Four years of IASI CO2 , CH4 , N2O retrievals: Validation with in situ observations from the Mauna Loa station
IASI (Infrared Atmospheric Sounder Interferometer) soundings for the years 2014 to 2017 over sea surface for the Hawaii region have been used to retrieve column amount of CO 2 , CH 4 , N 2 O. The analysis allowed us to derive CO 2 , CH 4 and N 2 O growth rates, trend and seasonality, which have been...
Published in: | Remote Sensing of Clouds and the Atmosphere XXIII |
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Online Access: | http://hdl.handle.net/11563/136514 https://doi.org/10.1117/12.2325569 |
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ftunivbasilicata:oai:iris.unibas.it:11563/136514 2024-04-14T08:05:44+00:00 Four years of IASI CO2 , CH4 , N2O retrievals: Validation with in situ observations from the Mauna Loa station Masiello, Guido Serio, Carmine Venafra, Sara Liuzzi, Giuliano Camy-Peyret, Claude Masiello, Guido Serio, Carmine Venafra, Sara Liuzzi, Giuliano Camy-Peyret, Claude 2018 http://hdl.handle.net/11563/136514 https://doi.org/10.1117/12.2325569 eng eng SPIE country:USA place:Bellingham, WA info:eu-repo/semantics/altIdentifier/isbn/9781510621558 info:eu-repo/semantics/altIdentifier/wos/WOS:000453909700011 ispartofbook:REMOTE SENSING OF CLOUDS AND THE ATMOSPHERE XXIII Remote Sensing of Clouds and the Atmosphere XXIII 2018 volume:10786 firstpage:15 serie:PROCEEDINGS OF SPIE, THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING http://hdl.handle.net/11563/136514 doi:10.1117/12.2325569 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85058410346 Atmospheric composition Greenhouse gase Hyperspectral sounder Infrared Inverse problem Random projection Remote sensing Satellite Electronic Optical and Magnetic Material Condensed Matter Physic Computer Science Applications1707 Computer Vision and Pattern Recognition Applied Mathematic Electrical and Electronic Engineering info:eu-repo/semantics/conferenceObject 2018 ftunivbasilicata https://doi.org/10.1117/12.2325569 2024-03-21T17:32:08Z IASI (Infrared Atmospheric Sounder Interferometer) soundings for the years 2014 to 2017 over sea surface for the Hawaii region have been used to retrieve column amount of CO 2 , CH 4 , N 2 O. The analysis allowed us to derive CO 2 , CH 4 and N 2 O growth rates, trend and seasonality, which have been compared to in situ observations from the Mauna Loa validation station. Day and night soundings have been used. During the day, for CO 2 and N 2 O we make specifically use of the IASI short wave band (2000 to 2250 cm -1 ), which is sensitive to sun radiation. Our forward/inverse module deals with sun radiation using a Cox-Munck model for the bidirectional reflectance distribution function. This makes it possible to exploit IASI soundings in sun-glint or close to sun-glint mode, which improves sensitivity of retrievals close to the surface. The analysis has been performed with our total IASI level 2 processor or τ 2 IP, which uses the whole IASI spectral coverage, therefore making it possible to exploit the whole information content of data. The code τ 2 IP also uses a random projection approach to reduce the dimensionality of the data space. Our analysis show that growth rate, trend and seasonality are extracted with high accuracy (we observe correlation with in situ data close or higher than 0.90). After validation, we have applied τ 2 IP to seven years of data over the Arctic sea basin and computed summer maps (July to September) of CO 2 and sea skin temperature. The results show that the increase of skin temperature parallels the increase of CO 2 column amount over the Arctic basin. Conference Object Arctic Basin Arctic Università degli Studi della Basilicata: CINECA IRIS Arctic Remote Sensing of Clouds and the Atmosphere XXIII 15 |
institution |
Open Polar |
collection |
Università degli Studi della Basilicata: CINECA IRIS |
op_collection_id |
ftunivbasilicata |
language |
English |
topic |
Atmospheric composition Greenhouse gase Hyperspectral sounder Infrared Inverse problem Random projection Remote sensing Satellite Electronic Optical and Magnetic Material Condensed Matter Physic Computer Science Applications1707 Computer Vision and Pattern Recognition Applied Mathematic Electrical and Electronic Engineering |
spellingShingle |
