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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Visualization and Analysis of Near Real-Time Global Cloud Composites (GCC): Integration in a Geospatial Web Mapping Application

The NASA Langley Satellite ClOud and Radiation Property retrieval System (SatCORPS) team provides tools for retrieving cloud information from operational and research meteorological imager data. LEO and GEO satellite imagers are used for fusing hourly mosaics which create the Global Cloud Composite (GCC). The GCC provides global cloud products with a low latency which can help satisfy the growing needs of the research, modeling and business communities. The Esri ArcGIS system is used to transform the GCC data into Analysis Ready Data (ARD) which can be utilized for a variety of visualization and analysis activities in support of weather diagnoses/forecasting, Earth Sciences remote sensing applications, and disaster management. Additionally, the data is enabled as ArcGIS Image Services and Open Geospatial Consortium (OGC) Web Mapping/Coverage Services to be consumed via API within a web mapping application. We will present a preview of the new interactive SatCORPS GCC web mapping application and its capabilities in allowing users to access and use GIS data within it.

Web Mapping Application↗
NASA NTRS2024

Earth-Independent Medical Operations (EIMO) Concept of Operations (ConOps)

Compared to the current paradigm for crew health in low-Earth orbit and Lunar missions that rely on constant communication with Mission Control, there is an anticipated shift in medical operations for deep-space exploration missions. This shift stems from mission constraints imposed by the considerable distance from Earth, which include resource limitations due to a lack of resupply, mass, power, volume, and data limitations, challenges imposed by communication latency and the inability to evacuate in case of emergencies. To transition towards a more self-reliant medical approach, a comprehensive strategy is essential to progressively enable crew autonomy and mitigate mission success risks in the challenging environment of space. This transformative shift is collectively referred to as "Earth-Independent Medical Operations" (EIMO), signifying the gradual transfer of medical care and decision-making from terrestrial resources to space-based assets. This transition is aimed at bolstering astronaut health and performance while simultaneously reducing the overall risks associated with space missions. The constraints related to EIMO necessitate an integrated development of medical systems, featuring interoperability with mission planning, vehicle design, spacesuit design, and data architecture. This integration is vital in establishing a robust medical infrastructure that not only supports the well-being of astronauts but also ensures the success of the mission as a whole. The Human Research Program (HRP) Exploration Medical Capability (ExMC) Element has developed a model-based Concept of Operations (ConOps) outlining an initial vision for EIMO. Within this ConOps, a comprehensive view is presented, encompassing stakeholder needs, system objectives, and system goals associated with EIMO. Additionally, it provides illustrative examples of the various activities (scenarios) for which the system will be employed during missions. The selection of these activities has been meticulous, aiming to encompass a wide spectrum of medical conditions, including those falling under different risk categories, such as low-likelihood-low-consequence, low-likelihood-high-consequence, and high-likelihood-low-consequence. The selection of these activities (scenarios) effectively encompasses the wide range of medical events situated within an assumed probability-consequence bell curve. In each scenario, at least one of the five main EIMO components identified is captured. Those EIMO components are: Pre-mission Planning, Acute and Emergent Management Decision Making, Prolonged Medical Management Decision Making, Supplies and Resource Management, and Task Load Management. The ConOps was developed by a multidisciplinary team consisting of systems engineers, scientists, and clinicians across NASA and aims to serve as an initial recommendation to gradually and safely enabling crew autonomy for Mars missions and beyond.

Earth Independent Medical Operations↗
NASA NTRS2023

Slow Solar Wind Connection Science during Solar Orbiter's First Close Perihelion Passage

