compiled by Tavhata Boyer
revised 23 August 2014


Adaptation or climate change adaptation is the adjustment of natural and human systems in response to actual or expected climate change impacts. Adaptation measures aim to moderate harm from climate change impacts. Examples of adaptation measures include: construction of barriers against sea level increases, water-use efficiency programs, and improving access to food for vulnerable communities. Adaptation has been subdivided into different categories, including anticipatory and reactive adaptation, private and public adaptation, and autonomous and planned adaptation (IPCC, 2001).


Anthropogenic means from human origin or produced by human beings. In the climate change literature the term anthropogenic appears in reference to changes in the environment due to the activities of human beings. These changes may have positive or negative impacts on the environment (Bortman, 2011, “Anthropogenic”; IPCC, 2001).

Bayesian Analysis

Approach to statistical analysis of unknown or uncertain quantity(ies). A Bayesian analysis is carried out in two steps. First, the researcher formulates a prior probability distribution for the uncertain quantity(ies) on the basis of existing knowledge. In the second step, the researcher updates the prior probability distribution using additional data and Thomas Bayes’ theorem. The updated probability distribution is known as posterior probability distribution (Grafton, 2012, p. 29).


Carbon can refer to either carbon dioxide (CO2) or black carbon.

Carbon dioxide (CO2) is a naturally occurring gas and by-product of burning fossil fuels, burning biomass, land use changes, and industrial processes. Anthropogenic CO2 serves as the reference gas against which other greenhouse gas changes are measured.

Black carbon refers to aerosol particles that contribute to the2 warming of the atmosphere by intercepting sunlight and absorbing it. These particles result from the incomplete combustion of fossil fuels, wood, and biomass. Soot, charcoal, and light absorbing refractory matter are examples of black carbon (IPCC, 2001; UNEP, 2011).

Carbon capture and storage (CCS)

Carbon capture and storage (CCS) is a form of mitigation that involves removing CO2 from the exhaust from burning fossil fuels, such as from smokestacks of coal-burning power plants, before it is emitted to the atmosphere. The CO2 is then stored in reservoirs underground or under the ocean.

Carbon Dioxide Reduction/Removal (CDR)

Set of techniques that aim to directly remove CO2 from the atmosphere. CDR techniques include increasing natural sinks for carbon and using chemical engineering to reduce atmospheric CO2 concentration. CDR methods can involve the ocean and land systems, for instance, through iron fertilization and large-scale afforestation. CDR methods fall under the category of geoengineering, and, in some cases, climate change mitigation (Morgan, 2011).

Carbon dioxide reduction (CDR) is a class of geoengineering that seeks to take CO2 out of the atmosphere to reduce the greenhouse effect. Suggested CDR techniques include reforestation, direct absorption of CO2 by chemical means, enhances surface weathering, and ocean fertilization. CDR is distinct from CCS.

Categories of uncertainty

A general classification of sources of uncertainty includes epistemic uncertainty and aleatoric uncertainty. A second classification focusing on numerical and statistical modeling considers parametric uncertainty and structural uncertainty. Both parametric uncertainty and structural uncertainty can be mapped onto epistemic and aleatoric uncertainty.

Epistemic uncertainty or systemic uncertainty refers to uncertainty caused by the epistemic state of the decision maker. It covers issues related to lack of knowledge, imprecise information, scarce information, and expert judgement (Clavreul, 2013, pp 1393-403).

Aleatoric uncertainty or statistical uncertainty refers to the notion of randomness, that is, the variability in the outcome of an experiment which is due to inherently random effects (Senge, 2014, pp. 16-29).

Parametric uncertainty refers to discrepancies between the values of actual physical systems and the input parameters used for the analysis (Castro-Triguero, 2013, pp. 268-287).

Structural uncertainty, model inadequacy, model bias, or model discrepancy is caused by complexity. Complexity refers to the number of degrees of freedom in a system and how the parameters that express the degrees of freedom interact (Rowe, 1994, pp. 743-50).


The statistical description of the weather over a period of time.  The World Meteorological Organization defines a classical climate period as thirty years. Weather includes temperature, precipitation, wind, sunshine hours, and extreme events. Climate is often defined as the “average weather,” but also includes weather variability (IPCC 2001).

