Global warming estimates,media expectations,and the asymmetry of scientific challenge

Mass media in the U.S. continue to suggest that scientific consensus estimates of global climate disruption, such as those from the Intergovernmental Panel on Climate Change (IPCC), are “exaggerated” and overly pessimistic. By contrast, work on the Asymmetry of Scientific Challenge (ASC) suggests that such consensus assessments are likely to understate climate disruptions. This paper offers an initial test of the competing expectations, making use of the tendency for science to be self-correcting, over time. Rather than relying in any way on the IPCC process, the paper draws evidence about emerging science from four newspapers that have been found in past work to be biased against reporting IPCC findings, consistently reporting instead that scientific findings are “in dispute.” The analysis considers two time periods — one during the time when the papers were found to be overstating challenges to then-prevailing scientific consensus, and the other focusing on 2008, after the IPCC and former Vice-President Gore shared the Nobel Prize for their work on climate disruption, and before opinion polls showed the U.S. public to be growing more skeptical toward climate science once again. During both periods, new scientific findings were more than twenty times as likely to support the ASC perspective than the usual framing of the issue in the U.S. mass media. The findings indicate that supposed challenges to the scientific consensus on global warming need to be subjected to greater scrutiny, as well as showing that, if reporters wish to discuss “both sides” of the climate issue, the scientifically legitimate “other side” is that, if anything, global climate disruption may prove to be significantly worse than has been suggested in scientific consensus estimates to date.     

Do weak AR4 models bias projections of future climate changes over Australia?

Regional climate projections using climate models commonly use an “all-model” ensemble based on data sets such as the Intergovernmental Panel on Climate Change’s (IPCC) 4th Assessment (AR4). Some regional assessments have omitted models based on specific criteria. We use a criteria based on the capacity of climate models to simulate the observed probability density function calculated using daily data, model-by-model and region-by-region for each of the AR4 models over Australia. We demonstrate that by omitting those climate models with relatively weak skill in simulating the observed probability density functions of maximum and minimum temperature and precipitation, different regional projections are obtained. Differences include: larger increases in the mean maximum and mean minimum temperatures, but smaller increases in the annual maximum and minimum temperatures. There is little impact on mean precipitation but the better models simulate a larger increase in the annual rainfall event combined with a larger decrease in the number of rain days. The weaker models bias the amount of mean warming towards lower increases, bias annual maximum temperatures to excessive warming and bias precipitation such that the amount of the annual rainfall event is under-estimated. We suggest that omitting weak models from regional scale estimates of future climate change helps clarify the nature and scale of the projected impacts of global warming.     

The stability of the MOC as diagnosed from model projections for pre-industrial, present and future climates

The stability of the Atlantic meridional overturning circulation (MOC) is investigated for various climate scenario runs, using data from the CMIP3 archive of coupled atmosphere-ocean models. Apart from atmospheric feedbacks, the sign of the salt flux into the Atlantic basin that is carried by the MOC determines whether the MOC is in the single or multiple equilibria regime. This salt advection feedback is analyzed by diagnosing the freshwater and salt budgets for the combined Atlantic and Arctic basins. Consistent with the finding that almost all coupled climate models recover from hosing experiments, it is found that most models feature a negative salt advection feedback in their pre-industrial climate: freshwater perturbations are damped by this feedback, excluding the existence of a stable off-state for the MOC. All models feature enhanced evaporation over the Atlantic basin in future climates, but for a moderate increase in radiative forcing (B1 and 2 CO₂ scenarios), there is a decrease of the fresh water flux carried by the MOC into the Atlantic (the deficit is made up by increased fresh water transport by the gyre circulation). In this forcing regime the salt advection feedback becomes less negative: for three models from an ensemble of eight it is positive in a 2 CO₂ climate, while two models feature a positive feedback in the pre-industrial climate. For even warmer climates (A1B-equilibrium and 4 CO₂) the salt feedback becomes more negative (damping) again. It is shown that the decrease in northward fresh water transport at 34°S by the MOC (in B1-equilibrium and 2 CO₂) is due to a reduction of the inflow of intermediate waters relative to thermocline waters, associated with a robust shoaling of the MOC in future, warmer climates. In A1B and 4 CO₂ climates northward freshwater transport increases again. The MOC keeps shoaling, but both intermediate and thermocline water masses freshen.     

