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Summary of the 10th DSCOVR EPIC and NISTAR Science Team Meeting
Introduction
The 10th Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Camera (EPIC) and National Institute of Standards and Technology (NIST) Advanced Radiometer [NISTAR] Science Team Meeting (STM) was held October 16–18, 2024. Over 50 scientists attended, most of whom were from NASA’s Goddard Space Flight Center (GSFC), with several participating from other NASA centers, U.S. universities, and U.S. Department of Energy laboratories. There was one international participant – from Estonia. A full overview of DSCOVR’s Earth-observing instruments was published in a previous article in The Earth Observer and will not be repeated here. This article provides the highlights of the 2024 meeting. The meeting agenda and full presentations can be downloaded from GSFC’s Aura Validation Data Center.
Opening Presentations
The opening session of the 10th DSCOVR STM was special. Former U.S., Vice President Al Gore attended the opening session and gave a presentation at the panel discussion “Remote Sensing and the Future of Earth Observations” – see Photo. Gore was involved in the early days of planning the DSCOVR mission, which at that time was known as Triana. He reminisced about his involvement and praised the team for the work they’ve done over the past decade to launch and maintain the DSCOVR mission. Following the STM Opening Session, Gore spoke at a GSFC Engage session in Building 3 later that afternoon on the same topic, but before a wider audience. [Link forthcoming.]
Following Gore’s remarks, the remainder of the opening session consisted of a series of presentations from DSCOVR mission leaders and representatives from GSFC and National Oceanic and Atmospheric Administration (NOAA). Thomas Neumann [GSFC, Earth Sciences Division (ESD)—Deputy Director] opened the meeting and welcomed Vice President Gore and the STM participants on behalf of the ESD. Adam Szabo [GSFC—DSCOVR Project Scientist] briefly reported that the spacecraft was still in “good health.” The EPIC and NISTAR instruments on DSCOVR continue to return their full science observations. He also gave an update on DSCOVR Space Weather research. Alexander Marshak [GSFC—DSCOVR Deputy Project Scientist] briefly described DSCOVR mission history and the science results based on DSCOVR observations from the first Sun–Earth Lagrange point (hereinafter, the L1 point). He also summarized the major EPIC and NISTAR results to date. At this time, more than 125 papers related to DSCOVR are listed on the EPIC website. Elsayed Talaat [NOAA, Office of Space Weather observations—Director] discussed the future of Earth and space science studies from the L1 point.
Photo. Former U.S. Vice President Al Gore spoke at the opening session of the 10th DSCOVR Science Team Meeting. This photo shows Gore together with Makenzie Lystrup [NASA’s Goddard Space Flight Center (GSFC)—Center Director], Christa Peters-Lidard [GSFC, Director of the Science and Exploration Directorate], Elsayed Talaat [National Oceanic and Atmospheric Administration (NOAA)—Director of the Office of Space Weather Observations], Dalia Kirschbaum [GSFC—Director of Earth Sciences], other GSFC management, and members of the DSCOVR Science Team. Photo credit: Katy Comber (GSFC) Updates on DSCOVR Operations
The DSCOVR mission components continue to function nominally. The meeting was an opportunity to update participants on progress over the past year on several fronts, including data acquisition, processing, and archiving, and release of new versions of several data products. The number of people using DSCOVR data continues to increase, with a new Science Outreach Team having been put in place to aid users in several aspects of data discovery, access, and user friendliness.
Amanda Raab [NOAA, DSCOVR Mission Operations and Systems] reported on the current status of the DSCOVR mission. She also discussed spacecraft risks and issues such as memory fragmentation and data storage task anomalies but indicated that both these issues have been resolved.
Hazem Mahmoud [NASA’s Langley Research Center (LaRC)] discussed the work of the Atmospheric Science Data Center (ASDC), which is based at LaRC. He showed DSCOVR mission metrics since 2015, focusing on data downloads and the global outreach of the mission. He noted that there has been a significant rise in the number of downloads and an increasing diversity of countries accessing ozone (O3), aerosol, and cloud data products. Mahmoud also announced that the ASDC is transitioning to the Amazon Web Services cloud, which will further enhance global access and streamline DSCOVR data processing.
Karin Blank [GSFC] covered the discovery of a new type of mirage that can only be seen in deep space from EPIC. The discussion included the use of a ray tracer in determining the origin of the phenomenon, and under what conditions it can be seen.
Alexander Cede [SciGlob] and Ragi Rajagopalan [LiftBlick OG] gave an overview of the stability of the EPIC Level-1A (L1A) data over the first decade of operation. They explained that the only observable changes in the EPIC calibration are to the dark count and flat field can – and that these changes can be entirely attributed to the temperature change of the system in orbit compared to prelaunch conditions. No additional hot or warm pixels have emerged since launch and no significant sensitivity drifts have been observed. The results that Cede and Rajagopalan showed that EPIC continues to be a remarkably stable instrument, which is attributed to a large extent to its orbit around the L1 point, which is located outside the Earth’s radiation belts and thus an extremely stable temperature environment. Consequently, in terms of stability, the L1 point is far superior to other Earth observation points, e.g., ground-based, low-Earth orbit (LEO), polar orbit, or geostationary Earth orbit (GEO).
Marshall Sutton [GSFC] discussed the state of the DSCOVR Science Operation Center (DSOC). He also talked about processing EPIC Level-1 (L1) data into L2 science products, daily images available on the EPIC website, and special imaging opportunities, e.g., volcanic eruptions.
EPIC Calibration
After 10 years of operation in space, the EPIC instrument on DSCOVR continues to be a remarkably stable instrument. The three presentations describe different ways that are used to verify the EPIC measurements remain reliable.
Conor Haney [LaRC] reported on anomalous outliers during February and March 2023 from the broadband shortwave (SW) flux using EPIC L1B channel radiances. To ensure that these outliers were not a result of fluctuations in the EPIC L1B channel radiances, both the EPIC radiance measurements and coincident, ray-matched radiance measurements from the Visible Infrared Imaging Radiometer Suite (VIIRS), on the Suomi National Polar-orbiting Partnership (Suomi NPP) platform, were processed using the same deep convective cloud invariant target (DCC-IT) algorithm. This analysis confirmed that the anomalous behavior was due to the DCC-IT algorithm – and not because of fluctuations in the EPIC L1B channel radiances. The improved DCC-IT methodology was also applied to the EPIC L1B radiances. The results indicate that the EPIC record is quite stable with a lower uncertainty than when processed using the previous DCC-IT methodology.
Igor Geogdzhaev [NASA’s Goddard Institute for Space Studies (GISS)/Columbia University] reported that EPIC Visible–Near Infrared (VIS-NIR) calibration based on VIIRS (on Suomi NPP) data has showed excellent stability, while VIIRS (on NOAA-20 and -21) derived gains agree to within 1–2%. Preliminary analysis showed continuity in the gains derived from Advanced Baseline Imager (ABI) data. (ABI flies on NOAA’s two operational Geostationary Operational Environmental Satellite–Series R satellites – GOES-17 and GOES-18.
