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Summary of the Second OMI–TROPOMI Science Team Meeting


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Summary of the Second OMI–TROPOMI Science Team Meeting

Introduction

The second joint Ozone Monitoring Instrument (OMI)–TROPOspheric Monitoring Instrument (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 Earth Observing System (EOS) Aura platform, launched July 15, 2004. TROPOMI flies on the European Space Agency’s (ESA)–Copernicus Sentinel-5 Precursor 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., Africa); 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.

OMIT-TROPOMI Science Team Meeting Group Photo
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 death 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 Microwave Limb Sounder (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 Total and Spectral Solar Irradiance Sensor (TSIS-1) on the International Space Station. Continuation of OMI measurements will allow comparisons with the upcoming NASA TSIS-2 mission. Antje Inness [European Centre for Medium-range Weather Forecasts (ECMWF)] described operational assimilation of OMI and TROPOMI near-real time data into the European Copernicus Atmosphere Monitoring Service (CAMS) daily analysis/forecast and re-analysis – see Figure 1.

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In Memoriam: Johan de Vries

Johan de Vries In Memoriam Photo
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 Ozone Monitoring Instrument (OMI)–TROPOspheric Monitoring Instrument (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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OMI–TROPOMI Figure 1
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 0.5o. Cloudy locations are colored grey. TROPOMI super observations are tested for use in the European 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 Pede [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.

OMI–TROPOMI Figure 2
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 period. 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 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.

OMI–TROPOMI 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.

OMI–TROPOMI Figure 4
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 productsincluding a new aerosol layer optical centroid height product, which takes advantage of the TROPOMI extended spectral range – see Figure 5.

OMI–TROPOMI 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 NOdiurnal 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 O3Andrew 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 (SO)] 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 km(~1.5 mi2)] of CO, CH, and NO2.

Jochen Landgraf [SRON] described ESA’s new Twin Anthropogenic Greenhouse Gas Observers (TANGO) mission, which has the objective to measure CO, CH, 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 CO, 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.

OMI–TROPOMI Figure 6
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).

OMI–TROPOMI Figure 7
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 NOobservations 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 Odata 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 NOdata 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 NOdata 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: 