Dynamics,stratospheric ozone,and climate change

Abstract

Dynamics affects the distribution and abundance of stratospheric ozone directly through transport of ozone itself and indirectly through its effect on ozone chemistry via temperature and transport of other chemical species. Dynamical processes must be considered in order to understand past ozone changes, especially in the northern hemisphere where there appears to be significant low‐frequency variability which can look “trend‐like” on decadal time scales. A major challenge is to quantify the predictable, or deterministic, component of past ozone changes. Over the coming century, changes in climate will affect the expected recovery of ozone. For policy reasons it is important to be able to distinguish and separately attribute the effects of ozone‐depleting substances and greenhouse gases on both ozone and climate. While the radiative‐chemical effects can be relatively easily identified, this is not so evident for dynamics — yet dynamical changes (e.g., changes in the Brewer‐Dobson circulation) could have a first‐order effect on ozone over particular regions. Understanding the predictability and robustness of such dynamical changes represents another major challenge. Chemistry‐climate models have recently emerged as useful tools for addressing these questions, as they provide a self‐consistent representation of dynamical aspects of climate and their coupling to ozone chemistry. We can expect such models to play an increasingly central role in the study of ozone and climate in the future, analogous to the central role of global climate models in the study of tropospheric climate change.     

Spatiotemporal change in geographical distribution of global climate types in the context of climate warming

After standardizing global land climate gridded data from the Climatic Research Unit TS (time-series) 3.1 dataset for the period 1901–2009, cluster analysis is used to objectively classify world climates into 14 climate types. These climate types establish a baseline classification map and the types are named according to Köppen–Geiger climate classifications. Although the cluster analysis and Köppen classification methods are very different, the distributions of climate types obtained by the two methods are similar. Moreover, the climate types we identify also coincide well with their corresponding vegetation types. Thus, cluster analysis can be used as an effective alternative to the Köppen classification method for classifying world climate types. The spatial and temporal changes in geographical distribution of global climate types were investigated in 25-year intervals, and Cohen’s kappa coefficient is used to detect agreement between the periods. Globally, although an obvious trend in increasing global temperature is found, distribution of climate types overall show no distinct changes over the periods. However, at the regional scale, spatial change in distribution of climate types is evident in South America and Africa. In South America, larger areas of the “fully humid equatorial rainforest” (Af) and “equatorial savannah with dry winter” (Aw) climate types have changed types. In Africa, changes mainly occurred in the Af, “equatorial savannah with dry summer” (As), Aw, “steppe climate” (BS), and “desert climate” (BW) climate types. Moreover, some climate types, including Af, “equatorial monsoon” (Am), BS, BW, and “tundra climate” (ET), were susceptible to temporal climate changes, especially in the period 1976–2009.     

Shifts in African crop climates by 2050, and the implications for crop improvement and genetic resources conservation

Increased understanding of the substantial threat climate change poses to agriculture has not been met with a similarly improved understanding of how best to respond. Here we examine likely shifts in crop climates in Sub-Saharan Africa under climate change to 2050, and explore the implications for agricultural adaptation, with particular focus on identifying priorities in crop breeding and the conservation of crop genetic resources. We find that for three of Africa's primary cereal crops – maize, millet, and sorghum – expected changes in growing season temperature are considerable and dwarf changes projected for precipitation, with the warmest recent temperatures on average cooler than almost 9 out of 10 expected observations by 2050. For the “novel” crop climates currently unrepresented in each country but likely extant there in 2050, we identify current analogs across the continent. The majority of African countries will have novel climates over at least half of their current crop area by 2050. Of these countries, 75% will have novel climates with analogs in the current climate of at least five other countries, suggesting that international movement of germplasm will be necessary for adaptation. A more troubling set of countries – largely the hotter Sahelian countries – will have climates with few analogs for any crop. Finally, we identify countries, such as Sudan, Cameroon, and Nigeria, whose current crop areas are analogs to many future climates but that are poorly represented in major genebanks – promising locations in which to focus future genetic resource conservation efforts.     

