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NASA NTRS2010

Spheres of Earth: An Introduction to Making Observations of Earth Using an Earth System's Science Approach. Student Guide

Scientists from the Image Science and Analysis Laboratory (ISAL) at NASA's Johnson Space Center (JSC) work with astronauts onboard the International Space Station (ISS) who take images of Earth. Astronaut photographs, sometimes referred to as Crew Earth Observations, are taken using hand-held digital cameras onboard the ISS. These digital images allow scientists to study our Earth from the unique perspective of space. Astronauts have taken images of Earth since the 1960s. There is a database of over 900,000 astronaut photographs available at http://eol.jsc.nasa.gov . Images are requested by ISAL scientists at JSC and astronauts in space personally frame and acquire them from the Destiny Laboratory or other windows in the ISS. By having astronauts take images, they can specifically frame them according to a given request and need. For example, they can choose to use different lenses to vary the amount of area (field of view) an image will cover. Images can be taken at different times of the day which allows different lighting conditions to bring out or highlight certain features. The viewing angle at which an image is acquired can also be varied to show the same area from different perspectives. Pointing the camera straight down gives you a nadir shot. Pointing the camera at an angle to get a view across an area would be considered an oblique shot. Being able to change these variables makes astronaut photographs a unique and useful data set. Astronaut photographs are taken from the ISS from altitudes of 300 - 400 km (~185 to 250 miles). One of the current cameras being used, the Nikon D3X digital camera, can take images using a 50, 100, 250, 400 or 800mm lens. These different lenses allow for a wider or narrower field of view. The higher the focal length (800mm for example) the narrower the field of view (less area will be covered). Higher focal lengths also show greater detail of the area on the surface being imaged. Scientists from the Image Science and Analysis Laboratory (ISAL) at NASA s Johnson Space Center (JSC) work with astronauts onboard the International Space Station (ISS) who take images of Earth. Astronaut photographs, sometimes referred to as Crew Earth Observations, are taken using hand-held digital cameras onboard the ISS. These digital images allow scientists to study our Earth from the unique perspective of space. Astronauts have taken images of Earth since the 1960s. There is a database of over 900,000 astronaut photographs available at http://eol.jsc.nasa.gov . Images are requested by ISAL scientists at JSC and astronauts in space personally frame and acquire them from the Destiny Laboratory or other windows in the ISS. By having astronauts take images, they can specifically frame them according to a given request and need. For example, they can choose to use different lenses to vary the amount of area (field of view) an image will cover. Images can be taken at different times of the day which allows different lighting conditions to bring out or highlight certain features. The viewing angle at which an image is acquired can also be varied to show the same area from different perspectives. Pointing the camera straight down gives you a nadir shot. Pointing the camera at an angle to get a view across an area would be considered an oblique shot. Being able to change these variables makes astronaut photographs a unique and useful data set. Astronaut photographs are taken from the ISS from altitudes of 300 - 400 km (approx.185 to 250 miles). One of the current cameras being used, the Nikon D3X digital camera, can take images using a 50, 100, 250, 400 or 800mm lens. These different lenses allow for a wider or narrower field of view. The higher the focal length (800mm for example) the narrower the field of view (less area will be covered). Higher focal lengths also show greater detail of the area on the surface being imaged. There are four major systems or spheres of Earth. They are: Atmosphere, Biosphere, Hydrosphe, and Litho/Geosphere.

Graff, Paige Valderrama↗

NASA NTRS1982

Cloud cover estimation: Use of GOES imagery in development of cloud cover data base for insolation assessment

The potential of using digital satellite data to establish a cloud cover data base for the United States, one that would provide detailed information on the temporal and spatial variability of cloud development are studied. Key elements include: (1) interfacing GOES data from the University of Wisconsin Meteorological Data Facility with the Jet Propulsion Laboratory's VICAR image processing system and IBIS geographic information system; (2) creation of a registered multitemporal GOES data base; (3) development of a simple normalization model to compensate for sun angle; (4) creation of a variable size georeference grid that provides detailed cloud information in selected areas and summarized information in other areas; and (5) development of a cloud/shadow model which details the percentage of each grid cell that is cloud and shadow covered, and the percentage of cloud or shadow opacity. In addition, comparison of model calculations of insolation with measured values at selected test sites was accomplished, as well as development of preliminary requirements for a large scale data base of cloud cover statistics.

