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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17

Clouds Around the World: How a Simple Citizen Science Data Challenge Became a Worldwide Success

Citizen science is often recognized for its potential to directly engage the public in science, and is uniquely positioned to support and extend participants’ learning in science. In March 2018, the Global Learning and Observations to Benefit the Environment (GLOBE) Program, NASA’s largest and longest-lasting citizen science program about Earth, organized a month-long event that asked people around the world to contribute daily cloud observations and photographs of the sky (15 March–15 April 2018). What was considered a simple engagement activity turned into an unprecedented worldwide event that garnered major public interest and media recognition, collecting over 55,000 observations from 99 different countries, in more than 15,000 locations, on every continent including Antarctica. The event was called the “Spring Cloud Challenge” and was created to 1) engage the general public in the scientific process and promote the use of the GLOBE Observer app, 2) collect ground-based visual observations of varying cloud types during boreal spring, and 3) increase the number and locations of ground-based visual cloud observations collocated with cloud-observing satellites. The event resulted in roughly 3 times more observations than during the historic and highly publicized 2017 North American total solar eclipse. The dataset also includes observations over the Drake Passage in Antarctica and reports from intense Saharan dust events. This article describes how the challenge was crafted, outreach to volunteer scientists around the world, details of the data collected, and impact of the data.

GLOBE↗

A Statistical Selection Strategy for Normalization Procedures in LC-MS Proteomics Experiments through Dataset Dependent Ranking of Normalization Scaling Factors

Quantification of LC-MS peak intensities assigned during peptide identification in a typical comparative proteomics experiment will deviate from run-to-run of the instrument due to both technical and biological variation. Thus, normalization of peak intensities across a LC-MS proteomics dataset is a fundamental step in pre-processing. However, the downstream analysis of LC-MS proteomics data can be dramatically affected by the normalization method selected . Current normalization procedures for LC-MS proteomics data are presented in the context of normalization values derived from subsets of the full collection of identified peptides. The distribution of these normalization values is unknown a priori. If they are not independent from the biological factors associated with the experiment the normalization process can introduce bias into the data, which will affect downstream statistical biomarker discovery. We present a novel approach to evaluate normalization strategies, where a normalization strategy includes the peptide selection component associated with the derivation of normalization values. Our approach evaluates the effect of normalization on the between-group variance structure in order to identify candidate normalization strategies that improve the structure of the data without introducing bias into the normalized peak intensities.

60 APPLIED LIFE SCIENCES↗

Pulsed laser generation of ultrasound in a metal plate between the melting and ablation thresholds

The generation of ultrasound in a metal plate exposed to nanosecond pulsed laser heating, sufficient to cause melting but not ablation, is treated. Consideration is given to the spatial and temporal profiles of the laser pulse, penetration of the laser beam into the sample, the evolution of the melt pool, and thermal conduction in the melt and surrounding solid. The excitation of the ultrasound takes place over a few nanoseconds, and occurs predominantly within the thermal diffusion length of a micron or so beneath the surface. Because of this, the output of the thermal simulations can be represented as axially symmetric transient radial and normal surface force distributions. The epicentral displacement response at the opposite surface to these forces is obtained by two methods, the one based on the elastodynamic Green’s functions for plate geometry determined by the Cagniard generalized ray method, and the other using a finite element numerical method. The two approaches are in very close agreement. Numerical simulations are reported of the epicentral displacement response of a 3.12mm thick tungsten plate irradiated with a 4 ns pulsed laser beam with Gaussian spatial profile, at intensities below and above the melt threshold. Comparison is made between results obtained using available temperature dependent thermophysical data, and room temperature materials constants except near the melting point.