  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 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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      2024 Workshop Overview
      The most recent AEOIP workshop took place April 23–25, 2024, with a hybrid format. The in-person participants met in Ann Arbor, MI. The three-day event had a similar structure to its predecessors but with a wildland fire management theme. Altogether, 135 people participated in the workshop, with 77 attending in person and 58 virtually – see Photo 1.
      Photo 1. Participants at the 2024 AEOIP workshop. Photo credit: AEOIP Meeting Objectives
      The workshop objectives were to:
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      A large segment of this workshop was dedicated to four concurrent topical breakout sessions – referred to in this report as Breakout Sessions A–D. The topics covered in each breakout session are listed below, along with the name(s) of those who facilitated discussion.
      Breakout Session A: Fuels, Wildland Fire Emissions, Carbon & Climate – Andy Hudak [USFS] and Edil Sepulveda Carlo [NASA’s Goddard Space Flight Center (GSFC)/Science Systems and Applications Inc. (SSAI)]; Breakout Session B: Prescribed Fire Planning & Management – Nancy French [Michigan Tech Research Institute (MTRI)], Birgit Peterson [USGS], and Jessica Meisel [University of Idaho]; Breakout Session C: Fractional Vegetation Cover Products & Decision Making – Tim Assal and Jake Slyder [both U.S. Department of Interior, BLM], and Liz Hoy and Amanda Armstrong [both at GSFC]; and Alexis O’Callahan [University of Arkansas]. Breakout Session D: Post-fire Effects & Recovery: Assess, Predict, Remediate, and Monitor – Mary Ellen Miller [MTRI]. All of the breakout groups met on each day of the meeting. On the morning of the first day, the facilitators of each group gave brief “elevator pitches” about each breakout topic, and participants selected a topic for focus. After that, a block of time each day was dedicated to breakout activities and discussions. Participants were asked to focus on different aspects of the topic each day. In the afternoon of the first day, each group focused on identifying needs and challenges in the area being discussed – with a brief report-out at the end of the day. On the afternoon of the second day, the focus was on data availability and solutions – i.e., finding ways to overcome obstacles to making data more readily available to users – again with a brief report- out at the end of the day. On the morning of the third day, there were topical presentations. Each group worked to synthesize their three days of discussions and chose a representative to give a summary report during the closing plenary later that morning.
      Workshop Summary
      The remainder of this article presents highlights from each day of the workshop. This includes the most important presentations given during the meeting and those given during the breakout sessions. The report also includes highlights from training breakouts given on the second day of the workshop and a summary of a prescribed fire field trip, which took place the day before the workshop and visited two locations – see Optional “Field Trip” for AEOIP Workshop Participants to learn more.
      Optional “Field Trip” for AEOIP Workshop Participants
      On April 22, 2024, an optional field trip was offered that featured two sites demonstrating prescribed fire in Michigan. For the first stop on the trip, Kevin Butler [Washtenaw County—Natural Areas Preservation Program Stewardship Supervisor] gave a tour of a prescribed fire site in Park Lyndon, a county park in the northwest part of Washtenaw County, MI. The park is being restored to maintain native species using prescribed fire as invasive species control. The intent of these efforts is to restore oak meadows and preserve over 500 species of plants across fens, marshes, ponds, forest, and prairie lands.
      On the second leg of the trip, Tina Stephens [City of Ann Arbor—Volunteer and Outreach Coordinator] led a tour of Furstenberg Nature Area, in the city of Ann Arbor, MI. She highlighted the importance of prescribed burning to achieve ecological benefits. The 0.15-km2 (38-acre) park contains wetlands, woodlands, prairie, and oak savanna. Since the mid-1990’s, Natural Area Preservation staff and volunteers have maintained those ecosystems through controlled burns and invasive shrub removal. The second tour stop included a small prescribed fire demonstration – see Photo 2.
      Photo 2. Ann Arbor park staff conduct a prescribed fire demonstration for workshop participants during the Furstenberg Nature Area tour portion of the AEOIP field trip. Photo credit: Joseph Paki DAY ONE
      On the first day, Kira Sullivan-Wiley [Pew Institute] gave a plenary presentation, in which she discussed the value of coproduction, which in the context of AEOIP can be described as honoring the generative capacity of others as a means of optimizing the use of Earth by natural resource managers for decision making – see Photo 3. The benefits of this approach include cost reduction, tracking new ideas, and empowering marginalized voices.
      The first block of breakout sessions also occurred during the afternoon of the first day, along with a short report-out. In light of the keynote discussion on coproduction, deliverables from this meeting’s breakout sessions can be seen as coproduced, new or improved conduits between NASA and land-managing entities.
      After the keynote, representatives of government agencies (NASA, USFS, and BLM) presented their respective agency’s perspectives. The manager of a nearby state park in Michigan followed with a local perspective. A series of short presentations in the late afternoon featured various program highlights from NASA’s Earth Science Division, which are not detailed in this report – see workshop agenda for list of programs and speakers.
      Notable Presentations
