A rose by any other name ...?: What members of the general public prefer to call “climate change”

Unlike many other environmental problems, the terms used to describe the phenomenon of increasing atmospheric concentrations of anthropogenic greenhouse gases are many, with multiple and sometimes conflicting meanings. Whether there are meaningful distinctions in public perceptions of “global warming,” “climate change,” and “global climate change” has been a topic of research over the past decade. This study examines public preferences for these terms based on respondent characteristics, including climate change beliefs, political affiliation, and audience segment status derived from the “Global Warming’s Six Americas” classification. Certainty of belief in global warming, political affiliation and audience segment status were found to be the strongest predictors of preference, although “I have no preference” was the modal response. Global warming appears to be a more polarizing term than climate change, preferred most by people already concerned about the issue, and least by people who don’t believe climate change is occurring. Further research is needed to identify which of these two names promotes the engagement of people across the spectrum of climate change beliefs in constructive dialogue about the issue.     

Bayesian multi-model projection of climate: bias assumptions and interannual variability

Current climate change projections are based on comprehensive multi-model ensembles of global and regional climate simulations. Application of this information to impact studies requires a combined probabilistic estimate taking into account the different models and their performance under current climatic conditions. Here we present a Bayesian statistical model for the distribution of seasonal mean surface temperatures for control and scenario periods. The model combines observational data for the control period with the output of regional climate models (RCMs) driven by different global climate models (GCMs). The proposed Bayesian methodology addresses seasonal mean temperatures and considers both changes in mean temperature and interannual variability. In addition, unlike previous studies, our methodology explicitly considers model biases that are allowed to be time-dependent (i.e. change between control and scenario period). More specifically, the model considers additive and multiplicative model biases for each RCM and introduces two plausible assumptions (“constant bias” and “constant relationship”) about extrapolating the biases from the control to the scenario period. The resulting identifiability problem is resolved by using informative priors for the bias changes. A sensitivity analysis illustrates the role of the informative prior. As an example, we present results for Alpine winter and summer temperatures for control (1961–1990) and scenario periods (2071–2100) under the SRES A2 greenhouse gas scenario. For winter, both bias assumptions yield a comparable mean warming of 3.5–3.6°C. For summer, the two different assumptions have a strong influence on the probabilistic prediction of mean warming, which amounts to 5.4°C and 3.4°C for the “constant bias” and “constant relation” assumptions, respectively. Analysis shows that the underlying reason for this large uncertainty is due to the overestimation of summer interannual variability in all models considered. Our results show the necessity to consider potential bias changes when projecting climate under an emission scenario. Further work is needed to determine how bias information can be exploited for this task.     

The coupling of optimal economic growth and climate dynamics

In this paper, we study optimal economic growth programs coupled with climate change dynamics. The study is based on models derived from MERGE, a well established integrated assessment model (IAM). We discuss first the introduction in MERGE of a set of “tolerable window” constraints which limit both the temperature change and the rate of temperature change. These constraints, obtained from ensemble simulations performed with the Bern 2.5-D climate model, allow us to identity a domain intended to preserve the Atlantic thermohaline circulation. Next, we report on experiments where a two-way coupling is realized between the economic module of MERGE and an intermediate complexity “3-D-” climate model (C-GOLDSTEIN) which computes the changes in climate and mean temperature. The coupling is achieved through the implementation of an advanced “oracle based optimization technique” which permits the integration of information coming from the climate model during the search for the optimal economic growth path. Both cost-effectiveness and cost-benefit analysis modes are explored with this combined “meta-model” which we refer to as GOLDMERGE. Some perspectives on future implementations of these approaches in the context of “collaborative” or “community” integrated assessment modules are derived from the comparison of the different approaches.     