Liang–Kang Huang [Science Systems and Applications, Inc. (SSAI)] reported on updates to the EPIC ultraviolet (UV) channel sensitivity time dependences using Sun-normalized radiance comparisons between EPIC and measurements from the Ozone Mapping and Profiler Suite (OMPS) Nadir Mapper (NM) on Suomi NPP, with coinciding footprints and solar/satellite angles. Huang’s team determined vignetting factors in the sensitivity calibration between 2021–2024, as a function of charge coupled device (CCD) pixel radius and pixel polar angles, using special lunar measurement sequences.
NISTAR Status and Science with Its Observations
The NISTAR instrument remains fully functional and continues its uninterrupted data record. The NISTAR-related presentations during this meeting included more details on specific topics related to NISTAR as well as on efforts to combine information from both EPIC and NISTAR.
Steven Lorentz [L-1 Standards and Technology, Inc.] reported that the NISTAR on DSCOVR has been measuring the irradiance from the sunlit Earth in three bands for more than nine years. The three bands measure the outgoing total and reflected-solar radiation from Earth at a limited range of solar angles. To compare the long-term stability of EPIC and NISTAR responses, researchers developed a narrowband to wideband conversion model to allow the direct comparison of the EPIC multiband imagery and NISTAR SW – see Figure 1 – and silicon photodiode channels. Lorentz presented daily results spanning several years. The comparison employed different detectors from the same spacecraft – but with the same vantage point – thereby avoiding any model dependent orbital artifacts.
Figure 1. NISTAR daily average shortwave (SW) radiance plotted for each year from 2017–2024. The results indicated a 10% increase in the shortwave radiance as the backscattering angle approaches 178° in December 2020. A 6% increase is noted in September of the same year. Figure credit: Steven Lorentz (L-1 Standards and Technology) Clark Weaver [University of Maryland, College Park (UMD)] used spectral information from the SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY), which flew on the European Space Agency’s (ESA) Envisat satellite from 2002–2012, to fill EPIC spectral gaps. He reported on construction of a composite height resolution spectrum that was spectrally integrated to produce SW energy. Weaver explained that he compared the EPIC reflected SW with four-hour averages from Band 4 on NISTAR. He used spectral information from SCIAMACHY to fill in gaps. Weaver also discussed results of a comparison of area integrated EPIC SW energy with observations from NISTAR .
Andrew Lacis [GISS] reported on results of analysis of seven years of EPIC-derived planetary albedo for Earth, which reveal global-scale longitudinal variability occurring over a wide range of frequencies – with strong correlation between nearby longitudes and strong anticorrelation between diametrically opposed longitudes. This behavior in the Earth’s global-scale energy budget variability is fully corroborated by seven years of NISTAR silicon photodiode measurements, which view the Earth with 1º longitudinal resolution. This analysis establishes the DSCOVR mission EPIC/NISTAR measurements as a new and unmatched observational data source for evaluating global climate model performance– e.g., see Figure 2.
Figure 2. This graph shows the diurnal variation in planetary albedo as measured by EPIC for five different eight-day-Blurred Meridians relative to Global Mean for 2021 [left] and 2022 [right]. Figure credit: Andrew Lacis [GISS] Wenying Su [LaRC] discussed global daytime mean SW fluxes within the EPIC field of view produced from January 2016–June 2024. These quasi-hourly SW fluxes agree very well with the Synoptic data product from the Clouds and the Earth’s Radiant Energy System (CERES) instruments (currently flying on the Terra and Aqua, Suomi NPP, and NOAA-20 platforms) with the root mean square errors (rmse) less than 3 W/m2. This SW flux processing framework will be used to calculate NISTAR SW flux when Version 4 (V4) of the NISTAR radiance becomes available. Su noted that SW fluxes from EPIC are not suitable to study interannual variability as the magnitude of EPIC flux is sensitive to the percentage of daytime area visible to EPIC.
Update on EPIC Products and Science Results
EPIC has a suite of data products available. The following subsections summarize content during the DSCOVR STM related to these products. The updates focus on several data products and the related algorithm improvements.
Total Column Ozone
Jerry Ziemke [Morgan State University (MSU), Goddard Earth Sciences Technology and Research–II (GESTAR II)] and Natalya Kramarova [GSFC] reported that tropospheric O3 from DSCOVR EPIC shows anomalous reductions of ~10% throughout the Northern Hemisphere (NH) starting in Spring 2020 that continues to the present. The EPIC data, along with other satellite-based (e.g., Ozone Monitoring Instrument (OMI) on NASA’s Aura platform) and ground-based (e.g., Pandora) data, indicate that the observed NH reductions in O3 are due to combined effects from meteorology and reduced pollution, including reduced shipping pollution in early 2020 (during COVID) – see Figure 3. EPIC 1–2 hourly data are also used to evaluate hourly total O3 and derived tropospheric O3 from NASA’s Tropospheric Emissions: Monitoring of Pollution (TEMPO) geostationary instrument. Ziemke explained that comparison of TEMPO data with EPIC data has helped the researchers characterize a persistent latitude-dependent offset in TEMPO total O3 data of ~10–15% from south to north over the North American continent.
Figure 3. This dataset combines input from EPIC, OMPS, and OMI from 2004–2022. The onset of the COVID-19 pandemic in 2020 can be seen clearly in the data as it corresponds to a sudden drop in tropospheric column ozone by ~3 Dobson Units in the Northern Hemisphere. Figure credit: Jerry Ziemke (Morgan State University, GESTAR-II) Algorithm Improvement for Ozone and Sulfur Dioxide Products
Kai Yang [UMD] presented a comprehensive evaluation of total and tropospheric O3 retrievals, highlighting the long-term stability and high accuracy of EPIC measurements. He also validated EPIC’s volcanic sulfur dioxide (SO2) retrievals by comparing them with ground-based Brewer spectrophotometer measurements and summarized EPIC’s observations of SO2 from recent volcanic eruptions.
Simon Carn [University of Michigan] showed the first comparisons between the EPIC L2 volcanic SO2 product and SO2 retrievals from the Geostationary Environment Monitoring Spectrometer (GEMS) on the Korean GEO-Kompsat-2B satellite. GEMS observes East Asia as part of the new geostationary UV air quality (GEO-AQ) satellite constellation (which also includes TEMPO that observes North America and will include the Ultraviolet–Visible–Near Infrared (UVN) instrument on the European Copernicus Sentinel-4 mission, that will be launched in 2025 to observe Europe and surrounding areas) – but is not optimized for measurements of high SO2 columns during volcanic eruptions. EPIC SO2 data for the 2024 eruption of Ruang volcano in Indonesia are being used to validate a new GEMS volcanic SO2 product. Initial comparisons show good agreement between EPIC and GEMS before volcanic cloud dispersal and confirm the greater sensitivity of the hyperspectral GEMS instrument to low SO2 column amounts.
