Search NASA⌕ Search

SEARCH · Search NASA

Results for “map series”

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

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Lightning and Other Influences On Tropical Tropospheric Ozone: Empirical Studies of Covariation

Tropical and subtropical tropospheric ozone are important radiatively active species, with particularly large effects in the upper third of the troposphere. Temporal variability of O3 has proved difficult to simulate day by day in process models. Thus, individual roles of lightning, biomass burning, and other pollution in providing precursor NO(x), radicals, and chain carriers (CO, hydrocarbons) remain unquantified by simulation, and it is theoretically reasonable that individual roles are magnified by a joint synergy. We use wavelet analysis and Burg-algorithm maximum entropy spectral analyses to describe time-scales and correlation of ozone with proxies for processes controlling its concentration. Our empirical studies link time variations apparent in several datasets: the SHADOZ (Southern Hemisphere Additional Ozonesondes) network stations (Nairobi, Fiji), and auxiliary series with power to explain ozone-determining processes, with some interpretation based on the TTO (Tropical Tropospheric Ozone) product derived from TOMS (the Total Ozone Mapping Spectrometer). The auxiliary series are The OTD/LIS(Optical Transient Detector/Lightning Imaging Sensor) measurements of the lightning NO(x) source, the OLR (Outgoing Longwave Radiation)measurement of high-topped clouds, and standard meteorological variables from the United States NCEP (National Centers for Environmental Prediction) and Data Assimilation Office analyses. Concentrating on equatorial ozone, we compare the statistical evidence on the variability of tropospheric ozone. Important variations occur on approximately two-week, two-month (Madden-Julian Oscillation) and annual scales, and relations with OLR suggest controls associated with continental clouds. Hence we are now using the Lightning Imaging Sensor data set to indicate NO(x) sources. We report initial results defining relative roles of the process mentioned affecting O3 using their covariance properties.

Chatfield, Robert B.↗
DOE OSTI2023

Double Diffusion Maps and their Latent Harmonics for scientific computations in latent space

In this work, we introduce a data-driven approach to building reduced dynamical models through manifold learning; the reduced latent space is discovered using Diffusion Maps (a manifold learning technique) on time series data. A second round of Diffusion Maps on those latent coordinates allows the approximation of the reduced dynamical models. This second round enables mapping the latent space coordinates back to the full ambient space (what is called lifting); it also enables the approximation of full state functions of interest in terms of the reduced coordinates. In our work, we develop and test three different reduced numerical simulation methodologies, either through pre-tabulation in the latent space and integration on the fly or by going back and forth between the ambient space and the latent space. The data-driven latent space simulation results, based on the three different approaches, are validated through (a) the latent space observation of the full simulation through the Nyström Extension formula, or through (b) lifting the reduced trajectory back to the full ambient space, via Latent Harmonics. Latent space modeling often involves additional regularization to favor certain properties of the space over others, and the mapping back to the ambient space is then constructed mostly independently from these properties; here, we use the same data-driven approach to construct the latent space and then map back to the ambient space.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1986

Fifty year canon of solar eclipses: 1986-2035

A reference of moderately detailed eclipse predictions and maps for use by the professional astronomical community is provided. The general characteristics of every solar eclipse and a detailed set of cylindrical project world maps which show the umbral paths of every solar eclipse from 1901 to 2100 are presented. The geodetic path coordinates and local circumstance on the center line, and a series of orthographic projection maps which show the regions of visibility of both partial and central phases for every eclipse from 1986 through 2035 are also provided.

Espenak, Fred↗
NASA NTRS2014

Developing GIOVANNI-based Online Prototypes to Intercompare TRMM-Related Global Gridded-Precipitation Products

New online prototypes have been developed to extend and enhance the previous effort by facilitating investigation of product characteristics and intercomparison of precipitation products in different algorithms as well as in different versions at different spatial scales ranging from local to global without downloading data and software. Several popular Tropical Rainfall Measuring Mission (TRMM) products and the TRMM Composite Climatology are included. In addition, users can download customized data in several popular formats for further analysis. Examples show product quality problems and differences in several monthly precipitation products. It is seen that differences in daily and monthly precipitation products are distributed unevenly in space and it is necessary to have tools such as those presented here for customized and detailed investigations. A simple time series and two area maps allow the discovery of abnormal values of 3A25 in one of the months. An example shows a V-shaped valley issue in the Version 6 3B43 time series and another example shows a sudden drop in 3A25 monthly rain rate, all of which provide important information when the products are used for long-term trend studies. Future plans include adding more products and statistical functionality in the prototypes.

