CGD's Dr. Tom Wigley

Abstract

Observations show both a pronounced increase in ocean heat content (OHC) over the second half of the 20th century and substantial OHC variability on interannual to decadal timescales. While climate models are able to simulate overall changes in OHC, they are generally thought to underestimate the amplitude of OHC variability. Using simulations of 20th century climate performed with 13 numerical models, we demonstrate that the apparent discrepancy between modeled and observed variability is largely explained by accounting for changes in observational coverage and instrumentation and including the effects of volcanic eruptions. Our work casts doubt on two recent claims: that the 0-700 meter layer of the global ocean experienced a substantial OHC decrease over 2003 to 2005, and that models cannot replicate such changes. Our analysis shows that the 2003 to 2005 cooling is largely an artifact of a systematic change in the observing system, with the deployment of ARGO floats reducing a warm bias in the original observing system.

Figure caption: Effect of subsampling on the temporal variability of 0-700 meter volume averaged ocean temperature changes. Results were calculated using temperature anomalies spatially-averaged over the global ocean. The temporal standard deviations computed from spatially complete data (x-axis) are plotted against the temporal standard deviations obtained from subsampled data (y-axis). The observed coverage mask (from WOA 2005) was used to subsample both the model and the ISHII6.2 temperature data. Colored symbols identify the 44 realizations of the IPCC 20c3m experiment. Colored circles (triangles) represent models that include (exclude) volcanic forcing. The diagonal lines denote equal standard deviations in the spatially complete and subsampled data. Temporal standard deviations were calculated after removal of overall linear trends, and are based on annual mean anomaly data for the period 1955 to 2000 (or 1999 in the case of model 20c3m experiments ending in that year).

Support: National Science Foundation.

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Bonfils, C., Duffy, P.B., Santer, B.D., Lobell, D.B., Phillips, T.J., Wigley, T.M.L., and Doutriaux, C., 2007: Detection of unusual trends in California seasonal-Mean temperatures. Climatic Change (in press).

Abstract

We use nine different observational datasets to estimate California-average temperature trends during the periods 1950-1999 and 1915-2000. Observed results are compared to trends from a suite of climate model simulations of natural internal climate variability. On the longer (86-year) timescale, increases in annual-mean surface temperature in all observational datasets are consistently distinguishable from climate noise. On the shorter (50-year) timescale, results are sensitive to the choice of observational dataset. For both timescales, the most robust results are large positive trends in mean and maximum daily temperatures in late winter/early spring, as well as increases in minimum daily temperatures from January to September. These trends are inconsistent with model-based estimates of natural internal climate variability, and thus require one or more external forcing agents to be explained. Observational datasets with adjustments for urbanization effects do not yield markedly different results from unadjusted data. Our findings suggest that the warming of Californian winters over the twentieth century is associated with human-induced changes in large-scale atmospheric circulation. We hypothesize that the lack of a detectable increase in summertime maximum temperature arises from a cooling associated with large-scale irrigation. This cooling may have, until now, counteracted summertime warming induced by increasing greenhouse gases and urbanization effects.

Figure caption: Observed temperature trends over 1950-1999 (solid dots) and model-derived estimates of the 95% confidence interval for natural internal variability. Observational trends are from a variety of different datasets. Climate noise estimates are based on multi-model unforced 50-year trend distributions. The upper and lower limits of the shaded area represent the 95% confidence intervals of the trend distributions and were computed as +/-1.96 × SE, the standard error of the sampling distribution. Results are for daily-mean temperature, daily minimum temperature, and daily maximum temperature, and for JFM and JAS seasons. Vertical bars represent the standard error for the trend (accounting for the temporal autocorrelation of the regression residuals) × 1.641 (one-tailed t-test; see Santer et al., 2000).

Support: California Energy Commission.

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Richels, R., Manne, A.S. and Wigley, T.M.L., 2007: Moving beyond concentrations: The challenge of limiting temperature change. (In) Human Induced Climate Change: An Interdisciplinary Assessment, eds. Michael Schlesinger, Haroon Kheshgi, Joel Smith, Francisco de la Chesnaye, John M. Reilly, Tom Wilson and Charles Kolstad, Eds., Cambridge University Press, 387-402.

Introduction

The climate debate is fraught with uncertainty. In order to better understand the link between human activities and impacts, we must first understand the causal chain between the two, i.e., the relationship between human activities, emissions, concentrations, radiative forcing, temperature, climate, and impacts. The focus of the UNFCCC is on atmospheric concentrations of greenhouse gases. Although this represents a major step forward by advancing the debate beyond emissions, it does not go far enough. In this paper, we carry the analysis beyond atmospheric concentrations to temperature change. Although closely linked to concentrations, we believe that temperature is a more meaningful metric in that it incorporates several additional considerations critical for informed policymaking. In particular, the uncertainty related to climate sensitivity can dramatically alter the effectiveness of a prescribed concentration ceiling when trying to control temperature change. If the focus is on limiting atmospheric concentrations, policymakers may be given a false impression regarding the impact of their actions.

