Overview of the O3M SAF GOME-2 operational atmospheric composition and UV radiation data products and data availability

Hassinen, S.; Balis, Dimitris; Bauer, H.; Begoin, M.; Delcloo, Andy; Eleftheratos, Kostas; García, Sebastián Gimeno; Granville, J.; Grossi, M.; Hao, Nan; Hedelt, Pascal; Hendrick, F.; Heß, Michael; Heue, Klaus-Peter; Hovila, Jari; Jonch-Sorensen, H.; Kalakoski, Niilo; Kauppi, Anu; Kiemle, Stephan; Kins, L.; Koukouli, M. E.; Kujanpää, Jukka; Lambert, Jean-Christopher; Lang, Ruediger; Lerot, Christophe; Loyola, Diego; Pedergnana, Mattia; Pinardi, Gaia; Romahn, Fabian; Roozendaël, Michel Van; Lutz, Ronny; Smedt, Isabelle De; Stammes, P.; Steinbrecht, Wolfgang; Tamminen, J.; Theys, Nicolas; Tilstra, L. G.; Tuinder, O. N. E.; Valks, Pieter; Zerefos, C. S.; Zimmer, Walter; Zyrichidou, I.

doi:10.5194/amt-9-383-2016

Cited by 57 publications

(55 citation statements)

References 65 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the fitting residuals of GOME-2B compared to those of GOME-2A are much smaller in 2013 and higher in early 2007 (Hao et al, 2014). According to Hassinen et al (2016), the impact of GOME-2 instrument degradation on Level-2 product quality depends on the spectral region and the type of retrieval methods selected. The operational GOME-2 total and tropospheric NO 2 columns from MetOp-A and MetOp-B are generated by the Remote Sensing Technology Institute (IMF) of the German Aerospace Center (DLR) using the UPAS (Universal Processor for UV/VIS Atmospheric Spectrometers) environment version 1.3.9, implementing the Level-1-to-2 GOME data processor (GDP) version 4.7 algorithm (http://atmos.eoc.dlr.…”

Section: Satellite Observationsmentioning

confidence: 99%

See 1 more Smart Citation

Comparisons of ground-based tropospheric NO2 MAX-DOAS measurements to satellite observations with the aid of an air quality model over the Thessaloniki area, Greece

et al. 2017

Self Cite

View full text Add to dashboard Cite

Abstract. One of the main issues arising from the comparison of ground-based and satellite measurements is the difference in spatial representativeness, which for locations with inhomogeneous spatial distribution of pollutants may lead to significant differences between the two data sets. In order to investigate the spatial variability of tropospheric NO 2 within a sub-satellite pixel, a campaign which lasted for about 6 months was held in the greater area of Thessaloniki, Greece. Three multi-axial differential optical absorption spectroscopy (MAX-DOAS) systems performed measurements of tropospheric NO 2 columns at different sites representative of urban, suburban and rural conditions. The direct comparison of these ground-based measurements with corresponding products from the Ozone Monitoring Instrument onboard NASA's Aura satellite (OMI/Aura) showed good agreement over the rural and suburban areas, while the comparison with the Global Ozone Monitoring Experiment-2 (GOME-2) onboard EUMETSAT's Meteorological Operational satellites' (MetOp-A and MetOp-B) observations is good only over the rural area. GOME-2A and GOME-2B sensors show an average underestimation of tropospheric NO 2 over the urban area of about 10.51 ± 8.32 × 10 15 and 10.21 ± 8.87 × 10 15 molecules cm −2 , respectively.The mean difference between groundbased and OMI observations is significantly lower (6.60 ± 5.71 × 10 15 molecules cm −2 ). The differences found in the comparisons of MAX-DOAS data with the different satellite sensors can be attributed to the higher spatial resolution of OMI, as well as the different overpass times and NO 2 retrieval algorithms of the satellites. OMI data were adjusted using factors calculated by an air quality modeling tool, consisting of the Weather Research and Forecasting (WRF) mesoscale meteorological model and the Comprehensive Air Quality Model with Extensions (CAMx) multiscale photochemical transport model. This approach resulted in significant improvement of the comparisons over the urban monitoring site. The average difference of OMI observations from MAX-DOAS measurements was reduced to −1.68 ± 5.01 × 10 15 molecules cm −2 .

