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At least 271 records · Page 15

Fortran for the nineties

Fortran has largely enjoyed prominence for the past few decades as the computer programming language of choice for numerically intensive scientific, engineering, and process control applications. Fortran's well understood static language syntax has allowed resulting parsers and compiler optimizing technologies to often generate among the most efficient and fastest run-time executables, particularly on high-end scalar and vector supercomputers. Computing architectures and paradigms have changed considerably since the last ANSI/ISO Fortran release in 1978, and while FORTRAN 77 has more than survived, it's aged features provide only partial functionality for today's demanding computing environments. The simple block procedural languages have been necessarily evolving, or giving way, to specialized supercomputing, network resource, and object-oriented paradigms. To address these new computing demands, ANSI has worked for the last 12-years with three international public reviews to deliver Fortran 90. Fortran 90 has superseded and replaced ISO FORTRAN 77 internationally as the sole Fortran standard; while in the US, Fortran 90 is expected to be adopted as the ANSI standard this summer, coexisting with ANSI FORTRAN 77 until at least 1996. The development path and current state of Fortran will be briefly described highlighting the many new Fortran 90 syntactic and semantic additions which support (among others): free form source; array syntax; new control structures; modules and interfaces; pointers; derived data types; dynamic memory; enhanced I/O; operator overloading; data abstraction; user optional arguments; new intrinsics for array, bit manipulation, and system inquiry; and enhanced portability through better generic control of underlying system arithmetic models. Examples from dynamical astronomy, signal and image processing will attempt to illustrate Fortran 90's applicability to today's general scalar, vector, and parallel scientific and engineering requirements and object oriented programming paradigms. Time permitting, current work proceeding on the future development of Fortran 2000 and collateral standards will be introduced.

Himer, J. T.↗

Development of Level of Detail System and First-Person Camera for the GCAS Visualization Suite

The use of data-driven simulations has become standard practice as part of planning for future space missions. These simulations allow visualizing the data interactively to show what the data represents, as well as the importance of the data in the context of the mission. Using this visualized data can enhance users’ understanding of it and accelerate analysis efforts related to missions planned around it. Three-dimensional (3D) visualization software was developed to allow creating 3D representations of various communication systems, as well as the physical terrain of the Moon, for upcoming missions. The goal of this software development effort was to create interactive visualization capabilities in the Glenn Research Center Communication Analysis Suite (GCAS) using data exported from MATLAB® (MathWorks, Inc.) scripts. This software had the functionality to visualize the line of sight and dynamic link margins of the communication satellites orbiting the Earth and the Moon. One important addition to this was the visualization of the terrain data located within the GeoTIFF files, which were produced in an effort to understand the Moon’s terrain. Proper displacement values of this data have to be visualized to showcase where craters are located and how the shadow casting works with said craters at different points of the day, as well as analysis of possible landing sites for future lunar expeditions. The graphics library coded in JavaScript, three.js, had been previously selected for developing this visualization software. The software was revised to conform to modern standards, then further developed to convert the MATLAB® data into JavaScript 3D objects and Blender GL Transmission Format Binary file (GLB) objects, which were to be imported into the scene. In the process, a variety of other testing projects were created to be combined with this project at a later point; these included the first-person camera movements around spherical objects to portray human movement around the Moon, GeoTIFF loading methods, data transfer methods for incorporating the elevation data into the scene, and level of detail (LOD) capabilities to decrease memory usage and rendering time.

Visualization↗

Hybrid Exploration Agent Platform and Sensor Web System

A sensor web to collect the scientific data needed to further exploration is a major and efficient asset to any exploration effort. This is true not only for lunar and planetary environments, but also for interplanetary and liquid environments. Such a system would also have myriad direct commercial spin-off applications. The Hybrid Exploration Agent Platform and Sensor Web or HEAP-SW like the ANTS concept is a Sensor Web concept. The HEAP-SW is conceptually and practically a very different system. HEAP-SW is applicable to any environment and a huge range of exploration tasks. It is a very robust, low cost, high return, solution to a complex problem. All of the technology for initial development and implementation is currently available. The HEAP Sensor Web or HEAP-SW consists of three major parts, The Hybrid Exploration Agent Platforms or HEAP, the Sensor Web or SW and the immobile Data collection and Uplink units or DU. The HEAP-SW as a whole will refer to any group of mobile agents or robots where each robot is a mobile data collection unit that spends most of its time acting in concert with all other robots, DUs in the web, and the HEAP-SWs overall Command and Control (CC) system. Each DU and robot is, however, capable of acting independently. The three parts of the HEAP-SW system are discussed in this paper. The Goals of the HEAP-SW system are: 1) To maximize the amount of exploration enhancing science data collected; 2) To minimize data loss due to system malfunctions; 3) To minimize or, possibly, eliminate the risk of total system failure; 4) To minimize the size, weight, and power requirements of each HEAP robot; 5) To minimize HEAP-SW system costs. The rest of this paper discusses how these goals are attained.

