[NASA] Summary of the Second OMI–TROPOMI Science Team Meeting

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22 min read

Summary of the Second OMI–TROPOMI Science Team Meeting

Introduction

The second ******

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(OMI)–

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(TROPOMI) Science Team (ST) meeting was held June 3–6, 2024. The meeting used a hybrid format, with the in-person meeting hosted at the National Center for Atmospheric Research (NCAR) in Boulder, CO. This was the first OMI meeting to offer virtual participation since the COVID-19 travel restrictions. Combining the onsite and virtual attendees, the meeting drew 125 participants – see Photo.

OMI flies on NASA’s

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platform, launched July 15, 2004. TROPOMI flies on the ********* Space Agency’s (ESA)–

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platform. OMI has collected nearly 20 years of data and TROPOMI now has amassed 5 years of data. 

Meeting content was organized around the following four objectives:

• discussion of the final reprocessing of OMI data (called Collection 4) and of data preservation;
• discussion of OMI data continuity and enhancements using TROPOMI measurements;
• development of unique TROPOMI products [e.g., methane (CH₄)], applications (e.g., tracking emissions – and using them as indicators of socioeconomic and military activities), and new focus regions (e.g., *******); and
• leverage synergies between atmospheric composition (AC) and greenhouse gas (GHG) missions, which form the international constellation of low Earth orbit (LEO) and geostationary orbit (GEO) satellites.

The remainder of this article summarizes the highlights from each day of the meeting.

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Photo. Group photo of the in-person participants at the OMI–TROPOMI Science Team meeting.

Photo credit: Shaun Bush/NCAR’s Atmospheric Chemistry Observations & Modeling

DAY ONE

The topics covered on the first day of the meeting included OMI instrument performance, calibration, final Collection 4 reprocessing, and plans for data preservation.

OMI and Data Products Update

Pieternel Levelt [Royal Netherlands Meteorological Institute (KNMI)—OMI Principal Investigator (PI) and NCAR’s Atmospheric Chemistry Observations & Modeling (ACOM) Laboratory—Director] began her presentation by dedicating the meeting to the memory of Johan de Vries, whose untimely ****** came as a shock to the OMI and TROPOMI teams – see In Memoriam: Johan de Vries for a celebration of his accomplishments and contributions to the OMI-TROPOMI team. She then went on to give a status update on OMI, which is one of two currently operating instruments on EOS Aura [the other being the 

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 (MLS)]. OMI is the longest operating and stable ultraviolet–visible (UV-VIS) spectrometer. It continues to “age gracefully” thanks to its design, contamination control measures undertaken after the launch, and stable optical bench temperature. Lessons learned during integration of OMI on the Aura spacecraft (e.g., provide additional charged couple device shielding) and operations (i.e., monitor partial Earth-view port blockages) guided the development and operations of the follow-on TROPOMI mission.

Continued monitoring of OMI performance is crucial for extending science- and trend-quality OMI records to the end of the Aura mission (currently expected in 2026). Antje Ludewig [KNMI] described the new OMI Level-1B (L1B) processor (Collection 4), which is based on TROPOMI data flow and optimized calibrations. The processor has been transferred to the U.S. OMI ST, led by Joanna Joiner [NASA’s Goddard Space Flight Center (GSFC)]. Matthew Bandel [Science Systems and Applications, Inc. (SSAI)] described NASA’s new OMI monitoring tools.

Sergey Marchenko [SSAI] discussed OMI daily spectral solar irradiance (SSI) data, which are used for monitoring solar activity and can be compared with the dedicated

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(TSIS-1) on the International Space Station. Continuation of OMI measurements will allow comparisons with the upcoming NASA

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mission. Antje Inness [********* Centre for Medium-range Weather Forecasts (ECMWF)] described operational assimilation of OMI and TROPOMI near-real time data into the *********

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CAMS) daily analysis/forecast and re-analysis – see Figure 1.