Huning, J. R.↗

NASA NTRS2000

Non-Tidal Non-Seasonal Oceanic Mass Redistribution Estimated from the TOPEX/Poseidon Observation

Topex/Poseidon altimetry data are used to estimate the non-tidal mass redistribution as a function of space-time. The goal is to study the contribution of ocean circulations in the geodynamic effects including Earth's rotational and gravitational variations. We examine the non-seasonal anomalies at monthly sampling rate over the T/P span of eight years, concentrating especially on interannual variabilities. Since the sea-surface height data obtained from altimetry is the combined effect of steric change (primarily thermal effect) and the mass flux, and because the former has zero contribution to the geodynamic effects, one needs to do a so-called steric correction by removing from the altimetry data the steric contributions. We achieve it using multiyear monthly sea-surface temperature maps, together with monthly "climatology" for mixed-layer depth maps for mean-months of the year. We analyze both sets of the altimetry data and the steric correction data using the empirical orthogonal function/principal component analysis (in which we take care of issues associated with the area-weighting and non-zero mean), and examine the most important modes, either globally or regionally. In particular, the ENSO in the tropical Pacific/Indian Oceans exhibits the most prominent pattern. The net mass transport after the steric correction can then be compared with: (1) ocean general circulation model outputs for the same period of time (such as from POCM-4B); (2) non-atmospheric Earth rotation variations obtained from space geodesy data and atmospheric angular momentum data; (3) non-atmospheric low-degree gravitational variations from satellite-laser-ranging observations and global atmospheric data.

Chao, Benjamin F.↗

NASA NTRS1995

Remote-sensing based technique to account for sub-grid scale variability of land surface properties

A method has been presented for the representation of sub-grid scale variability of surface properties within a land surface processes model. The method uses remotely-sensed data to directly or indirectly estimate probability density functions (PDF's) or key surface variables. Application of this technique in a coupled land surface-atmosphere model requires only grid-scale values of the variables of interest, obtained from low-resolution satellite imagery or surface/remote sensing data assimilation. The PDF's of each controlling surface property are superimposed on the respective grid-scale values to simulate sub-grid scale heterogeneity. Sensitivity studies will be carried out to ascertain the relative importance of the heterogeneity of several variables, and the degree to which non-linear property-process interactions impact large-scale fluxes.

Crosson, William L.↗

NASA NTRS1938

Aerodynamic characteristics of a large number of airfoils tested in the variable-density wind tunnel

The aerodynamic characteristics of a large number of miscellaneous airfoils tested in the variable-density tunnel have been reduced to a comparable form and are published in this report for convenient reference. Plots of the standard characteristics are given in tabular form. Included is a tabulation of important characteristics for the related airfoils reported in NACA report 460. This report, in conjunction with NACA report 610, makes available in comparable and convenient form the aerodynamic data for airfoils tested in the variable-density tunnel since January 1, 1931.

Pinkerton, Robert M↗

NASA NTRSDate not supplied

Data Democratization: Challenges and Opportunities

Democratizing Earth data is one of the challenges many organizations around the world face in order to maximize the use of their Earth data for research, applications, education, and societal benefits. For example, at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC), over 1600 global and regional datasets in several NASA Earth science focus areas, including atmospheric composition, water and energy cycles, and climate variability, are archived and distributed to the public. Giovanni, the Geospatial Interactive Online Visualization and Analysis Infrastructure, was developed by GES DISC to facilitate data access and exploration, especially for novice users of Earth science. With Giovanni, users can analyze and visualize over 2000 Earth science variables (e.g., precipitation, aerosol, surface wind) without downloading data, software, the expert understanding of data formats and structures, and coding skills, lowering the barrier to data analysis/comparison by preprocessing and accessing to the data. Results of data analysis and visualization can be accessed in several popular formats (e.g., NetCDF, CSV). As a result of Giovanni's efforts, more than 3000 referral papers have been published in various fields. In spite of this, Giovanni is still difficult to use for some users. For instance, if one searches for "precipitation," it will return over 150 related variables. The question is, which one to use? Furthermore, variables from different data providers (e.g., satellites and models) are named differently with different units, further confusing users, especially those outside the communities. Data democratization is complex and multifaceted. Challenges include service and data discovery, user experiences, visualization, data quality, trustworthiness, and more. In this presentation, we will examine Giovanni as an example of challenges and opportunities in developing data democratization services.