Stoffel, A. William↗

Using Total Lightning Observations to Enhance Lightning Safety

Lightning is often the underrated threat faced by the public when it comes to dangerous weather phenomena. Typically, larger scale events such as floods, hurricanes, and tornadoes receive the vast majority of attention by both the general population and the media. This comes from the fact that these phenomena are large, longer lasting, can impact a large swath of society at one time, and are dangerous events. The threat of lightning is far more isolated on a case by case basis, although millions of cloud-to-ground lightning strikes hit this United States each year. While attention is given to larger meteorological events, lightning is the second leading cause of weather related deaths in the United States. This information raises the question of what steps can be taken to improve lightning safety. Already, the meteorological community s understanding of lightning has increased over the last 20 years. Lightning safety is now better addressed with the National Weather Service s access to the National Lightning Detection Network data and enhanced wording in their severe weather warnings. Also, local groups and organizations are working to improve public awareness of lightning safety with easy phrases to remember, such as "When Thunder Roars, Go Indoors." The impacts can be seen in the greater array of contingency plans, from airports to sports stadiums, addressing the threat of lightning. Improvements can still be made and newer technologies may offer new tools as we look towards the future. One of these tools is a network of sensors called a lightning mapping array (LMA). Several of these networks exist across the United States. NASA s Short-term Prediction Research and Transition Center (SPoRT), part of the Marshall Spaceflight Center, has access to three of these networks from Huntsville, Alabama, the Kennedy Space Center, and Washington D.C. The SPoRT program s mission is to help transition unique products and observations into the operational forecast environment. SPoRT has been collaborating with the Huntsville National Weather Service (NWS) Office since 2003 and has since included several other offices to better implement LMA observations into real-time applications. Much of that work has focused on the LMA s ability to detect intra-cloud lightning in addition to cloud-to-ground lightning strikes. Combined, these observations are called total lightning. With total lightning observations, NWS offices can enhance their situational awareness and improve severe weather warnings. Just as importantly, the observed intra-cloud flashes often precede the first cloud-to-ground strike by a few minutes. SPoRT and its partner NWS offices are working to develop visualizations and applications to better utilize these data. However, there is a drawback. The LMAs have a short range of no more than 200 km. This is being addressed with the next generation geostationary satellite, GOES-R, which will boast the Geostationary Lightning Mapper (GLM). SPoRT, in conjunction with NOAA s GOES-R Proving Ground, is working to prepare the end user community for the GLM era using the LMA observations as a demonstration tool. Working collaboratively with our NWS partners, SPoRT is working to determine how best to integrate these future observations to improve both severe storm warnings and lightning safety.

Stano, Geoffrey T.↗

Evaluation of Experimental Data from the Gains Balloon GPS Surface Reflection Instrument

The GPS Surface Reflection Instrument was integrated as an experiment on the GAINS (Global Airocean IN-situ System) 48-hour balloon mission flown in June 2002. The data collected by similar instruments in the past has been used to measure sea state from which ocean surface winds can be accurately estimated. The GPS signal has also been shown to be reflected from wetland areas and even from subsurface moisture. The current version of the instrument has been redesigned to be more compact, use less power, and withstand a greater variation in environmental conditions than previous versions. This instrument has also incorporated a new data collection mode to track 5 direct satellites (providing a continuous navigation solution) and multiplex the remaining 7 channels to track the reflected signal of the satellite tracked in channel 0. The new software mode has been shown to increase the signal to noise ratio of the collected data and enhance the science return of the instrument. During the GAINS balloon flight over the Northwest US, the instrument measured surface reflections as they were detected over the balloon's ground track. Since ground surface elevations in this area vary widely from the WGS-84 ellipsoid altitude, the instrument software has been modified to incorporate a surface altitude correction based on USGS 30-minute Digital Elevation Models. Information presented will include facts about instrument design goals, data collection methodologies and algorithms, and will focus on results of the science data analyses for the mission.

