Results for “operator decision support” — Page 9

NASA NTRSDate not supplied

How to Educate Decision Makers on the Value and Necessity of Modal Testing and Model Correlation: Tips for Young Engineers

Engineers need to effectively communicate the justification and value of their modal testing and model correlation in terminology familiar to decision makers as it relates to the program’s risk tolerance. This communication must relate to the program’s risk tolerance and the metrics used to judge the performance of both the program and individual decision makers. The challenge is the terminologies familiar to engineers and decision makers are quite different and seemingly unrelated. The engineering profession has developed a specific terminology to solve highly technical issues, which are many times themselves unique to very specific engineering problems. It is all too easy for engineers to believe that everyone in their organization, including the decision makers, has an intrinsic understanding of what they do and the value it brings to the program’s success. This is especially true for young engineers who have recently spent the last four plus years in an academic engineering learning environment, which has a highly technical research oriented atmosphere. Effective communication with decision makers is increasingly important as the technical breadth and practical program and project experience level for up and coming decision makers diminishes. It is not unusual for the decision makers to have technical knowledge in a domain different from structural dynamics (e.g., electronics or systems). Competition among satellite manufactures has increased the focus on programmatic cost and ability to deliver on schedule. NASA programs are also seeing more restrictive programmatic cost and schedule constraints, which impact both analysis and testing. It should also be noted that a comprehensive suite of tests are required to verify a satellite’s design capability with some margin. These tests include static strength verification tests, shock, acoustic, and vibration tests (sine and random) of systems, subsystems, and components. Each of these verification tests provide opportunities for model correlation and risk reduction. It is important to recognize dynamic loads/modal test models may not include all of the flight hardware (i.e., harness, coax, waveguides, connectors, etc.) and the previously mentioned tests are still required for qualification/verification of the design. This paper provides tips to young engineers on how to bridge this communications gap, have a better understanding of the environment in which decision makers operate, and assist them to better support successful missions. While this paper primarily focuses on modal testing and model correlation as related to spacecraft missions, the concepts and recommendations presented here are equally applicable to other fields such as aeronautics, automotive, power generation, etc.

Decision Maker↗

NASA NTRS2011

Use of Probabilistic Risk Assessment in Shuttle Decision Making Process

This slide presentation reviews the use of Probabilistic Risk Assessment (PRA) to assist in the decision making for the shuttle design and operation. Probabilistic Risk Assessment (PRA) is a comprehensive, structured, and disciplined approach to identifying and analyzing risk in complex systems and/or processes that seeks answers to three basic questions: (i.e., what can go wrong? what is the likelihood of these occurring? and what are the consequences that could result if these occur?) The purpose of the Shuttle PRA (SPRA) is to provide a useful risk management tool for the Space Shuttle Program (SSP) to identify strengths and possible weaknesses in the Shuttle design and operation. SPRA was initially developed to support upgrade decisions, but has evolved into a tool that supports Flight Readiness Reviews (FRR) and near real-time flight decisions. Examples of the use of PRA for the shuttle are reviewed.

Boyer, Roger L.↗

NASA NTRSDate not supplied

LIS-Hydro: Authoritative Source for OCONUS Hydro-Intelligence

U.S. military forces are often tasked to participate in a variety of transboundary water-related decision-making activities, including humanitarian assistance operations through Department of State tasking, support of in-country infrastructure development activities that help develop or improve diplomatic relationships, and support of transboundary water treaty negotiations or disputes to reduce risk of conflict caused by water security issues. The U.S. intelligence communities have identified the coordination over shared water resources as an area of significant concern to U.S. national security (U.S. National Defense Strategy, 2018). Such transboundary water issues are projected to intensify in the future under increasingly complex population dynamics, political tensions due to parallel issues, and a changing climate. A 2017 joint NASA, USACE/RDC, and U.S. Air Force co-sponsored workshop revealed a lack of sufficient decision support tools and access to timely technical and contextual information needed to assess and respond to potential water-related threats around the world. The need for an integrated operational service, with the capacity to combine and synthesize hydrological modeling, assimilation, forecasting, and visualization capabilities across the U.S. Government, was highlighted as a key recommendation. In direct response, a subset of the U.S. Department of Defense, National Intelligence Community, and Oak Ridge National Laboratory are collaborating on the development of a fully integrated hydro-modeling and streamflow prediction system (i.e., LIS-Hydro). Completion of the project and sustainment of the operational capability by Air Force Weather will establish a national asset to assist federal agencies implement government-wide strategies around water resources (U.S. Global Water Strategy, 2017). The hydrological products and services will, for the very first time, establish a routinely available authoritative source of global water intelligence information supporting war-fighters, planners, and decision makers at all echelons and services of the U.S. military, Federal government, and intelligence community. A summary of the interagency scientific collaboration in addressing some of the key gaps and needs identified during the 2017 workshop will be presented.

