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Developing Earth science data products that meet the needs of diverse users is a challenging task for both data producers and service providers, as user requirements can vary significantly and evolve over time. In this comment, we discuss several strategies to improve Earth science data products that everyone can use.
As Lunar missions increase in complexity, inspired by NASA’s Artemis Program, they will require reliable and sufficient Position, Navigation, and Timing (PNT) capability to support the upcoming Lunar users. The navigation service should also be compatible with the smaller platforms, like CubeSats, being sent by the public and private sectors. A non-dedicated, ad-hoc Lunar navigation constellation can provide PNT services on-demand using the non-dedicated swarm assets. Swarm members cooperatively and autonomously localize themselves with minimal interaction from Earth, freeing up valuable bandwidth and ground segment resources. The autonomous localization of Lunar constellations utilizes neighbor two-way intersatellite link (ISL) measurements in a distributed extended Kalman filter (DEKF) system to minimize operating costs. Because the decentralized Lunar PNT system relies on relay communication amongst the agents, network failures or loss of assets among ad-hoc Lunar constellations may impact localization performance. This study presents an evaluation of localization performance under increasing levels of network degradation. A simulation of an ad-hoc Lunar PNT swarm is augmented to include system faults and the impacts of intermittent and permanent failures on localization performance are evaluated. We investigate three potential causes of network degradation: single spacecraft loss, multiple spacecraft loss, and antenna failure. The numerical assessments from the simulation show that the LPNT system under study, based on an autonomous decentralized concept of operation, is highly robust and resilient to communication failures. Minor faults, such as single spacecraft loss, solar interference, technical malfunctions, message delays, and antenna outages, have minimal impact on state estimation, with only a 4.47% and 3.75% degradation in median position error for assets and a representative ground user, respectively, compared to an ideal communication scenario. However, major faults, such as hardware failures or meteor strikes leading to the loss of multiple spacecrafts, are more concerning. The permanent loss of three spacecraft results in a more severe performance degradation, with median position error increasing by 23.3% for assets and 11.7% for a representative ground user, despite the Lunar PNT system remaining functional.
The circular economy (CE) has been proposed to be an operational framework for sustainable development that decouples economic growth from resource consumption. The CE ambition is to maximize the retention of value in products, materials, and resources in the economy over time with the help of CE strategies such as selling a service rather than a product, reusing and repairing products or their components, and recycling. The social, economic, and environmental performances of CE strategies need to be measured against their linear counterparts to avoid strategies that increase circularity but have other unintended externalities. However, there is currently no tool specifically designed to compare circular to linear systems and, thus, various methods from different fields have been applied. This session aims at reviewing, contrasting, and critiquing different methods that have been applied to assess the CE until now, along with an up to date state of the science in this field. Methods from the industrial ecology field have most often been applied to study the CE. However, the transition to CE involves both technological improvements as well as social changes. New business models such as collaborative consumption models (e.g., Uber or Airbnb) are examples of the new patterns of production and consumption of the CE, which may be difficult to analyze from a purely industrial ecology perspective. Methods from complexity science and humanities could therefore complement the industrial ecology perspective to extend the scope of the analysis. Such an approach could also answer a longstanding criticism of the CE which, in contrast with sustainability, solely focuses on the environment and the economy. Moreover, the hybridization of two or more existing methods can yield additional capabilities, which may enable the exploration of additional CE-related research questions. The 90 minutes session will have several presentations and conclude with a moderated, interactive panel discussion on how methods from different fields could be combined to harness their relative strengths.
The current Electronic Data Management System (EDMS) makes it difficult to efficiently access information in critical time frames. This project explored ways to allow Environmental Support and Services staff the ability to efficiently access documents with necessary historic information while leveraging existing data classification methods and the capabilities of EDMS.
This presentation will discuss challenges and opportunities on interregional coordination in the areas of interchange transaction, congestion management, reserve sharing and deliverability across multi-stage operational processes. It will then provide an overview of the interregional transmission operational coordination (IRTOC) project that currently focuses on congestion management, including Inter-regional transmission coordination in real time operations and operational planning, HVDC optimization (intra- and interregional), ancillary service deliverability (intra- and interregional). In addition, it will discuss the Sienna-Decomposition tool development to systematically study interregional coordination methods.
