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By NASA
6 min read
Preparations for Next Moonwalk Simulations Underway (and Underwater)
This animation shows data taken by NASA’s PACE and the international SWOT satellites over a region of the North Atlantic Ocean. PACE captured phytoplankton data on Aug. 8, 2024; layered on top is SWOT sea level data taken on Aug. 7 and 8, 2024. NASA’s Scientific Visualization Studio One Earth satellite can see plankton that photosynthesize. The other measures water surface height. Together, their data reveals how sea life and the ocean are intertwined.
The ocean is an engine that drives Earth’s weather patterns and climate and sustains a substantial portion of life on the planet. A new animation based on data from two recently launched missions — NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) and the international Surface Water and Ocean Topography (SWOT) satellites — gives a peek into the heart of that engine.
Physical processes, including localized swirling water masses called eddies and the vertical movement of water, can drive nutrient availability in the ocean. In turn, those nutrients determine the location and concentration of tiny floating organisms known as phytoplankton that photosynthesize, converting sunlight into food. These organisms have not only contributed roughly half of Earth’s oxygen since the planet formed, but also support economically important fisheries and help draw carbon out of the atmosphere, locking it away in the deep sea.
“We see great opportunity to dramatically accelerate our scientific understanding of our oceans and the significant role they play in our Earth system,” said Karen St. Germain, director of the Earth Science Division at NASA Headquarters in Washington. “This visualization illustrates the potential we have when we begin to integrate measurements from our separate SWOT and PACE ocean missions. Each of those missions is significant on its own. But bringing their data together — the physics from SWOT and the biology from PACE — gives us an even better view of what’s happening in our oceans, how they are changing, and why.”
A collaboration between NASA and the French space agency CNES (Centre National d’Études Spatiales), the SWOT’ satellite launched in December 2022 to measure the height of nearly all water on Earth’s surface. It is providing one of the most detailed, comprehensive views yet of the planet’s ocean and its freshwater lakes, reservoirs, and rivers.
Launched in February 2024, NASA’s PACE satellite detects and measures the distribution of phytoplankton communities in the ocean. It also provides data on the size, amount, and type of tiny particles called aerosols in Earth’s atmosphere, as well as the height, thickness, and opacity of clouds.
“Integrating information across NASA’s Earth System Observatory and its pathfinder missions SWOT and PACE is an exciting new frontier in Earth science,” said Nadya Vinogradova Shiffer, program scientist for SWOT and the Integrated Earth System Observatory at NASA Headquarters.
Where Physics and Biology Meet
The animation above starts by depicting the orbits of SWOT (orange) and PACE (light blue), then zooms into the North Atlantic Ocean. The first data to appear was acquired by PACE on Aug. 8. It reveals concentrations of chlorophyll-a, a vital pigment for photosynthesis in plants and phytoplankton. Light green and yellow indicate higher concentrations of chlorophyll-a, while blue signals lower concentrations.
Next is sea surface height data from SWOT, taken during several passes over the same region between Aug. 7 and 8. Dark blue represents heights that are lower than the mean sea surface height, while dark orange and red represent heights higher than the mean. The contour lines that remain once the color fades from the SWOT data indicate areas of the ocean with the same height, much like the lines on a topographic map indicate areas with the same elevation.
The underlying PACE data then cycles through several groups of phytoplankton, starting with picoeukaryotes. Lighter green indicates greater concentrations of this group. The final two groups are cyanobacteria — some of the smallest and most abundant phytoplankton in the ocean — called Prochlorococcus and Synechococcus. For Prochlorococcus, lighter raspberry colors represent higher concentrations. Lighter teal colors for Synechococcus signal greater amounts of the cyanobacteria.
The animation shows that higher phytoplankton concentrations on Aug. 8 tended to coincide with areas of lower water height. Eddies that spin counterclockwise in the Northern Hemisphere tend to draw water away from their center. This results in relatively lower sea surface heights in the center that draw up cooler, nutrient-rich water from the deep ocean. These nutrients act like fertilizer, which can boost phytoplankton growth in sunlit waters at the surface.
