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

The authors investigate the change of atmospheric angular momentum (AAM) in long, transient, coupled atmosphere–ocean model simulations with increasing atmospheric greenhouse gas concentration and sulfate aerosol loading. A significant increase of global AAM, on the order of 4 × 1025 kg m2 s−1 for 3 × CO2–1 × CO2, was simulated by the Canadian Centre for Climate Modelling and Analysis (CCCma) coupled model. The increase was mainly contributed by the relative component of total AAM in the form of an acceleration of zonal mean zonal wind in the tropical–subtropical upper troposphere. Thus, under strong global warming, a superrotational state emerged in the tropical upper troposphere. The trend in zonal mean zonal wind in the meridional plane was characterized by 1) a tropical–subtropical pattern with two maxima near 30° in the upper troposphere, and 2) a tripole pattern in the Southern Hemisphere extending through the entire troposphere and having a positive maximum at 60°S. The implication of the ...

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.

The responses of Sea Surface Temperature (SST) to greenhouse gas (GHG) and anthropogenic aerosol in the North Pacific are compared based on the historical single and all-forcing simulations with Geophysical Fluid Dynamics Laboratory Climate Model version 3 (GFDL CM3). During 1860–2005, the effect of GHG forcing on the North Pacific SST is opposite to that of the aerosol forcing. Specifically, the aerosol cooling effect exceeds the GHG warming effect in the Kuroshio Extension (KE) region during 1950–2004 in the CM3 single forcing. The mid-latitude response of ocean circulation to the GHG (aerosol) forcing is to enhance (weaken) the Subtropical Gyre. Then the SST warming (cooling) lies on the zonal band of 40°N because of the increased (reduced) KE warm advection effect in the GHG (aerosol) forcing simulations, and the cooling effect to SST will surpass the warming effect in the KE region in the historical all-forcing simulations. Besides, the positive feedback between cold SST and cloud can also strengthen the aerosol cooling effect in the KE region during boreal summer, when the mixed layer depth is shallow. In the GHG (aerosol) forcing simulations, corresponding to warming (cooling) SST in the KE region, the weakened (enhanced) Aleutian Low appears in the Northeast Pacific. Consequently, the SST responses to all-forcing in the historical simulations are similar to the responses to aerosol forcing in sign and spatial pattern, hence the aerosol effect is quite important to the SST cooling in the mid-latitude North Pacific during the past 55 years.

<p>The Indian summer monsoon is a key meteorological event in the Indian calendar, bringing approximately 80% of India’s annual rainfall over the months of June—September. How the monsoon system will react to a changing future climate is of crucial importance for India’s agriculture, industry and economy.</p><p> </p><p>Uncertainty remains in the future climate projections of the Indian monsoon,  primarily due to uncertainties in the amount and composition of aerosols over the Asian region. A further complication is that greenhouse gases, expected to increase over the next 50 years and dominate over aerosol forcing, have a directly competing effect on the monsoon. Generally, greenhouse gases act to heat the Earth’s surface, enabling greater moisture uptake and enhancing monsoonal precipitation. In contrast, aerosols have a cooling effect at the surface. The presence of aerosols is analogous to anomalous heating in the mid-troposphere, increasing the static stability of the atmosphere, which is associated with a weakening of the large-scale circulation and thus a weakening of the monsoon. </p><p> </p><p>We use the Planet Simulator (PlaSim), an intermediate complexity climate model, to investigate the interplay between varying aerosol and greenhouse gas forcing, in relation to the Indian summer monsoon. The model is modified to include anomalous heating in the mid-troposphere, which represents the presence of aerosols and effectively cools the surface. Varying the intensity and location of aerosol forcing, as well doubling the amount of carbon dioxide, alters the spatial pattern of precipitation over the Asian region. Increasing the anomalous heating to 150 Watts and applying over the regions of India, East China and Southeast Asia, significantly weakens the large-scale circulation and reduces the summer precipitation to 10-20% of a normal year; essentially a breakdown of the monsoon system. Through modelling sensitivity studies, we define a safe operating space of future climate conditions, where the Indian and East Asian monsoons retain their current regimes. We can also show early warning signals in the precipitation intensity, indicating a phase change of the Indian or the East Asian monsoon.</p>

