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NASA NTRS1990

Rapid calculation of terrain parameters for radiation modeling from digital elevation data

Digital elevation models are now widely used to calculate terrain parameters to determine incoming solar and longwave radiation for use in surface climate models, interpretation of remote-sensing data, and parameters in hydrologic models. Because of the large number of points in an elevation grid, fast algorithms are useful to save computation time. A description is given of rapid methods for calculating slope and azimuth, solar illumination angle, horizons, and view factors for radiation from sky and terrain. Calculation time is reduced by fast algorithms and lookup tables.

Dozier, Jeff↗

NASA NTRS1992

Survey Data for Geomagnetic Field Modelling

The survey data discussed here are based on observations made relatively recently at points on land. A special subset of land survey data consists of those made at specially designated sites known as repeat stations. This class of data will be discussed in another part of this document (Barton, 1991b), so only the briefest of references will be made to repeat stations here. This discussion of 'ordinary' land survey data begins with a description of the spatial and temporal distributions of available survey data based on observations made since 1900. (The reason for this rather arbitrary choice of cut-off date is that this was the value used in the production of the computer file of magnetic survey data (land, sea, air, satellite, rocket) that is the primary source of data for geomagnetic main-field modeling). This is followed by a description of the various types of error to which these survey data are, or may be, subject and a discussion of the likely effects of such errors on field models produced from the data. Finally, there is a short section on the availability of geomagnetic survey data, which also describes how the data files are maintained.

Barraclough, D. R.↗

NASA NTRS2014

Real-Time Onboard Global Nonlinear Aerodynamic Modeling from Flight Data

Flight test and modeling techniques were developed to accurately identify global nonlinear aerodynamic models onboard an aircraft. The techniques were developed and demonstrated during piloted flight testing of an Aermacchi MB-326M Impala jet aircraft. Advanced piloting techniques and nonlinear modeling techniques based on fuzzy logic and multivariate orthogonal function methods were implemented with efficient onboard calculations and flight operations to achieve real-time maneuver monitoring and analysis, and near-real-time global nonlinear aerodynamic modeling and prediction validation testing in flight. Results demonstrated that global nonlinear aerodynamic models for a large portion of the flight envelope were identified rapidly and accurately using piloted flight test maneuvers during a single flight, with the final identified and validated models available before the aircraft landed.

Brandon, Jay M.↗

NASA NTRS1994

Data assimilation and model evaluation experiment datasets

The Institute for Naval Oceanography, in cooperation with Naval Research Laboratories and universities, executed the Data Assimilation and Model Evaluation Experiment (DAMEE) for the Gulf Stream region during fiscal years 1991-1993. Enormous effort has gone into the preparation of several high-quality and consistent datasets for model initialization and verification. This paper describes the preparation process, the temporal and spatial scopes, the contents, the structure, etc., of these datasets. The goal of DAMEE and the need of data for the four phases of experiment are briefly stated. The preparation of DAMEE datasets consisted of a series of processes: (1) collection of observational data; (2) analysis and interpretation; (3) interpolation using the Optimum Thermal Interpolation System package; (4) quality control and re-analysis; and (5) data archiving and software documentation. The data products from these processes included a time series of 3D fields of temperature and salinity, 2D fields of surface dynamic height and mixed-layer depth, analysis of the Gulf Stream and rings system, and bathythermograph profiles. To date, these are the most detailed and high-quality data for mesoscale ocean modeling, data assimilation, and forecasting research. Feedback from ocean modeling groups who tested this data was incorporated into its refinement. Suggestions for DAMEE data usages include (1) ocean modeling and data assimilation studies, (2) diagnosis and theoretical studies, and (3) comparisons with locally detailed observations.

Lai, Chung-Cheng A.↗

NASA NTRS2021

A multi-model CMIP6-PMIP4 study of Arctic sea ice at 127 ka: sea ice data compilation and model differences

