EUMETSAT, the European Organization for the Exploitation of Meteorological Satellites, has planned for the next generation of geostationary meteorological satellites Meteosat Third Generation series (MTG) a payload for operational optical lightning detection, the Lightning Imager (LI). LI is intended to provide a real time and accurate lightning detection, observing the phenomena per se for the individuation, surveillance and short-term forecast of severe weather in the timeframe 2021-2040. As atmospheric lightning is strongly correlated with intense convection, LI mission is to serve furtherly as observing platform for storm related phenomena like intense precipitation, heavy hail formation, vertical wind shear and severe turbulence in cloudy air. The goal of the present study is to explore the MTG-LI data and the user challenge to exploit in the future as maximum as possible that data. First it is discussed LI design and observational technique, how science data is generated and managed, how it is affected by several noise sources on the basis of known instrument design and data level documentation, and then simulated by coding and computation, developing specific software routines, with the goal to represent realistically the LI mission behavior, without any similar european geostationary heritage. The second part of the study is dedicated in drawing an outlook plan for data processing, to maximize the impact of LI L2 data in decision making, in particular in support of aviation, by minimal delays for processing and smart data reduction approach, ensuring vital information preservation, describing also a list of possible Level 2 products for the user benefit and towards operational applications. Results exploiting real lightning data from US Geostationary Lightning Mapper (GLM) are presented, as reliable demonstration of future potentialities during the operations of LI into orbit.

Investigation on the exploitation of the data of Meteosat Third Generation Lightning Imager

BIRON, DANIELE
2019

Abstract

EUMETSAT, the European Organization for the Exploitation of Meteorological Satellites, has planned for the next generation of geostationary meteorological satellites Meteosat Third Generation series (MTG) a payload for operational optical lightning detection, the Lightning Imager (LI). LI is intended to provide a real time and accurate lightning detection, observing the phenomena per se for the individuation, surveillance and short-term forecast of severe weather in the timeframe 2021-2040. As atmospheric lightning is strongly correlated with intense convection, LI mission is to serve furtherly as observing platform for storm related phenomena like intense precipitation, heavy hail formation, vertical wind shear and severe turbulence in cloudy air. The goal of the present study is to explore the MTG-LI data and the user challenge to exploit in the future as maximum as possible that data. First it is discussed LI design and observational technique, how science data is generated and managed, how it is affected by several noise sources on the basis of known instrument design and data level documentation, and then simulated by coding and computation, developing specific software routines, with the goal to represent realistically the LI mission behavior, without any similar european geostationary heritage. The second part of the study is dedicated in drawing an outlook plan for data processing, to maximize the impact of LI L2 data in decision making, in particular in support of aviation, by minimal delays for processing and smart data reduction approach, ensuring vital information preservation, describing also a list of possible Level 2 products for the user benefit and towards operational applications. Results exploiting real lightning data from US Geostationary Lightning Mapper (GLM) are presented, as reliable demonstration of future potentialities during the operations of LI into orbit.
2019
Inglese
DEL FRATE, FABIO
Università degli Studi di Roma "Tor Vergata"
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/199504
Il codice NBN di questa tesi è URN:NBN:IT:UNIROMA2-199504