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In Memoriam: Johan de Vries

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Johan de Vries
June 10, 1956 – May 8, 2024

Johan de Vries [Airbus Netherlands—Senior Specialist Remote Sensing] passed away suddenly on May 8, 2024, after a distinguished career. As a member of the

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 (OMI)–

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 (TROPOMI) program, Johan conceptualized the idea of using a two-dimensional (2D) charged couple detector (CCD) for the OMI imaging spectrometer. This “push-broom” design led to high-spatial resolution spectra combined with high-spatial resolution and daily global coverage capability. His pioneering design for OMI has now been repeated on several other U.S. and international atmospheric composition measuring instruments – in both low and geostationary orbits – that are either in orbit or planned for launch soon. This achievement ensures that Johan’s legacy will live on for many years to come as these push-broom Earth observing spectrometers result in unprecedented data for environmental research and applications. The OMI and TROPOMI teams express their deepest condolences to de Vries family and colleagues over this loss. 

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Figure 1. An example of TROPOMI pixel nitrogen dioxide (NO₂) observations over Europe on September 8, 2018 [top] and the corresponding super observations [bottom] for a model grid of 0.5 x 0.5^o. Cloudy locations are ******** grey. TROPOMI super observations are tested for use in the ********* Centre for Medium Range Weather Forecasting (ECMWF) Copernicus Atmosphere Monitoring Service (CAMS) data assimilation framework and will also be used for combined OMI–TROPOMI gridded datasets.

Figure credit: reprinted from a 2024 paper posted on EGUSphere.

Updates on OMI and TROPOMI Level-2 Data Products

The U.S. and Netherlands OMI STs continue to collaborate closely on reprocessing and improving OMI and TROPOMI L2 science products. During the meeting, one or more presenters reported on each product, which are described in the paragraphs that follow.

Serena Di ***** [KNMI] discussed the latest algorithm updates to the Collection 4 OMI Total Column Ozone (O₃) product, which is derived using differential absorption spectroscopy (DOAS). She compared results from the new algorithm with the previous Collection 3 and with both the TROPOMI and OMI NASA O₃ total column (Collection 3) algorithms. Collection 4 improved on previous versions by reducing the retrieval fit error and the along-track stripes of the product.

Juseon “Sunny” Bak and Xiong Liu [both from Smithsonian Astrophysical Observatory (SAO)] gave updates on the status of the Collection 4 O₃ profile products.

Lok Lamsal [GSFC/University of Maryland, Baltimore County (UMBC)] and Henk Eskes [KNMI] compared Collection 3 and Collection 4 of the nitrogen dioxide (NO₂) products.  

Zolal Ayzpour [SAO] discussed the status of the OMI Collection 4 formaldehyde (HCHO) product.

Hyeong-Ahn Kwon [SAO] presented a poster that updated the Glyoxal product.

Omar Torres [GSFC] and Changwoo Ahn [GSFC/SSAI] presented regional trend analyses using the re-processed OMI Collection 4 absorbing aerosol product – see Figure 2.

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Figure 2. Reprocessed OMI records (from Collection 4) of monthly average aerosol optical depth (AOD) at 388 nm derived from the OMI aerosol algorithm (OMAERUV) over Western North America (WNA): 30°N–50°N, 110°W–128°W) [top] and over Eastern China (EC): 25°N–43°N, 112°E–124°E) [bottom]. A repeatable annual cycle over WNA occurred with autumn minimum at around 0.1 and a spring maximum in the vicinity of 0.4 during the 2005–2016 *******. After 2017 much larger AOD maxima in the late summer are associated with wildfire smoke occurrence. Over EC (bottom) the 2005–2014 AOD record depicts a large spring maxima (0.7 and larger) due to long-range transport of dust and secondary pollution aerosols followed by late autumn minima (around 0.3). A significant AOD decrease is observed starting in 2015 with reduced minimum and maximum values to about 0.2 and 0.5 respectively. The drastic change in AOD load over this region is associated with pollution control measures enacted over the last decade.

