Open AccessPrediction of monthly rainfall statistics from data with long integration time
Author(s) -
Luini L.,
Capsoni C.
Publication year - 2013
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2013.2088
Subject(s) - statistics , soundness , rain gauge , meteorology , environmental science , mathematics , climatology , computer science , geography , precipitation , geology , programming language
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 ) 1 m , 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.