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At least 271 records · Page 15

A User-Focused Renovation of CERES Metadata

Production software and public data products for Clouds and the Earth’s Radiant Energy System (CERES) continue to evolve as the project extends its climate data record. The data management team for CERES is currently undertaking major renovations of both code and data products, the latter of which is, of course, in service of improving user experience. A major mode of CERES’ data product improvement is in renovating products’ metadata. Metadata standards have evolved since CERES began producing its data products in 2000. In its twentieth year, CERES essentially asked the question: how would the project design its data products if it could start all over again? With forthcoming editions, this rebirth will be realized. CERES has redesigned its metadata standards to best position itself for data discoverability. The project has used the latest standards being developed in NASA’s Earth Science Data and Information Systems (ESDIS) Project’s Unified Metadata Model (UMM) documentation; collaborated with the Atmospheric Science Data Center (ASDC) to ensure compliance with Common Metadata Repository compatibility, and continued compliance with Climate and Forecast (CF) Conventions. In doing so, the team created its own, internal document for proper metadata creation and metadata verification software that is deployed prior to all code deliveries. This presentation will discuss this redesign process, as well as needs met and those that are still outstanding in the search for an improved user experience with CERES data products.

Kathleen Dejwakh↗

Modeling Atmospheric Science Knowledge from Research Publications

NASA Earth Science Data Centers contain enormous amounts of remote sensing digital data. It is often a significant challenge for users to find data suitable for their research topic in these vast archives. One of the approaches is the usage-driven dataset discovery, where users seek publications on projects similar to their intended study. For this approach to be effective, users need a clear connection between the underlying data in the publications and the study objectives; this is not often apparent to non-expert users. Tools and methodologies that can help facilitate and organize these connections are therefore valuable for creating improved knowledge mappings, which can be further used by search engines to suggest data or publications best tailored to a user’s specific research goal. As an illustration of these challenges, in this work we focus on the atmospheric chemistry processes related to Earth environmental impacts such as ozone depletion, aerosols, smog formation, acid rain, and radiative forcing. We further limit our study to publications that use data from the Microwave Limb Sounder (MLS) instrument flown on the Aura Earth Observing System. To create knowledge representations of science carried out in these publications, we use existing ontologies such as the Global Change Master Directory (GCMD) and Semantic Web for Earth and Environmental Terminology (SWEET). These ontologies together encompass term dictionaries that include measured variables, names of molecules or radicals, mission and instrument names, locations, action words, among many others. Based on these terms acknowledge graph database was populated with the terms retrieved from scientific publications that study atmospheric chemistry. These databases can be used to further enhance the automation of knowledge discovery and facilitate machine learning and artificial intelligence algorithms or applications. These tools and methods can also be extended to apply to content from other related Earth science domains.

Irina Gerasimov↗

On Generalizably Improving RANS Predictions of Flow Separation and Reattachment

This work presents progress in an ongoing data-driven turbulence modeling effort at NASA Langley Research Center to improve predictions for separated flows. Two augmentation strategies are presented – one to improve predictions for the point of reattachment after smooth-body separation, and another to improve predictions for flow separation due to prolonged adverse pressure gradients. The reattachment augmentation was inspired from lessons learned during attempts at using field inversion and machine learning (FIML); however, it is prescribed as a conventional analytic closed-form expression. Results show that, when introduced into the SST k-w model, it shortens the otherwise overpredicted separation bubble length for three cases characterized by different Reynolds numbers and flow geometries. The second augmentation, which addresses flow separation under prolonged adverse pressure gradients, is inferred via FIML and applied as a neural network within the Spalart-Allmaras model. It uses features that are chosen such that the presented results show an improved predictive accuracy for the training case without affecting other cases where the augmentation is not needed. Further testing is required to establish the generalizability of this augmentation. The rationale behind the chosen features that serve as inputs to both these augmentations is also presented for the benefit of the reader.

machine learning↗

Assimilating GCOM-W1 AMSR2 and TRMM TMI Radiance Data in GEOS Analysis and Reanalysis

The Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI) observed the Earth in lower latitudes between 1997 - 2015. Its conical-scan radiometer has nine channels and measured microwave radiances between 10 and 89 GHz. These data provide information on atmospheric temperature, humidity, clouds, precipitation, as well as sea surface temperature. Radiance data from other microwave radiometers such as Special Sensor Microwave Imager (SSM/I) and Special Sensor Microwave Imager Sounder (SSMIS) onboard various Defense Meteorological Satellite Program (DMSP) satellites are assimilated in clear-sky conditions in the Modern-Era Retrospective analysis for Research and Applications (MERRA) and its version 2 (MERRA-2) data sets at the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center. The GMAO's Hybrid 4D-EnVar-based Atmospheric Data Assimilation System (ADAS) is enhanced with an all-sky microwave radiance data assimilation capability in the real-time GEOS-Forward Processing (FP) system. Currently, the FP system assimilates Global Precipitation Measurement (GPM) microwave imager (GMI) radiance data utilizing this all-sky capability, and is being extended to use more all-sky data from other microwave radiometers. In this presentation, we will focus on impacts of all-sky TMI radiance data on GEOS analyses of atmospheric moisture, precipitation and other fields, and discuss their applications for future GEOS reanalyses.

Jin, Jianjun↗

Interactive Sectoring and Animation of Global Change Data

In order to analyze and share results of global change climate data sets, scientists require a venue in which to exchange their results. The perfect medium for these collaborative efforts is the world wide web. Intuitive and efficient user interfaces, and background processes were developed at the Global Hydrology and Climate Center to interactively view weather satellite, radar, global temperature anomaly, and model output data using the world wide web. These tools combine scripts, Java, and C code, which allows the end user to easily interact with data, to create high resolution sector images, and sectored animation sequences. This paper examines the architecture and interfaces which were designed at the Global Hydrology and Climate Center and how they are used for collaborative research.

Meyer, Paul J.↗

Simulation Studies of Forest Structure using 3D Lidar and Radar Models

The use of lidars and radars to measure forest structure attributes such as height and biomass are being considered for future Earth Observation missions. Large footprint lidar makes a direct measurement of the heights of scatterers in the illuminated footprint and can yield information about the vertical profile of the canopy. Synthetic Aperture Radar (SAR) is known to sense the canopy volume, especially at longer wavelengths and is useful for estimating biomass. Interferometric SAR (InSAR) has been shown to yield forest canopy height information. For example, the height of scattering phase retrieved from InSAR data is considered to be correlated with the three height and the spatial structure of the forest stand. There is much interest in exploiting these technologies separately and together to get important information for carbon cycle and ecosystem science. More detailed information of the electromagnetic radiation interactions within forest canopies is needed. And backscattering models can be of much utility here. As part of a NASA funded project to explore data fusion, a three-dimensional (3D) coherent radar backscattering model and a 3D lidar backscatter models were used to investigate the use of large footprint lidar, SAR and InSAR for characterizing realistic forest scenes. For this paper, we use stem maps and other forest measurements to develop a realistic spatial structure of a spruce-hemlock forest canopy found in Maine, USA. The radar and lidar models used measurements of the 3D forest scene as input and simulated the coherent radar backscattering signature and 1064nm energy backscatter, respectively. The relationships of backscatter derived forest structure were compared with field measurements. In addition, we also had detailed airborne lidar (Laser Imaging Vegetation Sensor, LVIS) data available over the stem map sites that was used to study the accuracies of tree height derived from modeled SAR backscatter and the scattering phase center retrieved from the simulated InSAR data will be compared with the height indices, or other structure parameters derived from the lidar data. These results will address the possible synergies between lidar and radar in data in terms of forest structural information.

Sun, Guoqing↗

DFW microburst model based on AA-539 data

Analysis of the August 2, 1985 crash for an L-1011 jumbo jet (DL-191) on approach to the Dallas-Ft. Worth International Airport (DFW) in a thunderstorm indicates that the severe windshear microburst that caused the crash was composed not only of a strong downflow and outflow but also included several large-scale vortex rings entrained in the flowfield. This paper presents a detailed two-dimensional model of the DFW microburst based on data from the MD-80 (AA-539) that followed behind DL-191 and flew through the microburst about two minutes after the crash of DL-191. The model was developed using wind-vector and flight-path data reconstructed by NASA Ames Research Center and a combination of interactive graphics and least-squares error best fit between the modeled and measured wind vectors along the AA-539 flight path. The model indicates that the flowfield contains some significant elements and vortices not previously reported. The alternating direction of rotation of the vortices in the model suggests a microburst structure based on a von Karman vortex street rather than on a Kelvin-Helmholtz instability. The model also indicates that the reconstructed wind-vector data contain a time lag of at least one second in the horizontal winds.