The Slow Solar Wind Connection Solar Orbiter Observing Plan (Slow Wind SOOP) was developed to utilize the extensive suite of remote-sensing and in situ instruments on board the ESA/NASA Solar Orbiter mission to answer significant outstanding questions regarding the origin and formation of the slow solar wind. The Slow Wind SOOP was designed to link remote-sensing and in situ measurements of slow wind originating at open–closed magnetic field boundaries. The SOOP ran just prior to Solar Orbiter's first close perihelion passage during two remote-sensing windows (RSW1 and RSW2) between 2022 March 3–6 and 2022 March 17–22, while Solar Orbiter was at respective heliocentric distances of 0.55–0.51 and 0.38–0.34 au from the Sun. Coordinated observation campaigns were also conducted by Hinode and IRIS. The magnetic connectivity tool was used, along with low-latency in situ data and full-disk remote-sensing observations, to guide the target pointing of Solar Orbiter. Solar Orbiter targeted an active region complex during RSW1, the boundary of a coronal hole, and the periphery of a decayed active region during RSW2. Postobservation analysis using the magnetic connectivity tool, along with in situ measurements from MAG and SWA/PAS, showed that slow solar wind originating from two out of three of the target regions arrived at the spacecraft with velocities between ∼210 and 600 km s −1 . The Slow Wind SOOP, despite presenting many challenges, was very successful, providing a blueprint for planning future observation campaigns that rely on the magnetic connectivity of Solar Orbiter.

Slow solar wind↗
NASA NTRSDate not supplied

On The Processing of Log Files for Monitoring Antenna Health

In order to improve the quality of geodetic results, we have developed an infrastructure for timely processing of telemetry from IVS observing stations. We check every hour for new log files with telemetry from both VLBI observing sessions, single dish experiments, and stow-in data collection and automatically process them. The telemetry data we use is the system temperature, phase calibration phases and amplitudes, system equivalent flux density, and the differences between formatter clock and GPS clock. For the system temperature and phase calibration, processing includes filtering out outliers and computing averages and rms of the scatter in each scan. Furthermore, for the phase calibration we also compute the group delay and detect spurious signals. Cleaned and post-processed telemetry is archived. Our process detects abnormalities, such as, anomalously high system temperature, unstable phase calibration phases, jumps in the GPS and formatter clock differences, and others. With our procedure, the latency of detection of station abnormalities is reduced to less than two hours. Early detection of abnormalities reduces the amount of affected data since station personnel get early alerts. We discuss our experience of running this system since 2022.

VLBI↗
NASA NTRSDate not supplied

NASA’s Satellite Needs Working Group Management Office: Developing Solutions in an Agile, Open Science Environment

Every two years, the National Aeronautics and Space Administration (NASA) leads an assessment of U.S. Federal civilian agency Earth observation needs submitted through the Satellite Needs Working Group (SNWG) survey. In four survey cycles beginning in 2016, nearly 400 high-priority satellite needs have been identified, spanning Earth Science and representing a wide variety of potential applications for Earth observation data. During each assessment cycle, new data products and services (i.e., solutions) that meet the needs of multiple agencies are identified and proposed for funding. The majority of solutions being developed or currently operational are global in scope, including harmonized land surface reflectance data from Landsat and Sentinel-2; composites of cloud properties derived from MODIS, VIIRS, and five geostationary satellites; dynamic surface water extent and land surface disturbance products derived from multiple optical and radar missions; a suite of low-latency products from the ICESat-2 mission; and a soil moisture product derived from the upcoming NISAR mission. The SNWG Management Office, within the Earth Action element of NASA’s Earth Science Division, manages both the biennial SNWG survey assessment and the development of solutions starting at full capacity with the 2020 cycle. Each solution project is required to align with NASA’s open science policy, including developing source code in an open code repository, having an open-source software license, and making all data freely available via NASA’s Earthdata website. The presentation will include an overview of the SNWG process, its emphasis on open science, and highlight several operational solutions freely available to the global research and applications communities.

Katrina Virts↗
NASA NTRSDate not supplied

The Crustal Dynamics Data Information System (CDDIS) – Updates and Future Developments

As earth observing services and techniques have flourished, data and products have exponentially grown, like the proliferation of GNSS stations capable of providing real-time data, SLR stations shifting to kHz lasers, and VLBI’s implementation of VGOS telescopes. The CDDIS is continually evolving to fulfill the new storage, quality check, and latency requirements that these changes bring, as well as meet new standards such as the shift toward FAIR and open science. These have shaped how the CDDIS develops new software and resources. Beginning next year, the CDDIS will begin to transition their data and products to the AWS cloud, beginning with DORIS data. This poster will highlight the CDDIS’s recently updated processing system, new data and products available, and future work.