The goal of the UN Framework Convention on Climate Change (UNFCCC) is to stabilize atmospheric concentrations of greenhouse gases. Although closely linked to concentrations, we believe that focusing on temperature change would be more meaningful in that it incorporates the sensitivity of the climate system to changes in atmospheric composition. The analysis explicitly incorporates several uncertainties critical to future temperature: economic growth, climate sensitivity and the rate of ocean heat uptake. We then examine the concentration ceilings necessary to limit temperature change to 2°C and 3°C and find that the uncertainty in the required ceilings can exceed 300ppmv by 2100. Such information is critical for managing the risks of climate change. We also find that, in terms of mitigation costs, differences in the assumed technological future can translate into trillions of dollars worldwide over the 21st century. Finally, we find that although expectations about the long-term price of greenhouse gas abatement have little effect on rate of departure from the emissions baseline, they do have a substantial effect on the near-term price of carbon.

Figure caption: Gross benefits from a research and development program under alternative global-mean temperature constraints (50th percentile values highlighted).

Support: National Science Foundation.

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Santer, B.D., Mears, C., Wentz, F.J., Taylor, K.E., Gleckler, P.J., Wigley, T.M.L., Barnett, T.P., Boyle, J.S., Brüggemann, W., Gillett, N.P., Klein, S.A., Meehl, G.A., Nozawa, T., Pierce, D.W., Stott, P.A., Washington, W.M. and Wehner, M.F., 2007: Identification of human-induced changes in atmospheric moisture content. Proceedings of the National Academy of Sciences (PNAS), 104 (39) doi:10.1073/pnas.0702872104, 15248-15253.

Abstract

Data from the satellite-based Special Sensor Microwave Imager (SSM/I) show that the total atmospheric moisture content over oceans has increased by 0.41 kg/m²/decade since 1988. Results from current climate models indicate that water vapor increases of this magnitude cannot be explained by climate noise alone. In a formal detection and attribution analysis using the pooled results from 22 different climate models, the simulated "fingerprint" pattern of anthropogenically-caused changes in water vapor is identifiable with high statistical confidence in the SSM/I data. Experiments in which forcing factors are varied individually suggest that this "fingerprint match" is primarily due to human-caused increases in greenhouse gases, and not to solar forcing or recovery from the eruption of Pinatubo. Our findings provide preliminary evidence of an emerging anthropogenic signal in the moisture content of Earth's atmosphere.

Figure caption: Comparison of observed trends in <W_o>, the atmospheric water vapor over near-global oceans, with model simulations of unforced (A) and externally-forced <W_o> trends (B). The sampling distribution of unforced 19-year trends in <W_o> was calculated from control runs performed with 22 different climate models. This comprises a total of 8,848 years of data, and 459 independent samples of unforced <W_o> trends. Residual control run drift was not subtracted prior to the estimation of the trend sampling distribution, thus inflating the standard error of the distribution and making it more difficult to reject the null hypothesis that internal variability alone could explain the observed water vapor trend. Forced <W_o> trends over 1988 to 1999 were estimated from 71 realizations of the 20CEN experiment performed with the same 22 climate models. The SSM/I trend over 1988 to 1999 is larger than the mean of the model distribution of forced trends, in part because of the effects of the large observed El Niño event in 1997/98 (Fig. 1A), which is close to the end of the trend period used in Fig. 2B.

Support: Partially supported by the National Science Foundation.

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Santer, B.D. and Wigley, T.M.L., 2007: Progress in detection and attribution research. (In) Climate Change Science and Policy, eds. S.H. Schneider, A. Rosencranz and M.D. Mastrandrea, Island Press, Washington, DC, in press.

Abstract

Over the last century, we have observed large and coherent changes in many different aspects of Earth's climate. The oceans and land surface have warmed. Atmospheric moisture has increased. Glaciers have retreated over most of the globe. Sea level has risen. Snow and sea-ice extent have decreased in the Northern Hemisphere. The stratosphere has cooled, and there are now reliable indications that the troposphere has warmed. The height of the tropopause has increased. Individually, all of these changes are consistent with our scientific understanding of how the climate system should be responding to anthropogenic forcing. Collectively, this behavior is inconsistent with the changes that we would expect to occur due to natural variability alone. Our chapter provides a personal perspective on recent developments (post IPCC TAR) in the field of detection and attribution (D&A) research - that is, research directed towards detecting significant climate change, and attributing it to a specific cause or causes.