36 MATERIALS SCIENCE↗

Flat-histogram extrapolation as a useful tool in the age of big data

In this work, we review recent work by the authors to revisit the concept of extrapolating thermodynamic properties of classical systems using statistical mechanical principles. Specifically, we discuss how the combination of these principles with biased sampling techniques enables the prediction of free energy landscapes and other detailed information, such as structural properties, of the system in question. Remarkably accurate estimates of physical properties across a broad range of conditions have been achieved using this approach, greatly reducing the number of simulations needed to explore a given system's behaviour. While approximate, these extrapolations significantly amplify the amount of reasonably accurate information that can be extracted from simulations enabling a small set of them to feed data-intensive regression algorithms such as neural networks. Thus, this extrapolation methodology represents a useful tool for performing tasks such as high-throughput screening of physical properties, optimising force field parameters, exploring equilibrium phase behaviour, and enabling theory-guided data science for these systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Predictions for microlensing planetary events from core accretion theory

We conduct the first microlensing simulation in the context of a planet formation model. The planet population is taken from the Ida and Lin core accretion model for 0.3 M {sub ☉} stars. With 6690 microlensing events, we find that for a simplified Korea Microlensing Telescopes Network (KMTNet), the fraction of planetary events is 2.9%, out of which 5.5% show multiple-planet signatures. The numbers of super-Earths, super-Neptunes, and super-Jupiters detected are expected to be almost equal. Our simulation shows that high-magnification events and massive planets are favored by planet detections, which is consistent with previous expectation. However, we notice that extremely high-magnification events are less sensitive to planets, which is possibly because the 10 minute sampling of KMTNet is not intensive enough to capture the subtle anomalies that occur near the peak. This suggests that while KMTNet observations can be systematically analyzed without reference to any follow-up data, follow-up observations will be essential in extracting the full science potential of very high magnification events. The uniformly high-cadence observations expected for KMTNet also result in ∼55% of all detected planets not being caustic crossing, and more low-mass planets even down to Mars mass being detected via planetary caustics. We also find that the distributions of orbital inclinations and planet mass ratios in multiple-planet events agree with the intrinsic distributions.

79 ASTRONOMY AND ASTROPHYSICS↗

Atmospheric Ion Composition, SGP, April-May 2023

These files contain select ion count rates measured by an atmospheric pressure interface time-of-flight mass spectrometer (APi-ToF) at the Atmospheric Radiation Measurement Southern Great Plains site from April 28, 2023 to May 31, 2023. Files are in ICARTT format. The APi-ToF measures the chemical composition of naturally charged ions using mass spectrometry. Due to the nature of the measurements, time-series data are non-quantitative. This dataset contains time-series information for the ions that are typically the most intense ions observed.

54 ENVIRONMENTAL SCIENCES↗

COURAGE S7 TBS AIRBORNE SONIC WIND AND TURBULENCE DATA

These data were collected with airborne wind instrumentation booms onboard the TBS at CoURAGE S7 during February 2025. The data include 60 Hz wind speed, component wind speed, wind direction, TKE, TI, and altitude measurements.

54 ENVIRONMENTAL SCIENCES↗

BNF M1 TBS AIRBORNE SONIC WIND AND TURBULENCE DATA

These data were collected with airborne wind instrumentation booms onboard the TBS at BNF M1. The data include 60 Hz wind speed, component wind speed, wind direction, TKE, TI, and altitude measurements.

54 ENVIRONMENTAL SCIENCES↗

Cassini Camera Contamination Anomaly: Experiences and Lessons Learned

We discuss the contamination 'Haze' anomaly for the Cassini Narrow Angle Camera (NAC), one of two optical telescopes that comprise the Imaging Science Subsystem (ISS). Cassini is a Saturn Orbiter with a 4-year nominal mission. The incident occurred in 2001, five months after Jupiter encounter during the Cruise phase and ironically at the resumption of planned maintenance decontamination cycles. The degraded optical performance was first identified by the Instrument Operations Team with the first ISS Saturn imaging six weeks later. A distinct haze of varying size from image to image marred the images of Saturn. A photometric star calibration of the Pleiades, 4 days after the incident, showed stars with halos. Analysis showed that while the halo's intensity was only 1 - 2% of the intensity of the central peak of a star, the halo contained 30 - 70% of its integrated flux. This condition would impact science return. In a review of our experiences, we examine the contamination control plan, discuss the analysis of the limited data available and describe the one-year campaign to remove the haze from the camera. After several long conservative heating activities and interim analysis of their results, the contamination problem as measured by the camera's point spread function was essentially back to preanomaly size and at a point where there would be more risk to continue. We stress the importance of the flexibility of operations and instrument design, the need to do early infight instrument calibration and continual monitoring of instrument performance.

