Evaluation of the operational Aerosol Layer Height retrieval algorithm for Sentinel-5 Precursor: application to O<sub>2</sub> A band observations from GOME-2A

Abstract

Abstract. An algorithm setup for the operational Aerosol Layer Height product for TROPOMI on the Sentinel-5 Precursor mission is described and discussed, applied to GOME-2A data, and evaluated with lidar measurements. The algorithm makes a spectral fit of reflectance at the O 2 A band in the near-infrared and the fit window runs from 758 to 770 nm. The aerosol profile is parameterised by a scattering layer with constant aerosol volume extinction coefficient and aerosol single scattering albedo and with a fixed pressure thickness. The algorithm's target parameter is the height of this layer. In this paper, we apply the algorithm to observations from GOME-2A in a number of systematic and extensive case studies, and we compare retrieved aerosol layer heights with lidar measurements. Aerosol scenes cover various aerosol types, both elevated and boundary layer aerosols, and land and sea surfaces. The aerosol optical thicknesses for these scenes are relatively moderate. Retrieval experiments with GOME-2A spectra are used to investigate various sensitivities, in which particular attention is given to the role of the surface albedo.From retrieval simulations with the single-layer model, we learn that the surface albedo should be a fit parameter when retrieving aerosol layer height from the O 2 A band. Current uncertainties in surface albedo climatologies cause biases and non-convergences when the surface albedo is fixed in the retrieval. Biases disappear and convergence improves when the surface albedo is fitted, while precision of retrieved aerosol layer pressure is still largely within requirement levels. Moreover, we show that fitting the surface albedo helps to ameliorate biases in retrieved aerosol layer height when the assumed aerosol model is inaccurate. Subsequent retrievals with GOME-2A spectra confirm that convergence is better when the surface albedo is retrieved simultaneously with aerosol parameters. However, retrieved aerosol layer pressures are systematically low (i.e., layer high in the atmosphere) to the extent that retrieved values no longer realistically represent actual extinction profiles. When the surface albedo is fixed in retrievals with GOME-2A spectra, convergence deteriorates as expected, but retrieved aerosol layer pressures become much higher (i.e., layer lower in atmosphere). The comparison with lidar measurements indicates that retrieved aerosol layer heights are indeed representative of the underlying profile in that case. Finally, subsequent retrieval simulations with two-layer aerosol profiles show that a model error in the assumed profile (two layers in the simulation but only one in the retrieval) is partly absorbed by the surface albedo when this parameter is fitted. This is expected in view of the correlations between errors in fit parameters and the effect is relatively small for elevated layers (less than 100 hPa). If one of the scattering layers is near the surface (boundary layer aerosols), the effect becomes surprisingly large, in such a way that the retrieved height of the sin...

Comparison of dust-layer heights from active and passive satellite sensors

“…While it has been already demonstrated that a positive deviation of the true surface albedo from the assumed prior value leads to an underestimation of layer height (Sanders et al, 2015), the similar tendency of lower retrievals by GOME-2 and SCIAMACHY suggests that the influence of a wrongly prescribed aerosol model can be ruled out. This is because the KNMI/GOME-2 algorithm uses a HenyeyGreenstein phase function, whereas IUP-SCIAMACHY ingests spectrally resolved T-matrix calculations of the phase matrix representing aspherical dust particles (see Table 1).…”

“…While IASI is mainly sensitive to the aerosol coarse mode, SCIAMACHY and GOME-2 are sensitive to both the fine and coarse modes. The height retrieved from these sensors depends on whether the surface albedo is retrieved simultaneously or not as shown by Sanders et al (2015). They found that fixing the albedo in the retrieval gave a lower dust height than when retrieving both the albedo and the dust height.…”

An exploratory study on the aerosol height retrieval from OMI measurements of the 477 nm O<sub>2</sub> − O<sub>2</sub> spectral band using a neural network approach

“…An ideal surface albedo database should be aerosol and cloud free, as well as representative of the viewing and solar angles encountered by the space-borne sensor. Problems related to uncertainties in surface albedo climatology for the aerosol retrieval problem are well known and were recently highlighted by Sanders et al (2015), although a different spectral band is used (O 2 −A at 758-770 nm).…”

“…While g = 0.7 is the reference value for most of aerosols, scenes with g = 0.6 are related to finer and weakly absorbing particles with a somewhat reduced forward scattering direction such as carbonaceous aerosols, desert dust and volcanic dash models as given by the ESA aerosol CCI project (de Leeuw et al, 2013). Values of g = 0.8 are associated with larger particles and an increased forward scattering direction such as cirrus (Sanders et al, 2015). An overestimation of g (i.e.…”

“…With a reference asymmetry parameter of g = 0.7, the intermediate value typically observed (Dubovik et al, 2002), the Henyey-Greenstein function is known to be smooth and reproduce the Mie scattering functions reasonably well for most of aerosol types. This approach is also used for the preparation of the operational aerosol layer height retrieval algorithm from Sentinel-5 Precursor (Sanders et al, 2015) and for explicit aerosol corrections in the AMF calculation when retrieving trace gases such as tropospheric NO 2 (Spada et al, 2006;Wagner et al, 2007;Castellanos et al, 2015).…”