In this paper we show the applicability of Genetic Algorithms with Chauvenet's criterion to the reconstruction of vertical temperature profiles from RASS (Radio Acoustic Sounding System). RASS is usually an option added to Wind Profiler to provide profiles of virtual temperature data. Recovered data must be processed in a given period and are accepted if only they belong to a consensus window, whose amplitude is in general 3 m/s and only for those data it is suitable to make an average. An other problem is the unchanging of data with the increasing of height. Genetic Algorithms and Chauvenet's criterion solve automatically these difficulties.
Genetic Algorithm Application for Rass-Wind Profiler Data Processing in Remote Sensing
LAY EKUAKILLE, Aime;
2000-01-01
Abstract
In this paper we show the applicability of Genetic Algorithms with Chauvenet's criterion to the reconstruction of vertical temperature profiles from RASS (Radio Acoustic Sounding System). RASS is usually an option added to Wind Profiler to provide profiles of virtual temperature data. Recovered data must be processed in a given period and are accepted if only they belong to a consensus window, whose amplitude is in general 3 m/s and only for those data it is suitable to make an average. An other problem is the unchanging of data with the increasing of height. Genetic Algorithms and Chauvenet's criterion solve automatically these difficulties.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
