An examination of the long-term CO records from MOPITT and IASI: comparison of retrieval methodology

Abstract

Abstract. Carbon monoxide (CO) is a key atmospheric compound that can be remotely sensed by satellite on the global scale. Fifteen years of continuous observations are now available from the MOPITT/Terra mission (2000 to present). Another 15 and more years of observations will be provided by the IASI/MetOp instrument series (2007-2023 >). In order to study long-term variability and trends, a homogeneous record is required, which is not straightforward as the retrieved quantities are instrument and processing dependent. The present study aims at evaluating the consistency between the CO products derived from the MOPITT and IASI missions, both for total columns and vertical profiles, during a 6-year overlap period (2008)(2009)(2010)(2011)(2012)(2013). The analysis is performed by first comparing the available 2013 versions of the retrieval algorithms (v5T for MOPITT and v20100815 for IASI), and second using a dedicated reprocessing of MO-PITT CO profiles and columns using the same a priori information as the IASI product. MOPITT total columns are generally slightly higher over land (bias ranging from 0 to 13 %) than IASI data. When IASI and MOPITT data are retrieved with the same a priori constraints, correlation coefficients are slightly improved. Large discrepancies (total column bias over 15 %) observed in the Northern Hemisphere during the winter months are reduced by a factor of 2 to 2.5. The detailed analysis of retrieved vertical profiles compared with collocated aircraft data from the MOZAIC-IAGOS network, illustrates the advantages and disadvantages of a constant vs. a variable a priori. On one hand, MOPITT agrees better with the aircraft profiles for observations with persisting high levels of CO throughout the year due to pollution or seasonal fire activity (because the climatology-based a priori is supposed to be closer to the real atmospheric state). On the other hand, IASI performs better when unexpected events leading to high levels of CO occur, due to a larger variability associated with the a priori.

Toward a chemical reanalysis in a coupled chemistry‐climate model: An evaluation of MOPITT CO assimilation and its impact on tropospheric composition

“…Despite these remaining uncertainties, our present understanding of the spatiotemporal distribution of CO and its variability has greatly improved in the past decade. This is largely due to the availability of aircraft measurements; thanks to the National Oceanic and Atmospheric Administration (NOAA) and the Measurement of Ozone and Water Vapor by Airbus In-Service Aircraft (MOZAIC) observational programs [e.g., Novelli et al, 1998Novelli et al, , 2003Emmons et al, 2004;Nédélec et al, 2003;Zbinden et al, 2013;Novelli and Masarie, 2015] and spaceborne measurements such as the Measurement of the Pollution in the Troposphere (MOPITT), the Atmospheric Infrared Sounder (AIRS), the Tropospheric Emissions Spectrometer (TES), and the Infrared Atmospheric Sounding Interferometer (IASI) [e.g., Jones et al, 2003;Warner et al, 2007;Worden et al, 2013Worden et al, , 2014Deeter et al, 2014;George et al, 2015;Clerbaux et al, 2015]. Past studies have integrated these observations of CO and related gases in both regional and global chemical transport models to constrain sources and sinks, in particular CO emissions [Streets et al, 2013, and references therein].…”

Top‐Down CO Emissions Based On IASI Observations and Hemispheric Constraints on OH Levels

“…The OH levels being overestimated by most models in the Northern Hemisphere, the total hemispheric top-down CO emissions are likely too high. Here we conduct an inverse modeling assessment of the global CO budget based on Infrared Atmospheric Sounding Interferometer (IASI) retrievals (George et al, 2015) for 2013, taking into account the MCF-derived constraints on global and (Table 1). hemispheric mean OH levels.…”

Multi-model evaluation of short-lived pollutant distributions over east Asia during summer 2008

“…In a similar manner to the IASI ozone columns, IASI CO columns are smoothed using Equation 1 (George et al, 2015). ECLIPSE models are compared to average August 2008 IASI total CO columns in Fig.…”