate and hydrology since 1550

A climate simulation of an ocean/atmosphere general circulation model driven with natural forcings alone (constant “pre-industrial” land-cover and well-mixed greenhouse gases, changing orbital, solar and volcanic forcing) has been carried out from 1492 to 2000. Another simulation driven with natural and anthropogenic forcings (changes in greenhouse gases, ozone, the direct and first indirect effect of anthropogenic sulphate aerosol and land-cover) from 1750 to 2000 has also been carried out. These simulations suggest that since 1550, in the absence of anthropogenic forcings, climate would have warmed by about 0.1 K. Simulated response is not in equilibrium with the external forcings suggesting that both climate sensitivity and the rate at which the ocean takes up heat determine the magnitude of the response to forcings since 1550. In the simulation with natural forcings climate sensitivity is similar to other simulations of HadCM3 driven with CO₂ alone. Climate sensitivity increases when anthropogenic forcings are included. The natural forcing used in our experiment increases decadal–centennial time-scale and large spatial scale climate variability, relative to internal variability, as diagnosed from a control simulation. Mean conditions in the natural simulation are cooler than in our control simulation reflecting the reduction in forcing. However, over certain regions there is significant warming, relative to control, due to an increase in forest cover. Comparing the simulation driven by anthropogenic and natural forcings with the natural-only simulation suggests that anthropogenic forcings have had a significant impact on, particularly tropical, climate since the early nineteenth century. Thus the entire instrumental temperature record may be “contaminated” by anthropogenic influences. Both the hydrological cycle and cryosphere are also affected by anthropogenic forcings. Changes in tree-cover appear to be responsible for some of the local and hydrological changes as well as an increase in northern hemisphere spring snow cover.

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Optimal filtering for Bayesian detection and attribution of climate change

In the conventional approach to the detection of an anthropogenic or other externally forced climate change signal, optimal filters (fingerprints) are used to maximize the ratio of the observed climate change signal to the natural variability noise. If detection is successful, attribution of the observed climate change to the hypothesized forcing mechanism is carried out in a second step by comparing the observed and predicted climate change signals. In contrast, the Bayesian approach to detection and attribution makes no distinction between detection and attribution. The purpose of filtering in this case is to maximize the impact of the evidence, the observed climate change, on the prior probability that the hypothesis of an anthropogenic origin of the observed signal is true. Whereas in the conventional approach model uncertainties have no direct impact on the definition of the optimal detection fingerprint, in optimal Bayesian filtering they play a central role. The number of patterns retained is governed by the magnitude of the predicted signal relative to the model uncertainties, defined in a pattern space normalized by the natural climate variability. Although this results in some reduction of the original phase space, this is not the primary objective of Bayesian filtering, in contrast to the conventional approach, in which dimensional reduction is a necessary prerequisite for enhancing the signal-to-noise ratio. The Bayesian filtering method is illustrated for two anthropogenic forcing hypotheses: greenhouse gases alone, and a combination of greenhouse gases plus sulfate aerosols. The hypotheses are tested against 31-year trends for near-surface temperature, summer and winter diurnal temperature range, and precipitation. Between six and thirteen response patterns can be retained, as compared with the one or two response patterns normally used in the conventional approach. Strong evidence is found for the detection of an anthropogenic climate change in temperature, with some preference given to the combined forcing hypothesis. Detection of recent anthropogenic trends in diurnal temperature range and precipitation is not successful, but there remains strong net evidence for anthropogenic climate change if all data are considered jointly.

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Future changes in internal variability of the Atlantic Meridional Overturning Circulation

The response of the internal variability of the Atlantic Meridional Overturning Circulation (MOC) to enhanced atmospheric greenhouse gas concentrations has been estimated from an ensemble of climate change scenario runs. In the model, enhanced greenhouse forcing results in a weaker and shallower MOC with reduced internal variability. At the same time at 55°N between 0 and 1,000 m the overturning increases as a result of a change in the area of convection. In a warmer world, new regions of deepwater formation form further north due to the poleward retreat of the sea-ice boundary. The dominant pattern of internal MOC-variability consists of a monopole centered around 35°N. Due to anthropogenic warming this monopole shifts poleward. The shift is associated with a stronger relation between MOC-variations and heat flux variations over the subpolar gyre. In old convective sites (Labrador Sea) convection becomes more irregular which leads to enhanced heat flux variability. In new convective sites heat flux variations initially are related to sea-ice variations. When the sea-ice coverage further decreases they become associated with (irregular) deepwater formation. Both processes act to tighten the relation between subpolar surface heat flux variability and MOC-variability, resulting in a poleward shift of the latter.     

A global perspective on African climate

We describe the global climate system context in which to interpret African environmental change to support planning and implementation of policymaking action at national, regional and continental scales, and to inform the debate between proponents of mitigation v. adaptation strategies in the face of climate change. We review recent advances and current challenges in African climate research and exploit our physical understanding of variability and trends to shape our outlook on future climate change. We classify the various mechanisms that have been proposed as relevant for understanding variations in African rainfall, emphasizing a “tropospheric stabilization” mechanism that is of importance on interannual time scales as well as for the future response to warming oceans. Two patterns stand out in our analysis of twentieth century rainfall variability: a drying of the monsoon regions, related to warming of the tropical oceans, and variability related to the El Niño–Southern Oscillation. The latest generation of climate models partly captures this recent continent-wide drying trend, attributing it to the combination of anthropogenic emissions of aerosols and greenhouse gases, the relative contribution of which is difficult to quantify with the existing model archive. The same climate models fail to reach a robust agreement regarding the twenty-first century outlook for African rainfall, in a future with increasing greenhouse gases and decreasing aerosol loadings. Such uncertainty underscores current limitations in our understanding of the global climate system that it is necessary to overcome if science is to support Africa in meeting its development goals.     