data democratization↗

NASA NTRS2023

Mobile Observations of Ozone and Aerosols in Alabama: Southeastern US Summer Pollution and Coastal Variability

We present a detailed analysis of measurements of ozone (O 3 ) and aerosols collected using multiple platforms and instruments during a 5-day mini-campaign in Alabama, for improving our understanding of the chemistry and air quality in the Southeastern United States. Our study features the first on-road O 3 lidar profiling on highways and the coordinated airborne observations that captured O 3 and aerosol structures associated with synoptic weather conditions, stratospheric intrusions, wildfire smoke transport, and enhancements in urban areas. The Doppler wind lidar data suggest that the vertical structures and variability of O 3 and aerosols at Dauphin Island, a coastal site in the Gulf of Mexico, were related to both the synoptic flow and local-scale land-sea breeze circulation. The onshore gulf breeze, which typically started in the afternoon, helped to quickly dilute air pollutants near the surface, resulting in large gradients toward inland areas. In contrast, gradients were much smaller on days without a gulf breeze. O 3 and humidity were highly anti-correlated in the lower free troposphere, but weakly anti-correlated in the planetary boundary layer (PBL) suggesting more complicated emissions and sink of O 3 in the PBL. Our on-road and airborne measurement strategies to quantify the vertical and horizontal chemical gradients will be useful for future geostationary satellite validation.

Shi Kuang↗

NASA NTRS2000

Optimization of Car Body under Constraints of Noise, Vibration, and Harshness (NVH), and Crash

To be competitive on the today's market, cars have to be as light as possible while meeting the Noise, Vibration, and Harshness (NVH) requirements and conforming to Government-man dated crash survival regulations. The latter are difficult to meet because they involve very compute-intensive, nonlinear analysis, e.g., the code RADIOSS capable of simulation of the dynamics, and the geometrical and material nonlinearities of a thin-walled car structure in crash, would require over 12 days of elapsed time for a single design of a 390K elastic degrees of freedom model, if executed on a single processor of the state-of-the-art SGI Origin2000 computer. Of course, in optimization that crash analysis would have to be invoked many times. Needless to say, that has rendered such optimization intractable until now. The car finite element model is shown. The advent of computers that comprise large numbers of concurrently operating processors has created a new environment wherein the above optimization, and other engineering problems heretofore regarded as intractable may be solved. The procedure, shown, is a piecewise approximation based method and involves using a sensitivity based Taylor series approximation model for NVH and a polynomial response surface model for Crash. In that method the NVH constraints are evaluated using a finite element code (MSC/NASTRAN) that yields the constraint values and their derivatives with respect to design variables. The crash constraints are evaluated using the explicit code RADIOSS on the Origin 2000 operating on 256 processors simultaneously to generate data for a polynomial response surface in the design variable domain. The NVH constraints and their derivatives combined with the response surface for the crash constraints form an approximation to the system analysis (surrogate analysis) that enables a cycle of multidisciplinary optimization within move limits. In the inner loop, the NVH sensitivities are recomputed to update the NVH approximation model while keeping the Crash response surface constant. In every outer loop, the Crash response surface approximation is updated, including a gradual increase in the order of the response surface and the response surface extension in the direction of the search. In this optimization task, the NVH discipline has 30 design variables while the crash discipline has 20 design variables. A subset of these design variables (10) are common to both the NVH and crash disciplines. In order to construct a linear response surface for the Crash discipline constraints, a minimum of 21 design points would have to be analyzed using the RADIOSS code. On a single processor in Origin 2000 that amount of computing would require over 9 months! In this work, these runs were carried out concurrently on the Origin 2000 using multiple processors, ranging from 8 to 16, for each crash (RADIOSS) analysis. Another figure shows the wall time required for a single RADIOSS analysis using varying number of processors, as well as provides a comparison of 2 different common data placement procedures within the allotted memories for each analysis. The initial design is an infeasible design with NVH discipline Static Torsion constraint violations of over 10%. The final optimized design is a feasible design with a weight reduction of 15 kg compared to the initial design. This work demonstrates how advanced methodology for optimization combined with the technology of concurrent processing enables applications that until now were out of reach because of very long time-to-solution.