The Last Interglacial period (LIG) is a period with increased summer insolation at high northern latitudes, which results in strong changes in the terrestrial and marine cryosphere. Understanding the mechanisms for this response via climate modelling and comparing the models' representation of climate reconstructions is one of the objectives set up by the Paleoclimate Modelling Intercomparison Project for its contribution to the sixth phase of the Coupled Model Intercomparison Project. Here we analyse the results from 16 climate models in terms of Arctic sea ice. The multi-model mean reduction in minimum sea ice area from the pre industrial period (PI) to the LIG reaches 50 % (multi-model mean LIG area is 3.20×10^6 sq.km, compared to 6.46×10^6 sq.km for the PI). On the other hand, there is little change for the maximum sea ice area (which is 15–16×10^6 sq.km for both the PI and the LIG. To evaluate the model results we synthesise LIG sea ice data from marine cores collected in the Arctic Ocean, Nordic Seas and northern North Atlantic. The reconstructions for the northern North Atlantic show year-round ice-free conditions, and most models yield results in agreement with these reconstructions. Model–data disagreement appear for the sites in the Nordic Seas close to Greenland and at the edge of the Arctic Ocean. The northernmost site with good chronology, for which a sea ice concentration larger than 75 % is reconstructed even in summer, discriminates those models which simulate too little sea ice. However, the remaining models appear to simulate too much sea ice over the two sites south of the northernmost one, for which the reconstructed sea ice cover is seasonal. Hence models either underestimate or overestimate sea ice cover for the LIG, and their bias does not appear to be related to their bias for the pre-industrial period. Drivers for the inter-model differences are different phasing of the up and down short-wave anomalies over the Arctic Ocean, which are associated with differences in model albedo; possible cloud property differences, in terms of optical depth; and LIG ocean circulation changes which occur for some, but not all, LIG simulations. Finally, we note that inter-comparisons between the LIG simulations and simulations for future climate with moderate (1 %/yr) CO2 increase show a relationship between LIG sea ice and sea ice simulated under CO2 increase around the years of doubling CO2. The LIG may therefore yield insight into likely 21st century Arctic sea ice changes using these LIG simulations.

Arctic sea ice↗

NASA NTRS1999

The Upper Atmosphere Research Satellite: From Coffee Table Art to Quantitative Science

The Upper Atmosphere Research Satellite (UARS) has provided an unprecedented set of observations of constituents of the stratosphere. When used in combination with data from other sources and appropriate modeling tools, these observations are useful for quantitative evaluation of stratospheric photochemical processes. This is illustrated by comparing ozone observations from airborne Differential Absorption Lidar (DIAL), from the Polar Ozone and Aerosol Measurement (POAM), from the Microwave Limb Sounder (MLS), and from the Halogen occultation Experiment (HALOE) with ozone fields generated with a three dimensional model. For 1995-96, at polar latitudes, observations from DIAL flights on December 9 and January 30, and POAM and MLS between late December and late January are compared with ozone fields from the GSFC 3D chemistry and transport model. Data from the three platforms consistently show that the observed ozone has a negative trend relative to the modeled ozone, and that the trend is uniform in time between early and mid winter, with no obvious dependence on proximity to the vortex edge. The importance of chlorine catalyzed photochemistry to this ozone loss is explored by comparing observations from MLS and HALOE with simulations for other northern winters, particularly 1997-98.

Douglass, Anne R.↗

NASA NTRSDate not supplied

Learjet Flight Test Update

The status of the future jet-noise test using a Lear 25 aircraft is provided. The intent of the test is to provide data for comparisons with scale-model data acquired in the Aero-Acoustic Propulsion Laboratory (AAPL) and a new single-stream jet noise model.

Jet Noise↗

NASA NTRS2016

Exploring and Analyzing Climate Variations Online by Using NASA MERRA-2 Data at GES DISC

NASA Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) (http:giovanni.sci.gsfc.nasa.govgiovanni) is a web-based data visualization and analysis system developed by the Goddard Earth Sciences Data and Information Services Center (GES DISC). Current data analysis functions include Lat-Lon map, time series, scatter plot, correlation map, difference, cross-section, vertical profile, and animation etc. The system enables basic statistical analysis and comparisons of multiple variables. This web-based tool facilitates data discovery, exploration and analysis of large amount of global and regional remote sensing and model data sets from a number of NASA data centers. Long term global assimilated atmospheric, land, and ocean data have been integrated into the system that enables quick exploration and analysis of climate data without downloading, preprocessing, and learning data. Example data include climate reanalysis data from NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) which provides data beginning in 1980 to present; land data from NASA Global Land Data Assimilation System (GLDAS), which assimilates data from 1948 to 2012; as well as ocean biological data from NASA Ocean Biogeochemical Model (NOBM), which provides data from 1998 to 2012. This presentation, using surface air temperature, precipitation, ozone, and aerosol, etc. from MERRA-2, demonstrates climate variation analysis with Giovanni at selected regions.

