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A numerical climate model is a computer program building on mathematical descriptions of the relevant processes of the climate system. The model progressively calculates the evolution of the state of the climate system over long periods of time (e.g. decades to centuries) in short time steps (minutes to hours).
The models are formulated considering the governing physical processes for momentum, mass, energy and water conservation etc. These are represented by a set of differential equations that are solved for their time tendencies. These tendencies are subsequently added to the state of the system thereby generating a future state. From the future state new tendencies are calculated that, in turn, are used to derive yet another new state etc.
Regional climate models have been developed as a tool to improve horizontal resolution, and thereby representation of detailed regional and local processes. The EURO-CORDEX regional climate models operate on a computational grid covering parts of the North Atlantic and Europe. To run these regional models, information from the larger scale global climate system is taken as input from a global climate model at the lateral boundaries, typically 4-8 times every day. Also, sea-surface temperatures and sea-ice conditions to be used in the regional model are most often taken from the global climate model unless regional ocean models are included in the regional climate model system. In the case of coupled models, also the regional ocean model needs to take input from the global ocean model at its boundaries. For Europe, such coupled models exist for the Baltic Sea and the North Sea in northern Europe and for the Mediterranean in the south. Such coupled models are, however, not currently part of EURO-CORDEX, however some of them are available for the Med-CORDEX domain.
Which processes are included in a climate model?
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The problem is the strongly increasing need for computing power with finer resolution. A doubling of the resolution (e.g. from 20 to 10 km) leads to an eightfold increase in computing power.
A twofold increase in the resolution of the computational grid implies that the number of gridpoints increase by a factor of four (two dimensions). Added on top of this is also the temporal resolution as the time step needs to be shorter to avoid numerical instability. Consequently, a doubling of the resolution (or halving of the grid size) implies an eightfold increase in demand for compute power. In addition, also the need for storage of results increaseincreases.
Another issue with increasing resolution is that some processes may need to be completely reformulated as they become increasingly resolved. This is the case with convection that is parameterized at coarse resolution but explicitly treated in convection-permitting models. This is a limitation for several regional climate models used in EURO-CORDEX that are not developed for being applied at grid spacing finer than around 10 km.
References
Kendon, EJ, NM Roberts, HJ Fowler, MJ Roberts, SC Chan, and CA Senior (2014) Heavier summer downpours with climate change revealed by weather forecast resolution model, Nature Climate Change, 4, 570–576, doi:10.1038/nclimate2258
Olsson J, Berg P and Kawamura A (2015) Impact of RCM Spatial Resolution on the Reproduction of Local, Subdaily Precipitation. J. Hydrometeorol., 16, 534–547, doi:10.1175/jhm-d-14-0007.1.
Prein AF, Gobiet A, Suklitsch M, Truhetz H, Awan NK, Keuler K and Georgievski G (2013) Added value of convection permitting seasonal simulations. Clim. Dyn., 41, 2655–2677, doi:10.1007/s00382-013-1744-6.
Torma Cs, Giorgi F, and Coppola E (2015) Added value of regional climate modeling over areas characterized by complex terrain—Precipitation over the Alps, J. Geophys. Res. Atmos., 120, 3957– 3972. doi: 10.1002/2014JD022781.