Aerosols
Alexei Lyapustin [GSFC] reported that the latest EPIC aerosols algorithm (V3) simultaneously retrieves aerosol optical depth, aerosol spectral absorption, and aerosol layer height (ALH) – achieving high accuracy. He showed that global validation of the single scattering albedo in the blue and red shows 66% and 81–95% agreement respectively, with Aerosol Robotic Network (AERONET) observations – which is within the expected error of 0.03 for smoke and dust aerosols. Lyapustin also reported on a comparison of EPIC aerosol data collected from 2015–2023 by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), which flew on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission. The results show that ALH is retrieved with rmse ~1.1 km (0.7 mi). ALH is unbiased over the ocean and is underestimated by 450 m (1470 ft) for the smoke and by 750 m (2460 ft) for the dust aerosols over land.
Myungje Choi and Sujung Go [both from University of Maryland, Baltimore County’s (UMBC), GESTAR II] presented results from a global smoke and dust characterization using Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. This study characterized smoke and dust aerosol properties derived from MAIAC EPIC processing, examining spectral absorption, ALH, and chemical composition (e.g., black and brown carbon). Regions with smoldering wildfires, e.g., North America and Siberia, exhibited high ALH and a significant fraction of brown carbon, while Central Africa showed lower ALH with higher black carbon emissions.
Omar Torres [GSFC] discussed how L1 DSCOVR-EPIC observations are being used to study air quality (i.e., tropospheric O3 and aerosols) globally. Torres noted that this application of EPIC-L1 observations is of particular interest in the Southern Hemisphere (SH) where, unlike over the NH, there are currently no space GEO-based air quality measurements – and no plans for them in the foreseeable future.
Hiren Jethva [MSU, GESTAR II] presented the new results of the aerosol optical centroid height retrieved from the EPIC Oxygen-B band observations. He described the algorithm details, showed retrieval maps, and reviewed the comparative analysis against CALIOP backscatter-weighted measurements. The analysis showed a good level of agreement with more than 70% of matchup data within 1–1.5 km (0.6–0.9 mi) difference.
Jun Wang [University of Iowa] presented his team’s work on advancing the second generation of the aerosol optical centroid height (AOCH) algorithm for EPIC. Key advancements included: constraining surface reflectance in aerosol retrieval using an EPIC-based climatology of surface reflectance ratios between 442–680 nm; incorporating a dynamic aerosol model to characterize aged smoke particles; and employing a spectral slope technique to distinguish thick smoke plumes from clouds. Results show that both atmospheric optical depth (AOD) and AOCH retrievals are improved in the second generation of AOCH algorithm.
Olga Kalashnikova [NASA/Jet Propulsion Laboratory (JPL)] reported on improving brown carbon evolution processes in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) model with EPIC products. She indicated that DSCOVR product evaluation, using lidar aerosol height measurements from CALIOP, led to an improved operational brown carbon product. To better resolve the temporal evolution of brown carbon, chemical transport models need to include more information about near-source fires.
Mike Garay [NASA/Jet Propulsion Laboratory (JPL)] discussed constraining near-source brown carbon emissions from 2024 Canadian ‘zombie’ fires with EPIC products. He reported that fires in British Columbia, Canada showed differences in brown carbon emission near the sources. Garay explained that their investigation has revealed that these differences were related to fire intensity and variations in vegetation/soil content.
Yuekui Yang [GSFC] presented work that examined the impact of Earth’s curvature consideration on EPIC cloud height retrievals. Biases under the Plane Parallel (PPL) assumption is studied by comparing results using the improved pseudo-spherical shell approximation. PPL retrievals in general bias high and for a cloud with height of 5 km (3 mi), the bias is about 6%.
Alfonso Delgado Bonal [UMBC] stated that the EPIC vantage point offers a unique opportunity to observe not only the current state of the Earth but also its temporal evolution. By capturing multiple observations of the planet throughout the day, EPIC enables statistical reconstruction of diurnal patterns in clouds and other atmospheric parameters. Bonal’s team focused their research on O3 (primarily tropospheric) over the U.S. to demonstrate the presence of a diurnal cycle in the western regions of the continental U.S. However, ground-based data from PANDORA for specific locations do not support these diurnal variations – underscoring the critical role of space-based O3 retrievals. The proposed methodology is not limited to clouds or O3 but is broadly applicable to other EPIC measurements for the dynamic nature of our planet.
Elizabeth Berry [Atmospheric and Environmental Research (AER)] presented results from a coincident DSCOVR–CloudSat dataset [covering 2015–2020]. Cloud properties (e.g., cloud height and optical depth) from DSCOVR and CloudSat are moderately correlated and show quite good agreement given differences in the instruments sensitivities and footprints. Berry explained that a machine-learning model trained on the coincident data demonstrates high accuracy at predicting the presence of vertical cloud layers. However, precision and recall metrics highlight the challenge of predicting the precise location of cloud boundaries.
Anthony Davis [JPL] presented a pathway toward accurate estimation of the cloud optical thickness (COT) of opaque clouds and cloud systems, e.g., supercells, mesoscale convective complexes, and tropical cyclones (TCs). He described the approach, which uses differential oxygen absorption spectroscopy (DOAS) that has resolving power greater than 104 – which is comparable to that of the high-resolution spectrometers on NASA’s Orbiting Carbon Observatory–2 (OCO-2) – but is based upon the cloud information content of EPIC’s O2 A- and B-band radiances. Unlike the current operational retrieval of COT – which uses data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua – the DOAS-based technique does not saturate at COT exceeding ~60. According to a popular TC model with two-moment microphysics, COT in a tropical storm or hurricane can reach well into the hundreds, sometimes exceeding 1000. Davis said that once the new COT estimates become available, they will provide new observational constraints on process and forecast models for TCs.
Ocean
Robert Frouin [Scripps Institution of Oceanography, University of California] discussed ocean surface radiation products derived from EPIC data. He explained that significant advancements have been achieved in processing and evaluating ocean biology and biogeochemistry products derived from EPIC imagery. V1 updates enhanced accuracy by integrating Modern-Era Retrospective analysis for Research and Applications V2 (MERRA-2) ancillary data and refining calculations for atmospheric and surface parameters. Frouin introduced several diurnal products, including hourly photosynthetically active radiation (PAR) fluxes, spectral water reflectance, and chlorophyll-a concentrations. He said that these new MODIS-derived products have been validated through comparisons with data from the Advanced Himawari Imager on the Japanese Himawar–8 and –9 satellites. In order to address the gaps in these diurnal products, Frouin explained that the team developed a convolutional neural network that has been used effectively to reconstruct missing PAR values with high accuracy.