Climate Change

The IPCC defines climate change as “a change of climate which is attributed directly or indirectly to human activity that alters the composition of the global atmosphere and which is in addition to natural climate variability observed over comparable time periods.” (IPCC, 2001) But this definition is too restrictive.  Climate change just means changes of climate, no matter what the cause.  Some say that the shift by scientists from using “global warming” to using “climate change” implies that they no longer accept global warming, but this could not be further from the truth. “Global warming” means that the global average temperature is going up, and this has certainly been true for the past 120 years.  But along with that temperature change, many other aspects of the climate system are also changing, such as stronger storms, more flooding, more drought, Arctic sea ice melt, melting ice sheets and sea level rise. These are all part of the climate change associated with global warming.  The climate has changed for the entire history of Earth due to natural causes, including the changing orbit of Earth around the Sun, changes of the amount of energy we receive from the Sun, and episodic volcanic eruptions.

Climate Engineering

Climate engineering is synonymous with geoengineering.  The term climate engineering is preferred by European researchers, as it more precisely defines this area of research, but the use of geoengineering will certainly continue for some time.

Climate Model

A climate model is a numerical representation of the climate system, expressed as a computer program, which serves as a research tool to study the climate and project future climate conditions. Climate models vary in complexity and consider some or all of the known physical, chemical, and biological properties of the components of the climate system and their interactions and feedback processes. The most complex climate models are coupled atmosphere-ocean general circulation models (GCMs) (IPCC, 2001).

Coupled Ethical-Epistemic Analysis

Coupled ethical-epistemic analysis poses interrelated questions at the interface between epistemology (how can knowledge be acquired?) and ethics (how should one act?). For example, this type of analysis indicates that studies to characterize uncertainty and improve knowledge in the Earth sciences have implicit value judgments (e.g., regarding the appropriate level of approximation in models). Similarly, studies that identify economically efficient strategies in climate risk management typically adopt a single ethical framework. SCRiM researchers use coupled ethical-epistemic analysis to study how the conclusions of natural and social science studies in the area of climate risk management change when value judgments are identified and included as an element of the research questions (SCRiM Annual Report, 2013; SCRiM Project White Papers, 2013).

Decision support

In general, decision support conveys making scientific knowledge useful for decision-making. Climate-related decision support refers to “organized efforts to produce, disseminate, and facilitate the use of data and information in order to improve the quality and efficacy of climate-related decisions.” Over time, climate-related decision support influences humans’ awareness and responses to risk.

Decision support systems are “knowledge-action systems or networks” formed by individuals, organizations, communication networks, and institutional structures that provide decision support (National Research Council, 2009, pp. 22, 34, 36).

Deep uncertainty

Deep uncertainty is a condition where the relevant range of system models and the associated probability density functions for their parameterizations are unknown and/or when decision-makers strongly disagree on their formulations. Under deep uncertainty the standard tools of decision analysis are difficult to apply and may not accurately represent the goals of decision-makers (Lempert, 2007, pp. 1009-26; Lempert, 2002, pp. 7309-13; Keller, 2008, pp. 5-10).

Discount rate

A rate that is used to convert future costs or benefits to their present value, based on assumptions about how to discount or reduce the value of each in the future (Park, 2013, “discount rate”).  

Distributive justice

Distributive justice is concerned with how harms and benefits ought to be shared among persons. A state of affairs is distributively just if and only if harms and benefits are shared as they ought to be among persons. However, theorists differ as to how harms and benefits ought to be shared. According to egalitarian theorists, harms and benefits ought to be shared equally, but these theorists themselves disagree on what exactly counts as equality of harms and benefits. Theorists with a desert-based approach of distributive justice hold that harms and benefits ought to be shared among persons according to the degree persons deserve those harms and benefits (Svoboda, 2011, pp. 157-180).


Downscaling or climate downscaling refers to reducing the level of detail of a climate model from a global (typically 100 km) to regional level (typically 1 to 10 km) to project future climate conditions in small-scale areas. Two main methods for climate downscaling exist: dynamical downscaling and empirical/statistical downscaling. Dynamical methods use data from coarse-resolution global climate models to derive regional high-resolution climate models. Empirical/statistical methods develop statistical relationships that link the large-scale atmospheric variables with local/regional climate variables (IPCC, 2013; IPCC, 2001).


From the Greek epistēmē, meaning knowledge. Epistemology (from the Greek epistēmē, meaning knowledge and logos, discourse, reason, body of knowledge) is a branch of philosophy concerned with the nature, kinds, conditions, scope, and mutual relations of belief, doubt, truth, and knowledge. Epistemic means of or relating to knowledge (Iannone, 2001, p. 176).


Relating to morals, mores, moral inquiry, and the process of doing moral inquiry (Iannone, 2001, p. 176).

