Potential of multispectral synergism for observing ozone pollution by combining IASI-NG and UVNS measurements from EPS-SG satellite
Lorenzo Costantino1, Juan Cuesta1, Emanuele Emili2, Adriana Coman1, Gilles Foret1, Gaëlle Dufour1, Maxim Eremenko1, Yohann Chailleux1, Matthias Beekmann1, and Jean-Marie Flaud11LISA, CNRS UMR7583 Université Paris-Est Créteil et Université Paris Diderot, 61 Av. Général de Gaulle, 94010, Créteil, France 2CERFACS, 42 Av. G. Coriolis, 31057, Toulouse, France
Received: 12 Nov 2016 – Accepted for review: 12 Dec 2016 – Discussion started: 21 Dec 2016
Abstract. Present and future satellite observations offer a great potential for monitoring air quality on daily and global basis. However, measurements from currently in orbit satellites do not allow using a single sensor to probe accurately surface concentrations of gaseous pollutants such as tropospheric ozone (Liu et al., 2010). Using single-band approaches based on spaceborne measurements of either thermal infrared radiance (TIR, Eremenko et al., 2008) or ultraviolet reflectance (UV, Liu et al., 2010) only ozone down to the lower troposphere (3 km) may be observed. A recent multispectral method (referred to as IASI+GOME-2) combining the information of IASI and GOME-2 (both onboard MetOp satellites) spectra, respectively from the TIR and UV, has shown enhanced sensitivity for probing ozone at the lowermost troposphere (LMT, below 3 km of altitude) with maximum sensitivity down to 2.20 km a.s.l. over land, while sensitivity for IASI or GOME-2 only peaks at 3 to 4 km at lowest (Cuesta et al., 2013). Future spatial missions will be launched in the upcoming years, such as EPS-SG, carrying new-generation sensors of IASI and GOME-2 (respectively IASI-NG and UVNS) that will enhance the capacity to observe ozone pollution and particularly by synergism of TIR and UV measurements.
In this work we develop a pseudo-observation simulator and evaluate the potential of future EPS-SG satellite observations through IASI-NG+UVNS multispectral method to observer near-surface O3. The pseudo-real state of atmosphere (nature run) is provided by the MOCAGE (MOdèle de Chimie Atmosphérique à Grande Échelle) chemical transport model. Simulations are calibrated by careful comparisons with real data, to ensure the best consistency between pseudo-reality and reality, as well as between the pseudo-observation simulator and existing satellite products. We perform full and accurate forward and inverse radiative transfer calculations for a period of 4 days (8–11 July 2010) over Europe.
In the LMT, there is a remarkable agreement in the geographical distribution of O3 partial columns, calculated between the surface and 3 km of altitude, between IASI-NG+UVNS pseudo-observations and the corresponding MOCAGE pseudo-reality. With respect to synthetic IASI+GOME-2 products, IASI-NG+UVNS shows a higher correlation between pseudo-observations and pseudo-reality, enhanced by about 11 %. The bias on high ozone retrieval is reduced and the average accuracy increases by 22 %. The sensitivity to LMT ozone is enhanced on average with 154 % (from 0.29 to 0.75, over land) and 208 % (from 0.21 to 0.66, over ocean) higher degrees of freedom. The mean height of maximum sensitivity for the LMT peaks at 1.43 km over land and 2.02 km over ocean, respectively 1.03 km and 1.30 km below that of IASI+GOME-2. IASI-NG+UVNS shows also good retrieval skill in the surface-2 km altitude range with a mean DOF (degree of freedom) of 0.52 (land) and 0.42 (ocean), and an average Hmax (altitude of maximum sensitivity) of 1.29 km (land) and 1.96 km (ocean).
Unique of its kind for retrieving ozone layers of 2–3 km thickness, in the first 2–3 km of the atmosphere, IASI-NG+UVNS is expected to largely enhance the capacity to observe ozone pollution from space.
Costantino, L., Cuesta, J., Emili, E., Coman, A., Foret, G., Dufour, G., Eremenko, M., Chailleux, Y., Beekmann, M., and Flaud, J.-M.: Potential of multispectral synergism for observing ozone pollution by combining IASI-NG and UVNS measurements from EPS-SG satellite, Atmos. Meas. Tech. Discuss., doi:10.5194/amt-2016-374, in review, 2016.