Figure credit: Changwoo Ahn/GSFC/SSAI and Omar Torres/GSFC

Updates on EOS Synergy Products

Several presenters and posters during the meeting gave updates on EOS synergy products, where OMI data are combined with data from another instrument on one of the EOS flagships. These are described below.

Brad Fisher [SSAI] presented a poster on the ****** OMI–

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 (MODIS) cloud products.

Wenhan Qin [GSFC/SSAI] presented a poster on the MODIS–OMI Geometry Dependent Lambertian Equivalent Surface Reflectivity (GLER) product.

Jerry Ziemke [GSFC and Morgan State University (MSU)] presented on the OMI–MLS Tropospheric Ozone product that showed post-COVID tropospheric O₃ levels measured using this product, which are consistent with similar measurements obtained using other satellite O₃ data – see Figure 3.

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Figure 3. Anomaly maps of merged tropospheric column O₃ (TCO) satellite data (Dobson Units) for spring–summer 2020–2023. In this context, an anomaly is defined as deseasonalized O₃ data. The anomaly maps are derived by first calculating seasonal climatology maps for 2016–2019 (i.e., pre-COVID pandemic) and then subtracting these climatology maps from the entire data record. 
Note: The sensors used in this analysis include: the Ozone Mapping and Profiler Suite (OMPS)/ Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) and Cross-track Infrared Sounder (CrIS) on the ****** Polar Satellite System (JPSS) missions, which currently include the ****** NASA–NOAA Suomi National Polar-orbiting Partnership (Suomi NPP), NOAA-20, and NOAA-21; the Earth Polychromatic Imaging Camera (EPIC)/MERRA-2 on the Deep Space Climate Observatory (DSCOVR); the Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS), both on EOS Aura; the Infrared Atmospheric Sounding Interferometer (IASI)/ Fast Optimal Retrievals on Layers (FORLI), IASI/SOftware for Fast Retrievals of IASI Data (SOFRID), and IASI/Global Ozone Monitoring Experiment–2 (GOME2). IASI flies on the ********* MetOp-A, -B, and -C missions. The OMPS/MERRA-2 and EPIC/MERRA-2 products subtract coincident MERRA-2 stratospheric column O₃ from total O₃ to derive tropospheric column O₃.

Figure credit: Jerry Ziemke/GSFC and Morgan State University (MSU) 

Updates on Multisatellite Climate Data Records

The OMI ST also discussed refining and analyzing multisatellite climate data records (CDRs) that have been processed with consistent algorithms. Several presenters reported on this work, who are mentioned below.

Jenny Stavrakou [Koninklijk Belgisch Instituut voor Ruimte-Aeronomie, Royal Belgian Institute for Space Aeronomy (BIRA–IASB)], reported on work focusing on the OMI and TROPOMI HCHO CDR and Huan Yu [BIRA–IASB)] reported harmonized OMI and TROPOMI cloud height datasets based on improved O₂-O₂ absorption retrieval algorithm.

Lok Lamsal [GSFC/UMBC, Goddard Earth Sciences Technology and Research (GESTAR) II], Henk Eskes, and Pepijn Veefkind [KNMI] reported on the OMI and TROPOMI NO₂ CDRs – see Figure 4. 

Si-Wan Kim [Yonsei University, South Korea] reported on OMI and TROPOMI long-term NO₂ trends.

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Figure 4. OMI nitrogen dioxide (NO₂) time series bridging the first GOME mission (which flew on the ********* Remote Sensing Satellite–2 (ERS–2) from 1995–2011 with limited coverage after 2003) and measurements from the two currently operating missions – OMI (2004–present) and TROPOMI (2017–present) – offer consistent climate data records that allow for studying long-term changes. This example shows tropospheric NO₂ column time series from three instruments over Phoenix, AZ. The overlap between the OMI and TROPOMI missions allows for intercomparison between the two, which is crucial to avoid continuity-gaps in multi-instrument time series. The ERS-2 (GOME) had a morning equator crossing time (10:30 AM), while Aura (OMI) and Metop (TROPOMI) have afternoon equator crossing times of 1:45 PM and 1:30 PM respectively.

