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NASA NTRSDate not supplied

Importance of Radiative Transfer Models in Atmospheric Remote Sensing

Radiative transfer models (RTMs) play a significant role in the development of satellite instruments for remote sensing applications. These models simulate electromagnetic radiation's propagation through the atmosphere, providing valuable insights into atmosphere-radiation interactions. RTMs facilitate the optimization of satellite instrument designs, ensuring their ability to measure targeted atmospheric and surface properties accurately. Moreover, they aid in simulating instrument’s measurements under various atmospheric conditions, enabling calibration and validation processes to enhance data quality and reliability. RTMs are extensively used in the Observing System Simulation Experiments (OSSE), to generate synthetic observations. By incorporating RTMs into OSSE, we can assess the potential impact of future satellite missions, sensor configurations, and data assimilation techniques. This approach allows for the optimization of satellite instruments and constellations and the evaluation of their influence on weather forecasting, climate monitoring, and other Earth science applications. Another crucial application area of RT models is data assimilation, where they play a fundamental role in combining satellite observations with numerical models to improve atmospheric and environmental predictions. RTMs provide the link between observed radiances and atmospheric parameters, enhancing the accuracy of numerical models and generating more reliable forecasts for weather events, air quality assessments, and climate projections. Moreover, adapting RT models to capture the intricate radiation interactions within the Planetary Boundary Layer will significantly contribute to improving weather forecasting and climate change projections. Current community radiative transfer (RT) models are primarily developed and optimized for operational data assimilation of satellite observations. These models excel at assimilating satellite data into numerical weather prediction models to improve forecast accuracy. However, their focus on data assimilation limits their suitability for other important applications, such as satellite instrument development, OSSE, and Planetary Boundary Layer (PBL) studies. Moreover, for PBL studies, RT models need to be adapted to capture the intricate radiation interactions within this crucial atmospheric layer. Developing RT models that can represent the PBL's unique characteristics, such as surface interactions, will contribute significantly to understanding and predicting weather phenomena, air quality, and climate dynamics. This abstract provides a comprehensive overview of the current status of RT models and highlights their limitations concerning satellite instrument development, OSSE, and PBL studies. Addressing these shortcomings requires concerted efforts to enhance RT models' capabilities and expand their applications beyond data assimilation. By investing in research and development to improve these

Isaac Moradi↗
NASA NTRS1999

Performance Analysis of TCP Enhancements in Satellite Data Networks

This research examines two proposed enhancements to the well-known Transport Control Protocol (TCP) in the presence of noisy communication links. The Multiple Pipes protocol is an application-level adaptation of the standard TCP protocol, where several TCP links cooperate to transfer data. The Space Communication Protocol Standard - Transport Protocol (SCPS-TP) modifies TCP to optimize performance in a satellite environment. While SCPS-TP has inherent advantages that allow it to deliver data more rapidly than Multiple Pipes, the protocol, when optimized for operation in a high-error environment, is not compatible with legacy TCP systems, and requires changes to the TCP specification. This investigation determines the level of improvement offered by SCPS-TP's Corruption Mode, which will help determine if migration to the protocol is appropriate in different environments. As the percentage of corrupted packets approaches 5 %, Multiple Pipes can take over five times longer than SCPS-TP to deliver data. At high error rates, SCPS-TP's advantage is primarily caused by Multiple Pipes' use of congestion control algorithms. The lack of congestion control, however, limits the systems in which SCPS-TP can be effectively used.

Broyles, Ren H.↗
NASA NTRS2017

Weathering the Storm: Unmanned Aircraft Systems in the Maritime, Atmospheric and Polar Environments

Remotely piloted aircraft (RPA) have the potential to revolutionize local to regional data collection for geophysicists as platform and payload size decrease while aircraft capabilities increase. In particular, data from RPAs combine high-resolution imagery available from low flight elevations with comprehensive areal coverage, unattainable from ground investigations and difficult to acquire from manned aircraft due to budgetary and logistical costs. Low flight elevations are particularly important for detecting signals that decay exponentially with distance, such as electromagnetic fields. Onboard data processing coupled with high-bandwidth telemetry open up opportunities for real-time and near real-time data processing, producing more efficient flight plans through the use of payload-directed flight, machine learning and autonomous systems. Such applications not only strive to enhance data collection, but also enable novel sensing modalities and temporal resolution. NASAs Airborne Science Program has been refining the capabilities and applications of RPA in support of satellite calibration and data product validation for several decades. In this paper, we describe current platforms, payloads, and onboard data systems available to the research community. Case studies include Fluid Lensing for littoral zone 3D mapping, structure from motion for terrestrial 3D multispectral imaging, and airborne magnetometry on medium and small RPAs.

