Glossary of terms

Glossary terms



These represent the departures of specific measurements and/or forecasts from their long-term climatological values. Anomalies describe how much a specific variable differs from its normal state.



The average difference between the values of the forecasts and the observations on the long term. While accuracy is always positive the bias could be either positive of negative depending on the situation.


(or ‘bias-adjustment’) - methods to ‘calibrate’ model simulations to ensure their statistical properties are similar to those of the corresponding observed values.



Climate in a narrow sense 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. 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

Climate change

Climate change is any change in the climate at a regional scale or in the whole earth. It is commonly used to refer to anthropogenic climate change caused by the increase of greenhouse gases concentration in the atmosphere.

Climate model

A climate model is a numerical 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. They are usually implemented as computer programs which are used to produce climate simulations at different timescales and levels of complexity.

Climate model simulations

These are numerical solutions of sets of equations that represent the most relevant processes describing the climate system. Climate models can be of very different levels of complexity but the most elaborated ones appear to be able to realistically reproduce the key meteorological and climatological phenomena.

Climate prediction

is the result of an attempt to produce (starting from a particular state of the climate system) an estimate of the actual evolution of the climate in the future, for example, at seasonal, interannual or decadal time scales. Since the future evolution of the climate system may be highly sensitive to initial conditions, such predictions are usually probabilistic in nature. See also Climate projection and Climate scenario.

Climate scenario

These are socioeconomic scenarios used by analysts to make projections of future greenhouse gas emissions and to assess future vulnerability to climate change.

Climate services

Climate services involve the production, translation, transfer, and use of climate knowledge and information fordecision making, policy and planning.

Climate system

It is the highly complex system consisting of five major components: the atmosphere, the hydrosphere, the cryosphere, the lithosphere and the biosphere and the interactions between them. This system evolves in time under the influence of its own internal dynamics and because of external forcings such as volcanic eruptions, solar variations and anthropogenic forcings such as the changing composition of the atmosphere and land-use change.

Climate variability

Climate variability refers to variations in the mean state and other statistics (such as standard deviations, the occurrence of extremes, etc.) of the climate on all spatial and temporal scales beyond that of individual weather events. Variability may be due to natural internal processes within the climate system (internal variability), or to variations in natural or anthropogenic external forcing (external variability ). See also Climate change


Can be defined as the science of climate, but is also used in the meaning of the normal state such as a base line over the normal period. Climatology is often taken as the mean value for a given month over, for example, 1961-1990.


The validity of a finding based on the type, amount, quality, and consistency of evidence (e.g., mechanistic understanding, theory, data, models, expert judgment) and on the degree of agreement. Confidence is expressed qualitatively (Mastrandrea et al., 2010).

Convective Available Potential Energy

Convective available potential energy (CAPE) is the amount of energy that would be released if a parcel of air is lifted above the level of free convection, when it becomes less dense than the surrounding air and "floats", until the equilibrium level, where it stops floating again. This buoyancy appears thanks to the latent heat released by water vapour of the parcel, which starts condensing above the lifting condensation level. CAPE is used by forecasters as a indicator of the possible formation of thunderstorms.

Convective storm

A local storm produced by cumulonimbus clouds when Convective Available Potential Energy is released. Also called thunderstorms, because they are often accompanied by lightning. They can produce hazards like heavy rain, strong winds, and even hail and tornadoes.


The term "cyclone" applies to numerous types of low pressure areas, one of which is the extra-tropical cyclone. They are also often called "lows" or "storms".



Downscaling is a method that derives local- to regional-scale (10 to 100 km) 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 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.


El Niño Southern Oscillation

The term El Niño was initially used to describe a warm-water current that periodically flows along the coast of Ecuador and Peru, disrupting the local fishery. It has since become identified with a basin-wide warming of the tropical Pacific Ocean east of the dateline. This oceanic event is associated with a fluctuation of a global-scale tropical and subtropical surface pressure pattern called the Southern Oscillation. This coupled atmosphere-ocean phenomenon, with preferred time scales of 2 to about 7 years, is collectively known as the El Niño-Southern Oscillation (ENSO). It is often measured by the surface pressure anomaly difference between Darwin and Tahiti and the sea surface temperatures in the central and eastern equatorial Pacific. This event has a great impact on the wind, sea surface temperature, and precipitation patterns in the tropical Pacific and in many other parts of the world, through global teleconnections. The cold phase of ENSO is called La Niña.

