Application Of Neural Networks To Model The Monin-Obukhov Length And The Mixed-layer Height From Ground-based Meteorological Data
Price
Free (open access)
Transaction
Volume
37
Pages
10
Published
1999
Size
810 kb
Paper DOI
10.2495/AIR991021
Copyright
WIT Press
Author(s)
A. Pelliccioni, U. Poll, P. Agnello & A. Coni
Abstract
The aim of this paper is to present the results of an application of a 3-layer Perceptron model with error back-propagation learning rule in order to reproduce the calculated time evolution of the Monin-Obukhov length, typically its inverse, and the Mixed-Layer height from ground based meteorological information. A summer data set of meteorological parameters have been measured in a meteo station using sonic anemometer, sensors of absolute and differential temperature and solar radiation. From these data the analytical values of Monin- Obukhov length and Mixed-Layer height have bee
Keywords