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

Author:

Vandenbussche SophieORCID,Langerock BavoORCID,Vigouroux CorinneORCID,Buschmann MatthiasORCID,Deutscher Nicholas M.ORCID,Feist Dietrich G.ORCID,García OmairaORCID,Hannigan James W.,Hase Frank,Kivi RigelORCID,Kumps Nicolas,Makarova MariaORCID,Millet Dylan B.ORCID,Morino IsamuORCID,Nagahama TomooORCID,Notholt Justus,Ohyama HirofumiORCID,Ortega IvanORCID,Petri ChristofORCID,Rettinger Markus,Schneider Matthias,Servais Christian P.,Sha Mahesh KumarORCID,Shiomi Kei,Smale Dan,Strong KimberlyORCID,Sussmann Ralf,Té YaoORCID,Velazco Voltaire A.ORCID,Vrekoussis MihalisORCID,Warneke Thorsten,Wells Kelley C.ORCID,Wunch DebraORCID,Zhou MinqiangORCID,De Mazière MartineORCID

Abstract

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.

Funder

Belgian Federal Science Policy Office

National Oceanic and Atmospheric Administration

European Space Agency

Federal Ministry for Economic Affairs and Energy

Integrated Carbon Observation System

European Union

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

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