Abstract
Abstract. Dynamically induced rainfall is strongly connected with synoptic atmospheric circulation patterns at the upper levels. This study investigates the relationship between days of high precipitation volume events in the eastern Mediterranean and the associated geopotential height patterns at 500 hPa. To reduce the number of different patterns and to simplify the statistical processing, the input days were classified into clusters of synoptic cases having similar characteristics, by utilizing Kohonen Self Organizing Maps (SOM) architecture. Using this architecture, synoptic patterns were grouped into 9, 18, 27 and 36 clusters which were subsequently used in the analysis. The classification performance was tested by applying the method to extreme rainfall events in the eastern Mediterranean. The relationship of the synoptic upper air patterns (500 hPa height) and surface features (heavy rainfall events) was established, while the 36 member classification proved to be the most efficient.
Highlights
IntroductionThere is a strong relationship between large scale circulation patterns and regional surface variables such as surface pressure, dynamical rainfall, wind and temperature
The island of Cyprus lies between latitude circles 34.6◦ and 35.6◦ N and between meridians 32◦ and 34.5◦ E, surrounded by the eastern Mediterranean Sea
An advantage of the Self Organizing Maps (SOM) networks over other neural network classification techniques is that the Kohonen technique creates a network that stores information in such a way that any topological relationships within the training set are maintained, so even if the Kohonen network associates weather patterns with rainfall inaccurately, the error obtained will not be of great amplitude, since the result will be a class with similar characteristics
Summary
There is a strong relationship between large scale circulation patterns and regional surface variables such as surface pressure, dynamical rainfall, wind and temperature. Synoptic upper air charts at certain levels provide a valuable tool for the operational weather forecaster to predict qualitatively occurrences of heavy rainfall over particular areas. The height pattern at 500 hPa (the so-called level of no divergence, according to Dine’s simple two-level model of the atmosphere) is often used for this purpose. In order to take advantage of these semi-empirical methods and to simplify the statistical processing, stochastic downscaling methods are often applied to the actual weather patterns in order to generate clusters of synoptic cases with similar characteristics. Weather type classifications are simple, discrete characterizations of the current atmospheric conditions and they are commonly used in atmospheric sciences. There are several weather type classification techniques, developed for different regions and for different purposes.
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