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NASA NTRSDate not supplied

Thermal Modelling of the In-Situ Consolidation of Automated Fiber Placement Of Thermoplastic Composites

NASA is developing carbon fiber reinforced thermoplastic composites processing methods under the Hi-rate Composites Aircraft Manufacturing (HiCAM) project. The in-situ consolidation automated fiber placement (AFP) of thermoplastics (ICAT) process has high potential to increase manufacturing throughput and lower costs as it combines the repeatability and fast lay down rates of AFP with the thermoformability of thermoplastic materials to achieve part consolidation out of the autoclave. Physics-based process models are employed in the ICAT process development to understand, fundamentally, the thermal response of the carbon fiber (CF)/polyaryletherketone (PAEK) material during the rapid heating and cooling associated with laser-assisted AFP. A one-dimensional (1-D) closed-form model was developed capable of predicting the temperature profile through-the-thickness of the tape material. In addition, a two-dimensional (2-D) model was developed to predict the heat transfer through-the-thickness and in the laydown x-direction of the AFP head motion. The solution of the Fourier heat-transfer equations in the 2-D model is approximated using the explicit finite difference numerical method. The temperature profile during placement of PAEK slit-tape materials at various laser target temperatures and placement speeds were measured during ICAT process development trials at Electroimpact®, Inc. †† and the resulting experimental data is compared with the predictions of the 1-D and 2-D models.

Christopher J. Stelter↗

NASA NTRS1992

Analysis of satellite-derived ozone and water vapor measurements

Research under this grant has involved analyses of satellite-derived measurements of water vapor and total ozone. Upper tropospheric water vapor data from the Nimbus 7 temperature-humidity infrared radiometer (THIR) 6.7 micron channel were analyzed by Fourier transformation to provide wavenumber spectra for a case of an upper level system over Europe. The power law spectrum for horizontal scales from 60 to several hundred km suggests that when convective cloud energy sources are not present, the enstrophy-cascading process (with variance proportional to the minus three power of wavenumber) may hold to much smaller scales than previously thought. Several investigations of the middle atmosphere (stratosphere and mesosphere) were also conducted. Slow atmospheric oscillations with periods of 1-2 months were investigated in total ozone measurements and in ionospheric data. Using one-point correlation maps and total ozone mapping spectrometer (TOMS) data, strong statistical evidence was found for the planetary-scale oscillations at these periods. A dipole-like pattern in the tropical equatorial Indian ocean-western Pacific region was documented, along with wavetrain-like patterns emanating into the extratropics. While attempting to follow the oscillations upward above stratosphere, oscillations were studied in ionospheric data (D-region radio wave absorption, in the upper mesosphere, around 80-90 km altitude). Cross-spectral analyses with solar flux data revealed that much of the observed 1-2 month variance in the ionospheric D-region was well correlated to solar variations. Further research has involved investigations of the photochemical lifetime of greenhouse gases methane and nitrous oxide. Using Nimbus 7 satellite data, a new analysis technique was employed to determine the lifetime of these gases in situ in the upper stratosphere. The lifetimes are found to be in good agreement with theoretical estimates.

Stanford, John L.↗

NASA NTRS2016

Evaluating a Priori Ozone Profile Information Used in TEMPO Tropospheric Ozone Retrievals

Ozone (O3) is a greenhouse gas and toxic pollutant which plays a major role in air quality. Typically, monitoring of surface air quality and O3 mixing ratios is primarily conducted using in situ measurement networks. This is partially due to high-quality information related to air quality being limited from space-borne platforms due to coarse spatial resolution, limited temporal frequency, and minimal sensitivity to lower tropospheric and surface-level O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite is designed to address these limitations of current space-based platforms and to improve our ability to monitor North American air quality. TEMPO will provide hourly data of total column and vertical profiles of O3 with high spatial resolution to be used as a near-real-time air quality product.TEMPO O3 retrievals will apply the Smithsonian Astrophysical Observatory profile algorithm developed based on work from GOME, GOME-2, and OMI. This algorithm uses a priori O3 profile information from a climatological data-base developed from long-term ozone-sonde measurements (tropopause-based (TB) O3 climatology). It has been shown that satellite O3 retrievals are sensitive to a priori O3 profiles and covariance matrices. During this work we investigate the climatological data to be used in TEMPO algorithms (TB O3) and simulated data from the NASA GMAO Goddard Earth Observing System (GEOS-5) Forward Processing (FP) near-real-time (NRT) model products. These two data products will be evaluated with ground-based lidar data from the Tropospheric Ozone Lidar Network (TOLNet) at various locations of the US. This study evaluates the TB climatology, GEOS-5 climatology, and 3-hourly GEOS-5 data compared to lower tropospheric observations to demonstrate the accuracy of a priori information to potentially be used in TEMPO O3 algorithms. Here we present our initial analysis and the theoretical impact on TEMPO retrievals in the lower troposphere.