The connection of more loads and distributed energy resources (DERs) to the distribution power system brings both challenges and opportunities to system operators. There are opportunities to aggregate flexible loads and DERs to provide transmission grid services, but the coordinated actions of DERs being managed by independent, third-party DER aggregators to support transmission system operations can present challenges. We developed a federated DER management architecture and control framework that aims to manage heterogeneous DERs to deliver reliable transmission grid services while respecting distribution system constraints. The controls include stochastic day-ahead optimization, model predictive control, and a simple real-time management scheme. We present simulation results obtained from a realistic laboratory test bed of federated controls managing DERs within a substation service area to make the substation net power follow the optimal net power determined by the day-ahead optimization based on cost and limiting reverse power flow.
This project aims to establish a framework capable of efficiently predicting the properties of structural materials for service in harsh environments over a wide range of temperatures and over long periods of time. The approach is to develop and integrate high throughput first-principles calculations in combination with machine learning (ML) methods, perform high throughput CALPHAD (calculations of phase diagrams) modeling, and carry out finite element method (FEM) simulations. Relevant to high temperature service in fossil power system, nickel-based superalloys such as Inconel 740 and Haynes 282 as well as the associated (Ni-Cr-Co)-Al-C-Fe-Mn-Mo-Nb-Si-Ti system, were investigated. The present framework was built on the concept of phase-based property data, in which properties of individual phases are modeled as a function of internal and external independent variables. This project established an open-source infrastructure with the following capabilities: (1) High throughput implementation of first-principles calculations at finite temperatures and variable compositions using both accurate phonon calculations and the efficient Debye model for thermodynamic properties, elastic constants, diffusion coefficients, vacancy formation, stacking and twin faults, and dislocation mobility; i.e., using the developed code DFTTK; (2) Machine learning capabilities to predict the above properties so that the number of first-principles calculations can be significantly reduced; e.g., using the developed code SIPFENN; (3) High throughput CALPHAD modeling of the above properties as a function of temperature and composition using our unique capability based on ESPEI and PyCalphad; (4) New capabilities to predict the stress-strain behavior of individual phases; and (5) New models for tensile strength prediction in common FEM software with the crystal plasticity finite element simulations (CPFEM).
Flooding and drought are two key forecasting challenges for the Kenya Meteorological Service (KMS). Atmospheric processes leading to excessive precipitation and/or prolonged drought can be quite sensitive to the state of the land surface, which interacts with the planetary boundary layer (PBL) of the atmosphere providing a source of heat and moisture. The development and evolution of precipitation systems are affected by heat and moisture fluxes from the land surface, particularly within weakly-sheared environments such as in the tropics and sub-tropics. These heat and moisture fluxes during the day can be strongly influenced by land cover, vegetation, and soil moisture content. Therefore, it is important to represent the land surface state as accurately as possible in land surface and numerical weather prediction (NWP) models. Enhanced regional modeling capabilities have the potential to improve forecast guidance in support of daily operations and high-impact weather over eastern Africa. KMS currently runs a configuration of the Weather Research and Forecasting (WRF) NWP model in real time to support its daily forecasting operations, making use of the NOAA/National Weather Service (NWS) Science and Training Resource Center's Environmental Modeling System (EMS) to manage and produce the KMS-WRF runs on a regional grid over eastern Africa. Two organizations at the NASA Marshall Space Flight Center in Huntsville, AL, SERVIR and the Shortterm Prediction Research and Transition (SPoRT) Center, have established a working partnership with KMS for enhancing its regional modeling capabilities through new datasets and tools. To accomplish this goal, SPoRT and SERVIR is providing enhanced, experimental land surface initialization datasets and model verification capabilities to KMS as part of this collaboration. To produce a land-surface initialization more consistent with the resolution of the KMS-WRF runs, the NASA Land Information System (LIS) is run at a comparable resolution to provide real-time, daily soil initialization data in place of data interpolated from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) model soil moisture and temperature fields. Additionally, realtime green vegetation fraction (GVF) data from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (Suomi- NPP) satellite will be incorporated into the KMS-WRF runs, once it becomes publicly available from the National Environmental Satellite Data and Information Service (NESDIS). Finally, model verification capabilities will be transitioned to KMS using the Model Evaluation Tools (MET; Brown et al. 2009) package in conjunction with a dynamic scripting package developed by SPoRT (Zavodsky et al. 2014), to help quantify possible improvements in simulated temperature, moisture and precipitation resulting from the experimental land surface initialization. Furthermore, the transition of these MET tools will enable KMS to monitor model forecast accuracy in near real time. This paper presents preliminary efforts to improve land surface model initialization over eastern Africa in support of operations at KMS. The remainder of this extended abstract is organized as follows: The collaborating organizations involved in the project are described in Section 2; background information on LIS and the configuration for eastern Africa is presented in Section 3; the WRF configuration used in this modeling experiment is described in Section 4; sample experimental WRF output with and without LIS initialization data are given in Section 5; a summary is given in Section 6 followed by acknowledgements and references.