Identifying climatic analogs for Wisconsin under 21st-century climate-change scenarios

There is a deep disconnect between scientific and public concern about climate change. One reason is that global climate change is a fairly abstract concept with little perceived relevance, so a key challenge is to translate climate-change projections into locally concrete examples of potential impacts. Here we use climate analog analyses as an alternative method for identifying and communicating climate-change impacts. Our analysis uses multiple downscaled general circulation models for the state of Wisconsin, at 0.1 decimal degree resolution, and identifies contemporary locations in North America that are the most similar to the projected future climates for Wisconsin. We assess the uncertainties inherent in climate-change projections among greenhouse gas emission scenarios, time windows (mid-21st century vs. late 21st-century) and different combinations of climate variables. For all future scenarios and simulations, contemporary climatic analogs within North America were found for Wisconsin’s future climate. Closest analogs are primarily 200–500 km to the south-southwest of their Wisconsin reference location. Temperature has the largest effect on choice of climatic analog, but precipitation is the greatest source of uncertainty. Under the higher-end emission scenarios, the contemporary climatic analogs for Wisconsin’s end-21st-century climates are almost entirely outside the state. Climate-analog analyses offer a place-based means of assessing climate impacts that is complementary to the species-based approaches of species distributional models, and carries no assumptions about the characterization and conservatism of species niches. The analog method is simple and flexible, and can be readily extended to other regions and other environmental variables.     

Understanding and partitioning future climates for Australian regions from CMIP3 using ocean warming indices

The patterns of large-scale climate change over the 21st century simulated by 23 CMIP3 global climate models are analyzed to provide understanding of the range of projected temperature T and precipitation P changes for Australia published in 2007. Means of change, standardized by the global warming, within each of 11 regions are calculated for each model. Correlations between regions across the 23 models indicate that the changes are rather coherent across much of the mainland. The all-Australian average changes are also well correlated with a pattern of tropical sea surface temperatures. A Pacific-Indian Dipole index, representing this pattern, correlates strongly with Australian P. It also correlates well with variables in Southeast Asia. The global warming itself correlates well with Australian warming. These two indices of large-scale ocean warming are used to partition the 23 models into four representative future climates. For Australia overall, these can be described as much warmer and drier, much warmer, warmer and drier, and warmer. The four climates span much of the range of the earlier Australian projections over most of the continent. Further, they may be reproduced by a downscaling model forced with the SST anomalies. An assessment of the realism of the ocean pattern changes has the potential to reduce the uncertainty of projections, both for Australia and beyond.     

Potential changes in extremes and links with the Southern Annular Mode as simulated by a multi-model ensemble

We assess the likely changes in climate extremes under enhanced greenhouse gases over the southern extratropics, with emphasis in southern South America and sub-Antarctic seas, through the analysis of extreme indices measured from models participating in the IPCC 4th Assessment Report. We discuss how the anthropogenic climate change under A1B scenario influences both the patterns of mean change of extreme indices and the likelihood of occurrence of severe extreme indices. The likelihood of occurrence of a year with a large number of days with “warm” minimum temperatures is estimated to increase by a factor of 4 by the end of this century over most of the southern extratropics. By that time, the risk of “severe” precipitation intensity is projected to rise in most areas with the exception of the subtropical anticyclones, which experience particularly strong drying. Over the Southern Ocean this likelihood has increased to over 60%. Corresponding estimates of the changing likelihood for very long dry spells show a banded structure with positive ratios to the north of about 50° S and negative ratios in the sub Antarctic seas. In southern South America this risk about doubled between present and future climates. Then, we explore if the Southern Annular Mode influences the occurrence of severe extreme indices during the period 2070–2099. Its positive phase inhibits the extremely warm minimum temperatures in the Southern Ocean, with the exception of the eastern Bellingshausen Sea, and favors severe frost days to the north of the Ross Sea. Temperature indices show very little change induced by the SAM to the north of 50° S. Severe dry spells are inhibited during the positive phase along the sub Antarctic seas, while the mid-latitudes, including most of Patagonia, show the opposite behaviour. The Southern Ocean reveals a non-uniform distribution with both increases and decreases in the occurrence of heavier precipitation during positive SAM.     