TEMPO↗

NASA NTRS2017

Development of Storage Methods for Saccharomyces Strains to be Utilized for In situ Nutrient Production in Long-Duration Space Missions

Long-duration space missions will benefit from closed-loop life support technologies that minimize mass, volume, and power as well as decrease reliance on Earth-based resupply. A system for In situ production of essential vitamins and nutrients can address the documented problem of degradation of stored food and supplements. Research has shown that the edible yeast Saccharomyces cerevisiae can be used as an on-demand system for the production of various compounds that are beneficial to human health. A critical objective in the development of this approach for long-duration space missions is the effective storage of the selected microorganisms. This research investigates the effects of different storage methods on survival rates of the non-sporulating probiotic S. boulardii, and S. cerevisiae spores and vegetative cells. Dehydration has been shown to increase long-term yeast viability, which also allows increased shelf-life and reduction in mass and volume. The process of dehydration causes detrimental effects on vegetative cells, including oxidative damage and membrane disruption. To maximize cell viability, various dehydration methods are tested here, including lyophilization (freeze-drying), air drying, and dehydration by vacuum. As a potential solution to damage caused by lyophilization, the efficacy of various cryoprotectants was tested. Furthermore, in an attempt to maintain higher survival rates, the effect of temperature during long-term storage was investigated. Data show spores of the wild-type strain to be more resilient to dehydration-related stressors than vegetative cells of either strain, and maintain high viability rates even after one year at room temperature. In the event that engineering the organism to produce targeted nutrient compounds interferes with effective sporulation of S. cerevisiae, a more robust method for improving vegetative cell storage is being sought. Therefore, anhydrobiotic engineering of S. cerevisiae and S. boulardii is being conducted

nutrient↗

NASA NTRS2018

Smallholder Crop Area Mapped with Wall-To-Wall WorldView Sub-Meter Panchromatic Image Texture: A Test Case for Tigray, Ethiopia

Global food production in the developing world occurs within sub-hectare fields that are difficult to identify with moderate resolution satellite imagery. Knowledge about the distribution of these fields is critical in food security programs. We developed a semi-automated image segmentation approach using wall-to-wall sub-meter imagery with high-performance computing to map crop area (CA) throughout Tigray, Ethiopia that encompasses over 41,000 km (exp 2). Multiple processing streams were tested to minimize mapping error while applying five unique smoothing kernels to capture differences in land surface texture associated to CA. Typically, very-small fields (mean < 2 ha) have a smooth image roughness compared to natural scrub/shrub woody vegetation at the ~1m scale and these features can be segmented in panchromatic imagery with multi-level histogram thresholding. Multi-temporal very-high resolution (VHR) panchromatic imagery with multi-spectral VHR are sufficient in extracting critical CA information needed in food security programs. A 2011 to 2015 CA map was produced, using over 3000 WorldView-1 panchromatic images wall-to-wall in 1/2 deg mosaics for Tigray, Ethiopia. CA was evaluated with nearly 3000 WorldView-2 2m multispectral 250 X 250 m image subsets by seven expert interpretations, and with in-situ global positioning system photography. CA estimates ranged from 32 to 41% in sub regions of Tigray with median maximum per bin commission and omission errors of 11% and 1% respectively, with most of the error occurring in bins <15%. This empirical, simple, and low direct cost approach via U.S. government license agreement to access commercial VHR data, could be a viable big-data high-performance computing methodology to extract wall-to-wall CA for other regions of the world that have very-small agriculture fields with similar image texture."