Implementation of metal and resin matrix composites into supersonic vehicle usage is contingent upon accelerating the demonstration of service capacity and design technology. Because of the added material complexity and lack of extensive service data, laboratory replication of the flight service will provide the most rapid method of documenting the airworthiness of advanced composite systems. A program in progress to determine the time temperature stress capabilities of several high temperature composite materials includes thermal aging, environmental aging, fatigue, creep, fracture, and tensile tests as well as real time flight simulation exposure. The program has two parts. The first includes all the material property determinations and aging and simulation exposures up through 10,000 hours. The second continues these tests up to 50,000 cumulative hours. Results are presented of the 10,000 hour phase, which has now been completed.
Japanese prediction services for HF radio communications are outlined in relation to prediction method, performance and evaluation. The current prediction is based on the CCIR interim method with some modifications matching to a computer system. The principal service is the monthly median prediction issued regularly three months in advance for various communication circuits. A daily prediction for short distance circuits is being prepared by using real time ionospheric sounding data. An evaluation theory and practice is expected to be introduced in the future prediction service.
The reference time scale for all scientific and technologic applications on the Earth, the Universal Coordinated Time (UTC), must be as stable, reliable, and accurate as possible. With this in view the BIPM and before it the BIH, have always calculated and then disseminated UTC with a delay of about 80 days. There are three fundamental reasons for doing this: (1) It takes some weeks for data, gathered from some 200 clocks spread world-wide, to be collected and for errors to be eliminated; (2) changes in clock rates can only be measured with high precision well after the fact; and (3) the measurement noise originating in time links, in particular using Loran-C, is smoothed out only when averaging over an extended period. Until mid-1992, the ultimate stability of UTC was reached at averaging times of about 100 days and corresponded to an Allan deviation sigma(sub y)(tau) of about 1,5x10(exp -14) then compared to the best primary clock in the world, the PTB CS2. For several years now, a predicted UTC has been computed by the USNO through an extrapolation of the values as published in deferred time by the BIPM. This is made available through the USNO Series 4, through the USNO Automated Data Service, and through GPS signals. Due to the instability of UTC, the poor predictability of the available clocks, and the intentional SA degradation of GPS signals, the real-time access to this extrapolated UTC has represented the true deferred-time UTC only to within several hundreds of nanoseconds.
Low Earth orbit (LEO) hyper-spectral infrared (IR) sounders have significant yet untapped potential for characterizing thermodynamic environments of convective initiation and ongoing convection. While LEO soundings are of enormous value to weather forecasters, they cannot provide the temporal resolution needed to resolve the rapidly evolving thermodynamics of the convective environment. A novel methodology was developed to extend snapshots of LEO soundings forward in time up to six hours into the future and has been made available within the NOAA National Weather Service Advanced Weather Interactive Processing System (AWIPS) for testing in a quasi-operational setting. This methodology is based on parcel forward-trajectory calculations from the satellite observing time to recreate future soundings of temperature and moisture at regularly gridded intervals in space and time. The soundings are based on NOAA-Unique Combined Atmospheric Processing System (NUCAPS) retrievals from the Suomi NPP and NOAA-20 satellite platforms to allow for rapid near-real time product processing. Science code was transitioned to operational production in 2019 and the product, NUCAPS-Forecast, was tested at the NOAA Hazardous Weather Testbed Spring Experiment in 2019 and 2021. Forecaster feedback has led to improving the product and processing system to address product limitations and improve its applicability for pre-convective forecasting. This presentation highlights the design of the NUCAPS-Forecast system. Solutions were tested and implemented to remove excess moisture and conjoin forward-trajected parcels into vertical profiles for calculating grids of stability indices. Additionally, use cases that explore the tendencies of derived convective available potential energy (CAPE) and convective inhibition (CIN) were investigated. When evaluated against gridded, hourly accumulated rainfall obtained from the Multi-Radar Multi-Sensor (MRMS) observational data set areas with elevated CAPE (reduced CIN) are shown to be associated with areas of precipitation and increase confidence the LEO soundings advected forward in time physically represent atmospheric processes. These results suggest that adiabatic parcel advection of LEO satellite sounding snapshots forward in time exhibits skill in discriminating locations and times that are more likely to lead to convective initiation. Leveraging trajectory modeling to increase the spatial and temporal resolution of LEO IR sounding observations today demonstrates the value of these observations from the future constellation of JPSS satellites and GeoXO mission.