Justine Woo↗
NASA NTRS2024

Future Lunar Surface Network Study: Final Project Report-Unlimited Data Rights

Nokia of America Corporation (Nokia) powered by the research and innovation of Nokia Bell Labs, is honored to have been asked by NASA to conduct a Systems Engineering and Integration (SE&I) study to evaluate an Initial Operating Capability (IOC) for a 3rd Generation Partnership Project (3GPP)-based future lunar surface communication network for the Artemis Program. In particular, the SE&I study has focused on developing an architecture and a 3GPP-based network solution that meets the requirements of the Artemis V mission and at the same time can be evolved and expanded to meet the needs and requirements of future missions in the Moon to Mars program. Nokia strongly believes that 3GPP-based communications and networking solutions present the most effective and future-proof technological path for advanced lunar surface communications (and beyond) for the next decades. 3GPP technologies (whether 4G, 5G or 6G in the future) have revolutionized voice, video, and data transmissions on Earth in consumer, enterprise, and industrial applications, and continue to enable significant gains in productivity, efficiency, and safety. The same benefits can be harnessed for space missions and the future lunar economy including, but not limited to the Artemis program. 3GPP technologies will revolutionize lunar surface communications by increasing data-rates, reducing latency, and providing critical voice, video and data communication capabilities across large surface areas while meeting the stringent reliability requirements of human-rated space flight missions.

Nokia Bell Labs↗
NASA NTRS2024

Crew Health and Performance Integrated Data Architecture (CHP-IDA) Project

BACKGROUND: Future Human Exploration missions introduce a new paradigm as crews move further from the resupply and near real-time ground support typical of Low Earth Orbit missions today. Without immediate support from ground-based personnel, exploration crews will be more reliant on inflight data and technology to respond to emergencies and anomalies. A data architecture to support a new generation of technologies, employing advanced analytical and predictive modeling techniques, is needed to enable crew autonomy. OVERVIEW: The Crew Health and Performance Integrated Data Architecture (CHP-IDA) project funded by NASA’s Exploration Medical Integrated Product Team (XMIPT) is laying a foundation for future in-flight informatics by providing a back-end architecture for collecting, storing, and integrating multiple sources of data generated by and around the crew. CHP-IDA provides a platform for common data models and Application Programming Interfaces to access, integrate, process, and display CHP data (e.g., environmental, exercise, medical, sleep, performance, etc.). This will facilitate the increased situation awareness and decision support required by the crew and remote support of exploration missions. This presentation will describe the currently ongoing effort to develop and evaluate a path-to-flight concept of the CHP-IDA software and its core capabilities. Current integrations will be discussed, including analytics for Extravehicular Activity metabolic rate and data ingestion from a multi-functional integrated medical device. The presentation will also provide examples of scenarios used to demonstrate the CHP-IDA through human-in-the-loop test bed activities as well as examples of appropriate system performance metrics. DISCUSSION: Today, in-flight data is often siloed, unsynchronized, and largely inaccessible in real time. Many data sets require manual entry and/or data transfer between vehicles and the ground. These issues contribute to risks in supporting exploration medical capabilities. The CHP-IDA is a back-end data system providing core capabilities needed for timely and meaningful data insights across CHP domains to crew and remote personnel to enable increased crew autonomy. Future work includes collaboration with additional CHP domains, new technology integrations, and further demonstrations of the IDA within different vehicle and communication latency contexts. LEARNING OBJECTIVES 1. The audience will understand that the CHP-IDA is a back-end system, providing a platform to facilitate access, promote decision tools, and provide meaningful insights to crew and to remote stakeholders during exploration missions. 2. The audience will gain insight into human-centered research and activities used to discover CHP domain data needs and pain points and how this information is used to guide development of the IDA.