Kodiyalam, Srinivas↗

NASA NTRS1979

28-Bit serial word simulator/monitor

Modular interface unit transfers data at high speeds along four channels. Device expedites variable-word-length communication between computers. Operation eases exchange of bit information by automatically reformatting coded input data and status information to match requirements of output.

Durbin, J. W.↗

NASA NTRSDate not supplied

NASA POWER: Providing Analysis-Ready, Cloud-Optimized Data for AI /ML Training and Applications in Earth Science

As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.

Neha Khadka↗

NASA NTRS1971

Study of an intraurban travel demand model incorporating commuter preference variables

The model is based on the substantial travel data base for the nine-county San Francisco Bay Area, provided by the Metropolitan Transportation Commission. The model is of the abstract type, and makes use of commuter attitudes towards modes and simple demographic characteristics of zones in a region to predict interzonal travel by mode for the region. A characterization of the STOL/VTOL mode was extrapolated by means of a subjective comparison of its expected characteristics with those of modes characterized by the survey. Predictions of STOL demand were made for the Bay Area and an aircraft network was developed to serve this demand. When this aircraft system is compared to the base case system, the demand for STOL service has increased five fold and the resulting economics show considerable benefit from the increased scale of operations. In the previous study all systems required subsidy in varying amounts. The new system shows a substantial profit at an average fare of $3.55 per trip.

Holligan, P. E.↗

NASA NTRS1985

Interannual variability of Martian weather

Pressure, temperature, imaging, and wind data from the Mutch Memorial Station, the Viking lander located in Mars' subtropics, are used to demonstrate the existence of two disctinct regimes of northern hemisphere winter weather on Mars. One of these regime is characterized by one or more intense global dust storms in which the optical depth reaches about 5 over most of the planet. During these events, traveling baroclinic waves of the winter hemisphere are suppressed. In the other regime, there are no global dust storms, but traveling baroclinic waves are active, and high winds associated with these storms raise large quantities of dust which remain confined to a shallow layer in the northern hemisphere. The strongest winds at the Mutch Memorial Station occur during intense storms in the latter regime.

Leovy, C. B.↗

NASA NTRS1987

Vegetation spatial variability and its effect on vegetation indices

Landsat MSS data were used to simulate low resolution satellite data, such as NOAA AVHRR, to quantify the fractional vegetation cover within a pixel and relate the fractional cover to the normalized difference vegetation index (NDVI) and the simple ratio (SR). The MSS data were converted to radiances from which the NDVI and SR values for the simulated pixels were determined. Each simulated pixel was divided into clusters using an unsupervised classification program. Spatial and spectral analysis provided a means of combining clusters representing similar surface characteristics into vegetated and non-vegetated areas. Analysis showed an average error of 12.7 per cent in determining these areas. NDVI values less than 0.3 represented fractional vegetated areas of 5 per cent or less, while a value of 0.7 or higher represented fractional vegetated areas greater than 80 per cent. Regression analysis showed a strong linear relation between fractional vegetation area and the NDVI and SR values; correlation values were 0.89 and 0.95 respectively. The range of NDVI values calculated from the MSS data agrees well with field studies.

Ormsby, J. P.↗

NASA NTRS2012

Utilizing Chamber Data for Developing and Validating Climate Change Models

Controlled environment chambers (e.g. growth chambers, SPAR chambers, or open-top chambers) are useful for measuring plant ecosystem responses to climatic variables and CO2 that affect plant water relations. However, data from chambers was found to overestimate responses of C fluxes to CO2 enrichment. Chamber data may be confounded by numerous artifacts (e.g. sidelighting, edge effects, increased temperature and VPD, etc) and this limits what can be measured accurately. Chambers can be used to measure canopy level energy balance under controlled conditions and plant transpiration responses to CO2 concentration can be elucidated. However, these measurements cannot be used directly in model development or validation. The response of stomatal conductance to CO2 will be the same as in the field, but the measured response must be recalculated in such a manner to account for differences in aerodynamic conductance, temperature and VPD between the chamber and the field.