Limitations of time-slice experiments for predicting regional climate change over South Asia

While time-slice simulations with atmospheric general circulation models (GCMs) have been used for many years to regionalize climate projections and/or assess their uncertainties, there is still no consensus about the method used to prescribe sea surface temperature (SST) in such experiments. In the present study, the response of the Indian summer monsoon to increasing amounts of greenhouse gases and sulfate aerosols is compared between a reference climate scenario and three sets of time-slice experiments, consisting of parallel integrations for present-day and future climates. Different monthly mean SST boundary conditions have been tested in the present-day integrations: raw climatological SST derived from the reference scenario, observed climatological SST, and observed SST with interannual variability. For future climate, the SST forcing has been obtained by superimposing climatological monthly mean SST anomalies derived from the reference scenario onto the present-day SST boundary conditions. None of these sets of time-slice experiments is able to capture accurately the response of the Indian summer monsoon simulated in the transient scenario. This finding suggests that the ocean–atmosphere coupling is a fundamental feature of the climate system. Neglecting the SST feedback and variability at the intraseasonal to interannual time scales has a significant impact on the projected monsoon response to global warming. Adding interannual variability in the prescribed SST boundary conditions does not mitigate the problem, but can on the contrary reinforce the discrepancies between the forced and coupled experiments. The monsoon response is also shown to depend on the simulated control climate, and can therefore be sensitive to the use of observed rather than model-derived SSTs to drive the present-day atmospheric simulation, as well as to any approximation in the prescribed radiative forcing. While such results do not challenge the use of time-slice experiments for assessing uncertainties and understanding mechanisms in transient scenarios, they emphasize the need for high-resolution coupled atmosphere-ocean GCMs for dynamical downscaling, or at least for high-resolution atmospheric GCMs coupled with a slab or a regional ocean model.     

Climate change impacts and adaptation in cities: a review of the literature

Many of the decisions relating to future urban development require information on climate change risks to cities This review of the academic and “grey” literature provides an overview assessment of the state of the art in the quantification and valuation of climate risks at the city-scale. We find that whilst a small number of cities, mostly in OECD countries, have derived quantitative estimates of the costs of climate change risks under alternative scenarios, this form of analysis is in its infancy. The climate risks most frequently addressed in existing studies are associated with sea-level rise, health and water resources. Other sectors such as energy, transport, and built infrastructure remain less studied. The review has also undertaken a case study to examine the progress in two cities—London and New York—which are relatively advanced in the assessment of climate risks and adaptation. The case studies show that these cities have benefited from stakeholder engagement at an early stage in their risk assessments. They have also benefited from the development of specific institutional responsibilities for co-ordinating such research from the outset. This involvement has been critical in creating momentum and obtaining resources for subsequent in-depth analysis of sectoral impacts and adaptation needs..While low cost climate down-scaling applications would be useful in future research, the greatest priority is to develop responses that can work within the high future uncertainty of future climate change, to build resilience and maintain flexibility. This can best be used within the context of established risk management practices.     

Dynamic normals of surface air temperature

Cited are the latest data on the contemporary climate changes in surface air temperature (to the year 2011 inclusive). Substantiated is the necessity of extending the concept on the normals and anomalies of surface air temperature under conditions of the changing climate. Formulated is a concept of “dynamic normals” and “dynamic anomalies” of surface air temperature taking account of current trends of climate change and interseasonal variations. It is proposed to adopt this concept both for the problems of forthcoming climate change assessments and for the long-range forecasting out of the “limit of predictability.” An adaptive regression method is proposed to compute such dynamic normals as a function of the indicator of global climate changes. Presented are the skill scores of dynamic normals as of “intermediate” forecasts (an analogue of the climate forecast under a changing climate).     