Exploration↗
NASA NTRS2024

ISS Technology Demonstrations for Future Spaceflight Medical Systems

Throughout the history of human spaceflight, crewmembers have experienced various in-flight medical conditions including illness and injury. Planned missions to the Moon and Mars will require capabilities to maintain the health of future space travelers. Mass, power, and volume available in the vehicles and habitats for these missions will be severely constrained; resupply of resources will be limited or non-existent, as will opportunities for evacuation to Earth. Furthermore, ground-based support will be hampered by communication latencies and blackouts. These vehicle and mission constraints will necessitate a medical system that has been efficiently planned, providing on-board procedural guidance in addition to a variety of medical devices and consumable resources. Medical capabilities required for the diagnosis and treatment of potential medical conditions during future spaceflight missions may include real-time health monitoring, medical imaging, and biomarker analyses ( e.g., blood or urine). Terrestrial medicine shares these needs, thus many of these medical capabilities could likely be satisfied by Commercial-Off-The-Shelf (COTS) devices and methodologies; however, in some cases the unique space environment and increased mission duration will drive the need to modify technologies and the way care is provided. NASA’s Human Research Program (HRP) Exploration Medical Capability (ExMC) Element and Mars Campaign Office’s Exploration Medical Integrated Product Team (XMIPT) are working together to decrease medical risk during exploration missions. Flight-tested medical diagnostic and treatment technologies are necessary to effectively manage medical conditions relevant to exploration missions while meeting vehicle constraints, integrating with medical decision-support tools, and enabling increasingly Earth-independent operations. Several projects have leveraged the ISS as a testbed for exploration, including 1) i n- situ blood analysis, 2) medical inventory, 3) intravenous fluid generation, and 4) autonomous medical procedure guidance. Management of several in-flight medical conditions, such as bacterial and viral infections and acute radiation syndrome, is dramatically improved with ability to assess blood cell populations, electrolytes, and metabolites. I n December 2020 and January 2021 ExMC performed an ISS technology demonstration (Tech Demo) of the HemoCue® WBC DIFF analyzer (HemoCue, Brea, CA), a COTS device that was modified to enable functionality in a spaceflight environment. This Tech Demo marked the first time that hematology measurements were successfully performed real-time in microgravity. Also modified and demonstrated was the reusable Handheld Electrolytes and Lab Technology for Humans (rHEALTH) ONE analyzer (rHEALTH, Bedford, MA), which uses flow cytometry and sheath-based hydrodynamic focusing methodologies. The rHEALTH ONE ISS Tech Demo in May 2022 demonstrated test results obtained in-flight matched those on the ground. NASA currently relies on crew self-reporting to manage and maintain medical inventory on ISS.The ability to maintain an accurate inventory becomes more critical during long duration missions since the crew will need to be increasingly autonomous in finding and utilizing medical items, including those scenarios when alternative treatments need to be considered due to limited or no resupply. HRP’s Medical Consumables Tracking (MCT) project was developed by ZIN Technologies, Inc. (Cleveland, OH), and demonstrated real-time tracking of medical supplies aboard the ISS between December 2016 and July 2018. The MCT system design utilized Radio Frequency Identification Device (RFID) technology to perform automated inventory and was installed in the Crew Health Care System (CHeCS) Resupply Stowage Rack (RSR). The challenge of limited shelf life, exacerbated by the lack of resupply opportunities, affects a plethora of medical system components including consumables, pharmaceuticals, and intravenous (IV) fluid. In 2010, ExMC funded ZIN Technologies, Inc. (Cleveland, OH), to develop the Intravenous Fluid Generation (IVGEN) system. IV fluids were successfully generated with IVGEN using the potable water supply on ISS during ISS Expedition 23. The XMIPT is in the process of developing a miniaturized version of the original IVGEN hardware for a future Tech Demo aboard the ISS. Current ISS medical operations rely heavily on preflight training and real-time remote guidance, both of which become impractical or impossible for exploration missions. The primary goal of the Autonomous Medical Officer Support (AMOS) Software Tech Demos on ISS was to confirm telemedical proof-of-concept for autonomous medical imaging in an operational setting. This novel software tool shifts emphasis from preflight training and real-time remote guidance to in-flight just-in-time instruction, a new and necessary paradigm for crew medical autonomy. AMOS introduces a novel, streamlined skill management concept for exploration missions featuring comprehensive training and guidance modules for ultrasound examinations using the ISS Ultrasound 2 (a modified GE Vivid-q™; General Electric HealthCare, Chicago, IL). With no prior crew training or remote guidance, two Tech Demos on the ISS (April 2020 and June 2022) resulted in high quality, clinically useful image sets. We will provide a review of historical, current, and planned medical devices and technologies considered for inclusion within future spaceflight medical systems and summarize hardware development activities and medical device tech demos conducted on the ISS.