show abstract

Section: Satellite Observationsmentioning

confidence: 99%

“…The profiles can be fitted by an exponential decrease and, similarly to OMI a priori profiles, compare better with RC and SC sites. More details on the GDP 4.7 algorithm can be found in Valks et al (2011) and Hassinen et al (2016).…”

Section: Satellite Observationsmentioning

confidence: 99%

Comparisons of ground-based tropospheric NO2 MAX-DOAS measurements to satellite observations with the aid of an air quality model over the Thessaloniki area, Greece

et al. 2017

Self Cite

View full text Add to dashboard Cite

show abstract

“…The current primary GOME-2B is operated in this mode, whereas the older GOME-2A is operated in a reduced swath with a swath width of 960 km and nadir ground pixel size of 40 km × 40 km since June 2013. Further description of the GOME-2 instruments may be found in Munro et al (2015) and Hassinen et al (2016). The NASA Aura satellite was launched in 2004 also in a polar orbit and with Equatorcrossing time of 13:30 LT.…”

Section: Satellite Tropospheric No 2 Observationsmentioning

confidence: 99%

MAX-DOAS NO2 observations over Guangzhou, China; ground-based and satellite comparisons

et al. 2018

Self Cite

View full text Add to dashboard Cite

Abstract. In this study, the tropospheric NO 2 vertical column density (VCD) over an urban site in Guangzhou megacity in China is investigated by means of MAX-DOAS measurements during a campaign from late March 2015 to mid-March 2016. A MAX-DOAS system was deployed at the Guangzhou Institute of Geochemistry of the Chinese Academy of Sciences and operated there for about 1 year, during the spring and summer months. The tropospheric NO 2 VCDs retrieved by the MAX-DOAS are presented and compared with space-borne observations from GOME-2/MetOp-A, GOME-2/MetOp-B and OMI/Aura satellite sensors. The comparisons reveal good agreement between satellite and MAX-DOAS observations over Guangzhou, with correlation coefficients ranging between 0.795 for GOME-2B and 0.996 for OMI. However, the tropospheric NO 2 loadings are underestimated by the satellite sensors on average by 25.1, 10.3 and 5.7 %, respectively, for OMI, GOME-2A and GOME-2B. Our results indicate that GOME-2B retrievals are closer to those of the MAX-DOAS instrument due to the lower tropospheric NO 2 concentrations during the days with valid GOME-2B observations. In addition, the effect of the main coincidence criteria is investigated, namely the cloud fraction (CF), the distance (d) between the satellite pixel center and the ground-based measurement site, as well as the time period within which the MAX-DOAS data are averaged around the satellite overpass time. The effect of CF and time window criteria is more profound on the selection of OMI overpass data, probably due to its smaller pixel size. The available data pairs are reduced to half and about one-third for CF ≤ 0.3 and CF ≤ 0.2, respectively, while, compared to larger CF thresholds, the correlation coefficient is improved to 0.996 from about 0.86, the slope value is very close to unity (∼ 0.98) and the mean satellite underestimation is reduced to about half (from ∼ 7 to ∼ 3.5 × 10 15 molecules cm −2 ). On the other hand, the distance criterion affects mostly GOME-2B data selection, because GOME-2B pixels are quite evenly distributed among the different radii used in the sensitivity test. More specifically, the number of collocations is notably reduced when stricter radius limits are applied, the r value is improved from 0.795 (d ≤ 50 km) to 0.953 (d ≤ 20 km), and the absolute mean bias decreases about 6 times for d ≤ 30 km compared to the reference case (d ≤ 50 km).

show abstract

“…The maximum swath is about 1920 km, providing almost global coverage of the sunlit part of the atmosphere within 1 day. The reader is kindly referred to Munro et al (2016) for a full description of the instrument design, calibration, and L1 processing and to Hassinen et al (2016) for a description of the full suite of GOME-2 L2 operational products. In this study, two different TOC products from GOME-2/MetOp-A (GOME-2A) were used for the validation of IASI TOCs from FORLI: (1) GOME-2 TOC data that have been generated as part of the EU-METSAT Ozone Monitoring and Atmospheric Composition Satellite Application Facility (O3M SAF) with the GOME Data Processor (GDP) operational algorithm, which is an iterative differential optical absorption spectroscopy (DOAS) air-mass factor fitting algorithm and uses the ozone absorption features in Huggins band between 325 and 335 nm Hao et al, 2014); and (2) GOME-2 TOC data generated as part of the ESA Ozone Climate Change Initiative (O3-CCI) with the GOME-type Direct Fitting (GODFIT) algorithm Lerot et al, 2014) and publicly available at http://www.esa-ozone-cci.org.…”