Expected utility

Function of both an agent’s estimation of the utility of the various possible outcomes of an action and the probability of those outcomes occurring. The expected value of an action is calculated by multiplying the utility of each outcome by its probability of occurring and then summing those numbers. Mathematically, the expected utility of outcome is expressed as EU(x) = ΣiP(oi)U(oi), where x represents an action, P(o) is the probability of an outcome, and U(o) to the utility of an outcome (Grafton, 2012, p. 360).


Deliberate large-scale manipulation of the planetary environment to counteract anthropogenic climate change (Shepherd, 2009). Most scholars use the term geoengineering to describe different activities, methods, and technologies within the scope of carbon dioxide removal (CDR) and solar radiation management (SRM).

Greenhouse Effect

The greenhouse effect is the additional heating of Earth caused by energy trapped by greenhouse gases. Greenhouse gases in Earth’s atmosphere allow sunlight to penetrate to the surface, but also emit infrared radiation downward, providing additional heating that would not be there if there were no atmosphere. The term greenhouse effect comes from the analog with greenhouses used to grow plants, but actual greenhouses heat mainly by trapping hot air at the ground, preventing convection, which would cool the ground.

Greenhouse gases (GHG)

Gaseous constituents of the atmosphere, both natural and anthropogenic, that absorb and emit radiation at specific wavelengths within the spectrum of terrestrial radiation emitted by Earth’s surface, the atmosphere itself, and by clouds. Water vapor (H2O), carbon dioxide (CO2), nitrous oxide (NO), methane (CH4) and ozone (O3) are the primary greenhouse gases in Earth’s atmosphere. Artificial human-made greenhouse gases in the atmosphere include halocarbons, sulfur hexafluoride (SF6), hydrofluorocarbons (HFCs) and perfluorocarbons (PFCs) (IPCC, 2013).

Integrated Assessment Model (IAM)

Method of analysis to better understand and assess uncertainties and risks, inform policy and decision-making regarding responses to climate change, and comprehend complex system interactions, such as linkages between socioeconomic and biophysical processes. Assessment consists of social processes that bridge the domains of knowledge and decision-making, assembling and synthesizing expert scientific or technical knowledge to advise policy or decision-making. Assessment is integrated according to the breadth of the expert knowledge it synthesizes in advising the issue at hand. Integrated modeling is a representational approach seeking to advance understanding by constructing a formal representation of the issue to be studied (Parson, 1997, pp. 590-591; Tuana, 2010, pp. 483-484; Schienke, 2011, pp. 503-23; IPCC, 2001).

Intergenerational justice

Intergenerational justice is concerned with relations between persons who are not contemporaries. In particular, intergenerational justice studies how harms and benefits ought to be shared across generations. Intergenerational justice is a kind of distributive justice (Svoboda, 2011, pp. 157-180).


In the climate change literature, learning refers to the acquisition of new information that leads to changes in assessments ofuncertainty (O’Neill, 2006, pp. 1-6).

##Longwave geoengineering Longwave geoengineering is the modification of the climate system via alteration of Earth’s longwave (infrared) radiation balance. It includes CDR and suggestions of means to dissipate cirrus clouds, allowing more longwave radiation to escape fromEarth (Matthews, 2010, pp. 135-44).


A mixture or fusion of disparate elements.

Maximin criterion

John Rawls (1921-2002) proposed the maximin principle as theory of distributive justice. Accordingly, society’s objective should be the maximization of the utility of the worst-off person in society. The maximin or Rawlsian social welfare function is represented by W=mIN{Uh} (Black, 2012, “maximin”; Blackburn, 2008, “maximin principle”).

In decision theory and game theory, maximin is the strategy that maximizes the minimum possible gain of an agent (Colman,2015, “maximin”).

Mental model

A person’s internal representations of external reality that allow them to interact with the world. The cognitive structure that forms the basis of reasoning, decision making and in part, behavior. Mental models are constructed by individuals based on their personal life experiences, perceptions, and understanding of the world. They provide the mechanism through which new information is filtered and stored. Mental models are commonly displayed as influence diagrams with arrows or “influences” connecting related “nodes” that may represent uncertain circumstances or states of the world and choices made by the decision maker (Morgan, 2002; Craik, 1943; Collins, 1987, p. 243).