Ethiopia↗

NASA NTRS2017

Development of Storage Methods for Saccharomyces Strains to be Utilized for In Situ Nutrient Production in Long-Duration Space Missions

life support↗

NASA NTRS2026

The Future of in-Situ Sequencing-Based Microbial Monitoring: Development of a Shelf-Stable Method for Artemis and Beyond

Microbial monitoring onboard the International Space Station (ISS) is essential for assessing the efficiency of the Environmental Control and Life Support Systems (ECLSS) and providing insight into potential risk to both crew and spacecraft. Historically, this monitoring required the need to culture organisms onboard, return these cultures to Earth, and then complete the identifications, a process that would take months. Over the past decade, and through numerous payloads, advances in molecular biology have enabled in-flight microbial identifications using nanopore sequencing. The swab-to-sequencer method resulting from these efforts was transitioned from research to operations for microbial monitoring under the Crew Health Care Systems (CHeCS) BioMole. Collectively, these accomplishments have propelled the swab-to-sequencer method to be selected as the Microbial Surface Monitor (MSM) for Gateway, as well as a payload on Artemis IV. However, the lack of cold stowage availability for Artemis requires modifications to the entire method due to the thermal instability of the reagents required for sample preparation. To achieve this, new development, optimization, and validations were undertaken. Key considerations included enzyme concentration, buffer compatibility, and equal or enhanced sensitivity and specificity. At each step, thorough side-by-side comparisons with the current ISS method were performed. The development of a robust shelf-stable method will ensure continued sequencing-based microbial monitoring for Artemis and beyond, providing data in near real-time, enhancing risk response time, and yielding clear insight into the microbiome of spacecraft.

Christian G Mena↗

NASA NTRS2011

A Critical Examination of Spatial Biases Between MODIS and MISR Aerosol Products - Application for Potential AERONET Deployment

AErosol RObotic NETwork (AERONET) data are the primary benchmark for evaluating satellite-retrieved aerosol properties. However, despite its extensive coverage, the representativeness of the AERONET data is rarely discussed. Indeed, many studies have shown that satellite retrieval biases have a significant degree of spatial correlation that may be problematic for higher-level processes or inverse-emissions-modeling studies. To consider these issues and evaluate relative performance in regions of few surface observations, cross-comparisons between the Aerosol Optical Depth (AOD) products of operational MODIS Collection 5.1 Dark Target (DT) and operational MODIS Collection 5.1 Deep Blue (DB) with MISR version 22 were conducted. Through such comparisons, we can observe coherent spatial features of the AOD bias while side-stepping the full analysis required for determining when or where either retrieval is more correct. We identify regions where MODIS to MISR AOD ratios were found to be above 1.4 and below 0.7. Regions where lower boundary condition uncertainty is likely to be a dominant factor include portions of Western North America, the Andes mountains, Saharan Africa, the Arabian Peninsula, and Central Asia. Similarly, microphysical biases may be an issue in South America, and specific parts of Southern Africa, India Asia, East Asia, and Indonesia. These results help identify high-priority locations for possible future deployments of both in situ and ground based remote sensing measurements. The Supplement includes a km1 file.

Shi, Y.↗

NASA NTRS2015

Aqueous Alteration on Mars: Evidence from Landed Missions

Mineralogical and geochemical data returned by orbiters and landers over the past 15 years have substantially enhanced our understanding of the history of aqueous alteration on Mars. Here, we summarize aqueous processes that have been implied from data collected by landed missions. Mars is a basaltic planet. The geochemistry of most materials has not been “extensively” altered by open-system aqueous processes and have average Mars crustal compositions. There are few examples of open-system alteration, such as Gale crater’s Pahrump Hills mudstone. Types of aqueous alteration include (1) acid-sulfate and (2) hydrolytic (circum-neutral/alkaline pH) with varying water-to-rock ratios. Several hypotheses have been suggested for acid-sulfate alteration including (1) oxidative weathering of ultramafic igneous rocks containing sulfides; (2) sulfuric acid weathering of basaltic materials; (3) acid fog weathering of basaltic materials; and (4) near-neutral pH subsurface solutions rich in Fe (sup 2 plus) that rapidly oxidized to Fe (sup 3 plus) producing excess acidity. Meridiani Planum’s sulfate-rich sedimentary deposit containing jarosite is the most “famous” acid-sulfate environment visited on Mars, although ferric sulfate-rich soils are common in Gusev crater’s Columbia Hills and jarosite was recently discovered in the Pahrump Hills. An example of aqueous alteration under circum-neutral pH conditions is the formation of Fe-saponite with magnetite in situ via aqueous alteration of olivine in Gale crater’s Sheepbed mudstone. Circum-neutral pH, hydrothermal conditions were likely required for the formation of Mg-Fe carbonate in the Columbia Hills. Diagenetic features (e.g., spherules, fracture filled veins) indicate multiple episodes of aqueous alteration/diagenesis in most sedimentary deposits. However, low water-to-rock ratios are prominent at most sites visited by landed missions (e.g., limited water for reaction to form crystalline phases possibly resulting in large amounts of short-range ordered materials and little physical separation of primary and secondary materials). Most of the aqueous alteration appears to have occurred early in the planet’s history; however, minor aqueous alteration may be occurring at the surface today (e.g., thin films of water forming carbonates akin to those discovered by Phoenix).

