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NASA’S OSIRIS-REx Curation Team Reveals Remaining Asteroid Sample


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Advanced Curation Systematic Imaging Documentation for OSIRIS-REX Sample Return Mission Physical Examination
Photo: NASA/Erika Blumenfeld & Joseph Aebersold

The astromaterials curation team at NASA’s Johnson Space Center in Houston has completed the disassembly of the OSIRIS-REx sampler head to reveal the remainder of the asteroid Bennu sample inside. On Jan. 10, they successfully removed two stubborn fasteners that had prevented the final steps of opening the Touch-and-Go-Sample-Acquisition-Mechanism (TAGSAM) head.

Erika Blumenfeld, creative lead for the Advanced Imaging and Visualization of Astromaterials (AIVA) and Joe Aebersold, AIVA project lead, captured this photograph of the open TAGSAM head including the asteroid material inside using manual high-resolution precision photography and a semi-automated focus stacking procedure. The result is an image that shows extreme detail of the sample.

Next, the curation team will remove the round metal collar and prepare the glovebox to transfer the remaining sample from the TAGSAM head into pie-wedge sample trays.

These trays will be photographed before the sample is weighed, packaged, and stored at Johnson, home to the most extensive collection of astromaterials in the world. The remaining sample material includes dust and rocks up to about 0.4 inch (one cm) in size. The final mass of the sample will be determined in the coming weeks. The curation team members had already collected 2.48 ounces (70.3 grams) of asteroid material from the sample hardware before the lid was removed, surpassing the agency’s goal of bringing at least 2.12 ounces (60 grams) to Earth.

The curation team will release a catalog of all the Bennu samples later this year, which will allow scientists and institutions around the world to submit requests for research or display.

Download high-resolution images here: https://images.nasa.gov/details/jsc2024e006057

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      Breakout Sessions—Session 1
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      Chris Hakkenberg [Northern Arizona University (NAU)] led a breakout session on structural diversity, including the horizontal and vertical components. Different structural attributes, (e.g., stand structure, height, cover, and vegetation density) have different – but related – metrics and measurement approaches. Participants discussed biodiversity-structure relationships (BSRs), how to better characterize horizontal structural diversity, and how to define which metrics (i.e., scale, sampling unit, and spatial resolution) are most meaningful in different situations.
      Jim Kellner led a session that focused on biomass calibration and validation and how to create the best data products given global environmental variation. Special cases – e.g., mangroves – pose challenges for calibration and validation because they don’t always have as much plot-level data as other environments. Participants discussed how to determine strata while considering climactic and environmental covariates as well as constraints of data availability and consistency.
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      The FORest Carbon Estimation (FORCE) Project is exploring the use of GEDI-derived canopy structure metrics to map forest biomass in the U.S. and Canada. Daniel Hayes [University of Maine] presented comparisons of GEDI metrics and canopy height models derived from airborne lidar and photo point clouds over different forest types and disturbance history in managed forests of Maine. Co-PI Andy Finley [Michigan State University] presented new work that adjusts GEDI L4B biomass estimates to plot data over the continental U.S. from Forest Inventory and Analysis (FIA) program of the U.S. Department of Agriculture’s Forest Research and Development Branch. The project’s next steps are to fuse GEDI canopy structure metrics with other covariates in a spatial model to produce wall-to-wall estimates of biomass for boreal–temperate transition forests in northeast North America.
      GEDI data is also being used to study tropical forests. Chris Doughty [NAU] described how he and his team analyzed GEDI L2A data across all tropical forests and found that tropical forest structure was less stratified and more exposed to sunlight than previously thought. Most tropical forests (80% of the Amazon and 70% of southeast Asia and the Congo Basin) have a peak in the number of leaves at 15 m (49 ft) instead of at the canopy top. Doughty and his team have found that deviation from more ideal conditions (i.e., lower fertility or higher temperatures) lead to shorter, less-stratified tropical forests with lower biomass.
      Paul Moorcroft [Harvard University] reported on studies of current and future carbon dynamics across the Pacific Coast region based on forest structure and rates of carbon uptake. Moorcroft’s group examined how these ecosystems will behave in the future under different climate scenarios and have plans to conduct similar studies in other regions.
      DAY TWO
      Naikoa Aguilar-Amuchastegui [World Bank] kicked off day two with his perspective on the importance of streamlining the monitoring, reporting, and validation (MRV) process from scientific estimation to actual use of the data. Once scientific data is generated, end users are often faced with challenges related to transparency and understandability. Scientists can better communicate how to use their datasets properly, by familiarizing themselves with who wants to use their data, why they want to use it, and what their needs are. With this information in mind, data can be presented in more practical ways that allow for a variety of institutions with different standards and frameworks to integrate GEDI data more easily into their reporting. As the GEDI team continues to produce high-quality maps, efforts are underway to connect with end users and provide tutorials, workshops, and other resources.
      GEDI Demonstrative Products
      Demonstrative products show how GEDI data can be used in practice and in combination with other resources. Ecosystem modeling is one way that GEDI data are being used to address questions about aboveground carbon balance, future atmospheric CO2 concentrations, and habitat quality and biodiversity. George Hurtt [UMD—GEDI Co-I] shared his progress on integrating GEDI canopy height measurements with the Ecosystem Demography model to estimate current global forest carbon stocks and project future sequestration gaps under climate change – see Figure 6. Hurtt emphasized that this unprecedented volume of lidar data significantly enhances the ability of carbon models to capture spatial heterogeneity of forest carbon dynamics at 1 km (0.6 mi) scale, which is crucial for local policymaking regarding climate mitigation.