Section: Comparison With Gome-2 Retrievalsmentioning

confidence: 99%

Seven years of IASI ozone retrievals from FORLI: validation with independent total column and vertical profile measurements

et al. 2016

Self Cite

View full text Add to dashboard Cite

Ozone Monitoring Experiment-2 (GOME-2) launched on board MetOp-A and Brewer-Dobson data show that, on average, IASI overestimates the ultraviolet (UV) data by 5-6 % with the largest differences found in the southern high latitudes. The comparison with UV-visible SAOZ (Système d'Analyse par Observation Zénithale) measurements shows a mean bias between IASI and SAOZ TOCs of 2-4 % in the midlatitudes and tropics and 7 % at the polar circle. Part of the discrepancies found at high latitudes can be attributed to the limited information content in the observations due to low brightness temperatures. The comparison with ozonesonde vertical profiles (limited to 30 km) shows that on average IASI with FORLI processing underestimates O 3 by ∼ 5-15 % in the troposphere while it overestimates O 3 by ∼ 10-40 % in the stratosphere, depending on the latitude. The largest relative differences are found in the tropPublished by Copernicus Publications on behalf of the European Geosciences Union. 4328A. Boynard et al.: Seven years of IASI ozone retrievals from FORLI ical tropopause region; this can be explained by the low O 3 amounts leading to large relative errors. In this study, we also evaluate an updated version of FORLI-O3 retrieval software (v20151001), using look-up tables recalculated to cover a larger spectral range using the latest HITRAN spectroscopic database (HITRAN 2012) and implementing numerical corrections. The assessment of the new O 3 product with the same set of observations as that used for the validation exercise shows a correction of ∼ 4 % for the TOC positive bias when compared to the UV ground-based and satellite observations, bringing the overall global comparison to ∼ 1-2 % on average. This improvement is mainly associated with a decrease in the retrieved O 3 concentration in the middle stratosphere (above 30 hPa/25 km) as shown by the comparison with ozonesonde data.

show abstract

Overview of the O3M SAF GOME-2 operational atmospheric composition and UV radiation data products and data availability

Cited by 57 publications

References 65 publications

Comparisons of ground-based tropospheric NO<sub>2</sub> MAX-DOAS measurements to satellite observations with the aid of an air quality model over the Thessaloniki area, Greece

Comparisons of ground-based tropospheric NO<sub>2</sub> MAX-DOAS measurements to satellite observations with the aid of an air quality model over the Thessaloniki area, Greece

MAX-DOAS NO<sub>2</sub> observations over Guangzhou, China; ground-based and satellite comparisons

Seven years of IASI ozone retrievals from FORLI: validation with independent total column and vertical profile measurements

Contact Info

Product

Resources

About

Overview of the O3M SAF GOME-2 operational atmospheric composition and UV radiation data products and data availability

Cited by 57 publications

References 65 publications

Comparisons of ground-based tropospheric NO&lt;sub&gt;2&lt;/sub&gt; MAX-DOAS measurements to satellite observations with the aid of an air quality model over the Thessaloniki area, Greece

Comparisons of ground-based tropospheric NO&lt;sub&gt;2&lt;/sub&gt; MAX-DOAS measurements to satellite observations with the aid of an air quality model over the Thessaloniki area, Greece

MAX-DOAS NO&lt;sub&gt;2&lt;/sub&gt; observations over Guangzhou, China; ground-based and satellite comparisons

Seven years of IASI ozone retrievals from FORLI: validation with independent total column and vertical profile measurements

Contact Info

Product

Resources

About

Comparisons of ground-based tropospheric NO<sub>2</sub> MAX-DOAS measurements to satellite observations with the aid of an air quality model over the Thessaloniki area, Greece

Comparisons of ground-based tropospheric NO<sub>2</sub> MAX-DOAS measurements to satellite observations with the aid of an air quality model over the Thessaloniki area, Greece

MAX-DOAS NO<sub>2</sub> observations over Guangzhou, China; ground-based and satellite comparisons