Troposphere / Ozone

With the convective cloud differential algorithm (CCD) the tropospheric ozone column (below 10 km) is calculated as the difference between the total ozone column for cloud free observations and the stratospheric column given by the vertical column above high reaching convective clouds. In this study our CCD algorithm is applied to the total ozone column product from GOME, SCIAMACHY, OMI and GOME-2. The resulting timeseries includes 20 years of tropospheric ozone data from 1995 to 2015. Here the same retrieval was applied to all instruments both for the total ozone column (GODFIT) as for the tropospheric column (CCD). This results in a very consitent data set. For the trend analysis individual ozone sonde stations as well as certain latitude bands were considered. Together with the linear term we fitted an El Niño index, a QBO index and a combination of several sinus and cosinus functions to simulate the seasonal variations as well as the phase shift. Despite the fact that the same algorithms were used, the observed trends still depend on the satellite instrument. While GOME-2 tropospheric ozone data showed a trend of 0.22 DU/yr in the 10^°S to 0° latitude band between 2007 and 2014, the data from OMI increased by 0.037 DU/yr in the same latitude band and period. Assuming that the atmospheric trends are the same for the two overpass times of the instruments, we looked forinstrumental effectsasone possibleexplanation for the different trends.Therefore the data were compared to the SHADOZ ozone soundings. The partialcolumn below 10 km was subtracted from the satellite insturments' data.The difference to the soundings showed temporal drifts for all instruments varying between -1.08 DU/yr and 0.06 DU/yr. The different trends in both the troposphericsatellite data and the validation indicates the need of further harmonized CCD data before analysing long-term trends.

Stratospheric ozone is well known for protecting the surface from harmful ultraviolet solar radiation whereas ozone in the troposphere plays a more complex role. In the lower troposphere ozone can be extremely harmful for human health as it can oxidize biological tissues and causes respiratory problems. Several studies have shown that the tropospheric ozone burden (300±30Tg (IPCC, 2007)) increases by 1-7% per decade in the tropics (Beig and Singh, 2007; Cooper et al., 2014) which makes the need to monitor it on a global scale crucial. Remote sensing from satellites has been proven to be very useful in providing consistent information of tropospheric ozone concentrations over large areas. Tropical tropospheric ozone columns can be retrieved with the Convective Cloud Differential (CCD) technique (Ziemke et al. 1998) using retrieved total ozone columns and cloud parameters from space-borne observations. We have developed a CCD-IUP algorithm which was applied  to GOME/ ERS-2 (1995-2003), SCIAMACHY/ Envisat (2002-2012), and GOME-2/ MetOpA (2007-2012) weighting function DOAS (Coldewey-Egbers et al., 2005, Weber et al., 2005) total ozone data. A unique long-term record of monthly averaged tropical tropospheric ozone columns (20°S – 20°N) was created starting in 1996. This dataset has been extensively validated by comparisons with SHADOZ (Thompson et al., 2003) ozonesonde data and limb-nadir Matching (Ebojie et al. 2014) tropospheric ozone data. The comparison shows good agreement with respect to range, inter-annual variation, and variance. Biases where found to be within 5DU and the RMS errors less than 10DU. The CCD tropospheric ozone comparisons using SCIAMACHY data with tropospheric ozone columns from limb-nadir Matching (Ebojie et al., 2014) have shown that CCD results are less noisy and correlate better with ozonesondes. This 17-years dataset has been harmonized into one consistent time series, taking into account the three instruments’ difference in ground pixel size.  The harmonised dataset is used to determine tropical tropospheric ozone trends. The first results of tropospheric ozone trends are to be presented.

It has been shown that adding visible measurements in the Chappuis band to UV measurements in the Hartley/Huggins bands can significantly enhance retrieval sensitivity to lower tropospheric ozone from backscattered solar radiances due to deeper photon penetration in the visible to the surface than in the ultraviolet. The first NASA EVI (Earth Venture Instrument) TEMPO (Tropospheric Emissions: Monitoring of Pollution) instrument is being developed to measure backscattered solar radiation in two channels (~290-490 and 540-740 nm) and make atmospheric pollution measurements over North America from the Geostationary orbit. However, this retrieval enhancement has yet to be solidly demonstrated from existing measurements due to the weak ozone absorption in the visible and strong interferences from surface reflectance and the requirement of accurate radiometric calibration across different spectral channels.

We present GOME-2 retrievals from joint UV/visible measurements using the SAO optimal estimation based ozone profile retrieval algorithm, to directly explore the retrieval improvement in lower tropospheric ozone from additional visible measurements. To reduce the retrieval interference from surface reflectance, we add characterization of surface spectral reflectance in the visible based on ASTER and other surface reflectance spectra and MODIS BRDF climatology into the ozone profile algorithm using two approaches: fitting several EOFs (Empirical Orthogonal Functions) and scaling reflectance spectra. We also perform empirical radiometric calibration of the GOME-2 data based on radiative transfer simulations. We evaluate the retrieval improvement of joint UV/visible retrieval over the UV retrieval. These results clearly show the potential of using the visible to improve lower tropospheric ozone retrieval.