A significant portion of Earth Science investigations is phenomenon- (or event-) based, such as the studies of Rossby waves, volcano eruptions, tsunamis, mesoscale convective systems, and tropical cyclones. However, except for a few high-impact phenomena, e.g. tropical cyclones, comprehensive records are absent for the occurrences or events of these phenomena. Phenomenon-based studies therefore often focus on a few prominent cases while the lesser ones are overlooked. Without an automated means to gather the events, comprehensive investigation of a phenomenon is at least time-consuming if not impossible. We have constructed a prototype Automated Event Service (AES) system that is used to methodically mine custom-defined events in the reanalysis data sets of atmospheric general circulation models. Our AES will enable researchers to specify their custom, numeric event criteria using a user-friendly web interface to search the reanalysis data sets. Moreover, we have included a social component to enable dynamic formation of collaboration groups for researchers to cooperate on event definitions of common interest and for the analysis of these events. An Earth Science event (ES event) is defined here as an episode of an Earth Science phenomenon (ES phenomenon). A cumulus cloud, a thunderstorm shower, a rogue wave, a tornado, an earthquake, a tsunami, a hurricane, or an El Nino, is each an episode of a named ES phenomenon, and, from the small and insignificant to the large and potent, all are examples of ES events. An ES event has a duration (often finite) and an associated geo-location as a function of time; it's therefore an entity embedded in four-dimensional (4D) spatiotemporal space. Earth Science phenomena with the potential to cause massive economic disruption or loss of life often rivet the attention of researchers. But, broader scientific curiosity also drives the study of phenomena that pose no immediate danger, such as land/sea breezes. Due to Earth System's intricate dynamics, we are continuously discovering novel ES phenomena. We generally gain understanding of a given phenomenon by observing and studying individual events. This process usually begins by identifying the occurrences of these events. Once representative events are identified or found, we must locate associated observed or simulated data prior to commencing analysis and concerted studies of the phenomenon. Knowledge concerning the phenomenon can accumulate only after analysis has started. However, as mentioned previously, comprehensive records only exist for a very limited set of high-impact phenomena; aside from these, finding events and locating associated data currently may take a prohibitive amount of time and effort on the part of an individual investigator. The reason for the lack of comprehensive records for most of the ES phenomena is mainly due to the perception that they do not pose immediate and/or severe threat to life and property. Thus they are not consistently tracked, monitored, and catalogued. Many phenomena even lack precise and/or commonly accepted criteria for definitions. Moreover, various Earth Science observations and data have accumulated to a previously unfathomable volume; NASA Earth Observing System Data Information System (EOSDIS) alone archives several petabytes (PB) of satellite remote sensing data, which are steadily increasing. All of these factors contribute to the difficulty of methodically identifying events corresponding to a given phenomenon and significantly impede systematic investigations. We have not only envisioned AES as an environment for identifying customdefined events but also aspired for it to be an interactive environment with quick turnaround time for revisions of query criteria and results, as well as a collaborative environment where geographically distributed experts may work together on the same phenomena. A Big Data technology is thus required for the realization of such a system. In the following, we first introduce the technology selected for AES in the next section. We then demonstrate the utility of AES using a use case, Blizzard, before we conclude.
