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NASA’s Webb Opens New Window on Supernova Science


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NASA’s Webb Opens New Window on Supernova Science

Webb Space telescope deep field image showing hundreds of objects of different colors, shapes, and sizes scattered across the black background of space.
The JADES Deep Field uses observations taken by NASA’s James Webb Space Telescope (JWST) as part of the JADES (JWST Advanced Deep Extragalactic Survey) program. A team of astronomers studying JADES data identified about 80 objects that changed in brightness over time. Most of these objects, known as transients, are the result of exploding stars or supernovae. See annotated image below.

Peering deeply into the cosmos, NASA’s James Webb Space Telescope is giving scientists their first detailed glimpse of supernovae from a time when our universe was just a small fraction of its current age. A team using Webb data has identified 10 times more supernovae in the early universe than were previously known. A few of the newfound exploding stars are the most distant examples of their type, including those used to measure the universe’s expansion rate.

“Webb is a supernova discovery machine,” said Christa DeCoursey, a third-year graduate student at the Steward Observatory and the University of Arizona in Tucson. “The sheer number of detections plus the great distances to these supernovae are the two most exciting outcomes from our survey.”

DeCoursey presented these findings in a press conference at the 244th meeting of the American Astronomical Society in Madison, Wisconsin.

Image A: Jades Deep Field Annotated

Space telescope image showing hundreds of objects of different colors, shapes, and sizes scattered across the black background of space, with about 80 of the objects circled in green.
The JADES Deep Field uses observations taken by NASA’s James Webb Space Telescope (JWST) as part of the JADES (JWST Advanced Deep Extragalactic Survey) program. A team of astronomers studying JADES data identified about 80 objects (circled in green) that changed in brightness over time. Most of these objects, known as transients, are the result of exploding stars or supernovae.

Prior to this survey, only a handful of supernovae had been found above a redshift of 2, which corresponds to when the universe was only 3.3 billion years old — just 25% of its current age. The JADES sample contains many supernovae that exploded even further in the past, when the universe was less than 2 billion years old. It includes the farthest one ever spectroscopically confirmed, at a redshift of 3.6. Its progenitor star exploded when the universe was only 1.8 billion years old.

‘A Supernova Discovery Machine’

To make these discoveries, the team analyzed imaging data obtained as part of the JWST Advanced Deep Extragalactic Survey (JADES) program. Webb is ideal for finding extremely distant supernovae because their light is stretched into longer wavelengths — a phenomenon known as cosmological redshift.

Prior to Webb’s launch, only a handful of supernovae had been found above a redshift of 2, which corresponds to when the universe was only 3.3 billion years old — just 25% of its current age. The JADES sample contains many supernovae that exploded even further in the past, when the universe was less than 2 billion years old.

Previously, researchers used NASA’s Hubble Space Telescope to view supernovae from when the universe was in the “young adult” stage. With JADES, scientists are seeing supernovae when the universe was in its “teens” or “pre-teens.” In the future, they hope to look back to the “toddler” or “infant” phase of the universe.

To discover the supernovae, the team compared multiple images taken up to one year apart and looked for sources that disappeared or appeared in those images. These objects that vary in observed brightness over time are called transients, and supernovae are a type of transient. In all, the JADES Transient Survey Sample team uncovered about 80 supernovae in a patch of sky only about the thickness of a grain of rice held at arm’s length.

“This is really our first sample of what the high-redshift universe looks like for transient science,” said teammate Justin Pierel, a NASA Einstein Fellow at the Space Telescope Science Institute (STScI) in Baltimore, Maryland. “We are trying to identify whether distant supernovae are fundamentally different from or very much like what we see in the nearby universe.”

Pierel and other STScI researchers provided expert analysis to determine which transients were actually supernovae and which were not, because often they looked very similar.

The team identified a number of high-redshift supernovae, including the farthest one ever spectroscopically confirmed, at a redshift of 3.6. Its progenitor star exploded when the universe was only 1.8 billion years old. It is a so-called core-collapse supernova, an explosion of a massive star. 

