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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

Shuttle Laser Altimeter

The Shuttle Laser Altimeter (SLA) is a Hitchhiker experiment that has flown twice; first on STS-72 in January 1996 and then on STS-85 in August 1997. Both missions produced successful laser altimetry and surface lidar data products from approximately 80 hours per mission of SLA data operations. A total of four Shuttle missions are planned for the SLA series. This paper documents SLA mission results and explains SLA pathfinder accomplishments at the mid-point in this series of Hitchhiker missions. The overall objective of the SLA mission series is the transition of the Goddard Space Flight Center airborne laser altimeter and lidar technology to low Earth orbit as a pathfinder for NASA operational space-based laser remote sensing devices. Future laser altimeter sensors will utilize systems and approaches being tested with SLA, including the Multi-Beam Laser Altimeter (MBLA) and the Geoscience Laser Altimeter System (GLAS). MBLA is the land and vegetation laser sensor for the NASA Earth System Sciences Pathfinder Vegetation Canopy Lidar (VCL) Mission, and GLAS is the Earth Observing System facility instrument on the Ice, Cloud, and Land Elevation Satellite (ICESat). The Mars Orbiting Laser Altimeter, now well into a multi-year mapping mission at the red planet, is also directly benefiting from SLA data analysis methods, just as SLA benefited from MOLA spare parts and instrument technology experience [5] during SLA construction in the early 1990s.

Bufton, Jack L.↗

NASA NTRS2022

Effective Uncertainty Quantification for Multi-Angle Polarimetric Aerosol Remote Sensing Over Ocean

Multi-angle polarimetric (MAP) measurements can enable detailed characterization of aerosol microphysical and optical properties and improve atmospheric correction in ocean color remote sensing. Advanced retrieval algorithms have been developed to obtain multiple geophysical parameters in the atmosphere–ocean system. Theoretical pixel-wise retrieval uncertainties based on error propagation have been used to quantify retrieval performance and determine the quality of data products. However, standard error propagation techniques in high-dimensional retrievals may not always represent true retrieval errors well due to issues such as local minima and the nonlinear dependence of the forward model on the retrieved parameters near the solution. In this work, we analyze these theoretical uncertainty estimates and validate them using a flexible Monte Carlo approach. The Fast Multi-Angular Polarimetric Ocean coLor (FastMAPOL) retrieval algorithm, based on efficient neural network forward models, is used to conduct the retrievals and uncertainty quantification on both synthetic HARP2 (Hyper-Angular Rainbow Polarimeter 2) and AirHARP (airborne version of HARP2) datasets. In addition, for practical application of the uncertainty evaluation technique in operational data processing, we use the automatic differentiation method to calculate derivatives analytically based on the neural network models. Both the speed and accuracy associated with uncertainty quantification for MAP retrievals are addressed in this study. Pixel-wise retrieval uncertainties are further evaluated for the real AirHARP field campaign data. The uncertainty quantification methods and results can be used to evaluate the quality of data products, as well as guide MAP algorithm development for current and future satellite systems such as NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission.

PACE↗

NASA NTRS2014

Cloud Retrieval Intercomparisons Between SEVIRI, MODIS and VIIRS with CHIMAERA PGE06 Data Collection 6 Products

The Cross-platform HIgh resolution Multi-instrument AtmosphEric Retrieval Algorithms (CHIMAERA) system allows us to perform MODIS-like cloud top, optical and microphysical properties retrievals on any sensor that possesses a minimum set of common spectral channels. The CHIMAERA system uses a shared-core architecture that takes retrieval method out of the equation when intercomparisons are made. Here we show an example of such retrieval and a comparison of simultaneous retrievals done using SEVIRI, MODIS and VIIRS sensors. All sensor retrievals are performed using CLAVR-x (or CLAVR-x based) cloud top properties algorithm. SEVIRI uses the SAF_NWC cloud mask. MODIS and VIIRS use the IFF-based cloud mask that is a shared algorithm between MODIS and VIIRS. The MODIS and VIIRS retrievals are performed using a VIIRS branch of CHIMAERA that limits available MODIS channel set. Even though in that mode certain MODIS products such as multilayer cloud map are not available, the cloud retrieval remains fully equivalent to operational Data Collection 6.