data analysis↗
NASA NTRS2018

Developing Land Use Land Cover Maps for the Lower Mekong Basin to Aid Hydrologic Modeling and Basin Planning

This paper discusses research methodology to develop Land Use Land Cover (LULC) mapsfor the Lower Mekong Basin (LMB) for basin planning, using both MODIS and Landsat satellitedata. The 2010 MODIS MOD09 and MYD09 8-day reflectance data was processed into monthlyNDVI maps with the Time Series Product Tool software package and then used to classify regionallycommon forest and agricultural LULC types. Dry season circa 2010 Landsat top of atmosphere reflectance mosaics were classified to map locally common LULC types. Unsupervised ISODATAclustering was used to derive most LULC classifications. MODIS and Landsat classifications werecombined with GIS methods to derive final 250-m LULC maps for Sub-basins (SBs) 1–8 of the LMB.The SB 7 LULC map with 14 classes was assessed for accuracy. This assessment compared randomlocations for sampled types on the SB 7 LULC map to geospatial reference data such as Landsat RGBs,MODIS NDVI phenologic profiles, high resolution satellite data, and Mekong River Commissiondata (e.g., crop calendars). The SB 7 LULC map showed an overall agreement to reference data of~81%. By grouping three deciduous forest classes into one, the overall agreement improved to ~87%.The project enabled updated regional LULC maps that included more detailed agriculture LULCtypes. LULC maps were supplied to project partners to improve use of Soil andWater AssessmentTool for modeling hydrology and water use, plus enhance LMB water and disaster managementin a region vulnerable to flooding, droughts, and anthropogenic change as part of basin planningand assessment.

land use land cover mapping; SWAT hydrologic model↗
DOE OSTI2023

Refractivity Observations from Radar Phase Measurements: The 22 May 2002 Dryline Case during IHOP Project

The dryline, often associated with the development of severe storms in the Southern Great Plains of the United States of America, is a boundary layer phenomenon that occurs when a warm and moist air mass from the Gulf of Mexico meets a hot and dry air mass from the southwest desert area. An accurate knowledge of the water vapor spatio-temporal variability in the lower part of the atmosphere is crucial for a better understanding of the evolution of the dryline. The tropospheric refractivity, directly related to water vapor content, is a proxy for the water vapor content of the troposphere. It has already been demonstrated that the refractivity and the refractivity vertical gradient can be jointly estimated from radar phase measurements. In fact, it has been shown that using kriging interpolation techniques, accurate refractivity maps within the coverage area of the radar can be obtained with high temporal resolution. In this paper, a detailed analysis of the time series of radar-based refractivity maps obtained during a dryline that occurred on the afternoon of 22 May 2002 during the International H 2 O Project is presented. Comparisons between the time series of radar refractivity maps, obtained with the NCAR S-Pol radar, and the refractivity measurements derived from automatic ground-based weather stations and the AERI instrument, placed at different locations within the coverage area of the NCAR S-Pol radar, demonstrate the accuracy of radar refractivity estimates even for highly variable conditions, both in time and space, in the troposphere. Correlation coefficients higher than 0.95 are obtained in all weather station locations. Regarding the RMSE, errors less than 6 N-units are obtained for all cases, being even as low as 2.92 N-units at some locations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1984

SAS 3 survey of the soft X-ray background

The results of a survey of the soft X-ray sky in the C band (0.10-0.28keV) are reported. The observations were carried out using two independent flow proportional counters on board the SAS 3 X-ray satellite which had a total angular resolution of 2.9 deg FWHM, and a total exposure of 2.2 x 10 to the 4th per sq cm s sr. It is found that C band counting rates were generally inversely correlated with the column density of the neutral hydrogen on all angular scales down to the lowest angular resolution of the detectors. In the region 90-180 deg l and 0-10 deg b, the relation between C-band rates and the column densities of neutral hydrogen was fitted with a residual rms deviation of less than 13 percent by a two-component numerical model of the X-ray background. For the apparent attenuation column density a value of 2.7 x 10 to the 20th per sq cm was obtained. On the basis of a computer simulation of the SAS 3 data, it is shown that the observed clumping of interstellar matter was consistent with the magnitude of spatial fluctuations in the C-band map. When the background rates were subtracted from the survey map, the subsequent map showed foreground emission and absorption features with improved sensitivity and clarity. A series of computer-generated maps incorporating the SAS 3 data is given in an appendix.