Indian Ocean warming during 1958–2004 simulated by a climate system model and its mechanism

The mechanism responsible for Indian Ocean Sea surface temperature (SST) basin-wide warming trend during 1958–2004 is studied based on both observational data analysis and numerical experiments with a climate system model FGOALS-gl. To quantitatively estimate the relative contributions of external forcing (anthropogenic and natural forcing) and internal variability, three sets of numerical experiments are conducted, viz. an all forcing run forced by both anthropogenic forcing (greenhouse gases and sulfate aerosols) and natural forcing (solar constant and volcanic aerosols), a natural forcing run driven by only natural forcing, and a pre-industrial control run. The model results are compared to the observations. The results show that the observed warming trend during 1958–2004 (0.5 K (47-year)^?1) is largely attributed to the external forcing (more than 90 % of the total trend), while the residual is attributed to the internal variability. Model results indicate that the anthropogenic forcing accounts for approximately 98.8 % contribution of the external forcing trend. Heat budget analysis shows that the surface latent heat flux due to atmosphere and surface longwave radiation, which are mainly associated with anthropogenic forcing, are in favor of the basin-wide warming trend. The basin-wide warming is not spatially uniform, but with an equatorial IOD-like pattern in climate model. The atmospheric processes, oceanic processes and climatological latent heat flux together form an equatorial IOD-like warming pattern, and the oceanic process is the most important in forming the zonal dipole pattern. Both the anthropogenic forcing and natural forcing result in easterly wind anomalies over the equator, which reduce the wind speed, thereby lead to less evaporation and warmer SST in the equatorial western basin. Based on Bjerknes feedback, the easterly wind anomalies uplift the thermocline, which is unfavorable to SST warming in the eastern basin, and contribute to SST warming via deeper thermocline in the western basin. The easterly anomalies also drive westward anomalous equatorial currents, against the eastward climatology currents, which is in favor of the SST warming in the western basin via anomalous warm advection. Therefore, both the atmospheric and oceanic processes are in favor of the IOD-like warming pattern formation over the equator.     

Uncertainty in climate change projections: the role of internal variability

Uncertainty in future climate change presents a key challenge for adaptation planning. In this study, uncertainty arising from internal climate variability is investigated using a new 40-member ensemble conducted with the National Center for Atmospheric Research Community Climate System Model Version 3 (CCSM3) under the SRES A1B greenhouse gas and ozone recovery forcing scenarios during 2000–2060. The contribution of intrinsic atmospheric variability to the total uncertainty is further examined using a 10,000-year control integration of the atmospheric model component of CCSM3 under fixed boundary conditions. The global climate response is characterized in terms of air temperature, precipitation, and sea level pressure during winter and summer. The dominant source of uncertainty in the simulated climate response at middle and high latitudes is internal atmospheric variability associated with the annular modes of circulation variability. Coupled ocean-atmosphere variability plays a dominant role in the tropics, with attendant effects at higher latitudes via atmospheric teleconnections. Uncertainties in the forced response are generally larger for sea level pressure than precipitation, and smallest for air temperature. Accordingly, forced changes in air temperature can be detected earlier and with fewer ensemble members than those in atmospheric circulation and precipitation. Implications of the results for detection and attribution of observed climate change and for multi-model climate assessments are discussed. Internal variability is estimated to account for at least half of the inter-model spread in projected climate trends during 2005–2060 in the CMIP3 multi-model ensemble.     

A climate change simulation starting from 1935

Due to restrictions in the available computing resources and a lack of suitable observational data, transient climate change experiments with global coupled ocean-atmosphere models have been started from an initial state at equilibrium with the present day forcing. The historical development of greenhouse gas forcing from the onset of industrialization until the present has therefore been neglected. Studies with simplified models have shown that this cold start error leads to a serious underestimation of the anthropogenic global warming. In the present study, a 150-year integration has been carried out with a global coupled ocean-atmosphere model starting from the greenhouse gas concentration observed in 1935, i.e., at an early time of industrialization. The model was forced with observed greenhouse gas concentrations up to 1985, and with the equivalent C0₂ concentrations stipulated in Scenario A (Business as Usual) of the Intergovernmental Panel on Climate Change from 1985 to 2085. The early starting date alleviates some of the cold start problems. The global mean near surface temperature change in 2085 is about 0.3 K (ca. 10%) higher in the early industrialization experiment than in an integration with the same model and identical Scenario A greenhouse gas forcing, but with a start date in 1985. Comparisons between the experiments with early and late start dates show considerable differences in the amplitude of the regional climate change patterns, particularly for sea level. The early industrialization experiment can be used to obtain a first estimate of the detection time for a greenhouse-gas-induced near-surface temperature signal. Detection time estimates are obtained using globally and zonally averaged data from the experiment and a long control run, as well as principal component time series describing the evolution of the dominant signal and noise modes. The latter approach yields the earliest detection time (in the decade 1990–2000) for the time-evolving near-surface temperature signal. For global-mean temperatures or for temperatures averaged between 45°N and 45°S, the signal detection times are in the decades 2015–2025 and 2005–2015, respectively. The reduction of the cold start error in the early industrialization experiment makes it possible to separate the near-surface temperature signal from the noise about one decade earlier than in the experiment starting in 1985. We stress that these detection times are only valid in the context of the coupled model's internally-generated natural variability, which possibly underestimates low frequency fluctuations and does not incorporate the variance associated with changes in external forcing factors, such as anthropogenic sulfate aerosols, solar variability or volcanic dust.     

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.