Title : 
Prediction of monthly rainfall statistics from data with long integration time
         
        
            Author : 
Luini, Lorenzo ; Capsoni, Carlo
         
        
            Author_Institution : 
Dipt. di Elettron., Inf. e Bioing., Politec. di Milano, Milan, Italy
         
        
        
        
        
        
        
        
            Abstract : 
Conversion models, originally devised to turn yearly rainfall statistics from long (e.g. 30 or 60 min) to short integration time T (i.e. 1 min), are assessed for their ability to also predict monthly 1-min integrated statistics, P(R)1m, knowledge of which may be beneficial for specific services (e.g. reconfigurable systems) and for the definition of a reliable approach to estimate monthly (hence worst month) rain attenuation statistics. Tests, performed for 5 ≤ T ≤ 60 min against monthly raingauge-derived rainfall data collected in some sites worldwide, indicate that the EXponential CELL rainfall statistics conversion (EXCELL RSC) and Lavergnat-Golé models, in force of their physical soundness, provide a good performance when used to predict 1-min integrated rainfall statistics both on yearly and on monthly bases.
         
        
            Keywords : 
rain; weather forecasting; 1-min integrated rainfall statistics; Exponential CELL rainfall statistics conversion; Lavergnat-Gole models; conversion models; integration time; monthly 1-min integrated statistics; monthly rainfall statistics; monthly raingauge-derived rainfall data; rain attenuation statistics;
         
        
        
            Journal_Title : 
Electronics Letters
         
        
        
        
        
            DOI : 
10.1049/el.2013.2088