A global perspective on African climate

We describe the global climate system context in which to interpret African environmental change to support planning and implementation of policymaking action at national, regional and continental scales, and to inform the debate between proponents of mitigation v. adaptation strategies in the face of climate change. We review recent advances and current challenges in African climate research and exploit our physical understanding of variability and trends to shape our outlook on future climate change. We classify the various mechanisms that have been proposed as relevant for understanding variations in African rainfall, emphasizing a “tropospheric stabilization” mechanism that is of importance on interannual time scales as well as for the future response to warming oceans. Two patterns stand out in our analysis of twentieth century rainfall variability: a drying of the monsoon regions, related to warming of the tropical oceans, and variability related to the El Niño–Southern Oscillation. The latest generation of climate models partly captures this recent continent-wide drying trend, attributing it to the combination of anthropogenic emissions of aerosols and greenhouse gases, the relative contribution of which is difficult to quantify with the existing model archive. The same climate models fail to reach a robust agreement regarding the twenty-first century outlook for African rainfall, in a future with increasing greenhouse gases and decreasing aerosol loadings. Such uncertainty underscores current limitations in our understanding of the global climate system that it is necessary to overcome if science is to support Africa in meeting its development goals.     

A note on climate change adaptation for seaports: a challenge for global ports, a challenge for global society

With 80 % of world trade carried by sea, seaports provide crucial linkages in global supply-chains and are essential for the ability of all countries to access global markets. Seaports are likely to be affected directly and indirectly by climatic changes, with broader implications for international trade and development. Due to their coastal location, seaports are particularly vulnerable to extreme weather events associated with increasing sea levels and tropical storm activity, as illustrated by hurricane “Sandy”. In view of their strategic role as part of the globalized trading system, adapting ports in different parts of the world to the impacts of climate change is of considerable importance. Reflecting the views of a diverse group of stakeholders with expertise in climate science, engineering, economics, policy, and port management, this essay highlights the climate change challenge for ports and suggests a way forward through the adoption of some initial measures. These include both “soft” and “hard” adaptations that may be spearheaded by individual port entities, but will require collaboration and support from a broad range of public and private sector stakeholders and from society at large. In particular, the essay highlights a need to shift to more holistic planning, investment and operation.     

Assessing the robustness of projected precipitation changes over central Africa on the basis of a multitude of global and regional climate projections

It is well accepted within the scientific community that a large ensemble of different projections is required to achieve robust climate change information for a specific region. For this purpose we have compiled a state-of-the-art multi-model multi-scenario ensemble of global and regional precipitation projections. This ensemble combines several global projections from the CMIP3 and CMIP5 databases, along with some recently downscaled regional CORDEX-Africa projections. Altogether daily precipitation data from 77 different climate change projections is analysed; separated into 31 projections for a high and 46 for a low emission scenario. We find a robust indication that, independent of the underlying emission scenario, annual total precipitation amounts over the central African region are not likely to change severely in the future. However some robust changes in precipitation characteristics, like the intensification of heavy rainfall events as well as an increase in the number of dry spells during the rainy season are projected for the future. Further analysis shows that over some regions the results of the climate change assessment clearly depend on the size of the analyzed ensemble. This indicates the need of a “large-enough” ensemble of independent climate projections to allow for a reliable climate change assessment.     

A conceptual framework for multi-regional climate change assessments for international market systems with long-term investments

A conceptual framework for climate change assessments of international market systems that involve long-term investments is proposed. The framework is a hybrid of dynamic and static modeling. Dynamic modeling is used for those system components for which temporally continuous modeling is possible, while fixed time slices are used for other system components where it can be assumed that underlying assumptions are held constant within the time slices but allowed to vary between slices. An important component of the framework is the assessment of the “metauncertainty” arising from the structural uncertainties of a linked sequence of climate, production, trade and decision-making models. The impetus for proposing the framework is the paucity of industry-wide assessments for market systems with multiple production regions and long-term capital investments that are vulnerable to climate variations and change, especially climate extremes. The proposed framework is pragmatic, eschewing the ideal for the tractable. Even so, numerous implementation challenges are expected, which are illustrated using an example industry. The conceptual framework is offered as a starting point for further discussions of strategies and approaches for climate change impact, vulnerability and adaptation assessments for international market systems.     