Ganoe, George G.↗

Evaluation of Experimental Data from the GAINS Balloon GPS Surface Reflection Instrument

The GPS Surface Reflection Instrument was integrated as an experiment on the GAINS (Global Airocean IN-situ System) 48-hour balloon mission flown in September 2001. The data collected by similar instruments in the past has been used to measure sea state from which ocean surface winds can be accurately estimated. The GPS signal has also been shown to be reflected from wetland areas and even from subsurface moisture. The current version of the instrument has been redesigned to be more compact, use less power, and withstand a greater variation in environmental conditions than previous versions. This instrument has also incorporated a new data collection mode to track 5 direct satellites (providing a continuous navigation solution) and multiplex the remaining 7 channels to track the reflected signal of the satellite tracked in channel 0. The new software mode has been shown to increase the signal to noise ratio of the collected data and enhance the science return of the instrument. During the 48-hour flight over the Northwest US, the instrument will measure surface reflections that can be detected over the balloon's ground track. Since ground surface elevations in this area vary widely from the WGS-84 ellipsoid altitude, the instrument software has been modified to incorporate a surface altitude correction based on USGS 30-minute Digital Elevation Models. Information presented will include facts about instrument design goals, data collection methodologies and algorithms, and results of the science data analyses for the 48-hour mission.

Gance, George G.↗

Machine Learning Application in Aircraft Engine Conceptual Design

In the current competitive environment, the successful creation and application of machine learning (ML) technologies have become crucial across multiple industries. This study outlines the process of creating and implementing ML models for conceptualizing and evaluating aircraft engines. These models use supervised deep-learning algorithms to analyze patterns within an open-source repository containing data on both production and research conventional turbofan engines. Key focus areas include crucial engine parameters such as thrust-specific fuel consumption (TSFC), engine weight, engine diameter, and turbomachinery stage counts. While developing ML models is fundamental, ensuring their seamless deployment is equally important. To address this, a conversational AI chatbot is constructed using natural language processing (NLP) techniques to facilitate the deployment of these ML models. The comprehensive workflow includes several key stages: gathering and enhancing engine data, training and cross validating the ML models, testing and evaluating their performance, and finally, deploying, monitoring, and updating the ML models. By following this systematic approach, the aim is to streamline the development and deployment process of ML models tailored for aircraft engine conceptual design.

Aircraft Engine↗

Petrographic studies of refractory inclusions from the Murchison meteorite

Textural and mineral-chemical data on freeze-thaw disaggregated refractory inclusions from the Murchison meteorite are reported. The data were obtained with neutron activation analysis, SEM, and spectroscopy, the study revealed corundum-bearing inclusions, spinel-hibonite aggregates and spherules, and spinel-pyroxene and elivine-pyroxene inclusions. One of the three spinel-, pyroxene-, forsterite-rich inclusions had an amoeba-shaped spinel-pyroxene core, implying vapor-to-solid condensation and therefore crystallization from a melt. It is concluded that the meteorite formation encompassed diverse nebular materials, and that further studies of the meteorite will enhance the data base on the planetary nebular processes.

Macpherson, G. J.↗

Remote sensing of evaporite mineral zonation in salt flats (salars)

Compositional zoning within Salar de Atacama and Salar de Llulliallaco has been mapped from Landsat Thematic Mapper (TM) data. The data were enhanced using decorrelation stretching of TM bands 7, 5, and 4, which were considered to possess the majority of the mineralogical information. The resulting 7, 5, 4 (red, green, blue) color composites provide excellent discrimination of evaporite mineral zones within the salar. The interpretation is supported by fieldwork at the Salar de Atacama and spectral considerations. A strong relationship between the mineralogy of a unit and surface roughness was observed in the field, hence there is potential for imaging radar to provide complementary zonal data.