Vegetation
Yuri Knyazikhin [Boston University] reported on the status of the Vegetation Earth System Data Record (VESDR) that provides a variety of parameters including: Leaf Area Index (LAI), diurnal courses of Normalized Difference Vegetation Index (NDVI), Sunlit LAI (SLAI), Fraction of incident Photosynthetically Active Radiation (FPAR) absorbed by the vegetation, Directional Area Scattering Function (DASF), Earth Reflector Type Index (ERTI), and Canopy Scattering Coefficient (CSC). Knyazikhin discussed analysis of the diurnal and seasonal variations of these quantities. EPIC LAI and FPAR are consistent with MODIS-derived measurements of the same parameters.
Jan Pisek [University of Tartu/Tartu Observatory, Estonia] discussed efforts to derive leaf inclination information from EPIC data. The very first evaluation over Tumbarumba site (in New South Wales, Australia) showed that the angular variation in parameters obtained from EPIC reflects the expected variations due to the erectophile vegetation present at the site.
Sun Glint
Tamás Várnai [UMBC, JCET] discussed EPIC observations of Sun glint from ice clouds. The cloud glints come mostly from horizontally oriented ice crystals and have strong impact in EPIC cloud retrievals. Várnai reported that the EPIC glint product is available from the ASDC – see Figure 4. Glint data can help reduce the uncertainties related to horizontally oriented ice crystals and yield additional new insights about the microphysical and radiative properties of ice clouds.
Figure 4. [top row] EPIC glint mask examples over land in [left to right] Paraguay, Sudan, Thailand, and Brazil. [bottom row] The corresponding EPIC glint mask for each image on the top row indicates the band (red, green and blue) and the size of sun glint for each of them. Figure credit: Tamás Várnai (University of Maryland, Baltimore County) Alexander Kostinski [Michigan Technology University] explained that because they detected climatic signals (i.e., longer-term changes and semi-permanent features, e.g., ocean glitter), they developed a technique to suppress geographic “noise” in EPIC images that involves introducing temporally (monthly) and conditionally (classifying by surface/cover type, e.g., land, ocean, clouds) averaged reflectance images – see Figure 5. The resulting images display seasonal dependence in a striking manner. Additionally, cloud-free, ocean-only images highlight prominent regions of ocean glitter.
Figure 5. Monthly reflectances for clear land pixels. Earth masquerading as Jupiter; latitudinal bright bands are caused by features such as the Sahara and Antarctica. Black spots are due to the lack or dearth of clear land pixels at that latitude. Repeated spots within latitudinal bands reflect roughly bi-hourly image sampling. Figure credit: Alexander Kostinski (Michigan Technology University); from a 2024 paper published in Frontiers of Remote Sensing Jiani Yang [Caltech] reported that spatially resolving light curves from DSCOVR is crucial for evaluating time-varying surface features and the presence of an atmosphere. Both of these features are essential for sustaining life on Earth – and thus can be used to assess the potential habitability of exoplanets. Using epsilon machine reconstruction, the statistical complexity from the time series data of these light curves can be calculated. The results show that statistical complexity serves as a reliable metric for quantifying the intricacy of planetary features. Higher levels of planetary complexity qualitatively correspond to increased statistical complexity and Shannon entropy, illustrating the effectiveness of this approach in identifying planets with the most dynamic characteristics.
Other EPIC Science Results
Guoyong Wen [MSU, GESTAR II] analyzed the variability of global spectral reflectance from EPIC and the integrated broadband reflectance on different timescales. He reported that on a diurnal timescale, the global reflectance variations in UV and blue bands are statistically similar – and drastically different from those observed in longer wavelength bands (i.e., green to NIR). The researchers also did an analysis of monthly average results and found that temporal averaging of the global reflectance reduces the variability across the wavelength and that the variability of broadband reflectance is similar to that for the red band on both timescales. These results are mainly due to the rotation of the Earth on diurnal timescale and the change of the Earth’s tilt angle.
Nick Gorkavyi [Science Systems and Applications, Inc. (SSAI)] reported that EPIC – located at the L1 point, 1.5 million km (0.9 million mi) away from Earth – can capture images of the far side of the Moon in multiple wavelengths. These images, taken under full solar illumination, can be used to calibrate photographs obtained by lunar artificial satellites. Additionally, he discussed the impact of lunar libration – the changing view of the Moon from Earth, or it’s apparent “wobble” – on Earth observations from the Moon.
Jay Herman [UMBC] discussed a comparison of EPIC O3 with TEMPO satellite and Pandora ground-based measurement. The results show that total column O3 does not have a significant photochemical diurnal variation. Instead, the daily observed diurnal variation is caused by weather changes in atmospheric pressure. This measurement result agrees with model calculations.
Conclusion
Alexander Marshak, Jay Herman, and Adam Szabo led a closing discussion with ST participants on how to make the EPIC and NISTAR instruments more visible in the community. It was noted that the EPIC website now allows visitors to observe daily fluctuations of aerosol index, cloud fraction, cloud height, and the ocean surface – as observed from the L1 point. More daily products, (e.g., aerosol height and sunlit leaf area index) will be added soon, which should attract more users to the website.
Overall, the 2023 DSCOVR EPIC and NISTAR STM was successful. It provided an opportunity for participants to learn the status of DSCOVR’s Earth-observing instruments, EPIC and NISTAR, the status of recently released L2 data products, and the science results being achieved from the L1 point. As more people use DSCOVR data worldwide, the ST hopes to hear from users and team members at its next meeting. The latest updates from the mission can be found on the EPIC website.
Alexander Marshak
NASA’s Goddard Space Flight Center
alexander.marshak@nasa.gov
Adam Szabo
NASA’s Goddard Space Flight Center
adam.szabo@nasa.gov
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Last Updated Feb 14, 2025 Related Terms
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NASA’s Swift Reaches 20th Anniversary in Improved Pointing Mode
After two decades in space, NASA’s Neil Gehrels Swift Observatory is performing better than ever thanks to a new operational strategy implemented earlier this year. The spacecraft has made great scientific strides in the years since scientists dreamed up a new way to explore gamma-ray bursts, the most powerful explosions in the universe.
“The idea for Swift was born during a meeting in a hotel basement in Estes Park, Colorado, in the middle of a conference,” said John Nousek, the Swift mission director at Pennsylvania State University in State College. “A bunch of astrophysicists got together to brainstorm a mission that could help us solve the problem of gamma-ray bursts, which were a very big mystery at the time.”
Watch to learn how NASA’s Neil Gehrels Swift Observatory got its name.
NASA’s Goddard Space Flight Center Gamma-ray bursts occur all over the sky without warning, with about one a day detected on average. Astronomers generally divide these bursts into two categories. Long bursts produce an initial pulse of gamma rays for two seconds or more and occur when the cores of massive stars collapse to form black holes. Short bursts last less than two seconds and are caused by the mergers of dense objects like neutron stars.