Grantham, Walter J.↗

The Transition of Satellite Observations Assimilated in GEOS to JEDI

In order to incorporate the Joint Effort for Data assimilation Integration (JEDI) in the Goddard Earth Observing System (GEOS), which is used for weather, climate, and air quality forecasts and producing reanalysis datasets, it is necessary to validate the observing system in JEDI. NASA’s Global Modeling and Assimilation Office (GMAO), with the Joint Center for Satellite Data Assimilation (JCSDA), is developing the Unified Forward Operator (UFO) and adding all the necessary features to replicate existing capability. Various satellite and conventional observations are assimilated by the Gridpoint Statistical Interpolation (GSI)–based GEOS atmospheric data assimilations system. GMAO has been adding, validating, and updating procedures including the GEOS all-sky microwave radiance assimilation framework to assimilate those observation in UFO. Robust tests are conducted to ensure correct configurations of observational data bias correction (BC), quality control (QC), and observation error in UFO and good agreements between UFO and GSI results. Our work on satellite observations is reported in this presentation.

Jianjun Jin↗

Design of the Wind Tunnel Model Communication Controller Board

The NASA Langley Research Center's Wind Tunnel Reinvestment project plans to shrink the existing data acquisition electronics to fit inside a wind tunnel model. Space limitations within a model necessitate a distributed system of Application Specific Integrated Circuits (ASICs) rather than a centralized system based on PC boards. This thesis will focus on the design of the prototype of the communication Controller board. A portion of the communication Controller board is to be used as the basis of an ASIC design. The communication Controller board will communicate between the internal model modules and the external data acquisition computer. This board is based around an Field Programmable Gate Array (FPGA), to allow for reconfigurability. In addition to the FPGA, this board contains buffer Random Access Memory (RAM), configuration memory (EEPROM), drivers for the communications ports, and passive components.

Wilson, William C.↗

Jet Noise Prediction Using Hybrid RANS/LES with Structured Overset Grids

Hybrid RANS/LES simulations using the structured overset grid approach and a low dissipation finite-difference method within the Launch Ascent and Vehicle Aerodynamics (LAVA) solver framework are presented for jet noise prediction. The simulations are part of a validation effort to demonstrate jet noise prediction capability, to assess noise characteristics of next generation quiet supersonic commercial jets. Results are compared with experimental data acquired in the Small Hot Jet Acoustic Rig in the Aeroacoustic Propulsion Laboratory at NASA Glenn Research Center. Details of the structured overset grids, numerical discretization, and turbulence model are provided. Near-field comparisons to PIV data and far-field comparisons to microphone data are discussed. Excellent agreement of time-averaged mean quantities along the jet center-line and lip-line are obtained. Good agreement with root-mean-squared (RMS) quantities along the jet center-line are also obtained. An over prediction of lip-line RMS at the nozzle exit is observed leading to a small over-prediction of side-line far-field noise (less than 2 dB). Good agreement with far-field noise in the Mach wave radiation directions is achieved.

Housman, Jeffrey A.↗

The NASA Merra-2 Reanalysis Products: Data and Tools Used for Aerosol and Air Quality Studies

The NASA Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) is atmospheric reanalysis data spanning 1980 to present. It has been produced by the NASA Global Modeling and Assimilation Office (GMAO) and is distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). MERRA-2 data includes 100 collections of Earth system variables, mainly from the atmospheric model, such as aerosol fields and meteorological fields, radiation fields, and aerosol fields, guided by the assimilation of as many as six million observations every six hours. MERRA-2 has been one of the most popular datasets from NASA and is widely used in interdisciplinary research and applications, with increasing numbers of new users. For example, at least 7000 users accessed MERRA-2 data at GES DISC in the year 2021, ~1000 more users than in the year 2020. In this presentation, we will introduce the MERRA-2 datasets associated with aerosol and air quality studies and use a wildfire case study to demonstrate the data tools developed at GES DISC to analyze and visualize MERRA-2 data, such as Giovanni and the level 3 and level 4 subsetter, and Jupyter Python notebook. We will also update the status of cloud migration of the MERRA-2 data to Amazon Web Services (AWS).