Numerous studies have drawn attention to the complexities related to the retrievals of tropospheric NO₂ columns derived from satellite UV-Vis measurements in the presence of aerosols. Aerosol particles will be a challenge for the next generation of air quality satellite instruments such as TROPOMI on Sentinel-5 Precursor, Sentinel-4 and Sentinel-5.  Fine particles affect the UV-Vis satellite spectral measurements and the length of the average light path followed by the photons. The Ozone Monitoring Instrument (OMI) instrument, on board of the NASA EOS-Aura satellite, has provided daily global measurements of tropospheric NO₂ for more than a decade. However, aerosols are not explicitly taken into account in the current operational OMI tropospheric NO₂ retrieval chain (DOMINO v2 [Boersma et al., 2011]).

Instead, the operational OMI O₂-O₂ cloud retrieval algorithm, based on the Differential Optical Absorption Spectroscopy (DOAS) approach, is applied both to cloudy and to cloud-free scenes with aerosols present. Perturbation of the OMI cloud retrievals over scenes dominated by aerosols has been observed in recent studies led by [Castellanos et al., 2015; Lin et al., 2015; Lin et al., 2014]. We investigated the reasons of these perturbations by analyzing in detail the complex interplay between the spectral effects of aerosols and the OMI O₂-O₂ cloud retrieval algorithm, as it is implemented in the operational chain, over cloud-free scenes [Chimot et al., 2015]. For that purpose, collocated OMI and MODIS Aqua aerosol product and OMI products are analyzed over East China, in industrialized area. In addition, the behavior of the OMI O₂-O₂ cloud retrieval algorithm in presence of aerosols is simulated.

Over cloud-free scenes dominated by aerosols, the OMI effective cloud fraction represents the enhancement of the scene brightness induced by the additional scattering effects of fine particles. The general decrease of the OMI effective cloud pressure with increasing Aerosol Optical Thickness (AOT) primarily represents the shielding of the O₂-O₂ column. These analyses also point out that the O₂-O₂ spectral domain contains some information about aerosols: the continuum reflectance is primarily constrained by the AOT while the O₂-O₂ slant column density (SCD) mostly results from the combination of AOT and aerosols altitude. Since effective cloud retrievals cannot distinguish cloud and aerosol impacts, these perturbations have direct impacts on the tropospheric NO₂ retrieval.

One of the key findings identified by our study is the coarse sampling of the employed cloud Look-Up Table (LUT) to convert the results of the applied DOAS fit into effective cloud fraction and pressure. This leads to an underestimation of tropospheric NO₂ amount in cases of elevated aerosol particles. A high sampling of the variation of O₂-O₂ SCD and continuum reflectance as a function of effective cloud fraction and pressure in case of low continuum reflectance values is requested for applying an aerosol correction. The elaboration of a new OMI cloud LUT is scheduled in the next update of the OMI O₂-O₂ cloud algorithm. The updates of the OMI O₂-O₂ cloud algorithm will be presented in terms of impacts of the effective cloud retrievals and reduced biases of tropospheric NO₂ columns over cloud-free scenes dominated by aerosols in China. Finally, we will discuss preliminary results about the sensitivity to retrieve some aerosol parameters from the O₂-O₂ DOAS fit and the potential expectations for a first explicit aerosol correction, without the use of effective cloud parameters.

Air quality is a crucial societal issue in East Asia, which is seriously aggravating in the 21st century. The main gaseous pollutant is tropospheric ozone. Rapid population growth and economic development in regions as the North China Plain is leading to emission of large quantities of ozone precursors. In consequence, a greater production of tropospheric ozone is transported beyond the urban scale, thus causing trans-boundary pollution. However, analysis of trans-boundary pollution is difficult due to a complete absence of measurements over the East China Sea and few available ozone observations over China.

Advanced analysis of satellite observations is a new very promising approach to analyse the evolution and transport of tropospheric ozone pollution plumes at the regional scale. Recently, an innovative multispectral approach has been developed, which combines IASI IR observations and GOME-2 UV measurements (Cuesta et al., 2013). This unique multispectral approach has allowed the observation of ozone plumes in the lowermost troposphere (below 3 km of altitude), for the first time from space.

The current presentation will show the characterization of a major lowermost tropospheric ozone event over East Asia (including China and Japan) occuring during the springtime of 2009, based on a unique synergism of innovative multispectral satellite observations, ground-based measurements and state-of-the-art regional model simulations. We will assess the dynamics of lower tropospheric ozone over East Asia, studying the associated transport patterns, meteorological conditions and atmospheric composition. A key question to be addressed is the identification the origin of the pollution outbreak, thus determining whether it is associated to westerly transport, local production or stratospheric transport.