Extra-tropical cyclone

A type of cyclone which generally occurs outside the tropics and in the middle latitudes of Earth between 30° and 60° latitude. Weather forecasters and the general public often describe them simply as "depressions" or "lows". Extratropical cyclones have cold air at their core, and derive their energy from the release of potential energy when cold and warm air masses interact.


In the context of climatology, a extreme is a relatively rare event, which can be harmful, as the infrastructures may not be prepared to handle it. These events are usually defined using the 5% and 95% percentiles of the statistical distribution of a variable. For example a extreme warm day can be defined as such if its temperature raises above the 95% percentile of the daily summer temperatures over a base period of 30 years.


High resolution

In the context of global climate models, 25 km is considered as high resolution. In this kind of models, reaching this resolution range is a technical challenge, as they involve running coupled models of atmosphere, ocean, chemistry, and other components of the climate system, which is very heavy computationally. Processing the large amount of data produced is also a challenge. This is why the scope and resolution of the climate projections produced in PRIMAVERA is unprecedented.



A probabilistic estimate of the occurrence of a single event or of an outcome, for example, a climate parameter, observed trend, or projected change lying in a given range. Likelihood may be based on statistical or modeling analyses, elicitation of expert views, or other quantitativeanalyses.


North Atlantic Oscillation

The North Atlantic Oscillation consists of opposing variations of barometric pressure near Iceland and near the Azores. It therefore corresponds to fluctuations in the strength of the main westerly winds across the Atlantic into Europe, and thus to fluctuations in the embedded cyclones with their associated frontal systems.


Post-tropical cyclone

A post-tropical cyclone is an extra-tropical cyclone born after a tropical cyclone went through an extra-tropical transition. Because of their tropical origin, these cyclones have characteristics that differentiate them from regular extra-tropical cyclones, like carrying large amounts of moisture which can lead to heavy rain.


PRIMAVERA is a European H2020 project dedicated to deliver climate simulations with a a new generation of advanced and well-evaluated high-resolution global climate models.

Probability density function (pdf)

Probability density function is a function that indicates the relative chances of occurrence of different outcomes of a variable. The function integrates to unity over the domain for which it is defined and has the property that the integral over a sub-domain equals the probability that the outcome of the variable lies within that sub-domain. For example, the probability that a temperature anomaly defined in a particular way is greater than zero is obtained from its PDF by integrating the PDF over all possible temperature anomalies greater than zero. Probability density functions that describe two or more variables simultaneously are similarly defined.


A projection is a potential future evolution of a quantity or set of quantities, often computed with the aid of a climate model. Unlike predictions, projections are conditional on assumptions concerning, for example, future socioeconomic and technological developments that may or may not be realised. See also Climate prediction.



Reanalyses are estimates of historical atmospheric or hydrographic or other climate relevant quantities, created by processing past climate data using fixed state-of-the-art weather forecasting or ocean circulation models with data assimilation techniques.

Regional Climate Model

Regional Climate Models (RCMs) are climate models which run over a limited area instead of the whole globe. They are able to do this by using data from a coarser resolution global climate model as boundary and initial conditions. Such models are used in downscaling global model simulations over specific regions.


Often taken to be the product of the probability of an event and the severity of its consequences. In statistical terms, this can be expressed as Risk(Y)=Pr(X) C(Y|X), where Pr is the probability, C is the cost, X is a variable describing the magnitude of the event, and Y is a sector or region.



Long-term evolution, such as climate change and global warming. Trend analysis is used to describe trends, and can involve linear or multiple regression with time as a covariate. A trend model may be a straight line (linear) or more complex (polynomial), and the long-term rate of change can be described in terms of the time derivative from the trend model.



Means lack of precision or that the exact value for a given time is not predictable, but it does not usually imply lack of knowledge. Often, the future state of a process may not be predictable, such as a roll with dice, but the probability of finding it in a certain state may be well known (the probability of rolling a six is 1/6, and flipping tails with a coin is 1/2). In climate science, the dice may be loaded, and we may refer to uncertainties even with perfect knowledge of the odds. Uncertainties can be modelled statistically in terms of pdfs, extreme value theory and stochastic time series models.