NASA engineers on the Hubble Space Telescope program are actively preparing a shuttle mission to service the orbiting observatory, perhaps as early as 2007, pending a safe return to flight of the shuttle fleet. Administrator Michael D. Griffin must give final clearance to mount the mission, scuttled by former Administrator Sean O'Keefe on what he said were safety grounds in the wake of the Columbia accident. But Griffin, who has overturned much of O'Keefe's policy in his three months on the job, has already told the Hubble program to proceed as though the mission will take place. In that, he has at least the acquiescence of Harold Gehman, the retired admiral who headed the Columbia Accident Investigation Board (CAIB). The CAIB never intended its recommendations to preclude a shuttle-borne Hubble servicing mission, Gehman says, and its members still believe the risk would be no greater than missions to the International Space Station (ISS).
To maintain its competitive position in the 1990s, satellite communications must evolve to provide new services and to reduce the costs of supplying existing services. NASA's Advanced Communications Technology Satellite (ACTS) program is directed toward developing the technology base that will support this evolution. The ACTS communications payload is optimized for digital communications using a time-division multiple access format. Scanning spot-beam antennas provide high-performance on-demand service to the earth communication stations. On-board processing and switching allow full connectivity in a single-hop network architecture. ACTS employs Ka-band (30/20 GHz) links for communications traffic and includes techniques for mitigating rain fades. Scheduled to be launched by a Space Shuttle in 1992, ACTS will provide in-orbit technology verification and support experimental communications networks for up to four years.
My name is James Moon and I am a senior at Tennessee State University where my major is Aeronautical and Industrial Technology with a concentration in industrial electronics. I am currently serving my internship in the Engineering and Technical Services Directorate at the Glenn Research Center (GRC). The Engineering and Technical Service Directorate provides the services and infrastructure for the Glenn Research Center to take research concepts to reality. They provide a full range of integrated services including engineering, advanced prototyping and testing, facility management, and information technology for NASA, industry, and academia. Engineering and Technical Services contains the core knowledge in Information Technology (IT). This includes data systems and analysis, inter and intranet based systems design and data security. Including the design and development of embedded real-time s o h a r e applications for flight and supporting ground systems, Engineering and Technical Services provide a wide range of IT services and products specific to the Glenn Research Center research and engineering community. In the 7000 Directorate I work directly in the 7611 organization. This organization is known as the Aviation Environments Technical Branch. My mentor is Vincent Satterwhite who is also the Branch Chief of the Aviation Environments Technical Branch. In this branch, I serve as the Assistant program manager of the Engineering Technology Program. The Engineering Technology Program (ETP) is one of three components of the High School L.E.R.C.I.P. This is an Agency-sponsored, eight-week research-based apprenticeship program designed to attract traditionally underrepresented high school students that demonstrate an aptitude for and interest in mathematics, science, engineering, and technology.
The currently available services at the Goddard Earth Sciences Data Information Services Center (GES DISC) only allow users to select variables from a single data set at a time. Because entire variables from a data set are often displayed, user selection of variables of interest can be overwhelming. At the American Geophysical Union (AGU) 2016 Fall Meeting, GES DISC unveiled a new service called Datalist: a collection of predefined or user-defined data variables from one or more archived data sets. Our science support team has been curating Datalists and providing added value to the user community.Originally known as Afternoon Constellation, A-Train includes six currently on polar-orbiting Earth observation satellites: OCO-2, GCOM-W1, Aqua, CALIPSO, CloudSat, and Aura, which travel a few minutes apart from each other. This constellation arrangement has enabled coordinated science observations further forming comprehensive pictures of Earth weather and climate that are readily for use in crucial studies such as climate change.GES DISC Datalists are based on the software architecture of the new GES DISC website (also unveiled at the AGU 2016 Fall Meeting). The GES DISC science support team has created a Datalist to support the A-Train Data Depot (ATDD). Using pre-defined Datalist should hopefully save users significant effort in their data searches.
The part of the geostationary (GEO) orbital arc used for United States domestic fixed, communications service is rapidly becoming filled with satellites. One of the factors currently limiting its utilization is that communications satellites must be designed to have sufficient capacity to handle peak traffic leads, and thus are under utilized most of the time. A solution is to use satellites in suitable non-geostationary orbits to unload the traffic peaks. Three different designs for a non-geostationary orbit communications satellite system are presented for the 1995 time frame. The economic performance is analyzed and compared with geostationary satellites for two classes of service, trunking and customer premise service. The result is that the larger payload of the non-geostationary satellite offsets the burdens of increased complexity and worse radiation environment to give improved economic performance. Depending on ground terminal configuration, the improved economic performance of the space segment may be offset by increased ground terminal expenses.