In human systems, the process of adjustment to actual or expected climate and its effects, in order to moderate harm or exploit beneficial opportunities. In natural systems, the process of adjustment to actual climate and its effects; human intervention may facilitate adjustment to expected climate and its effects.
Adaptation measures means action whose implementation contributes to meeting the policy's objectives. Usually addressed together with policy, they respond to the need for climate adaptation in distinct, but sometimes overlapping ways (Lim et al., 2004). While the policy refers to the principles to apply to address a specific issue or situation, the measure is something to do to implement the policy, so it implies a concrete action. Adaptation measures can be individual interventions or they consist of packages of related measures. Specific measures might include actions that promote the chosen policy direction, such as implementing a green infrastructure project or setting up a citizen information advice and early warning program. Both of these measures would contribute to the national goal of reducing vulnerability (Lim et al., 2004; Levina & Tirpak, 2006).
The ability of systems, institutions, humans and other organisms to adjust to potential damage, to take advantage of opportunities or to respond to consequences (IPCC 2014).
The deviation of a variable from its value averaged over a reference period
Resulting from or produced by human activities
In a narrow sense, climate is usually defined as the average weather, or more rigorously as the statistical description in terms of the mean and variability of relevant quantities over a period of time ranging from months to thousands or millions of years. The classical period for averaging these variables is 30 years, as defined by the World Meteorological Organization (WMO). The relevant quantities are most often surface variables such as temperature, precipitation and wind. Climate in a wider sense is the state, including a statistical description, of the climate system.
A change in the state of the climate that can be identified (e.g., by using statistical tests) by changes in the mean and/or the variability of its properties and that persists for an extended period, typically decades or longer. Climate change may be due to natural internal processes or external forcings such as modulations of the solar cycles, volcanic eruptions and persistent anthropogenic changes in the composition of the atmosphere or in land use. Note that the United Nations Framework Convention on Climate Change (UNFCCC), in its Article 1, 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’. The UNFCCC thus makes a distinction between climate change attributable to human activities altering the atmospheric composition and climate variability attributable to natural causes.
A time series constructed from climate variables that provides an aggregate summary of the state of the climate system. For example, the difference between sea level pressure in Iceland and the Azores provides a simple yet useful historical North Atlantic Oscillation (NAO) index. Because of their optimal properties, climate indices are often defined using principal components — linear combinations of climate variables at different locations that have maximum variance subject to certain normalization constraints (e.g., the Northern Annular Mode (NAM) and Southern Annular Mode (SAM) indices which are principal components of Northern Hemisphere and Southern Hemisphere gridded pressure anomalies, respectively). Definitions of observational indices for Modes of climate variability can be found in Annex VI of the AR6 WGI report
Misure del sistema climatico che includono variabili su larga scala e proxy climatici.
A qualitative or quantitative representation of the climate system based on the physical, chemical and biological properties of its components, their interactions and feedback processes and accounting for some of its known properties. The climate system can be represented by models of varying complexity; that is, for any one component or combination of components a spectrum or hierarchy of models can be identified, differing in such aspects as the number of spatial dimensions, the extent to which physical, chemical or biological processes are explicitly represented, or the level at which empirical parameterizations are involved. There is an evolution towards more complex models with interactive chemistry and biology. Climate models are applied as a research tool to study and simulate the climate and for operational purposes, including monthly, seasonal and interannual climate predictions.
Climate proofing is a term that refers to a process of mainstreaming climate change into mitigation and/or adaptation strategies and programmes. The term is often used in the development context, i.e. development is viewed through a climate change lens. EC refer the term to the development of infrastructure projects (EC, 2021b; Climate Policy Info Hub, n.a.).
The global system consists of five major components: the atmosphere, the hydrosphere, the cryosphere, the lithosphere and the biosphere and the interactions between them. The climate system changes in time under the influence of its own internal dynamics and because of external forcings such as volcanic eruptions, solar variations, orbital forcing, and anthropogenic forcings such as the changing composition of the atmosphere and land-use change.
Deviations of climate variables from a given mean state (including the occurrence of extremes, etc.) at all spatial and temporal scales beyond that of individual weather events. Variability may be intrinsic, due to fluctuations of processes internal to the climate system (internal variability), or extrinsic, due to variations in natural or anthropogenic external forcing (forced variability).
Climatic impact-drivers (CIDs) are physical climate system conditions (e.g., means, events, extremes) that affect an element of society or ecosystems. Depending on system tolerance, CIDs and their changes can be detrimental, beneficial, neutral, or a mixture of each across interacting system elements and regions (IPCC, 2022a). The IPCC AR6 identifies 33 CIDs grouped into seven main types: heat and cold, wet and dry, wind, snow and ice, coastal, open ocean and other.