      Figure 6. [Top] Average lidar canopy height at 0.01° resolution, computed by gridding both GEDI and ICESat-2 together, and carbon stocks [middle] and fluxes [bottom] from ED-Lidar (GEDI and ICESat-2 combined). The insets highlight fine-scale spatial distribution and coverage gaps at selected regions (1.5° × 1.5°). Note that the three maps show grid-cell averages aggregated from sub-grid scale heterogeneity for each variable. Figure credit: From a 2023 article in Global Change Biology. There is also great potential for the development and application of methods for mapping forest structure, carbon stocks, and their changes by fusing data from GEDI and the Deutsches Zentrum für Luft- und Raumfahrt’s (DLR) [German Space Operations Center] TerraSAR-X Add-oN for Digital Elevation Measurement (TanDEM-X) satellite mission, which uses synthetic aperture radar (SAR) to gather three-dimensional (3D) images of Earth’s surface. This fusion product is being spearheaded by Wenlu Qi [UMD], who presented on efforts to create maps of pantropical canopy height, biomass, forest structure, and biomass change using the fusion product as well as maps of forests in temperate U.S. and Hawaii.
      Data from the GEDI mission are also being used to quantify the spatial and temporal distribution of habitat structure, which influences habitat quality and biodiversity. Scott Goetz [NAU—GEDI Deputy PI] presented on biodiversity-related activities, citing a 2023 paper in Nature that examined the effectiveness of protected areas (PAs) across southeast Asia using GEDI data to compare canopy structure within and outside of PAs – see Figure 7. He also presented an analysis of tree and plant diversity across U.S. National Ecological Observation Network (NEON) sites that showed similar capabilities of GEDI with airborne laser scanning (ALS) for tree diversity.
      Figure 7. [Top] Protected Areas (PAs) such as national parks can reduce habitat loss and degradation (from logging) and extractive behaviors such as hunting (shown in red circle), but this figure shows there are a wide range of real-world outcomes based on management effectiveness. [Middle] PAs are aimed at safeguarding multiple facets of biodiversity, including species richness (SR), functional richness (FR) and phylogenetic diversity (PD). PAs often focus on vertebrate conservation, owing to their threat levels and value to humans – including for tourism. This study focused on wildlife in southeast Asia, with mammals shown here representing a variation of feeding guilds and sizes. The same approach is repeated for birds. [Bottom] Wildlife communities inside PAs and in the surrounding landscape may exhibit distinct levels and types of diversity. Figure credit: From a 2023 article in Nature. Competed Science Team Presentations—Session 3
      One unique application of GEDI data is using lidar height to improve radiative transfer models for snow processes. Steven Hancock [University of Edinburgh, Scotland] reported on his group’s work studying snow, forest structure, and heterogeneity in forests, explaining that the majority of land surface models used for climate and weather forecasting use one-dimensional (1D) radiative transfer (RT) models driven by leaf area alone. Heterogeneous forests cast shadows and cause the surface albedo to depend upon sun angle and tree height for moderate leaf area indices (LAI), i.e., LAI values from  1-3 – which are common in snow-affected areas. This complexity cannot be represented in 1D models. An RT model can represent the effect of tree height and horizontal heterogeneity to simulate the observed change in albedo with height, which itself spatially varies.
      In contrast to a snowy study area, Ovidiu Csillik [NASA/Jet Propulsion Laboratory] and his team are developing statistical models to link GEDI relative height metrics to tropical forest characteristics traceable to inventory measurements. This dataset of forest structure variables over the Amazon will be used to initialize a demographic ecosystem model to produce projections of future potential tropical forest carbon, as demonstrated by Amazon-wide simulations using initializations from airborne lidar sampling.
      Wenge Ni-Meister [Hunter College of the City University of New York] is working on improving aboveground biomass estimates using GEDI waveform measurements. Ni-Meister and her team are testing models in both domestic and international tropical and temperate forests.
      Breakout Sessions—Session 2
      Two more breakout sessions occurred on day two:  
      Sean Healey led a discussion on modes of inference for GEDI data. Inference – formally derived uncertainty for area estimates of biomass, height, or other metrics – can take different forms, each of which includes specific assumptions. In this breakout session, participants considered the strengths and limitations of different inference types (e.g., intensity of computation or the ability to use different models).
      Laura Duncanson [UMD—GEDI Co-I] led a discussion about facilitation of open science, in other words, how to make GEDI data more accessible and digestible for data users. While GEDI data area free and publicly available via the LP DAAC and ORNL DAAC, gaining access to said data can be intimidating. Sharing more about existing resources and creating new ones can help remove barriers. The LP DAAC and ORNL DAAC have excellent tutorials on GitHub (a cloud-based software development platform that is primarily Python-based), and Google Earth Engine applications are available for accessing and visualizing GEDI data. Future endeavors may include more webinars, R-based tutorials, workshops, and trainings on specific topics and ways to use GEDI data. More information is available via an online compilation of GEDI-related tutorials.
      Perspective: A NUVIEW of Earth’s Land Surface
      For the second perspective presentation of day two, meeting attendees heard from Clint Graumann, CEO and co-founder of NUVIEW, a company whose mission is to build a commercial satellite constellation of lidar-imaging satellites that will produce 3D maps of the Earth’s entire land surface. Graumann shared NUVIEW’s intent to produce land surface maps on an annual basis and provide a variety of products and services, including digital surface models (DSMs), digital terrain models (DTMs), and a point cloud generated by laser pulses.
      Competed Science Team Presentations—Session 4
      Laura Duncanson began the second round of science presentations with her group’s research on global forest carbon hotspots. She discussed her 2023 paper in Nature Communications on the effectiveness of global PAs for climate change mitigation – see Figure 8, which found that the creation of PAs led to more biomass – especially in the Amazon. Within GEDI-domain terrestrial PAs, total aboveground biomass (AGB) storage was found to be 125 Pg, which is around 26% of global estimated AGB. Without the existence of PAs, 19.7 Gt of the 125 Pg would have likely been lost.