      In addition to Kira Sullivan–Wiley’s keynote (described above), Christina Moats-Xavier [NASA Headquarters, Earth Action Program—Program Manager for Mission Engagement] shared NASA’s perspective, focusing on NASA’s Earth Science-to-Action strategy, which aims to increase the impact of scientific data. NASA’s Applied Science Program is now included under the broader umbrella of the new Earth Action program element of NASA’s Earth Science Division. This strategy has three pillars: 1) scaling existing efforts; 2) building bridges; and 3) focusing on the user. By collaborating with NASA, AEOIP can address real-world challenges to develop solutions that benefit society. Overall, the presentations on the first day highlighted the importance of collaborative, user-centered approaches and community engagement in addressing environmental challenges.
      Everett Hinkley and Frenchy Morisette [both USFS] provided a practitioner’s perspective. They discussed USFS efforts to address climate adaptation, wildfire management, and incorporation of Indigenous traditional ecological knowledge. They also emphasized the application of artificial intelligence/machine learning (AI/ML) for mapping and remote sensing tools.
      Both Jake Slyder and Tim Assal described their respective government agency’s management of vast (mostly western) land areas and use of remote sensing for post-fire emergency stabilization and integration with the Assessment, Inventory, and Monitoring (AIM) program.
      Kevin Butler offered more of a local perspective as he discussed land stewardship in Michigan. He emphasized the importance of community involvement and respecting natural ecosystems, especially fire-dependent ones, at the local level.
      Photo 3. Kira Sullivan-Wiley [Pew Institute] presents on co-production of knowledge during the first day’s plenary session. Photo credit: AEOIP DAY TWO
      The presentations on the second day of the workshop highlighted the opportunities that Earth observing satellite data presents for natural resource management applications. Five presenters contributed to the panel discussion, titled “Communicating and Soliciting End User Needs: Past, Present and Future.” The second – longer – block of breakout sessions also occurred with a short report-out at the end of the day. A poster session ran concurrently with the report-outs. While this session is not described in this report, it afforded participants an opportunity to showcase their Earth observation related projects and/or interact with their peers. Highlights from the day follow below.
      Notable Presentations
      Pontus Olafsson [NASA’s Marshall Space Flight Center] and Natasha Sadoff [NASA HQ—Satellite Needs Program Manager] presented on the Satellite Needs Working Group (SNWG), which provides a coordinated approach to identify and communicate federal satellite Earth observation needs and develop solutions based on Earth observation data. The speakers explained that as part of this effort, SNWG facilitates a biannual survey to all civilian federal agencies. SNWG provides federal agencies a path to coordinate Earth observing needs and a mechanism to develop actionable solutions for decision makers. Solutions cover thematic areas, including air quality, land use/land cover, and water resources. They noted that NASA is also making a greater effort to engage with agency partners in the co-development of new solutions that are useful, accessible, and actionable.
      Alison York [University of Alaska Fairbanks] spoke about the Joint Fire Science Program (JFSP) and Fire Science Exchange Network (FSEN). JFSP’s main function is to maintain and grow a data repository and community based on fuels, fire behavior, fire ecology, and human dimensions. The goal is to help enable informed, actionable change by policy makers and land managers with the best available scientific support. York then discussed the FSEN, which acts as a mechanism to collate research needs from a collection of regional fire exchanges. The syntheses of data and data needs provides more effective understanding and management of fire.
      Training Breakout Session Takeaways
      On the second day, the four breakout sessions met, beginning with four short (25-minute) trainings. The speakers each gave half-hour presentations, which they repeated twice during the hour dedicated to the training breakouts, allowing participants to engage in two of the training breakouts if desired.
      Pete Robichaud [USFS] discussed training opportunities for modeling post-fire hydrological response using the Water Erosion Prediction Project (WEPP). Soil burn severity is first assessed with remote sensing and then field verified. A subsequent soil burn severity map can be created to give details on physical features, e.g., ash color, ash depth, fine roots, soil structure, water repellency, and ground cover. This resource can be used to create a risk assessment table of probability and consequence parameters. Following the risk assessment, the Forest Service Water WEPP suite of tools can be used to model the landscape. The WEPP suite includes both hillslope and watershed modeling tools. The final step in the Burned Area for Emergency Response (BAER) program is to implement and monitor solutions.
      Rupesh Shretha [Oak Ridge National Laboratory (ORNL), Distributed Active Archive Center (DAAC)] discussed the Earth Observing System Data and Information System (EOSDIS) DAACs, which are collocated with centers of science discipline expertise and archive and distribute NASA Earth Science data products. The ORNL DAAC archives and distributes terrestrial ecology data, particularly data from field and airborne campaigns. The Terrestrial Ecology Subsetting & Visualization Services (TESViS) – formerly MODIS–VIIRS subsets tool – provide subsets of satellite data in easy-to-use formats that are particularly valuable for site-based field research. The Ecological Spectral Information System (ECOSIS) integrates spectral data with measurements of vegetation functional traits (i.e., species, foliar chemistry). ECOSIS allows users to submit spectral data and return a citable DOIs. ECOSIS also provides users application programming interface (API)-based methods to retrieve thousands of field spectra.