But in 1997, at the time of that basement meeting, the science community disagreed over the origin models for these events. Astronomers needed a satellite that could move quickly to locate them and move to point additional instruments at their positions.
What developed was Swift, which launched Nov. 20, 2004, from Complex 17A at what is now Cape Canaveral Space Force Station in Florida. Originally called the Swift Observatory for its ability to quickly point at cosmic events, the mission team renamed the spacecraft in 2018 after its first principal investigator Neil Gehrels.
Swift uses several methods for orienting and stabilizing itself in space to study gamma-ray bursts.
Sensors that detect the Sun’s location and the direction of Earth’s magnetic field provide the spacecraft with a general sense of its location. Then, a device called a star tracker looks at stars and tells the spacecraft how to maneuver to keep the observatory precisely pointed at the same position during long observations.
Swift uses three spinning gyroscopes, or gyros, to carry out those moves along three axes. The gyros were designed to align at right angles to each other, but once in orbit the mission team discovered they were slightly misaligned. The flight operations team developed a strategy where one of the gyros worked to correct the misalignment while the other two pointed Swift to achieve its science goals.
The team wanted to be ready in case one of the gyros failed, however, so in 2009 they developed a plan to operate Swift using just two.
Swift orbits above Earth in this artist’s concept. NASA’s Goddard Space Flight Center Conceptual Image Lab Any change to the way a telescope operates once in space carries risk, however. Since Swift was working well, the team sat on their plan for 15 years.
Then, in July 2023, one of Swift’s gyros began working improperly. Because the telescope couldn’t hold its pointing position accurately, observations got progressively blurrier until the gyro failed entirely in March 2024.
“Because we already had the shift to two gyros planned out, we were able to quickly and thoroughly test the procedure here on the ground before implementing it on the spacecraft,” said Mark Hilliard, Swift’s flight operations team lead at Omitron, Inc. and Penn State. “Actually, scientists have commented that the accuracy of Swift’s pointing is now better than it was since launch, which is really encouraging.”
For the last 20 years, Swift has contributed to groundbreaking results — not only for gamma-ray bursts but also for black holes, stars, comets, and other cosmic objects.
“After all this time, Swift remains a crucial part of NASA’s fleet,” said S. Bradley Cenko, Swift’s principal investigator at NASA’s Goddard Space Flight Center in Greenbelt, Maryland. “The satellite’s abilities have helped pioneer a new era of astrophysics called multimessenger astronomy, which is giving us a more well-rounded view of how the universe works. We’re looking forward to all Swift has left to teach us.”
Swift is a key part of NASA’s strategy to look for fleeting and unpredictable changes in the sky with a variety of telescopes that use different methods of studying the cosmos.
Goddard manages the Swift mission in collaboration with Penn State, the Los Alamos National Laboratory in New Mexico, and Northrop Grumman Space Systems in Dulles, Virginia. Other partners include the University of Leicester and Mullard Space Science Laboratory in the United Kingdom, Brera Observatory in Italy, and the Italian Space Agency.
Download high-resolution images on NASA’s Scientific Visualization Studio
By Jeanette Kazmierczak
NASA’s Goddard Space Flight Center, Greenbelt, Md.
Media Contact:
Claire Andreoli
301-286-1940
claire.andreoli@nasa.gov
NASA’s Goddard Space Flight Center, Greenbelt, Md.
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Last Updated Nov 20, 2024 Editor Jeanette Kazmierczak Location Goddard Space Flight Center Related Terms
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By NASA
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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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Summary of the 10th SWOT Applications Workshop
Introduction
The tenth Surface Water Ocean Topography (SWOT) Applications Workshop took place December 7–8, 2023 at the California Institute of Technology Keck Institute for Space Studies. The meeting was organized to highlight the work and project status of the SWOT Early Adopters (EAs). NASA’s Applied Sciences Program (which is now housed within the NASA Earth Science in Action element of NASA’s Earth Science Division), the SWOT Project, the Centre National d’Etudes Spatiales (CNES’s), or French space agency’s SWOT Downstream Program, the SWOT Applications Working Group (SAWG), and members of the SWOT science community have coordinated efforts in support of the SWOT Applications Program since 2010.
The 2023 meeting, which was the latest in an annual series organized by the SAWG, welcomed over 100 participants online and in person during the two days, with many joining virtually across different time zones, to share their project status and explore the many facets of operational and applied uses of SWOT data. Presentations covered the current state of and near-term plans for using SWOT data products and highlighted related applied science efforts focused on SWOT. A significant focus explored the use of the new mission data to improve hydrology and ocean models.
After a brief introduction to SWOT and its instruments and a short update on the SWOT EAs, the remainder of this article contains a select group of summaries from EA projects. The complete meeting agenda and a list of presentations are available on the 10th SWOT Application Meeting website.
SWOT Mission Overview and Update
SWOT launched December 16, 2022, from Vandenberg Space Force Base in California. After a successful checkout of the satellite systems, instruments, and data systems, SWOT entered Science Mode on July 21, 2023. It continues to operate nominally as of this writing. A detailed account of SWOT Significant Events since launch is available online.
The goal of SWOT is to make the first global survey of Earth’s surface water, observe the fine details of the ocean’s surface topography, and measure how water bodies change over time. The international partnership is led by NASA and CNES, with contributions from the U.K. Space Agency and the Canadian Space Agency.
The SWOT Science Team is made up of researchers from all over the world with expertise in oceanography and hydrology. Together the team is using SWOT data to study a range of topics, including availability of Earth’s freshwater resources and our changing ocean and coasts. Studies like these are crucial to meet society’s growing needs for clean air and water, to help prepare for and mitigate impacts of extreme weather, and to help the world adapt to long-term changes in climate on continental scales.
SWOT’s payload has been designed to provide the data that allow the SWOT team to study the topics listed in the previous paragraph. While the complete compliment of instruments is listed on the website, the three most relevant to the current article are described here.
Ka-band Radar Interferometer (KaRIn). This state-of-the-art, wide-swath, interferometric radar can measure the ocean, major lake, river, and wetland levels over a 120-km (75-mi) wide swath with a ~20-km (~12-mi) gap along nadir, which is filled by the Jason-class altimeter described below. KaRIn can operate in two modes: It uses low-resolution mode over the ocean with significant onboard processing to reduce data volume; and high-resolution mode over broad, primarily continental regions defined by the SWOT Science Team, where the focus is on hydrological studies as opposed to oceanographic ones. Jason-class Altimeter (nadir altimeter). The altimeter flying on SWOT is similar to those flown on the series of ocean surface topography missions that have operated since 1992, including the (TOPEX)/Poseidon, Jason-1, Jason-2, and Jason-3 missions, and the newest mission, Sentinel 6 Michael Freilich (S6MF), developed in partnership with the European Space Agency (ESA). The altimeter sends and receives signals that travel straight up and down beneath the spacecraft (or nadir-pointing) making it ideal to fill in the “gap” between KaRIn swaths. Microwave Radiometer (radiometer). This radiometer measures the amount of water vapor between SWOT and Earth’s surface. More water vapor present in the atmosphere slows down the radar signals and this instrument aids in correcting the signal. SWOT’s sea surface height (SSH) measurements will be added to the existing 32-year time series of measurements of oceans and large water bodies compiled by the series NASA–CNES altimetry missions listed above. With higher resolution observations, SWOT will enable hydrological research and applications and provide more detailed information on heights and extent of rivers, lakes, reservoirs, and wetlands, as well as derived parameters such as river discharge.
