Tom M. L. Wigley

Avoiding dangerous climate change

The impacts of climate change are already being observed in a variety of sectors and there is greater clarity that these changes are being caused by human activities, mainly through release of greenhouse gases. In 2005 the UK Government hosted the Avoiding Dangerous Climate Change conference to take an in-depth look at the scientific issues associated with climate change. This volume presents the most recent findings from the leading international scientists that attended the conference. The topics addressed include critical thresholds and key vulnerabilities of the climate system, impacts on human and natural systems, socioeconomic costs and benefits of emissions pathways, and technological options for meeting different stabilisation levels of greenhouse gases in the atmosphere. The volume provides invaluable information for researchers in environmental science, climatology, and atmospheric chemistry, policy-makers in governments and environmental organizations, and scientists and engineers in industry.Tropical forests affect atmospheric carbon dioxide concentrations, and hence modulate the rate of climate change - by being a source of carbon, from land-use change (deforestation), and as a sink or source of carbon in remaining intact forest. These fluxes are among the least understood and most uncertain major fluxes within the global carbon cycle. We synthesise recent research on the tropical forest biome carbon balance, suggesting that intact forests presently function as a carbon sink of approx. 1.2 Pg C a ^-1, and that deforestation emissions at the higher end of the reported 1 - 3 Pg C a^ -1 spectrum are likely. Scenarios suggest that the source from deforestation will remain high, whereas the sink in intact forest is unlikely to continue, and remaining tropical forests may become a major carbon source via one or more of (i) changing photosynthesis/respiration rates, (ii) functional/biodiversity changes within intact forest, or widespread forest collapse via (iii) drought, or (iv) fire. Each scenario risks possible positive feedbacks with the climate system suggesting that current estimates of the possible rate, magnitude and effects of global climate change over the coming decades may be conservative.

Energy implications of future stabilization of atmospheric CO2 content

The United Nations Framework Convention on Climate Change calls for “stabilization of greenhouse-gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system . . . ”. A standard baseline scenario, that assumes no policy intervention to limit greenhouse-gas emissions has 10 TW (10 × 1012 watts) of carbon-emission-free power being produced by the year 2050, equivalent to the power provided by all todays energy sources combined. Here we employ a carbon-cycle/energy model to estimate the carbon-emission-free power needed for various atmospheric CO2 stabilization scenarios. We find that CO2 stabilization with continued economic growth will require innovative, cost-effective and carbon-emission-free technologies that can provide additional tens of terawatts of primary power in the coming decades, and certainly by the middle of the twenty-first century, even with sustained improvement in the economic productivity of primary energy. At progressively lower atmospheric CO2-stabilization targets in the 750–350 p.p.m.v. range, implementing stabilization will become even more challenging because of the increasing demand for carbon-emission-free power. The magnitude of the implied infrastructure transition suggests the need for massive investments in innovative energy research.

Solar and Greenhouse Gas Forcing and Climate Response in the Twentieth Century

Ensemble experiments with a global coupled climate model are performed for the twentieth century with time-evolving solar, greenhouse gas, sulfate aerosol (direct effect), and ozone (tropospheric and stratospheric) forcing. Observed global warming in the twentieth century occurred in two periods, one in the early twentieth century from about the early 1900s to the 1940s, and one later in the century from, roughly, the late 1960s to the end of the century. The model’s response requires the combination of solar and anthropogenic forcing to approximate the early twentieth-century warming, while the radiative forcing from increasing greenhouse gases is dominant for the response in the late twentieth century, confirming previous studies. Of particular interest here is the model’s amplification of solar forcing when this acts in combination with anthropogenic forcing. This difference is traced to the fact that solar forcing is more spatially heterogeneous (i.e., acting most strongly in areas where sunlight reaches the surface) while greenhouse gas forcing is more spatially uniform. Consequently, solar forcing is subject to coupled regional feedbacks involving the combination of temperature gradients, circulation regimes, and clouds. The magnitude of these feedbacks depends on the climate’s base state. Over relatively cloud-free oceanic regions in the subtropics, the enhanced solar forcing produces greater evaporation. More moisture then converges into the precipitation convergence zones, intensifying the regional monsoon and Hadley and Walker circulations, causing cloud reductions over the subtropical ocean regions, and, hence, more solar input. An additional response to solar forcing in northern summer is an enhancement of the meridional temperature gradients due to greater solar forcing over land regions that contribute to stronger West African and South Asian monsoons. Since the greenhouse gases are more spatially uniform, such regional circulation feedbacks are not as strong. These regional responses are most evident when the solar forcing occurs in concert with increased greenhouse gas forcing. The net effect of enhanced solar forcing in the early twentieth century is to produce larger solar-induced increases of tropical precipitation when calculated as a residual than for early century solar-only forcing, even though the size of the imposed solar forcing is the same. As a consequence, overall precipitation increases in the early twentieth century in the Asian monsoon regions are greater than late century increases, qualitatively consistent with observed trends in all-India rainfall. Similar effects occur in West Africa, the tropical Pacific, and the Southern Ocean tropical convergence zones.