      Figure 8. PAs effectively preserve additional aboveground carbon (AGC) across continents and biomes, with forest biomes dominating the global signal, particularly in South America. The additional preserved AGC (Gt) in WWF biome classes (total Gt + /− SEM*area). World base map made with Natural Earth. The full set of analyzed GEDI data are represented in this figure (n = 412,100,767). Figure credit: From a 2023 article in Nature Communications. Another unique application of GEDI data has to do with water on the Earth’s surface. Kyungtae Lee [UMD], who works with Michelle Hofton [UMD—GEDI Co-I], reported that GEDI appears to capture the monthly annual cycle of lake elevation, showing good correlation with the ground-based observations. Lee explained that even though the GEDI lake elevation estimates show systematic biases relative to the local gauges, GEDI captures lake elevation dynamics well – especially the annual cycle variations. This work has the potential to expand knowledge of hydrological significance of lakes, particularly in data-limited areas of the world. Stephen Good [Oregon State University] presented a survey of his team’s recent work integrating observations from GEDI into hydrology and hydraulics studies of how vegetation can block and intercept moving water. The team found important nonlinear relationships between inferred canopy storage and canopy biomass and were able to estimate canopy water storage capacities and map these globally.
      Finally, Patrick Burns [NAU], who works with Scott Goetz, presented results using GEDI canopy structure metrics in mammal species distribution models across southeast Asia (specifically focusing on Borneo and Sumatra). The team’s early results indicate that GEDI canopy structure metrics are important in many mammal distribution models and improve model performance for another smaller subset of species. In other words, when looking at predictors like mean annual precipitation or forest structure (forest structure being a metric that GEDI data provide), the GEDI-derived structure metrics are more intuitive and help us understand distributional changes and fine-scale habitat suitability. In a region like southeast Asia, for example, which has undergone high rates of deforestation in the recent decades, forest structure may be a more relevant predictor in a species distribution model (SDM) than other metrics like climate or vegetation composition. The team will continue to produce models for additional species and expand the extent of the analysis to include mainland Asia.
      DAY THREE
      Competed Science Team Presentations—Session 5
      Day three began with the meeting’s last round of competed ST presentations. John Armston presented the progress of GEDI L2B Plant Area Volume Density (PAVD) product validation using a global Terrestrial Laser Scanning (TLS) database and fusion of the L2B product with Landsat time-series for quantifying change in canopy structure from the Australian wildfires of 2019–2020. Participants then heard from Jim Kellner on using machine-learning algorithms for L4A aboveground biomass density (AGBD). The performance of machine-learning algorithms on a testing data set was comparable to linear regressions used for the first releases of GEDI AGBD data products on average – although there were important geographical differences associated with machine learning. One application under investigation is using machine learning to identify new potential stratifications for GEDI footprint aboveground biomass density.
      Lastly, Jingyu Dai [New Mexico State University (NMSU)], who works with Niall Hanan [NMSU], presented on her analysis of the global limits to tree height. Her study shows that hydraulic limitation is the most important constraint on maximum canopy height globally. This result is mediated by plant functional type. In addition, rougher terrain promotes forest height at sub-landscape scales by enriching local niche diversity and probability of larger trees.
      Perspective from the Data Side
      As described in the summary of Ralph Dubayah’s introductory remarks, the LP DAAC and ORNL DAAC play essential roles in the dissemination of GEDI data and the success of the GEDI program. Representatives from each of these DAACs addressed the ST to summarize recent GEDI-related activities.
      Aaron Friesz [United States Geological Survey (USGS)] represented the LP DAAC and gave an update on the current archive size, distribution metrics, and outreach activities. He also discussed plans to support the growth and sustainability of the community through collaboration activities that will leverage the GitHub application; he described some of the resources that are available. Friesz then highlighted the USGS Eyes on Earth podcast and the Institute of Electrical and Electronics Engineers (IEEE) Geoscience and Remote Sensing Society (GRSS)’s Down to Earth podcast, which have featured Ralph Dubayah and Laura Duncanson, and shared plans to update the current GitHub tutorials and how-to guides in the Earthdata Cloud of GEDI V2 and V3.
      Rupesh Shrestha [ORNL] represented the ORNL DAAC and shared the status of GEDI L3, L4A, and L4B datasets archived there. He gave an overview of data tools and services for the GEDI datasets, which can be found on the GEDI website and GitHub tutorials website. GEDI L3, L4A, and L4B are available on NASA’s Earthdata Cloud and various enterprise-level services, such as NASA’s WorldView, Harmony, and OpenDAP. GEDI data usage metrics, data tutorials and workshops, and outreach activities, as well as other published community and related datasets were also highlighted. GEDI L3, L4A, and L4B have been downloaded over four million times collectively.
      Neha Hunka [UMD] gave the final presentation of the meeting on biomass harmonization activities. She reported that the GEDI estimates of aboveground biomass are capable of directly contributing to the United Nations Framework Convention on Climate Change Global Stocktake. Hunka and her colleagues’ research is aimed at bridging the science–policy gap to enable the use of space-based aboveground biomass estimates for policy reporting and impact – see Figure 9.
      Figure 9. Forest biomass estimates in the format of Intergovernmental Panel on Climate Change (IPCC) Tier 1 values from NASA GEDI and ESA Climate Change Initiative (CCI) maps. Figure credit: Neha Hunka Conclusion
      Overall, the 2023 GEDI STM showcased an exceptional array of scientific research that is highly relevant to addressing pressing global challenges and answering key questions about global forest structure, carbon balance, habitat quality, and biodiversity among other topics. As the GEDI instrument enters its second epoch, we are excited to welcome a new competed GEDI science team cohort and look forward to the release of V3 data products later this year.
      Ralph Dubayah concluded the STM with a summary of hibernation period goals and a farewell to this iteration of the competed ST. He extended a heartfelt thank you and farewell to Hank Margolis [NASA Headquarters, emeritus] who has been the NASA Program Scientist for the GEDI mission since 2015. Thank you, Hank. We will miss you.