Xiaohua Pan↗

Associative Flow Rule Used to Include Hydrostatic Stress Effects in Analysis of Strain-Rate-Dependent Deformation of Polymer Matrix Composites

designing reliable composite engine cases that are lighter than the metal cases in current use. The types of polymer matrix composites that are likely to be used in such an application have a deformation response that is nonlinear and that varies with strain rate. The nonlinearity and the strain-rate dependence of the composite response are due primarily to the matrix constituent. Therefore, in developing material models to be used in the design of impact-resistant composite engine cases, the deformation of the polymer matrix must be correctly analyzed. However, unlike in metals, the nonlinear response of polymers depends on the hydrostatic stresses, which must be accounted for within an analytical model. By applying micromechanics techniques along with given fiber properties, one can also determine the effects of the hydrostatic stresses in the polymer on the overall composite deformation response. First efforts to account for the hydrostatic stress effects in the composite deformation applied purely empirical methods that relied on composite-level data. In later efforts, to allow polymer properties to be characterized solely on the basis of polymer data, researchers at the NASA Glenn Research Center developed equations to model the polymers that were based on a non-associative flow rule, and efforts to use these equations to simulate the deformation of representative polymer materials were reasonably successful. However, these equations were found to have difficulty in correctly analyzing the multiaxial stress states found in the polymer matrix constituent of a composite material. To correct these difficulties, and to allow for the accurate simulation of the nonlinear strain-rate-dependent deformation analysis of polymer matrix composites, in the efforts reported here Glenn researchers reformulated the polymer constitutive equations from basic principles using the concept of an associative flow rule. These revised equations were characterized and validated in an experimental program carried out through a university grant with the Ohio State University, wherein tensile and shear deformation data were obtained for a representative polymer for strain rates ranging from quasi-static to high rates of several hundred per second. Tensile deformation data also were obtained over a variety of strain rates and fiber orientation angles for a representative polymer matrix composite composed using the polymer.

Goldberg, Robert K.↗

Heat transfer tests of an 0.006-scale thin-skin space shuttle thermocouple model (141-OT) in the Langley Research Center Freon tunnel at M-6 (IH18)

Ascent heating data were obtained at conditions simulating real gas effects at hypersonic Mach numbers. The configurations tested were Orbiter alone, external tank alone, and mated Orbiter and external tank. A boundary layer trip investigation was conducted for all configurations. The test was conducted at Mach 6 and Reynolds number of one half million per foot for 0 deg and -5 deg angle-of-attack. Selected thermocouples were chosen from the Orbiter and external tank to be used for obtaining heat transfer measurements. A maximum of 42 thermocouples could be measured by the facility data acquisition at one time and no attempt was made to record the excess thermocouples located on the model. Photographs of the test configurations are shown.

Walstad, D. G.↗

A computational and experimental study of high Reynolds number viscous/inviscid interaction about a cone at high angle of attack

The flow over a 5 deg semi-angle cone at incidence in supersonic flow is studied as a model problem for the flow over aircraft forebodies. A computational method utilizing the conically symmetric Navier-Stokes equations is used to obtain theoretical flow results which are compared with experimental data from the Ames Research Center 6- by 6-Foot Wind Tunnel and with results from a cone model sting mounted on an F-15 aircraft. The computed results agree well with the wind-tunnel data but less well with the flight data. Modification of the algebraic turbulence model was necessary to reflect an apparent lower turbulence level in flight than was present in the wind tunnel.

