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At least 271 records · Page 15

Challenges in Transitioning Research Data to Operations: The SPoRT Paradigm

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 and planned NPP, 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 volume 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.

Jedloved, Gary J.↗

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.↗

Adaptive Wavelength Scanning Lidar (AWSL) for 3D Mapping from Space

We present the design and performance of an adaptive wavelength scanning lidar (AWSL) for highly efficient mapping from low Earth orbit (LEO). Mapping is accomplished by steering a laser beam across 1,200 resolvable spots using wavelength tuning and grating dispersion. Any subset of these 1,200 spots can be selected by wavelength switching. The design is validated with an 1550-nm prototype using a fast wavelength-tuned (500-kHz) pulsed (2-ns) fiber laser with the beam dispersed by gratings for beam steering. Reflected pulses are detected with an eight-pixel detector array with single-photon sensitivity. Eight lidar returns are time-multiplexed to one output that is digitized with a single 1-GSPS-digitizer, to save power. A grating spectrometer rejects solar background noise spatially and spectrally, and images laser footprints on to the detector array. The gratings retain the fiber laser beam quality. We are developing a 1030-nm AWSL intended for a LEO SmallSat platform.

Guangning Yang↗

Development of Concurrent Artificially-Intelligent Spectrometry and Adaptive Lidar System (CASALS) for Swath Mapping From Space

We present the design and performance of a Concurrent Artificially-intelligent Spectrometry and Adaptive Lidar System (CASALS) for 3D imaging from Space. With a single fast wavelength tuning laser, CASALS accomplishes a 1,200 resolvable spots swath mapping by grating dispersion wavelength steering. Any subset of these 1,200 spots can be selected by wavelength switching. The validation operating principle was accomplished and reported in IGASS-2022. With configurable base design, we report the designs and progress of the CASALS airplane campaign with 256 contiguous ground spots. It is accomplished with a single fast tuning lase at 1040-nm, 1.152MHz tuning rate, and pulse modulated 2-ns on each wavelength. Return pulses are mapped to an eight-pixel detector array with single-photon sensitivity. The lidar returns are time-multiplexed to two outputs that are digitized with two 1-GSPS-digitizer. A grating spectrometer rejects solar background noise spatially and spectrally. We are developing a 1040-nm CASALS intended for multiple LEO orbit missions: Earth Venture Mission on ESPA Grande, STV Mission on ESPA Grande SmallSat, STV Mission on spacecraft equivalent to ICESat power (SWaP,) and splitting the laser beam requires higher laser pulse energy.

ranging lidar↗

Asteroid rotation rates

A trend of increasing mean rotational frequency with increasing diameter is noted in asteroids with diameters greater than 120 km, irrespective of M-, S-, and C-type asteroid subset and family or nonfamily membership. This trend cannot be accounted for by observational selection. For asteroids with diameters smaller than 120 km mean rotational frequency increases with decreasing diameter, but within this group there is a subset with exceptionally long rotational periods. This marked change in the distribution at 120-km diameter could separate primordial asteroids from their collision products. It is also noted that, for asteroids of a given diameter, M asteroids rotate faster than S asteroids, which in turn rotate faster than C asteroids. For all types, family members rotate faster than nonfamily members.

Dermott, S. F.↗

The Role of Data Filtering in Open Source Software Ranking and Selection

Faced with more than 100M open source projects, a more manageable small subset is needed for most empirical investigations. More than half of the research papers in leading venues investigated filtering projects by some measure of popularity with explicit or implicit arguments that unpopular projects are not of interest, may not even represent "real" software projects, or that less popular projects are not worthy of study. However, such filtering may have enormous effects on the results of the studies if and precisely because the sought-out response or prediction is in any way related to the filtering criteria.This paper exemplifies the impact of this common practice on research outcomes, specifically how filtering of software projects on GitHub based on inherent characteristics affects the assessment of their popularity. Using a dataset of over 100,000 repositories, we used multiple regression to model the number of stars -a commonly used proxy for popularity- based on factors such as the number of commits, the duration of the project, the number of authors and the number of core developers. Our control model included the entire dataset, while a second filtered model considered only projects with ten or more authors. The results indicated that while certain characteristics of the repository consistently predict popularity, the filtering process significantly alters the relationships between these characteristics and the response. We found that the number of commits exhibited a positive correlation with popularity in the control sample but showed a negative correlation in the filtered sample. These findings highlight the potential biases introduced by data filtering and emphasize the need for careful sample selection in empirical research of mining software repositories. We recommend that empirical work should either analyze complete datasets such as World of Code, or employ stratified random sampling from a complete dataset to ensure that filtering is not biasing the results.