Overlapping SWOT and PACE data enables a better understanding of the connections between ocean dynamics and aquatic ecosystems, which can help improve the management of resources such as fisheries, since phytoplankton form the base of most food chains in the sea. Integrating these kinds of datasets also helps to improve calculations of how much carbon is exchanged between the atmosphere and the ocean. This, in turn, can indicate whether regions of the ocean that absorb excess atmospheric carbon are changing.
More About SWOT
The SWOT satellite was jointly developed by NASA and CNES, with contributions from the Canadian Space Agency (CSA) and the UK Space Agency. NASA’s Jet Propulsion Laboratory, managed for the agency by Caltech in Pasadena, California, leads the U.S. component of the project. For the flight system payload, NASA provided the Ka-band radar interferometer (KaRIn) instrument, a GPS science receiver, a laser retroreflector, a two-beam microwave radiometer, and NASA instrument operations. The Doppler Orbitography and Radioposition Integrated by Satellite system, the dual frequency Poseidon altimeter (developed by Thales Alenia Space), the KaRIn radio-frequency subsystem (together with Thales Alenia Space and with support from the UK Space Agency), the satellite platform, and ground operations were provided by CNES. The KaRIn high-power transmitter assembly was provided by CSA.
To learn more about SWOT, visit:
https://swot.jpl.nasa.gov
More About PACE
The PACE mission is managed by NASA Goddard Space Flight Center, which also built and tested the spacecraft and the Ocean Color Instrument, which collected the data shown in the visualization. The satellite’s Hyper-Angular Rainbow Polarimeter #2 was designed and built by the University of Maryland, Baltimore County, and the Spectro-polarimeter for Planetary Exploration was developed and built by a Dutch consortium led by Netherlands Institute for Space Research, Airbus Defence, and Space Netherlands.
To learn more about PACE, visit:
https://pace.gsfc.nasa.gov
News Media Contacts
Jacob Richmond (for PACE)
NASA’s Goddard Space Flight Center, Greenbelt, Md.
jacob.a.richmond@nasa.gov
Jane J. Lee / Andrew Wang (for SWOT)
Jet Propulsion Laboratory, Pasadena, Calif.
818-354-0307 / 626-379-6874
jane.j.lee@jpl.nasa.gov / andrew.wang@jpl.nasa.gov
2024-169
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Last Updated Dec 09, 2024 Related Terms
PACE (Plankton, Aerosol, Cloud, Ocean Ecosystem) Climate Science Oceans SWOT (Surface Water and Ocean Topography) Explore More
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Expanded AI Model with Global Data Enhances Earth Science Applications
On June 22, 2013, the Operational Land Imager (OLI) on Landsat 8 captured this false-color image of the East Peak fire burning in southern Colorado near Trinidad. Burned areas appear dark red, while actively burning areas look orange. Dark green areas are forests; light green areas are grasslands. Data from Landsat 8 were used to train the Prithvi artificial intelligence model, which can help detect burn scars. NASA Earth Observatory NASA, IBM, and Forschungszentrum Jülich have released an expanded version of the open-source Prithvi Geospatial artificial intelligence (AI) foundation model to support a broader range of geographical applications. Now, with the inclusion of global data, the foundation model can support tracking changes in land use, monitoring disasters, and predicting crop yields worldwide.
The Prithvi Geospatial foundation model, first released in August 2023 by NASA and IBM, is pre-trained on NASA’s Harmonized Landsat and Sentinel-2 (HLS) dataset and learns by filling in masked information. The model is available on Hugging Face, a data science platform where machine learning developers openly build, train, deploy, and share models. Because NASA releases data, products, and research in the open, businesses and commercial entities can take these models and transform them into marketable products and services that generate economic value.
“We’re excited about the downstream applications that are made possible with the addition of global HLS data to the Prithvi Geospatial foundation model. We’ve embedded NASA’s scientific expertise directly into these foundation models, enabling them to quickly translate petabytes of data into actionable insights,” said Kevin Murphy, NASA chief science data officer. “It’s like having a powerful assistant that leverages NASA’s knowledge to help make faster, more informed decisions, leading to economic and societal benefits.”