cloud retrieval↗

NASA NTRS2011

A Compilation of Space Shuttle Sonic Boom Measurements - Supplemental STS Sonic Boom Files

Supplemental STS Sonic Boom Files for NASA/CR-2011-217080. Data files included on CDROM formatted to ISO 9660 standards. Sonic boom measurements have been obtained on 26 flights of the Space Shuttle system beginning with the launch of STS-1 on April 12, 1981, to the reentry-descent of STS-41 into EAFB on Oct. 10, 1990. A total of 23 boom measurements were acquired within the focus region off the Florida coast during 3 STS launch-ascents and 113 boom measurements were acquired during 23 STS reentry-descent to landing into Florida and California. Sonic boom measurements were made under, and lateral to, the vehicle ground track and cover the Mach-altitude range of about 1.3 to 23 and 54,000 feet to 243,000 feet, respectively. Vehicle operational data, flight profiles and weather data were also gathered during the flights. This STS boom database is contained in 26 documents, some are formal and referenceable but most internal documents. Another 38 documents, also non-referenceable, contain predicted sonic boom footprints for reentry-descent flights on which no measurements were made. The purpose of this report is to provide an overview of the STS sonic boom database and summarize the main findings.

Maglieri, Domenic J.↗

NASA NTRS2024

Satellite-Based Tracking of Reservoir Operations for Flood Management During the 2018 Extreme Weather Event in Kerala, India

Uncoordinated management of hydropower dams during extreme and unexpected precipitation events in mountainous terrain can have disastrous consequences due to the competing nature of flood control and hydropower generation. Numerous cases of flooding events that have been exacerbated due to insufficient storage conditions in hydropower dams have been reported worldwide. There is a need for a scalable and publicly accessible monitoring framework that is capable of providing reliable, near-real time, and transparent reservoir operations data. A fully satellite-based framework is the most viable solution to build such capability. The Reservoir Assessment Tool (RAT 3.0), which utilizes high frequency remote sensing-based surface area and reservoir storage estimation alongside hydrological modelled inflow was applied here for the 2018 Kerala floods in India as a globally representative case for a mountainous river basin with high precipitation and hydropower dams. Application of satellite-based RAT 3.0 in monitoring the state of 19 reservoirs in Kerala during the flood event showed very promising results. In general, RAT 3.0, using satellite remote sensing, was found to be able to capture the temporal trend of the reservoir storage and pinpoint the sudden shift in filling or release decisions made by the dam operator. Inflow modelling in such regions was found to require careful calibration with identification of reservoirs that are heavily regulated being a critical aspect. The perennial high cloud cover in such regions necessitate and highlights the central role played by microwave and radar-based satellite sensors, such as the Surface Water and Ocean Topography (SWOT) mission, in tracking reservoir state. An operational version of RAT 3.0 for stakeholder agencies tailored for hydropower dams operating in high precipitation and mountainous environments is a real-world outcome of this study.

Sarath Suresh↗

NASA NTRS2017

Real Time Metrics and Analysis of Integrated Arrival, Departure, and Surface Operations

A real time dashboard was developed in order to inform and present users notifications and integrated information regarding airport surface operations. The dashboard is a supplement to capabilities and tools that incorporate arrival, departure, and surface air-traffic operations concepts in a NextGen environment. As trajectory-based departure scheduling and collaborative decision making tools are introduced in order to reduce delays and uncertainties in taxi and climb operations across the National Airspace System, users across a number of roles benefit from a real time system that enables common situational awareness. In addition to shared situational awareness the dashboard offers the ability to compute real time metrics and analysis to inform users about capacity, predictability, and efficiency of the system as a whole. This paper describes the architecture of the real time dashboard as well as an initial set of metrics computed on operational data. The potential impact of the real time dashboard is studied at the site identified for initial deployment and demonstration in 2017; Charlotte-Douglas International Airport. Analysis and metrics computed in real time illustrate the opportunity to provide common situational awareness and inform users of metrics across delay, throughput, taxi time, and airport capacity. In addition, common awareness of delays and the impact of takeoff and departure restrictions stemming from traffic flow management initiatives are explored. The potential of the real time tool to inform the predictability and efficiency of using a trajectory-based departure scheduling system is also discussed.

