Ozone II

The global record of ozone profiles derived from nadir UV sensors – BUV, SBUV and SBUV/2 – is continued with the OMPS NP on board of Suomi NPP and JPSS-1 satellites. Ozone retrievals from multiple UV nadir instruments are combined into the merged ozone record for studying long-term ozone trends. Small offsets between the instruments can affect trend estimates and related uncertainties. In version 8.6, all SBUV instruments were accurately cross-calibrated, but nevertheless small but consistent differences in ozone between overlapping SBUV instruments were found. To understand and attribute these differences, we compared recent SBUV instruments with MLS observations and GEOS CCM model simulations. We found that some of the observed differences are related to geophysical effects. In the upper stratosphere, a large fraction of differences can be explained if the diurnal ozone cycle is accounted for. Using 13 years of MLS data, we developed an additive correction for the seasonal ozone climatology to account for the QBO vertical pattern in the low resolution nadir retrievals. Our ultimate goal is to improve cross-calibrations among SBUV sensors and therefore reduce uncertainties in the ozone trend.

We present an updated global total ozone trend assessment for the 22-year period from 1995 to 2017 using the European Space Agency's Climate Change Initiative (ESA-CCI) GOME-type Total Ozone Essential Climate Variable (GTO-ECV) data record. We show that the expected onset of ozone recovery - as a consequence of decreasing amounts of ozone depleting substances - is still largely masked by strong dynamically induced inter-annual variability. Only for small regions slight indications, i.e. significant positive trends, were found. Thus, uncertainty still remains as to the exact timing of ozone recovery, in particular in the middle latitudes. The GTO-ECV data record has been compiled from a series of nadir-viewing satellite instruments including GOME/ERS-2, SCIAMACHY/ENVISAT, GOME-2/MetOp-A, GOME-2/MetOp-B, as well as OMI/AURA. The individual sensors provide observations of the total ozone column with a high degree of consistency which has been achieved through the application of a common advanced direct retrieval algorithm GODFIT Version 4. Currently, GTO-ECV covers the past 22 years, but it is regularly extended on a quasi-operational basis as part of the EU Copernicus Climate Change Service operated by the European Centre for Medium-Range Weather Forecasts (ECMWF). Geophysical validation of the GTO-ECV data record using ground-based Dobson, Brewer and SAOZ (Système d’Analyse par Observation Zénitale) instruments has demonstrated its remarkable accuracy and long-term stability. In particular, GTO-ECV meets the specific requirements for total ozone formulated by the Global Climate Observing System (GCOS) program. In addition to the evaluation of spatially resolved inter-annual ozone variability and long-term trends, the data record is used to verify the abilities of Chemistry-Climate Models (CCMs) to reproduce the observed ozone features. Confronting model simulations with observations helps to identify the strengths and weaknesses of the model's system and to improve the description of the processes relevant for the short- and long-term ozone variability in a changing climate. We compare ozone trends derived from GTO-ECV with those obtained from different model simulations performed with the ECHAM/MESSY Atmospheric Chemistry (EMAC) CCM system. During the next two decades GTO-ECV will be further extended with measurements from the Copernicus mission Sentinel-5 Precursor (successfully launched in October 2107), the third GOME-2 instrument on-board MetOp-C (launch planned in September 2018), Sentinel-4, and Sentinel-5.

Total ozone columns have been routinely retrieved from satellite nadir observations in the Huggins bands for several decades using algorithms in constant evolution. In Europe, DOAS-type algorithms are used for operational processing of total ozone from GOME/ERS-2, SCIAMACHY/Envisat, OMI/Aura and GOME-2/Metop. The DOAS approach is fast and provides good results for most geophysical conditions. However it generally neglects the wavelength-dependence of the effective light path in the fit interval, which can lead to significant biases under conditions of large ozone optical depth. This motivated the development of a direct-fitting algorithm (GODFIT), which provides more accurate results under a wider range of conditions but at the cost of more demanding computational resources. The total ozone direct-fitting algorithm is the baseline for the generation of climate data records within the ESA CCI and Copernicus Climate Change service activities.

We present an improved DOAS-type total ozone algorithm currently developed as part of the level-2 prototype processor project for the future Sentinel-5 mission, which preserves accuracy, while maintaining high computational performance compatible with near-real time processing. The approach uses a Taylor expansion of the O₃ slant columns considering their wavelength dependence. In addition, a new iterative molecular Ring correction is implemented, which leads to a substantial reduction of ozone biases. This is combined with a derivation of the effective surface albedo of the observed scene at 340 nm, while air mass factors are pre-computed at the wavelength of 328.2 nm and stored in external LUTs for fast slant-to-vertical column conversion. Random and systematic error estimates are provided on a pixel-per-pixel basis, as well as averaging kernels. We present OMI and TROPOMI ozone datasets derived with this new algorithm and test their accuracy against reference direct-fitting results. Additional validation using independent ground-based Brewer and Dobson data confirm the good performance of the new DOAS retrievals, which show no significant dependence with respect to geophysical parameters such as solar or viewing zenith angle, latitude and cloud parameters.