Land Information System↗

NASA NTRS1974

Medical results of the Skylab program

The Skylab food system, waste management system, operational bioinstrumentation, personal hygiene provisions, in-flight medical support system, and the cardiovascular counterpressure garment worn during reentry are described. The medical experiments program provided scientific data and also served as the basis for real-time decisions on flight duration. Premission support, in-flight operational support, and postflight medical activities are surveyed. Measures devised to deal with possible food spoilage, medical instrument damage, and toxic atmosphere caused by the initial failures on the Orbital Workshop (OWS) are discussed. The major medical experiments performed in flight allowed the study of physiological changes as a function of exposure to weightless flight. The experiments included studies of the cardiovascular system, musculoskeletal and fluid/electrolyte balance, sleep, blood, vestibular system, and time and motion studies.

Johnston, R. S.↗

NASA NTRS2012

GeoLab 2011: New Instruments and Operations Tested at Desert RATS

GeoLab is a geological laboratory and testbed designed for supporting geoscience activities during NASA's analog demonstrations. Scientists at NASA's Johnson Space Center built GeoLab as part of a technology project to aid the development of science operational concepts for future planetary surface missions [1, 2, 3]. It is integrated into NASA's Habitat Demonstration Unit, a first generation exploration habitat test article. As a prototype workstation, GeoLab provides a high fidelity working space for analog mission crewmembers to perform in-situ characterization of geologic samples and communicate their findings with supporting scientists. GeoLab analog operations can provide valuable data for assessing the operational and scientific considerations of surface-based geologic analyses such as preliminary examination of samples collected by astronaut crews [4, 5]. Our analog tests also feed into sample handling and advanced curation operational concepts and procedures that will, ultimately, help ensure that the most critical samples are collected during future exploration on a planetary surface, and aid decisions about sample prioritization, sample handling and return. Data from GeoLab operations also supports science planning during a mission by providing additional detailed geologic information to supporting scientists, helping them make informed decisions about strategies for subsequent sample collection opportunities.

Evans, Cindy A.↗

NASA NTRS2019

Modeling Deicing Operations in Departure Scheduling Using Fast Time Simulation

In winter snow conditions, aircraft need inspection for deicing service before takeoff. Deicing service is a procedure to remove frost, ice, slush, or snow from aircraft for safe operation. Deicing operations vary by airport in many ways. Some airports have designated deicing zones, whereas some use a closed runway or terminal area to perform the procedure. Nonetheless, deicing operations add extra workloads to controllers, and cause increased taxi traffic on the ground. NASA and Korea Aerospace Research Institute (KARI) have been collaborating to model deicing operations at Incheon International Airport (ICN). This paper describes the deicing model and the study of deicing operations in departure scheduling using fast time simulations. The deicing model uses a heuristic algorithm for deicing zone assignment. In the fast time simulations, the model uses probability distributions derived from actual operation data to model deicing request and deicing zone time. It is envisioned that such a deicing model can be useful in airport surface scheduling to provide decision support and improve traffic management performance in winter snow operations.

modeling and simulation↗

NASA NTRS2019

Modeling Deicing Operations in Departure Scheduling using Fast Time Simulation

In winter snow conditions, aircraft need inspection for deicing service before takeoff. Deicing service is a procedure to remove frost, ice, slush, or snow from aircraft for safe operation. Deicing operations vary by airport in many ways. Some airports have designated deicing zones, whereas some use a closed runway or terminal area to perform the procedure. Nonetheless, deicing operations add extra workloads to controllers, and cause increased taxi traffic on the ground. NASA and Korea Aerospace Research Institute (KARI) have been collaborating to model deicing operations at Incheon International Airport (ICN). This paper describes the deicing model and the study of deicing operations in departure scheduling using fast time simulations. The deicing model uses a heuristic algorithm for deicing zone assignment. In the fast time simulations, the model uses probability distributions derived from actual operation data to model deicing request and deicing zone time. It is envisioned that such a deicing model can be useful in airport surface scheduling to provide decision support and improve traffic management performance in winter snow operations.