Mitigation or climate change mitigation refers to anthropogenic interventions to reduce emissions of greenhouse gases and particles that cause global warming. Mitigation measures include switching energy sources from those that burn fossil fuels to those that do not, such as solar, wind, and nuclear power, changes in land use, reducing energy consumption by increased efficiency and conservation, and CCS. Policy instruments for climate change mitigation include emissions trading schemes, carbon taxes, and investment in research and development (IPCC, 2001).


The term model can refer to a way of thinking (mental model), a statistical representation of observations (statistical model) or a numerical representation of the climate system (climate model).

Monte Carlo Simulation

Computerized mathematical technique used in testing models and hypotheses. Monte Carlo simulations rely on multiple runs of randomly generated parameter values to account for natural variability or poorly known quantities in quantitative analysis and decision-making. Hence, this technique is also known as a probability simulation (Grafton, 2012, p. 226).

Panel data

Panel data, longitudinal data, or cross-sectional time-series data ** refer to a data set with several units of analysis observed for more than one time period (Grafton, 2012, p. 256).

Pareto improvement

Pareto improvement is a “change in the state of the world in which the expected utility of every individual in the new state is at least equal to the status quo level of utility, and strictly greater for at least one individual” (Grafton, 2012, p. 256).


After in position, sequence, or time; behind; following (Cammac, 2006, “posterior”).

Precautionary principle

The precautionary principle refers to the sustainable use of the environment and natural resources to address credible yet uncertain climate-change related hazards. In general, the precautionary principle states that decision-makers should take actions to avoid known risks and reduce exposure to potential hazards, even if there is lack of full scientific certainty over such hazards and their causes. Accordingly, the precautionary principle promotes actions and policies based on early warning rather than incontrovertible proof or precise quantification of potential impacts (Lempert, 2007, 1009-26).


The likelihood of an event occurring. The probability of an event is mathematically represented as P(x), where x is the event. If the event will occur with perfect certainty then P(x)=1, if the event will never occur P(x)=0 (Grafton, 2012, p. 275).

Procedural Justice

Procedural justice is concerned with how decisions ought to be made from an ethical perspective. A decision is procedurally just if and only if it is reached in the manner it ought to be reached. It is a widespread assumption that procedural justice requires that all those to be affected by a decision have the opportunity to guide that decision in some way (Svoboda, 2011, pp. 157-180).


John Rawls (1921-2002) was a philosopher in the liberal tradition. Rawls is best know for A Theory of Justice (1971). Rawls argued that “each person possess an inviolability founded in justice that even the welfare of society as a whole cannot override.” Rawl’s ideas challenge utilitarianism, which claims that the good of society can override the claims of justice by the individual. Rawls introduced two thought experiments, the “original position” and the “veil of ignorance”, to explain individuals’ inviolable rights. People in the “original position” of equality ignore all knowledge that might lead them to decide on the basis of self-interest. Accordingly, they situate behind the “veil of ignorance.” The “original position” and “veil of ignorance” are relevant to explain the basic principles of justice and fairness that free and rational individuals would agree upon if they had to enter a social contract. People in the original position would agree on two principles of justice: 1) each person is to have an equal right to the most extensive scheme of equal basic liberties compatible with a similar scheme of liberties for others. 2) Social and economic inequalities are to be arranged so that they are both (a) reasonably expected to be to everyone’s advantage, and (b) attached to positions and offices open to all. The first principle has priority over the second, and both principles are to govern basic political, economic, and social structures that determine people’s chances in life (Svoboda, 2011, pp. 157-180; Putnam, 2005, p. 113; Gale Publishing, 2004, “John Rawls”; Darity, 2008, pp. 84-85; Nagel, 2005, “Rawls, John”; Wenar, 2013, “John Rawls”).


Risk refers to adverse consequences under uncertainty. Risk can be quantified by identifying adverse consequences / events and assigning them a probability of occurrence. Risk analyses use many kinds of theories and styles of scientific reasoning to define risk as it is (Novogradec, 2008, pp. 865-868; Kadvany, 1996, pp. 1-27).

Robust Decision Making (RDM)

Method to support decision making under conditions of deep uncertainty. It engages stakeholders and decision-makers to identify, evaluate, and choose robust strategies (i.e., that perform well over a wide range of possible futures and can manage surprise), characterize the vulnerabilities of such strategies, and evaluate the tradeoffs among them. Accordingly, RDM identifies strategies that perform well across a wide range of plausible impacts and a wide range of plausible probability density functions (Tuana, 2013; Keller, 2008, pp. 5-10; Lempert, 2002, pp. 7309-13).