Marshall, F. J.↗
NASA NTRS1992

Interannual variability of monthly Southern Ocean sea ice distributions

The interannual variability of the Southern-Ocean sea-ice distributions was mapped and analyzed using data from Nimbus-5 ESMR and Nimbus-7 SMMR, collected from 1973 to 1987. The set of 12 monthly maps obtained reveals many details on spatial variability that are unobtainable from time series of ice extents. These maps can be used as baseline maps for comparisons against future Southern Ocean sea ice distributions. The maps are supplemented by more detailed maps of the frequency of ice coverage, presented in this paper for one month within each of the four seasons, and by the breakdown of these results to the periods covered individually by each of the two passive-microwave imagers.

Parkinson, Claire L.↗
NASA NTRS1993

The fate of captured gas: NGC 3077 and star formation in the M81 system

NGC 3077 is the third largest system in the M81 swarm of galaxies, after the giant spiral M81 itself and dwarf oddity M82. We are interested in exploring the fate of molecular material in NGC 3077. For that reason we have mapped the distribution of J = 1 to 0 CO emission in the central approximately 1 arcmin (1 kpc) diameter region of the galaxy using the Owens Valley millimeter-array with an angular resolution of 6.'7 x 5.'7 (110 pc x 90 pc). The results are shown on the following page as a series of velocity channel maps with delta v = 13 km s(exp -1).

Thronson, Harley A., Jr.↗
NASA NTRSDate not supplied

Improving Access to the GEOS Composition Forecast Model with API Development and Ingestion into Google Earth Engine

The GEOS Composition Forecast (GEOS-CF) model produces forecast and historical estimates of atmospheric composition and meteorology fields, which provide useful insight into air quality issues and events. In a year for which Canadian wildfires created adverse air quality conditions in the eastern United States, access to model fields such as PM2.5 are in high demand. The GEOS-CF team at the NASA Global Modeling and Assimilation Office (GMAO) first developed in-house solutions to improve data access via the CF API, and recently partnered with Google to ingest a collated set of model diagnostics into the Google Earth Engine (GEE) data repository. GEOS-CF model output is also being ingested into AWS storage. Creating these various open access points to GEOS-CF model diagnostics provides the public with an opportunity to easily interact with air quality information. Users are able to use a temporally consistent global grid of air quality fields in machine learning applications, mapping tools, and data informatics. Hosting GEOS-CF forecasts and the historical timeseries of these chemistry and meteorology fields in GEE allows users to create dynamic JavaScript-based air quality applications in the GEE code editor. GEOS-CF users can also access the model output via the GEE Python application programming interface (API), making it easy to perform various analyses with Python. This presentation will show two examples of accessing the GEOS-CF model through GEE. The first is an example application made in the GEE code editor which allows users to view time series plots and downscaled maps of surface level NO2. The second example exhibits using the GEE Python API to create a machine learning model to temporally gap-fill between air quality observations. These examples are an introduction to the many possible benefits of having open access to the GEOS-CF model through multiple platforms.

Callum Wayman↗
NASA NTRSDate not supplied

Improving Access to the GEOS Composition Forecast Model with API Development and Ingestion into Google Earth Engine

The GEOS Composition Forecast (GEOS-CF) model produces forecast and historical estimates of atmospheric composition and meteorology fields, which provide useful insight into air quality issues and events. In a year for which Canadian wildfires created adverse air quality conditions in the eastern United States, access to model fields such as PM2.5 are in high demand. The GEOS-CF team at the NASA Global Modeling and Assimilation Office (GMAO) first developed in-house solutions to improve data access via the CF API, and recently partnered with Google to ingest a collated set of model diagnostics into the Google Earth Engine (GEE) data repository. GEOS-CF model output is also being ingested into AWS storage. Creating these various open access points to GEOS-CF model diagnostics provides the public with an opportunity to easily interact with air quality information. Users are able to use a temporally consistent global grid of air quality fields in machine learning applications, mapping tools, and data informatics. Hosting GEOS-CF forecasts and the historical timeseries of these chemistry and meteorology fields in GEE allows users to create dynamic JavaScript-based air quality applications in the GEE code editor. GEOS-CF users can also access the model output via the GEE Python application programming interface (API), making it easy to perform various analyses with Python. This presentation will show two examples of accessing the GEOS-CF model through GEE. The first is an example application made in the GEE code editor which allows users to view time series plots and downscaled maps of surface level NO 2 . The second example exhibits using the GEE Python API to create a machine learning model to temporally gap-fill between air quality observations. These examples are an introduction to the many possible benefits of having open access to the GEOS-CF model through multiple platforms.

