Relative detectability of greenhouse-gas and aerosol climate change signals

 The use of pattern correlations to compare observed temperature changes with predicted anthropogenic effects has greatly increased our confidence in the reality of these effects. Here we use synthetic observed data to determine the expected behavior of the pattern correlation statistic, R(t), and hence clarify some results obtained in previous studies. We show that, for the specific case considered here (near-surface temperature changes), even with a perfectly-known signal, expected values of R(t) currently should be only of order 0.3–0.5, as observed; that R(t) may show markedly non-linear variations in time; that the CO₂-alone signal pattern should be difficult to detect today primarily because of data coverage deficiencies; and why the signal due to combined CO₂-aerosol forcing is easier to detect than either the CO₂-alone or aerosol-alone signals. Finally, we show that little is to be gained at present by searching for a time-dependent signal compared with a representative constant signal pattern. Received: 24 June 1996/Revised: 3 March 1998     

How much information is lost by using global-mean climate metrics? an example using the transport sector

Metrics are often used to compare the climate impacts of emissions from various sources, sectors or nations. These are usually based on global-mean input, and so there is the potential that important information on smaller scales is lost. Assuming a non-linear dependence of the climate impact on local surface temperature change, we explore the loss of information about regional variability that results from using global-mean input in the specific case of heterogeneous changes in ozone, methane and aerosol concentrations resulting from emissions from road traffic, aviation and shipping. Results from equilibrium simulations with two general circulation models are used. An alternative metric for capturing the regional climate impacts is investigated. We find that the application of a metric that is first calculated locally and then averaged globally captures a more complete and informative signal of climate impact than one that uses global-mean input. The loss of information when heterogeneity is ignored is largest in the case of aviation. Further investigation of the spatial distribution of temperature change indicates that although the pattern of temperature response does not closely match the pattern of the forcing, the forcing pattern still influences the response pattern on a hemispheric scale. When the short-lived transport forcing is superimposed on present-day anthropogenic CO₂ forcing, the heterogeneity in the temperature response to CO₂ dominates. This suggests that the importance of including regional climate impacts in global metrics depends on whether small sectors are considered in isolation or as part of the overall climate change.     

The response of the climate system to the indirect effects of anthropogenic sulfate aerosol

 The indirect effects of anthropogenic sulfate aerosols on the albedo and lifetime of clouds may produce a significant impact on the climate system. A `state of the art' general circulation model (GCM) which includes an interactive sulfur cycle and a physically based cloud microphysics scheme is coupled to a mixed-layer ocean model in order to study the impact of the indirect effects on the coupled climate system. The linearity of the two indirect effects on the model response is also investigated by including each effect separately in the model. The response of the sea surface temperatures (SSTs) and sea ice is found to provide an important feedback on the cooling at high latitudes and the change in meridional SST gradient results in a southward shift of the inter-tropical convergence zone (ITCZ). The sensitivity of the model to the forcing from the indirect effects of sulfate aerosol is found to be similar to, but slightly weaker than that obtained from a doubling of CO₂. Received: 30 August 2000 / Accepted: 3 January 2001     

Internal Variability as a Cause of Qualitative Intermodel Disagreement on Anthropogenic Climate Changes

Summary The qualitative agreement of two climate models, HADCM2 and ECHAM3, on the response of surface climate to anthropogenic climate forcing in the period 2020 – 2049 is studied. Special attention is paid to the role of internal climate variability as a source of intermodel disagreement. After illustrating the methods in an intermodel comparison of simulated changes in June–August mean precipitation, some global statistics are presented. Excluding surface air temperature, the four-season mean proportion of areas in which the two models agree on the sign of the climatic response is only 53 – 60% both for increases in CO₂ alone and for increases in CO₂ together with direct radiative forcing by sulphate aerosols, but somewhat larger, 59 – 70% for the separate aerosol effect. In areas where the response is strong (at least twice the standard error associated with internal variability) in both models, the agreement is better and the contrast between the different forcings becomes more marked. The proportion of agreement in such areas is 57 – 75% for the response to increases in CO₂ alone, 64 – 84% for the response to combined CO₂ and aerosol forcing, and as high as 88 – 94% for the separate aerosol effect. The relatively good intermodel agreement for aerosol-induced climate changes is suggested to be associated with the uneven horizontal distribution of aerosol forcing. Received December 2, 1998 Revised May 5, 1999     