Ming, Douglas W.↗

NASA NTRS2016

Evaluating A Priori Ozone Profile Information Used in TEMPO Tropospheric Ozone Retrievals

Ozone (O3) is a greenhouse gas and toxic pollutant which plays a major role in air quality. Typically, monitoring of surface air quality and O3 mixing ratios is primarily conducted using in situ measurement networks. This is partially due to high-quality information related to air quality being limited from space-borne platforms due to coarse spatial resolution, limited temporal frequency, and minimal sensitivity to lower tropospheric and surface-level O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite is designed to address these limitations of current space-based platforms and to improve our ability to monitor North American air quality. TEMPO will provide hourly data of total column and vertical profiles of O3 with high spatial resolution to be used as a near-real-time air quality product. TEMPO O3 retrievals will apply the Smithsonian Astrophysical Observatory profile algorithm developed based on work from GOME, GOME-2, and OMI. This algorithm uses a priori O3 profile information from a climatological data-base developed from long-term ozone-sonde measurements (tropopause-based (TB) O3 climatology). It has been shown that satellite O3 retrievals are sensitive to a priori O3 profiles and covariance matrices. During this work we investigate the climatological data to be used in TEMPO algorithms (TB O3) and simulated data from the NASA GMAO Goddard Earth Observing System (GEOS-5) Forward Processing (FP) near-real-time (NRT) model products. These two data products will be evaluated with ground-based lidar data from the Tropospheric Ozone Lidar Network (TOLNet) at various locations of the US. This study evaluates the TB climatology, GEOS-5 climatology, and 3-hourly GEOS-5 data compared to lower tropospheric observations to demonstrate the accuracy of a priori information to potentially be used in TEMPO O3 algorithms. Here we present our initial analysis and the theoretical impact on TEMPO retrievals in the lower troposphere.

ozone↗

NASA NTRS1999

Crystal Growth Using MEPHISTO

The shuttle flight experiment "In Situ Monitoring of Crystal Growth Using MEPHISTO" was accomplished during STS-87 as part of the fourth flight of the United States Microgravity Payload (USMP-4), which was flown from November 19 to December 5, 1997. The data returned from that flight are just now beginning to yield quantitative results. This project is an international collaboration: the furnace system known as MEPHISTO was built in France by CNES (French National Space Agency) and CEA (French Atomic Energy Commission); the principal investigator, Prof. Reza Abbaschian, is from the University of Florida at Gainesville; and numerical and analytical modeling support includes collaborators from the University of New South Wales, Australia, the University of Wisconsin at Milwaukee, the National Institute of Standards and Technology, and the NASA Lewis Research Center. MEPHISTO is a French acronym that translates into English as Materials for the Study of Interesting Phenomena of Solidification on Earth and in Orbit. Since this was the fourth flight of the MEPHISTO furnace, the experiment is referred to as MEPHISTO-4. MEPHISTO-4 was a directional solidification experiment that studied the liquid-to-solid transformation of bismuth alloyed with tin. Directional solidification is a freezing technique common to the processing of the electronic materials used in integrated circuits and detectors, such as silicon and germanium. When liquids are frozen on Earth, they must be cooled. The cooling causes stirring because of density variations in the liquid. This stirring, known as natural convection, influences the quality of the resulting solid. During freezing, regions of high and low concentrations of tin are created. This introduces another important phenomenon: diffusion, or the movement by molecular action of matter from regions of high concentration to regions of lower concentration. In MEPHISTO-4, it is tin that diffuses from the high-concentration region in front of the solid-liquid interface to more distant low-concentration regions.