Figure caption: Zonally-averaged temperature changes as a function of latitude (from 90°N-90°S) and height (from 1000 hPa to 10 hPa). Results are from single forcing experiments (A through E) with historical changes in five individual forcings, and from an experiment with simultaneous changes in all five forcings (F). All experiments were performed with the coupled atmosphere-ocean Parallel Climate Model (PCM). Temperature changes are expressed as linear trends in degrees Celsius per century, and were calculated over the period from 1890 to 1999. All results are ensemble means (averages over four individual realizations).

Support: Partially supported by the National Science Foundation.

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Santer, B. D., T. M. L. Wigley, P. J. Gleckler, C. Bonfils, M. Wehner, K. M. AchutaRao, T. P. Barnett, J. S. Boyle, W. Brüggemann, M. Fiorino, N. Gillett, J. E. Hansen, P. D. Jones, S. A. Klein, G. A. Meehl, S. C. B. Raper, R. W. Reynolds, K. E. Taylor, W. M. Washington, 2006: Forced and unforced ocean temperature changes in the Atlantic and Pacific tropical cyclogenesis regions. Proceedings of the National Academy of Sciences (PNAS), 103, 13905-13910.

Abstract

Previous research has identified links between changes in sea surface temperature (SST) and hurricane intensity. We use climate models to study the possible causes of SST changes in Atlantic and Pacific tropical cyclogenesis regions. The observed SST increases in these regions range from 0.32 to 0.67C over the 20th century. The 22 climate models examined here suggest that century-timescale SST changes of this magnitude cannot be explained solely by unforced variability of the climate system. We employ model simulations of natural internal variability to make probabilistic estimates of the contribution of external forcing to observed SST changes. For the period 1906-2005, we find an 84% chance that external forcing explains at least 67% of observed SST increases in the two tropical cyclogenesis regions. Model "20th century" simulations, with external forcing by combined anthropogenic and natural factors, are generally capable of replicating observed SST increases. In experiments where forcing factors are varied individually rather than jointly, human-caused changes in greenhouse gases are the main driver of the 20th century SST increases in both tropical cyclogenesis regions.

Figure caption: Time series of monthly-mean, spatially averaged SST anomalies for the Atlantic (A) and Pacific tropical cyclogenesis regions. Observed data are from the NOAA ERSST data set. Model simulations are partitioned into two groups, with and without volcanic forcing (V and No-V). All data are anomalies with respect to 1900 through 1909 averages and are low-pass filtered. Yellow and gray envelopes are 1 and 2-sigma confidence intervals for the V averages. Model data are through Dec. 1999; observed data are through Dec. 2005. Panel C shows an estimate of volcanic forcing, with dashed vertical lines being at the times of maximum forcing.

Support: Partially supported by the National Science Foundation.

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Smith, S. J., T. M. L. Wigley, 2006: Multi-gas forcing stabilization with MiniCAM. Energy J., Special Issue, 373-391.

Abstract

This paper examines the role of climate forcing agents other than carbon dioxide using the MiniCAM integrated assessment model for both no-climate-policy and policy emissions scenarios. Non-CO₂ greenhouse-gas forcing is dominated by methane and tropospheric ozone. Assumptions about the prevalence of methane recovery and local air pollution controls in the no-policy cases are a critical determinant of methane and ozone-precursor emissions. When these factors are considered, emissions are substantially reduced relative to earlier estimates. This reduces their potential as climate mitigation agents through specific climate policies. Nevertheless, the addition of non-CO₂ greenhouse gas and ozone precursor abatement options significantly reduces mitigation costs in the first half of the 21st century (by up to 40%) compared to the case where only CO₂ abatement options are pursued. While the influences of aerosols are small by the end of the century, there is a significant interaction in the early 21st century between policies to reduce CO₂ emissions and SO2 emissions, even in the presence of SO2-related pollution control policies. The attendant reduced aerosol cooling can more than offset the reduction in warming that accrues from reduced CO₂. When non-CO₂ gases are included in the policy, the net effect is that global-mean climate change to 2050 is practically unaffected by mitigation policy.

Figure caption: Forcing from pre-industrial times to 2100 for tropospheric ozone and sulfate aerosols oxide in the 35 scenarios. Note reversal of axis for aerosol forcing such that high absolute forcing is on the right. Each of the five models used to construct these scenarios is identified by a different symbol. Symbols represent the model (Nakicenevic et al. 2000). Colors indicate the SRES scenario family with red -A1, brown -A2, green -B1, and blue -B2. Note that MiniCAM tropospheric ozone values are not considered in this analysis since emissions for precursor gases for the MiniCAM SRES scenarios were derived from other scenarios (MiniCAM ozone values were arbitrarily set to 0.50 W/m² in this Figure.)

Support: EPRI and by NSF.