Image B: Jades Deep Field Transients (NIRCam)

Six space telescope images show close-ups of two different observations (rows) of three different galaxies (columns). Of note arrows point to the bright blobs that are visible in one observation of the galaxy, but not the other.
This mosaic displays three of about 80 transients, or objects of changing brightness, identified in data from the JADES (JWST Advanced Deep Extragalactic Survey) program. Most of the transients are the result of exploding stars or supernovae. By comparing images taken in 2022 and 2023, astronomers could locate supernovae that recently exploded (like the examples shown in the first two columns), or supernovae that had already exploded and whose light was fading away (third column).

The age of each supernova can be determined from its redshift (designated by ‘z’). The light of the most distant supernova, at a redshift of 3.8, originated when the universe was only 1.7 billion years old. A redshift of 2.845 corresponds to a time 2.3 billion years after the big bang. The closest example, at a redshift of 0.655, shows light that left its galaxy about 6 billion years ago, when the universe was just over half its current age.

Uncovering Distant Type Ia Supernovae

Of particular interest to astrophysicists are Type Ia supernovae. These exploding stars are so predictably bright that they are used to measure far-off cosmic distances and help scientists to calculate the universe’s expansion rate. The team identified at least one Type Ia supernova at a redshift of 2.9. The light from this explosion began traveling to us 11.5 billion years ago when the universe was just 2.3 billion years old. The previous distance record for a spectroscopically confirmed Type Ia supernova was a redshift of 1.95, when the universe was 3.4 billion years old.

Scientists are eager to analyze Type Ia supernovae at high redshifts to see if they all have the same intrinsic brightness, regardless of distance. This is critically important, because if their brightness varies with redshift, they would not be reliable markers for measuring the expansion rate of the universe.

Pierel analyzed this Type Ia supernova found at redshift 2.9 to determine if its intrinsic brightness was different than expected. While this is just the first such object, the results indicate no evidence that Type Ia brightness changes with redshift. More data is needed, but for now, Type Ia supernova-based theories about the universe’s expansion rate and its ultimate fate remain intact. Pierel also presented his findings at the 244th meeting of the American Astronomical Society.

Looking Toward the Future

The early universe was a very different place with extreme environments. Scientists expect to see ancient supernovae that come from stars that contain far fewer heavy chemical elements than stars like our Sun. Comparing these supernovae with those in the local universe will help astrophysicists understand star formation and supernova explosion mechanisms at these early times.

“We’re essentially opening a new window on the transient universe,” said STScI Fellow Matthew Siebert, who is leading the spectroscopic analysis of the JADES supernovae. “Historically, whenever we’ve done that, we’ve found extremely exciting things — things that we didn’t expect.”

“Because Webb is so sensitive, it’s finding supernovae and other transients almost everywhere it’s pointed,” said JADES team member Eiichi Egami, a research professor at the University of Arizona in Tucson. “This is the first significant step toward more extensive surveys of supernovae with Webb.”

The James Webb Space Telescope is the world’s premier space science observatory. Webb is solving mysteries in our solar system, looking beyond to distant worlds around other stars, and probing the mysterious structures and origins of our universe and our place in it. Webb is an international program led by NASA with its partners, ESA (European Space Agency) and CSA (Canadian Space Agency). 

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Media Contacts

Laura Betzlaura.e.betz@nasa.gov, Rob Gutrorob.gutro@nasa.gov
NASA’s Goddard Space Flight Center, Greenbelt, Md.

Ann Jenkinsjenkins@stsci.edu / Christine Pulliamcpulliam@stsci.edu
Space Telescope Science Institute, Baltimore, Md.

Animation: Type 1a Supernovae Animations

Infographic: Massive Stars: Engines of Creation

Articles: Explore Other Supernova Articles

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Webb Mission Page

What is a supernova?

