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NASA NTRS2020

Acoustic Testing of the Bell 699 Rotor on the Tiltrotor Test Rig (TTR) in the National Full-Scale Aerodynamics Complex 40- by 80- Foot Wind Tunnel in Conversion and Airplane Configuration

The Tiltrotor Test Rig (TTR) provides new proprotor testing capabilities to the National Aeronautics and Space Administration (NASA) and the Department of Defense (DoD). A checkout test for the TTR with the 699 proprotor was performed in the National Full-Scale Aerodynamics Complex (NFAC) 40- by 80 Foot Wind Tunnel from 2017 to 2018. Four microphones were placed around the rotor to capture acoustic data. Revolution based acoustic data processing techniques are evaluated for appropriateness in both helicopter and airplane configurations. This paper presents the acoustic data acquired for the rotor in conversion and airplane configuration.

Shelts, Kelly↗

NASA NTRSDate not supplied

NASA’s NextGen Remote Sensing Instruments Have Arrived: Data Products For Studying Disease Vectors

Remote sensing can be used to measure, evaluate or estimate both the environment (state functions) and interfaces (processfunctions) defining vector habitats. The products of remote sensing can be integrated directly into the epidemiological equationsto significantly enhance our understanding of disease vector’s life cycles and habitats. The next generation of NASA’s remotesensing instruments which have become recently operational will provide a significant enhancement in our ability to studydisease vector’s life cycles and habitats. These instruments are on the International Space Station (ISS) and includeECOSTRESS, DESIS, and GEDI. ECOSTRESS is a 5 channel, thermal IR instrument with 70 m resolution and approximately1-5 day repeat cycle of day/night pairs. DESIS jointly developed by German Aerospace Center and Teledyne Brown Engineeringis a hyperspectral sensor system of 235 channels and 30 m resolution. DESIS data is only being acquired on demand. GEDI is ahigh-resolution laser ranger used for observing Earth’s forests and topography. NASA’s current ISS instrument configuration provides measurements of the critical environmental measures of environmentalstate functions important to vector & disease life cycles. Remote sensing data provide a spatial context and time series oflandscape scale process functions represented by land use mapping and measurements of ecological functions. Global publichealth is entering a new information age through the use of spatial models of disease vector/host ecologies driven by the use ofremotely sensed data to measure environmental and structural factors critical in determining disease vector habitats. In 2018, NASA initiated a new study for the Surface Biology and Geology (SBG) Designated Observable, identified in the 2018National Academies’ Decadal Survey entitled, “Thriving on Our Changing Planet: A Decadal Strategy for Earth Observationfrom Space.” (https://www.nap.edu/catalog/24938/thriving-on-our-changing-planet-a-decadal-strategy-for-earth) . The SBG isplanned to collect global remote sensing measurements using a hyperspectral spectrometer and multispectral thermal data. Thesedata sets will provide a significant enhancement in our ability to study disease vector’s life cycles and habitats globally. The 3sensors on the ISS provide precursor data to prepare the community for the application of future SBG data toward diseasestudies.

Disease Vectors↗

NASA NTRS2021

NOAA-20 VIIRS on-Orbit Calibration Improvements

The NOAA-20 (N-20) VIIRS has successfully operated for more than two years since its launch in November 2017. Shortly after completing its initial instrument check-outs and post-launch testing (PLT) activities, the N-20 VIIRS sensor data records (SDR) achieved the beta, provisional, and validated maturity status in January, February, and April 2018, respectively. In this paper, we briefly describe the instrument on-orbit operation and calibration activities, provide an overall assessment of its on-orbit performance, and discuss the methodologies developed to maintain and improve sensor calibration and data quality. As illustrated in this paper, the N-20 VIIRS continues to perform with excellent stability, allowing high-quality environmental data records (EDR) to be generated from its well-calibrated SDR.