integrated arrival departure surface operations↗

NASA NTRS1990

On-orbit assembly/servicing task definition study

The OEXP vehicles being envisioned to carry out the Presidential space goals of a lunar outpost and human exploration of Mars will require on-orbit assembly, refurbishment, checkout, and launch. The On-orbit Assembly/Servicing Task Definition Study applies the space vehicle processing experience and procedures archives resident at NASA's Kennedy Space Center (KSC) to determine the task flows, and resources/facilities necessary to process the OEXP vehicles at Space Station Freedom (SSF). This data base is examined to find the closest analogies to OEXP vehicle components and assembly/refurbishment tasks. Transition tables are generated to provide traceability from KSC hardware processing experience to analogous on-orbit processing of the OEXP vehicles. Iterations in which the task flows are broken down into realistic extravehicular activity (EVA) primitive subtasks and times, and to apply automation and robotic technology to reduce crew risks and minimize EVA time, will enhance the value and accuracy of the predicted flows. These processing scenarios and the resulting resource/facility requirements are used to determine impacts of SSF, resulting in change requests to SSF requirements for provision of 'hooks and scars' to evolve the assembly complete Space Station into a transportation node. Study results to date include assembly analysis of the Martin Marietta Phobos Gateway Vehicle, refurbishment analysis of the Martin Marietta Lunar Evolution Piloted and Cargo Vehicles, and assembly analysis of the Boeing Mars Evolution Vehicle. The results of this study will be accumulated into the vehicle processing operations data base for subsequent modeling, life cycle cost, vehicle growth, and SSF impact analysis.

Vargo, Rick↗

NASA NTRS2012

Transition of Suomi National Polar-Orbiting Partnership (S-NPP) Data Products for Operational Weather Forecasting Applications

SPoRT is a team of NASA/NOAA scientists focused on demonstrating the utility of NASA and future NOAA data and derived products on improving short-term weather forecasts. Work collaboratively with a suite of unique products and selected WFOs in an end-to-end transition activity. Stable funding from NASA and NOAA. Recognized by the science community as the "go to" place for transitioning experimental and research data to the operational weather community. Endorsed by NWS ESSD/SSD chiefs. Proven paradigm for transitioning satellite observations and modeling capabilities to operations (R2O). SPoRT s transition of NASA satellite instruments provides unique or higher resolution data products to complement the baseline suite of geostationary data available to forecasters. SPoRT s partnership with NWS WFOs provides them with unique imagery to support disaster response and local forecast challenges. SPoRT has years of proven experience in developing and transitioning research products to the operational weather community. SPoRT has begun work with CONUS and OCONUS WFOs to determine the best products for maximum benefit to forecasters. VIIRS has already proven to be another extremely powerful tool, enhancing forecasters ability to handle difficult forecasting situations.

