Text is temporary placeholder from description in the EU project “Intact”. To be replaced by more appropriate text.

Climate change refers to 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.”^[1] Referring to the climate change experienced in the last century, the Framework Convention on Climate Change (UNFCCC), in its Article 1^[2] 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”.

Description

One of the main indications of the current climate change is the continued warming of the climate system, as observed from global air and ocean temperatures increase (mainly due to the increase in anthropogenic greenhouse gas concentrations), melting of snow and ice and global sea level rise ^[3], such as also from changes in precipitation amounts, ocean salinity and wind patterns.

Changes in temperature and other parameters lead to changes in the circulation patterns, due to the interaction between the different components of the climatic system. These changes affect not only to the mean climate but also the frequency, intensity, spatial extent or duration of weather and climate extremes such as, for example, heat waves, heavy precipitation, drought and cyclones^[4].

Causes

Climate change may be due to natural internal processes or external forces, such as modulations of the solar cycles, volcanic eruptions and persistent anthropogenic changes in the composition of the atmosphere or in land use. According to this, the UNFCCC makes a distinction between climate change attributable to human activities altering the atmospheric composition and climate variability attributable to natural causes^[1].

Climate models

Climate models are described as “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” ^[1]. In this regard, Climate models are mathematical representations of atmospherical processes which are used to predict future changes in weather and climate features^[5], constituted by equations derived by physical, biological and chemical principles, solved numerically on a grid in which earth, ocean and atmosphere are divided. Furthermore, different parameterizations are used in climate models in order to take into account some processes not explicitly solved by the equations adopted.

Use of climate models

Schematic climate model

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. These representations can differ in aspects such 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. The most advanced representation model of the climatic system currently available are Coupled Atmosphere-Ocean General Circulation Models (AOGCMs) which provide a representation of the climate system that is near or at the most comprehensive end of the spectrum. Ongoing modelling and analysis within this area is directed towards the evolution of more complex models encompassing interactive chemistry and biology elements^[1].

Climate models are generally applied as a research tool in order to study and simulate the climate, and for operational purposes, including monthly and seasonal predictions, and inter-annual climate change projections.

Global and regional climate models

Regional Climate Model nesting approach

 Global Climate Models (GCMs) are generally used to simulate the response of the climate to increasing greenhouse gas concentrations. However, GCMs are constrained as they are characterized by resolution outputs (typical order of 100km) not suitable to provide information at regional scale^[7]. To overcome this spatial resolution issue, a downscaling of the information provided by the GCMs is necessary. This approach considers Limited Area/Regional Climate Models driven at the boundary of the target domain by the output results of GCMs, increasing the spatial resolution (currently 12 km approximately for Europe) and including atmospheric processes not solved at global scale^{[8] [9]}.

The use of scenarios

The assessment of the future effects of climate changes is affected by

Temperature change in Europe

• A1: A future world of very rapid economic growth, global population that peaks mid-century and declines thereafter, and rapid introduction of new and more efficient technologies. Major underlying themes are economic and cultural convergence and capacity-building, with a substantial reduction in regional differences in per capita income. The A1 scenario family develops into three groups that describe alternative directions of technological change in the energy system: fossil-intensive (A1FI), nonfossil energy sources (A1T), and a balance across all sources (A1B).

• A2: A differentiated world. The underlying theme is self-reliance and preservation of local identities. Fertility patterns across regions converge very slowly, resulting in continuously increasing population. Economic development is primarily regionally orientated, and per capita economic growth and technological change are more fragmented and slower than other storylines.

• B1: A convergent world with rapid change in economic structures toward a service and information economy, reductions in material intensity, and introduction of clean technologies. The emphasis is on global solutions to economic, social, and environmental sustainability, including improving equity, but without additional climate change policies.

• B2: A world in which the emphasis is on local solutions to economic, social, and environmental sustainability. This is a world with continuously increasing global population at a lower rate than in scenario A2, intermediate levels of economic development, and less rapid and more diverse technological change than in the A1 and B1 storylines. Although this scenario also is orientated toward environmental protection and social equity, it focuses on the local and regional levels.

• RCP2.6 (radiative forcing reaches a peak of about 3 W/m² before 2100 and then declines),
• RCP4.5 (radiative forcing is stabilized at 4.5 W/m² after 2100), *
• RCP6.0 (radiative forcing is stabilized at 6 W/m² after 2100) and
• RCP8.5 (radiative forcing reaches 8.5 W/m² by 2100 and continues to rise)

They will be used for assessment of future climate changes for the five case studies identified in the framework of INTACT project.

The figure to the right shows the temperature change projected by these RCPs in northern (NEU) and southern (SEM) Europe for the rest of this century, with each calculation yielding a prediction in which a bandwidth of uncertainty is indicated. The orange band represents the uncertainty of the A1B scenario, with the associated variability of this scenario (for the period between 2091 and 2100) depicted in the orange line. In addition, the variability of the B1 scenario (blue line) the A2 scenario (red line) for this period are also presented.