SWOT Early Adopter Overview and Update
The SWOT Early Adopters Program was initiated in 2018 to ensure community preparedness to make use of SWOT data. The program comprises a growing community working to incorporate SWOT data into the operational and applied science activities of their organizations – see Figure 1. The current SWOT EA cohort spans surface hydrology and oceanography domains and organizations, including both U.S. and international private-sector companies, academia, nonprofits, operational agencies, state and national government organizations, and research communities.
Figure 1. Forty SWOT Early Adopter (EA) teams span the globe with a wide range of operational and applied science project topics. Figure credit: NASA The 2023 SWOT Applications Workshop offered an opportunity to assess how the SWOT user community is using the data in anticipation of future SWOT data reprocessing and releases. The 2023 meeting explored three themes: 1) planned and current operational and applied uses of SWOT data; 2) the current state of the data products and access to the data; and 3) a variety of other projects that may/will include SWOT data in their applications.
The first public release of SWOT data came in June 2023, with the release of nadir altimeter and radiometer data. These data had a head-start in processing due to the instrument and processing heritage. These early releases allowed the EA community to begin incorporating SWOT into their operational models and systems. A public release of beta pre-validated SWOT KaRIn data products took place in November 2023, and the subsequent public release of pre-validated SWOT KaRIn data products in February 2024. SWOT KaRIn, nadir altimeter, and radiometer products are now in operational production and routinely available.
Workshop Overview
This workshop focused on the achievements of the SWOT EAs, offering a platform to share their projects with the community as they transition from “early adoption” to simply “adoption” of SWOT as a valuable resource in their system management toolbox. In addition, the meeting provided a space for discussions, an increased community awareness of the gaps and challenges of incorporating SWOT data into operational and decision-support framework for models, modeling systems, and other operational uses. Feedback from these discussions – especially concerning the known limitations of SWOT data with respect to data latency and mission length – will be exceptionally useful to the SWOT Project and Applications Teams.
Meeting Welcome and “Keynote” Presentations
Brad Doorn [NASA Headquarters (HQ)—Programmatic Lead], Annick Sylvestre-Baron [CNES—Programmatic Lead], Parag Vaze [JPL—SWOT Project Manager], and Pierre Sengenes [CNES—Project Lead] gave remarks to open the meeting. They welcomed attendees on behalf of NASA and CNES.
The first morning session closed with two highly relevant and illuminating presentations. Jinbo Wang [JPL] spoke about SWOT KaRIn performance and calibration/validation (Cal/Val) activities. Curtis Chen [JPL] detailed critical and important proclivities of KaRIn data products that EAs may find beneficial as they interpret data results. Understanding the information in Chen’s talk is critical for those planning to use the data.
SWOT Early Adopter Project Updates
The EA project summaries selected for this article provide an overview of the range and depth of the extensive work accomplished by the SWOT EA community to date. These examples illustrate the potential of SWOT data as a tool to manage surface water resources and forecast ocean and coastal conditions via operational systems in the coming years.
Daniel Moreira [Brazil Geological Society (BGS)—Project Investigator] explained that the current gauge network on rivers across the Amazon basin is limited. SWOT data offers unprecedented spatial and temporal coverage of water storage processes and may be beneficial to prepare for floods and extreme events in the basin. Moreira’s group has compared several sites using Global Navigation Satellite System data and a gauge station elevation time series with very good results. In addition, BGS maintains a weekly water level report and a web application that leverages satellite altimetry data from the S6MF and Jason-3 missions for comparison across the Amazon Basin. BGS plans to produce discharge datasets over the Amazon using altimetry.
Isabel Houghton [Sofar Ocean] introduced the Sofar Ocean ship route optimization and navigational safety platform, incorporating 10-day, data-assimilating marine weather forecasts. That data includes significant wave height estimates from both the Sofar spotter buoy network and estimates derived from nadir altimeters on NASA’s S6MF and Jason-3 missions and the joint CNES–Indian Space Research Agency (ISRO) Satellite with ARgos and ALtiKa (SARAL) satellites. (Argos collects data from a floating oceanic buoy network with the same name that CNES operates; AltiKa is a CNES-contributed Ka-band altimeter.) TheWaveWatch III model improves on the forecast through the addition of altimeter data. Houghton explained that Sofar Ocean is in the preliminary stages of using SWOT significant wave height data in their model, which is less noisy than the predecessor altimeters reducing forecast error. Sofar expects SWOT to improve their observation numbers by 50–100% in a given 24-hour period. Additionally, Sofar plan to use KaRIn observations in an Earth system model under development to address waves, circulation, and atmosphere.
Robert Dudley [U.S. Geological Survey (USGS)] presented a project that involved the team integrating data from SWOT and in situ sources together to derive discharge and flow velocity for the Tanana and Yukon Rivers in Alaska. The USGS is collaborating with the Physical Oceanography Distributed Active Archive (PO.DAAC) to integrate SWOT in SatRSQ measurements to develop the Water Information from Space (WISP) dashboard to access time series of SWOT hydrology products. WISP is in development and not yet publicly available. When operational, it will enable comparisons with collocated, ground-gauged time series. WISP contains SWOT orbital ground tracks and will add the SWOT lake database in the future. The dashboard should be publicly available later in 2024.
Gregg Jacobs [U.S. Naval Research Laboratory (NRL)] explained how NRL has evaluated SWOT KaRIn SSH data accuracy and integrated it into ocean forecast models by characterizing along-track errors in early data products to determine the necessary corrections. Jacobs then explained how the team computed daily interpolation of nadir altimeter data at SWOT crossover locations. They found good agreement between the corrected SWOT estimates and interpolated SSH from nadir altimeters and conducted ocean forecast experiments on California SWOT crossover Cal/Val sites – see Figure 2. NRL has had success in assimilating KaRIn data at a resolution of 5 km (~3 mi).
Figure 2. Altimetry data collected over calibration/validation (Cal/Val) sites using traditional nadir altimeter data only [left], a combination of traditional nadir altimeter data and in situ observations [center], and a combination of traditional altimeter data and SWOT altimeter data. The dotted lines indicate the satellite ground track paths. Figure credit: U.S. Naval Research Laboratory Pierre Yves Le Traon [Mercator Ocean International (MOi)] explained that MOi is a non-profit that is now transforming into an intergovernmental organization. He began with a description of the Copernicus Marine Service, which is a long-term partnership between CNES, MOi, and a French company called Collecte Localisation Satellites (CLS) that focuses on ocean monitoring and forecasting. SWOT data will be used to constrain small scales in models – see Figure 3. The preliminary results are in good agreement with CNES Level-3 (L3) products. SWOT KaRIn data will be integrated into the operational Copernicus Marine Service operational forecast portfolio in 2025.