What is the Webb Telescope?

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      Brad Fisher [SSAI] presented a poster on the Joint OMI–Moderate Resolution Imaging Spectroradiometer (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.
      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 Joint Polar Satellite System (JPSS) missions, which currently include the joint 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 European 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.
      Figure 4. OMI nitrogen dioxide (NO2) time series bridging the first GOME mission (which flew on the European 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 Measurements of Pollution in the Troposphere (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.
      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 Geostationary Environmental Monitoring Spectrometer (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 PANDORA Global Network over Asia and aircraft measurements from the ASIA–AQ field campaign.
      Liu discussed NASA’s Tropospheric Emission Monitoring of Pollution (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 AGES+ website.
      Ben Veihelmann [ESA’s European Space Research and Technology Center—PI] explained that ESA’s Copernicus Sentinel-4 mission will be the final member of the GEO AC constellation. Veefkind summarized the Sentinel-4 mission, which is expected to launch on the Meteosat Third Generation (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 Africa. Sentinel-4 will deploy the first operational UV-Vis-NIR (UVN) imaging spectrometer 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 European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) will operate Sentinel-4, and the Deutsches Zentrum für Luft- und Raumfahrt (DLR) or German 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.) Sentinel-5 (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 Global Ozone Monitoring Experiment (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 Africa and advocated for the new geostationary measurements.
      Synergy with Other Current or Upcoming Missions
      Attendees discussed the synergy between upcoming AC, GHG, and ocean color 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 Twin Anthropogenic Greenhouse Gas Observers (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) Global Observing SATellite for greenhouse gases and water cycle (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—Geostationary Extended Operations (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 BAE Systems, which acquired Ball Aerospace and Technology, and will also build the GeoXO ocean color spectrometer (OCX).
      Andrew Sayer [UMBC] described NASA’s Plankton, Aerosols, Clouds, and ocean Ecosystem (PACE), which launched on February 8, 2024. The PACE payload includes a high-spatial resolution [~1 km (~0.6 mi) at nadir] Ocean Color Instrument (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 joint crossover session with NASA’s Health and Air Quality Applied Sciences Team (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 disease 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 TROPOMI CH4 web site 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., GHGSat 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.
      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 MethaneSAT 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 (PM2.5) nitrate sensitivity regime. Jacob emphasized the challenges related to satellite NO2 retrievals (e.g., accounting for a free-tropospheric NO2 background and aerosols).
      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 (NOx). 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 Visible Infrared Imaging Radiometer Suite (VIIRS) ocean color 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 Ozone Mapping and Profiling Suite Nadir Mapper (OMPS-NM) on joint NOAA–NASA Suomi-National Polar-orbiting Partnership (Suomi NPP) satellite with the possibility to continue afternoon measurements using similar OMPS-NM instruments on the four Joint Polar Satellite System 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 Africa. She also advocated for additional geostationary AQ measurements over Africa.
      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 GReenhouse gas And Air Pollutants Emissions System (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, NOx emissions adjust faster and tend to perform better at the urban scale. Adrian Jost [Max Planck Institute for Chemistry] described the ESA-funded World Emission 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 NASA SO2 emissions catalogue.
      Ivar van der Velde [SRON] presented a method to evaluate fire 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 Dix [University of Colorado, Boulder, Cooperative Institute for Research in Environmental Sciences] derived NOx 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. Dix 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 (AGES+ ), including NOAA CSL Atmospheric Emissions and Reactions observed from Megacities to Marine Aeras (AEROMMA) and NASA’s Synergistic TEMPO Air Quality Science (STAQS) 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 “Celebrating Ten Years of OMI Observations,” 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 American 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: 
      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. 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. 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. 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 remains 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
      Nickolay.a.krotkov@nasa.gov
      Pieternel Levelt
      National Center for Atmospheric Research, Atmospheric Chemistry Observations & Modeling
      levelt@ucar.edu
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