Astronaut health and performance↗
NASA NTRSDate not supplied

FLASHFlux Working Group Status: Assessing FF NOAA-20 Products and Future Upgrades

The CERES Fast Longwave and SHortwave radiative Flux working provides low latency data products from the CERES measurements within about 5-6 days of real time. This presentation reviews progress made toward evaluating the current data products and shows some examples of users daily averaged data products. Since the last CERES Science Team meeting the FLASHFlux group has updated it's production to use the GEOS-IT reanalysis from the GMAO. In this presentation the comparisons to surface surface measurements are made through December 2023 constrasting old and new versions for the SSF and TISA products. Also, we provide an update on activities to replace the footprint fluxes and also update our current gridded global products with GEO observations. Lastly, present update plans for the next 6-9 months.

radiation budget↗
NASA NTRSDate not supplied

Intercomparing Open Source Surface Water Extent Mapping Products & Software Packages

The open source revolution of Earth Observation (EO) science has resulted in increased openness of EO data, workflows to transform that data into end products (e.g. surface water extent maps), and the products themselves. However, this revolution has oversaturated decision-makers with products that can give conflicting results. Thus, it is increasingly crucial for scientists to communicate their methodologies and assumptions so scientific products can be used accurately. Recognizing this challenge, SERVIR – a joint initiative between NASA, USAID, and geospatial organizations in Asia, Africa, and Latin America – is conducting a regional intercomparison of open source surface water extent products and packages. SERVIR’s Hindu Kush Himalaya and Southeast Asia “hubs” have developed satellite-based surface water mapping services involving customizable code packages that are operationally run at each hub. These services are regionally and locally tailored to inform specific decisions and early actions. Conversely, the scientific community has released surface water products that are global or near-global, but are not customizable. These packages and products employ different methodologies and sensors, causing decision-makers to evaluate trade-offs related to physical sensor characteristics (e.g. spectral, temporal, and spatial resolution, and latency). We will discuss the tradeoffs, strengths, and weaknesses of the sensor characteristics and methodologies associated with each product/package, and provide preliminary results of a validation effort intercomparing products/packages for case studies in South and Southeast Asia. Understanding the strengths and weaknesses of these products is crucial in both the aftermath of a flood event and in preparing for future floods.

Micky Maganini↗
NASA NTRSDate not supplied

Flight Test Evaluation of Automation-Induced Oscillations

Flight-test systems analysis techniques are applied to the case of aircraft automation-induced oscillations(AIO). Emerging technological advancements in flight control automation and artificial intelligence have created a need for evaluating the age-old aerial phenomenon of undesired aircraft oscillations. This paper is an overview on the study of AIO as interactions between human pilot, software engineer, and vehicle dynamics(e.g., latency) with the presence of winds aloft. Flight-test evaluation included a broad, non-comprehensive theory on cyclical and non-cyclical oscillations and a preliminary evaluation of the ecosystem from software engineer, airspace architect, and human test pilot.

David Zahn↗
NASA NTRS2024

Multidisciplinary Analytics, Visualization, and Reporting Interface for Integrated Countermeasures

Exploration class missions will have communication latency requiring crew members to make decisions more autonomously, with less support from ground personnel. Therefore, new software is needed to provide crew the ability to not only visualize their countermeasures data, but to also derive comprehensive, nuanced, and multidisciplinary insights regarding the health and performance informatics throughout a mission. The Multidisciplinary Analytics, Visualization, and Reporting Interface for Integrated Countermeasures (MAVRIIC) software seeks to establish a centralized approach to countermeasure data visualization that will facilitate a more holistic understanding of crew members' well-being and performance and enable the development of informed and autonomous decision-making support systems aligned with the evolving requirements of Exploration missions. The culmination of MAVRIIC phase 1 (end of FY23) marked the release of a full-stack, cloud-based ground tool displaying visualizations of in-flight exercise data, exercise ground testing, and exercise MEDB reports. Phase 2 of MAVRIIC (FY24) focuses on beginning the expansion of data contents to domains outside of exercise, including functional fitness, sensorimotor, food/nutrition, radiation, bone, and cardio/vision. Phase 3 and phase 4 will comprise enhanced analytics integration and initiation of flight tool development for infusion into the Artemis Program and eventually the Mars Transit Habitat.