deGroh, Henry C., III↗

NASA NTRS2012

Quality Assessment of Landsat Surface Reflectance Products Using MODIS Data

Surface reflectance adjusted for atmospheric effects is a primary input for land cover change detection and for developing many higher level surface geophysical parameters. With the development of automated atmospheric correction algorithms, it is now feasible to produce large quantities of surface reflectance products using Landsat images. Validation of these products requires in situ measurements, which either do not exist or are difficult to obtain for most Landsat images. The surface reflectance products derived using data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS), however, have been validated more comprehensively. Because the MODIS on the Terra platform and the Landsat 7 are only half an hour apart following the same orbit, and each of the 6 Landsat spectral bands overlaps with a MODIS band, good agreements between MODIS and Landsat surface reflectance values can be considered indicators of the reliability of the Landsat products, while disagreements may suggest potential quality problems that need to be further investigated. Here we develop a system called Landsat-MODIS Consistency Checking System (LMCCS). This system automatically matches Landsat data with MODIS observations acquired on the same date over the same locations and uses them to calculate a set of agreement metrics. To maximize its portability, Java and open-source libraries were used in developing this system, and object-oriented programming (OOP) principles were followed to make it more flexible for future expansion. As a highly automated system designed to run as a stand-alone package or as a component of other Landsat data processing systems, this system can be used to assess the quality of essentially every Landsat surface reflectance image where spatially and temporally matching MODIS data are available. The effectiveness of this system was demonstrated using it to assess preliminary surface reflectance products derived using the Global Land Survey (GLS) Landsat images for the 2000 epoch. As surface reflectance likely will be a standard product for future Landsat missions, the approach developed in this study can be adapted as an operational quality assessment system for those missions.

Landsat↗

NASA NTRS2021

A Chlorophyll-a Algorithm for Landsat-8 Based on Mixture Density Networks

Retrieval of aquatic biogeochemical variables, such as the near-surface concentration of chlorophyll-a (Chla) in inland and coastal waters via remote observations, has long been regarded as a challenging task. This manuscript applies Mixture Density Networks (MDN) that use the visible spectral bands available by the Operational Land Imager (OLI) aboard Landsat-8 to estimate Chla. We utilize a database of co-located in situ radiometric and Chla measurements (N = 4,354), referred to as Type A data, to train and test an MDN model (MDN(A)). This algorithm’s performance, having been proven for other satellite missions, is further evaluated against other widely used machine learning models (e.g., support vector machines), as well as other domain-specific solutions (OC3), and shown to offer significant advancements in the field. Our performance assessment using a held-out test data set suggests that a 49% (median) accuracy with near-zero bias can be achieved via the MDN(A) model, offering improvements of 20 to 100% in retrievals with respect to other models. The sensitivity of the MDN(A) model and benchmarking methods to uncertainties from atmospheric correction (AC) methods, is further quantified through a semi-global matchup dataset (N = 3,337), referred to as Type B data. To tackle the increased uncertainties, alternative MDN models (MDN(B)) are developed through various features of the Type B data (e.g., Rayleigh-corrected reflectance spectra ρ(s)). Using held-out data, along with spatial and temporal analyses, we demonstrate that these alternative models show promise in enhancing the retrieval accuracy adversely influenced by the AC process. Results lend support for the adoption of MDN(B) models for regional and potentially global processing of OLI imagery, until a more robust AC method is developed. Index Terms—Chlorophyll-a, coastal water, inland water, Landsat-8, machine learning, ocean color, aquatic remote sensing.