Monje, Oscar↗

NASA NTRS2014

Interannual Variation in Phytoplankton Class-specific Primary Production at a Global Scale

Phytoplankton is responsible for over half of the net primary production on earth. The knowledge on the contribution of various phytoplankton groups to the total primary production is still poorly understood. Data from satellite observations suggest that for upwelling regions, photosynthetic rates by microplankton is higher than that of nanoplankton but that when the spatial extent is considered, the production by nanoplankton is comparable or even larger than microplankton. Here, we used the NASA Ocean Biogeochemical Model (NOBM) combined with remote sensing data via assimilation to evaluate the contribution of 4 phytoplankton groups to the total primary production. Globally, diatoms were the group that contributed the most to the total phytoplankton production (approx. 50%) followed by coccolithophores and chlorophytes. Primary production by diatoms was highest in high latitude (>45 deg) and in major upwelling systems (Equatorial Pacific and Benguela system). We assessed the effects of climate variability on the class-specific primary production using global (i.e. Multivariate El Nino Index, MEI) and 'regional' climate indices (e.g. Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO)). Most interannual variability occurred in the Equatorial Pacific and was associated with climate variability. These results provide a modeling and data assimilation perspective to phytoplankton partitioning of primary production and contribute to our understanding of the dynamics of the carbon cycle in the oceans at a global scale.

OBM↗

NASA NTRS1992

TOVS Pathfinder product validation and intercomparison

Validation and intercomparison is an essential part of the Pathfinder program. Since its organization within the International TOVS Working Group, the TOVS community has continuously emphasized this aspect of the product retrieval problem. In the previous sections of this report, the TOVS Pathfinder SWG has recommended a careful and coherent reorganization and archiving of TOVS radiance data, and three distinct pathways for deriving product variables from this TOVS radiance archive. The importance in taking this multiple path approach to creating climate datasets rests in our firm belief that there is now global 'absolute truth' data for any of the derived physical parameters. Each of the selected methods is based upon a different set of assumptions. The challenge in interpreting Pathfinder data is to determine what alterations in the physical attributes of the environment contribute to evidence of global change extracted from observed or derived Pathfinder datasets. The Pathfinder validation and intercomparison activity must include validation of the forward problem, by which one calculates an estimate of upwelling radiance information from given earth and atmospheric data, and validation of the inverse problem, by which one calculates estimates of earth and atmospheric information from given upwelling satellite spectral radiance data.

Source record↗

NASA NTRS1999

Correlations Between Topex Altimeter and Temperature Profile Data in the Equatorial Pacific

Observations of sea-surface heights from satellite altimeters have been a major contributor to monitoring the evolution of the recent major El Nino event. Assimilating altimeter data directly into numerical models only takes advantage of the surface signature provided by the data. However, that surface signature is usually indicative of processes occurring at depth, especially in the equatorial Pacific. In order for assimilation schemes to make maximum use of surface data, it is helpful to have knowledge of how to best extend that data in the vertical to account for that variability. Toward that end, the vertical correlation structure between satellite-observed sea-surface heights and in situ temperature measurements is examined using TOPEX altimeter and TOGA TAO profile data for the period 1993-1998. This time period includes several states of the tropical Pacific, including a perturbed state from 1993-1994, a quiescent state encompassing 1995-1996, and the major ENSO event of 1997-1998. Analyses for each of these periods, as well as the total period will be presented. In addition to analyses at specific depth levels, analyses for particular density surfaces will also be presented.

Adamec, David↗

NASA NTRS1991

Information content of polarimetric SAR data

The information content of the compressed Stoke's matrix data from the Airborne Synthetic Aperture Radar (AIRSAR) is examined in two ways - by measuring how each feature separates classes of terrain in an image, and by measuring how well a classifier performs with and without each feature. In this way, the features may then be ranked in order of information content (or in order of utility to the classifier). Suggestions are made regarding those variables that can be omitted in a data compression scheme or in a future simplified radar system.

Cumming, Ian G.↗