NOAA-20↗

NASA NTRS2019

Slow Crack Growth of Boron Nitrides for Electric Propulsion Components

The Deep Space Gateway requires thruster systems to maintain spatial position. One control system being considered involves Hall thrusters. Historically, Hall thruster discharge channels have used several grades of hot-pressed hexagonal boron nitride. This study compliments data presented at ICACC (International Conference and Expo on Advanced Ceramics and Composites) 2018 and investigates the fracture toughness and slow crack growth parameters of several commercially available boron nitride grades including HP, M, M26, and Shapal Hi-M. The prior work revealed that some grades of BN absorb water and change strength thus presenting a philosophical conundrum on crack growth test methods. Advantages of different test methods will be discussed. The grades selected for this study are of interest because their available billet size is sufficient for Hall thruster discharge channels, or because they have heritage in Hall thruster applications. Ultimately, the data will be used to perform material selection, system design and reliability analyses.

Ceramics↗

NASA NTRSDate not supplied

Formaldehyde Column Density as an Indicator for Elevated Surface Ozone

Efforts to observe near-surface ozone directly from space are hindered by the limited sensitivity of ozone satellite retrievals to the lower troposphere. Formaldehyde (HCHO) column observations from the NASA DISCOVER-AQ campaign showed a strong relationship with surface ozone, particularly when biogenic volatile organic compounds (VOCs) were the dominant ozone precursor due to their strong temperature-driven variability. Both tropospheric ozone and HCHO are secondarily produced through the oxidation of VOCs and in regions where the main fate of RO2 is reaction with NO, thus formaldehyde and ozone are generally co-produced. This work explores the relationship between column formaldehyde and surface ozone using data from two air quality research campaigns, the Long Island Sound Tropospheric Ozone Study (LISTOS) in 2018 and the Korea U.S. - Air Quality (KORUS-AQ) campaign in 2016. These campaigns included HCHO column information from airborne in-situ profiling and remote sensing and ground-based Pandora spectrometers in combination with surface ozone monitors in each region. These data are used to further explore the HCHO-ozone relationship and its potential for identifying areas of elevated ozone using remote sensing or satellite observations of column HCHO alone. These two regions offer a valuable comparison given their different VOC mixtures and the higher NOx levels in Seoul that result in ozone titration effects. This work will also address the potential for this application with future geostationary satellite observations.

Laura Margaret Judd↗

NASA NTRSDate not supplied

NASA Life Sciences Portal (NLSP): Supporting Scientific Transparency and Reproducibility

NASA’s Life Sciences Ports (NLSP) serves the scientific community by providing curated data from space life science experiment. The Human Research Program (HRP) with the help of NLSP is currently transforming their life sciences data archive systems and processes to improve compliance with the FAIR principles [1]. Some of these improvements will at the same time support the twin pillars of Open Science [2]: transparency of methods and reproducibility of results. Scientific transparency is marked by the easily intelligible communication of what has been investigated: what were the procedures for collecting sample and the characteristics of samples collected? what kinds of measurements were made, what were the environmental conditions of the measurements? What were the analysis techniques of the collected data? Reproducibility of the results and findings from the investigation requires a high level of transparency for all but the simplest investigations; the slightest deviation in communicating and replicating complex experimental procedures or data analyses can often yield quite different data and even findings, thwarting their validation. One of the ways the NLSP is aiming to improve the communication of scientific information is through the use of ontology-driven metadata. Ontologies are powerful, graph-based knowledge representation structures, which can be leveraged to increase data interoperability, the area of the FAIR principles in which many data systems most lack compliance. Over the past decade, there has been a concerted effort in the biomedical community to develop modular and narrowly focused domain and application-specific ontologies in a common, open-source framework, the Open Biological and Biomedical Ontology (OBO) Foundry [3]. The open sharing and modular nature of this effort promises huge increases in harmonized data sharing for systems that leverage these models. Which is in line with the FAIR Data Principles of Findability, Accessibility, Interoperability, and Reuse for scientific data management and stewardship. 1. Wilkinson, M.D., et al., The FAIR Guiding Principles for scientific data management and stewardship. Sci Data, 2016. 3: p. 160018. 2. National Academies of Sciences, E. and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. 2018, Washington, DC: The National Academies Press. 232. 3. Smith, B., et al., The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol, 2007. 25(11): p. 1251-5.

