Nitrous Oxide Profiling from Infrared Radiances (NOPIR): Algorithm Description, Application to 10 Years of IASI Observations and Quality Assessment
journal contribution
posted on 2024-11-17, 15:37authored bySophie Vandenbussche, Bavo Langerock, Corinne Vigouroux, Matthias Buschmann, Nicholas M Deutscher, Dietrich G Feist, Omaira García, James W Hannigan, Frank Hase, Rigel Kivi, Nicolas Kumps, Maria Makarova, Dylan B Millet, Isamu Morino, Tomoo Nagahama, Justus Notholt, Hirofumi Ohyama, Ivan Ortega, Christof Petri, Markus Rettinger, Matthias Schneider, Christian P Servais, Mahesh Kumar Sha, Kei Shiomi, Dan Smale, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A Velazco, Mihalis Vrekoussis
Nitrous oxide (N2 O) 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 N2 O 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 N2 O ν3 band, the Radiative Transfer for TOVS (RTTOV) tools and the Tikhonov regularization scheme. A time series of ten years (2011–2020) of IASI N2 O 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) N2 O 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.