Cassini↗

Impact of Canadian Wildfires on Mid Atlantic’s Region Air Quality: An Analysis Using ASDC Data

Wildfires pose a growing concern in North America due to their harmful impacts on air quality and public health, with increased wildfire activity in recent years leading to widespread smoke plumes that can transcend borders. The exposure of New York City (NYC), the most populous city in North America, to Canadian wildfire smoke highlights the substantial implications for public health and urban environments. To better understand the impact of Canadian wildfires on air quality in NYC, satellite data from the NASA Atmospheric Science Data Center (ASDC) at Langley Research Center, along with ground-based measurements and atmospheric modeling results, are analyzed. We examine concentrations of atmospheric aerosols—particularly PM2.5 particulate matter originating from Canadian wildfires—their dispersion patterns, and the duration and intensity of smoke events impacting NYC. Data from multiple satellites, such as those from the Earth Polychromatic Imaging Camera (EPIC), are synergistically used to identify regions affected by wildfires and estimate aerosol loading. Ground-based measurements, including data from air quality monitoring stations, provide localized information for validation and calibration purposes. The findings of this study contribute to our understanding of the impact of Canadian wildfires on NYC's air quality and emphasize the importance of monitoring and prediction of transboundary smoke events using data synthesized from multiple sources, such as those provided by the ASDC. This information is crucial for policymakers, public health officials, and residents in affected areas to develop effective strategies for mitigating the health risks associated with wildfire smoke and improving air quality during wildfire seasons. The utilization of ASDC data in this research highlights the critical role of atmospheric remote sensing in addressing the challenges posed by wildfires and their consequences on regional scales.

Ingrid Garcia-Solera↗

Analyzing the Impact of Canadian Wildfires on Air Quality in the U.S. Mid-Atlantic: with Data and Tools from NASA’s Atmospheric Sciences Data Center

Wildfires pose a growing concern in North America due to their harmful impacts on air quality and public health, with increased wildfire activity in recent years leading to widespread smoke plumes that can transcend borders. The exposure of New York City (NYC), the most populous city in North America, to Canadian wildfire smoke highlights the substantial implications for public health and urban environments. To better understand the impact of Canadian wildfires on air quality in NYC, satellite data from the NASA Atmospheric Science Data Center (ASDC) at Langley Research Center, along with ground-based measurements and atmospheric modeling results, are analyzed. We examine concentrations of atmospheric aerosols—particularly PM2.5 particulate matter originating from Canadian wildfires—their dispersion patterns, and the duration and intensity of smoke events impacting NYC. Data from multiple satellites, such as those from the Earth Polychromatic Imaging Camera (EPIC), are synergistically used to identify regions affected by wildfires and estimate aerosol loading. Ground-based measurements, including data from air quality monitoring stations, provide localized information for validation and calibration purposes. The findings of this study contribute to our understanding of the impact of Canadian wildfires on NYC's air quality and emphasize the importance of monitoring and prediction of transboundary smoke events using data synthesized from multiple sources, such as those provided by the ASDC. This information is crucial for policymakers, public health officials, and residents in affected areas to develop effective strategies for mitigating the health risks associated with wildfire smoke and improving air quality during wildfire seasons. The utilization of ASDC data in this research highlights the critical role of atmospheric remote sensing in addressing the challenges posed by wildfires and their consequences on regional scales.

Ingrid Garcia-Solera↗

Soil Moisture Active Passive Mission L4_C Data Product Assessment (Version 2 Validated Release)