data collection↗
NASA NTRS2016

Using Remotely Piloted Aircraft and Onboard Processing to Optimize and Expand Data Collection

Remotely piloted aircraft (RPA) have the potential to revolutionize local to regional data collection for geophysicists as platform and payload size decrease while aircraft capabilities increase. In particular, data from RPAs combine high-resolution imagery available from low flight elevations with comprehensive areal coverage, unattainable from ground investigations and difficult to acquire from manned aircraft due to budgetary and logistical costs. Low flight elevations are particularly important for detecting signals that decay exponentially with distance, such as electromagnetic fields. Onboard data processing coupled with high-bandwidth telemetry open up opportunities for real-time and near real-time data processing, producing more efficient flight plans through the use of payload-directed flight, machine learning and autonomous systems. Such applications not only strive to enhance data collection, but also enable novel sensing modalities and temporal resolution. NASA’s Airborne Science Program has been refining the capabilities and applications of RPA in support of satellite calibration and data product validation for several decades. In this paper, we describe current platforms, payloads, and onboard data systems available to the research community. Case studies include Fluid Lensing for littoral zone 3D mapping, structure from motion for terrestrial 3D multispectral imaging, and airborne magnetometry on medium and small RPAs.

Fladeland, Matthew M.↗
NASA NTRSDate not supplied

NASA POWER: Providing Analysis-Ready, Cloud-Optimized Data for AI /ML Training and Applications in Earth Science

As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.

Neha Khadka↗
NASA NTRS1983

Potential impact of remote sensing data on sea-state analysis and prediction

The severe North Atlantic storm which damaged the ocean liner Queen Elizabeth 2 (QE2) was studied to assess the impact of remotely sensed marine surface wind data obtained by SEASAT-A, on sea state specifications and forecasts. Alternate representations of the surface wind field in the QE2 storm were produced from the SEASAT enhanced data base, and from operational analyses based upon conventional data. The wind fields were used to drive a high resolution spectral ocean surface wave prediction model. Results show that sea state analyses would have been vastly improved during the period of storm formation and explosive development had remote sensing wind data been available in real time. A modest improvement in operational 12 to 24 hour wave forecasts would have followed automatically from the improved initial state specification made possible by the remote sensing data in both numerical and sea state prediction models. Significantly improved 24 to 48 hour wave forecasts require in addition to remote sensing data, refinement in the numerical and physical aspects of weather prediction models.

Cardone, V. J.↗
NASA NTRS1986

Design and performance of the halogen occultation experiment (HALOE) remote sensor

HALOE is an optical remote sensor that measures extinction of solar radiation caused by the earth's atmosphere in eight channels, ranging in wavelength from 2.5 to 10.1 microns. These measurements, which occur twice each satellite orbit during solar occultation, are inverted to yield vertical distributions of middle atmosphere ozone (O3), water vapor, nitrogen dioxide, nitric oxide, hydrogen fluoride, hydrogen chloride, and methane. A channel located in the 2.7 region is used to infer the tangent point pressure by measuring carbon dioxide absorption. The HALOE instrument consists of a two-axis gimbal system, telescope, spectral discrimination optics and a 12-bit data system. The gimbal system tracks the solar radiometric centroid in the azimuthal plane and tracks the solar limb in the elevation plane, placing the instrument's instantaneous field-of-view 4 arcmin down from the solar top edge. The instrument gathers data for tangent altitudes ranging from 150 km to the earth's horizon. Prior to an orbital sunset and after an orbital sunrise, HALOE automatically performs calibration sequences to enhance data interpretation. The instrument is presently being tested at the NASA Langley Research Center in preparation for launch on the Upper Atmosphere Research Satellite near the end of this decade. This paper describes the instrumenmt design, operation, and functional performance.