Combinations of Natural and Anthropogenic Forcings in Twentieth-Century Climate

Ensemble simulations are run with a global coupled climate model employing five forcing agents that influence the time evolution of globally averaged surface air temperature during the twentieth century. Two are natural (volcanoes and solar) and the others are anthropogenic [e.g., greenhouse gases (GHGs), ozone (stratospheric and tropospheric), and direct effect of sulfate aerosols]. In addition to the five individual forcing experiments, an additional eight sets are performed with the forcings in various combinations. The late-twentieth-century warming can only be reproduced in the model with anthropogenic forcing (mainly GHGs), while the early twentieth-century warming is mainly caused by natural forcing in the model (mainly solar). However, the signature of globally averaged temperature at any time in the twentieth century is a direct consequence of the sum of the forcings. The similarity of the response to the forcings on decadal and interannual time scales is tested by performing a principal component analysis of the 13 ensemble mean globally averaged temperature time series. A significant portion of the variance of the reconstructed time series can be retained in residual calculations compared to the original single and combined forcing runs. This demonstrates that the statistics of the variances for decadal and interannual time-scale variability in the forced simulations are similar to the response from a residual calculation. That is, the variance statistics of the response of globally averaged temperatures in the forced runs are additive since they can be reproduced in the responses calculated as a residual from other combined forcing runs.

Towards the detection and attribution of an anthropogenic effect on climate

It has been hypothesized recently that regional-scale cooling caused by anthropogenic sulfate aerosols may be partially obscuring a warming signal associated with changes in greenhouse gas concentrations. Here we use results from model experiments in which sulfate and carbon dioxide have been varied individually and in combination in order to test this hypothesis. We use centered [R(t)] and uncentered [C(t)] pattern similarity statistics to compare observed time-evolving surface temperature change patterns with the model-predicted equilibrium signal patterns. We show that in most cases, the C(t) statistic reduces to a measure of observed global-mean temperature changes, and is of limited use in attributing observed climate changes to a specific causal mechanism. We therefore focus on R(t), which is a more useful statistic for discriminating between forcing mechanisms with different pattern signatures but similar rates of global mean change. Our results indicate that over the last 50 years, the summer (JJA) and fall (SON) observed patterns of near-surface temperature change show increasing similarity to the model-simulated response to combined sulfate aerosol/CO2 forcing. At least some of this increasing spatial congruence occurs in areas where the real world has cooled. To assess the significance of the most recent trends in R(t) and C(t), we use data from multi-century control integrations performed with two different coupled atmosphere-ocean models, which provide information on the statistical behavior of ‘unforced’ trends in the pattern correlation statistics. For the combined sulfate aerosol/CO2 experiment, the 50-year R(t) trends for the JJA and SON signals are highly significant. Results are robust in that they do not depend on the choice of control run used to estimate natural variability noise properties. The R(t) trends for the C02-only signal are not significant in any season. C(t) trends for signals from both the C02-only and combined forcing experiments are highly significant in all seasons and for all trend lengths (except for trends over the last 10 years), indicating large global-mean changes relative to the two natural variability estimates used here. The caveats regarding the signals and natural variability noise which form the basis of this study are numerous. Nevertheless, we have provided first evidence that both the largest-scale (global-mean) and smaller-scale (spatial anomalies about the global mean) components of a combined C02/anthropogenic sulfate aerosol signal are identifiable in the observed near-surface air temperature data. If the coupled-model noise estimates used here are realistic, we can be highly confident that the anthropogenic signal that we have identified is distinctly different from internally generated natural variability noise. The fact that we have been able to detect the detailed spatial signature in response to combined C02 and sulfate aerosol forcing, but not in response to C02 forcing alone, suggests that some of the regional-scale background noise (against which we were trying to detect a C02-only signal) is in fact part of the signal of a sulfate aerosol effect on climate. The large effect of sulfate aerosols found in this study demonstrates the importance of their inclusion in experiments designed to simulate past and future climate change.

A Bivariate Time Series Approach to Anthropogenic Trend Detection in Hemispheric Mean Temperatures

Abstract A bivariate time series regression approach is used to model observed variations in hemispheric mean temperature over the period 1900–96. The regression equations include deterministic predictor variables and lagged values of the two predictands, and two different forms of this basic structure are employed. The deterministic predictors considered are simple linear trends, various climate model–generated time series based on different combinations of greenhouse gas, sulfate aerosol, and solar forcing, and the Southern Oscillation index (SOI). With linear trends as the only predictors, the best model is a fourth-order bivariate autoregressive model including lagged Southern Hemisphere (SH) to Northern Hemisphere (NH) dependence, as in previous work by Kaufmann and Stern. The estimated NH and SH trends are both +0.67°C century−1, and both are highly statistically significant. If SOI is included as an additional predictor, however, a first-order time series model, with no SH to NH dependence, is an a...