Malviya Thakur, Addi↗

GeoNEX-SUBSETS: Cutouts of geostationary satellite data over long-term monitoring sites

Satellite remote sensing data are important tool for extrapolating the knowledge obtained at the Fluxnet towers. We introduce our GEO-NEX geostationary satellite subset products, which make it easy to compare between ground observation and Geo-NEX products. The MODIS subset has been frequently used for validating ecosystem models developed at flux towers and upscaling the observed flux data to regional scales. However, MODIS on the polar orbiting satellites can observe target regions only once a day, while the Fluxnet eddy-covariance data are compiled as sub-hourly datasets. As a results, summarizing the sub-hourly flux data into daily statistics is necessary for the comparison between MODIS and Flux data. Here, the new generation geostationary satellite sensors (GOES-16/17 ABI and Himawari-8/9 AHI) has the high-frequent observation feature (10 minutes) in addition to similar spectral band and spatial resolution with MODIS. The high frequent observation allows us to compare the flux diurnal cycle with geostationary satellite sensor data. Some studies have already shown the effective utilization of time series of geostationary satellite data for ecosystem modeling. We are producing NEX Level-1G products, which is the gridded Top-of-Atmosphere reflectance and brightness temperature data of geostationary satellite sensors. We cut out the NEX Level-1G data using the same file format with the MODIS subset except for the projection. The other data products (e.g., surface reflectance, land surface temperature, vegetation indices and climate data) will be also added upon their availability. We selected the ground observation sites from Fluxnet, Phenocam, and AERONET networks. The NEX subset data will be provided through NASA NEX data portal.

GeoNEX↗

Hypoxia-cultured mouse mesenchymal stromal cells from bone marrow and compact bone display different phenotypic traits

Highlights: • Mouse compact bone is richer in MSC compared to central bone marrow. • Derivation of MSC from mouse compact bone is associated with lower risk of contamination with hematopoietic cells. • MSC from compact bone display higher osteogenic differentiation capacity than bone marrow MSC. It has been suggested that the bone marrow microenvironment harbors two distinct populations of mesenchymal stromal cells (MSC), one with a perivascular location and other present in the endosteum. A better understanding of the biology of these MSC subsets has been pursued in order to refine its clinical application. However, most comparative characterizations of mouse MSC have been performed in normoxia. This can result in misleading interpretations since mouse MSC subsets with low/defective p53 activity are known to be selected during culture in normoxia. Here, we report a comprehensive in vitro characterization of mouse MSC isolated from bone marrow (BM-MSC) and compact bone (CB-MSC) expanded and assayed under hypoxia for their morphology, clonogenic efficiency and differentiation capacity. We found that, under hypoxia, compact bone is richer in absolute numbers of MSC and isolation of MSC from compact bone is associated with a reduced risk of hematopoietic cell carryover. In addition, CB-MSC have higher in vitro osteogenic capacity than BM-MSC, while adipogenic differentiation potential is similar. These findings reinforce the hypothesis of the existence of MSC in bone marrow and compact bone representing functionally distinct cell populations and highlight the compact bone as an efficient source of murine MSC under physiological oxygen concentrations.

60 APPLIED LIFE SCIENCES↗

An interactive machine learning platform for analyzing multi-particle coincidence data from cold target recoil ion momentum spectroscopy

We present SCULPT (Supervised Clustering and Uncovering Latent Patterns with Training), a comprehensive software platform for analyzing tabulated high-dimensional multi-particle coincidence data from Cold Target Recoil Ion Momentum Spectroscopy (COLTRIMS) experiments. The software addresses critical challenges in modern momentum spectroscopy by integrating advanced machine learning techniques with physics-informed analysis in an interactive web-based environment. SCULPT implements uniform manifold approximation and projection for non-linear dimensionality reduction to reveal correlations in high-dimensional data. We also discuss potential extensions to deep autoencoders for feature learning and genetic programming for automated discovery of physically meaningful observables. A novel adaptive confidence scoring system provides quantitative reliability assessments by evaluating user-selected clustering quality metrics with predefined weights that reflect each metric’s robustness. The platform features configurable molecular profiles for different experimental systems, interactive visualization with selection tools, and comprehensive data filtering capabilities. Utilizing a subset of SCULPT’s capabilities, we analyze photo-double-ionization data measured using the COLTRIMS method for three-body dissociation of the D 2 O molecule, revealing distinct fragmentation channels and their correlations with physics parameters. The software’s modular architecture and web-based implementation make it accessible to the broader atomic and molecular physics community, significantly reducing the time required for complex multi-dimensional analyses. This opens the door to finding and isolating rare events exhibiting non-linear correlations on the fly during experimental measurements, which can help steer exploration and improve the efficiency of experiments.