AI foundation models are pre-trained on large datasets with self-supervised learning techniques, providing flexible base models that can be fine-tuned for domain-specific downstream tasks.
Crop classification prediction generated by NASA and IBM’s open-source Prithvi Geospatial artificial intelligence model. Focusing on diverse land use and ecosystems, researchers selected HLS satellite images that represented various landscapes while avoiding lower-quality data caused by clouds or gaps. Urban areas were emphasized to ensure better coverage, and strict quality controls were applied to create a large, well-balanced dataset. The final dataset is significantly larger than previous versions, offering improved global representation and reliability for environmental analysis. These methods created a robust and representative dataset, ideal for reliable model training and analysis.
The Prithvi Geospatial foundation model has already proven valuable in several applications, including post-disaster flood mapping and detecting burn scars caused by fires.
One application, the Multi-Temporal Cloud Gap Imputation, leverages the foundation model to reconstruct the gaps in satellite imagery caused by cloud cover, enabling a clearer view of Earth’s surface over time. This approach supports a variety of applications, including environmental monitoring and agricultural planning.
Another application, Multi-Temporal Crop Segmentation, uses satellite imagery to classify and map different crop types and land cover across the United States. By analyzing time-sequenced data and layering U.S. Department of Agriculture’s Crop Data, Prithvi Geospatial can accurately identify crop patterns, which in turn could improve agricultural monitoring and resource management on a large scale.
The flood mapping dataset can classify flood water and permanent water across diverse biomes and ecosystems, supporting flood management by training models to detect surface water.
Wildfire scar mapping combines satellite imagery with wildfire data to capture detailed views of wildfire scars shortly after fires occurred. This approach provides valuable data for training models to map fire-affected areas, aiding in wildfire management and recovery efforts.
Burn scar mapping generated by NASA and IBM’s open-source Prithvi Geospatial artificial intelligence model. This model has also been tested with additional downstream applications including estimation of gross primary productivity, above ground biomass estimation, landslide detection, and burn intensity estimations.
“The updates to this Prithvi Geospatial model have been driven by valuable feedback from users of the initial version,” said Rahul Ramachandran, AI foundation model for science lead and senior data science strategist at NASA’s Marshall Space Flight Center in Huntsville, Alabama. “This enhanced model has also undergone rigorous testing across a broader range of downstream use cases, ensuring improved versatility and performance, resulting in a version of the model that will empower diverse environmental monitoring applications, delivering significant societal benefits.”
The Prithvi Geospatial Foundation Model was developed as part of an initiative of NASA’s Office of the Chief Science Data Officer to unlock the value of NASA’s vast collection of science data using AI. NASA’s Interagency Implementation and Advanced Concepts Team (IMPACT), based at Marshall, IBM Research, and the Jülich Supercomputing Centre, Forschungszentrum, Jülich, designed the foundation model on the supercomputer Jülich Wizard for European Leadership Science (JUWELS), operated by Jülich Supercomputing Centre. This collaboration was facilitated by IEEE Geoscience and Remote Sensing Society.
For more information about NASA’s strategy of developing foundation models for science, visit https://science.nasa.gov/artificial-intelligence-science.
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Last Updated Dec 04, 2024 Related Terms
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Earth Observer Earth Home Earth Observer Home Editor’s Corner Feature Articles Meeting Summaries News Science in the News Calendars In Memoriam More Archives 3 min read
Summary of Aura 20th Anniversary Event
Snippets from The Earth Observer’s Editor’s Corner
The last of NASA’s three EOS Flagships – Aura – marked 20 years in orbit on July 15, 2024, with a celebration on September 18, 2024, at the Goddard Space Flight Center’s (GSFC) Recreational Center. The 120 attendees – including about 40 virtually – reminisced about Aura’s (originally named EOS-CHEM) tumultuous beginning, from the instrument and Principal Investigator (PI) selections up until the delayed launch at the Vandenberg Space Force Base (then Vandenberg Air Force Base) in California. They remembered how Bill Townsend, who was Deputy Director of GSFC at the time, and Ghassem Asrar, who was NASA’s Associate Administrator for Earth Science, spent many hours on site negotiating with the Vandenberg and Boeing launch teams in preparation for launch (after several delays and aborts). The Photo shows the Aura mission program scientist, project scientists (PS), and several instrument principal investigators (PI) shortly before launch.