      Jake Slyder discussed the use of remote sensing for efficient resource management over vast tracts of land with limited human and financial resources. He explained that while the vast collection of remotely sensed data makes it challenging to effectively exploit, Google Earth Engine (GEE) has become an important tool in leveraging remotely sensed information to address BLM management questions. The Change and Disturbance Event Detection Tool (CDEDT), a GEE-based application, allows users to detect and develop vector geospatial products to identify changes and disturbances to surface cover between two dates of observations [10 m (~33 ft) resolution] from the European Space Agency’s (ESA) Copernicus Sentinel-2 mission. Slyder said that the Version 2 (V2) beta product includes the National Agriculture Imagery Program (NAIP) and ESA Copernicus Sentinel-1 SAR Imagery. CDEDT supports a range of BLM monitoring applications, including disaster events, energy development, forest disturbances, and seasonal patterns and processes (e.g., vegetation, water cover). The CDEDT tool is publicly available and does not require any license or special software.
      DAY THREE
      The third day was dedicated to the final block of the breakout sessions and a final plenary, where a representative from each breakout group gave five to seven minute summaries of their discussions throughout the meeting. The overview was followed by a meeting wrap-up and adjournment. The sections below summarize the topical presentations given on day three and encapsulate the three days of discussions.
      Breakout Session A: Focus on Carbon
      The carbon breakout aimed to inform participants about carbon-related EO initiatives and spark discussion about user needs.
      Aaron Piña [USFS] spoke about the Forest Service’s broad base of applied research that spans wildfire weather and behavior to dynamics of the smoke produced – see Photo 2. Recent assessments have been made for wildland fire, controlled burn smoke, and remote air monitors. Piña spoke about Bluesky Playground, a community-driven tool aimed at providing the public with information on fuels and smoke modeling. These data have been used to identify important indicators for fires and fuels (e.g., vertical plume structure).
      Piña then discussed a fusion Fire Radiative Power (FRP) data product [MOD19A2] that combines data from four sources – the Visible and Infrared Scanner (VIRS) on the former Tropical Rainfall Measuring Mission (TRMM), the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (Suomi NPP), the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua platforms, and the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product.
      A group discussion followed Piña’s presentation, during which several participants expressed concerns about the continuity of VIIRS and the other observations that are used in the fusion FRP product. Another topic of discussion was the potential of remotely sensed data to improve the characterization of duff (decaying vegetation) in satellite data products. NASA’s Tropospheric Emissions: Monitoring of Pollution (TEMPO) mission data have also been used to characterize the vertical structure of smoke plumes; however, these efforts have thus far been limited by personnel knowledge gaps as well as raw data formats.
      Chris Woodall [USFS] discussed the growing emphasis on carbon metrics for a variety of sectors and applications. The USFS wants to work in tandem with other entities, especially federal organizations, to maximize efforts and workstream. USFS is seen as the in-situ carbon observer, while NASA is the remote sensor, and USGS is the lateral flux assessor. The coproduction of knowledge and data regarding carbon among these agencies is an iterative process. The USFS investment in improved Measurement, Monitoring, Reporting, and Verification (MMRV) of greenhouse gas (GHG), for example, can expand soil and land-use inventories to improve alignment with remote-sensing platforms. Challenges to implementing this cooperative approach to collecting carbon metrics include creating a workflow that incorporates a wealth of existing resources and accruing data from multiple federal agencies concerned with ecosystem carbon management to create scalable GHG knowledge. The coproduction, iteration, and dissemination of knowledge should be a major focus with all interested parties – not just the aforementioned federal agencies.
      Sydney Neugebauer [NASA’s Langley Research Center] and Melanie Follette-Cook [GSFC] discussed NASA’s capacity building initiatives, which are aimed at developing and strengthening an organization or community’s skills, abilities, processes, and resources to enable them to survive, adapt, and thrive in a fast changing world. The DEVELOP, Indigenous Peoples Initiative, and SERVIR programs (all under the Earth Action program element) work towards capacity building through co-development projects, collaborative training, and data availability. The NASA Applied Remote Sensing Training (ARSET) program has offered over 100,000 training sessions since it was created in 2009 – primarily to international participants. The trainings are free and virtual for individuals interested in using remotely sensed data in a diverse suite of environmental applications. All content is archived. NASA’s Carnegie-Ames-Stanford Approach (CASA), which has contributed to global carbon dioxide (CO2) sequestration datasets for the past 30-years, will be upgraded to incorporate CO2 fluxes. The NASA cooperative interagency U.S. Greenhouse Gas Center is also looking for feedback on its beta portal.
      The group discussions that followed identified and addressed AEOIP needs and questions (e.g., obtaining carbon and smoke emission estimates from prescribed wildfires and ensuring global satellite fire record continuity). Participants also identified the need for near real-time active fire and burned area mapping at medium scale and for continuity of these measurements. The group is interested in engaging federal agency end users to obtain feedback on their capacity to facilitate and elucidate capacity needs. Prominent challenges going forward include preparing for the end of the Terra and Aqua missions, which will include the decommissioning of MODIS, and ensuring the continuity of VIIRS, which is being used to allow for continuity of MODIS data products. One of the greatest unknowns identified was being able to determine wildfire fuel conditions in near-real time, and the ability to constrain estimates of fuel attributes to a focused fire event.