Correlation methods in fingerprint detection studies

This investigation addresses two general issues regarding the role of pattern similarity statistics in greenhouse warming detection studies: normalization, and the relative merits of centered versus uncentered statistics. A pattern correlation statistic is used to search for the greenhouse warming signals predicted by five different models in the observed records of land and ocean surface temperature changes. Two forms of this statistic were computed: R (t), which makes use of nonnormalized data, and (t), which employs point-wise normalized data in order to focus the search on regions where the signal-to-noise ratio is large. While there are no trends in the R (t) time series, the time series of (t) show large positive trends. However, it is not possible to infer from the (t) results that the observed pattern of temperature change is, in fact, becoming increasingly similar to the model-predicted signal. This is because point-wise normalization of the observed and simulated mean change fields by a single common field introduces a common factor effect, which means that the quantities being compared should show some similarity a priori. This does not necessarily make normalization inapplicable, because the detection test involves seeking a trend in the similarity statistic. We show, however, that trends in (t) must arise almost completely from the observed data, and cannot be an indicator of increasing observed data/signal similarity. We also compare the information provided by centered statistics such as R(t) and the uncentered C(t) statistic introduced by Barnett. We show that C(t) may be expressed as the weighted sum of two terms, one proportional to R(t) and the other proportional to the observed spatial mean. For near-surface temperatures, the spatial average term dominates over the R(t) term. In this case the use of C(t) is equivalent to the use of spatial-mean temperature. We conclude that at present, the most informative pattern correlation statistic for detection purposes is R(t), the standard product-moment correlation coefficient between the observed and model fields. Our failure to find meaningful trends in R(t) may be due to the fact that the signal is being obscured by the background noise of natural variability, and/or because of incorrect model signals or sensitivities.     

Characterizing the annual-mean climatic effect of anthropogenic CO<Subscript>2</Subscript> and aerosol emissions in eight coupled atmosphere-ocean GCMs

This work examines the spatial patterns of the transient response of mean annual temperature and precipitation to CO₂ (or CO₂ plus aerosol or aerosol proxy) radiative forcing in eight coupled AOGCMs, generally for the period 1900–2099. Response patterns are characterized using empirical orthogonal functions (EOFs) and the quasi-EOFs of Harvey and Wigley (the first qEOF field, discussed here, is given by the correlation between local year-by-year temperature changes and the global mean temperature change). The first temperature EOF accounts for 80–95% of the space-time variation of the CO₂ run in all of the models, and is almost identical to qEOF₁ of the temperature response or to the temperature change pattern averaged over the last 30 years of the simulations. EOF₁ accounts for 80–95% of the space-time variation in the CO₂+aerosol runs in six of the eight models. The CO₂ response patterns of different models are highly correlated with one another (R ² generally >0.5), and are also highly correlated with the CO₂+aerosol response patterns (R ² 0.85 in all except one model). The difference between CO₂ and CO₂+aerosol runs can be represented by EOF₁ of the year-by-year differences, by qEOF₁ of the year-by-year differences, or by the difference in temperature averaged over the last 30 years of each run. In models where these representations are highly correlated with each other, they are also highly correlated with CO₂ EOF₁. In other cases, aerosol EOF₁ is modestly to highly correlated with control EOF₁ (i.e.: the year-by-year differences between CO₂ and CO₂+aerosol runs are dominated by internal variability), while aerosol qEOF₁ and the 30-year difference are highly correlated with each other. For all models, the decadal mean temperature change can be closely replicated by scaling the CO₂ EOF₁ pattern based on the global mean temperature changes (RMSE for the last decade is <6% of the RMS temperature change for CO₂ runs, <8% for CO₂+aerosol runs). The first EOF of the precipitation response to increasing CO₂ accounts for only 10–30% of the space-time variation, and is generally highly correlated (R ² up to 0.85) with control EOF₁. In all of the models, there is an increase in precipitation in the ITCZ and a decrease in bands at or near 30°S and 30°N. In many models there is an El Niño-like response, including a substantial decrease in precipitation over the Amazon. Global-mean precipitation increases in all models due to CO₂ forcing, but aerosols appear to have a disproportionally large effect in suppressing the increase compared to their effect in suppressing the warming. There is evidence in some models that the non-absorbing aerosols considered here reduce summer monsoon rainfall compared to the changes that would be expected based on the globally averaged effect of aerosols on precipitation. When regional precipitation changes over time are predicted by scaling a fixed precipitation-change pattern with the global mean temperature change, the global mean RMSE in the predicted change in decadal-mean precipitation is 25–35% of the global RMS precipitation changes by the end of the simulation.     