Figure 3. Both these maps show the root mean square (RMS) error in the SWOT 21-day phase data in sea level anomaly (SLA) over one month on the 1/12° Mercator Ocean global forecasting system The image pair contrasts the SLA RMS error without including SWOT data in the assimilation [left] versus when SWOT data are included in the assimilation [right]. Note that including SWOT data make smaller scale errors in the data become more apparent. Figure credit: Mercator Ocean International Guy Schumann [Water in Sight]explained this Swedish start-up company uses SWOT data to validate in situ gauge data in Malawi. Gauge readers and observers collect data at monitoring stations from south to north Malawi to support the government’s efforts in managing water and climate risks. They have used free Short Message Service and leveraged citizen science to develop a cloud platform for data access. For the next step, the project plans to integrate SWOT data into two-dimensional (2D) flood models. This EA project aims to address latency – time delay between collection and transmission of data – and interoperability challenges, enhancing hydrological network optimization as well as demonstrating the diverse complementary value of satellite observations. The group supports codesigned joint explorations, engagement activities, and technology alignment. The CNES hydroweb tool may be very useful in this endeavor, but Schumann acknowledges that there are interoperability challenges that need to be overcome.
Jerry Wegiel [NASA’s Goddard Space Flight Center] explained that the U.S. Air Force’s Weather Land Information System (LIS) is a software framework used by multiple agencies for simulating land/hydrology processes. The Global Hydrology Intelligence (GHI) system (rebranding of LIS) is a comprehensive framework for hydrologic analysis, forecasting, and projections across scales encompassing all aspects of water security and addressing significant hydro-intelligence gaps identified by the defense and national security communities. Integration of SWOT L2 products operationally into the LIS Hydrological Modeling and Analysis Platform (HyMAP) model is expected to improve the global hydrological model data analysis system, as well as improve extreme hydrological event monitoring, reduce forecasting uncertainty, and support water security conflicts.
Alexandre de Amorim Teixeira and Alexandre Abdalla Araujo [both at Agência Nacional de Águas e Saneamento Básico (ANA), or Brazilian National Water and Sanitation Agency] began by explaining that the ANA hydrography datasets [e.g., Base Hidrográfica Ottocodificada (BHO)] and water atlases [e.g., Base Hidrográfica Atlas-Estudos (BHAE)] have been extended using information from the SWOT River Database (SWORD) river reaches, which are roughly 10 km (~6 mi) SWORD-specified sections of a river, in Brazil – see Figure 4. By incorporating SWORD data into the BHAE, over 400,000 reaches have been identified – compared to 20,000 identified previously using SWORD alone. The latest version (6.2) of BHO will combine SWORD and BHAE data increasing numbers exponentially to nearly 5.5 million. The ANA EA project will use SWOT data to support water resource management in Brazil. ANA is working in collaboration with University Brasilia to integrate available gauge information on rivers and reservoirs to fulfill their mandate to determine and report on water availability in the country. They described a sophisticated hexagonal hierarchical geospatial indexing system that will support hydrological and hydrodynamical modeling and cross-validation. The team will use SWOT data pixel cloud or raster products to best serve their needs.
Figure 4. The Agência Nacional de Águas e Saneamento Básico’s (ANA) [Brazilian National Water and Sanitation Agency] SWOT Early Adopter project is extending hydrography datasets, e.g., Base Hidrográfica Ottocodificada (BHO) [top] and water atlases, e.g., Base Hidrográfica Atlas-Estudos (BHAE) [middle] using the SWOT data to produce the SWOT River Database (SWORD) product [bottom] that expands on the extent of the BHO hydrography dataset. Image credit: ANA Data Systems and Products for Early Adopters
In 2021, the SWOT Project Science Team made simulated datasets available for select hydrologic and oceanographic regions. These datasets shared many characteristics in common with future SWOT data products (e.g., formats, metadata, and data contents) and were intended to familiarize users with the expected SWOT science data products.
At this meeting, teams from both the NASA and CNES mission data system and data repositories shared timely and valuable information and updates with the EA community. The talks provided information and insight into what users can expect from SWOT products.
Lionel Zawadzki and Cyril Germineaud [both at CNES] described the use of SWOT data available from CNES through the AVISO (ocean and coastal) and hydroweb.next (hydrology and ocean) data portals. Systems supporting data access include data acquisition and production, data repositories, and ultimately cloud data access through thematic portals.
Catalina Taglialatela and Cassandra Nickles [both at JPL] discussed the use of KaRIn high-resolution and low-resolution SWOT data products available through PO.DAAC, which provides centralized, searchable access that is available using an in-cloud commercial web service through the NASA EarthData portal. The team demonstrated resources and tutorials available via the online PO.DAAC Cookbook: SWOT Chapter, as well as the new Hydrocron SWOT time series applications programming interface (API) for generating time series over water features identified in SWORD and SWODLR, which is a system for creating on-demand L2 SWOT raster products.
Shailen Desai [JPL] explained how KaRIn products depend on upstream orbit, attitude, and radiometer products for optimal accuracy. SWOT KaRIn, nadir altimeter, and radiometer products are now in operational production and routinely available. Product description documents and SWOT algorithm theoretical basis documents are all publicly available.
Curtis Chen [JPL] discussed how the SWOT science data system team have reduced complexities of the KaRIn measurements to ensure robust interpretation of the results. Knowledge of measurement details may be especially important in trying to interpret the pre-validated data products. During his presentation, Chen addressed practical aspects of interpreting KaRIn data products, including answers to frequently asked questions and tips to avoid confusion and misinterpretation in using the data.
Yannice Faugere [CNES] explained how CNES will assimilate SWOT data into Mercator Ocean with value-added elements, including multimission calibration, noise mitigation, and images that blend KaRIn and nadir instruments. A preliminary assessment of L4 products was conducted using one-day Cal/Val orbit measurements with promising results. Tests on 21-day data and an L4 data challenge for community feedback to compare mapping and validation methods are in process.
Complementary Projects
Participants spoke about a number of other projects and programs during the meeting. The selected presentations address elements relevant to SWOT applications.
Charon Birkett [NASA] discussed how SWOT data will be incorporated into the Global REservoir and LAke Monitor (G-REALM) and Global Water Measurements (GWM) portal, to integrate nadir radiometer and KaRIn measurements. G-REALM maintains a 30-plus-year time series of nadir altimeter data from the NASA/CNES reference missions for this measurement (i.e., Topex/Poseidon; Jason -1, -2, and -3; and S6MF) as well as the European Remote Sensing Satellite. GWM is focused on lakes and reservoirs, rivers, and wetland water levels to derive surface extents and storage change.