Kent Lawrence Kalogera↗
NASA NTRS2024

Configuring and Testing Mesh Radios for Air-To-Ground Communications

The initial mesh network used to demonstrate a simple mesh network for the air-to-ground challenge will consist of 4 mesh radios purchased from DoodleLabs. The multiband radios operate in both the 915MHz and 2450MHz frequencies and can use Wi-Fi to connect to deployed devices. The DoodleLabs radios come preconfigured with unique IP addresses but to make sure of compatibility each radio will be assigned an IP address. For initial testing configurations will be changed using the built-in local web server interface that DoodleLabs radios provide. To access the webserver a computer connects to the radios broadcast Wi-Fi network using the default credentials, then enter the default IP address into a browser. This webserver will allow the user to monitor the radio performance and make changes to the various systems. The simple configuration page will allow an operator to make many of the initial changes to place each radio on the network and secure each connection with a new password. Further testing will then be performed by building out a simulated virtual network of 26 nodes and connecting the 4 DoodleLabs radios into this simulation. This will give insight into the radio’s performance in the larger system they will likely operate in given the project requirements. This testing will focus on multi-hop throughput, latency and the resiliency to packet loss.

Mesh Radio↗
NASA NTRS2024

Evaluating Precipitation Events Using GPM IMERG 30-Minute Near Real-Time Precipitation Estimates

Accurately detecting and estimating precipitation at near–real time (NRT) is of utmost importance for the early detection and monitoring of hydrometeorological hazards. The precipitation product, Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), provides NRT 0.1° and 30-min precipitation estimates across the globe with only a 4-h latency. This study was an evaluation of the GPM IMERG version 6 level-3 early run 30-min precipitation product for precipitation events from 2014 through 2020. The purpose of this research was to identify when, where, and why GPM IMERG misidentified and failed to detect precipitation events in California, Nevada, Arizona, and Utah in the United States. Precipitation events were identified based on 15-min precipitation from gauges and 30-min precipitation from the IMERG multisatellite constellation. False-positive and false-negative precipitation events were identified and analyzed to determine their characteristics. Precipitation events identified by gauges had longer duration and had higher cumulative precipitation than those identified by GPM IMERG. GPM IMERG had many false event detections during the summer months, suggesting possible virga event detection, which is when precipitation falls from a cloud but evaporates before it reaches the ground. The frequency and timing of the merged passive microwave (PMW) product and forward propagation were responsible for IMERG overestimating cumulative precipitation during some precipitation events and underestimating others. This work can inform experts that are using the GPM IMERG NRT product to be mindful of situations where GPM IMERG–estimated precipitation events may not fully resolve the hydrometeorological conditions driving these hazards.

Jessica R P Sutton↗
NASA NTRS2024

Oculometric Biomarkers of Visuomotor Deficits in Clinically Asymptomatic Patients With Systemic Lupus Erythematosus Undergoing Long-Term Hydroxychloroquine Treatment