      Talia Schwelling
      University of Maryland, College Park
      tschwell@umd.edu
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    • By NASA
      Representatives from NASA, FEMA, and the planetary defense community participate in the fifth Planetary Defense Interagency Tabletop Exercise on April 2 and 3, 2024, to discuss the nation’s ability to respond effectively to the threat of a potentially hazardous asteroid or comet.Credits: NASA/JHU-APL/Ed Whitman NASA will host a virtual media briefing at 3:30 p.m. EDT, Thursday, June 20, to discuss a new summary of a recent tabletop exercise to simulate national and international responses to a hypothetical asteroid impact threat.
      The fifth biennial Planetary Defense Interagency Tabletop Exercise was held April 2 and 3, 2024, at the Johns Hopkins Applied Physics Laboratory (APL) in Laurel, Maryland.
      NASA’s Planetary Defense Coordination Office, in partnership with FEMA (Federal Emergency Management Agency) and with the assistance of the U.S. Department of State Office of Space Affairs, convened the tabletop exercise to inform and assess our ability as a nation to respond effectively to the threat of a potentially hazardous asteroid or comet. This exercise supports NASA’s planetary defense strategy to protect our planet and continues the agency’s mission to innovate for the benefit of humanity.
      Video of the briefing will stream live on NASA TV and NASA’s YouTube channel.
      The following participants will review the history and purpose of the exercise, the scenario encountered during this year’s simulation, and its findings and recommendations:
      Lindley Johnson, NASA’s Planetary Defense Officer Emeritus, NASA Headquarters, Washington Leviticus “L.A.” Lewis, FEMA detailee to NASA’s Planetary Defense Coordination Office, NASA Headquarters Terik Daly, planetary defense section supervisor, Johns Hopkins Applied Physics Laboratory, Laurel, Maryland To register for the briefing, media must RSVP no later than two hours before the event to Alise Fisher at alise.m.fisher@nasa.gov. NASA’s media accreditation policy is available online.
      While there are no known significant asteroid impact threats for the foreseeable future, hypothetical exercises like this one, which are conducted about every two years, provide valuable insights on how the United States could respond effectively if a potential asteroid impact threat is identified.
      This year’s exercise was the first to include participation by NASA’s international collaborators in planetary defense and the first to have the benefit of actual data from NASA’s successful DART (Double Asteroid Redirection Test) mission, the world’s first in-space technology demonstration for defending Earth against potential asteroid impacts.
      NASA established the Planetary Defense Coordination Office in 2016 to manage the agency’s ongoing efforts in planetary defense.
      To learn more about planetary defense at NASA, visit: 
      https://science.nasa.gov/planetary-defense/
      -end-
      Charles Blue / Karen Fox
      Headquarters, Washington 
      202-802-5345 / 202-358-1600
      charles.e.blue@nasa.gov / karen.fox@nasa.gov
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      Last Updated Jun 14, 2024 LocationNASA Headquarters Related Terms
      Planetary Defense Coordination Office Planetary Defense Planetary Science Division Science & Research Science Mission Directorate View the full article
    • By NASA
      Earth Observer Earth and Climate Earth Observer Home Editor’s Corner Feature Articles News Science in the News Calendars In Memoriam More Meeting Summaries Archives 22 min read
      Summary of the Ninth DSCOVR EPIC and NISTAR Science Team Meeting
      Introduction
      The ninth 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 virtually October 16–17, 2023. Over 35 scientists attended, most of whom were from NASA’s Goddard Space Flight Center (GSFC), with several participating from other NASA field centers, U.S. universities, and U.S. Department of Energy laboratories. One international participant joined the meeting from Estonia. A full overview of DSCOVR’s Earth-observing instruments was printed in a previous article in The Earth Observer and will not be repeated here. This article provides the highlights of the 2023 meeting. The meeting agenda and full presentations can be downloaded from GSFC’s Aura Validation Data Center.
      Opening Presentations
      The opening session consisted of a series of presentations from DSCOVR mission leaders and representatives from GSFC and NASA Headquarters (HQ), who gave updates on the mission and the two Earth-viewing science instruments on board. Alexander Marshak [GSFC—DSCOVR Deputy Project Scientist] opened the meeting. He discussed the agenda for the meeting and mentioned that both Earth science instruments on DSCOVR are functioning normally – see Figure 1. At this time, more than 115 papers related to DSCOVR are listed on the EPIC website. Marshak emphasized the importance of making the Earth Science community more aware of the availability of the various EPIC and NISTAR science data products.
      Figure 1. Sun-Earth-Vehicle (SEV) angle (red curve) and the distance between Earth and the DSCOVR satellite (blue curve) versus time starting from the DSCOVR launch on February 15, 2015 to April 1, 2024. These two measurements are used to track the location and orientation, respectively, of DSCOVR. The spacecraft changes its location by about 200,000 km (~124,274 mi) over about a 3-month period, and its SEV gets close to zero (which would correspond to perfect backscattering). The gap around the year 2020 was when DSCOVR was in Safe Mode for an extended period. Figure credit: Adam Szabo (Original figure by Alexander Marshak, with data provided by Joe Park/NOAA) Adam Szabo [GSFC—DSCOVR Project Scientist] welcomed the STM participants and briefly reported that the spacecraft, located at “L1” – the first of five Lagrange points in the Sun-Earth system – was still in “good health.” The EPIC and NISTAR instruments on DSCOVR continue to return their full science observations. Szabo gave an update on the 2023 Earth Science Senior Review, which DSCOVR successfully passed with overall science scores of ‘Excellent/Very Good.’ The Senior Review Panel unanimously supported the continuation of DSCOVR for the 2024–2026 period.
      Thomas Neumann [GSFC, Earth Sciences Division (ESD)—Deputy Director] welcomed meeting participants on behalf of the ESD. Neumann noted the impressive engineering that has led to 8.5 years of operations and counting. He also commended the team on the continued production of important science results from these instruments – with nearly 110 papers in the peer-reviewed literature.