Identification of Anthropogenic Climate Change Using a Second-Generation Reanalysis

[1] Changes in the height of the tropopause provide a sensitive indicator of human effects on climate. A previous attempt to identify human effects on tropopause height relied on information from ‘first-generation’ reanalyses of past weather observations. Climate data from these initial model-based reanalyses have well-documented deficiencies, raising concerns regarding the robustness of earlier detection work that employed these data. Here we address these concerns using information from the new second-generation ERA-40 reanalysis. Over 1979 to 2001, tropopause height increases by nearly 200 m in ERA-40, partly due to tropospheric warming. The spatial pattern of height increase is consistent with climate model predictions of the expected response to anthropogenic influences alone, significantly strengthening earlier detection results. Atmospheric temperature changes in two different satellite data sets are more highly correlated with changes in ERA-40 than with those in a first-generation reanalysis, illustrating the improved quality of temperature information in ERA-40. Our results provide support for claims that human activities have warmed the troposphere and cooled the lower stratosphere over the last several decades of the 20th century, and that both of these changes in atmospheric temperature have contributed to an overall increase in tropopause height. INDEX TERMS: 0350 Atmospheric Composition and Structure: Pressure, density, and temperature; 0370 Atmospheric Composition and Structure: Volcanic effects (8409); 1620 Global Change: Climate dynamics (3309); 1640 Global Change: Remote sensing; KEYWORDS: climate change, detection, reanalysis

On past temperatures and anomalous late-20th century warmth

Evidence from paleoclimatic sources and modeling studies support AGUs official position statement on climate change and greenhouse gases; namely that there is a compelling basis for concern over future climate changes, including increases in global-mean surface temperatures, due to increased concentrations of greenhouse gases, primarily from fossil fuel burning. More specifically a number of reconstructions of large-scale temperature changes over the past millennium support the conclusion that late-20th century warmth was unprecedented over at least the past millennium. Modeling and statistical studies indicate that such anomalous warmth cannot be fully explained by natural factors, but instead, require a significant anthropogenic forcing of climate that emerged during the 19th and 20th centuries.

Identifying human influences on atmospheric temperature.

We perform a multimodel detection and attribution study with climate model simulation output and satellite-based measurements of tropospheric and stratospheric temperature change. We use simulation output from 20 climate models participating in phase 5 of the Coupled Model Intercomparison Project. This multimodel archive provides estimates of the signal pattern in response to combined anthropogenic and natural external forcing (the fingerprint) and the noise of internally generated variability. Using these estimates, we calculate signal-to-noise (S/N) ratios to quantify the strength of the fingerprint in the observations relative to fingerprint strength in natural climate noise. For changes in lower stratospheric temperature between 1979 and 2011, S/N ratios vary from 26 to 36, depending on the choice of observational dataset. In the lower troposphere, the fingerprint strength in observations is smaller, but S/N ratios are still significant at the 1% level or better, and range from three to eight. We find no evidence that these ratios are spuriously inflated by model variability errors. After removing all global mean signals, model fingerprints remain identifiable in 70% of the tests involving tropospheric temperature changes. Despite such agreement in the large-scale features of model and observed geographical patterns of atmospheric temperature change, most models do not replicate the size of the observed changes. On average, the models analyzed underestimate the observed cooling of the lower stratosphere and overestimate the warming of the troposphere. Although the precise causes of such differences are unclear, model biases in lower stratospheric temperature trends are likely to be reduced by more realistic treatment of stratospheric ozone depletion and volcanic aerosol forcing.

Ensemble Simulation of Twenty–First Century Climate Changes: Business–as–Usual versus CO2 Stabilization

Abstract Natural variability of the climate system imposes a large uncertainty on future climate change signals simulated by a single integration of any coupled ocean–atmosphere model. This is especially true for regional precipitation changes. Here, these uncertainties are reduced by using results from two ensembles of five integrations of a coupled ocean–atmosphere model forced by projected future greenhouse gas and sulfate aerosol changes. Under a business–as–usual scenario, the simulations show a global warming of ~1.9°C over the twenty–first century (continuing the trend observed since the late 1970s), accompanied by a ~3% increase in global precipitation. Stabilizing the CO2 level at 550 ppm reduces the warming only moderately (by ~0.4°C in 2100). The patterns of seasonal–mean temperature and precipitation change in the two cases are highly correlated (r » 0.99 for temperature and r » 0.93 for precipitation). Over the midlatitude North Atlantic Ocean, the model produces a moderate surface cooling (1...