Chapman, J. E.↗

Harmonizing Multi-Disciplinary Data for Applied Research: A Comprehensive Analysis of GES DISC Datasets through NLP and TF-IDF Techniques

Data centers distribute data encompassing multiple disciplines, making it necessary to evaluate dataset applicability to applied research. Typically, these datasets are generated by specialized science teams and consist of single-discipline data, such as atmospheric temperature, pressure, and precipitation, leading to unique dataset formats and access services. However, in applied research, the utilization of datasets from multiple disciplines is commonly necessary. The increasing availability of research literature citing Earth Science datasets presents an opportunity to analyze the usage of datasets in multi-disciplinary research. This study proposes a novel approach wherein research publications citing datasets archived at the GES DISC (Goddard Earth Sciences Data and Information Services Center) are collected, and each publication is associated with specific research topics through the application of Natural Language Processing (NLP), using the Term Frequency Inverse Document Frequency (TF-IDF) technique on the publication titles and abstracts. Through this analysis, we gain insights into the distribution of dataset disciplines as they are being used in various applied research areas. This knowledge is essential for the development of dataset tools and services tailored to effectively support applied research studies, as it enhances a data center's comprehension of how datasets from multiple disciplines are integrated into research endeavors.

Infometrics↗

The Development and Deployment of Machine Learning Models for Aircraft Engine Concept Assessment

In today's competitive landscape, the effective development and utilization of machine-learning (ML) applications have become imperative across various sectors. This study presents an outline of the procedure involved in creating and implementing ML models for conceptualizing and evaluating aircraft engines. These models leverage supervised deep-learning algorithms to analyze patterns within an open-source repository containing data on both production and research conventional turbofan engines. The main areas of focus encompass crucial engine parameters like thrust-specific fuel consumption (TSFC), engine weight, engine diameter, and turbomachinery stage counts. While the creation of ML models is fundamental for their utilization, ensuring their seamless deployment holds equal significance. To address this aspect, a conversational AI chatbot is constructed, utilizing natural language processing (NLP) techniques, to facilitate the deployment of these ML models. The comprehensive workflow encompasses several key stages: gathering and enhancing engine data, training and cross validating the ML models, testing and evaluating their performance, and finally, deploying, monitoring, and updating the ML models. By following this systematic approach, the aim is to streamline the development and deployment process of ML models tailored for aircraft engine assessment.

Development↗

The Development and Deployment of Machine Learning Models for Aircraft Engine Concept Assessment

In today's competitive landscape, the effective development and utilization of machine-learning (ML) applications have become imperative across various sectors. This study presents an outline of the procedure involved in creating and implementing ML models for conceptualizing and evaluating aircraft engines. These models leverage supervised deep-learning algorithms to analyze patterns within an open-source repository containing data on both production and research conventional turbofan engines. The main areas of focus encompass crucial engine parameters like thrust-specific fuel consumption (TSFC), engine weight, engine diameter, and turbomachinery stage counts. While the creation of ML models is fundamental for their utilization, ensuring their seamless deployment holds equal significance. To address this aspect, a conversational AI chatbot is constructed, utilizing natural language processing (NLP) techniques, to facilitate the deployment of these ML models. The comprehensive workflow encompasses several key stages: gathering and enhancing engine data, training and cross validating the ML models, testing and evaluating their performance, and finally, deploying, monitoring, and updating the ML models. By following this systematic approach, the aim is to streamline the development and deployment process of ML models tailored for aircraft engine assessment.

Development↗

The Development and Deployment of Machine Learning Models for Aircraft Engine Concept Assessment

In today's competitive landscape, the effective development and utilization of machine-learning (ML) applications have become crucial across diverse economic sectors. This study presents an outline of the procedure involved in creating and implementing ML models for conceptualizing and evaluating aircraft engines. These models leverage supervised deep-learning algorithms to analyze patterns within an open-source repository containing data on both production and research conventional turbofan engines. The main areas of focus encompass crucial engine parameters like thrust-specific fuel consumption (TSFC), engine weight, engine diameter, and turbomachinery stage counts. While the creation of ML models is fundamental for their utilization, ensuring their seamless deployment holds equal significance. To address this aspect, a conversational AI chatbot that specifically focuses on propulsion has been developed. Leveraging natural language processing (NLP) techniques, this chatbot simplifies the deployment of machine learning (ML) models. The comprehensive workflow encompasses several key stages: gathering and enhancing engine data, training and cross validating the ML models, testing and evaluating their performance, and finally, deploying, monitoring, and updating the ML models. By following this systematic approach, the aim is to streamline the development and deployment process of ML models tailored for aircraft engine assessment.