surface operation↗

NASA NTRS2025

Evaluating the Viability of Compact and Portable X-Ray Systems for an Exploration Medical System in a Ground Demonstration

MOTIVATION FOR INCLUDING X-RAY CAPABILITIES For upcoming exploration missions, the need for enhanced medical care becomes critical due to extended mission durations, significant communication delays, and minimal evacuation opportunities. Previous evidence by our team has revealed that among the 119 medical conditions targeted for management during spaceflight within NASA Exploration Medical Capability’s IMPACT Condition List, at least 36 could benefit from radiography (XR). Utilizing XR for diagnosis and management is hypothesized to significantly improve management of crew health by enabling the immediate evaluation and confirmation of potential injuries or illnesses. Beyond clinical applications, XR also holds potential for non-destructive testing (NDT). This includes applications such as assessing the structural integrity of the spacecraft, analyzing surface and meteorite samples, and inspecting onboard electronics. THREE CANDIDATE X-RAY SYSTEMS CHOSEN FOR GROUND DEMONSTRATION The Exploration Medical Capability Element (ExMC) and the Exploration Medical Integrated Product Team (XMIPT) of the Mars Campaign Office initiated early background work for ground demonstrations. In FY21, ExMC published a Concept of Operations to guide requirements development. By FY23, XMIPT and yet2, a technology scouting and open innovation consulting firm, had completed a market survey and trade study to identify potential miniature XR systems. Selection criteria included commercial-off-the-shelf availability, low mass and volume, and regulatory compliance. The top three candidate devices—Remedi REMEX-KA6, MinXray Impact, and FujiFilm Xair—were acquired to characterize the requirements and capabilities of each device. To facilitate testing, phantoms, and radiographic personal protective equipment (PPE) were purchased, and a dedicated space was designated for XRS usage at Glenn Research Center. During this presentation, the mass, volume, and power requirements for each of the three piloted devices are revealed, as well as information regarding the detector, mA, and kV of the devices. GOAL AND OBJECTIVES OF A MINI XRS GROUND DEMONSTRATION The primary goal of ExMC/XMIPT technology demonstrations is to bridge the gap in available, flight-ready medical device technology by flight-testing diagnostic and treatment technologies essential for managing medical conditions during exploration missions. These technologies must adhere to vehicle constraints such as mass, volume, power, and data requirements, integrate seamlessly with medical decision-support tools, and support increasingly Earth-independent operations. There are three main objectives for the future ground demonstration of these three devices. First, we aim to determine the full capabilities of these three miniature XR systems within the context of the spaceflight environment. While medical applications are the primary focus for the miniature XR, a comprehensive exploration of non-medical uses has been initiated by an XMIPT-sponsored NASA SPARK campaign to identify collaborators. Second, we plan to establish criteria and to use insights gained from evaluating each miniature XR against those criteria to select the most suitable system among the three candidates. Third, we intend to evaluate their suitability for flight certification, which includes assessing its durability for launch, reentry, and exposure to high background radiation, as well as its compatibility with existing data architecture systems. Numerous subject matter experts from NASA and partner institutions will support these objectives.

C A Haddix↗

NASA NTRS2013

SARDA: An Integrated Concept for Airport Surface Operations Management

The Spot and Runway Departure Advisor (SARDA) is an integrated decision support tool for airlines and air traffic control tower enabling surface collaborative decision making (CDM) and departure metering in order to enhance efficiency of surface operations at congested airports. The presentation describes the concept and architecture of the SARDA as a CDM tool, and the results from a human-in-the-loop simulation of the tool conducted in 2012 at the FutureFlight Central, the tower simulation facility. Also, presented is the current activities and future plan for SARDA development. The presentation was given at the meeting with the FAA senior advisor of the Surface Operations Office.

surface collaborative decision making↗

NASA NTRS2014

First Results from the Mojave Volatiles Prospector (MVP) Field Campaign, a Lunar Polar Rover Mission Analog