Photo 1. The Aura (formerly EOS CHEM) mission program scientist, project scientists (PS), and several of instrument principal investigators (PI) at Vandenberg Space Force Base (then Air Force Base) shortly before launch on July 15, 2004. The individuals pictured [left to right] are Reinhold Beer [NASA/Jet Propulsion Laboratory (JPL)—Tropospheric Emission Spectrometer (TES) PI]; John Gille [University of Colorado, Boulder/National Center for Atmospheric Research (NCAR)—High Resolution Dynamics Limb Sounder (HIRDLS) PI]; Pieternel Levelt [Koninklijk Nederlands Meteorologisch Instituut (KNMI), Royal Netherlands Meteorological Institute—Ozone Monitoring Instrument (OMI) PI]; Ernest Hilsenrath [NASA’s Goddard Space Flight Center (GSFC)—Aura Deputy Scientist and U.S. OMI Co-PI];Anne Douglass [GSFC—Aura Deputy PS]; Mark Schoeberl [GSFC—Aura Project Scientist]; Joe Waters [NASA/JPL—Microwave Limb Sounder (MLS) PI]; P.K. Bhartia [GSFC—OMI Science Team Leader and former Aura Project Scientist]; and Phil DeCola [NASA Headquarters—Aura Program Scientist]. NOTE: Affiliations/titles listed for individuals named were those at the time of launch. Photo Credit: Ernest Hilsenrath At the anniversary event, Bryan Duncan [GSFC—Aura Project Scientist] gave formal opening remarks. Aura’s datasets have given a generation of scientists the most comprehensive global view of gases in Earth’s atmosphere to better understand the chemical and dynamic processes that shape their concentrations. Aura’s objective was to gather data to monitor Earth’s ozone layer, examine trends in global air pollutants, and measure the concentration of atmospheric constituents contributing to climate forcing. To read more about Aura’s incredible 20 years of accomplished air quality and climate science, see the anniversary article “Aura at 20 Years” in The Earth Observer.
Bill Guit [GSFC—Aqua and Aura Program Manager and former Aura Mission Operations Lead] gave brief remarks focusing on how Aura became part of the international Afternoon Constellation, or “A-Train,” of satellites, including Aqua, which launched in 2002, and joined by several other NASA and international missions. Aura and Aqua have provided data for over two decades of multidisciplinary Earth science discovery and enhancement.
Both current and former Aura instrument PIs gave brief remarks. Each discussed Aura’s scientific legacy and their instrument’s contributions. They thanked their engineering teams for the successful development and operation of their instruments, and the members of the instrument science teams for developing the algorithms, discovering new science, and demonstrating how the science will serve the public. The PIs were particularly grateful that their instruments or the variants thereof will continue to fly on current and/or future NASA science missions or on international operational satellites.
Steve Platnick
EOS Senior Project Scientist
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Last Updated Nov 14, 2024 Related Terms
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By NASA
Earth Observer Earth Home Earth Observer Home Editor’s Corner Feature Articles Meeting Summaries News Science in the News Calendars In Memoriam More Archives 22 min read
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.
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.
In Memoriam: Johan de Vries
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.
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.
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.
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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Last Updated Nov 12, 2024 Related Terms
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By NASA
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Preparations for Next Moonwalk Simulations Underway (and Underwater)
A SWOT data visualization shows water on the northern side of Greenland’s Dickson Fjord at higher levels than on the southern side on Sept. 17, 2023. A huge rockslide into the fjord the previous day led to a tsunami lasting nine days that caused seismic rumbling around the world. NASA Earth Observatory Data from space shows water tilting up toward the north side of the Dickson Fjord as it sloshed from south to north and back every 90 seconds for nine days after a 2023 rockslide.