      Andy Hudak discussed the diverse coalition of practitioners who manage more than just carbon (e.g., forest health, harvest, fires). Of the diverse group of stakeholders, Indigenous Tribes are at the cutting edge using lidar for carbon assessment. While Forest Inventory and Analysis plots are used for bias correction, they do not provide synoptic coverage for accurate carbon assessments. Lidar and other passive remote sensing satellite data provide a way to address this need. Tree lists are also highly valuable to carbon and forest managers for diverse applications. Application-specific metrics (e.g., timber volume, basal area, and density) can be weighted based on stakeholder priorities, as quantified from stakeholder surveys, to optimize data products.
      Sarah Lewis [USFS] explained the needs and applications of Earth observations in a post-fire environment. The information needs to be available quickly, integrated into effective decision-making tools, and delivered in a functional product. Information is needed on water, soils, vegetation recovery, and habitat – all major metrics of interest in a data product. Areas of concern during post-fire management for water quality and erosion control include ash and soil–water transport. In addition, major concerns exist for timely data acquisition and processing, along with the fate and transport mapping of post-fire ash. Data products would benefit from end-user input to optimize relevance and accessibility of decision ready maps, models, and trusted recommendations.
      The group identified the need for heavy carbon fuels and duff estimates for ecological modeling, which is critical to achieving a better understanding of smoke and carbon emissions. The heavy carbon fuel and duff estimates may be achieved through multiple means but may be most accessible currently through a new layer in the LANDFIRE database. They also identified the need for more post-fire data for model training and integration of active remote sensing data. Finally, the group identified the need for more regulation and research on prescribed fire emissions and disturbance.
      Breakout Session B: Prescribed Fire
      This breakout session focused on prescribed fires. Some of the major objectives and needs that emerged from this session were improved access to data, cultivating deeper public trust in the practice, creating networks of future coproduction, and assessing end-user needs, burn maps, and securing funding. The discussions emphasized knowledge and awareness gaps as a major impediment to prescribed fire implementation. Uniform capacity building is an ideal approach to engage stakeholders at a reference level appropriate to their background to optimize equity and efficacy.
      Another issue that came up during discussion is that land management professionals do not have the time or resources to stay current with data sources and analysis techniques. The participants suggested the creation of a “Fire Science Library” as an iterative data tool to organize and present fire knowledge in an actionable and streamlined manner for public land managers. The interface would allow practitioners to filter unique categories (e.g., role, scope, region, ecosystem type, weather, agency affiliation) to provide the ability to search, modify, and maintain fire science knowledge as it evolves. This interface would also provide provenance through references to papers, justification for methods, and case studies. The library would guide and streamline data collection, analyses, and interpretation workflows that are needed for holistic prescribed fire planning and monitoring based on tangible needs from fire professionals.
      The virtual library tool would provide a user with a fire-science knowledge graph, which is an organized representation of real-world entities and their relationships that could quickly connect fire-related management with current research questions concerning data products, processing methods, and data sources along with references and case studies. Information provided in the knowledge graph would need to be context specific but not overly prescriptive to avoid constraining users to a rigid workflow that is more common in basic data portals. Knowledge graphs are associated with semantic web technology that forms a modern version of a database. The tool establishes relationships between entities that promote new relationship discovery, search, and modification. It also provides a foundation on which other applications can be built, such as prescribed fires in the southeast and incorporating drone data. Focusing on prescribed fire may help to bound the initial product development but leave the door open for eventual expansion for wildfire.
      The group identified objectives moving forward, including the need to finalize the main set of prescribed fire management questions (e.g., planning, implementation, pre/post monitoring), establish user personas based on known representatives and gaps, engage the Earth Science Information Partners (ESIP), identify cluster members (e.g., subject matter experts from local and federal agencies, private industry, and academia/research), and investigate additional funding sources. (Clusters are agile working groups within ESIP formed to focus on specific topics.)
      Breakout Session C: Fractional Vegetation Cover
      This breakout session focused on fractional vegetation cover (FVC) – see Photo 4. The presenters introduced three large FVC assessment efforts, and the participants contributed to a Strengths, Weakness, Opportunities, and Threats (SWOT) analysis of FVC products intended to improve the use of this data by decision makers – see Table.
      Photo 4. [left to right] Amanda Armstrong, Elizabeth Hoy [both at Goddard Space Flight Center], and Timothy Assal [Bureau of Land Management] collaborating during the Fractional Vegetation Cover Breakout. Photo credit: AEOIP Tim Assal discussed the BLM’s Assessment Inventory and Monitoring (AIM) strategy. He explained that AIM has nearly 60,000 monitoring locations across the terrestrial uplands, aquatic systems, and riparian and wetland habitat of the U.S., and the data collected are being used for monitoring and restoration activities. Assai added that integration of remote sensing data with field plot data enables the generation of continuous datasets (e.g., FVC that can relate field plot-level indicators to those based on remote-sensing). He also reported that FVC data are currently being used to address numerous management decisions.