Glacial termination: sensitivity to orbital and CO2 forcing in a coupled climate system model

 To study glacial termination and related feedback mechanisms, a continental ice dynamics model is globally and asynchronously coupled to a physical climate (atmosphere-ocean-sea ice) model. The model performs well under present-day, 11 kaBP (thousand years before present) and 21 kaBP perpetual forcing. To address the ice-sheet response under the effects of both perpetual orbital and CO₂ forcing, sensitivity experiments are conducted with two different orbital configurations (11 kaBP and 21 kaBP) and two different atmospheric CO₂ concentrations (200 ppmv and 280 ppmv). This study reveals that, although both orbital and CO₂ forcing have an impact on ice-sheet maintenance and deglacial processes, and although neither acting alone is sufficient to lead to complete deglaciation, orbital forcing seems to be more important. The CO₂ forcing has a large impact on climate, not uniformly or zonally over the globe, but concentrated over the continents adjacent to the North Atlantic. The effect of increased CO₂ (from 200 ppmv to 280 ppmv) on surface air temperature has its peak there in winter associated with a reduction in sea-ice extent in the northern North Atlantic. These changes are accompanied by an enhancement in the intensity of the meridional overturning and poleward ocean heat transport in the North Atlantic. On the other hand, the effect of orbital forcing (from 21 kaBP to 11 kaBP) has its peak in summer. Since the summer temperature, rather than winter temperature, is found to be dominant for the ice-sheet mass balance, orbital forcing has a larger effect than CO₂ forcing in deglaciation. Warm winter sea surface temperature arising from increased CO₂ during the deglaciation contributes to ice-sheet nourishment (negative feedback for ice-sheet retreat) through slightly enhanced precipitation. However, the precipitation effect is totally overwhelmed by the temperature effect. Our results suggest that the last deglaciation was initiated through increasing summer insolation with CO₂ providing a powerful feedback. Received: 22 February 2000 / Accepted: 17 September 2000     

CO<Subscript>2</Subscript> and non-CO<Subscript>2</Subscript> radiative forcings in climate projections for twenty-first century mitigation scenarios

Climate is simulated for reference and mitigation emissions scenarios from Integrated Assessment Models using the Bern2.5CC carbon cycle–climate model. Mitigation options encompass all major radiative forcing agents. Temperature change is attributed to forcings using an impulse–response substitute of Bern2.5CC. The contribution of CO₂ to global warming increases over the century in all scenarios. Non-CO₂ mitigation measures add to the abatement of global warming. The share of mitigation carried by CO₂, however, increases when radiative forcing targets are lowered, and increases after 2000 in all mitigation scenarios. Thus, non-CO₂ mitigation is limited and net CO₂ emissions must eventually subside. Mitigation rapidly reduces the sulfate aerosol loading and associated cooling, partly masking Greenhouse Gas mitigation over the coming decades. A profound effect of mitigation on CO₂ concentration, radiative forcing, temperatures and the rate of climate change emerges in the second half of the century.     

Climate Change Impacts for the Conterminous USA: An Integrated Assessment

As carbon dioxide and other greenhouse gases accumulate in the atmosphere and contribute to rising global temperatures, it is important to examine how derivative changes in climate may affect natural and managed ecosystems. In this series of papers, we study the impacts of climate change on agriculture, water resources and natural ecosystems in the conterminous United States using twelve scenarios derived from General Circulation Model (GCM) projections to drive biophysical impact models. These scenarios are described in this paper. The scenarios are first put into the context of recent work on climate-change by the IPCC for the 21st century and span two levels of global-mean temperature change and three sets of spatial patterns of change derived from GCM results. In addition, the effect of either the presence or absence of a CO₂ fertilization effect on vegetation is examined by using two levels of atmospheric CO₂ concentration as a proxy variable. Results from three GCM experiments were used to produce different regional patterns of climate change. The three regional patterns for the conterminous United States range from: an increase in temperature above the global-mean level along with a significant decline in precipitation; temperature increases in line with the global-mean with an average increase in precipitation; and, with a sulfate aerosol effect added to in the same model, temperature increases that are lower than the global-mean. The resulting set of scenarios span a wide range of potential climate changes and allows examination of the relative importance of global-mean temperature change, regional climate patterns, aerosol cooling, and CO₂ fertilization effects.     

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.     