The international Surface Water and Ocean Topography (SWOT) satellite mission, a collaboration between NASA and France’s CNES (Centre National d’Études Spatiales), detected the unique contours of a tsunami that sloshed within the steep walls of a fjord in Greenland in September 2023. Triggered by a massive rockslide, the tsunami generated a seismic rumble that reverberated around the world for nine days. An international research team that included seismologists, geophysicists, and oceanographers recently reported on the event after a year of analyzing data.
The SWOT satellite collected water elevation measurements in Dickson Fjord on Sept. 17, 2023, the day after the initial rockslide and tsunami. The data was compared with measurements made under normal conditions a few weeks prior, on Aug. 6, 2023.
In the data visualization (above), colors toward the red end of the scale indicate higher water levels, and blue colors indicate lower-than-normal levels. The data suggests that water levels at some points along the north side of the fjord were as much as 4 feet (1.2 meters) higher than on the south.
“SWOT happened to fly over at a time when the water had piled up pretty high against the north wall of the fjord,” said Josh Willis, a sea level researcher at NASA’s Jet Propulsion Laboratory in Southern California. “Seeing the shape of the wave — that’s something we could never do before SWOT.”
In a paper published recently in Science, researchers traced a seismic signal back to a tsunami that began when more than 880 million cubic feet of rock and ice (25 million cubic meters) fell into Dickson Fjord. Part of a network of channels on Greenland’s eastern coast, the fjord is about 1,772 feet (540 meters) deep and 1.7 miles (2.7 kilometers) wide, with walls taller than 6,000 feet (1,830 meters).
Far from the open ocean, in a confined space, the energy of the tsunami’s motion had limited opportunity to dissipate, so the wave moved back and forth about every 90 seconds for nine days. It caused tremors recorded on seismic instruments thousands of miles away.
From about 560 miles (900 kilometers) above, SWOT uses its sophisticated Ka-band Radar Interferometer (KaRIn) instrument to measure the height of nearly all water on Earth’s surface, including the ocean and freshwater lakes, reservoirs, and rivers.
“This observation also shows SWOT’s ability to monitor hazards, potentially helping in disaster preparedness and risk reduction,” said SWOT program scientist Nadya Vinogradova Shiffer at NASA Headquarters in Washington.
It can also see into fjords, as it turns out.
“The KaRIn radar’s resolution was fine enough to make observations between the relatively narrow walls of the fjord,” said Lee-Lueng Fu, the SWOT project scientist. “The footprint of the conventional altimeters used to measure ocean height is too large to resolve such a small body of water.”
More About SWOT
Launched in December 2022 from Vandenberg Space Force Base in California, SWOT is now in its operations phase, collecting data that will be used for research and other purposes.
The SWOT satellite was jointly developed by NASA and CNES, with contributions from the Canadian Space Agency (CSA) and the UK Space Agency. NASA’s Jet Propulsion Laboratory, managed for the agency by Caltech in Pasadena, California, leads the U.S. component of the project. For the flight system payload, NASA provided the KaRIn instrument, a GPS science receiver, a laser retroreflector, a two-beam microwave radiometer, and NASA instrument operations. CNES provided the Doppler Orbitography and Radioposition Integrated by Satellite (DORIS) system, the dual frequency Poseidon altimeter (developed by Thales Alenia Space), the KaRIn radio-frequency subsystem (together with Thales Alenia Space and with support from the UK Space Agency), the satellite platform, and ground operations. CSA provided the KaRIn high-power transmitter assembly. NASA provided the launch vehicle and the agency’s Launch Services Program, based at Kennedy Space Center in Florida, managed the associated launch services.
To learn more about SWOT, visit:
https://swot.jpl.nasa.gov
News Media Contacts
Jane J. Lee / Andrew Wang
Jet Propulsion Laboratory, Pasadena, Calif.
818-354-0307 / 626-379-6874
jane.j.lee@jpl.nasa.gov / andrew.wang@jpl.nasa.gov
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Last Updated Oct 31, 2024 Related Terms
SWOT (Surface Water and Ocean Topography) Earth Earth Science Earth Science Division Jet Propulsion Laboratory Explore More
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