AI Chatbot↗

Washboard Terrain on Pluto

Washboard texture or patterning consists of fields of parallel to sub-parallel ridges typically spaced ~1-2 km crest to crest and a few 100 m in amplitude (Fig. 4a in Moore et al., 2016, Science, 351, 1284-1293). For the most part, underlying topography can be easily discerned. We will refer to discrete, well-bounded patches of these landforms as Washboard Terrain (WT). WT is observed to occur along the rim, and just beyond the rim, of Sputnik basin from the West to NNW. Where it is seen in high-resolution data, it has clearly defined limits, beyond which it would be able to be seen if it were there. WT doesn't occur at very low latitudes or very high latitudes (ranging from 22degN to 62degN). WT seems to occur most conspicuously on relatively level, gently sloping terrain. It is restricted to elevations between approximately 2 km to less than +1.5 km (i.e. not at high elevations). The most noticeable regional aspect of the area in which WT occurs is the sinuous valley network, which is suspected to have been formed, or at least substantially modified, by glaciation. WT also appears to occur mainly on an intermediate-albedo reddish material, where seen in enhanced color data. Where it occurs in level terrain, WT tends to trend ENE - there doesn't seem to be a strong local control of its orientation in response to valley drainage directions. WT can display a greater range of orientations where it occurs in higher-relief (not higher elevation) settings such as spurs. WT appears superposed on very ancient landscapes, but is itself cratered locally by clusters of small (approximately 1-3 km) craters, which may be secondaries. This implies that WT may be intermediate in age. Of several working hypotheses, we currently provisionally favor that WT may be akin to terrestrial recessional moraines (or de Geer moraines) associated with the retreat of a higher stand of N2 glaciation that once overfilled Sputnik basin. These putative moraine features may owe their spacing to superseasonal retreat on Milankovitch timescales of approximately 1 Ma. If this hypothesis has validity, then perhaps the intermediate-albedo reddish material may be akin to ground moraine deposits.

Moore, Jeffrey M.↗

A Dedicated Relay Network to Enable the Future of Mars Exploration

A highly successful international collaboration, the “Mars Relay Network” (MRN) leverages the combined NASA and ESA orbiter capabilities to transfer data to and from Mars surface missions. The MRN has admirably flight-demonstrated the benefits of a relay network and validated how international protocol standards may be used to ensure interoperability. However, principally designed for science missions, these orbiters addressed relay requirements as a secondary function, which introduced limitations to what can be achieved with the network. Next-decade missions are expected to have significantly greater communication needs than can be accommodated by the aging MRN. This paper reports the results of a broad study that evaluated the potential of a next-generation relay network, referencing the current MRN as a benchmark. A wide variety of orbital altitudes, surface latitudes, and mission scenarios were evaluated around a specific set of assumptions regarding the telecommunications payloads included. The study outlined how current day technologies could be applied to greatly enhance the data throughput to and from Mars on behalf of future science and reconnaissance missions. The instantiation of such a network would be enabling for a variety of missions and mission classes that have been heretofore unachievable, including both large and small orbiters, and landed vehicles representing new mission types (i.e. climbers, diggers, drones, etc.), and further argues that such a network would be instrumental in advancing human exploration interests at Mars.

Davis, Richard M.↗

A new technology for manufacturing scheduling derived from space system operations

A new technology for producing finite capacity schedules has been developed in response to complex requirements for operating space systems such as the Space Shuttle, the Space Station, and the Deep Space Network for telecommunications. This technology has proven its effectiveness in manufacturing environments where popular scheduling techniques associated with Materials Resources Planning (MRPII) and with factory simulation are not adequate for shop-floor work planning and control. The technology has three components. The first is a set of data structures that accommodate an extremely general description of a factory's resources, its manufacturing activities, and the constraints imposed by the environment. The second component is a language and set of software utilities that enable a rapid synthesis of functional capabilities. The third component is an algorithmic architecture called the Five Ruleset Model which accommodates the unique needs of each factory. Using the new technology, systems can model activities that generate, consume, and/or obligate resources. This allows work-in-process (WIP) to be generated and used; it permits constraints to be imposed or intermediate as well as finished goods inventories. It is also possible to match as closely as possible both the current factory state and future conditions such as promise dates. Schedule revisions can be accommodated without impacting the entire production schedule. Applications have been successful in both discrete and process manufacturing environments. The availability of a high-quality finite capacity production planning capability enhances the data management capabilities of MRP II systems. These schedules can be integrated with shop-floor data collection systems and accounting systems. Using the new technology, semi-custom systems can be developed at costs that are comparable to products that do not have equivalent functional capabilities and/or extensibility.