The SMAP satellite was successfully launched January 31st 2015, and began acquiring Earth observation data following in-orbit sensor calibration. Global data products derived from the SMAP L-band microwave measurements include Level 1 calibrated and geolocated radiometric brightness temperatures, Level 23 surface soil moisture and freezethaw geophysical retrievals mapped to a fixed Earth grid, and model enhanced Level 4 data products for surface to root zone soil moisture and terrestrial carbon (CO2) fluxes. The post-launch SMAP mission CalVal Phase had two primary objectives for each science product team: 1) calibrate, verify, and improve the performance of the science algorithms, and 2) validate accuracies of the science data products as specified in the L1 science requirements. This report provides analysis and assessment of the SMAP Level 4 Carbon (L4_C) product pertaining to the validated release. The L4_C validated product release effectively replaces an earlier L4_C beta-product release (Kimball et al. 2015). The validated release described in this report incorporates a longer data record and benefits from algorithm and CalVal refinements acquired during the SMAP post-launch CalVal intensive period. The SMAP L4_C algorithms utilize a terrestrial carbon flux model informed by SMAP soil moisture inputs along with optical remote sensing (e.g. MODIS) vegetation indices and other ancillary biophysical data to estimate global daily net ecosystem CO2 exchange (NEE) and component carbon fluxes for vegetation gross primary production (GPP) and ecosystem respiration (Reco). Other L4_C product elements include surface (10 cm depth) soil organic carbon (SOC) stocks and associated environmental constraints to these processes, including soil moisture and landscape freeze/thaw (FT) controls on GPP and respiration (Kimball et al. 2012). The L4_C product encapsulates SMAP carbon cycle science objectives by: 1) providing a direct link between terrestrial carbon fluxes and underlying FT and soil moisture constraints to these processes, 2) documenting primary connections between terrestrial water, energy and carbon cycles, and 3) improving understanding of terrestrial carbon sink activity in northern ecosystems. There are no L1 science requirements for the L4_C product; however self-imposed requirements have been established focusing on NEE as the primary product field for validation, and on demonstrating L4_C accuracy and success in meeting product science requirements (Jackson et al. 2012). The other L4_C product fields also have strong utility for carbon science applications; however, analysis of these other fields is considered secondary relative to primary validation activities focusing on NEE. The L4_C targeted accuracy requirements are to meet or exceed a mean unbiased accuracy (ubRMSE) for NEE of 1.6 g C/sq m/d or 30 g C/sq m/yr, emphasizing northern (45N) boreal and arctic ecosystems; this is similar to the estimated accuracy level of in situ tower eddy covariance measurement-based observations (Baldocchi 2008).

Cal/Val↗

FIRE Science Results 1988

FIRE (First ISCCP Regional Experiment) is a U.S. cloud-radiation program that seeks to address the issues of a basic understanding and parameterizations of cirrus and marine stratocumulus cloud systems and ISCCP data products. The papers describe research analysis of data collected at the 1986 Cirrus Intensive Field Observations (IFO), the 1987 Marine Stratocumulus IFO, and the Extended Time Observations. The papers are grouped into sessions on satellite studies, lidar/radiative properties/microphysical studies, radiative properties, thermodynamic and dynamic properties, case studies, and large scale environment and modeling studies.

Mcdougal, David S.↗

Raw Lidar and Camera Data Synchronized with Precipitation and Present Weather Data

As part of the sensor characterization task of the SMART 2.0 project, this dataset includes raw data from three spinning lidars ([Ouster OS2-128](https://ouster.com/products/scanning-lidar/os2-sensor/), [Velodyne Puck (VLP-16)](https://velodynelidar.com/products/puck/), and [Velodyne Ultra Puck (VLP-32)](https://velodynelidar.com/products/ultra-puck/)), one camera ([Mako G-319](https://www.alliedvision.com/en/camera-selector/detail/mako/g-319/)), and one present weather sensor ([Vaisala FD-70](https://www.vaisala.com/en/products/weather-environmental-sensors/forward-scatter-fd70)). All data were synchronized, with the log start time indicated in the file name (HHMMSS). The data can be filtered by date, log time (HHMMSS), sensor, frame ID, and weather classification. These data were gathered statically at the Argonne Testbed for Multiscale Observational Science (ATMOS). Two target stop signs were placed in view of the sensors to contribute a target for comparing sensor data under different conditions. The weather data for each day are stored in netCDF “.nc” files. The lidar data contain the X, Y, Z, intensity, reflectivity, and ring from Ouster OS2-128 rev6, Velodyne VLP-16, and Velodyne VLP-32 lidars. ![raw lidar image](LiDAR_pointcloud_ATMOS.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