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     

The Time Clustering of Floodings in Venice and the Cantor Dust Method

Summary The catalogue of sea-floodings in Venice, accurately reconstructed for a period of 12 centuries (interval: 872–1996) has been analysed according to the Cantor Dust method. This provides a means of testing whether clustering in time is a scale-invariant process: if the fraction R of the intervals of length t containing flooding events is related to the time interval by: R∼t ^(1−D) , then the fractal clustering is occurring with fractal dimension D (0<D<1). The main result is the evidence for a gradual increase of the fractal clustering starting from 1914, when the soil subsidence of the lagoon basin determines an increase in its hydrodynamic response to the marine forcing with a gradual increase of flooding occurrences. Received October 1, 1996 Revised September 10, 1997     

Latitudinal dependence of signal-to-noise patterns from two general circulation models with CO2 forcing

 Detection of an enhanced greenhouse effect on climate depends on recognition of a signal of change amidst the combined noise of climatic variability and uncertainty in the nature of the signal (functional response to changing CO₂). Using two different GCMs (one with a coupled dynamic upper ocean) and an ensemble of 20 equilibrium experiments with CO₂ ranging from 100 to 3500 ppm, we find that that two measures of signal-to-noise (S/N) for the response of surface temperature to CO₂ forcing are larger over tropical and subtropical oceans than over low-latitude landmasses and larger than at higher latitudes generally. One S/N measure has the noise based solely on inherent model variability, while the other S/N measure includes both this variability and a measure of the uncertainty in the functional nature of the signal. Although the experiments were not for transient forcing and sulphate aerosols and other potentially important forcings (e.g., ozone or solar variability) were not considered, the results suggest that the effects of enhanced greenhouse climate may be detected more readily in surface temperatures from low-latitude oceanic regions than from global or zonal temperature averages. Received: 27 June 1995/Accepted: 28 October 1996     

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

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

The atmospheric sulfur cycle in ECHAM-4 and its impact on the shortwave radiation

 The atmospheric general circulation model ECHAM-4 is coupled to a chemistry model to calculate sulfate mass distribution and the radiative forcing due to sulfate aerosol particles. The model simulates the main components of the hydrological cycle and, hence, it allows an explicit treatment of cloud transformation processes and precipitation scavenging. Two experiments are performed, one with pre-industrial and one with present-day sulfur emissions. In the pre-industrial emission scenario SO₂ is oxidized faster to sulfate and the in-cloud oxidation via the reaction with ozone is more important than in the present-day scenario. The atmospheric sulfate mass due to anthropogenic emissions is estimated as 0.38 Tg sulfur. The radiative forcing due to anthropogenic sulfate aerosols is calculated diagnostically. The backscattering of shortwave radiation (direct effect) as well as the impact of sulfate aerosols on the cloud albedo (indirect effect) is estimated. The model predicts a direct forcing of −0.35 W m^-2 and an indirect forcing of −0.76 W m^-2. Over the continents of the Northern Hemisphere the direct forcing amounts to −0.64 W m^-2. The geographical distribution of the direct and indirect effect is very different. Whereas the direct forcing is strongest over highly polluted continental regions, the indirect forcing over sea exceeds that over land. It is shown that forcing estimates based on monthly averages rather than on instantaneous sulfate pattern overestimate the indirect effect but have little effect on the direct forcing. Received: 16 October 1996/Accepted: 24 October 1996     

热带太平洋表面水中CO2对El Niño事件响应的数值模拟

文中用一个带生物泵的三维全球海洋碳循环模式模拟了热带太平洋表面水中CO2总量(TCO2)在ElNi     

Clear-sky aerosol radiative forcing effects based on multi-site AERONET observations over Europe