Sulfate aerosol particles have strong scattering effect on the solar radiation transfer which results in increasing the planet albedo and, hence, tend to cool the earth-atmosphere system. Also, aerosols can act as the cloud condensation nuclei (CCN) which tend to increase the albedo of clouds and cool the global warming. The ARPEGE-Climat version 3 AGCM with FMR radiation scheme is used to estimate the direct and indirect radiative forcing of sulfate aerosols. For minimizing the uncertainties in assessing this kind of cooling effect, all kinds of factors are analyzed which have been mixed in the assessment process and may lead to the different results of the radiative forcing of aerosols. It is noticed that one of the uncertainties to assess the climate forcing of aerosols by GCM results from the different definition of radiative forcing that was used. In order to clarify this vague idea, the off-line case for considering no feedbacks and on-line case for including all the feedbacks have been used for assessment. The direct forcing of sulfate aerosols in off-line case is −0.57 W/ m2 and −0.38 W/ m2 for the clear sky and all sky respectively. The value of on-line case appears to be a little larger than that in off-line case chiefly due to the feedback of clouds. The indirect forcing of sulfate aerosols in off-line case is −1.4 W/ m2 and −1.0 W/ m2 in on-line case. The radiative forcing of sulfate aerosols has obvious regional characteristics. There is a larger negative radiative forcing over North America, Europe and East Asia. If the direct and indirect forcing are added together, it is enough to offset the positive radiative forcing induced by the greenhouse gases in these regions.

Anthropogenic aerosols are highly spatially variable, whereas greenhouse gases are largely well-mixed at the global scale, but both affect climate. Nevertheless, climate simulations suggest that regional changes in sea surface temperature and precipitation to changes in greenhouse gas and aerosol forcings are similar. Spatial variations in ocean warming have been linked to regional changes in tropical cyclones1, precipitation2,3 and monsoons4. But development of reliable regional climate projections for climate change mitigation and adaptation remains challenging5. The presence of anthropogenic aerosols, which are highly variable in space and time, is thought to induce spatial patterns of climate response that are distinct from those of well-mixed greenhouse gases4,6,7,8,9. Using CMIP5 climate simulations that consider aerosols and greenhouse gases separately, we show that regional responses to changes in greenhouse gases and aerosols are similar over the ocean, as reflected in similar spatial patterns of ocean temperature and precipitation. This similarity suggests that the climate response to radiative changes is relatively insensitive to the spatial distribution of these changes. Although anthropogenic aerosols are largely confined to the Northern Hemisphere, simulations that include aerosol forcing predict decreases in temperature and westerly wind speed that reach the pristine Southern Hemisphere oceans. Over land, the climate response to aerosol forcing is more localized, but larger scale spatial patterns are also evident. We suggest that the climate responses induced by greenhouse gases and aerosols share key ocean–atmosphere feedbacks, leading to a qualitative resemblance in spatial distribution.

Long‐lived greenhouse gases (GHGs) are the most important driver of climate change over the next century. Aerosols and tropospheric ozone (O3) are expected to induce significant perturbations to the GHG‐forced climate. To distinguish the equilibrium climate responses to changes in direct radiative forcing of anthropogenic aerosols, tropospheric ozone, and GHG between present day and year 2100, four 80‐year equilibrium climates are simulated using a unified tropospheric chemistry‐aerosol model within the Goddard Institute for Space Studies (GISS) general circulation model (GCM) II′. Concentrations of sulfate, nitrate, primary organic (POA) carbon, secondary organic (SOA) carbon, black carbon (BC) aerosols, and tropospheric ozone for present day and year 2100 are obtained a priori by coupled chemistry‐aerosol GCM simulations, with emissions of aerosols, ozone, and precursors based on the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenario (SRES) A2. Changing anthropogenic aerosols, tropospheric ozone, and GHG from present day to year 2100 is predicted to perturb the global annual mean radiative forcing by +0.18 (considering aerosol direct effects only), +0.65, and +6.54 W m−2 at the tropopause, and to induce an equilibrium global annual mean surface temperature change of +0.14, +0.32, and +5.31 K, respectively, with the largest temperature response occurring at northern high latitudes. Anthropogenic aerosols, through their direct effect, are predicted to alter the Hadley circulation owing to an increasing interhemispheric temperature gradient, leading to changes in tropical precipitation. When changes in both aerosols and tropospheric ozone are considered, the predicted patterns of change in global circulation and the hydrological cycle are similar to those induced by aerosols alone. GHG‐induced climate changes, such as amplified warming over high latitudes, weakened Hadley circulation, and increasing precipitation over the Tropics and high latitudes, are consistent with predictions of a number of previous GCM studies. Finally, direct radiative forcing of anthropogenic aerosols is predicted to induce strong regional cooling over East and South Asia. Wintertime rainfall over southeastern China and the Indian subcontinent is predicted to decrease because of the increased atmospheric stability and decreased surface evaporation, while the geographic distribution of precipitation is also predicted to be altered as a result of aerosol‐induced changes in wind flow.