      Following Neumann’s remarks, Steve Platnick [GSFC, Earth Sciences Division—Deputy Director for Atmospheres] welcomed the members of the DSCOVR ST as well as users of EPIC and NISTAR observations. He thanked NASA HQ for its continued strong interest in the mission. Platnick also expressed his appreciation for the mission team members who have worked hard to maintain operation of the DSCOVR satellite and instruments during this challenging time.
      Richard Eckman [NASA HQ, Earth Science Division—DSCOVR EPIC/NISTAR Program Scientist] noted that a new call for proposals will be in ROSES-2025 and looks forward to learning about recent accomplishments by ST members, which will be essential in assessing the mission’s performance.
      Jack Kaye [NASA HQ, Earth Science Division—Associate Director for Research] discussed the NASA research program that studies the Earth, using satellites, aircraft, surface-based measurements, and computer models. The two Earth science instruments on DSCOVR (EPIC and NISTAR) play an important role in the program. He highlighted the uniqueness of the DSCOVR observations from the Sun–Earth “L1” point providing context for other missions and the ability to discern diurnal variations.
      Updates on DSCOVR Operations
      The DSCOVR mission components continue to function nominally, with progress on several fronts, including data acquisition, processing, archiving, and release of new versions of several data products. The number of people using the content 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.
      Hazem Mahmoud [NASA’s Langley Research Center (LaRC)] discussed the new tools in the Atmospheric Science Data Center (ASDC). He reported on DSCOVR metrics since 2015 and mentioned the significant increase in using ozone (O3) products. He also announced that ASDC is moving to the Amazon Web Services (AWS) cloud.
      Karin Blank [GSFC] covered the EPIC geolocation algorithm, including the general algorithm framework. She highlighted additional problems that needed to be resolved and detailed the various stages to refine the algorithm, emphasizing the enhancements made to improve geolocation accuracy.
      Marshall Sutton [GSFC] reported on the DSCOVR Science Operations Center (DSOC) and Level-2 (L2) processing. DSOC is operating nominally. EPIC L1A, L1B, and NISTAR data files are produced daily. EPIC L1 products are processed into L2 science products using the computing power of the NASA Center for Climate Simulations (NCCS). Products include daily data images, including a cloud fraction map, aerosol map, and the anticipated aerosol height image. In addition, Sutton reported that the DSCOVR spacecraft has enough fuel to remain in operation until 2033.
      EPIC Calibration
      Alexander Cede [SciGlob] and Ragi Rajagopalan [LiftBlick OG] reported on the latest EPIC calibration version (V23) that includes the new flat field corrections based on the lunar observations from 2023 and an update to the dark count model. The EPIC instrument remains healthy and shows no change in parameters, e.g., read noise, enhanced or saturated pixels, or hot or warm pixels. The current operational dark count model still describes the dark count in a satisfactory way.
      Liang-Kang Huang [Science Systems and Applications, Inc. (SSAI)] reported on EPIC’s July 2023 lunar measurements, which filled in the area near diagonal lines of the charged coupled device (CCD) not covered by 2021 and 2022 lunar data. With six short wavelength channels ranging from 317 to 551 nm, the two sets of lunar data are consistent with each other. For the macroscopic flat field corrections, he recommended the six fitted sensitivity change functions of radius and polar angle. 
      Igor Geogdzhaev [NASA’s Goddard Institute for Space Studies (GISS)/Columbia University] reported how continuous EPIC observations provide stable visible and near infrared (NIR) channels compared to the contemporaneous data from Visible Infrared Imaging Radiometer Suite (VIIRS) on NASA’s Suomi National Polar-orbiting Partnership (Suomi NPP) and the NASA–National Oceanic and Atmospheric Administration (NOAA) Joint Polar Satellite System (JPSS) missions. (To date, two JPSS missions have launched, JPSS-1, which is now known as NOAA-20, and JPSS-2, which is now known as NOAA-21.) Analysis of near simultaneous data from EPIC and from the Advanced Baseline Imager (ABI) on the Geostationary Operational Environmental Satellite–R (GOES R) platforms showed a high correlation coefficient, good agreement between dark and bright pixels, and small regression zero intercepts. EPIC moon views were used to derive oxygen (O2) channel reflectance by interpolation of the calibrated non-absorbing channels.
      Conor Haney [LaRC] reported that the EPIC sensor was intercalibrated against measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra and Aqua platforms as well as from VIIRS on Suomi NPP and NOAA-20, using ray-matched pair radiances, and was found to be radiometrically stable when tested against two invariant calibration targets: over deep convective clouds over the tropical Pacific (dark target) and over the Libya-4 site located in the Libyan desert in Africa (bright target). The ray-matched and Earth target EPIC gain trends were found to be consistent within 1.1%, and the EPIC sensor degradation was found to be less than 1% over the seven-year record. Preliminary results intercalibrating EPIC with the Advanced Himawari Imager (AHI) on the Japan Aerospace Exploration Agency’s (JAXA) “Himawari–8” Geostationary Meteorological Satellite were also promising when both subsatellite positions were close—i.e., during equinox.
      NISTAR Status and Science with Its Observations
      The NISTAR instrument remains fully functional and continues its uninterrupted data record. The presentations here include 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 NISTAR has been measuring the irradiance from the Sun-lit Earth in three bands for more than eight years. The bands measure the outgo­ing reflected solar and total radiation from Earth at a limited range of solar angles. These measurements assist researchers in answering questions addressing Earth radiation imbalance and predicting future climate change. NISTAR continues to operate nominally, and the team is monitoring any in-orbit degradation. Lorentz explained the evolution of the NISTAR view angle over time. He also provided NISTAR shortwave (SW) and photodiode (PD) intercomparison. NISTAR has proven itself to be an extremely stable instrument – although measurements of the offsets have measurement errors. A relative comparison with the scaled-PD channel implies long-term agreement below a percent with a constant background.