Stephanie Granger [JPL] introduced the Western Water Applications Office (WWAO), which provides NASA data, technology, and tools for water management to water managers in the western U.S. The WWAO team completes needs assessments for basins – a task complicated by the more than 100 agencies involved in water management activities in the western U.S. Granger identified several activities that could benefit from SWOT data, such as extreme event predictions and impacts, timely streamflow predictions at a sub-basin level, wet/dry indicators from streamflow monitoring, and flood plain mapping.
Babette Tchonang, Dimitris Menemenlis,and Matt Archer [all from JPL] presented a study that evaluates the feasibility of applying the Estimating the Circulation and Climate of the Ocean 4-Dimensional Variational (MITgcm-ECCO 4DVAR) data assimilation framework to a sub-mesoscale resolving model [grid resolution of 1 km (~0.6 mi)] in preparation for future studies to assimilate SSH measurements from SWOT. Two model solutions are nested within the global 1/12° Hybrid Coordinate Ocean Model (HYCOM)/Navy Coupled Ocean Data Assimilation (NCODA) analysis. Comparing the two model solutions against assimilated and withheld in situ observations indicates that the MITgcm-ECCO 4DVAR framework can be applied to the reconstruction of sub-mesoscale ocean variability. This data assimilation system is now being used by the Scripps Institution of Oceanography to support SWOT post-launch activities.
Matt Bonnema [JPL] presented the Observational Products for End-Users from Remote Sensing Analysis (OPERA) project, which produces a suite of surface water extent products, such as Dynamic Surface Water extent (DSWx). The products are based on a variety of optical and radar sensors built on existing satellite data that are freely available from NASA. DSWx gives two dimensions of surface water measurements (i.e., spatial extent), whereas SWOT produces three dimensions of surface water measurement (i.e., spatial extent and elevation). DSWx has the potential to fill in temporal gaps in SWOT observations and to cross-compare DSWx and SWOT when observations are concurrent. DSWx is a valuable source of global water information that can be used to interpret and enhance SWOT’s capabilities.
Renato Frasson [JPL] explained how the U.S. Army Corps of Engineers support the National Geospatial-Intelligence Agency (NGA), which uses water storage and lake/reservoir flux information primarily from NASA’s MODerate resolution Imaging Spectroradiometer (MODIS) that flies on both the Terra and Aqua platforms. SWOT data has a higher spatial resolution for river widths, and NASA–ISRO Synthetic Aperture Radar (NISAR) observations are planned to be incorporated into the OPERA platform.
Cedric David [NASA/JPL] discussed how SWOT data can improve state-of-the-art hydrologic models to address environmental and societal challenges in river system science (e.g., flooding, water security, river biodiversity, changing deltas, and transboundary issues). Model advancements (e.g., U.S. National Water Model) can be realized in areas such as uncertainty quantification, data assimilation, bias correction, and decreasing numbers of in situ observation systems. Incorporating SWOT data into river models will lead to more realistic representations of these rivers, which in turn will improve the users’ ability to understand and effectively manage these critical and threatened water resources.
Workshop Recommendations and Feedback
This 2023 SWOT Applications Workshop provided an opportunity to share early experiences with SWOT data and insight into integration of the data into operational and decision-support workflows and models (e.g., ocean circulation and hydrologic, hydrodynamic, and decision support). Understanding how EAs integrate SWOT data and the associated challenges is critical to provide a clear analytical path for assessing the value of SWOT’s observations.
Integrating satellite observations into models enhances the model’s capability to forecast natural phenomena and monitor remote or inaccessible regions, expanding modeling capabilities dynamically and spatially. The EA-user community shared information on the potential of incorporating SWOT data into local- or community-wide models or modeling systems. SWOT’s high-resolution data – particularly from the KaRIn instrument – can enhance the precision of hydrology and ocean models by enabling detailed simulations of water dynamics. This includes accurate mapping of freshwater bodies and SSH. Both these measurements are crucial for managing water resources, predicting floods, and understanding ocean circulation patterns. The incorporation of SWOT data into model systems enables significant advancement and insights that can inform environmental management policies and practices by supporting more informed decision-making.
Although the SWOT nadir altimeter data products are being operationally produced and distributed through the data centers, the new data products from the novel KaRIn instrument continue to be assessed. An entire year of data is necessary for a more comprehensive assessment of value, ease of use, and degree to which SWOT data will impact operations and decision-making.
Throughout the workshop, EAs shared their experiences and specific needs in regard to early use of SWOT data in their modeling frameworks. Overall impressions were positive, but the actual use of SWOT beta product data was limited to a few projects (e.g., NRL, Sofar Ocean, and Copernicus Marine Service). Overall, the meeting participants supported the need for lower-latency products.
In the coming year, the impact of SWOT data with lower 21-day science orbital repeat frequency and latency on various applications will be understood further. Ultimately, the most important feedback from SWOT EAs is yet to come.
SWOT has the potential to provide invaluable information to operational user communities through its ability to advance understanding of global surface water dynamics. The SWOT Applications Program has successfully engaged a diverse cohort of agencies and the commercial sector to support integrating SWOT data into operational workflows. Moving forward, the program aims to highlight societal benefits, support applied research in hydrology and oceanography, expand user engagement, and provide ongoing training to maximize the effective use of fully validated SWOT data products.
Conclusion
The 2023 SWOT Applications meeting was a successful and timely engagement opportunity, further strengthening the connection between the different collaborating organizations. Many EAs demonstrated early ingest of the preliminary release of KaRIn data, with some having already started using the nadir altimeter data in their operational processes. Engagement will continue as more data, including pre-validated and validated science products, become regularly available with support to the EA community.
Future SWOT Application activities will include continued communication at community meetings and conferences as well as with a broader audience to engage new users for both applied research and operational activities through workshops, hackathons, and telecons. The SAWG will continue working with EAs and the applied and operational user communities to identify and apply value of SWOT to support decision makers and operational agencies.
NASA and CNES data distribution centers will continue to train users in cloud data access, data formats, and preferred formats for different topics, as well as provide EA feedback to improve data products and platform services. NASA and CNES will continue to work with EAs to overcome technical hurdles, help complete their projects, and generate high-impact success stories, as well as expand the extent of SWOT EAs and applied science users to build recognition of SWOT among practitioners.
Acknowledgment: The author wishes to acknowledge the contribution of Stacy Kish [NASA’s Goddard Space Flight Center (GSFC)/Global Science and Technology, Inc. (GST)] for her editing work to reduce/repurpose the full summary report to create a version suitable for the context of The Earth Observer.
Margaret Srinivasan
NASA/Jet Propulsion Laboratory, California Institute of Technology
margaret.srinivasan@jpl.nasa.gov
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Last Updated Sep 30, 2024 Related Terms
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