A regional and global analysis of carbon dioxide physiological forcing and its impact on climate

An increase in atmospheric carbon dioxide concentration has both a radiative (greenhouse) effect and a physiological effect on climate. The physiological effect forces climate as plant stomata do not open as wide under enhanced CO₂ levels and this alters the surface energy balance by reducing the evapotranspiration flux to the atmosphere, a process referred to as ‘carbon dioxide physiological forcing’. Here the climate impact of the carbon dioxide physiological forcing is isolated using an ensemble of twelve 5-year experiments with the Met Office Hadley Centre HadCM3LC fully coupled atmosphere–ocean model where atmospheric carbon dioxide levels are instantaneously quadrupled and thereafter held constant. Fast responses (within a few months) to carbon dioxide physiological forcing are analyzed at a global and regional scale. Results show a strong influence of the physiological forcing on the land surface energy budget, hydrological cycle and near surface climate. For example, global precipitation rate reduces by ~3% with significant decreases over most land-regions, mainly from reductions to convective rainfall. This fast hydrological response is still evident after 5 years of model integration. Decreased evapotranspiration over land also leads to land surface warming and a drying of near surface air, both of which lead to significant reductions in near surface relative humidity (~6%) and cloud fraction (~3%). Patterns of fast responses consistently show that results are largest in the Amazon and central African forest, and to a lesser extent in the boreal and temperate forest. Carbon dioxide physiological forcing could be a source of uncertainty in many model predicted quantities, such as climate sensitivity, transient climate response and the hydrological sensitivity. These results highlight the importance of including biological components of the Earth system in climate change studies.     

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

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

An examination of climate sensitivity for idealised climate change experiments in an intermediate general circulation model

Radiative forcing and climate sensitivity have been widely used as concepts to understand climate change. This work performs climate change experiments with an intermediate general circulation model (IGCM) to examine the robustness of the radiative forcing concept for carbon dioxide and solar constant changes. This IGCM has been specifically developed as a computationally fast model, but one that allows an interaction between physical processes and large-scale dynamics; the model allows many long integrations to be performed relatively quickly. It employs a fast and accurate radiative transfer scheme, as well as simple convection and surface schemes, and a slab ocean, to model the effects of climate change mechanisms on the atmospheric temperatures and dynamics with a reasonable degree of complexity. The climatology of the IGCM run at T-21 resolution with 22 levels is compared to European Centre for Medium Range Weather Forecasting Reanalysis data. The response of the model to changes in carbon dioxide and solar output are examined when these changes are applied globally and when constrained geographically (e.g. over land only). The CO₂ experiments have a roughly 17% higher climate sensitivity than the solar experiments. It is also found that a forcing at high latitudes causes a 40% higher climate sensitivity than a forcing only applied at low latitudes. It is found that, despite differences in the model feedbacks, climate sensitivity is roughly constant over a range of distributions of CO₂ and solar forcings. Hence, in the IGCM at least, the radiative forcing concept is capable of predicting global surface temperature changes to within 30%, for the perturbations described here. It is concluded that radiative forcing remains a useful tool for assessing the natural and anthropogenic impact of climate change mechanisms on surface temperature.     

人类活动对气候影响的研究Ⅱ.对东亚和中国气候变化的影响

系统总结和介绍了20世纪90年代以来作者所开展的有关人类活动对东亚和中国气候影响的一系列研究活动.其中包括温室气体辐射强迫及其气候效应,大气微量气体的全球增温潜能,对流层和平流层气溶胶的辐射气候效应,气候系统外部因子对中国气候影响的总体评估,人类活动对中国和东亚地区未来气候变化的影响,以及20世纪和21世纪东亚及中国的气候变化.同时给出了一系列研究成果,这些研究成果对于正确认识和准确预测东亚地区以及中国气候变化具有十分重要的意义.     

Does recent global warming suggest an enhanced greenhouse effect?

Considerable controversy has been generated by the observation that the Earth's climate has warmed over the last century. Public policy decisions hinge on the question of whether this trend is natural climate variability or the result of the increase in atmospheric concentrations of greenhouse gases. The strength of the enhanced greenhouse effect depends, in large part, on the uncertain value of climate sensitivity. In this paper climate sensitivity is estimated from the global temperature record by assuming models for greenhouse forcing, climate response to forcing, and climate variability. We find optimal estimates of climate sensitivity are remarkably insensitive to assumptions, at least for forcing excluding the effect of aerosols, and these values are considerably less than most predictions arising from General Circulation Models (GCM's). It is, however, the statistical significance of these estimates that is sensitive to assumptions about climate variability. Assuming climate variability with a time scale of a decade or less, climate sensitivity is estimated to be significantly greater than zero, but also significantly lower than that predicted by GCM's. Climate variability with a century time scale is consistent with both the recent temperature record and the pre-instrumental record for the last millenium; if this type of variability is assumed, the estimate of climate sensitivity has a confidence band wide enough to encompass both zero and typical values obtained by GCM's. With century time-scale variability it will be several decades before confident estimates can be made.     