      Clark Weaver [University of Maryland, College Park (UMD)] discussed updates to a new reflected- SW energy estimate from EPIC. This new product uses generic Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) aircraft observations over homogeneous scenes to spectrally interpolate between the coarse EPIC channels. This approach assumes the spectra from an EPIC pixel is a weighted combination of a solid cloud scene and the underlying (cloud-free) surface. Weaver and his team used a vector discrete ordinate radiative transfer model with a full linearization facility, called VLIDORT, to account for the different viewing/illumination geometry of the sensors. Each pixel residual between EPIC observations at six different wavelengths (between 340 and 780 nm) and the composite high-resolution spectrum from AVIRIS has been reduced by about 50%, since the last report. While the total reflected energy for a single EPIC image can be about 15 W/m2 different than the NISTAR measurement, by 2017 the offset bias was, on average, about 1 W/m2. 
      Andrew Lacis [GISS] said that DSCOVR measurements of Earth’s reflected solar radiation from the “L1” position offer a unique perspective for the continuous monitoring of Earth’s sunlit hemisphere. Six years of EPIC data show the seasonal and diurnal variability of Earth’s planetary albedo – but with no discernible trend. Planetary scale variability, driven by changing patterns in cloud distribution, is seen to occur at all longitudes over a broad range of time scales. The planetary albedo variability is strongly correlated at neighboring longitudes but shows strongly anticorrelated behavior at diametrically distant longitudes.
      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. They provide updates on several of the data products and on related algorithm improvements. 
      Total Column Ozone
      Natalya Kramarova [GSFC] reported on the status of the EPIC total O3 using the V3 algorithm. The absolute calibrations are updated every year using collocated observations from the Ozone Mapping and Profiling Suite (OMPS) on Suomi NPP. EPIC total O3 measurements are routinely compared with independent satellite and ground-based measurements. Retrieved EPIC O3 columns agree within ±5–7 Dobson Units (DU, or 1.5–2.5%) with independent observations, including those from satellites [e.g., Suomi NPP/OMPS, NASA’s Aura/Ozone Monitoring Instrument (OMI), European Union’s (EU) Copernicus Sentinel-5 Precursor/TROPOspheric Monitoring Instrument (TROPOMI)], sondes, and ground-based Brewer and Dobson spectrophotometers. The EPIC O3 record is stable and shows no substantial drifts with respect to OMPS. In the future, the EPIC O3 team plans to compare EPIC time resolved O3 measurements with observations from NASA’s Tropospheric Emissions Monitoring of Pollution (TEMPO) and the South Korean Geostationary Environment Monitoring Spectrometer (GEMS) – both in geostationary orbit. (Along with the EU’s Copernicus Sentinel-4 mission, expected to launch in 2024, these three missions form a global geostationary constellation for monitoring air quality on spatial and temporal scales that will help scientists better understand the causes, movement, and effects of air pollution across some of the world’s most populated areas.) 
      Jerrald Ziemke [Morgan State University] explained that tropospheric column O3 is measured over the disk of Earth every 1–2 hours. These measurements are derived by combining EPIC observations with Modern-Era Retrospective Analysis for Research and Applications (MERRA2) assimilated O3 and tropopause fields. These hourly maps are available to the public from the Langley ASDC and extend over eight years from June 2015 to present. The EPIC tropospheric O3 is now indicating post-COVID anomalous decreases of ~3 DU in the Northern Hemisphere for three consecutive years (2020–2022). Similar decreases are present in other satellite tropospheric O3 products as well as OMI tropospheric nitrogen dioxide (NO2), a tropospheric O3 precursor.
      Algorithm Improvement for Ozone and Sulfur Dioxide Products
      Kai Yang [UMD] presented the algorithm for retrieving tropospheric O3 from EPIC by estimating the stratosphere–troposphere separation of retrieved O3 profiles. This approach contrasts with the traditional residual method, which relies on the stratospheric O3 fields from independent sources. Validated against the near-coincident O3 sonde measurements, EPIC data biased low by a few DU (up to 5 DU), consistent with EPIC’s reduced sensitivity to O3 in the troposphere. Comparisons with seasonal means of TROPOMI tropospheric O3 show consistent spatial and temporal distributions, with lows and highs from atmospheric motion, pollution, lightning, and biomass burning. Yang also showed EPIC measurements of sulfur dioxide (SO2) from recent volcanic eruptions, including Mauna Loa and Kilauea (Hawaii, U.S., 2022–2023), Sheveluch (Kamchatka, Russia, 2023), Etna (Italy, 2023), Fuego (Guatemala, 2023), Popocatépetl (Mexico, 2023), and Pavlof and Shishaldin (Aleutian Islands, U.S., 2023). Yang reported the maximum SO2 mass loadings detected by EPIC are 430 kt from the 2022 Mauna Loa and Kilauea eruptions and 351 kt from the 2023 Sheveluch eruption.
      Simon Carn [University of Michigan] showed EPIC observations of major volcanic eruptions in 2022–2023 using the EPIC L2 volcanic SO2 and UV Aerosol Index (UVAI) products to track SO2 and ash emissions. EPIC SO2 and UVAI measurements during the 2023 Sheveluch eruption show the coincident transport of volcanic SO2, ash, and Asian dust across the North Pacific. The high-cadence EPIC UVAI can be used to track the fallout of volcanic ash from eruption clouds, with implications for volcanic hazards. EPIC SO2 measurements during the November 2022 eruption of Mauna Loa volcano are being analyzed in collaboration with the U.S. Geological Survey, who monitored SO2 emissions using ground-based instruments during the eruption. Carn finished by mentioning that EPIC volcanic SO2 algorithm developments are underway including the simultaneous retrieval of volcanic SO2 and ash.
