Neural Network Approach to Forecast Hourly Intense Rainfall Using GNSS Precipitable Water Vapor and Meteorological Sensors

Neural Network Approach to Forecast Hourly Intense Rainfall Using GNSS Precipitable Water Vapor and Meteorological Sensors

This work presents a methodology for the short-term forecast of intense rainfall based on a neural network and the integration of Global Navigation and Positioning System (GNSS) and meteorological data. Precipitable water vapor (PWV) derived from GNSS is combined with surface pressure, surface tempe...

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Bibliographic Details
Main Authors: Pedro Benevides, Joao Catalao, Giovanni Nico
Format: Article
Language:English
Published: MDPI AG 2019-04-01
Series:Remote Sensing
Subjects:
global navigation satellite system (GNSS)
precipitable water vapor (PWV)
precipitation
meteorological sensors
spinning enhanced visible and infrared imager (SEVIRI)
neural network
forecast
Online Access:https://www.mdpi.com/2072-4292/11/8/966

Internet

https://www.mdpi.com/2072-4292/11/8/966

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