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.     

Why Does FGOALS-gl Reproduce But a Reasonable Little Ice Age a Weak Medieval Warm Period and 20th Century Warming？

To understand the strengths and limitations of a low-resolution version of Flexible Global Ocean Atmosphere-Land-Sea-ice （FGOALS-gl） to simulate the climate of the last millennium, the energy balance, climate sensitivity and absorption feedback of the model are analyzed. Simulation of last-millennium climate was carried out by driving the model with natural （solar radiation and volcanic eruptions） and anthropogenic （greenhouse gases and aerosols） forcing agents. The model feedback factors for （model sensitivity to） different forcings were calculated. The results show that the system feedback factor is about 2.5 （W m-2） K-1 in the pre-industrial period, while 1.9 （W m-2） K-1 in the industrial era. Thus, the model＇s sensitivity to natural forcing is weak, which explains why it reproduces a weak Medieval Warm Period. The relatively reasonable simulation of the Little Ice Age is caused by both the specified radiative forcing and unforced linear cold drift. The model sensitivity in the industrial era is higher than that of the pre-industrial period. A negative net cloud radiative feedback operates during whole-millennial simulation and reduces the model＇s sensitivity to specified forcing. The negative net cloud radiative forcing feedback under natural forcing in the period prior to 1850 is due to the underestimation （overestimation） of the response of cloudiness （in-cloud water path）. In the industrial era, the strong tropospheric temperature response enlarges the effective radius of ice clouds and reduces the fractional ice content within cloud, resulting in a weak negative net cloud feedback in the industrial period. The water vapor feedback in the industrial era is also stronger than that in the pre-industrial period. Both are in favor of higher model sensitivity and thus a reasonable simulation of the 20th century global warming.     

Probabilistic climate change projections using neural networks

Anticipated future warming of the climate system increases the need for accurate climate projections. A central problem are the large uncertainties associated with these model projections, and that uncertainty estimates are often based on expert judgment rather than objective quantitative methods. Further, important climate model parameters are still given as poorly constrained ranges that are partly inconsistent with the observed warming during the industrial period. Here we present a neural network based climate model substitute that increases the efficiency of large climate model ensembles by at least an order of magnitude. Using the observed surface warming over the industrial period and estimates of global ocean heat uptake as constraints for the ensemble, this method estimates ranges for climate sensitivity and radiative forcing that are consistent with observations. In particular, negative values for the uncertain indirect aerosol forcing exceeding –1.2 Wm^–2 can be excluded with high confidence. A parameterization to account for the uncertainty in the future carbon cycle is introduced, derived separately from a carbon cycle model. This allows us to quantify the effect of the feedback between oceanic and terrestrial carbon uptake and global warming on global temperature projections. Finally, probability density functions for the surface warming until year 2100 for two illustrative emission scenarios are calculated, taking into account uncertainties in the carbon cycle, radiative forcing, climate sensitivity, model parameters and the observed temperature records. We find that warming exceeds the surface warming range projected by IPCC for almost half of the ensemble members. Projection uncertainties are only consistent with IPCC if a model-derived upper limit of about 5 K is assumed for climate sensitivity.     

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     

Non-Kyoto radiative forcing in long-run greenhouse gas emissions and climate change scenarios

Climate policies must consider radiative forcing from Kyoto greenhouse gases, as well as other forcing constituents, such as aerosols and tropospheric ozone that result from air pollutants. Non-Kyoto forcing constituents contribute negative, as well as positive forcing, and overall increases in total forcing result in increases in global average temperature. Non-Kyoto forcing modeling is a relatively new component of climate management scenarios. This paper describes and assesses current non-Kyoto radiative forcing modeling within five integrated assessment models. The study finds negative forcing from aerosols masking (offsetting) approximately 25 % of positive forcing in the near-term in reference non-climate policy projections. However, masking is projected to decline rapidly to 5–10 % by 2100 with increasing Kyoto emissions and assumed reductions in air pollution—with the later declining to as much as 50 % and 80 % below today’s levels by 2050 and 2100 respectively. Together they imply declining importance of non-Kyoto forcing over time. There are however significant uncertainties and large differences across models in projected non-Kyoto emissions and forcing. A look into the modeling reveals differences in base conditions, relationships between Kyoto and non-Kyoto emissions, pollution control assumptions, and other fundamental modeling. In addition, under climate policy scenarios, we find air pollution and resulting non-Kyoto forcing reduced to levels below those produced by air pollution policies alone—e.g., China sulfur emissions fall an additional 45–85 % by 2050. None of the models actively manage non-Kyoto forcing for climate implications. Nonetheless, non-Kyoto forcing may be influencing mitigation results, including allowable carbon dioxide emissions, and further evaluation is merited.     