Figure credit: Lok Lamsal/GSFC/University of Maryland, Baltimore County (UMBC)

Update on Aura’s Drifting Orbit

Bryan Duncan [GSFC—Aura Project Scientist] closed out the first day with a presentation summarizing predictions of Aura’s drifting orbit. Overall, the impact of Aura’s drift is expected to be minor, and the OMI and MLS teams will be able to maintain science quality data for most data products. He thanked the OMI/TROPOMI ST and user community for expressing their strong support for continuing Aura observations until the end of the Aura mission in mid–2026.

DAY TWO

The second day of the meeting focused on current and upcoming LEO and GEO Atmospheric Composition (AC) missions.

TROPOMI Mission and Data Product Updates

Veefkind presented an update on the TROPOMI mission, which provides continuation and enhancements for all OMI products. Tobias Borssdorf [Stichting Ruimte Onderzoek Nederland (SRON), or Netherlands Institute for Space Research] explained how TROPOMI, with its innovative shortwave infrared (SWIR) spectrometer, measures CH₄ and carbon monoxide (CO). This approach continues measurements that began by the 

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 (MOPITT) instrument on Terra.

Hiren Jethva [NASA Airborne Science Program] and Torres presented new TROPOMI near-UV aerosol products, including a new aerosol layer optical centroid height product, which takes advantage of the TROPOMI extended spectral range – see Figure 5.

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Figure 5. Global gridded (0.10° x 0.10°) composite map of aerosol layer optical centroid height (AH) retrieved from TROPOMI O₂-B band observations from May–September 2023.

Figure credit: Hiren Jethva/NASA Airborne Science Program

GEMS–TEMPO–Sentinel-4 (UVN): A Geostationary Air Quality Constellation

TROPOMI global observations serve as a de facto calibration standard used to homogenize a new constellation of three missions that will provide AC observations for most of the Northern Hemisphere from GEO. Two of the three constellation members are already in orbit. Jhoon Kim [Yonsei University—PI] discussed the 

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 (GEMS), launched on February 19, 2020 aboard the Republic of Korea’s GEO-KOMPSAT-2B satellite. It is making GEO AC measurements over Asia. The GEMS team is working on validating measurements of NO₂ diurnal variations using ground-based measurements from the

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 over Asia and aircraft measurements from the ASIA–AQ field campaign.

Liu discussed NASA’s 

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 (TEMPO) spectrometer, launched on April 7, 2023, aboard a commercial INTELSAT 40E satellite. From its GEO vantage point, TEMPO can observe the Continental U.S., Southern Canada, Mexico, and the coastal waters of the Northwestern Atlantic and Northeastern Pacific oceans.

Gonzales Abad [SAO] presented the first measurements from TEMPO. He explained that TEMPO’s design is similar to GEMS, but GEMS includes an additional visible and near infrared (VNIR) spectral channel (540–740 nm) to measure tropospheric O₃, O₂, and water vapor (H₂Ov). TEMPO can perform optimized morning scans, twilight scans, and scans with high temporal resolution (5–10 minutes) over selected regions. Abad reported that the TEMPO team released L1B spectra and the first provisional public L2 products (Version 3), including NO₂, HCHO, and total column O₃. Andrew Rollins [National Oceanic and Atmospheric Administration’s (NOAA) Chemical Sciences Laboratory (CSL)] reported that the TEMPO team is working on validation of provisional data using both ground-based data from PANDORA spectrometers and data collected during several different airborne campaigns completed during the summer of 2023 and compiled on the 

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.