Life Sciences data↗

NASA NTRS2018

NOAA-20 VIIRS Thermal Emissive Bands On-Orbit Performance

The VIIRS (Visible Infrared Imaging Radiometer Suite) instrument onboard the NOAA-20 satellite (launched on November 18, 2017) started to collect Earth-view data after its nadir door opened on December 13, 2017. Seven of the VIIRS bands, I4-5 and M12-16 are thermal emissive bands (TEBs), covering a spectral range from 3.6 to 12.5 meters. They began collecting valid data after the cold focal plane assembly (CFPA) cooled down to its nominal operating temperature on January 6, 2018. This paper will present the performance of each TEB, including calibration coefficients, noise equivalent differential temperature (NEdT), on-orbit calibration coefficient estimates from scheduled onboard blackbody warm-up and cool-down (WUCD) data, as well as related telemetry temperatures. Several methods are tested and compared in the WUCD data analysis for estimating the calibration coefficients. Based on the preliminary results, the NEdT of each band is well below the design specification and very close to that of the VIIRS onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite. The detector gains appear stable for bands on the short- and mid-wave infrared CFPA, whereas the detector gains have larger than expected degradation for bands on the long-wave infrared CFPA during the early mission. All TEB-related telemetry temperatures are stable. The on-orbit performance of NOAA-20 VIIRS TEB is compared with VIIRS onboard the SNPP.

Thermal Emissive Bands (TEB)↗

NASA NTRS2019

Electronic Departure Approval Requests in ATD-2 Daily Operations

The NASA Airspace Technology Demonstration 2 project is investigating Integrated Arrival-Departure-Surface air traffic management through progressive refinement of a surface air traffic management system fielded at Charlotte-Douglas International Airport. Among the areas under study are departure release-time approval request (APREQ) traffic management initiatives. Scheduling departures at downstream points and complying with approved departure release times helps flights fit smoothly into busy traffic streams. This paper presents a review of APREQ operations and compliance data from daily electronic APREQ negotiations over fourteen months beginning in January 2018. It describes APREQ-compliance improvements observed as the electronic negotiation process has matured and discusses contributing factors, including renegotiation of departure release times.

Call for release↗

NASA NTRSDate not supplied

Examining Circadian Disadvantages in the National Basketball Association's (NBA) Playoffs

Introduction: Prior research on travel in the National Basketball Association’s (NBA) regular season has shown that teams journeying west relative to their home base face circadian disadvantages for evening games, while those traveling east have advantages. The current study extends previous research by examining these effects within the NBA playoffs. We hypothesized that teams would have a greater circadian advantage during eastward compared to westward travel. Methods: In 2013, the NBA implemented a 7-game series playoff structure, in which teams play an alternating home/away 2-2-1-1-1 format for the Finals. Data for all 499 postseason games played during the 2013-14 to 2018-2019 seasons were collected from Basketball-Reference and FiveThirtyEight. We investigated the impact of direction of travel based on home base city (same time zone, westward, eastward) and time zones traveled on actual game outcomes, Elo rating differences (i.e., a team quality metric based on wins and losses), Elo predicted win probability, and team scoring for visiting teams. Results: Teams had lower Elo predicted win probabilities following 3-hour westward than same time zone and all eastward travel, while 3-hour eastward travel related to higher probabilities of winning compared to same time zone and all westward travel (p < .02, d > .95). Teams travelling westward with 2-hour time changes lost significantly more games than those experiencing 1-hour westward (p = .04, OR = 2.45), 1-hour eastward (p = .05, OR = 2.34), and 3-hour eastward changes (p = .02, OR = 4.68). Scoring was significantly higher following eastward travel compared to both westward (p = .001, d = 0.60) and same time zone travel (p = .003, d = 0.44). There were no statistically clear differences in team quality based on overall direction of travel or number of time zones traveled, and game outcomes based on direction of travel (p > .05). Conclusion: Overall direction of travel was related to team scoring, while number of time zones traveled was associated with Elo predicted win probability and game outcomes. Generally, teams travelling eastward and within the same time zone gained an advantage over those travelling westward. Adjustment to travel and time zone changes appear to influence certain aspects of in-game performances and outcomes in the NBA playoffs.