Baker, R. L.↗
NASA NTRS2008

Overview of the Smart Network Element Architecture and Recent Innovations

In industrial environments, system operators rely on the availability and accuracy of sensors to monitor processes and detect failures of components and/or processes. The sensors must be networked in such a way that their data is reported to a central human interface, where operators are tasked with making real-time decisions based on the state of the sensors and the components that are being monitored. Incorporating health management functions at this central location aids the operator by automating the decision-making process to suggest, and sometimes perform, the action required by current operating conditions. Integrated Systems Health Management (ISHM) aims to incorporate data from many sources, including real-time and historical data and user input, and extract information and knowledge from that data to diagnose failures and predict future failures of the system. By distributing health management processing to lower levels of the architecture, there is less bandwidth required for ISHM, enhanced data fusion, make systems and processes more robust, and improved resolution for the detection and isolation of failures in a system, subsystem, component, or process. The Smart Network Element (SNE) has been developed at NASA Kennedy Space Center to perform intelligent functions at sensors and actuators' level in support of ISHM.

Perotti, Jose M.↗
NASA NTRS2016

HIAD on ULA (HULA) Orbital Reentry Flight Experiment Concept

This paper describes a proposed orbital velocity reentry flight test of a Hypersonic Inflatable Aerodynamic Decelerator (HIAD). The flight test builds upon ground development activities that continue to advance the materials, design, and manufacturing techniques for the inflatable structure and flexible thermal protection system (F-TPS) that comprise the inflatable heat shield. While certain aspects of material and system performance can be assessed using a variety of ground testing capabilities, only orbital velocity energy on a trajectory through the gradient density of the atmosphere can impart the combined aerodynamic and aeroheating design environments in real time. To achieve this at limited cost, the HIAD would be delivered to a spin-stabilized entry trajectory as a secondary payload on the Centaur stage of a United Launch Alliance (ULA) Atlas V launch vehicle. Initial trajectory studies indicate that the combination of launch vehicle capability and achievable reentry vehicle ballistic numbers make this a strategic opportunity for technology development. This 4 to 6 meter diameter scale aeroshell flight, referred to as HIAD on ULA (HULA), would also contribute to ULA asset recovery development. ULA has proposed that a HIAD be utilized as part of the Sensible, Modular, Autonomous Return Technology (SMART) initiative to enable recovery of the Vulcan launch vehicle booster main engines [1], including a Mid-Air Recovery (MAR) to gently return these assets for reuse. Whereas HULA will attain valuable aerothermal and structural response data toward advancing HIAD technology, it may also provide a largest-to-date scaled flight test of the MAR operation, which in turn would allow the examination of a nearly pristine post-entry aeroshell. By utilizing infrared camera imaging, HULA will also attain aft-side thermal response data, enhancing understanding of the aft side aerothermal environment, an area of high uncertainty. The aeroshell inflation will utilize a heritage design compressed gas system to minimize development costs. The data will be captured to both an onboard recorder and a recorder that is jettisoned and recovered separately from the reentry vehicle to mitigate risk. This paper provides an overview, including the architecture and flight concept of operations, for the proposed HULA flight experiment.

Dinonno, J. M.↗
NASA NTRS2013

High Efficiency Traveling-Wave Tube Power Amplifier for Ka-Band Software Defined Radio on International Space Station-A Platform for Communications Technology Development

The design, fabrication and RF performance of the output traveling-wave tube amplifier (TWTA) for a space based Ka-band software defined radio (SDR) is presented. The TWTA, the SDR and the supporting avionics are integrated to forms a testbed, which is currently located on an exterior truss of the International Space Station (ISS). The SDR in the testbed communicates at Ka-band frequencies through a high-gain antenna directed to NASA s Tracking and Data Relay Satellite System (TDRSS), which communicates to the ground station located at White Sands Complex. The application of the testbed is for demonstrating new waveforms and software designed to enhance data delivery from scientific spacecraft and, the waveforms and software can be upgraded and reconfigured from the ground. The construction and the salient features of the Ka-band SDR are discussed. The testbed is currently undergoing on-orbit checkout and commissioning and is expected to operate for 3 to 5 years in space.

Simons, Rainee N.↗
NASA NTRS2015

Comprehensive Non-Destructive Conservation Documentation of Lunar Samples Using High-Resolution Image-Based 3D Reconstructions and X-Ray CT Data