Ben Veihelmann [ESA’s ********* Space Research and Technology Center—PI] explained that ESA’s Copernicus 

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 mission will be the final member of the GEO AC constellation. Veefkind summarized the Sentinel-4 mission, which is expected to launch on the 

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 (MTG)-Sounder 1 (MTG-S1) platform in 2025. The mission is dedicated to measuring air quality and O₃ over Europe and parts of the Atlantic and North *******. Sentinel-4 will deploy the first operational 

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 on a geostationary satellite. (Airbus will build UVN, with ESA providing guidance.) Sentinel-4 includes two instruments launched in sequence on MTG-S1 and MTG-S2 platforms designed to have a combined lifetime of 15 years. The mission by the 

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 (EUMETSAT) will operate Sentinel-4, and the 

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 (DLR) or ******* Aerospace Center will be responsible for operational L2 processing.

These three GEO AC missions, along with the upcoming ESA/EUMETSAT/Copernicus LEO (morning orbit, 9:30 a.m.) 

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 (S5) mission, will complete a LEO–GEO satellite constellation that will enable monitoring of the most industrialized and polluted regions in the Northern Hemisphere into the 2030s. Sentinel-5 will not continue the OMI–TROPOMI data record in the early afternoon; however, it will be placed in the morning orbit and follow ESA’s 

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 (GOME) and EUMETSAT GOME-2 missions. By contrast, GEO AC observations over the Southern Hemisphere are currently not available. Several presenters described ongoing projects for capacity building for LEO satellite air quality data uptake and emission monitoring in ******* and advocated for the new geostationary measurements.

Synergy with Other Current or Upcoming Missions

Attendees discussed the synergy between upcoming AC, GHG, and ocean ****** missions. Current trends in satellite AC measurements are toward increased spatial resolution and combined observations of short-lived reactive trace gases – which are important for air quality (AQ) monitoring – and long-lived GHG – which are important for climate monitoring and carbon cycle assessments. Some trace gases (e.g., O₃ and CH₄) are both polluters and GHG agents. Others [e.g., NO₂ and sulfur dioxide (SO₂ )] are aerosol [particulate matter (PM)] and O₃ precursors and are used as proxies and spatial indicators for anthropogenic CO₂ and CH₄ emissions.

Yasjka Meijer [ESA—Copernicus Anthropogenic Carbon Dioxide Monitoring (CO₂M) Mission Scientist]) reviewed the plans for CO₂M, which includes high-resolution measurements [~4 km² (~1.5 mi²)] of CO₂ , CH₄ , and NO₂.

Jochen Landgraf [SRON] described ESA’s new 

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 (TANGO) mission, which has the objective to measure CO₂ , CH₄ , and NO₂ at even higher spatial resolution [~300 m (~984 ft)] using two small CubeSat spectrometers flying in formation.

Hiroshi Tanimoto [National Institute for Environmental Studies, Japan] described the Japan Aerospace Exploration Agency’s (JAXA) 

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 (GOSAT-GW) mission, which includes the Total Anthropogenic and Natural Emission mapping SpectrOmeter (TANSO-3) spectrometer to simultaneously measure CO₂ , CH₄, and NO₂ with ~1–3 km (~0.6–1.8 mi) spatial resolution in focus mode. GOSAT-GW will also fly the Advanced Microwave Scanning Radiometer 3 (AMSR3).

Joanna Joiner [GSFC—

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 (GeoXO) Project Scientist and ACX Instrument Scientist] described the plans for the next-generation U.S. geosynchronous satellite constellation, which will consist of three satellites covering the full Earth disk: GEO-East, GEO-West, and GEO-Central. (By contrast, the current Geostationary Operational Environmental Satellite (GOES) series has two satellites: GOES–East and GOES–West.) GEO-Central will carry an advanced infrared sounder (GXS) for measuring vertical profiles of many trace gases, temperature and humidity, and a new UV-VIS spectrometer (ACX), which is a follow-on to TEMPO for AQ applications. Both GXS and ACX instruments will be built by 

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, which acquired Ball Aerospace and Technology, and will also build the GeoXO ocean ****** spectrometer (OCX).