A serious disruption of the functioning of a community or a society at any scale due to hazardous events interacting with conditions of exposure, vulnerability and capacity, leading to one or more of the following: human, material, economic and environmental losses and impacts’ (UNGA, 2016).
The likelihood over a specified time period of severe alterations in the normal functioning of a community or a society due to hazardous physical events interacting with vulnerable social conditions, leading to widespread adverse human, material, economic, or environmental effects that require immediate emergency response to satisfy critical human needs and that may require external support for recovery.
A method that derives local- to regional-scale information from larger-scale models or data analyses. Two main methods exist: dynamical downscaling and empirical/statistical downscaling. The dynamical method uses the output of regional climate models, global models with variable spatial resolution, or high-resolution global models. The empirical/statistical methods are based on observations and develop statistical relationships that link the large-scale atmospheric variables with local/regional climate variables. In all cases, the quality of the driving model remains an important limitation on the quality of the downscaled information. The two methods can be combined, for example, applying empirical/statistical downscaling to the output of a regional climate model, consisting of a dynamical downscaling of a global climate model.
The presence of people; livelihoods; species or ecosystems; environmental functions, services, and resources; infrastructure; or economic, social, or cultural assets in places and settings that could be adversely affected.
The occurrence of a value of a weather or climate variable above (or below) a threshold value near the upper (or lower) ends of the range of observed values of the variable. By definition, the characteristics of what is called extreme weather may vary from place to place in an absolute sense. When a pattern of extreme weather persists for some time, such as a season, it may be classified as an extreme climate event, especially if it yields an average or total that is itself extreme (e.g., high temperature, drought or heavy rainfall over a season). For simplicity, both extreme weather events and extreme climate events are referred to collectively as climate extremes.
An event that is rare at a particular place and time of year. Definitions of ‘rare’ vary, but an extreme weather event would normally be as rare as, or rarer than, the 10th or 90th percentile of a probability density function estimated from observations. By definition, the characteristics of what is called extreme weather may vary from place to place in an absolute sense.
The potential occurrence of a natural or human-induced physical event or trend that may cause loss of life, injury, or other health impacts, as well as damage and loss to property, infrastructure, livelihoods, service provision, ecosystems and environmental resources
The consequences of realised risks on natural and human systems, where risks result from the interactions of climate-related hazards (including extreme weather/climate events), exposure, and vulnerability. Impacts generally refer to effects on lives, livelihoods, health and well-being, ecosystems and species, economic, social and cultural assets, services (including ecosystem services), and infrastructure. Impacts may be referred to as consequences or outcomes, and can be adverse or beneficial.
The surface level of the ocean at a particular point averaged over an extended period of time such as a month or year. Mean sea level is often used as a national datum to which heights on land are referred.
A human intervention to reduce emissions or enhance the sinks of greenhouse gases.
A partition value in a population distribution that a given percentage of the data values are below or equal to. The 50th percentile corresponds to the median of the population. Percentiles are often used to estimate the extremes of a distribution. For example, the 90th (10th) percentile may be used to refer to the threshold for the upper (lower) extremes.
The change in the net, downward minus upward, radiative flux (expressed in W m–2) due to a change in an external driver of climate change, such as a change in the concentration of carbon dioxide (CO2), the concentration of volcanic aerosols or in the output of the Sun. The stratospherically adjusted radiative forcing is computed with all tropospheric properties held fixed at their unperturbed values, and after allowing for stratospheric temperatures, if perturbed, to readjust to radiative-dynamical equilibrium. Radiative forcing is called instantaneous if no change in stratospheric temperature is accounted for. The radiative forcing once both stratospheric and tropospheric adjustments are accounted for is termed the ‘effective radiative forcing‘.
The descriptive time period of the current climate against which potential changes in climatic characteristics of a future time horizon are to be analyzed. For its selection, at least two requirements must be considered: on one hand, its length must be sufficiently, but not excessively, extended to consider the climate homogeneous and robustly assessable within the period; on the other hand, it must be a time span within which sufficient data is available (in terms of coverage and spatial and temporal resolution) for the physical variables to be analyzed, such as precipitation and temperature.