Brandon Smith↗

NASA NTRS1993

Experimental Determination of in Situ Utilization of Lunar Regolith for Thermal Energy Storage

A Lunar Thermal Energy from Regolith (LUTHER) experiment has been designed and fabricated at the NASA Lewis Research Center to determine the feasibility of using lunar soil as thermal energy storage media. The experimental apparatus includes an alumina ceramic canister (25.4 cm diameter by 45.7 cm length) which contains simulated lunar regolith, a heater (either radiative or conductive), 9 heat shields, a heat transfer cold jacket, and 19 type B platinum rhodium thermocouples. The simulated lunar regolith is a basalt, mined and processed by the University of Minnesota, that closely resembles the lunar basalt returned to earth by the Apollo missions. The experiment will test the effects of vacuum, particle size, and density on the thermophysical properties of the regolith. The properties include melt temperature (range), specific heat, thermal conductivity, and latent heat of storage. Two separate tests, using two different heaters, will be performed to study the effect of heating the system using radiative and conductive heat transfer. The physical characteristics of the melt pattern, material compatibility of the molten regolith, and the volatile gas emission will be investigated by heating a portion of the lunar regolith to its melting temperature (1435 K) in a 10(exp -4) pascal vacuum chamber, equipped with a gas spectrum analyzer. A finite differencing SINDA model was developed at NASA Lewis Research Center to predict the performance of the LUTHER experiment. The analytical results of the code will be compared with the experimental data generated by the LUTHER experiment. The code will predict the effects of vacuum, particle size, and density has on the heat transfer to the simulated regolith.

Richter, Scott W.↗

NASA NTRS2003

The CEOP Inter-Monsoon Studies (CIMS)

Prediction of climate relies on models, and better model prediction depends on good model physics. Improving model physics requires the maximal utilization of climate data of the past, present and future. CEOP provides the first example of a comprehensive, integrated global and regional data set, consisting of globally gridded data, reference site in-situ observations, model location time series (MOLTS), and integrated satellite data for a two-year period covering two complete annual cycles of 2003-2004. The monsoon regions are the most important socio-economically in terms of devastation by floods and droughts, and potential impacts from climate change md fluctuatinns nf the hydrologic cyc!e. Scientifically, it is most challenging, because of complex interactions of atmosphere, land and oceans, local vs. remote forcings in contributing to climate variability and change in the region. Given that many common features, and physical teleconnection exist among different monsoon regions, an international research focus on monsoon must be coordinated and sustained. Current models of the monsoon are grossly inadequate for regional predictions. For improvement, models must be confronted with relevant observations, and model physic developers must be made to be aware of the wealth of information from existing climate data, field measurements, and satellite data that can be used to improve models. Model transferability studles must be conducted. CIMS is a major initiative under CEOP to engage the modeling and the observational communities to join in a coordinated effort to study the monsoons. The objectives of CIMS are (a) To provide a better understanding of fundamental physical processes (diurnal cycle, annual cycle, and intraseasonal oscillations) in monsoon regions around the world and (b) To demonstrate the synergy and utility of CEOP data in providing a pathway for model physics evaluation and improvement. In this talk, I will present the basic concepts of CIMS and the key scientific problems facing monsoon climates and provide examples of common monsoon features, and possible monsoon induced teleconnections linking different parts of the world.

Lau, William K. M.↗

NASA NTRS2004

Improving the Transition of Earth Satellite Observations from Research to Operations

There are significant gaps between the observations, models, and decision support tools that make use of new data. These challenges include: 1) Decreasing the time to incorporate new satellite data into operational forecast assimilation systems, 2) Blending in-situ and satellite observing systems to produce the most accurate and comprehensive data products and assessments, 3) Accelerating the transition from research to applications through national test beds, field campaigns, and pilot demonstrations, and 4) Developing the partnerships and organizational structures to effectively transition new technology into operations. At the Short-term Prediction Research and Transition (SPORT) Center in Huntsville, Alabama, a NASA-NOAA-University collaboration has been developed to accelerate the infusion of NASA Earth science observations, data assimilation and modeling research into NWS forecast operations and decision-making. The SPoRT Center research focus is to improve forecasts through new observation capability and the regional prediction objectives of the US Weather Research Program dealing with 0-1 day forecast issues such as convective initiation and 24-hr quantitative precipitation forecasting. The near real-time availability of high-resolution experimental products of the atmosphere, land, and ocean from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Advanced Infrared Spectroradiometer (AIRS), and lightning mapping systems provide an opportunity for science and algorithm risk reduction, and for application assessment prior to planned observations from the next generation of operational low Earth orbiting and geostationary Earth orbiting satellites. This paper describes the process for the transition of experimental products into forecast operations, current products undergoing assessment by forecasters, and plans for the future. The SPoRT Web page is at (http://www.ghcc.msfc.nasa.gov/sport).