Andrew Sayer [UMBC] described NASA’s 

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 (PACE), which launched on February 8, 2024. The PACE payload includes a high-spatial resolution [~1 km (~0.6 mi) at nadir] 

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 (OCI), which is a UV-Vis-NIR spectrometer with discrete SWIR bands presenting additional opportunities for synergistic observations with the AC constellation. Sayer presented OCI “first light” aerosol data processed using the unified retrieval algorithm developed by Lorraine Remer [UMBC].

The second day concluded with a ****** crossover session with 

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 (HAQAST) followed by a poster session. Several OMI–TROPOMI STM participants presented on a variety of topics that illustrate how OMI and TROPOMI data are being used to support numerous health and AQ applications. Duncan, who is also a member of HAQAST team, presented “20 years of health and air quality applications enabled by OMI data.” He highlighted OMI contributions to AQ and health applications, including NO₂ trend monitoring, inferring trends of co-emitted species [e.g., CO₂, CO, some Volatile Organic Compounds (VOCs)], validation of new satellite missions (e.g., TEMPO, PACE), and burden of ******** studies.

DAY THREE

Discussions on the third day focused on advanced retrieval algorithms, leading to new products and new applications for OMI and TROPOMI data. Several presentations described applications of TROPOMI CH₄ data and synergy with small satellites.

Advanced Retrieval Algorithms and New Data Products

Ilse Aben [SRON] described TROPOMI global detection of CH₄ super-emitters using an automated system based on Machine Learning (ML) techniques – see Figure 6. Berend Schuit [SRON] provided additional detail on these methods. He introduced the

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to the meeting participants. He explained how TROPOMI global CH₄ measurements use “tip-and-cue” dedicated satellites with much higher spatial resolution instruments [e.g.,

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with ~25-m (~82-ft) resolution] to scan for individual sources and estimate emission rates. Most CH₄ super-emitters are related to urban areas and/or landfills, followed by plumes from gas and oil industries and coal mines.

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Figure 6. Methane plume map produced by SRON shows TROPOMI large CH₄ emission plumes for the week of the OMI–TROPOMI meeting (June 3–6, 2024).

Figure credit: Itse Aben/Stichting Ruimte Onderzoek Nederland (SRON)

Alba Lorente [Environmental Defense Fund—Methane Scientist] introduced a new

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satellite launched in March 2024, which aims to fill the gap in understanding CH₄ emissions on a regional scale [200 x 200 km² (~77 x 77 mi²)] from at least 80% of global oil and gas production, agriculture, and urban regions. Alex Bradley [University of Colorado, Boulder] described improvements to TROPOMI CH₄ retrievals that were achieved by correcting seasonal effects of changing surface albedo.

Daniel Jacob [Harvard University] presented several topics, including the highest resolution [~30 m (~98 ft)] NO₂ plume retrievals from Landsat-8 – see Figure 7 – and Sentinel-2 imagers. He also discussed using a ML technique trained with TROPOMI data to improve NO₂ retrievals from GEMS and modeling NO₂ diurnal cycle and emission estimates. He introduced the ratio of ammonia (NH₃) to NO₂ (NH₃/NO₂) as an indicator of particulate matter with diameters less than 2.5 µm (PM_2.5) nitrate sensitivity regime. Jacob emphasized the challenges related to satellite NO₂ retrievals (e.g., accounting for a free-tropospheric NO₂ background and aerosols).

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Figure 7. Landsat Optical Land Imager (OLI) image, obtained on October 17, 2021 over Saudi Arabia, shows power plant exhaust, which contains nitrogen dioxide (NO₂) drifting downwind from the sources (the two green circles are the stacks). The ultra-blue channel (430–450 nm) on OLI enables quantitative detection of NO₂ in plumes from large point sources at 30-m (~98-ft) resolution. This provides a unique ability for monitoring point-source emissions of oxides of nitrogen (NO_x). The two stacks in the image are separated by 2 km (~1.2 mi).