The “characterization of uncertainty with a multiplicity of plausible futures and a satisfying criterion for desirable strategies.” Robustness is both a property of decision-makers’ uncertainty and the richness of options available to the decision maker (Lempert, 2007).

Scenario discovery

Scenarios communicate and characterize uncertainty in many decision support applications. Scenario discovery is a technique for developing scenarios for problems that involve a large number of actors with diverging world views and values and where there are many uncertain factors. In scenario discovery, an ensemble of model runs is created that encompasses the various uncertainties perceived by the actors involved in particular decision making situations. The ensemble is subsequently screened to identify runs of interest and their conditions for occurring (Kwakkel, 2013, pp. 789-800).

Sea level

Sea level is a term for measurement of the level of the Earth’s oceans. The mean sea level (MSL) ** is the average sea level recorded across a period of time. The sea level experiences variation across space and time (Grafton, 2012, pp. 219 & 305).

Sea level rise

Sea level rise refers to an increase in the mean level of the ocean. Sea level rise is subdivided into eustatic sea level rise and relative sea level rise. Eustatic sea level rise is a change in global average sea level brought about by an alteration to the volume of the world ocean. The main causes of eustatic sea level rise are warming of the ocean, which causes it to expand, and melting of land-based ice sheets and glaciers, producing runoff that increase the ocean’s volume. Relative sea level rise is a net increase in the level of the ocean relative to local land movements (IPCC, 2001).


Sensitivity or climate sensitivity is a measure of how much Earth’s climate will to react to increases or decreases in radiation and reach a new equilibrium state (Park, 2013, “climate sensitivity” & “sensitivity”).

Social Welfare Function

The social welfare function is a mapping of the level of social welfare as a function of individual levels of welfare. It ranks social situations in a continuum of best to worst. Social welfare functions vary in relation to their aversion to inequalities between individual levels of welfare and the information about individual indices that they use. The utilitarian function and maximin function are examples of social welfare functions. The utilitarian function defines social welfare in relation to the sum of individual indices of welfare. The maximin function defines social welfare with the welfare of the worst-off individuals in society. Accordingly, the utilitarian function is indifferent to individual inequalities and considers a social situation as better than another in relation to the aggregate gains and losses of individuals. Contrastingly, the maximin function is finitely adverse to individual inequality and defines a social situation as better if the level of welfare of the worst-off individuals is greater. Current social welfare functions incorporate concepts of fairness and compare social situations across different populations. These social welfare functions have been influenced by theories of justice, particularly the ideas of John Rawls. Hence, they include interpretations of individual responsibility and measure individual situations in terms of opportunities or resources (Darity, 2008, “Social Welfare Functions”).

Solar Radiation Management (SRM)

Activities that aim to reflect a higher fraction of incoming solar radiation back into space before it is absorbed by Earth’s surface. In technical terms this is called increasing Earth’s albedo (Morgan, 2011) Suggested SRM techniques include space-based reflectors, a permanent stratospheric aerosol layer in the stratosphere, brightening marine stratocumulus clouds, and increasing the reflectivity of the ocean or land.


Person or entity holding any type of value that would be affected by a particular action or policy (IPCC, 2011).


The reconciliation of economic, environmental and social interests to meet the needs of the present without compromising the ability of future generations to meet their own needs. Sustainable development is a process of change in which the utilization of resources, the direction of investments, the orientation of technological development, and institutional change are made consistent with future as well as present needs (WCED, 1987).


Uncertainty expresses the degree to which a value is unknown. The sources of uncertainty are multiple, for example, lack of knowledge of basic scientific relationships, linguistic imprecision, statistical variation, measurement error, variability, approximation, and scientific disagreement on what is known or knowable. Uncertainty can be represented by quantitative measures, expressed in terms of probabilities, or by qualitative statements (IPCC, 2001).


A measure of the total well-being, satisfaction or value resulting from an outcome or course of action. In economics, utility is used as a synonym for individual welfare, as a measure of an individual’s happiness, and as an economist’s summary of what guides individual choice. An individual can be broadly interpreted to include organizations, institutions, countries, or any type of agent. A utility function can either be an individual’s utility or an economist’s representation of an individual’s preferences. Utility functions allow mathematical analysis of individuals’ preferences. A rational individual will act to maximize their own utility function (Black, 2009, “utility”; Clapham, 2009, “utility”).


The degree to which a system is susceptible to, or unable to cope with, adverse impacts of climate change. Vulnerability is a function of the character, magnitude, rate of exposure to climate variation, sensitivity, and adaptive capacity of a system (IPCC, 2001).