Climate forcings and climate sensitivities diagnosed from atmospheric global circulation models

Understanding the historical and future response of the global climate system to anthropogenic emissions of radiatively active atmospheric constituents has become a timely and compelling concern. At present, however, there are uncertainties in: the total radiative forcing associated with changes in the chemical composition of the atmosphere; the effective forcing applied to the climate system resulting from a (temporary) reduction via ocean-heat uptake; and the strength of the climate feedbacks that subsequently modify this forcing. Here a set of analyses derived from atmospheric general circulation model simulations are used to estimate the effective and total radiative forcing of the observed climate system due to anthropogenic emissions over the last 50 years of the twentieth century. They are also used to estimate the sensitivity of the observed climate system to these emissions, as well as the expected change in global surface temperatures once the climate system returns to radiative equilibrium. Results indicate that estimates of the effective radiative forcing and total radiative forcing associated with historical anthropogenic emissions differ across models. In addition estimates of the historical sensitivity of the climate to these emissions differ across models. However, results suggest that the variations in climate sensitivity and total climate forcing are not independent, and that the two vary inversely with respect to one another. As such, expected equilibrium temperature changes, which are given by the product of the total radiative forcing and the climate sensitivity, are relatively constant between models, particularly in comparison to results in which the total radiative forcing is assumed constant. Implications of these results for projected future climate forcings and subsequent responses are also discussed.     

CO2 climate sensitivity and snow-sea-ice albedo parameterization in an atmospheric GCM coupled to a mixed-layer ocean model

The snow-sea-ice albedo parameterization in an atmospheric general circulation model (GCM), coupled to a simple mixed-layer ocean and run with an annual cycle of solar forcing, is altered from a version of the same model described by Washington and Meehl (1984). The model with the revised formulation is run to equilibrium for 1 × CO₂ and 2 × CO₂ experiments. The 1 ×CO₂ (control) simulation produces a global mean climate about 1° warmer than the original version, and sea-ice extent is reduced. The model with the altered parameterization displays heightened sensitivity in the global means, but the geographical patterns of climate change due to increased carbon dioxide (CO₂) are qualitatively similar. The magnitude of the climate change is affected, not only in areas directly influenced by snow and ice changes but also in other regions of the globe, including the tropics where sea-surface temperature, evaporation, and precipitation over the oceans are greater. With the less-sensitive formulation, the global mean surface air temperature increase is 3.5 °C, and the increase of global mean precipitation is 7.12%. The revised formulation produces a globally averaged surface air temperature increase of 4.04 °C and a precipitation increase of 7.25%, as well as greater warming of the upper tropical troposphere. Sensitivity of surface hydrology is qualitatively similar between the two cases with the larger-magnitude changes in the revised snow and ice-albedo scheme experiment. Variability of surface air temperature in the model is comparable to observations in most areas except at high latitudes during winter. In those regions, temporal variation of the sea-ice margin and fluctuations of snow cover dependent on the snow-ice-albedo formulation contribute to larger-than-observed temperature variability. This study highlights an uncertainty associated with results from current climate GCMs that use highly parameterized snow-sea-ice albedo schemes with simple mixed-layer ocean models.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

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     

Trends in global temperature

Statistical models consisting of a trend plus serially correlated noise may be fitted to observed climate data such as global surface temperature, the trend and noise representing systematic change and other variations, respectively. When such a model is fitted, the estimated character of the noise determines the precision of the estimated trend, and hence the precision of the estimate of the magnitude of the systematic change in the variable considered. The results of fitting such models to global temperature imply that there is uncertainty in the amount of temperature change over the past century of up to ± 0.2 °C, but that the change of around one half of a degree Celsius is significantly different from zero.The statistical models for climate variability also imply that the observed temperature data provide only imprecise information about the climate sensitivity. This is defined here as the equilibrium response of global temperature to a doubling of the atmospheric concentration of carbon dioxide. The temperature changes observed to date are compatible with a wide range of climate sensitivities, from 0.7 °C to 2.2 °C. When data uncertainties are taken into account, the interval widens even further.     