circadian misalignment↗

NASA NTRS2021

The AOD Sensitivity Comparison between MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) and Standard MODIS Surface Reflectance

This study compares the Multi-Angle Implementation of Atmospheric Correction (MAIAC) and standard MODIS surface reflectance (SR) products (MOD09)for various aerosol optical depth (AOD) levels. Data from one MODIS tile in northern China for the whole year 2018 is compared. The results reveal that MAIAC SR has good stability for the full range of AOD for which SR is reported, whereas MOD09 SR shows increasing high bias with AOD increases. The cross-comparison of spectral characteristics between MAIAC SR and MOD09 SR shows a systematic MAIAC-MOD09 difference increasing from NIR to Blue. This pattern is consistent with the bias caused by Lambertian assumption used in MOD09 SR algorithm.

MAIAC↗

NASA NTRS2024

QSF18 Nonresponse Follow-up Reminders Survey Data Supplemental File

This minimal data set contains anonymized study subject identifier (PARTICIPANT_ID) and non-response follow up type (group) from the single events surveys conducted during the Quiet Supersonic Flights 2018 risk reduction study in Galveston, Texas, in November 2018. Nonresponse follow up groups and procedures are defined and discussed in Page et al. 2020, Section 6.2 (NASA/CR-2020-220589/Volume I). The data cleaning conventions are consistent with the assumptions of Lee et al. in the treatment of the single events survey data (Lee, Rathsam, Wilson (2020). Journal of the Acoustical Society of America. 147, doi: 10.1121/10.0001021). Filename: reminder_groups.csv Dimensions: 371 rows by 2 columns. Variables: PARTICIPANT_ID, group PARTICPANT_ID: numeric (integer, six digits) group: character string taking one of four values ('Email - No Reminder'; 'Email - Reminder'; 'Text - No Reminder'; 'Text - Reminder').

sample survey↗

NASA NTRS2024

The Martian Ionospheric Response to the Co-Rotating Interaction Region That Caused the Disappearing Solar Wind Event at Mars

An unusually low density solar wind event was observed in December 2022 moving past both Earth and Mars. The source was traced back to a coronal hole and active region on the Sun's surface. The resulting solar wind lead to the development of a co-rotating interaction region (CIR) and trailing rarefaction region that lasted for multiple solar rotations. Within this structure, the solar wind conditions, including density, velocity, and magnetic field magnitude and orientation drastically changed. In this study we analyze the response of the Martian ionosphere using MAVEN data to these changing solar wind conditions. The low density solar wind region associated with the December event resulted in the expansion of the Martian ionospheric boundaries. We show that the ion composition boundary (ICB) is located at extreme altitudes that are beyond previously observed locations from the MAVEN mission between 2015 and 2018. Furthermore, the boundary between shocked solar wind and the Martian ionosphere identified using electron and ion data moved together on the dayside of the planet with the changing solar wind conditions. However, at the flank region these boundaries do not move together, and we show here that the decoupling of the two boundaries may be the result of a change in the interplanetary magnetic field azimuthal angle.

S. R. Shaver↗

NASA NTRS2018

Improving Brightness Temperature Measurements Near Coastal Areas

The Soil Moisture Active Passive (SMAP) mission was designed to acquire and combine L-band radar and radiometer measurements for the estimation of soil moisture with 4% volumetric accuracy away from coastal zones. In regions near the coast or near inland bodies of water, the SMAP footprint contains land and water, resulting in errors in the soil moisture estimation. In this paper, we address the effort to extract the brightness temperature related to the land fraction or water fraction (depending on the center of the footprint location) from the affected SMAP measurements. We evaluate the performance of our algorithm over simulated data. We then show results over real data. The new SMAP upgraded product is expected to be delivered on April 2018.