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     

Numerical study for potential predictability of short— term anomalous climate change caused by El nino

In this paper, the two-layer IAP model with sea surface temperature anomalies in the equatorial central-eastern Pacific is used to investigate potential predictability of global short-term anomalous climate change caused by El Nino via the “switching” experiments. The experimental results show that short-term anomalous climate change in the tropics is mainly caused by instantaneous response of tropical atmosphere to SSTA in the tropics. The effective period of this kind of anomalous climate is shorter and about monthly scale. In the high latitudes, the anomalous cli-mate is mainly caused by the lag response of atmosphere to SSTA in the tropics. The strongest influence appears in the month after a half year when the SSTA in the tropics disappears. Therefore, potential predictability of short-term anomalous climate change may be reached to one year; anomalous climate change in the middle-latitudes is not only affected by instantaneous response to SSTA in the tropics, but also by lag response to that. Therefore, short-term climate change prediction with monthly time scale can be not only done by using SSTA in the tropics, but also predic-tion of short-term climate after a half year can be done and its effective predictable period may be reached to one year.     

Climate uncertainties and their discontents: increasing the impact of assessments on public understanding of climate risks and choices

US public awareness of the reality and risks of human-caused climate change remains limited, despite strong evidence presented in the IPCC and other major climate assessments. One contributing factor may be that the immense collective effort to produce periodic climate assessments is typically not well matched with public communication and outreach efforts for these reports, leaving a vacuum to be filled by less authoritative sources. Print and online media coverage provides one metric of the US public reach of selected climate assessments between 2000 and 2010. The number of Lexis-Nexis articles for the search terms “climate change” or “global warming” within 14 days of each report’s release varied significantly over time with a peak occurring in 2007. When compared to background “chatter” relating to climate change, each assessment had widely diverse penetration in the US media (~4% for US National Climate Assessment in 2000; ~17% for Arctic Climate Impacts Assessment in 2004; ~19% and ~10% for Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report Working Group I and Working Group II respectively in 2007; ~4% for the US Global Change Research Program (USGCRP) assessment report in 2009; and ~5% for US National Research Council’s America’s Climate Choices reports in 2010). We propose ways to improve the public reach of climate assessments, focusing in particular on approaches to more effectively characterize and communicate the role of uncertainty in human actions as distinct from other sources of uncertainty across the range of possible climate futures.     

Modelling the sensitivity of Mediterranean Outflow to anthropogenically forced climate change

 The possible future impact of anthropogenic forcing upon the circulation of the Mediterranean, and the exchange through the Strait of Gibraltar is investigated using a Cox-type model of the Mediterranean at 0.25° × 0.25° resolution, forced by “control” and “greenhouse” scenarios provided by the HadCM2 coupled climate model. The current structure of the Mediterranean forced by the “control” climate is compared with observations: certain aspects of the present circulation are reproduced, but others are absent or incorrectly represented. Deficiencies are most probably due to weaknesses in the forcing climatology generated by the climate model, so some caution must be exercised in interpreting the enhanced greenhouse simulation. Comparison of the control and greenhouse scenarios suggests that deep-water production in the Mediterranean may be reduced or cease in the relatively near future. The results also suggest that the Mediterranean outflow, may become warmer and more saline, but less dense, and hence shallower. The volume of the exchange at the Strait of Gibraltar seems to be relatively insensitive to future climate change, however. Our results indicate that a parameterisation of Gibraltar exchange and Mediterranean Outflow Water (MOW) production may be able to provide adequate representation of the changes we observe for the purposes of the current generation of climate models. Received: 10 August 1998 / Accepted: 11 October 1999     

用 IAP／LASG GOALS模式模拟CO2增加引起的东亚地区气候变化

Two simulations, one for the control run and another for the perturbation run, with a global coupled ocean-atmosphere-land system model (IAP / LASG GOALS version 4) have been carried out to study the global warming, with much detailed emphasis on East Asia. Results indicate that there is no climate drift in the control run and at the time of CO2 doubling the global temperature increases about 1.65℃. The GOALS model is able to simulate the observed spatial distribution and annual cycles of temperature and precipitation for East Asia quite well. But, in general, the model underestimates temperature and overestimates rainfall amount for regional annual average. For the climate change in East Asia, the temperature and precipitation in East Asia increase 2. l℃ and 5% respectively, and the maximum warming occurs at middle-latitude continent and the maximum precipitation increase occurs around 25°N with reduced precipitation in the tropical western Pacific.