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Surface parameters from SEVIRI observations through a Kalman filter approach: application and evaluation of the scheme in Southern Italy
Author(s) -
Grazia
Publication year - 2016
Publication title -
tethys journal of weather and climate of the western mediterranean
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.112
H-Index - 6
eISSN - 1697-1523
pISSN - 1139-3394
DOI - 10.3369/tethys.2016.13.01
Subject(s) - kalman filter , scheme (mathematics) , surface (topology) , environmental science , ensemble kalman filter , meteorology , extended kalman filter , computer science , moving horizon estimation , remote sensing , geology , geography , mathematics , artificial intelligence , mathematical analysis , geometry
Geostationary satellites are capable to resolve the diurnal cycle by providing time sequence of observations with a very high temporal resolution. A Kalman filter methodology was developed to exploit such time continuity in order to simultaneously retrieve surface temperature and emissivity from SEVIRI (Spinning Enhanced Visible and Infrared Imager) data. The methodology has been applied and tested over a geographic region in the Southern Italy characterized by different surface features: arid, cultivated, vegetated and urban areas, and sea water. The objective is to implement a real-time continuous monitoring of surface parameters, which could be used for the various purposes of tourism and agronomy, land surveillance, natural hazards and risk assessment analysis. Retrieval of surface parameters has been performed for the whole year 2013 and the results have been compared to other similar satellite observations such as those derived from AVHRR (Advanced Very High Resolution Radiometer) and MODIS (Moderate Reso-lution Imaging Spectroradiometer). Comparisons with ECMWF (European Centre for Medium range Weather Forecasts) analyses for sea surface are provided as well

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