BOREAS RSS-20 POLDER C-130 Measurements of Surface BRDF

This Boreal Ecosystem-Atmosphere Study (BOREAS) Remote Sensing Science (RSS)-20 data set contains measurements of surface bidirectional reflectance distribution function (BRDF) made by the polarization and Directionality of Earth reflectances (POLDER) instrument over several surface types (pine, spruce, fen) of the BOREAS southern study area (SSA) during the 1994 intensive field campaigns (IFCs). Single-point BRDF values were acquired either from the NASA Ames Research Center (ARC) C-130 aircraft or from a NASA Wallops Flight Facility (WFF) helicopter. A related data set collected from the helicopter platform is available as is POLDER imagery acquired from the C-130. The data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884) or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Leroy, Marc↗

A Case Study Comparing Citizen Science Aurora Data with Global Auroral Boundaries Derived from Satellite Imagery and Empirical Models

Aurorasaurus is a citizen science project that offers a new, global data source consisting of ground-based reports of the aurora. For this case study, aurora data collected during the 17-18 March 2015 geomagnetic storm are examined to identify their conjunctions with Defense Meteorological Satellite Program (DMSP) satellite passes over the high latitude auroral regions. This unique set of aurora data can provide ground-truth validation of existing auroral precipitation models. Particularly, the solar wind driven, Oval Variation, Assessment, Tracking, Intensity, and Online Nowcasting (OVATION) Prime 2013 (OP-13) model and a Kp-dependent model of Zhang-Paxton (Z-P) are utilized for our boundary validation efforts. These two similar models are compared for the first time. Global equatorward auroral boundaries are derived from the OP 13 model and the DMSP Special Sensor Ultraviolet Spectrographic Imager (SSUSI) far ultraviolet (FUV) data using the Z-P model at a fixed flux level of 0.2 erg cm(exp -2)s(exp -1). These boundaries are then compared with citizen science reports as well as with each other. Even though there are some large differences between the global boundaries for a few cases, the average difference is about 1.5 deg in geomagnetic latitude, with OP-13 being equatorward of Z-P model. When these boundaries are compared with each other as a function of local time, no clear overall trend as a function of local time was observed. It is also found that the ground based reports are more consistent with the predictions of the OP-13 model.

Kosar, Burcu C.↗

Raman spectroscopy of glasses in the As-Te system

For the first time, the Raman spectra of As{sub x}Te{sub 1-x} glasses, 0.2{<=}x{<=}0.6, have been measured over the entire glass-forming range. The spectra exhibit three broad spectral features attributed to vibrations of structural units having Te-Te, As-Te and As-As bonds. The observed chemical disorder in the glasses is discussed on the basis of partial bond fractions derived from the integrated intensity of the Raman modes. The underlying structural model suggests a dissociation of AsTe- or As{sub 2}Te{sub 3}-related units in the glass melt. The spectra of glasses quenched from different temperatures, as well as those of the annealed vitreous alloys, are consistent with predictions of the model. - Graphical abstract: Raman spectra of the As{sub x}Te{sub 1-x} glasses (0.2{<=}x{<=}0.4 and 0.4{<=}x{<=}0.6). Fractional concentrations of Te-Te, As-Te and As-As bonds in the As{sub x}Te{sub 1-x} glasses calculated using experimental Raman data. The solid lines represent predictions of the dissociation model assuming that the main chemically ordered structural units are related to AsTe. Highlights: Black-Right-Pointing-Pointer For the first time, the Raman spectra of As{sub x}Te{sub 1-x} glasses, 0.2{<=}x{<=}0.6, were measured. Black-Right-Pointing-Pointer The partial bond fractions were derived from the integrated intensity of the Raman modes. Black-Right-Pointing-Pointer An empirical quantitative approach to the Raman data was proposed for the reaction modeling.

36 MATERIALS SCIENCE↗

Modern Computational Techniques for the HMMER Sequence Analysis

This paper focuses on the latest research and critical reviews on modern computing architectures, software and hardware accelerated algorithms for bioinformatics data analysis with an emphasis on one of the most important sequence analysis applications—hidden Markov models (HMM). We show the detailed performance comparison of sequence analysis tools on various computing platforms recently developed in the bioinformatics society. The characteristics of the sequence analysis, such as data and compute-intensive natures, make it very attractive to optimize and parallelize by using both traditional software approach and innovated hardware acceleration technologies.

59 BASIC BIOLOGICAL SCIENCES↗