Summary One of the great unknowns in climate research is the contribution of aerosols to climate forcing and climate perturbation. In this study, retrievals from AERONET are used to estimate the direct clear-sky aerosol top-of-atmosphere and surface radiative forcing effects for 12 multi-site observing stations in Europe. The radiative transfer code sdisort in the libRadtran environment is applied to accomplish these estimations. Most of the calculations in this study rely on observations which have been made for the years 1999, 2000, and 2001. Some stations do have observations dating back to the year of 1995. The calculations rely on a pre-compiled aerosol optical properties database for Europe. Aerosol radiative forcing effects are calculated with monthly mean aerosol optical properties retrievals and calculations are presented for three different surface albedo scenarios. Two of the surface albedo scenarios are generic by nature bare soil and green vegetation and the third relies on the ISCCP (International Satellite Cloud Climatology Project) data product. The ISCCP database has also been used to obtain clear-sky weighting fractions over AERONET stations. The AERONET stations cover the area 0° to 30° E and 42° to 52° N. AERONET retrievals are column integrated and this study does not make any seperation between the contribution of natural and anthropogenic components. For the 12 AERONET stations, median clear-sky top-of-atmosphere aerosol radiative forcing effect values for different surface albedo scenarios are calculated to be in the range of −4 to −2 W/m². High median radiative forcing effect values of about −6 W/m² were found to occur mainly in the summer months while lower values of about −1 W/m² occur in the winter months. The aerosol surface forcing also increases in summer months and can reach values of −8 W/m². Individual stations often have much higher values by a factor of 2. The median top-of-atmosphere aerosol radiative forcing effect efficiency is estimated to be about −25 W/m² and their respective surface efficiency is around −35 W/m². The fractional absorption coefficient is estimated to be 1.7, but deviates significantly from station to station. In addition, it is found that the well known peak of the aerosol radiative forcing effect at a solar zenith angle of about 75° is in fact the average of the peaks occurring at shorter and longer wavelengths. According to estimations for Central Europe, based on mean aerosol optical properties retrievals from 12 stations, the critical threshold of the aerosol single scattering albedo, between cooling and heating in the presence of an aerosol layer, is close between 0.6 and 0.76.     

A step-response approach for predicting and understanding non-linear precipitation changes

Future changes in precipitation represent one of the most important and uncertain possible effects of future climate change. We demonstrate a new approach based on idealised CO₂ step-change general circulation model (GCM) experiments, and test it using the HadCM3 GCM. The approach has two purposes: to help understand GCM projections, and to build and test a fast simple model for precipitation projections under a wide range of forcing scenarios. Overall, we find that the CO₂ step experiments contain much information that is relevant to transient projections, but that is more easily extracted due to the idealised experimental design. We find that the temporary acceleration of global-mean precipitation in this GCM following CO₂ ramp-down cannot be fully explained simply using linear responses to CO₂ and temperature. A more complete explanation can be achieved with an additional term representing interaction between CO₂ and temperature effects. Energy budget analysis of this term is dominated by clear-sky outgoing long-wave radiation (CSOLR) and sensible heating, but cloud and short-wave terms also contribute. The dominant CSOLR interaction is attributable to increased CO₂ raising the mean emission level to colder altitudes, which reduces the rate of increase of OLR with warming. This behaviour can be reproduced by our simple model. On regional scales, we compare our approach with linear ‘pattern-scaling’ (scaling regional responses by global-mean temperature change). In regions where our model predicts linear change, pattern-scaling works equally well. In some regions, however, substantial deviations from linear scaling with global-mean temperature are found, and our simple model provides more accurate projections. The idealised experiments reveal a complex pattern of non-linear behaviour. There are likely to be a range of controlling physical mechanisms, different from those dominating the global-mean response, requiring focussed investigation for individual regions, and in other GCMs.     

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     

A nonlinear impulse response model of the coupled carbon cycle-climate system (NICCS)

 Impulse-response-function (IRF) models are designed for applications requiring a large number of climate change simulations, such as multi-scenario climate impact studies or cost-benefit integrated-assessment studies. The models apply linear response theory to reproduce the characteristics of the climate response to external forcing computed with sophisticated state-of-the-art climate models like general circulation models of the physical ocean-atmosphere system and three-dimensional oceanic-plus-terrestrial carbon cycle models. Although highly computer efficient, IRF models are nonetheless capable of reproducing the full set of climate-change information generated by the complex models against which they are calibrated. While limited in principle to the linear response regime (less than about 3 ^∘C global-mean temperature change), the applicability of the IRF model presented has been extended into the nonlinear domain through explicit treatment of the climate system's dominant nonlinearities: CO₂ chemistry in ocean water, CO₂ fertilization of land biota, and sublinear radiative forcing. The resultant nonlinear impulse-response model of the coupled carbon cycle-climate system (NICCS) computes the temporal evolution of spatial patterns of climate change for four climate variables of particular relevance for climate impact studies: near-surface temperature, cloud cover, precipitation, and sea level. The space-time response characteristics of the model are derived from an EOF analysis of a transient 850-year greenhouse warming simulation with the Hamburg atmosphere-ocean general circulation model ECHAM3-LSG and a similar response experiment with the Hamburg carbon cycle model HAMOCC. The model is applied to two long-term CO₂ emission scenarios, demonstrating that the use of all currently estimated fossil fuel resources would carry the Earth's climate far beyond the range of climate change for which reliable quantitative predictions are possible today, and that even a freezing of emissions to present-day levels would cause a major global warming in the long term. Received: 28 January 2000 / Accepted: 9 March 2001