It is generally accepted that the only scientifically sound way to understand the behaviour and future evolution of the climate is its numerical modelling. Recent global climate models (GCMs) are capable of describing the physical processes of each component of the climate system (atmosphere, hydrosphere, cryosphere, lithosphere, and biosphere; Fig. 1) and properly characterizing the complicated, non-linear interactions and feedbacks between them. Since these global models represent the Earth in its entire complexity, therefore, they are able to provide global response of the climate system for a hypothetical forcing.
Figure 1: The global climate system and its key interactions
One of the most uncertain elements of the future climate is the human activity. The anthropogenic factors influencing the climate system are quantified for the global climate models in the following way: the radiation constraints of the socio-economic aspects (population, energy consumption, industrial and agricultural structural changes, etc.) are determined (i.e., how much is their impact to the Earth's radiation balance), afterwards their carbon dioxide emission and concentration equivalents are computed (Fig. 2). The uncertainty is coming from the estimation of the future change of the anthropogenic activity. Consequently, in order to assess these uncertainties several scenarios are constructed for future emission tendencies, which include optimistic, pessimistic and realistic versions, as well. The global climate projections are carried out taking into account these scenarios for the entire globe. (In climate terms the expression of forecast is not used for this kind of model simulations, but they are called projections reflecting their hypothetical nature.)
Figure 2: Emission (left) and concentration (right) values (calculated in carbon dioxide
equivalent) of the most important global scenarios for the 21stcentury.
Nowadays, state-of-the-art global climate models are able to realistically simulate the behaviour of the climate system components together with the inter-relations between them, furthermore, they provide a basis for the description of the planetary (global, large-scale) features of the climate change. Contrary to weather prediction models, it is not expected from these projections to reflect weather events in every location and time: the main objective is to represent the mean spatial and temporal characteristics of the global system. Nevertheless, their sparse spatial resolution (mostly around 100 km) and their limited ability to describe the surface characteristics do not allow getting detailed projections about regional aspects of global changes. Therefore, regionalization (downscaling) techniques are indispensable to obtain sufficient and reliable information about regional characteristics, furthermore, these methods allow to amend the large-scale global information with the desired fine-scale details over the area of interest (e.g., over Central Europe in our case).
For such interpretation of the global simulations, regional climate models (RCMs) are applied in Hungary. These models (similarly to the short-range limited area weather predictions) dynamically downscale the global results for a smaller region using them as lateral boundary conditions (Fig. 3). Mostly, RCMs describe exclusively the atmospheric part of the climate system, consequently, they are usually adapted versions of already existing short-range numerical models. Such adaptation can be realized with modification of the physical parameterization schemes (e.g., radiation and cloud formation) being relevant at the involved temporal and spatial scales.
Figure 3: The regional climate change as a response for a global climate forcing