Established contemporary conservation methods within the fields of Natural and Cultural Heritage encourage an interdisciplinary approach to preservation of heritage material (both tangible and intangible) that holds "Outstanding Universal Value" for our global community. NASA's lunar samples were acquired from the moon for the primary purpose of intensive scientific investigation. These samples, however, also invoke cultural significance, as evidenced by the millions of people per year that visit lunar displays in museums and heritage centers around the world. Being both scientifically and culturally significant, the lunar samples require a unique conservation approach. Government mandate dictates that NASA's Astromaterials Acquisition and Curation Office develop and maintain protocols for "documentation, preservation, preparation and distribution of samples for research, education and public outreach" for both current and future collections of astromaterials. Documentation, considered the first stage within the conservation methodology, has evolved many new techniques since curation protocols for the lunar samples were first implemented, and the development of new documentation strategies for current and future astromaterials is beneficial to keeping curation protocols up to date. We have developed and tested a comprehensive non-destructive documentation technique using high-resolution image-based 3D reconstruction and X-ray CT (XCT) data in order to create interactive 3D models of lunar samples that would ultimately be served to both researchers and the public. These data enhance preliminary scientific investigations including targeted sample requests, and also provide a new visual platform for the public to experience and interact with the lunar samples. We intend to serve these data as they are acquired on NASA's Astromaterials Acquisistion and Curation website at http://curator.jsc.nasa.gov/. Providing 3D interior and exterior documentation of astromaterial samples addresses the increasing demands for accessability to data and contemporary techniques for documentation, which can be realized for both current collections as well as future sample return missions.

Blumenfeld, E. H.↗
NASA NTRS1993

Aviation Weather Program (AWP)

The Aviation Weather Program (AWP) combines additional weather observations, improved forecast technology, and more efficient distribution of information to pilots, controllers, and automated systems to improve the weather information provided to the air traffic control system, pilots, and other users of aviation weather information. Specific objectives include the needs to: improve airport and en-route capacity by accurate, high resolution, timely forecasts of changing weather conditions affecting airport and en-route operations; improve analyses and forecasts of upper-level winds for efficient flight planning and traffic management; and increase flight safety through improved aviation weather hazard forecasting (e.g. icing, turbulence, severe storms, microbursts, or strong winds). The AWP would benefit from participation in a cooperative multiscale experiment by obtaining data for: evaluation of aviation weather forecast products, analysis of four dimensional data assimilation schemes, and experimental techniques for retrieving aerosol and other visibility parameters. A multiscale experiment would also be helpful to AWP by making it possible to evaluate the added benefit of enhanced data sets collected during the experiment on those forecast and analysis products. The goals of the Coperative Multiscale Experiment (CME) are an essential step in attaining the long-term AWP objective of providing two-to-four hour location-specific forecasts of significant weather. Although the possibility of a funding role for the AWP in the CME is presently unclear, modest involvement of Federal Aviation Administration (FAA)/AWP personnel could be expected.

Foote, Brant↗
NASA NTRS2004

Comparison of Satellite Observations of Aerosol Optical Depth to Surface Monitor Fine Particle Concentration

Under NASA's Earth Science Applications Program, the Infusing satellite Data into Environmental Applications (IDEA) project examined the relationship between satellite observations and surface monitors of air pollutants to facilitate a more capable and integrated observing network. This report provides a comparison of satellite aerosol optical depth to surface monitor fine particle concentration observations for the month of September 2003 at more than 300 individual locations in the continental US. During September 2003, IDEA provided prototype, near real-time data-fusion products to the Environmental Protection Agency (EPA) directed toward improving the accuracy of EPA s next-day Air Quality Index (AQI) forecasts. Researchers from NASA Langley Research Center and EPA used data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument combined with EPA ground network data to create a NASA-data-enhanced Forecast Tool. Air quality forecasters used this tool to prepare their forecasts of particle pollution, or particulate matter less than 2.5 microns in diameter (PM2.5), for the next-day AQI. The archived data provide a rich resource for further studies and analysis. The IDEA project uses data sets and models developed for tropospheric chemistry research to assist federal, state, and local agencies in making decisions concerning air quality management to protect public health.

Kleb, Mary M.↗
NASA NTRS1989

Fortran Program for X-Ray Photoelectron Spectroscopy Data Reformatting

A FORTRAN program has been written for use on an IBM PC/XT or AT or compatible microcomputer (personal computer, PC) that converts a column of ASCII-format numbers into a binary-format file suitable for interactive analysis on a Digital Equipment Corporation (DEC) computer running the VGS-5000 Enhanced Data Processing (EDP) software package. The incompatible floating-point number representations of the two computers were compared, and a subroutine was created to correctly store floating-point numbers on the IBM PC, which can be directly read by the DEC computer. Any file transfer protocol having provision for binary data can be used to transmit the resulting file from the PC to the DEC machine. The data file header required by the EDP programs for an x ray photoelectron spectrum is also written to the file. The user is prompted for the relevant experimental parameters, which are then properly coded into the format used internally by all of the VGS-5000 series EDP packages.