This contribution focuses on the operational GOME-2 trace gas column products developed in the framework of EUMETSAT’s Satellite Application Facility on Atmospheric Composition Monitoring (AC SAF). We present an overview of the retrieval algorithms for ozone, OClO, NO2, SO2 and formaldehyde, and we show examples of various applications such as air quality and climate monitoring, using observations from the GOME-2 instruments on MetOp-A and MetOp-B.
Total ozone and the minor trace gas columns from GOME-2 are retrieved with the GOME Data Processor (GDP), which uses an optimized Differential Optical Absorption Spectroscopy (DOAS) algorithm, with air mass factor conversions based on the LIDORT model. Improved total and tropospheric NO2 columns are retrieved in the visible wavelength region between 425 and 497 nm. SO2 emissions from volcanic and anthropogenic sources can be measured by GOME-2 using the UV wavelength region around 320 nm. For formaldehyde, an optimal DOAS fitting window around 335 nm has been determined for GOME-2.
The use of trace gas observations from the GOME-2 instruments on MetOp-A and MetOp-B for air quality purposed will be illustrated, e.g. for South-East Asia and Europe. Furthermore, comparisons of the GOME-2 satellite observations with ground-based measurements will be shown. Finally, the use of GOME-2 trace-gas column data in the Copernicus Atmosphere Monitoring Service (CAMS) will be presented.

RAL's ozone profile retrieval scheme for the GOME-class of solar uv/vis backscatter spectrometer has unique sensitivity to tropospheric ozone, which led to its selection for nadir ozone profile retrieval from this class of sensor in ESA's Climate Change Initiative (CCI) and inclusion in the Tropospheric Ozone Assessment Report (TOAR). The JASMIN computing facility at RAL has enabled the production of full-mission global data sets from GOME-1, SCIAMACHY, OMI and GOME-2A & 2B, resulting in over 20 years of height-resolved dataset for ozone from 1995-2016, spanning both stratosphere and troposphere.

A reprocessing of data has been enabled under the Copernicus Climate Change (C3S) project and work is underway to reconcile these data time series. We present some of the retrieval scheme advancements and highlights of the latest version of the dataset, including comparisons with coupled chemistry climate models, chemical transport models and MACC/CAMS analyses.

The scheme has also been operating in near real-time for GOME-2 for several years. Following recent updates from CCI work, the data quality has improved. Highlights from the 2018 summer identified in the NRT scheme will also be presented.

The creation of homogenized long-term ozone datasets based on limb-viewing measurements from ENVISAT sensors (GOMOS, MIPAS, SCIAMACHY) as well as from ESA Third Party Missions (OSIRIS, SMR and ACE-FTS) is one of the objectives of the ESA ozone-CCI project.

In the framework of the ozone-CCI project, different datasets are created. The datasets from individual instruments are collected in the user-friendly HARMonized dataset of Ozone profiles (HARMOZ). For trend analyses, the ozone profile measurements from seven ESA and NASA satellite instruments (SAGE II, GOMOS, MIPAS, SCIAMACHY, ACE-FTS, OSIRIS, OMPS) are merged in a climate data record—the merged SAGE-CCI-OMPS dataset, which covers more than 30 years, from 1984 to 2017. This recently created dataset is used for evaluating ozone trends in the stratosphere through multiple linear regression. Negative ozone trends in the upper stratosphere are observed before 1997 and positive trends are found after 1997. The upper stratospheric trends are statistically significant at mid-latitudes and indicate ozone recovery, as expected from the decrease of stratospheric halogens that started in the middle of the 1990s and stratospheric cooling.

In the presentation, we will show the obtained results and discuss future developments.

Tropospheric ozone is the most hazardous gaseous pollutant. Monitoring and understanding the spatiotemporal evolution of ozone pollution is therefore a crucial societal issue. Observation of tropospheric ozone at continental and global scales is only possible by spaceborne remote sensing. However, standard spaceborne observations using single-band approaches using either UV or IR measurements show limited sensitivity to ozone in the atmospheric boundary layer, which is the major concern for air quality.

A new capacity to observe the daily distribution of ozone located at the lowermost troposphere (below 3 km of altitude) is now offered by an innovative multispectral synergism of IASI and GOME-2 measurements at the IR and UV respectively (Cuesta et al., 2013; 2018). This novel method called IASI+GOME2 retrieves ozone at the lowermost troposphere with a low mean bias, a linear correlation of 0.86 and a mean precision of 16% as compared to reference ozonesonde measurements around the world during all seasons. The retrieval sensitivity peaks down to 2 to 2.5 km over land during summer. This multispectral product is available at the IASI spatial resolution (pixels spaced by 25x25 km²) and for cloud fractions below 30%. IASI+GOME2 retrievals also show a good and currently unique agreement with respect to in situ measurements of ozone at the surface, over East Asia and Europe, for both ozone outbreak events and the seasonal evolution. IASI+GOME2 data is publicly available at the French data centre AERIS/ESPRI (http://cds-espri.ipsl.fr).

The current presentation focuses on the analysis of global observations of lowermost tropospheric ozone from IASI+GOME2. We study the main global hotspots of ozone at the lowermost troposphere at the tropics and mi-latitudes (e.g. over South and East Asia). We provide a new observational characterisation of the evolution and transport pathways of these ozone hotpots, in link with meteorological and dynamical conditions.