      Aerosols
      Myungje Choi [UMD, Baltimore County (UMBC)] presented an update on the EPIC V3 Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm to optimize smoke aerosol models and the inversion process. The retrieved smoke/dust properties showed an improved agreement with long-term, ground-based Aerosol Robotic Network (AERONET) measurements of solar spectral absorption (SSA) and with aerosol layer height (ALH) measurements from the Cloud–Aerosol Lidar with Orthogonal Projection (CALIOP) on the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission. (Update: As of the publication of this summary, both CALIPSO and CloudSat have ended operations.) Choi reported that between 60–90% of EPIC SSA retrievals are within ±0.03 of AERONET SSA measurements, and between 56–88% of EPIC ALH retrievals are within ±1km of CALIOP ALH retrievals. He explained that the improved algorithm effectively captures distinct smoke characteristics, e.g., the higher brown carbon (BrC) fraction from Canadian wildfires in 2023 and the higher black carbon (BC) fraction from agricultural fires over Mexico in June 2023.
      Sujung Go [UMBC] presented a global climatology analysis of major absorbing aerosol species, represented by BC and BrC in biomass burning smoke as well as hematite and goethite in mineral dust. The analysis is based on the V3 MAIAC EPIC dataset. Observed regional differences in BC vs. BrC concentrations have strong associations with known distributions of fuels and types of biomass burning (e.g., forest wildfire vs. agricultural burning) and with ALH retrievals linking injection heights with fire radiative power. Regional distributions of the mineral dust components have strong seasonality and agree well with known dust properties from published ground soil samples.
      Omar Torres [GSFC] reported on the upgrades of the EPIC near-UV aerosol (EPICAERUV) algorithm. The EPICAERUV algorithm’s diurnal cycle of aerosol optical depth compared to the time and space collocated AERONET observations at multiple sites around the world. The analysis shows remarkably close agreement between the two datasets. In addition, Torres presented the first results of an improved UV-VIS inversion algorithm that simultaneously retrieves aerosol layer height, optical depth, and single scattering albedo.
      Hiren Jethva [Morgan State University] discussed the unique product of absorbing aerosols above clouds (AAC) retrieved from EPIC near-UV observations between 340 and 388 nm. The validation analysis of the retrieved aerosol optical depth over clouds against airborne direct measurements from the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign revealed a robust agreement. EPIC’s unique capability of providing near-hourly observations offered an insight into the diurnal variations of regional cloud fraction and AAC over “hotspot” regions. A new and simple method of estimating direct radiative effects of absorbing aerosols above clouds provided a multiyear timeseries dataset, which is consistent with similar estimations from Aura–OMI.
      Jun Wang [University of Iowa] reported on the development and status of V1 of the L2 EPIC aerosol optical centroid height (AOCH) product – which is now publicly available through ASDC – and on improvements to the AOCH algorithm – which focus on the treatment of surface reflectance and aerosols models. He presented applications of this data product for both climate studies of Sahara dust layer height and air quality studies of surface particulate matter with diameter of 2.5 µm or less (PM2.5). In addition, Wang showed the comparisons of EPIC AOCH data product with those retrieved from TROPOMI and GEMS and discussed ongoing progress to reduce the AOCH data uncertainty that is estimated to be 0.5 km (0.3 mi) over the ocean and 0.8 km (0.5 mi) over land.
      Clouds
      Yuekui Yang [GSFC] explained the physical meaning of EPIC cloud effective pressure (CEP) in an “apples-to-apples” comparison with CEP measurements from the Global Ozone Monitoring Experiment 2 (GOME-2) on the European Operational Meteorology (MetOp) satellites. The results showed that the two products agreed well.
      Yaping Zhou [UMBC] showed how current EPIC O2 A-band and B-band use Moon calibrations due to lack of in-flight calibration and other comparable in-space instruments for absolute calibration. This approach is ineffective at detecting small changes in instrument response function (IRF). This study examined the O2 band’s calibration and stability using a unique South Pole location and Radiative Transfer Model (RTM) simulations with in situ soundings and surface spectral albedo and bidirectional reflectance distribution function (BRDF) measurements as input. The results indicate EPIC simulations are within 1% of observations for non-absorption bands, but large discrepancies exist for the O2 A-band (15.63%) and O2 B-band (5.76%). Sensitivity studies show the large discrepancies are unlikely caused by uncertainties in various input, but a small shift (-0.2–0.3 nm) of IRF could account for the model observation discrepancy. On the other hand, observed multiyear trends in O2 band ratios in the South Pole can be explained with orbital shift – which means the instrument is stable.
      Alfonso Delgado Bonal [UMBC] used the EPIC L2 cloud data to characterize the diurnal cycles of cloud optical thickness. To fully exploit the uniqueness of DSCOVR data, all clouds were separated in three groups depending on their optical thickness: thin (0–3), medium (3–10), and thick (3–25). Bonal explained that there is a predictable pattern for different latitudinal zones that reaches a maximum around noon local time – see Figure 2. It was also shown that that the median is a better measure of central tendency when describing cloud optical thickness.
      Figure 2. Daytime variability of the median liquid cloud optical thickness over the ocean for different seasons of the year derived using EPIC L2 data. The various colored curves represent data collected in different seasons of the year. The black curve represents the annual average – which is most useful for calculations of cloud optical thickness. Figure credit: Alfonso Delgado Bonal Elizabeth Berry [Atmospheric and Environmental Research (AER)] reported on how coincident observations from EPIC and the Cloud Profiling Radar (CPR) on CloudSat have been used to train a machine learning model to predict cloud vertical structure. A XGBoost decision tree model used input (e.g., EPIC L1B reflectance, L2 Cloud products, and background meteorology) to predict a binary cloud mask on 25 vertical levels. Berry discussed model performance, feature importance, and future improvements.
      Ocean
      Robert Frouin [Scripps Institution of Oceanography, University of California] discussed ocean surface radiation products from EPIC data. He reported that surface radiation products were developed to address science questions pertaining to biogeochemical cycling of carbon, nutrients, and oxygen as well as mixed-layer dynamics and circulation. These products include daily averaged downward planar and scalar irradiance and average cosine for total light just below the surface in the EPIC spectral bands centered on 317.5, 325, 340, 388, 443, 551, and 680 nm and integrated values over the photosynthetically active radiation (PAR) and UV-A spectral ranges. The PAR-integrated quantities were evaluated against in situ data collected at sites in the North Atlantic Ocean and Mediterranean Sea. Frouin and his colleagues have also developed, tested, and evaluated an autonomous system for collecting and transmitting continuously spectral UV and visible downward fluxes. 