Abel, Phillip B.↗
NASA NTRS1992

Reformatting Data From X-Ray Photoelectron Spectroscopy

ASCITOVG program for IBM PC-series computers creates files in binary format from columns of numbers in American National Standard Code for Information Interchange (ASCII) format. Files suitable for DEC PDP-11/73 computer under Micro-RSX operating system running the VGS-5000 Enhanced Data Processing (EDP) software package which analyzes data with color graphics display, speeding up analysis compared with batch job processing. Written in FORTRAN.

Abel, P. B.↗
NASA NTRSDate not supplied

Transcriptomics Processing Pipelines for Space Biology: An Open Source and Consensus-Driven Approach

Transcriptomics holds significant value in elucidating the relationship between gene expression, experimental factors, biological factors, and various types of omics data. Enhancing our understanding of these connections is paramount for foundational biology, which plays a pivotal role in devising solutions for challenges pertinent to both space travel and terrestrial life. The NASA GeneLab project, part of the Open Science Data Repository (OSDR.nasa.gov), seeks to accelerate space biology research through cataloging and democratizing ‘omics data, including transcriptomics. Since raw omics data are largely inaccessible to non-bioinformaticians, GeneLab works with the scientific community via the Open Science Analysis Working Groups (AWGs) to develop standard processing pipelines to generate and publish processed data. Unlike raw data, processed data have greater immediate value to diverse users with varying technical backgrounds and computational capabilities. Standardizing processing workflows is essential to match the pace of raw data generation, ensure reproducibility, and enable standardized processed data for comparison across datasets. As of June 2023, transcriptomics studies comprise over half of GeneLab datasets hosted on the OSDR, including data from bulk RNA-seq and Affymetrix or Agilent 1-Channel DNA microarray assays. In collaboration with the AWGs, GeneLab developed consensus processing pipelines for these transcriptomics data types that includes quality control, background correction (microarray only), data normalization and quantification, culminating in the detection and annotation of differentially expressed genes. The work presented here describes Nextflow implementations of GeneLab’s consensus transcriptomics pipelines that automates and accelerates processing of these datasets. In addition to the core data processing, these workflows also include raw data staging and a robust verification and validation program to identify errors in real-time, stop additional downstream computation, and preserve computational resources. These workflows are used to generate GeneLab processed data hosted on the OSDR, and are publicly available as open source software for others to use at: https://github.com/nasa/GeneLab_Data_Processing.

Jonathan Oribello↗
NASA NTRS1984

MERIT - A new approach to upper air forecasting for aviation

The development of a man/computer data enhancement and management system to provide very-short range upper air forecasts is examined. The forecast accuracy and precision problems encountered with the current numerical weather prediction models are discussed. The proposed system is to utilize both radiosonde data and automated pilot reports and provide a 2-12 hour analysis/forecast with a 3 hour forecast cycle. The minimum energy routes using interactive techniques (MERIT) system is described and a diagram is povided. The preliminary testing of a modified MERIT system reveals that the system is not as accurate as the Spectral 12 hour forecast, but is more accurate than the spectral 24 hour forecast. The coplete testing and validation of the MERIT system is required before a comparison with present techniques is possible.

Steinberg, R.↗
NASA NTRS2006

Sensor Management for Applied Research Technologies (SMART)-On Demand Modeling (ODM) Project

NASA requires timely on-demand data and analysis capabilities to enable practical benefits of Earth science observations. However, a significant challenge exists in accessing and integrating data from multiple sensors or platforms to address Earth science problems because of the large data volumes, varying sensor scan characteristics, unique orbital coverage, and the steep learning curve associated with each sensor and data type. The development of sensor web capabilities to autonomously process these data streams (whether real-time or archived) provides an opportunity to overcome these obstacles and facilitate the integration and synthesis of Earth science data and weather model output. A three year project, entitled Sensor Management for Applied Research Technologies (SMART) - On Demand Modeling (ODM), will develop and demonstrate the readiness of Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) capabilities that integrate both Earth observations and forecast model output into new data acquisition and assimilation strategies. The advancement of SWE-enabled systems (i.e., use of SensorML, sensor planning services - SPS, sensor observation services - SOS, sensor alert services - SAS and common observation model protocols) will have practical and efficient uses in the Earth science community for enhanced data set generation, real-time data assimilation with operational applications, and for autonomous sensor tasking for unique data collection.

Goodman, M.↗