knowledge base↗

NASA NTRS2024

The Mega-MUSCLES Treasury Survey: X-Ray to Infrared Spectral Energy Distributions of a Representative Sample of M Dwarfs

We present 5–1 × 107 Å spectral energy distributions (SEDs) for 12 M dwarf stars covering spectral types M0–M8. Our SEDs are provided for community use as a sequel to the Measurements of the Ultraviolet Spectral Characteristics of Low-mass Exoplanetary Systems (MUSCLES) survey. The 12 stars include eight known exoplanet hosts and four stars chosen to fill out key parameter space in spectral type and rotation period. The SEDs are constructed from Hubble Space Telescope ultraviolet spectroscopy and XMM Newton, Chandra, and/or Swift X-ray observations, and completed with various model data, including Lyα reconstructions, PHOENIX optical models, APEC coronal models, and differential emission measure models in the currently-unobservable extreme ultraviolet. We provide a complete overview of the Mega-MUSCLES program, including a description of the observations, models, and SED construction. The SEDs are available as MAST high-level science products and we describe the various data products here. We also present ensemble measurements from our sample that are of particular relevance to exoplanet science, including the high-energy fluxes in the habitable zone and the farultraviolet to near-ultraviolet ratio. Combined with MUSCLES, Mega-MUSCLES provides SEDs covering a wide range of M dwarf spectral types and ages such that suitable proxies for any M dwarf planet host of interest may be found in our sample. However, we find that ultraviolet and X-ray fluxes can vary even between stars with similar parameters, such that observations of each exoplanet host star will remain the gold standard for interpreting exoplanet atmosphere observations.

David J. Wilson↗

NASA NTRS2019

Using Big Data Technologies with Earth Science Data in HDF5: HDF5 Scalable Solutions

HDF5 (Hierarchical Data Format 5) is open-source, high-performance software that consists of an abstract data model, library, and fileformat used for storing and managing extremely large and/or complex data collections. NASA Earth Observing System (EOS) Data and Information Systems use HDF5 as an archival format to store remote sensing data from EOS satellites. HDF5 is also used to store other types of Geoscience and Strophysical data, e.g., seismic data and data from Low-Frequency Array (LOFAR) radio telescopes. Data stored in HDF5 has reached tens of petabytes and is growing at an accelerated rate.With the growing amout of HDF5 Earth Science data to analyze and process, scientists need to adopt big data technologies including new storage paradigms such as cloud and object storage. To run models and perform data analysis they also need to utilizied efficient and diverse ways to access data, from high-performance computing's (HPC) Message Passing Interface (MPI) I/O and deep memory hierarchies (DMH) to non-HPC frameworks such as Apache Hadoop, Spark, and Drill. The HDF Group continually works to enable usage of big data technologies in HDF software.

Knox, Larry↗

NASA NTRS1995

A Unified Air-Sea Visualization System: Survey on Gridding Structures

The goal is to develop a Unified Air-Sea Visualization System (UASVS) to enable the rapid fusion of observational, archival, and model data for verification and analysis. To design and develop UASVS, modelers were polled to determine the gridding structures and visualization systems used, and their needs with respect to visual analysis. A basic UASVS requirement is to allow a modeler to explore multiple data sets within a single environment, or to interpolate multiple datasets onto one unified grid. From this survey, the UASVS should be able to visualize 3D scalar/vector fields; render isosurfaces; visualize arbitrary slices of the 3D data; visualize data defined on spectral element grids with the minimum number of interpolation stages; render contours; produce 3D vector plots and streamlines; provide unified visualization of satellite images, observations and model output overlays; display the visualization on a projection of the users choice; implement functions so the user can derive diagnostic values; animate the data to see the time-evolution; animate ocean and atmosphere at different rates; store the record of cursor movement, smooth the path, and animate a window around the moving path; repeatedly start and stop the visual time-stepping; generate VHS tape animations; work on a variety of workstations; and allow visualization across clusters of workstations and scalable high performance computer systems.

Anand, Harsh↗

NASA NTRS2012

Efficient Global Aerodynamic Modeling from Flight Data

A method for identifying global aerodynamic models from flight data in an efficient manner is explained and demonstrated. A novel experiment design technique was used to obtain dynamic flight data over a range of flight conditions with a single flight maneuver. Multivariate polynomials and polynomial splines were used with orthogonalization techniques and statistical modeling metrics to synthesize global nonlinear aerodynamic models directly and completely from flight data alone. Simulation data and flight data from a subscale twin-engine jet transport aircraft were used to demonstrate the techniques. Results showed that global multivariate nonlinear aerodynamic dependencies could be accurately identified using flight data from a single maneuver. Flight-derived global aerodynamic model structures, model parameter estimates, and associated uncertainties were provided for all six nondimensional force and moment coefficients for the test aircraft. These models were combined with a propulsion model identified from engine ground test data to produce a high-fidelity nonlinear flight simulation very efficiently. Prediction testing using a multi-axis maneuver showed that the identified global model accurately predicted aircraft responses.