Scenarios that include time series of emissions and concentrations of the full suite of greenhouse gases (GHGs) and aerosols and chemically active gases, as well as land use/land cover. The word representative signifies that each RCP provides only one of many possible scenarios that would lead to the specific radiative forcing characteristics. The term pathway emphasises that not only the long-term concentration levels are of interest, but also the trajectory taken over time to reach that outcome. RCPs usually refer to the portion of the concentration pathway extending up to 2100, for which integrated assessment models produced corresponding emission scenarios. Extended concentration pathways describe extensions of the RCPs from 2100 to 2300 that were calculated using simple rules generated by stakeholder consultations, and do not represent fully consistent scenarios. The following four RCPs produced from integrated assessment models were selected from the published literature and used in the Fifth IPCC Assessment, and are also used in the AR6 for comparison, spanning the range from approximately below 2°C warming to high (>4°C) warming best-estimates by the end of the 21th century (IPCC, 2021a): RCP2.6, RCP4.5, RCP6.0, RCP8.5. Integrated assessments have also revealed two important findings: 1) the two RCPs with the least amount of climate forcing (RCP2.6 and RCP4.5) are not feasible without some amount of climate mitigation effort; 2) the RCP with the most climate forcing (RCP8.5) is only possible under a narrow set of socioeconomic conditions. With the release of the SSPs, modellers have expanded the range of mitigation targets that they are considering, and three new RCPs are being developed to fill these gaps: RCP1.9, RCP3.4 and RCP7.0. RCP1.9 is a new pathway that focuses on limiting warming to below 1.5 °C, the aspirational goal of the Paris Agreement. RCP3.4, on the other hand, represents an intermediate pathway between the “very stringent” RCP2.6 and less stringent mitigation efforts associated with RCP4.5. RCP7.0 will represent the medium-to-high end of the range of future emissions and warming, and is a baseline outcome rather than a mitigation target. It may provide a compelling alternative or complement to the commonly used RCP8.5 for studies comparing mitigation and “business-as-usual” scenarios (Hausfather, 2018; GLISA, 2021).
The capacity of interconnected social, economic and ecological systems to cope with a hazardous event, trend or disturbance, responding or reorganising in ways that maintain their essential function, identity and structure. Resilience is a positive attribute when it maintains capacity for adaptation, learning and/or transformation (Arctic Council, 2016).
The potential for adverse consequences for human or ecological systems, recognising the diversity of values and objectives associated with such systems. In the context of climate change, risks can arise from potential impacts of climate change as well as human responses to climate change. Relevant adverse consequences include those on lives, livelihoods, health and well-being, economic, social and cultural assets and investments, infrastructure, services (including ecosystem services), ecosystems and species. In the context of climate change impacts, risks result from dynamic interactions between climate-related hazards with the exposure and vulnerability of the affected human or ecological system to the hazards. Hazards, exposure and vulnerability may each be subject to uncertainty in terms of magnitude and likelihood of occurrence, and each may change over time and space due to socio-economic changes and human decision-making (see also risk management, adaptation and mitigation). In the context of climate change responses, risks result from the potential for such responses not achieving the intended objective(s), or from potential trade-offs with, or negative side-effects on, other societal objectives, such as the Sustainable Development Goals (SDGs). Risks can arise, for example, from uncertainty in implementation, effectiveness or outcomes of climate policy, climate-related investments, technology development or adoption, and system transitions.
The Shared Socioeconomic Pathways (SSP) are a collection of climate scenarios, introduced for the first time in the sixth IPCC Assessment Report on climate change (AR6, IPCC 2021). Scientists have examined five different "narratives" that correspond to as many possible socioeconomic futures. The scenarios thus defined cover alternatives ranging from "very low emissions" (SSP1 – 1.9) to "very high emissions" (SSP3 – 8.5), passing through various scenarios including "low emissions" (SSP1 – 2.6), "intermediate" (SSP2 – 4.5) and "high" (SSP3 – 7.0).
A plausible description of how the future may develop based on a coherent and internally consistent set of assumptions about key driving forces (e.g., rate of technological change, prices) and relationships. Note that scenarios are neither predictions nor forecasts, but are used to provide a view of the implications of developments and actions.