      Sarah McCord [USDA] discussed V3 of the Rangeland Analysis Platform (RAP). McCord explained that V3 uses vegetation cover and rangeland production data to monitor these parameters. The model also uses species composition data. She explained that there are approximately 85,000 training/validation locations across the U.S. that have been incorporated into the modeling process. She said that enhancements to future versions of RAP are expected as data from new satellite instruments, field plots, and deep learning (i.e., application of AI/ML techniques) are all incorporated into the model. McCord chairs a working group that is actively investigating sources of error and uncertainty within individual and across different FVC products.
      Matt Rigge [USGS Earth Resources Observation and Science (EROS) Center] discussed V3 of the Rangeland Condition Monitoring Assessment and Projection (RCMAP), which will provide current and future condition using Landsat time series. Data available includes cover maps and potential cover. The platform uses various training data in addition to AIM plot data. In the future RCMAP plans to incorporate data from synthetic NASA-Indian Space Research Organization Synthetic Aperture Radar (NISAR), from NASA’s Earth Surface Mineral Dust Source (EMIT) mission, and from convolution neural network-based (CNN) algorithms.
      Bo Zhou [University of California, Los Angeles (UCLA)] discussed V2 of the Landscape Cover Analysis and Reporting Tool (LandCART). V3 will be different and coming in the future. He explained that the BLM uses V3 to make legally defensible decisions. He then discussed the training data, which come mostly from AIM. The training dataset includes 71 Level-4 (L4) Ecoregions, as defined by the U.S. Environmental Protection Agency, with at least 100 observations. Zhou noted that these training data are used to define spatial extent, the temporal extent is defined by available satellite imagery, and uncertainty estimates are based on CNN and random forest (RF) machine-learning algorithms.
      Eric Jensen [Desert Research Institute] discussed how ClimateEngine.org uses cloud-based tools, such as GEE, to access, visualize, and share Earth observation datasets to overcome computational limitations of big data in a real-time environment. It encompasses over 85 datasets, including RAP and RCMAP, and the group is working to add LandCART. Two core functionalities of the ClimateEngine app are producing maps and making graphs. Jensen provided a brief demonstration of the app using a juniper removal project in sage grouse habitat in southern Idaho.
      Strengths
      • Tools available for accessing and processing data are user-friendly and widely accessible, making it easy to compile, use, and display data for users of all expertise levels across a range of management activities.
      • Tools provide a comprehensive view of an area, offering both current and retrospective insights that are highly regarded by the restoration community.
      • Tool format supports integration of new datasets, ensuring inclusivity and consistency over time and space.   Weaknesses
      • Training data exhibits spatial and temporal biases.
      • Training data is biased towards federal data, lacking global representation.
      • Sensors have limitations for both temporal and spatial accuracy.   Opportunities
      • Managers can use these tools to make informed decisions and evaluate the effectiveness of their treatments.
      • Additional training (e.g., training in how to process new data types, such as hyperspectral data) could institutionalize remote sensing and reach more end users.
      • Future expansion of AI/ML techniques and cloud-based services could reduce error, enhance data quality, and increase user reach.   Threats
      • Stability of funding could threaten continuity of measurements.
      • Falling into a “one size fits all” mentality could stifle innovation.
      • Variation in land management organizations’ willingness to update data and lack of cohesion could prevent obtaining full potential of FVC.
      • Transition from research to operations could hinder collaboration and tool development and weaken the community of practice.
      • Poor performance, misuse of information, and data sovereignty could diminish the community’s trust in the tools.
      • Rapid technological advancements could displace smaller businesses.   Table. Results of a Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis of the current state of Fractional Vegetation Cover (FVC) data analysis tools and techniques. Breakout Session D: Post-fire Effects and Recovery
      This session focused on assessing, predicting, remediating, and monitoring areas in the aftermath of fires. The focus was on “shovel-ready” ideas, such as improving operational soil burn severity maps to connect post-fire ground conditions and soil properties. The participants highlighted the need to leverage information (e.g., active fire thermal data) to better detect changes in post-fire cover and soil properties. Such information would be beneficial to USFS’s Burned Area for Emergency Response (BAER) program as well as to researchers, data providers, decision makers, and community leaders. The group discussed steps that would aid in this collaboration (e.g., incorporating thermal imagery into mapping soil burn severity, developing and validating products, getting first-look data to field teams, monitoring threats by conducting rapid burn severity assessment before official soil burn severity maps are made available, and sharing outputs quickly with decision makers).
      The breakout participants also noted the challenge of ash load mapping, which they suggested might be constrained by using information on pre-fire fuels (e.g., biomass, understory, and canopy vegetation) to constrain potential ash production. Derived information products [e.g., Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), LANDFIRE fuels layers, and RAP] may improve this process. The group noted the limitations of the VIIRS instrument for mapping fire duration and soil heating. The group proposed adding supplemental data through the use of National Infrared Operations (NIROPS) raw infrared imagery – see Figure 1.
