Neural Network Algorithms for Tropospheric Ozone Retrieval from Esa-envisat Sciamachy and Nasa-aura Omi Satellite Data
نویسندگان
چکیده
The ozone in troposphere is a direct greenhouse gas [1] and its importance, both from a radiative point of view and concerning its interaction with the biosphere, is outlined in several scientific papers. Monitoring its trends, especially in highly polluted locations, is a relevant topic in recent geo-sciences research. Obtaining information about ozone in the lower atmospheric levels from space is an arduous and exciting task. Difficulties stem both from the weak sensitivity of the Earth’s radiances to tropospheric ozone variations and from the relatively high horizontal resolution needed to resolve small scale features of regional air pollution. The maximum pixel dimension for monitoring air pollution from space has been estimated to be about 15 km [2]. A global daily coverage can be required to continuously observe the air masses and check the air quality.
منابع مشابه
PhD Thesis Neural networks algorithms for the estimation of atmospheric ozone from Envisat-SCIAMACHY and Aura-OMI data
Observations of ozone from satellite platform is a key source of information to monitor and understand processes that may have a relevant impact on public health, air quality and climate. To achieve at the same time a reasonable spatial resolutions and a sufficient sensitivity, nadir UV/VIS sensor may be exploited. The topic of the PhD thesis work summarized here is the use of neural networks (...
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