Nitrous Oxide Profiling from Infrared Radiances (NOPIR): Algorithm Description, Application to 10 Years of IASI Observations and Quality Assessment - CNRS - Centre national de la recherche scientifique Accéder directement au contenu
Article Dans Une Revue Remote Sensing Année : 2022

Nitrous Oxide Profiling from Infrared Radiances (NOPIR): Algorithm Description, Application to 10 Years of IASI Observations and Quality Assessment

Sophie Vandenbussche
Bavo Langerock
Corinne Vigouroux
  • Fonction : Auteur
Matthias Buschmann
Nicholas Deutscher
Dietrich Feist
Omaira García
James Hannigan
  • Fonction : Auteur
Frank Hase
  • Fonction : Auteur
Rigel Kivi
Nicolas Kumps
  • Fonction : Auteur
Maria Makarova
Dylan Millet
Isamu Morino
Tomoo Nagahama
Justus Notholt
  • Fonction : Auteur
Hirofumi Ohyama
Ivan Ortega
Christof Petri
Markus Rettinger
  • Fonction : Auteur
Matthias Schneider
  • Fonction : Auteur
Christian Servais
  • Fonction : Auteur
Mahesh Kumar Sha
Kei Shiomi
Dan Smale
  • Fonction : Auteur
Kimberly Strong
Ralf Sussmann
  • Fonction : Auteur
Voltaire Velazco
Mihalis Vrekoussis
Thorsten Warneke
  • Fonction : Auteur
Kelley Wells
Debra Wunch
Minqiang Zhou
Martine de Mazière

Résumé

Nitrous oxide (N2O) is the third most abundant anthropogenous greenhouse gas (after carbon dioxide and methane), with a long atmospheric lifetime and a continuously increasing concentration due to human activities, making it an important gas to monitor. In this work, we present a new method to retrieve N2O concentration profiles (with up to two degrees of freedom) from each cloud-free satellite observation by the Infrared Atmospheric Sounding Interferometer (IASI), using spectral micro-windows in the N2O ν3 band, the Radiative Transfer for TOVS (RTTOV) tools and the Tikhonov regularization scheme. A time series of ten years (2011–2020) of IASI N2O profiles and integrated partial columns has been produced and validated with collocated ground-based Network for the Detection of Atmospheric Composition Change (NDACC) and Total Carbon Column Observing Network (TCCON) data. The importance of consistency in the ancillary data used for the retrieval for generating consistent time series has been demonstrated. The Nitrous Oxide Profiling from Infrared Radiances (NOPIR) N2O partial columns are of very good quality, with a positive bias of 1.8 to 4% with respect to the ground-based data, which is less than the sum of uncertainties of the compared values. At high latitudes, the comparisons are a bit worse, due to either a known bias in the ground-based data, or to a higher uncertainty in both ground-based and satellite retrievals.
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Dates et versions

hal-03958606 , version 1 (27-01-2023)

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Paternité

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Sophie Vandenbussche, Bavo Langerock, Corinne Vigouroux, Matthias Buschmann, Nicholas Deutscher, et al.. Nitrous Oxide Profiling from Infrared Radiances (NOPIR): Algorithm Description, Application to 10 Years of IASI Observations and Quality Assessment. Remote Sensing, 2022, 14 (8), pp.1810. ⟨10.3390/rs14081810⟩. ⟨hal-03958606⟩
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