      Fire tools currently available – and under consideration for improving maps – include VIIRS active fire data through NASA’s Fire Information for Resource Management System (FIRMS), fire event tracking through NASA’s Earth Information System Fire Event Data Suite (FEDS), the burn severity prediction model at MTRI, and Rapid Differenced Normalized Burn Ratio Mapping at the University of Wisconsin, Madison. The group identified VIIRS L1 image capture to detect smoldering fires as a potential improvement in wildfire characterization. The group also suggested more frequent observations of moderate resolution satellites, GOES Integration [0.5–2 km (0.3–1.2 mi) spatial resolution], and comprehensive field data. They identified possible ways to improve post-fire soil burn severity maps (e.g., information on pre-fire fuels, soil characteristics, and thermal properties, such as fire heating, residence time, spread rate), optical characteristic (e.g., vegetation mortality, ash production), and lidar canopy metrics.
      Presently, burn severity is assessed using a simple spectral index derived from remote sensing data, driven by necessity, data access, and computing power. The group presented the need to break this single number into ecologically meaningful components for better post-fire assessment and remediation. Improvements could involve incorporating additional information (e.g., peak soil temperature, heat residence time, and fuel moisture). Coupling atmospheric fire behavior models could address temporal gaps, necessitating high-spatial and temporal resolution thermal data sets.
      The participants agreed that future strategies should include monitoring warmer areas and smoldering zones instead of just flaming fronts, as well as exploring temperature differences across burn severities. Additionally, post-fire assessments would benefit from using other spectral bands and post-fire Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) products. They also added that access to more field information is crucial for scientific post-fire observations. Efforts are underway to make the SBS S123 survey system a national standard, though surveys currently reside with local units that have good record-keeping practices.
      Figure 1. Optical [left and right] and thermal [right, overlay] images of participants at the 2024 AEOIP workshop obtained by an unpiloted aerial vehicle (UAV). Image credit: Colin Brooks Conclusion
      The 2024 AEOIP workshop addressed a wide range of geospatial data tool and training needs and forums. The meeting centered on coproduction of knowledge and community-of-practice building as key needs for the geospatial data topics. Participants identified capacity building – through awareness, accessibility, and utility of data and tools – as the top priority for processing and technological advancement initiatives.
      The breakout session topics selected (e.g., carbon concentrations, wildfires, prescribed fires, and landscape dynamics) were chosen to promote dialogue between data users and scientists, leading to plans for action and change in data and tool utility in four areas of interest for land managers. Following the meeting, the organizers submitted a spreadsheet detailing the data and tool needs identified during the breakouts to the Earth Action Program. The SNWG has also been made aware of the most compelling needs that participants identified. The AEOIP believes that by bridging two groups – data users and research and development – it will be possible to bolster user provenance and efficacy of NASA resources moving forward.
      Severin Scott
      Washington State University
      severin.scott@wsu.edu
      Alan B. Ward
      NASA’s Goddard Space Flight Center (GSFC)/Global Science and Technology (GST)
      alan.b.ward@nasa.gov
      Alexis O’Callahan
      University of Arkansas
      aocallah@uark.edu
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      Last Updated Jan 03, 2025 Related Terms
      Earth Science View the full article
    • By NASA
      More than 30,000 scientists gathered in Washington, D.C. during the second week of December – many to show off the work of NASA’s science volunteers! The American Geophysical Union held its annual meeting of professionals this month – the world’s largest gathering of Earth and Space Scientists. Here’s what they were talking about.
      Eighteen NASA-sponsored project team members presented discoveries made with volunteers on topics from solar eclipses to global freshwater lake monitoring and  exoplanet research. Overall, 175 posters and presentations featured the work of volunteers (up from 137 in 2023). Overall, 363 scientists and presenters at the conference described themselves as being involved in citizen science research (up from 201 in 2023). Two dozen scientists at the meeting gathered for lunch in the atrium of the National Portrait Gallery to talk about doing NASA science with volunteers. They discussed projects about asteroids, landslide hazard prediction, solar eclipse science, water quality, martian clouds, and more. Science done with volunteers is often called citizen science or participatory science – it does not require citizenship in any particular country. “Between the immense datasets being collected by NASA missions and the perennial need to open wide the doors to science so everyone can experience the joy and rewards of doing research together, citizen science is needed now more than ever!” said Sarah Kirn, the participatory science strategist at the Gulf of Maine Research Institute in Portland.” You can join one of NASA’s many participatory science projects right here!
      Two dozen scientists gathered for lunch in the atrium of the National Portrait Gallery to talk about working with volunteers. They discussed projects about asteroids, landslide hazard prediction, solar eclipse science, water quality, martian clouds and more. Credit: Sarah Kirn Facebook logo @DoNASAScience @DoNASAScience Share