The Mojave Volatiles Prospector (MVP) project is a science-driven field program with the goal to produce critical knowledge for conducting robotic exploration of the Moon. MVP will feed science, payload, and operational lessons learned to the development of a real-time, short-duration lunar polar volatiles prospecting mission. MVP achieves these goals through a simulated lunar rover mission to investigate the composition and distribution of surface and subsurface volatiles in a natural and a priori unknown environment within the Mojave Desert, improving our understanding of how to find, characterize, and access volatiles on the Moon. The MVP field site is the Mojave Desert, selected for its low, naturally occurring water abundance. The Mojave typically has on the order of 2-6% water, making it a suitable lunar analog for this field test. MVP uses the Near Infrared and Visible Spectrometer Subsystem (NIRVSS), Neutron Spectrometer Subsystem (NSS), and a downward facing GroundCam camera on the KREX-2 rover to investigate the relationship between the distribution of volatiles and soil crust variation. Through this investigation, we mature robotic in situ instruments and concepts of instrument operations, improve ground software tools for real time science, and carry out publishable research on the water cycle and its connection to geomorphology and mineralogy in desert environments. A lunar polar rover mission is unlike prior space missions and requires a new concept of operations. The rover must navigate 3-5 km of terrain and examine multiple sites in in just ~6 days. Operational decisions must be made in real time, requiring constant situational awareness, data analysis and rapid turnaround decision support tools. This presentation will focus on the first science results and operational architecture findings from the MVP field deployment relevant to a lunar polar rover mission.

Heldmann, Jennifer L.↗

NASA NTRS2020

Medical Data Architecture Prototype Development - Summary of Recent Work and Proposed Ideas for Upcoming Work

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically-relevant information to support medical operations during exploration missions, and in ExMC Gap Med 10: We do not have the capability to provide computed medical decision support during exploration missions. These gaps recognize the need for a comprehensive medical data management system and the accompanying computational support to provide autonomous medical care during long duration exploration missions. As the MDA matures—including the capability to comprehensively process and discover medically-relevant information to support medical operations during exploration missions—project focus will shift to maturing and extending the MDA platform to enable clinical decision support and real-time guidance. To date, the MDA foundational architecture has recommended exploration medical system Level of Care IV requirements through a series of test bed prototype developments and analog demonstrations. The next stage in the development will focus on more autonomous clinical decision making necessary to address challenges in executing a self-contained medical system that enables health care both with and without assistance from ground support. A thorough understanding of current state of medical decision support systems, advanced machine learning algorithms and vast and varied data sources is required. The development of a clinical decision support for exploration missions (Level of Care V) roadmap is needed: one that assesses of current state of the art of clinical decision support systems (CDSS), interoperability issues, identification of challenges in health and performance monitoring, obtaining and processing information from biosensors, knowledge and data management, data integration and fusion, and advanced algorithm development. This roadmap must also include rapid prototype development in the areas of data processing, advanced analysis and prediction of medical events, and treatment based on medically relevant information processing and evidence-based best practices. In this presentation, an overview of the relevant issues and the beginning framework of a Level of Care V CDSS development roadmap will be provided.

Krihak, M.↗

NASA NTRS2017

EVA Suit Studies: Human Forward Contamination Project

Background: NASA Strategic Knowledge Gap B5: Forward Contamination for Mars. Issue: we have knowledge gaps!: Whether / how microbes are released from crewed pressure systems. Why do we care?: Informs Mars operational concepts - How to protect the science; Informs architecture decisions - How “open” Environmental Control and Life Support (ECLS) systems are; Informs landing site selection decisions - How close we can land / operate to where life may be present. Project goal: get some data to fill in these gaps: Data will help determine whether we’re ready to go to Mars, or if we need to change our systems or operational designs.

Rucker, Michelle↗

NASA NTRS1995

An Open Specification for Space Project Mission Operations Control Architectures

An 'open specification' for Space Project Mission Operations Control Architectures is under development in the Spacecraft Control Working Group of the American Institute for Aeronautics and Astro- nautics. This architecture identifies 5 basic elements incorporated in the design of similar operations systems: Data, System Management, Control Interface, Decision Support Engine, & Space Messaging Service.

spacecraft ground systems↗

NASA NTRS2019

Prescheduling with EOBT’s

As the surface system is deployed across the NAS and fully integrated with existing FAA decision support, the roles of both ATC and Operators are expected to change. This will discuss first hand examples of this evolution as experienced at CLT.