Atmospheric composition Greenhouse gase Hyperspectral sounder Infrared Inverse problem Random projection Remote sensing Satellite Electronic Optical and Magnetic Material Condensed Matter Physic Computer Science Applications1707 Computer Vision and Pattern Recognition Applied Mathematic Electrical and Electronic Engineering Masiello, Guido Serio, Carmine Venafra, Sara Liuzzi, Giuliano Camy-Peyret, Claude Four years of IASI CO2 , CH4 , N2O retrievals: Validation with in situ observations from the Mauna Loa station |
topic_facet |
Atmospheric composition Greenhouse gase Hyperspectral sounder Infrared Inverse problem Random projection Remote sensing Satellite Electronic Optical and Magnetic Material Condensed Matter Physic Computer Science Applications1707 Computer Vision and Pattern Recognition Applied Mathematic Electrical and Electronic Engineering |
description |
IASI (Infrared Atmospheric Sounder Interferometer) soundings for the years 2014 to 2017 over sea surface for the Hawaii region have been used to retrieve column amount of CO 2 , CH 4 , N 2 O. The analysis allowed us to derive CO 2 , CH 4 and N 2 O growth rates, trend and seasonality, which have been compared to in situ observations from the Mauna Loa validation station. Day and night soundings have been used. During the day, for CO 2 and N 2 O we make specifically use of the IASI short wave band (2000 to 2250 cm -1 ), which is sensitive to sun radiation. Our forward/inverse module deals with sun radiation using a Cox-Munck model for the bidirectional reflectance distribution function. This makes it possible to exploit IASI soundings in sun-glint or close to sun-glint mode, which improves sensitivity of retrievals close to the surface. The analysis has been performed with our total IASI level 2 processor or τ 2 IP, which uses the whole IASI spectral coverage, therefore making it possible to exploit the whole information content of data. The code τ 2 IP also uses a random projection approach to reduce the dimensionality of the data space. Our analysis show that growth rate, trend and seasonality are extracted with high accuracy (we observe correlation with in situ data close or higher than 0.90). After validation, we have applied τ 2 IP to seven years of data over the Arctic sea basin and computed summer maps (July to September) of CO 2 and sea skin temperature. The results show that the increase of skin temperature parallels the increase of CO 2 column amount over the Arctic basin. |
author2 |
Masiello, Guido Serio, Carmine Venafra, Sara Liuzzi, Giuliano Camy-Peyret, Claude |
format |
Conference Object |
author |
Masiello, Guido Serio, Carmine Venafra, Sara Liuzzi, Giuliano Camy-Peyret, Claude |
author_facet |
Masiello, Guido Serio, Carmine Venafra, Sara Liuzzi, Giuliano Camy-Peyret, Claude |
author_sort |
Masiello, Guido |
title |
Four years of IASI CO2 , CH4 , N2O retrievals: Validation with in situ observations from the Mauna Loa station |
title_short |
Four years of IASI CO2 , CH4 , N2O retrievals: Validation with in situ observations from the Mauna Loa station |
title_full |
Four years of IASI CO2 , CH4 , N2O retrievals: Validation with in situ observations from the Mauna Loa station |
title_fullStr |
Four years of IASI CO2 , CH4 , N2O retrievals: Validation with in situ observations from the Mauna Loa station |
title_full_unstemmed |
Four years of IASI CO2 , CH4 , N2O retrievals: Validation with in situ observations from the Mauna Loa station |
title_sort |
four years of iasi co2 , ch4 , n2o retrievals: validation with in situ observations from the mauna loa station |
publisher |
SPIE |
publishDate |
2018 |
url |
http://hdl.handle.net/11563/136514 https://doi.org/10.1117/12.2325569 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Basin Arctic |
genre_facet |
Arctic Basin Arctic |
op_relation |
info:eu-repo/semantics/altIdentifier/isbn/9781510621558 info:eu-repo/semantics/altIdentifier/wos/WOS:000453909700011 ispartofbook:REMOTE SENSING OF CLOUDS AND THE ATMOSPHERE XXIII Remote Sensing of Clouds and the Atmosphere XXIII 2018 volume:10786 firstpage:15 serie:PROCEEDINGS OF SPIE, THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING http://hdl.handle.net/11563/136514 doi:10.1117/12.2325569 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85058410346 |
op_doi |
https://doi.org/10.1117/12.2325569 |
container_title |
Remote Sensing of Clouds and the Atmosphere XXIII |
container_start_page |
15 |
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1796302348560105472 |