Figure credit: Daniel Jacob – repurposed from a 2024 publication in Proceedings of the National Academies of Sciences (PNAS)

Steffen Beirle [Max Planck Institute for Chemistry, Germany] explained his work to fit TROPOMI NO₂ column measurements to investigate nitric oxide (NO) to NO₂ processing in power plant plumes. Debra Griffin [Environment and Climate Change Canada (ECCC)] used TROPOMI NO₂ observations and ML random forest technique to estimate NO₂ surface concentrations. Sara Martinez-Alonso [NCAR] investigated geographical and seasonal variations in NO₂ diurnal cycle using GEMS and TEMPO data.  Ziemkecombined satellite O₃ data to confirm a persistent low anomaly (~5–15%) in tropospheric O₃ after 2020.  Jethva presented advanced OMI and TROPOMI absorbing aerosol products. Yu described improved OMI and TROPOMI cloud datasets using the O₂-O₂ absorption band at 477 nm. Nicholas Parazoo [Jet Propulsion Laboratory (JPL)] described TROPOMI Fraunhofer line retrievals of red solar-induced chlorophyll fluorescence (SIF) near O₂-B band (663–685 nm) to improve mapping of ocean primary productivity. Liyin He [Duke University] described using satellite terrestrial SIF data to study the effect of particulate pollution on ecosystem productivity.

New Applications

Zachary Fasnacht [SSAI] used OMI and TROPOMI spectra to train a neural network to gap-fill MODIS and 

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 (VIIRS) ocean ****** data under aerosol, sun glint, and partly cloudy conditions. This ML method can also be applied to PACE OCI spectra. Anu-Maija Sundström [Finnish Meteorological Institute (FMI)] used OMI and TROPOMI SO₂ and O₃ data as proxies to study new particle formation events. Lindsey Anderson [University of Colorado, Boulder] described how she used TROPOMI NO₂ and CO measurements to estimate the composition of wildfire emissions and their effect on forecasted air quality. Heesung Chong [SAO] applied OMI bromine oxide (BrO) retrievals to the NOAA operational 

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 Nadir Mapper (OMPS-NM) on ****** NOAA–NASA 

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 (Suomi NPP) satellite with the possibility to continue afternoon measurements using similar OMPS-NM instruments on the four 

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 missions (JPSS-1,-2,-3,-4) into the 2030s. (JPSS-1 and -2 are now in orbit and known as NOAA-20 and -21 respectively; JPSS-4 is planned for launch in 2027, with JPSS-3 currently targeted for 2032.)

Kim demonstrated the potential for using satellite NO₂ and SO₂ emissions as a window into socioeconomic issues that are not apparent by other methods. For example, she showed how OMI and TROPOMI data were widely used to monitor air quality improvements in the aftermath of COVID-19 lockdowns. (Brad Fisher [SSAI] presented a poster on a similar topic.)

Cathy Clerbaux [Center National d’Études Spatiale (CNES), or French Space Agency] showed how her team used TROPOMI NO₂ data to trace the signal emitted by ships and used this information to determine how the shipping lanes through the Suez Canal changed in response to unrest in the Middle East. Iolanda Ialongo [FMI] showed a similar drop of NO₂ emissions over Donetsk region due to the war in Ukraine. Levelt showed how OMI and TROPOMI NO₂ data are used for capacity-building projects and for air quality reporting in *******. She also advocated for additional geostationary AQ measurements over *******.

DAY FOUR

Discussions on the final day focused on various methods of assimilating satellite data into air quality models for emission inversions and aircraft TEMPO validation campaigns. The meeting ended with Levelt giving her unique perspective on the OMI mission, as she reflected on more than two decades being involved with the development, launch, operation, and maintenance of OMI.  

Assimilating Satellite Data into Models for Emissions

Brian McDonald [CSL] described advance chemical data assimilation of satellite data for emission inversions and the

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(GRA²PES). He showed examples of assimilations using TROPOMI and TEMPO NO₂ observations to adjust a priori emissions. He also showed that when TEMPO data are assimilated, NO_x emissions adjust faster and tend to perform better at the urban scale. Adrian Jost [Max Planck Institute for Chemistry] described the ESA-funded

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project to improve pollutant and GHG emission inventories using satellite data. He showed examples of TROPOMI SO₂ emissions from large-point sources and compared the data with bottom-up and

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.