RCP4.5: a pathway for stabilization of radiative forcing by 2100

Representative Concentration Pathway (RCP) 4.5 is a scenario that stabilizes radiative forcing at 4.5?W?m^?2 in the year 2100 without ever exceeding that value. Simulated with the Global Change Assessment Model (GCAM), RCP4.5 includes long-term, global emissions of greenhouse gases, short-lived species, and land-use-land-cover in a global economic framework. RCP4.5 was updated from earlier GCAM scenarios to incorporate historical emissions and land cover information common to the RCP process and follows a cost-minimizing pathway to reach the target radiative forcing. The imperative to limit emissions in order to reach this target drives changes in the energy system, including shifts to electricity, to lower emissions energy technologies and to the deployment of carbon capture and geologic storage technology. In addition, the RCP4.5 emissions price also applies to land use emissions; as a result, forest lands expand from their present day extent. The simulated future emissions and land use were downscaled from the regional simulation to a grid to facilitate transfer to climate models. While there are many alternative pathways to achieve a radiative forcing level of 4.5?W?m^?2, the application of the RCP4.5 provides a common platform for climate models to explore the climate system response to stabilizing the anthropogenic components of radiative forcing.     

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     

Integrated Global System Model for Climate Policy Assessment: Feedbacks and Sensitivity Studies

Alternative policies to address global climate change are being debated in many nations and within the United Nations Framework Convention on Climate Change. To help provide objective and comprehensive analyses in support of this process, we have developed a model of the global climate system consisting of coupled sub-models of economic growth and associated emissions, natural fluxes, atmospheric chemistry, climate, and natural terrestrial ecosystems. The framework of this Integrated Global System Model is described and the results of sample runs and a sensitivity analysis are presented. This multi-component model addresses most of the major anthropogenic and natural processes involved in climate change and also is computationally efficient. As such, it can be used effectively to study parametric and structural uncertainty and to analyze the costs and impacts of many policy alternatives. Initial runs of the model have helped to define and quantify a number of feedbacks among the sub-models, and to elucidate the geographical variations in several variables that are relevant to climate science and policy. The effect of changes in climate and atmospheric carbon dioxide levels on the uptake of carbon and emissions of methane and nitrous oxide by land ecosystems is one potentially important feedback which has been identified. The sensitivity analysis has enabled preliminary assessment of the effects of uncertainty in the economic, atmospheric chemistry, and climate sub-models as they influence critical model results such as predictions of temperature, sea level, rainfall, and ecosystem productivity. We conclude that uncertainty regarding economic growth, technological change, deep oceanic circulation, aerosol radiative forcing, and cloud processes are important influences on these outputs.     

Present-day contribution of anthropogenic emissions from China to the global burden and radiative forcing of aerosol and ozone

The effect of anthropogenic emissions from China on global burdens of ozone, sulphate, organic carbon (OC) and black carbon (BC) aerosols is examined, using the three-dimensional chemistry transport model Oslo CTM2. Two model simulations were performed, the first with global present-day emissions and the second with the anthropogenic emissions from China set to their pre-industrial levels. The global radiative forcing for these species is then calculated. Industrial emissions from China are found to account for a 4–5% increase in the global burden of OC aerosol, the change in secondary organic aerosol being slightly less than that of primary organic aerosol. A 10% increase in the global sulphate aerosol burden is calculated, and the increase in BC is 23%. The global radiative forcing of aerosols from China was calculated to be −62, −3.7, −13 and 89 mW m⁻², for sulphate, secondary organic, primary organic and BC aerosols, respectively. The increase in ozone causes a forcing of 77 mW m⁻².     

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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Effects of Land Use on the Climate of the United States

Land use practices have replaced much of the natural needleleaf evergreen, broadleaf deciduous, and mixed forests of the Eastern United States with crops. To a lesser extent, the natural grasslands in the Central United States have also been replaced with crops. Simulations with a land surface process model coupled to an atmospheric general circulation model show that the climate of the United States with modern vegetation is significantly different from that with natural vegetation. Three important climate signals caused by modern vegetation are: (1) 1 °C cooling over the Eastern United States and 1 °C warming over the Western United States in spring; (2) summer cooling of up to 2 °C over a wide region of the Central United States; and (3) moistening of the near-surface atmosphere by 0.5 to 1.5 g kg^-1over much of the United States in spring and summer. Although individual months show large, statistically significant differences in precipitation due to land-use practices, these differences average out over the course of the 3-month seasons. These changes in surface temperature and moisture extend well into the atmosphere, up to 500 mb, and affect the boundary layer and atmospheric circulation. The altered climate is due to reduced surface roughness, reduced leaf and stem area index, reduced stomatal resistance, and increased surface albedo with modern vegetation compared to natural vegetation. The climate change caused by land use practices is comparable to other well known anthropogenic climate forcings. For example, it would take 100 to 175 years at the current, observed rate of summer warming over the United States to offset the cooling from deforestation. The summer sulfate aerosol forcing completely offsets the greenhouse forcing over the Eastern United States. Similarly, the climatic effect of North American deforestation, with extensive summer cooling, further offsets the greenhouse forcing.