Morelli, Eugene A.↗

NASA NTRS1986

The combined release and radiation effects satellite, a joint NASA/DOD program

The Combined Release and Radiation Effects Satellite (CRRES) program is a two-phase joint USAF/NASA program consisting of a low Earth orbit (LEO) phase and a geosynchronous transfer orbit (GTO) phase. The mission has been carefully planned to help clarify the geospace environment picture and its effects on space hardware, communications, and man. CRRES instruments were selected for synergism, accuracy, and applicability, and will be cross-calibrated for consistency. They will provide data to fill the gaps in geospace modeling data already obtained, and will update and correct existing models. The chemical release experiments and low altitude instruments will clarify the character of the ionosphere in low Earth orbit and the high altitude chemical release experiments will improve knowledge of how trapped particle populations behave out as far as synchronous altitudes. The ionospheric studies will lead to significantly improved Earth-space intercommunications.

Berrier, D. J.↗

NASA NTRS1994

Wave-current interaction study in the Gulf of Alaska for detection of eddies by synthetic aperture radar

High resolution Esa Remote Sensing Satellite-1 (ERS-1) Synthetic Aperture Radar (SAR) images are used to detect a mesoscale eddy. Such features limit dispersal of pollock larvae and therefore likely influence recruitment of fish in the Gulf of Alaska. During high sea states and high winds, the direct surface signature of the eddy was not clearly visible, but the wave refraction in the eddy area was observed. The rays of the wave field are traced out directly from the SAR image. The ray pattern gives information on the refraction pattern and on the relative variation of the wave energy along a ray through wave current interaction. These observations are simulated by a ray-tracing model which incorporates a surface current field associated with the eddy. The numerical results of the model show that the waves are refracted and diverge in the eddy field with energy density decreasing. The model-data comparison for each ray shows the model predictions are in good agreement with the SAR data.

Liu, Antony K.↗

NASA NTRS1991

Observations on practical turbulence modeling for high-speed jet/plume flowfields

An overview is presented of the current status in terms of simulating basic high-speed/straightback free jet flowfields with two-equation turbulence models. A building-block approach is described which provides a systematic method of calibrating such turbulence models. Data to support this approach focuses on obtaining turbulence modeling capabilities to reproduce basic mean flow structure for simple flows before progressing to more complex problems. For transverse jets and wall jets, new building-blocks of data are necessary with turbulence modeling capabilities unifying the free jet building-blocks discussed, and fundamental boundary layer and shock/boundary layer interaction building-blocks resulting from other studies.

Dash, Sanford M.↗

NASA NTRS1979

NSSDC Data Listing

Data available from the National Space Science Data Center (NSSDC) are listed. The spacecraft, principal investigator, the experiment, and time span of the data are given. A listing is also included of ground-based data, models, computer routines and composite spacecraft data that are available from NSSDC.

Source record↗

NASA NTRS1980

National Space Science Data Center (NSSDC) Data Listing

Satellite and nonsatellite data available from the National Space Science Data Center are listed. The Satellite Data listing includes the spacecraft name, launch date, and an alphabetical list of experiments. The Non-Satellite Data listing contains ground based data, models, computer routines, and composite spacecraft data. The data set name, data form code, quantity of data, and the time space covered are included in the data sets of both listings where appropriate. Geodetic tracking data sets are also included.

Source record↗

NASA NTRS1981

NSSDC Data listing

A convenient reference to space science and supportive data available from the National Space Science Data Center (NSSDC) is provided. Satellite data are organized by NSSDC spacecraft common name. The launch date and NSSDC ID are given. Experiments are listed alphabetically by the principal investigator or team leader. The experiment name and NSSDC ID, data set ID, data set name, data form code, quantity of data, and the time span of the data as verified by NSSDC are shown. Ground-based data, models, computer routines, and composite spacecraft data that are available from NSSDC are listed alphabetically by discipline, source, data type, data content, and data set. The data set name, data form code, quantity of data, and the time span covered where appropriate are included.

Source record↗