Hornstein, R. S.↗

Atmospheric and Surface Reflectance Measurements by the Geoscience Laser Altimeter System

The Geoscience Laser Altimeter System launched in early 2003 is the first satellite instrument IC space to globally observe the distribution of clouds and aerosol through laser remote sensing. The instrument is a basic backscatter lidar that operates at two wavelengths, 532 and 1064 nm. The mission data products for atmospheric observations include the calibrated, observed, attenuated backscatter cross section for cloud and aerosol; height detection for multiple cloud layers; planetary boundary layer height; cirrus and aerosol optical depth and the height distribution of aerosol and cloud scattering cross section profiles. The data will enhance knowledge in several areas of atmospheric science: the distribution, transport and influence of atmospheric aerosol, significantly more accurate measurements of the coverage and height of cirrus and other clouds, polar cloud climatology and radiation influence, the dynamics planetary boundary layer and others. An overview and summary of initial results are presented. Initial results from the first months of operation show the detailed height structure of clouds and aerosol on a global basis as expected. The 532 nm channel was expected to be the more sensitive and primary channel for aerosol measurements, but extensive aerosol loading in many regions are observed by the 1064 nm channel. Sensitivities are down to a few times l0(exp 6) l/(m-sr), much better than originally expected. The 532 channel adds an order of magnitude addition sensitivity. Initial comparisons to aerosol models have been done. Similarly for global cloud cover, good results are obtained just from the 1064 nm channel and from both channels, a measurement of multiple layers and cloud overlap has been made. Antarctica observations show high levels of total cloud cover including unique low-level cirrus and blowing snow. Data products have been generated for cloud, aerosol and PBL presence and heights in addition to the basic scattering cross section profiles.

Spinhirne, James D.↗

Managing and Servicing Physical Oceanographic Data at a NASA Distributed Active Archive Center

The NASA Earth Science Data Information Systems Project funds and operates 12 Distributed Active Archive Center(s) (DAAC) throughout the United States. Of these 12 centers, the Physical Oceanography DAAC (PO.DAAC) is committed to providing long term archival, distribution and stewardship for NASA physical oceanographic data, primarily derived from space-born satellite systems, but also including a growing set of recent and future in situ observations from the SPURS-1 and SPURS-2 campaigns. Notable NASA missions supported include: Seasat, TOPEX/Poseidon, NSCAT, QuikSCAT, ISS-RapidScat, Jason-1, Jason-2/OSTM, GRACE, Aquarius, GHRSST, and MODIS. The following interagency and international missions are also supported by PO.DAAC: AVHRR, Coriolis, DMSP, MetOp-A, MetOp-B, Oceansat-2. The PO.DAAC currently holds 525 datasets in public distribution, spanning the following observational parameters: sea surface temperature, sea surface salinity, ocean color, ocean surface currents, ocean surface wind speed, ocean surface wind direction, sea surface height, significant wave height, ocean water mass/thickness, and sea ice age. A hundred of these datasets are available in near-real-time. Datasets are distributed through a variety of open-source access protocols including FTP, OPeNDAP, and THREDDS. FTP will soon be phased out in favor of a recently introduced HTTPS PO.DAAC Drive interface that supports WebDAV and interoperable machine-to-machine communication. OPeNDAP supports remote data/metadata query, subset, and download. THREDDS provides the features of OPeNDAP with the additional feature of temporal aggregation. PO.DAAC also offers proprietary tools and services to further enhance the data discovery, visualization and analysis experience, including but not limited to: State of the Ocean, Web Services (data/metadata discovery and extraction), HiTIDE Level-2 subsetter, Live Access Server (LAS), Webification (w10nsci), and Rich Site Summary (RSS) Datacasting. To assist with provenance of datasets, PO.DAAC has implemented DOIs for the data it distributes so that they can be properly cited. There is a user forum and helpdesk that contains data recipes and via which users can get guidance. In summary, this presentation aims to provide a general overview of PO.DAAC’s web portal and data holdings along with a set of illustrative examples leading prospective data users into the practical utility of its tools and services.

Moroni, David F.↗