Recognition Of Meteorological Situations With Neural Networks

Abstract

This paper deals with the estimation of the amount of clouds and number of cloud layers above airports. A neural network model has been developed based on heterogeneous measurements from original instruments, to give a global estimate of cloudiness. A heuristic procedure is then suggested to find the number and heights of the cloud layers, and to divide the cloudiness into its components estimated layer by layer. 1 AMETIS II PROJECT The Ametis II project is a large project of the Swiss Meteorological Institute, which aims at automatizing weather messages sent to airplanes at the Swiss airports. Aeronautical meteorological observations are performed every thirty minutes, by human observers. These observations are encoded in METAR messages, broadcasted to the International Aeronautical Telecommunication Network. These METAR messages encode all the necessary information that airplanes have to know when they are in the vicinity of the airport. Here is an example of such a METAR: LSZH 064..