Goodman, Steven J.↗

NASA NTRSDate not supplied

Merging Analytic Collaborative Frameworks with New Observing Strategies Toward a Digital Twin: Earth – Episodic Pulse Event Impacts on Ocean Carbon Cycle as an Example

Virtual representations of the Earth will allow us to address some of the most critical environmental issues of our time. Here, we show the first steps toward representation of riverine, estuarine, and coastal carbon processes to enable scenario driven “what-if” analyses of the carbon system and human footprint. Excess sediment and nutrient runoff from land-based human activities impact water quality and can pose serious threats to coastal and marine ecosystems. Episodic pulse events, such as extreme precipitation events, can increase the amount of nutrients entering estuaries and coastal regions, potentially leading to large phytoplankton blooms followed by anoxic conditions. Consequences of coastal runoff are predicted to increase with the higher intensity and frequency of extreme events. Beyond the threat to coastal ecosystems, recent findings suggest these episodic pulses might play a significant role for biological production influencing regional and global carbon fluxes and budgets. An improved understanding of these events through optimal, dynamic observing strategies will increase our knowledge of the land-ocean continuum and how regional events and nutrient fluxes affect the carbon cycle and ocean ecosystem. This conceptual framework enables focused science investigations by pairing data analytics and artificial intelligence tools (otherwise termed an Analytic Center Framework, ACF) with targeted measurement acquisition through distributed sensing and intelligent asset tasking (or New Observing Strategies, NOS). This NOS and ACF iterative approach acquires and integrates complementary and coincident satellite, in-situ and model data to build a more complete and in-depth picture of science phenomena. Specifically, Apache Science Data Analytic Platform (SDAP) is extended to incorporate relevant datasets for data access, harmonized analysis, and anomaly detection. When conditions are met for a likely pulse event, NASA’s D-SHIELD (Distributed Spacecraft with Heuristic Intelligence to Enable Logistical Decisions) tool is triggered to optimize asset overpass frequency and schedule observations for persistent monitoring. Targeted data is ingested by SDAP for enhanced investigation via iterative analysis until the trigger criteria is no longer met - steps toward a digital twin.

Laura Rogers↗

NASA NTRS2020

The Chlorine-Isotopic Composition of Lunar KREEP From Magnesian-Suite Troctolite 76535

We conducted in-situ Cl isotopic measurements of apatite within intercumulus regions and within a holocrystalline olivine-hosted melt inclusion in magnesian-suite troctolite 76535 from Apollo 17. These data were collected to place constraints on the Cl-isotopic composition of the last liquid to crystallize from the lunar magma ocean (i.e., urKREEP, named after its enrichments in incompatible lithophile trace elements like potassium, rare earth elements, and phosphorus). The apatite in the olivine-hosted melt inclusion and within the intercumulus regions of the sample yielded Cl-isotopic compositions of 28.3 ± 0.9 ‰ (2σ) and 30.3 ± 1.1 ‰ (2σ), respectively. The concordance of these values from both textural regimes we analyzed indicates that the Cl-isotopic composition of apatites in 76535 likely represents the Cl-isotopic composition of the KREEP-rich magnesian-suite magmas. Based on the age of 76535, these results imply that the KREEP reservoir attained a Cl-isotopic composition of 28–30 ‰ by at least 4.31 Ga, consistent with the onset of Cl-isotopic fractionation at the time of lunar magma ocean crystallization or shortly thereafter. Moreover, lunar samples that yield Cl-isotopic compositions higher than the value for KREEP are likely affected by secondary processes such as impacts and/or magmatic degassing. The presence of KREEP-rich olivine-hosted melt inclusions within one of the most pristine and ancient KREEP-rich rocks from the Moon provides a new opportunity to characterize the geochemistry of KREEP. In particular, a broader analysis of stable isotopic compositions of highly and moderately volatile elements could provide an unprecedented advancement in our characterization of the geochemical composition of the KREEP reservoir and of volatile-depletion processes during magma ocean crystallization, more broadly.

Francis M. McCubbin↗