It remains difficult to disentangle the relative influences of aerosols and greenhouse gases on regional surface temperature trends in the context of global climate change. To address this issue, we use a new collection of initial‐condition large ensembles from the Community Earth System Model version 1 that are prescribed with different combinations of industrial aerosol and greenhouse gas forcing. To compare the climate response to these external forcings, we adopt an artificial neural network (ANN) architecture from previous work that predicts the year by training on maps of near‐surface temperature. We then utilize layer‐wise relevance propagation (LRP) to visualize the regional temperature signals that are important for the ANN's prediction in each climate model experiment. To mask noise when extracting only the most robust climate patterns from LRP, we introduce a simple uncertainty metric that can be adopted to other explainable artificial intelligence (AI) problems. We find that the North Atlantic, Southern Ocean, and Southeast Asia are key regions of importance for the neural network to make its prediction, especially prior to the early‐21st century. Notably, we also find that the ANN predictions based on maps of observations correlate higher to the actual year after training on the large ensemble experiment with industrial aerosols held fixed to 1920 levels. This work illustrates the sensitivity of regional temperature signals to changes in aerosol forcing in historical simulations. By using explainable AI methods, we have the opportunity to improve our understanding of (non)linear combinations of anthropogenic forcings in state‐of‐the‐art global climate models.

Over the 20th and 21st centuries, both anthropogenic greenhouse gas increases and changes in anthropogenic aerosols have affected rainfall in the Sahel. Using multiple characteristics of Sahel precipitation, we construct a multivariate fingerprint that allows us to distinguish between the model-predicted responses to greenhouse gases and anthropogenic aerosols. Models project the emergence of a detectable signal of aerosol forcing in the middle of the 20th century and a detectable signal of greenhouse gas forcing at the beginning of the 21st. However, the signals of both aerosol and greenhouse gas forcing in observations emerge earlier and are stronger than in the models, far stronger in the case of aerosols. The similarity between the response to aerosol forcing and the leading mode of internal variability makes it difficult to attribute this model-observation discrepancy to errors in the forcing, errors in the forced response, model inability to capture the amplitude of internal variability, or some combination of these. For greenhouse gases, however, the forced response is distinct from internal variability as estimated by models, and the observations are largely commensurate with the model projections.

ABSTRACTThe response of the tropical Indian Ocean (TIO) to greenhouse gases (GHGs) and aerosols are investigated based on historical single-forcing and all-forcing simulations using the Geophysical Fluid Dynamics Laboratory Climate Model, version 3 (GFDL CM3). Results reveal a positive Indian Ocean Dipole (pIOD)-like pattern in GHG forcing but a negative Indian Ocean Dipole (nIOD)-like pattern in aerosol forcing. The GHG-induced pIOD-like pattern features less (more) sea surface temperature (SST) warming over the southeastern (western) TIO, accompanied by equatorial easterly anomalies, as well as a shallower thermocline off Sumatra. The aerosol-induced nIOD-like pattern displays the reverse features, characterized by less (more) SST cooling over the southeastern (western) TIO, anomalous equatorial westerlies, and a deeper thermocline off Sumatra. Although the aerosol-induced pattern appears to resemble a reversal of the GHG-induced pattern, there is a strong asymmetry in the SST changes over the southeastern TIO, where the cooling responding to aerosol forcing exceeds the warming in response to GHG forcing, and a negative SST residual is thus produced. A mixed-layer heat budget analysis suggests that the negative SST residual results mainly from asymmetric responses of shortwave radiation, zonal advection, and diffusion to GHGs and aerosols. For comparison, the formation processes for the negative SST skewness over the southeastern TIO between the internal pIOD and nIOD are also discussed.

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.

A number of studies have investigated the mechanisms that determine changes in precipitation, including how a wet region gets wetter. However, not all monsoon areas get wetter—there is a need to understand the major factors behind changes in regional monsoon precipitation, in terms of external forcing and internal variabilities in the last six decades by a combination of different observed datasets and model runs. We have found that time of emergence of anthropogenic signals is robustly detected in the northern African monsoon before the 1990s with the use of the CESM Large Ensemble Project. From CMIP5 model runs and three reanalysis datasets, the results found are that the change in rainfall over African monsoon (AFM) is mainly due to anthropogenic forcing and that over Asian-Australian monsoon (AAM) is affected by internal variability. Moreover, the cause of American monsoon (AMM) rainfall change cannot be known due to a discrepancy among observed datasets. Here we show that the asymmetry between Northern Hemisphere (NH) and Southern Hemisphere (SH) parts by green-house gas (GHG) is detected over the AFM and AAM regions. However, the land monsoon rainfall in the northern AMM is decreased by a combination of GHG and aerosol forcing. In general, the aerosol forcing causes a decreasing rainfall over the monsoon regions. In future projection, the land rainfall over the AAM and AMM are expected to increase and decrease in the future from most models’ results. The asymmetry between an increase in NH and a decrease in SH is dominant in the future from most models’ future simulation results, which is well shown over the AFM and AAM. This study suggests that the physical process of GHG and aerosol effects in rainfall should be explored in the context of regional aspects.

