Retrievals of sulfur dioxide from the Global Ozone Monitoring Experiment 2 (GOME-2) using an optimal estimation approach: Algorithm and initial validation

Abstract

We apply an optimal estimation algorithm originally developed for retrieving ozone profiles from the Global Ozone Monitoring Experiment (GOME) and the Ozone Monitoring Instrument (OMI) to make global observations of sulfur dioxide from the Global Ozone Monitoring Experiment 2 (GOME‐2) on the MetOp‐A satellite. Our approach combines a full radiative transfer calculation, retrieval algorithm, and trace gas climatologies to implicitly include the effects of albedo, clouds, ozone, and SO2 profiles in the retrieval. Under volcanic conditions, the algorithm may also be used to directly retrieve SO2 plume altitude. Retrieved SO2 columns over heavy anthropogenic pollution typically agree with those calculated using a two‐step slant column and air mass factor approach to within 10%. Retrieval uncertainties are quantified for GOME‐2 SO2 amounts; these are dominated by uncertainty contributions from noise, surface albedo, profile shape, correlations with other retrieved parameters, atmospheric temperature, choice of wavelength fitting window, and aerosols. When plume altitudes are also simultaneously retrieved, additional significant uncertainties result from uncertainties in the a priori altitude, the model's vertical layer resolution, and instrument calibration. Retrieved plume height information content is examined using the Mount Kasatochi volcanic plume on 9 August 2008. An a priori altitude of 10 km and uncertainty of 2 km produce degrees of freedom for signal of at least 0.9 for columns >30 Dobson units. GOME‐2 estimates of surface SO2 are compared with in situ annual means over North America in 2008 from the Clear Air Status and Trends Network (CASTNET; r = 0.85, N = 65) and Air Quality System (AQS) and National Air Pollution Surveillance (NAPS; r = 0.40, N = 438) networks.

Tropospheric emissions: Monitoring of pollution (TEMPO)

“…The PCA algorithm has been successfully implemented with several polar-orbiting sensors including OMI, OMPS, TOMS, and GOME-2 and is now the operational algorithm for the new generation OMI standard planetary boundary layer (PBL) SO 2 product [28]. The other method is the SAO SO 2 optimal estimation algorithm [80], which was developed to retrieve SO 2 vertical columns simultaneously with ozone profiles. The optimal estimation approach applies the ozone profile algorithm for SO 2 , using an online radiative transfer calculation and trace gas climatologies to include the effects of surface albedo, clouds, ozone and SO 2 profiles in the retrieval.…”

“…Issues in the representation of snow-covered surfaces also lead to larger uncertainties [82]. Canadian academia and government are collaborating to address these by developing direct inversions [80] to improve sensitivity in the boundary layer [29], developing methods to better constrain stratospheric abundances including assimilation of stratospheric profiles, implementing an improved representation of snow in the inversions [74], and developing algorithms to explicitly account for the effects of aerosols on trace gas retrievals [64]. Validation of TEMPO observations over Canada is also a priority with an expansion of the Canadian Pandora network [37] and an aircraft measurement campaign being planned.…”

Sulfur dioxide retrievals from TROPOMI onboard Sentinel-5 Precursor: algorithm theoretical basis

“…Current algorithms exploit back-scattered radiance measurements in a wide spectral range using a direct fitting approach Nowlan et al, 2011), a principal component analysis (PCA) method (Li et al, 2013) or (some form of) differential optical absorption spectroscopy (DOAS; Platt and Stutz, 2008); see, e.g., Richter et al (2009), Hörmann et al (2013), or Theys et al (2015.…”

“…This type of instrument can only validate surface concentrations, and additional information on the SO 2 vertical profile (e.g., from model data) is required to make the link with the satellite retrieved column. However, in situ instruments are being operated for pollution monitoring in populated areas, and allow for extended and long-term comparisons with satellite data (see, e.g., Nowlan et al, 2011).…”

“…Over the last decades, a host of satellite-based UV-visible instruments have been used for the monitoring of anthropogenic and volcanic SO 2 emissions. Total vertical column density (VCD) of SO 2 has been retrieved with the sensors TOMS (Krueger, 1983), GOME (Eisinger and Burrows, 1998;Thomas et al, 2005;Khokar et al, 2005), SCIAMACHY (Afe et al, 2004), OMI (Krotkov et al, 2006;Yang et al, 2007Yang et al, , 2010Li et al, 2013;Theys et al, 2015), GOME-2 Bobrowski et al, 2010;Nowlan et al, 2011;Rix et al, 2012;Hörmann et al, 2013) and OMPS . In particular, the Ozone Monitoring Instrument (OMI) has largely demonstrated the value of satellite UV-visible remote sensing (1) in monitoring volcanic plumes in near-real time (Brenot et al, 2014) and changes in volcanic degassing at the global scale , and references therein) and (2) in detecting and quantifying large anthropogenic SO 2 emissions, weak or N. Theys et al: S-5P SO 2 algorithm theoretical basis unreported emission sources worldwide (Theys et al, 2015;Fioletov et al, 2016;McLinden et al, 2016) as well as investigating their long-term changes van der A et al, 2016;He et al, 2016).…”