Introduction: This study examines a set of oculomotor measurements, or “oculometric” biomarkers, as potential early indicators of visual and visuomotor deficits due to retinal toxicity in asymptomatic Systemic Lupus Erythematosus (SLE) patients on long-term hydroxychloroquine (HCQ) treatment. The aim is to identify subclinical functional impairments that are otherwise undetectable by standard clinical tests and to link them to structural retinal changes. Methods: We measured oculomotor responses in a cohort of SLE patients on chronic HCQ therapy using a previously established behavioral task and analysis technique. We also examined the relationship between oculometrics, OCT measures of retinal thickness, and standard clinical perimetry measures of visual function in our patient group using Bivariate Pearson Correlation and a Linear Mixed-Effects Model (LMM). Results: Significant visual and visuomotor deficits were found in 12 asymptomatic SLE patients on long-term HCQ therapy compared to a cohort of 17 age-matched healthy controls. Notably, six oculometrics were significantly different. The median initial pursuit acceleration was 22%, steady-state pursuit gain 16%, proportion smooth 7%, and target speed responsiveness 31% lower, while catch-up saccade amplitude was 46% and fixation error 46% larger. Excluding the two patients with diagnosed mild toxicity, four oculometrics, all but fixation error and proportion smooth, remained significantly impaired compared to controls. Across our population of 12 patients (24 retinae), we found that pursuit latency, initial acceleration, steady-state gain, and fixation error were linearly related to retinal thickness even when age was accounted for, while standard measures of clinical function (Mean Deviation and Pattern Standard Deviation) were not. Discussion: Our data show that specific oculometrics are sensitive early biomarkers of functional deficits in SLE patients on HCQ that could be harnessed to assist in the early detection of HCQ-induced retinal toxicity and other visual pathologies, potentially providing early diagnostic value beyond standard visual field and OCT evaluations.

eye movements↗
NASA NTRSDate not supplied

Integrated Multi-Satellite Retrievals for GPM (IMERG)

The Integrated Multi-satellitE Retrievals for GPM (IMERG) product from the U.S. Science Team of the NASA-JAXA Global Precipitation Measurement (GPM) mission provides global satellite precipitation estimates for a wide range of scientific research and societal applications. By adopting a constellation approach using low-Earth orbit passive microwave and geosynchronous-orbit infrared observations from domestic and international partners, IMERG is able to achieve a high resolution of 0.1° every half-hour globally, with three Runs to cater to applications with different latency requirements. With the completion of the reprocessing of the latest version, IMERG V07 now provides improved global satellite precipitation estimates for a period of more than 20 years. This presentation summarizes background on retrievals, the IMERG algorithm, and access to the data. As well, it showcases select results from the data, which might give participants ideas about how they can analyze the data themselves. The presentation ends with a prospectus for the timeline for the upcoming Version 08 and provides a list of references.

IMERG↗
NASA NTRSDate not supplied

Do Better Satellite Precipitation Algorithms Improve Landslide Hazard Assessment?

Satellites make it possible to estimate precipitation in near real time. Given the challenges of achieving global coverage by other means, these data are used widely. However, few systems for landslide hazard assessment rely on satellite precipitation estimates. This could be due in part to perceptions of accuracy, although latency, spatial resolution, and other factors may also be important. We test whether recent changes to data streams from the Global Precipitation Measurement mission (GPM) have improved its potential for use in landslide prediction. Specifically, we examine data produced by the Integrated Multi-satellitERetrievals for the GPM (IMERG) algorithm, which was upgraded to version 7 this year. IMERG relies upon other algorithms, including the Goddard Profiling Algorithm (GPROF) and the GPM Combined Radar-Radiometer Algorithm (CORRA). Many changes have been made during the switch from IMERG version 6 to version 7. These include upgrading CORRA and GPROF to version 7, to improve the accuracy of precipitation in frozen, mountainous, and coastal areas. The measured intensity of some storms has been enhanced with a new algorithm, the Scheme for Histogram Adjustment with Ranked Precipitation Estimates in the Neighborhood. Combined with many others, these changes to IMERG should improve its utility for landslide hazard assessment in a variety of contexts. To test this idea, we retrain the global Landslide Hazard Assessment for Situational Awareness (LHASA) model twice—first with data from IMERG version 6B and second with 7B. Since current daily rainfall is the most important variable in determining outcomes predicted by LHASA, it should reflect changes made to that input. First, we grid the landslides at a daily, thirty-arcsecond resolution. This serves as the response variable. At each of these sites current and antecedent rainfall are extracted, along with antecedent snow mass and soil moisture, slope, and PGA. In addition, one million grid cells are selected at random points to represent conditions under which landslides (probably) do not occur. After merging these data, we hold back 20% of the dataset for validation purposes and train a machine-learning model with the rest. We assess both the model’s overall ability to identify landslides and its ability to predict specific large landslide disasters.

Thomas A Stanley↗