An energy balance climate model with latitudinal, surface–air, and land–sea resolution is coupled to a two-dimensional (latitude–depth) ocean model and used to simulate changes in surface and surface air temperature since 1765. The climate model sensitivity can be prescribed by adjusting the parameterization of infrared radiation to space, and sensitivities corresponding to an equilibrium, global average warming to a CO2 doubling (ΔT2×) of 1.0° to 5.0°C are used here. The model is driven with various combinations of greenhouse gas (GHG), fossil fuel aerosol, biomass aerosol, solar, and volcanic forcings. The fossil fuel aerosol forcing is concentrated in the NH, while the biomass aerosol forcing is centered near the equator. The variation in the global mean air temperature, and in the NH minus SH temperature, is examined over the period 1856–2000, in order to simultaneously constrain both climate sensitivity and aerosol forcing. The model performance, compared to observations, is evaluated using three statistical measures. It is possible to identify a group of experiments that performs better than other experiments, but it cannot be claimed that any member of the group is better than any other member in a statistically rigorous manner. The different statistical measures and temperature variables (global mean, NH − SH, NH, or SH temperature) give slightly different groups of “more accurate” experiments. Based on the statistical measures and examination of the time series of model-simulated global mean and NH − SH temperature variation, the following conclusions can be drawn: (i) The most likely ΔT2× is around 2°C, which is at the lower end of the range of 2.1°–4.8°C obtained by recent general circulation models; (ii) the fossil fuel aerosol forcing is unlikely to have exceeded −1.0 W m−2 in the global mean by 1990; and (iii) the net biomass plus soil dust aerosol forcing is unlikely to have exceeded −0.5 W m−2 in the global mean by 1990. As an independent check of these conclusions, it was found that the simulated change of ocean heat content (over the 0–3000-m depth interval, during the period 1948–98) agrees well with the observed change in ocean heat content for climate sensitivity and aerosol forcing combinations that produce a good simulation of the observed temperature change during this time period, thereby validating the model uptake of heat by the oceans. Although the preferred ΔT2× is 2°C in this study, it is possible to choose fossil and biomass aerosol forcing combinations (within the ranges given above) that produce comparable simulations of global mean and NH − SH temperature variation after the 1880s for any ΔT2× in the range 1.0°–5.0°C. However, and in common with other models, this model simulates much too large a drop in temperature during the 1880s (in response to the eruption of Mount Krakatau in 1883). As ΔT2× ranges from 1.0° to 5.0°C, the simulated drop ranges from about 0.3° to about 0.7°C, compared to an observed change of about 0.2°C. On this basis, a lower ΔT2× is preferred. Inasmuch as the model response to the 1991 eruption of Mount Pinatubo accords well with observations, especially for intermediate and high sensitivities, it may be that the estimated radiative forcing due to the eruption of Krakatau is too large or that there was a short-term negative feedback, dependent on conditions just before this eruption, which reduced the effective radiative forcing. If half the base case forcing is assumed for Krakatau only, the temperature decrease during the 1880s ranges from 0.2°C for ΔT2× = 1°C (matching observations) to 0.3°C for ΔT2× = 5°C (modestly in excess of observations). Thus, the volcanic radiative forcing during the 1880s, and the quality of the historical and proxy temperature records around this time, are critical data in discriminating between different climate sensitivities, inasmuch as a smaller volcanic forcing might permit ΔT2× at the high end of the 1°–5°C range.

’s (2012) conclusion that observed climate change is comparableto projections, and in some cases exceeds projections, allows further inferences ifwe can quantify changing climate forcings and compare those with projections.The largest climate forcing is caused by well-mixed long-lived greenhouse gases.Here we illustrate trends of these gases and their climate forcings, and we discussimplications. We focus on quantities that are accurately measured, and we includecomparison with fixed scenarios, which helps reduce common misimpressionsabout how climate forcings are changing.Annual fossil fuel CO