Smith, Matthew R.↗

NASA NTRS2009

Microbial Risk Assessment

Historically, microbiological spaceflight requirements have been established in a subjective manner based upon expert opinion of both environmental and clinical monitoring results and the incidence of disease. The limited amount of data, especially from long-duration missions, has created very conservative requirements based primarily on the concentration of microorganisms. Periodic reevaluations of new data from later missions have allowed some relaxation of these stringent requirements. However, the requirements remain very conservative and subjective in nature, and the risk of crew illness due to infectious microorganisms is not well defined. The use of modeling techniques for microbial risk has been applied in the food and potable water industries and has exceptional potential for spaceflight applications. From a productivity standpoint, this type of modeling can (1) decrease unnecessary costs and resource usage and (2) prevent inadequate or inappropriate data for health assessment. In addition, a quantitative model has several advantages for risk management and communication. By identifying the variable components of the model and the knowledge associated with each component, this type of modeling can: (1) Systematically identify and close knowledge gaps, (2) Systematically identify acceptable and unacceptable risks, (3) Improve communication with stakeholders as to the reasons for resource use, and (4) Facilitate external scientific approval of the NASA requirements. The modeling of microbial risk involves the evaluation of several key factors including hazard identification, crew exposure assessment, dose-response assessment, and risk characterization. Many of these factors are similar to conditions found on Earth; however, the spaceflight environment is very specialized as the inhabitants live in a small, semi-closed environment that is often dependent on regenerative life support systems. To further complicate modeling efforts, microbial dose-response characteristics may be affected by a potentially dysfunctional crew immune system during a mission. In addition, microbial virulence has been shown to change under certain conditions during spaceflight, further complicating dose-response characterization. An initial study of the applicability of microbial risk assessment techniques was performed using Crew Health Care System (CHeCS) operational data from the International Space Station potable water systems. The risk of infection from potable water was selected as the flight systems and microbial ecology are well defined. This initial study confirmed the feasibility of using microbial risk assessment modeling for spaceflight systems. While no immediate threat was detected, the study identified several medically significant microorganisms that could pose a health risk if uncontrolled. The study also identified several specific knowledge gaps in making a risk assessment and noted that filling these knowledge gaps is essential as the risk estimates may change by orders of magnitude depending on the answers. The current phase of the microbial risk assessment studies focuses on the dose-response relationship of specific infectious agents, focusing on Salmonella enterica Typhimurium, Pseudomonas spp., and Escherichia coli, as their evaluation will provide a better baseline for determining the overall hazard characterization. The organisms were chosen as they either have been isolated on spacecraft or have an identified route of infection during a mission. The characterization will utilize dose-response models selected either from the peer-reviewed literature and/or by using statistical approaches. Development of these modeling and risk assessment techniques will help to optimize flight requirements and to protect the safety, health, and performance of the crew.

Ott, C. M.↗

NASA NTRS1998

A Table-Driven Control Method to Meet Continuous, Near-Real-Time Observation Requirements for the Solar X-Ray Imager

The design of the Solar X-Ray Imager (SXI) for the Geostationary Operational Environmental Satellite (GOES) presents an unusual scenario for controlling the observing sequences. The SXI is an operational instrument, designed not primarily for scientific research, but for providing "operational" data used by the National Oceanic and Atmospheric Administration (NOAA) to forecast the near-term space weather. To this end, a sequence of images selected to cover the full dynamic range of the sun will be executed routinely. As the dynamics of the sun have differing temporal cadences, the frequency of various images will differ. These images must be routinely received at the forecast center in near real-time, 24-hours a day, with a minimum of interruptions. While these requirements clearly lead to a 'routine patrol' of images, the parameters for each do not form a static set. The dynamics of the sun will change with the I 1-year solar cycle. The performance of the imaging will vary with on-orbit conditions and time. And while the SXI is not intended as a research instrument, forecasting techniques may change with time, which in turn will further alter the imaging sequences. An additional complication is the highly restricted commanding window, and a very slow commanding rate. To fulfill these requirements, the SXI was designed to utilize a table-driven approach. Sequences are defined using structured loops, with nested repetitions and delays. These sequences reference combinations of imaging parameters which in turn reference tables of parameters than can be loaded by ground commands. Multiple sequences can be built and stored in preparation for execution when determined appropriate by the NOAA forecasters. The result is an approach that can be used to provide a flexible, yet autonomous SXI capable of meeting both arbitrary forecasting requirements, and operating within the commanding constraints.