Artificial neural networks↗

Downscaled Daily 1 km Climate Data (NEX-GDDP-CMIP6) for Southeast Texas. Full ensemble of downscaled CMIP6 climate projections at 1 km daily resolution.

For the SETx-UIFL, the daily NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6) dataset climate projections were downscaled from approximately 27 km to 1 km. The SETx dataset provides very high-resolution climate data for the historical period (1950–2014) and future scenarios derived from CMIP6 global models under the four Tier 1 Shared Socioeconomic Pathways (SSPs 1.26, 2.45, 3.70, and 5.85), developed for the IPCC Sixth Assessment Report. A subset of ten NEX-GDDP-CMIP6 models was selected to represent a balance of model families, climate sensitivities, and availability across scenarios, ensuring a diverse and reliable ensemble for regional analysis. Selected models: BCC-CSM2-MR, CESM2, CMCC-ESM2, CNRM-ESM2-1, EC-Earth3, FGOALS-g3, GFDL-CM4, MPI-ESM1-2-HR, MRI-ESM2-0, NorESM2-MM. Daily variables downscaled include tasmax, tasmin, tas, pr, hurs, huss, rsds, rlds, and sfcWind.

Persad, Geeta↗

A demonstration of an intelligent control system for a reusable rocket engine

An Intelligent Control System for reusable rocket engines is under development at NASA Lewis Research Center. The primary objective is to extend the useful life of a reusable rocket propulsion system while minimizing between flight maintenance and maximizing engine life and performance through improved control and monitoring algorithms and additional sensing and actuation. This paper describes current progress towards proof-of-concept of an Intelligent Control System for the Space Shuttle Main Engine. A subset of identifiable and accommodatable engine failure modes is selected for preliminary demonstration. Failure models are developed retaining only first order effects and included in a simplified nonlinear simulation of the rocket engine for analysis under closed loop control. The engine level coordinator acts as an interface between the diagnostic and control systems, and translates thrust and mixture ratio commands dictated by mission requirements, and engine status (health) into engine operational strategies carried out by a multivariable control. Control reconfiguration achieves fault tolerance if the nominal (healthy engine) control cannot. Each of the aforementioned functionalities is discussed in the context of an example to illustrate the operation of the system in the context of a representative failure. A graphical user interface allows the researcher to monitor the Intelligent Control System and engine performance under various failure modes selected for demonstration.

Musgrave, Jeffrey L.↗

EOSDIS - Its role in the EOS program and its importance to the scientific community

In order to manage the global data sets required to understand the earth as a system, the EOS Data and Information System (EOSDIS) will collect and store satellite, aircraft, and in situ measurements and their resultant data products, and will distribute the data conveniently. EOSDIS will also provide product generation and science computing facilities to support the development, processing, and validation of standard EOS science data products. The overall architecture of EOSDIS, and how the Distributed Active Archive Centers fit into that structure, are shown. EOSDIS will enable users to query data bases nationally, make use of keywords and other mnemonic identifiers, and see graphic images of subsets of available data prior to ordering full (or selected pieces of) data sets for use in their 'home' environment.

Price, Robert D.↗

Reflectance-Based Sensor Validation Over Ice Surfaces

During this period work was performed in the following areas. These areas are defined in the Work Schedule presented in the original proposal: BRDF development, Data acquisition and processing, THR Table generation and Presentations and Publications. BRDF development involves creating and/or modifying a reflectance model of the Antarctic surface. This model must, for a temporal and spatial average, be representative of the East Antarctic plateau and be expressed in terms of the three standard surface angles: solar zenith angle (SolZA), view zenith angle (SatZA), and relative azimuth angle (RelAZ). We successfully acquired a limited amount of NOAA-9 AVHRR data for radiance validation. The data were obtained from the Laboratory for Terrestrial Physics at Goddard Space Flight Center. We developed our own reading and unpacking software, which we used to select Channel 1 data (visible). We then applied geographic subsetting criteria (same as used for TOMS), and wrote only the relevant data to packed binary files. We proceeded with analysis of these data, which is not yet complete.