      Vegetation
      Yuri Knyazikhin [Boston University] reported on the status of the Vegetation Earth System Data Record (VESDR) and discussed science with vegetation parameters. A new version of the VESDR software was delivered to NCCS and implemented for operational generation of the VESDR product. The new version passed tests of physics (e.g., various relationships between vegetation indices and vegetation parameters derived from the VESDR) and follow regularities reported in literature. Analysis of hotspot signatures derived from EPIC and from the Multiangle Imaging Spectroradiometer (MISR) on Terra over forests in southeastern Democratic Republic of the Congo reaffirms that long-term precipitation decline has had minimal impact on leaf area and leaf optical properties.
      Jan Pisek [University of Tartu/Tartu Observatory, Estonia] reported on the verification of the previously modeled link between the directional area scattering factor (DASF) from the EPIC VESDR product and foliage clumping with empirical data. The results suggest that DASF can be accurately derived from satellite observations and provide new evidence that the photon recollision probability theory concepts can be successfully applied even at a fairly coarse spatial resolution.
      Sun Glint
      Tamás Várnai [UMBC] discussed the EPIC Glint Product as well as impacts of sun glint off ice clouds on other EPIC data products – see Figure 3. The cloud glints come mostly from horizontally oriented ice crystals and have strong impact in EPIC cloud retrievals. Glints increase retrieved cloud fraction, the retrieved cloud optical depth, and cloud height. Várnai also reported that the EPIC glint product is now available at the ASDC. It is expected that glints yield additional new insights about the microphysical and radiative properties of ice clouds.
      Figure 3. EPIC image taken over Mexico on July 4, 2018. The red, white and blue spot over central Mexico is the result of Sun glint reflecting off high clouds containing ice crystals. EPIC is particularly well suited for studies of ice clouds that cause Sun glint, because unlike most other instruments, it uses a filter wheel to take images at multiple wavelengths, which means the image for each wavelength is obtained at a slightly different time. For example, it takes four minutes to cycle from red to blue. During that time, Earth moves by ~100 km (~62 mi) meaning each image will capture a slightly different scene. Brightness contrasts between images can be used to identify glint signals. Image credit: Tamas Vanai Alexander Kostinski [Michigan Technology University] reported on long-term changes and semi-permanent features, e.g., ocean glitter. They introduced pixel-pinned temporally and conditionally averaged reflectance images, uniquely suited to the EPIC observational circumstances. The preliminary resulting images (maps), averaged over months and conditioned on cover type (land, ocean, or clouds), show seasonal dependence at a glance (e.g., by an apparent extent of polar caps).
      More EPIC Science Results
      Guoyong Wen [Morgan State University] discussed spectral properties of the EPIC observations near backscattering, including four cases when the scattering angle reaches about 178° (only 2° from perfect backscattering). The enhancement addresses changes in scattering angle observed in 2020. (Scattering angle is a function of wavelength, because according to Mie scattering theory, the cloud scattering phase function in the glory region is wavelength dependent.) Radiative transfer calculations showed that the change in scattering angles has the largest impact on reflectance in the red and NIR channels at 680 nm and 780 nm and the smallest influence on reflectance in the UV channel at 388 nm – consistent with EPIC observations. The change of global average cloud amount also plays an important role in the reflectance enhancement.
      Nick Gorkavyi [SSAI] talked about future plans to deploy a wide-angle camera and a multislit spectrometer on the Moon’s surface for whole-Earth observations to complement EPIC observations. Gorkavyi explained that the apparent vibrational movement of Earth in the Moon’s sky complicates observations of Earth. This causes the center of Earth to move in the Moon’s sky in a rectangle, measuring 13.4° × 15.8° with a period of 6 years. 
      Jay Herman [UMBC] reported on EPIC O3 and trends from combining Nimbus 7/Solar Backscatter Ultraviolet (SBUV), the SBUV-2 series, and OMPS–Nadir Mapper (NM) data. (OMPS is made up of three instruments: a Nadir Mapper (NM), Nadir Profiler, and Limb Profiler. OMPS NM is a total ozone sensor). Herman compared EPIC O3 data to OMPS NM data, which showed good agreement (especially summer values) for moderate solar zenith angle (SZA). Comparison with long-term O3 time series (1978–2021) revealed that there were trends and latitude dependent O3 turn-around dates (1994–1998). Herman emphasized that global O3 models do not show this effect but rather have only a single turn-around date around 2000.
      Alexander Radkevich [LaRC] presented a poster that showed a comparative analysis of air quality monitoring by orbital and suborbital NASA missions using the DSCOVR EPIC O3 product as well as Pandora total O3 column retrievals. Comparison of the June 2023 total column O3 from EPIC data to the same periods in previous years revealed a significant – around 50 DU – increase of total O3 column in the areas impacted by the plume from 2023 Canadian wildfires.
      Conclusion
      At the end of the meeting Alexander Marshak, Jay Herman, and Adam Szabo discussed how to make the EPIC and NISTAR instruments more visible in the community. The EPIC website now allows visitors to observe daily fluctuations of aerosol index, cloud fraction, and the ocean surface – as observed from the “L1” point,  nearly one million miles away from Earth! More daily products, (e.g., cloud and aerosol height, total leaf area index, and sunlit leaf area index) will be added soon.
      The 2023 DSCOVR EPIC and NISTAR Science Team Meeting provided an opportunity 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 are found on the EPIC website. (UPDATE: The next DSCOVR EPIC and NISTAR STM will be held on October 16–18, 2024. Check the website for more details as the date approaches.)
      Alexander Marshak
      NASA’s Goddard Space Flight Center
      alexander.marshak@nasa.gov

      Adam Szabo
      NASA’s Goddard Space Flight Center
      adam.szabo@nasa.gov
      View the full article
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