Wallace, Shawn↗

NASA NTRS1951

Preliminary Transient Performance Data for Afterburner Operation of Westinghouse Electronic Power Regulator on XJ34-WE-32 Turbojet Engine in Altitude Wind Tunnel

At the request of the Bureau of Aeronautics, Department of the Navy, an investigation of the Westinghouse XJ34-WE-32 turbojet engine is being conducted in the NACA Lewis altitude wind tunnel to determine the steady-state and transient operating characteristics of the controlled and uncontrolled engine at various altitudes and ram pressure ratios. As part of this program, transient performance data that illustrate the operation of the engine is obtained in the form of oscillographic traces. Similar data for engine operation i n the afterburning range, covering a range of throttle settings from the minimum value giving rated speed (throttle position, 72 degrees) to full afterburning (throttle position, ll0 degrees), is presented herein. These data thus serve to indicate the transient characteristics of the engine when the throttle is advance into, withdrawn from, and moved within the afterburning range in a stepwise manner, as well as the steady-state stability of the engine during afterburning .

Vasu, George↗

NASA NTRS1994

Renaissance architecture for Ground Data Systems

The Mission Operations and Data Systems Directorate (MO&DSD) has embarked on a new approach for developing and operating Ground Data Systems (GDS) for flight mission support. This approach is driven by the goals of minimizing cost and maximizing customer satisfaction. Achievement of these goals is realized through the use of a standard set of capabilities which can be modified to meet specific user needs. This approach, which is called the Renaissance architecture, stresses the engineering of integrated systems, based upon workstation/local area network (LAN)/fileserver technology and reusable hardware and software components called 'building blocks.' These building blocks are integrated with mission specific capabilities to build the GDS for each individual mission. The building block approach is key to the reduction of development costs and schedules. Also, the Renaissance approach allows the integration of GDS functions that were previously provided via separate multi-mission facilities. With the Renaissance architecture, the GDS can be developed by the MO&DSD or all, or part, of the GDS can be operated by the user at their facility. Flexibility in operation configuration allows both selection of a cost-effective operations approach and the capability for customizing operations to user needs. Thus the focus of the MO&DSD is shifted from operating systems that we have built to building systems and, optionally, operations as separate services. Renaissance is actually a continuous process. Both the building blocks and the system architecture will evolve as user needs and technology change. Providing GDS on a per user basis enables this continuous refinement of the development process and product and allows the MO&DSD to remain a customer-focused organization. This paper will present the activities and results of the MO&DSD initial efforts toward the establishment of the Renaissance approach for the development of GDS, with a particular focus on both the technical and process implications posed by Renaissance to the MO&DSD.

Perkins, Dorothy C.↗

NASA NTRS2013

SPoRT: Transitioning NASA and NOAA Experimental Data to the Operational Weather Community

Established in 2002 to demonstrate the weather and forecasting application of real-time EOS measurements, the NASA Short-term Prediction Research and Transition (SPoRT) program has grown to be an end-to-end research to operations activity focused on the use of advanced NASA modeling and data assimilation approaches, nowcasting techniques, and unique high-resolution multispectral data from EOS satellites to improve short-term weather forecasts on a regional and local scale. With the ever-broadening application of real-time high resolution satellite data from current EOS, Suomi NPP, and planned JPSS and GOES-R sensors to weather forecast problems, significant challenges arise in the acquisition, delivery, and integration of the new capabilities into the decision making process of the operational weather community. For polar orbiting sensors such as MODIS, AIRS, VIIRS, and CRiS, the use of direct broadcast ground stations is key to the real-time delivery of the data and derived products in a timely fashion. With the ABI on the geostationary GOES-R satellite, the data volumes will likely increase by a factor of 5-10 from current data streams. However, the high data volume and limited bandwidth of end user facilities presents a formidable obstacle to timely access to the data. This challenge can be addressed through the use of subsetting techniques, innovative web services, and the judicious selection of data formats. Many of these approaches have been implemented by SPoRT for the delivery of real-time products to NWS forecast offices and other weather entities. Once available in decision support systems like AWIPS II, these new data and products must be integrated into existing and new displays that allow for the integration of the data with existing operational products in these systems. SPoRT is leading the way in demonstrating this enhanced capability. This paper will highlight the ways SPoRT is overcoming many of the challenges presented by the enormous data volumes of current and future satellite systems to get unique high quality research data into the operational weather environment.

Jedlovec, Gary J.↗

NASA NTRS1965