Capps, Al↗

NASA NTRS2013

Spot and Runway Departure Advisor

The Spot and Runway Departure Advisor (SARDA) is a research prototype of a decision support tool for ATC tower controllers to assist in manging and controlling traffic on the surface of an airport. SARDA employs a scheduler to generate an optimal runway schedule and gate push-back - spot release sequence and schedule that improves efficiency of surface operations. The advisories for ATC tower controllers are displayed on an Electronic Flight Strip (EFS) system. The human-in-the-loop simulation of the SARDA tool was conducted for east operations of Dallas-Ft. Worth International Airport (DFW) to evaluate performance of the SARDA tool and human factors, such as situational awareness and workload. The results indicates noticeable taxi delay reduction and fuel savings by using the SARDA tool. Reduction in controller workload were also observed throughout the scenario runs. The future plan includes modeling and simulation of the ramp operations of the Charlotte International Airport, and develop a decision support tool for the ramp controllers.

decision support tool↗

NASA NTRSDate not supplied

CLINICAL DECISION SUPPORT: PATH TO FUNCTIONAL REQUIREMENTS

Long-duration, deep-space exploration missions present significant challenges to crew health and performance. These challenges include the individual and combined effects of microgravity, radiation exposure, isolation, limited resources (mass, volume, power, data and crew time), limited options for evacuation and those associated with delayed or constrained communications, all of which demand greater crew autonomy. Specifically, as the communication delays intensify the further we explore space, the unqualified need for Earth-independent medical operations focused on autonomous diagnosis, treatment and prevention will be key to mission continuation and success. To augment the requisite knowledge, skills and abilities (KSAs) of a time-constrained crew operating under stressful conditions, combatting fatigue, and facing a potential medical crisis, a robust clinical decision support system (CDSS) is a probable solution that would facilitate, guide and inform Earth-independent medical operations, while assisting crewmembers through various clinical presentations. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) is expanding the boundaries of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit. ExMC is actively identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addresses gap Medical-701 within the Inflight Medical Conditions risk: “Enhance medical capabilities within an exploration medical system.” Though mass, volume, and power will face increasing constraints, the projected computational capabilities of spacecraft systems will increase exponentially as information technology continues to advance this decade and beyond. Hence, data, software and computational resources will play an essential and synergistic role in maintaining crew health, wellness and performance in deep space missions. The focus of the CDS project is to develop recommended requirements for an in-vehicle CDSS that acts as a ‘virtual assistant’ for delivering optimal health, performance and medical care during exploration missions. The CDSS is envisioned as an integrated, software-based tool deployed on a laptop computer or handheld device. The CDSS will assist the crew and ground support when interacting with knowledge/databases (e.g. records, pharmacy, schedule), instrumentation (e.g. imaging, physiological monitoring devices), and habitat (e.g. wellness system, task performance system) and vehicle systems (e.g. environmental system, communication system). In addition, the human interface will employ a context-based approach that accounts for the crew’s situation. Thus, extraneous and clinically/operationally non-relevant information are reduced to avoid an increase in cognitive load. The framework of an ideal spaceflight CDSS is to include core and advanced analytical features that incorporate work from collaborators yet maintain a flexible platform for integrating new technology in the future. In fiscal year 2021 (FY21), the CDS project identified requirements through two primary mechanisms: (i) the development of software implementation prototypes and (ii) the application of systems engineering processes. The CDS project developed and tested a series of increasingly complex system prototypes that were based on use cases derived from the CDSS concept of operations (ConOps). These software implementations yielded insights on CDSS functionality as well as lessons learned that provided the initial requirements for CDSS capability. By applying a systems engineering (SE) approach, medical scenarios provided in the ConOps and the use cases for software implementation underwent functional decomposition to identify CDSS functionality. Also, systems-based modeling language (SysML) tools such as activity diagrams were developed from the same ConOps and use cases to identify CDSS functionality. The lessons learned from software implementation defined both specific requirements and broad areas of requirements. Within these defined broad requirement areas, further analysis of the SE products identified specific capability that resulted in the final functional requirements. In summary, the software prototypes, functional decomposition of the ConOps and use cases, and SysML diagrams provided the basis for the CDSS requirements developed in FY21. In the upcoming year, these requirements will be refined for their final ExMC baseline review in latter FY22.