Entekhabi, Dara↗

NASA NTRS2021

Validation of SMAP L2 passive-only soil moisture products using upscaled in situ measurements collected in Twente, the Netherlands

The Twente region in the east of the Netherlands has a network with twenty soil monitoring stations that has been utilized for validation of the Soil Moisture Active/Passive (SMAP) passive-only soil moisture products. Over the period from April 2015 until December 2018, seven stations covered by the SMAP reference pixels 15 have fairly complete data records. Spatially distributed soil moisture simulations with the Dutch national hydrological model have been utilized for the development of upscaling functions to translate the spatial mean of point measurements to the domain of the SMAP reference pixels. The native and upscaled spatial soil moisture means computed using the in-situ measurements have been adopted as references to assess the performance of the SMAP i) Single Channel Algorithm at Horizontal Polarization (SCA-H), ii) Single Channel Algorithm at Vertical Polarization (SCA-V), and iii) Dual Channel Algorithm (DCA) soil moisture estimates. In the case of the Twente network it was found that the SCA-V soil moisture retrieved SMAP observations collected in the afternoon had the best agreement with the native spatial mean leading to an unbiased Root Mean Squared Error (uRMSE) of 0.059 m3 m-3, whereas for the upscaled in-situ references primarily larger biases were found. These error levels are larger than the mission’s target accuracy of 0.04 m3 m-3, which can be attributed to large over- and underestimation errors (>0.08 m3 m-3) in particular at the end of dry spells and during freezing, respectively. The strong vertical dielectric gradients associated with rapid soil freezing and wetting causes the disparity in soil depth characterized by SMAP and in situ that leads to the large mismatches. Once filtered for frozen conditions and antecedent rainfall the uRMSE improves to 0.043 m3 m-3.

Rogier van der Velde↗

NASA NTRS2020

The Next Generation of L Band Radiometry: User’s Requirements and Technical Solutions

After almost 10 years in operation (SMOS- Aquarius - SMAP) the very high potential of L band radiometry is clearly demonstrated. Several applications are already operational (assimilation at ECMWF, for hurricanes, for sea ice etc.) so it is crucial to maintain such measurements. To do so while satisfying the current missions specifications is also of prime importance. Degrading spatial resolution is thus a significant step back which will impact science and applications). These missions are now getting older and the goal of the study presented in this paper is to assess which planned mission could fulfill the requirements to ensure data continuity. For this purpose, an extensive users’ requirements study was performed in 2018-2019 assessing what would be required in the near future as well as when L band radiometry was absolutely necessary to satisfy the requirements. From the gathered results a cluster analysis was performed and the only.

Yann H Kerr↗

NASA NTRS2018

Soil Moisture Active Passive (SMAP) Project Assessment Report for Version 4 of the L4_SM Data Product

This report provides an assessment of Version 4 of the SMAP Level 4 Surface and Root Zone Soil Moisture (L4_SM) product, released on 14 June 2018. The assessment includes comparisons of L4_SM soil moisture and temperature estimates with in situ measurements from core validation sites and sparse networks. The assessment further includes a global evaluation of the internal diagnostics from the ensemble-based data assimilation system that is used to generate the L4_SM product, including observation-minus-forecast (O-F) brightness temperature residuals and soil moisture analysis increments.Together, the core validation site comparisons and the statistics of the assimilation diagnostics areconsidered primary validation methodologies for the L4_SM product. Comparisons against in situ measurements from regional-scale sparse networks are considered a secondary validation methodology because such in situ measurements are subject to upscaling errors from the point-scale to the grid-cell scale of the data product.The Version 4 L4_SM product benefits from an improved land surface modeling system and from retrospective surface meteorological forcing data that are as consistent as possible with the present-day datain terms of their climatology. Specifically, the model changes include revised parameters and parameterizations for (i) the surface energy balance, (ii) recharge from below of the model's surface excess reservoir, and (iii) the snow depletion curve. Updated ancillary inputs include improved datasets for landcover, topography, and vegetation height. The Version 4 algorithm further includes a revised approach to precipitation corrections that improves the precipitation climatology in Africa and the high-latitudes. Moreover, for system calibration the model is forced retrospectively with MERRA-2 reanalysis data, which are more consistent with the near-real time GEOS forward processing (FP) data used during the SMAP period than the retrospective GEOS data that were available for previous L4_SM versions. An analysis of the time-average surface and root zone soil moisture shows that the global pattern ofarid and humid regions is captured by the Version 4 L4_SM estimates. Owing to the changes in the landsurface modeling system, surface soil moisture is typically drier by several volumetric percent in Version 4 compared to Version 3, whereas root zone soil moisture is wetter in Version 4 in some regions and drierin others. Because of these climatological differences, the Version 3 and Version 4 products should not be combined into a single dataset for use in applications.Results from the core validation site comparisons indicate that Version 4 of the L4_SM data product meets the self-imposed L4_SM accuracy requirement, which is formulated in terms of the RMSE after removal of the long-term mean difference (ubRMSE). The overall ubRMSE of the 3-hourly L4_SM dataat the 9 km scale is 0.039 m3 m-3 for surface soil moisture and 0.029 m3 m-3 for root zone soil moisture,below the 0.04 m3 m-3 requirement. The L4_SM estimates are an improvement over estimates from a model-only Nature Run version 7.2 (NRv7.2), which demonstrates the beneficial impact of the SMAP brightness temperature data. Overall, L4_SM surface and root zone soil moisture estimates are more skillful than NRv7.2 estimates, with statistically significant improvements at the 5% level for surface soil moisture R and anomaly R values. Results from comparisons of the L4_SM product to i