Mcrae, D. S.↗

On-Line Fringe Tracking and Prediction at IOTA

The Infrared/Optical Telescope Array (IOTA) is a multi-aperture Michelson interferometer located on Mt. Hopkins near Tucson, Arizona. To enable viewing of fainter targets, an on-line fringe tracking system is presently under development at NASA Ames Research Center. The system has been developed off-line using actual data from IOTA, and is presently undergoing on-line implementation at IOTA. The system has two parts: (1) a fringe tracking system that identifies the center of a fringe packet by fitting a parametric model to the data; and (2) a fringe packet motion prediction system that uses characteristics of past fringe packets to predict fringe packet motion. Combined, this information will be used to optimize on-line the scanning trajectory, resulting in improved visibility of faint targets. Fringe packet identification is highly accurate and robust (99% of the 4000 fringe packets were identified correctly, the remaining 1% were either out of the scan range or too noisy to be seen) and is performed in 30-90 milliseconds on a Pentium II-based computer. Fringe packet prediction, currently performed using an adaptive linear predictor, delivers a 10% improvement over the baseline of predicting no motion.

Wilson, Edward↗

Visualizing an Exascale Data Center Digital Twin: Considerations, Challenges and Opportunities

Digital twins are an excellent tool to model, visualize, and simulate complex systems, to understand and optimize their operation. In this work, we present the technical challenges of real-time visualization of a digital twin of the Frontier supercomputer.We show the initial prototype and current state of the twin and highlight technical design challenges of visualizing such a large High Performance Computing (HPC) system. The goal is to understand the use of augmented reality as a primary way to extract information and collaborate on digital twins of complex systems. This leverages the spatio-temporal aspect of a 3D representation of a digital twin, with the ability to view historical and real-time telemetry, triggering simulations of a system state and viewing the results, which can be augmented via dashboards for details. Finally, we discuss considerations and opportunities for augmented reality of digital twins of large-scale, parallel computers.

Maiterth, Matthias↗

Results of investigation on an 0.004-scale 140c modified configuration space shuttle vehicle orbiter model (74-0) in the NASA/Langley Research Center hypersonic nitrogen tunnel (OA89)

Wind tunnel test data for the modified space shuttle vehicle orbiter is documented. Tests were made at various elevon settings and additionally in wing off/bodyflap off configuration at angles of attack from -5 to 42.5 degrees at zero yaw. Data obtained on high hypersonic longitudinal and lateral directional stability and control characteristics of the updated SSV configuration in an initially diatomic medium are included.

Hawthorne, P. J.↗

Atmospheric corrections for TIMS estimated emittance

The estimated temperature of the average of 500 lines of Thermal Infrared Multispectral Scanner (TIMS) data of the Pacific Ocean, from flight line 94, collected on 30 Sep. 1988, at 1931 GMT is shown. With no atmospheric corrections, estimated temperature decreases away from nadir (the center of the scan line). A LOWTRAN modeled correction, using local radiosonde data and instrument scan angle information, results in reversed limb darkening effects for most bands, and does not adequately correct all bands to the same temperature. The atmosphere tends to re-radiate energy at the wavelengths at which it most absorbs, and thus the overall difference between corrected and uncorrected temperatures is approximately 40 C, despite the average LOWTRAN calculated transmittance of only 60 percent between 8.1 and 11.6 microns. An alternative approach to atmospheric correction is a black body normalization. This is done by calculating a normalization factor for each pixel position and wavelength, which when applied results in a single calculated temperature, as would be expected for a gray body with near uniform emittance. The black body adjustment is based on the atmospheric conditions over the sea. The ground elevation profile along the remaining 3520 scan lines (approximately 10 km) of flight line 94, up the slopes of Kilauea, determined from aircraft pressure and laser altimeter data is shown. This flight line includes a large amount of vegetation that is clearly discernible on the radiance image, being much cooler than the surrounding rocks. For each of the 3520 scan lines, pixels were classified as vegetation or 'other'. A moving average of 51 lines was applied to the composite vegetation emittance for each scan line, to reduce noise. Assuming vegetation to be like water, and to act as gray body with an emittance of 0.986 across the spectrum, it is shown that that the LOWTRAN induced artifacts are severe, and other than for the 0.9.9 micron channel, not significantly different from applying no corrections at all. As expected, with increasing elevation atmospheric effects are slightly reduced, because moisture tends to be concentrated in the lowermost part of the atmosphere. The black body adjustment is highly robust, and even at elevations nearly 600 meters above the sea, remains an alternative procedure for use in calculating emittance.

Warner, T. A.↗