Turkish water foundation climate change downscaling model principles

Even though the atmosphere is modeled analytically, solutions are valid only if they are in good agreement with the necessary ground data within certain error bands. Available models provide basic information on the average behavior of the phenomenon concerned based on a set of simplifying assumptions. However, the natural phenomena temporal or spatial behavior shows unexpected deviations from the average. A set of assumptions such as the homogeneity, isotropy, uniformity, first order approximation, and alike cannot be valid at fine resolutions. In practice, simple but effective methods help to facilitate forecasting. The global circulation (climate) model (GCM) is functional mainly due to extraterrestrial solar irradiation and terrestrial free water bodies as rivers, lakes, seas, and oceans at coarse resolutions. The end products of such models are available at several centers. The main problem is to develop a local model, which renders the coarse resolution into a practically finer local resolution by taking into consideration the combined effects of GCM outputs with the available ground measurements such as radiation, temperature, precipitation, humidity, wind speed, etc. It is the main purpose of this paper to develop a local downscaling methodology based on a set of statistical temporal and spatial pattern description techniques. Among such techniques are the spatial dependence function (SDF) for spatial downscaling and the White Markov (WM) process for temporal downscaling in addition to their combination in an effective manner over Turkey as a regional downscaling model.