Reichle, Rolf H.↗

NASA NTRS2019

ACC Subduction by Mesoscales

The mesoscale contribution to Subduction in the Southern Ocean was recently studied by Salle'e and Rintoul (2011, SR) using the following mesoscale model. The adiabatic A-regime was modeled with the GM stream function, the diabatic D-regime was modeled with tapering functions,the D-A interface was taken to be at the mixed layer depth and the mesoscale diffusivity was either a constant or given by a 2D model. Since the resulting subductions were an order of magnitude smaller than the data of ±200 m/yr (Mazloff et al., 2010), SR showed that if instead of the above model-dependent mesoscale diffusivities, they employed the ones by Salle'e et al. (2008) from surface drifter observations, the subductions compared significantly better with the data. On those grounds, SR suggested a tenfold increase of the diffusivity. In this work, we suggest that since the mesoscale diffusivity is but one component of a muc large mesoscale parameterization, one should first assess the latter's overall performance followed by the assessment of the predicted ACC subduction. We employ the mesoscale model formulated31 in Canuto et al. (2018; 2019, that includes recent theoretical and observational advances and that was assessed against a variety of data including the output of 17 other OGCMs. The ACC diffusivities compare well with drifter data by Salle'e et al. (2008) and the ACC subduction rates are in agreement with the data.

V M Canuto↗

NASA NTRS2021

ICESat-2 Atmospheric Channel Description, Data Processing and First Results

The Advanced Topographic Laser Altimeter System (ATLAS) was launched aboard the Ice Cloud and land-Elevation Satellite-2 (ICESat-2) satellite in September 2018. ATLAS is a single wavelength (532 nm) lidar system designed to acquire high resolution measurements of the earth's surface while also obtaining atmospheric backscatter from molecules, clouds, and aerosols. Because ATLAS is optimized for altimetry, the atmospheric data acquired is unique in many respects and requires non-standard analysis techniques. For example, the high repetition rate laser limits the vertical extent of the profiles to just 14 km and causes atmospheric scattering from above 15 km to be added to the scattering in the lower 0–14 km profile. In addition, the limited vertical range of the acquired profiles renders it difficult to compute the magnitude of the solar background and hinders the application of standard calibration techniques. Despite these limitations, methods have been developed to successfully produce data products that have value to the atmospheric community for cloud and aerosol research and are currently available at the National Snow and Ice Data Center (NSIDC). In this paper we describe the ICESat-2 atmospheric channel and the methods used to process the ATLAS raw photon count data to obtain calibrated backscatter and higher level products such as layer heights and type, blowing snow, column optical depth and apparent surface reflectance.

Stephen P Palm↗