Jaross, Glen↗

Issues and Solutions for Bringing Heterogeneous Water Cycle Data Sets Together

The water cycle research community has generated many regional to global scale products using data from individual NASA missions or sensors (e.g., TRMM, AMSR-E); multiple ground- and space-based data sources (e.g., Global Precipitation Climatology Project [GPCP] products); and sophisticated data assimilation systems (e.g., Land Data Assimilation Systems [LDAS]). However, it is often difficult to access, explore, merge, analyze, and inter-compare these data in a coherent manner due to issues of data resolution, format, and structure. These difficulties were substantiated at the recent Collaborative Energy and Water Cycle Information Services (CEWIS) Workshop, where members of the NASA Energy and Water cycle Study (NEWS) community gave presentations, provided feedback, and developed scenarios which illustrated the difficulties and techniques for bringing together heterogeneous datasets. This presentation reports on the findings of the workshop, thus defining the problems and challenges of multi-dataset research. In addition, the CEWIS prototype shown at the workshop will be presented to illustrate new technologies that can mitigate data access roadblocks encountered in multi-dataset research, including: (1) Quick and easy search and access of selected NEWS data sets. (2) Multi-parameter data subsetting, manipulation, analysis, and display tools. (3) Access to input and derived water cycle data (data lineage). It is hoped that this presentation will encourage community discussion and feedback on heterogeneous data analysis scenarios, issues, and remedies.

Acker, James↗

Neutral Gas Properties of Extremely Isolated Early-Type Galaxies

We present the results of single-dish atomic hydrogen (H I) observations of six highly isolated early-type galaxies. These objects are a representative subset of galaxies previously studied at optical wavelengths and selected to be separated by at least 2.5Mpc from companions brighter than M(sub V) =−16.5 mag. Each galaxy was observed with a single pointing using the NRAO Green Bank Telescope L-band receiver. Five of these systems were strongly detected in H I. These five galaxies exhibit H I profiles with a range of properties: single Gaussian-like peaks, separate double peaks, and double horn-like profiles. The four bluest galaxies (B−V<0.54) all contain significant gas with H I masses ranging from 1.1 × 10(exp 8) to 1.4 × 10(exp 9).

Ashley, Trisha L.↗

System and method for characterization of air leakage in building using data from communicating thermostats and/or interval meters

Systems and methods for characterization of retrofit opportunities are described. Some embodiments are directed to methods for determining the air leakage rate of a building, and accordingly, for determining suitability of sealing of air leaks to improve the energy efficiency of a building. The methods may comprise computing, using at least one computing device disposed remote from a building and based at least in part on heating, ventilation and air conditioning (HVAC) runtime data associated with the building, one or more thermal characteristics of the building. The HVAC runtime data may be computed based on data received from a thermostat or a meter, such as an electric or a gas meter. To isolate the impact of air leakage, subsets of the HVAC runtime data at time intervals selected to have substantially the same conditions, but different wind speeds, may be computed.

Zeifman, Michael↗

Development of Building Design Optimization Methodology: Residential Building Applications

Building design optimization is a highly complex problem, requiring long computational running processes because of the many options that exist when a building is being designed. This paper introduces an integrated approach through which to perform this optimization within an acceptable time frame. The approach includes the methods of variable selection, model simplification, and a sequential optimization process. Using singular value decomposition, a large number of design variables is reduced to a smaller subset that can be solved more quickly through the optimization algorithm. To expedite the variable selection process, a modeling approach that quickly simulates annual energy consumption was developed to replace full annual energy simulations. The developed methodology was applied to two residential buildings in the US, and the results are discussed herein. To assess the accuracy of the integrated optimization methodology, the optimized life cycle costs are compaa variables demonstrating the strongest contributions in the optimization study were identified. The proposed methodology significantly shortened the time requirements for the optimization processes of the two case studies by 74% and 84%; the optimized life cycle costs were within 0.05% and 0.06%, respectively, of the optimum point.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

VLA continuum observations of barred spiral galaxies

Observations of NGC 613, NGC 1300, NGC 4314 and NGC 5383 using the VLA at frequencies of 1464.9 and 4885.1 MHz are reported. These objects are a subset of galaxies from which radio emission were searched. The selection criteria were: (1) they are barred spiral galaxies preferentially with different Hubble type; (2) they have a peculiar or hot spot nucleus; (3) they have been observed at far infrared wavelengths by IRAS; and (4) they are observable from the northern hemisphere. Their radio and far infrared properties are summarized and their composite spectra are shown.

Garcia-Barreto, J. Antonio↗