clinical decision support↗

NASA NTRSDate not supplied

Clinical Decision Support: Path to Functional Requirements

Long-duration, deep-space exploration missions present significant challenges to crew health and performance. These challenges include the individual and combined effects of microgravity, radiation exposure, isolation, limited resources (mass, volume, power, data and crew time), limited options for evacuation and those associated with delayed or constrained communications, all of which demand greater crew autonomy. Specifically, as the communication delays intensify the further we explore space, the unqualified need for Earth-independent medical operations focused on autonomous diagnosis, treatment and prevention will be key to mission continuation and success. To augment the requisite knowledge, skills and abilities (KSAs) of a time-constrained crew operating under stressful conditions, combatting fatigue, and facing a potential medical crisis, a robust clinical decision support system (CDSS) is a probable solution that would facilitate, guide and inform Earth-independent medical operations, while assisting crewmembers through various clinical presentations. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) is expanding the boundaries of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit. ExMC is actively identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addresses gap Medical-701 within the Inflight Medical Conditions risk: “Enhance medical capabilities within an exploration medical system.” Though mass, volume, and power will face increasing constraints, the projected computational capabilities of spacecraft systems will increase exponentially as information technology continues to advance this decade and beyond. Hence, data, software and computational resources will play an essential and synergistic role in maintaining crew health, wellness and performance in deep space missions. The focus of the CDS project is to develop recommended requirements for an in-vehicle CDSS that acts as a ‘virtual assistant’ for delivering optimal health, performance and medical care during exploration missions. The CDSS is envisioned as an integrated, software-based tool deployed on a laptop computer or handheld device. The CDSS will assist the crew and ground support when interacting with knowledge/databases (e.g. records, pharmacy, schedule), instrumentation (e.g. imaging, physiological monitoring devices), and habitat (e.g. wellness system, task performance system) and vehicle systems (e.g. environmental system, communication system). In addition, the human interface will employ a context-based approach that accounts for the crew’s situation. Thus, extraneous and clinically/operationally non-relevant information are reduced to avoid an increase in cognitive load. The framework of an ideal spaceflight CDSS is to include core and advanced analytical features that incorporate work from collaborators yet maintain a flexible platform for integrating new technology in the future. In fiscal year 2021 (FY21), the CDS project identified requirements through two primary mechanisms: (i) the development of software implementation prototypes and (ii) the application of systems engineering processes. The CDS project developed and tested a series of increasingly complex system prototypes that were based on use cases derived from the CDSS concept of operations (ConOps). These software implementations yielded insights on CDSS functionality as well as lessons learned that provided the initial requirements for CDSS capability. By applying a systems engineering (SE) approach, medical scenarios provided in the ConOps and the use cases for software implementation underwent functional decomposition to identify CDSS functionality. Also, systems-based modeling language (SysML) tools such as activity diagrams were developed from the same ConOps and use cases to identify CDSS functionality. The lessons learned from software implementation defined both specific requirements and broad areas of requirements. Within these defined broad requirement areas, further analysis of the SE products identified specific capability that resulted in the final functional requirements. In summary, the software prototypes, functional decomposition of the ConOps and use cases, and SysML diagrams provided the basis for the CDSS requirements developed in FY21. In the upcoming year, these requirements will be refined for their final ExMC baseline review in latter FY22.

Clinical decision support↗

NASA NTRS2007

The Transition of NASA EOS Datasets to WFO Operations: A Model for Future Technology Transfer

The collocation of a National Weather Service (NWS) Forecast Office with atmospheric scientists from NASA/Marshall Space Flight Center (MSFC) in Huntsville, Alabama has afforded a unique opportunity for science sharing and technology transfer. Specifically, the NWS office in Huntsville has interacted closely with research scientists within the SPORT (Short-term Prediction and Research and Transition) Center at MSFC. One significant technology transfer that has reaped dividends is the transition of unique NASA EOS polar orbiting datasets into NWS field operations. NWS forecasters primarily rely on the AWIPS (Advanced Weather Information and Processing System) decision support system for their day to day forecast and warning decision making. Unfortunately, the transition of data from operational polar orbiters or low inclination orbiting satellites into AWIPS has been relatively slow due to a variety of reasons. The ability to integrate these high resolution NASA datasets into operations has yielded several benefits. The MODIS (MODerate-resolution Imaging Spectrometer ) instrument flying on the Aqua and Terra satellites provides a broad spectrum of multispectral observations at resolutions as fine as 250m. Forecasters routinely utilize these datasets to locate fine lines, boundaries, smoke plumes, locations of fog or haze fields, and other mesoscale features. In addition, these important datasets have been transitioned to other WFOs for a variety of local uses. For instance, WFO Great Falls Montana utilizes the MODIS snow cover product for hydrologic planning purposes while several coastal offices utilize the output from the MODIS and AMSR-E instruments to supplement observations in the data sparse regions of the Gulf of Mexico and western Atlantic. In the short term, these datasets have benefited local WFOs in a variety of ways. In the longer term, the process by which these unique datasets were successfully transitioned to operations will benefit the planning and implementation of products and datasets derived from both NPP and NPOESS. This presentation will provide a brief overview of current WFO usage of satellite data, the transition of datasets between SPORT and the N W S , and lessons learned for future transition efforts.

Darden, C.↗