Ivar van der Velde [SRON] presented a method to evaluate ***** emissions using new satellite imagery of burned area and TROPOMI CO. Helene Peiro [SRON] described her work to combine TROPOMI CO and burned area information to compare the impact of prescribed fires versus wildfires on air quality in the U.S. She concluded that prescribed burning reduces CO pollution. Barbara **** [University of Colorado, Boulder, Cooperative Institute for Research in Environmental Sciences] derived NO_x emissions from U.S. oil and natural gas production using TROPOMI NO₂ data and flux divergence method. She estimated TROPOMI CH₄ emissions from Denver–Julesburg oil and natural gas production. **** explained that the remaining challenge is to separate oil and gas emissions from other co-located CH₄ sources. Ben Gaubert [NCAR, Atmospheric Chemistry Observations and Modeling] described nonlinear and non-Gaussian ensemble assimilation of MOPITT CO using the data assimilation research testbed (DART).

Andrew (Drew) Rollings [CSL] presented first TEMPO validation results from airborne field campaigns in 2023 (

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 ), including NOAA CSL Atmospheric Emissions and Reactions observed from Megacities to Marine Aeras (

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) and NASA’s Synergistic TEMPO Air Quality Science (

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) campaigns.

A Reflection on Twenty Years of OMI Observations

Levelt gave a closing presentation in which she reflected on her first involvement with the OMI mission as a young scientist back in 1998. This led to a collaboration with the international ST to develop the instrument, which was included as part of Aura’s payload when it launched in July 2004. She reminisced about important highlights from 2 decades of OMI, e.g., the 10-year anniversary STM at KNMI in 2014 (see “

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,” The Earth Observer, May–Jun 2014, 26:3, 23–30), and the OMI ST receiving the NASA/U.S. Geological Survey Pecora award in 2018 and the ********* Meteorological Society’s Special award in 2021.

Levelt pointed out that in this combined OMI–TROPOMI meeting the movement towards using air pollution and GHG data together became apparent. She ended by saying that the OMI instrument continues to “age gracefully” and its legacy continues with the TROPOMI and LEO–GEO atmospheric composition constellation of satellites that were discussed during the meeting.

Conclusion

Overall, the second OMI–TROPOMI STM acknowledged OMI’s pioneering role and TROPOMI’s unique enhancements in measurements of atmospheric composition: 

1. Ozone Layer Monitoring: Over the past two decades, OMI has provided invaluable data on the concentration and distribution of O₃ in the Earth’s stratosphere. This data has been crucial for understanding and monitoring the recovery of the O₃ layer following international agreements, such as the Montreal Protocol.
2. Air Quality Assessment: OMI’s high-resolution measurements of air pollutants, such as NO₂, SO₂, and HCHO, have significantly advanced our understanding of air quality. This information has been vital for tracking pollution sources, studying their transport and transformation, and assessing their impact on human health and the environment.
3. Climate Research: The data collected by OMI has enhanced our knowledge of the interactions between atmospheric chemistry and climate change. These insights have been instrumental in refining climate models and improving our predictions of future climate scenarios.
4. Global Impact: The OMI instrument has provided near-daily global coverage of atmospheric data, which has been essential for scientists and policymakers worldwide. The comprehensive and reliable data from OMI has supported countless research projects and informed decisions aimed at protecting and improving our environment.

OMI ******** one of the most stable UV/Vis instruments over its two decades of science and trend quality data collection. The success of the OMI and TROPOMI instruments is a testament to the collaboration, expertise, and dedication of both teams.

Nickolay Krotkov
NASA’s Goddard Space Flight Center
*****@*****.tld

Pieternel Levelt
National Center for Atmospheric Research, Atmospheric Chemistry Observations & Modeling
*****@*****.tld

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Last Updated

Nov 12, 2024

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