Shared Socio-economic Pathways (SSPs) have been developed to complement the Representative Concentration Pathways (RCPs). SSPs describe possible socio-economic conditions, land-use changes, and other human-caused climate drivers that influence greenhouse gas emissions, thus affecting radiative forcing. Potential mitigation actions can be “applied” within these baseline socio-economic scenarios to evaluate their effectiveness in achieving various targets. The five families of SSP-based scenarios are (climatedata, n.a.): o SSP1 (Sustainability), has low challenges to both mitigation and adaptation. In this scenario, policies focus on human well-being, clean energy technologies, and the preservation of the natural environment; o SSP2 (Middle of the Road) represents moderate challenges to both mitigation and adaptation; o SSP3 (Regional Rivalry) is characterized by high challenges to both mitigation and adaptation. In this scenario, nationalism drives policy and focus is placed on regional and local issues rather than global issues; o SSP4 (Inequality) is defined by high challenges to adaptation and low challenges to mitigation; o SSP5 (Fossil-fueled Development) is characterized by high challenges to mitigation and low challenges to adaptation. By design, the RCP emission and concentration pathways were stripped of their association with a certain socio-economic development. Different levels of emissions and climate change along the dimension of the RCPs can hence be explored against the backdrop of different socio-economic development pathways (SSPs) on the other dimension in a matrix. This integrative SSP-RCP framework is now widely used in the climate impact and policy analysis literature, where climate projections obtained under the RCP scenarios are analysed against the backdrop of various SSPs. As several emissions updates were due, a new set of emissions scenarios was developed in conjunction with the SSPs. Hence, the abbreviation SSP is now used for two things: on the one hand SSP1, SSP2, …, SSP5 are used to denote the five socio-economic scenario families; on the other hand, the abbreviations SSP1-1.9, SSP1-2.6, …, SSP5-8.5 are used to denote the newly developed emissions scenarios that are the result of an SSP implementation within an integrated assessment model. Those SSP scenarios are bare of climate policy assumption, but in combination with so-called shared policy assumptions (SPAs), various approximate radiative forcing levels of 1.9, 2.6, …, or 8.5 W/m2 are reached by the end of the century, respectively (IPCC, 2021a). The nine SSP-based scenarios resulting from the combination of RCPs and SSPs are listed below (the five core SSP scenarios used most commonly in the AR6 are underlined) (Meinshausen et al., 2020; Chen et al., 2021; IPCC, 2021b): o SSP1-1.9 Holds warming to approximately 1.5°C above 1850–1900 in 2100 after slight overshoot (median) and implied net zero CO2 emissions around the middle of the century. It reflects most closely a 1.5 °C target under the Paris Agreement; o SP1-2.6, “2 ◦C scenario” of the “sustainability” SSP1 socio-economic family Stays below 2.0°C warming relative to 1850–1900 (median) with implied net zero CO2 emissions in the second half of the century. This scenario approximately corresponds to the previous RCP2.6; o SSP4-3.4 A scenario between SSP1-2.6 and SSP2-4.5 in terms of end-of-century radiative forcing. It does not stay below 2.0°C in most CMIP6 runs relative to 1850–1900; o SSP2-4.5, the “middle of the road” socio-economic family SSP2 with a nominal 4.5 W/m2 radiative forcing level by 2100 Scenario approximately in line with the upper end of aggregate NDC emissions (Nationally Determined Contribution) levels by 2030. CO2 emissions remaining around current levels until the middle of the century, then falling but not reaching net zero by 2100. The estimated warming will be between 2.1°C and 3.5°C by 2100; o SSP4-6.0 The end-of-century nominal radiative forcing level of 6.0 W/m2 can be considered a ‘no-additional-climate-policy’ reference scenario, under SSP1 and SSP4 socio-economic development narratives; o SSP3-7.0, medium-high reference scenario within the “regional rivalry” socio-economic family An intermediate-to-high reference scenario resulting from no additional climate policy under the SSP3 socio-economic development narrative. CO2 emissions roughly double from current levels by 2100. SSP3-7.0 has particularly high non-CO2 emissions, including high aerosols emissions. The estimated warming will be between 2.8°C and 4.6°C by 2100; o SSP3-7.0-lowNTCF A variation of the intermediate-to-high reference scenario SSP3-7.0 but with mitigation of CH4 and/or short-lived species such as black carbon and other short-lived climate forcers (SLCF). Note that variants of SSP3-7.0-lowNTCF differ in terms of whether CH4 emissions are reduced; o SSP5-3.4-OS (Overshoot) A mitigation-focused variant of SSP5-8.5 that initially follows unconstrained emissions growth in a fossil fuel-intensive setting until 2040 and then implements the largest net negative CO2 emissions of all SSP scenarios in the second half of 21st century to reach SSP1-2.6 forcing levels in the 22nd century. Used to consider reversibility and strong overshoot scenarios; o SSP5-8.5 marks the upper edge of the SSP scenario spectrum with a high reference scenario with no additional climate policy in a high fossil-fuel development world throughout the 21st century. CO2 emissions roughly double from current levels by 2050. The estimated warming will be between 3.3°C and 5.7°C by 2100. The IPCC Sixth report did not estimate the likelihoods of the scenarios but Hausfather and Peters (2020) described SSP5–8.5 as highly unlikely, SSP3–7.0 as unlikely, and SSP2–4.5 as likely.
A state of incomplete knowledge that can result from a lack of information or from disagreement about what is known or even knowable. It may have many types of sources, from imprecision in the data to ambiguously defined concepts or terminology, incomplete understanding of critical processes or uncertain projections of human behaviour. Uncertainty can therefore be represented by quantitative measures (e.g., a probability density function) or by qualitative statements (e.g., reflecting the judgement of a team of experts) (Moss and Schneider, 2000; IPCC, 2004; Mastrandrea et al., 2010).
The propensity or predisposition to be adversely affected. Vulnerability encompasses a variety of concepts and elements, including sensitivity or susceptibility to harm and lack of capacity to cope and adapt (IPCC, 2022a).