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Wigley, T.M.L., 2007: The effect of changing climate on the frequency of extreme events. Climatic Change, accepted for publication.

In some areas of climate impact analysis, the possible impact of a changing mean climate has been dismissed by some writers either because of a belief that society can adapt to a slowly changing mean and/or because expected rates of future changes lie within or not far outside those experienced in the past. The two standard counter arguments to this optimistic view are; (1) the future will lead to much longer periods of protracted change in one direction, with final conditions well into the no-analogue region; and/or (2) the main impacts will accrue through changes in the frequency of extremes. In the literature on the greenhouse effect, lip service is often paid to the effect of changes in the frequency of extremes. But just how will a slowly changing mean affect the frequency of extremes? Quantitative discussions of this subject are rare, and, surprisingly, there are some extremely simple analyses that have not yet been carried out. The purpose of this note is to remedy this deficiency.

Figure caption: Change in the probability of exceeding a specified extreme value as the mean is changed, for Normally distributed data. The three curves correspond to "initial" probabilities (i.e. prior to a change in the mean) of 0.1, 0.01, and 0.001. As an example, an event with an initial probability of p=0.001 (point A) becomes 140 times more likely (p=0.14, point B) if the mean is increased by two standard deviations.

Support: NSF.

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Wigley, T. M. L., 2007: CO₂ emissions: A piece of the pie. Science, 316, 829-830.

In his policy forum "CO₂ Arithmetic" (9 Mar., p. 1371), W. S. Broecker uses the idea of a permissible cumulative CO₂ emissions "pie" to conceptualize the allocation of future emissions among the world's nations. The size of the pie is determined by the target for atmospheric CO₂ concentration stabilization; the higher the target level, the larger the pie. To calculate the size of the pie for different stabilization levels, Broecker notes that, for every 4 Gt of carbon emitted today, atmospheric CO₂ concentration increases by about 1 ppm. This corresponds to a current airborne fraction (i.e., the change in atmospheric loading per unit of total emissions) of about 0.5. He then assumes that this value for the airborne fraction can be applied to future concentration stabilization scenarios; i.e., he assumes that every 1 ppm of concentration increase relative to today increases the size of the pie by 4 Gt of carbon. This assumption is incorrect and leads to a serious underestimate of the size of the pie.

Figure caption: (Top) WRE concentration stabilization profiles (1) stabilizing at 450 ppm (in 2100), 550 ppm (in 2150), and 650 ppm (in 2200). (Middle) Corresponding cumulative emissions from mid-2007. Emissions are the sum of fossil and land-use change emissions. The horizontal lines show the allowable cumulative emissions given by Broecker for the 450 and 550 ppm stabilization cases. Arrows show how much larger the corrected cumulative emissions are compared with the Broecker estimates. (Bottom) Airborne fractions (change in atmospheric loading per unit of total emissions) for the three stabilization cases. Broecker assumes that the airborne fraction will remain constant at the present value (around 0.5).

Support: NSF and EPRI.

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Wigley, T.M.L., Richels, R. and Edmonds, J.A., 2007: Overshoot pathways to CO₂ stabilization in a multi-gas context. (In) Human Induced Climate Change: An Interdisciplinary Assessment, eds. Michael Schlesinger, Haroon Kheshgi, Joel Smith, Francisco de la Chesnaye, John M. Reilly, Tom Wilson and Charles Kolstad, Cambridge University Press, Cambridge, UK and New York, NY, USA, pp. 84-92.

Introduction

Stabilization of the climate system requires stabilization of greenhouse-gas concentrations. Most work to date has considered only stabilization of CO₂, where there are choices regarding both the concentration stabilization target and the pathway towards that target. Here we consider the effects of accounting for non-CO₂ gases (CH4 and N2O), for different CO₂ targets and different pathways. As primary cases for CO₂ we use the standard 'WRE' pathways to stabilization at 450ppm or 550ppm. We also consider a new 'overshoot' concentration profile for CO₂ in which concentrations initially exceed and then decline towards a final stabilization level of 450ppm, as might occur if an initial target choice were later found to be too high.

Figure caption: (a) Revised WRE and a new overshoot concentration stabilization profile for CO₂ compared with the baseline (P50) no-climate-policy scenario. (b) Methane concentrations based on cost-effective emissions reductions (Manne and Richels, 2001) corresponding to the WRE450, WRE550 and overshoot profiles for CO₂. The baseline (P50) no-climate-policy scenario result is shown for comparison. (c) Nitrous oxide concentrations based on cost-effective emissions reductions (Manne and Richels, 2001) corresponding to the WRE450, WRE550 and overshoot profiles for CO₂. The baseline (P50) no-climate-policy scenario result is shown for comparison.

Support: National Science Foundation.