Climate change prediction: Erring on the side of least drama?

Over the past two decades, skeptics of the reality and significance of anthropogenic climate change have frequently accused climate scientists of “alarmism”: of over-interpreting or overreacting to evidence of human impacts on the climate system. However, the available evidence suggests that scientists have in fact been conservative in their projections of the impacts of climate change. In particular, we discuss recent studies showing that at least some of the key attributes of global warming from increased atmospheric greenhouse gases have been under-predicted, particularly in IPCC assessments of the physical science, by Working Group I. We also note the less frequent manifestation of over-prediction of key characteristics of climate in such assessments. We suggest, therefore, that scientists are biased not toward alarmism but rather the reverse: toward cautious estimates, where we define caution as erring on the side of less rather than more alarming predictions. We call this tendency “erring on the side of least drama (ESLD).” We explore some cases of ESLD at work, including predictions of Arctic ozone depletion and the possible disintegration of the West Antarctic ice sheet, and suggest some possible causes of this directional bias, including adherence to the scientific norms of restraint, objectivity, skepticism, rationality, dispassion, and moderation. We conclude with suggestions for further work to identify and explore ESLD.     

Multiple adaptation types with mitigation: A framework for policy analysis

Effective climate policy will consist of mitigation and adaptation implemented simultaneously in a policy portfolio to reduce the risks of climate change. Previous studies of the tradeoffs between mitigation and adaptation have implicitly framed the problem deterministically, choosing the optimal paths for all time. Because climate change is a long-term problem with significant uncertainties and opportunities to learn and revise, critical tradeoffs between mitigation and adaptation in the near-term have not been considered. We propose a new framework for considering the portfolio of mitigation and adaptation that explicitly treats the problem as a multi-stage decision under uncertainty. In this context, there are additional benefits to near-term investments if they reduce uncertainty and lead to improved future decisions. Two particular features are fundamental to understanding the relevant tradeoffs between mitigation and adaptation: (1) strategy dynamics over time in reducing climate damages, and (2) strategy dynamics under uncertainty and potential for learning. Our framework strengthens the argument for disaggregating adaption as has been proposed by others. We present three stylized classes of adaptation investment types as a conceptual framework: short-lived “flow” spending, committed “stock” investment, and lower capacity “option” stock with the capability of future upgrading. In the context of sequential decision under uncertainty, these subtypes of adaptation have important tradeoffs among them and with mitigation. We argue that given the large policy uncertainty that we face currently, explicitly considering adaptation “option” investments is a valuable component of a near-term policy response that can balance between the flexible flow and committed stock approaches, as it allows for the delay of costly stock investments while at the same time allowing for lower-cost risk management of future damages.     

The bias of integrated assessment models that ignore climate catastrophes

Climate scientists currently predict there is a small but real possibility that climate change will lead to civilization threatening catastrophic events. Martin Weitzman has used this evidence along with his controversial “Dismal Theorem” to argue that integrated assessment models of climate change cannot be used to determine an optimal price for carbon dioxide. In this paper, I provide additional support for Weitzman’s conclusions by running numerical simulations to estimate risk premiums toward climate catastrophes. Compared to the assumptions found in most integrated assessment models, I incorporate into the model a more realistic range of uncertainty for both climate catastrophes and societal risk aversion. The resulting range of risk premiums indicates that the conclusions drawn from integrated assessment models that do not incorporate the potential for climate catastrophes are too imprecise to support any particular policy recommendation. The analysis of this paper is more straightforward and less technical than Weitzman’s, and therefore the conclusions should be accessible to a wider audience.