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      Last Updated Dec 23, 2024 Related Terms
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    • By NASA
      4 min read
      NASA Open Science Reveals Sounds of Space
      A composite image of the Crab Nebula features X-rays from Chandra (blue and white), optical data from Hubble (purple), and infrared data from Spitzer (pink). This image is one of several that can be experienced as a sonification through Chandra’s Universe of Sound project. X-ray: NASA/CXC/SAO; Optical: NASA/STScI; Infrared: NASA-JPL-Caltech NASA has a long history of translating astronomy data into beautiful images that are beloved by the public. Through its Chandra X-ray Observatory and Universe of Learning programs, NASA brings that principle into the world of audio in a project known as “A Universe of Sound.” The team has converted openly available data from Chandra, supplemented by open data from other observatories, into dozens of “sonifications,” with more on the way.
      Following the open science principle of accessibility, “A Universe of Sound” helps members of the public who are blind or low vision experience NASA data in a new sensory way. Sighted users also enjoy listening to the sonifications. 
      “Open science is this way to not just have data archives that are accessible and incredibly rich, but also to enhance the data outputs themselves,” said Dr. Kimberly Arcand, the visualization scientist and emerging technology lead at Chandra and member of NASA’s Universe of Learning who heads up the sonification team. “I want everybody to have the same type of access to this data that I do as a scientist. Sonification is just one of those steps.”
      Data sonification of the Milky Way galactic center, made using data from NASA’s Chandra X-ray Observatory, Hubble Space Telescope, and Spitzer Space Telescope. While the Chandra telescope provides data in X-ray wavelengths for most of the sonifications, the team also took open data from other observatories to create a fuller picture of the universe. Types of data used to create some of the sonifications include visual and ultraviolet light from the Hubble Space Telescope, infrared and visual light from the James Webb Space Telescope, and infrared light from the now-retired Spitzer Space Telescope. 
      The sonification team, which includes astrophysicist Matt Russo, musician Andrew Santaguida (both of the SYSTEM Sounds project), consultant Christine Malec, and Dr. Arcand, assigned each wavelength of observation to a different musical instrument or synthesized sound to create a symphony of data. Making the separate layers publicly available was important to the team to help listeners understand the data better. 
      “It’s not just about accessibility. It’s also about reproducibility,” Arcand said. “We’re being very specific with providing all of the layers of sound, and then describing what those layers are doing to make it more transparent and obvious which steps were taken and what process of translation has occurred.” 
      For example, in a sonification of the supernova remnant Cassiopeia A, modified piano sounds represent X-ray data from Chandra, strings and brass represent infrared data from Webb and Spitzer, and small cymbals represent stars located via visual light data from Hubble. 
      Data sonification of the Cassiopeia A supernova remnant, made using data from NASA’s Chandra X-ray Observatory, James Webb Space Telescope, and Hubble Space Telescope. The team brought together people of various backgrounds to make the project a success – scientists to obtain and interpret the data, audio engineers to mix the sonifications, and members of the blind and low vision community to direct the product into something that brought a greater understanding of the data. 
      “Another benefit to open science is it tends to open those pathways of collaboration,” Arcand said. “We invite lots of different community members into the process to make sure we’re creating something that adds value, that adds to the greater good, and that makes the investment in the data worthwhile.” 
      A documentary about the sonifications called “Listen to the Universe” is hosted on NASA+. Visitors can listen to all the team’s sonifications, including the separate layers from each wavelength of observation, on the Universe of Sound website.
      By Lauren Leese 
      Web Content Strategist for the Office of the Chief Science Data Officer 
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