Callum Wayman↗
NASA NTRS1983

Formulas for Precise Transverse Mercator Projection

Transverse mercator projection, surface of Earth or other spheroid is mapped onto cylinder tangent at meridian of longitude. New method performs mapping by means of mathematical series in which higher order terms correct for deviation from exact sphericity. New method yields precise geodetic maps.

Wallis, D. E.↗
NASA NTRS1999

Application of Spaceborne Scatterometer for Mapping Freeze-Thaw State in Northern Landscapes as a Measure of Ecological and Hydrological Processes

Landscape freeze/thaw transitions coincide with marked shifts in albedo, surface energy and mass exchange, and associated snow dynamics. Monitoring landscape freeze/thaw dynamics would improve our ability to quantify the interannual variability of boreal hydrology and river runoff/flood dynamics. The annual duration of frost-free period also bounds the period of photosynthetic activity in boreal and arctic regions thus affecting the annual carbon budget and the interannual variability of regional carbon fluxes. In this study, we use the NASA scatterometer (NSCAT) to monitor the temporal change in the radar backscatter signature across selected ecoregions of the boreal zone. We have measured vegetation tissue temperatures, soil temperature profiles, and micrometeorological parameters in situ at selected sites along a north-south transect extending across Alaska from Prudhoe Bay to the Kenai Peninsula and in Siberia near the Yenisey River. Data from these stations have been used to quantify the scatterometer's sensitivity to freeze/thaw state under a variety of terrain and landcover conditions. Analysis of the NSCAT temporal response over the 1997 spring thaw cycle shows a 3 to 5 dB change in measured backscatter that is well correlated with the landscape springtime thaw process. Having verified the instrument's capability to monitor freeze/thaw transitions, regional scale mosaicked data are applied to derive temporal series of freeze/thaw transition maps for selected circumpolar high latitude regions. These maps are applied to derive areal extent of frozen and thawed landscape and demonstrate the utility of spaceborne radar for operational monitoring of seasonal freeze-thaw dynamics and associated biophysical processes for the circumpolar high latitudes.

McDonald, Kyle↗
DOE OSTI2024

Mixed Delay/Nondelay Embeddings Based Neuromorphic Computing with Patterned Nanomagnet Arrays

Patterned nanomagnet arrays (PNAs) have been shown to exhibit a strong geometrically frustrated dipole interaction. Some PNAs have also shown emergent domain wall dynamics. Previous works have demonstrated methods to physically probe these magnetization dynamics of PNAs to realize neuromorphic reservoir systems that exhibit chaotic dynamical behavior and high-dimensional nonlinearity. These PNA reservoir systems from prior works leverage echo state properties and linear/nonlinear short-term memory of component reservoir nodes to map and preserve the dynamical information of the input time-series data into nondelay spatial embeddings. Such mappings enable these PNA reservoir systems to imitate and predict/forecast the input time series data. However, these prior PNA reservoir systems are based solely on the nondelay spatial embeddings obtained at component reservoir nodes. As a result, they require a massive number of component reservoir nodes, or a very large spatial embedding (i.e., high-dimensional spatial embedding) per reservoir node, or both, to achieve acceptable imitation and prediction accuracy. These requirements reduce the practical feasibility of such PNA reservoir systems. To address this shortcoming, we present a mixed delay/nondelay embeddings-based PNA reservoir system. Our system uses a single PNA reservoir node with the ability to obtain a mixture of delay/nondelay embeddings of the dynamical information of the time-series data applied at the input of a single PNA reservoir node. Our analysis shows that when these mixed delay/nondelay embeddings are used to train a perceptron at the output layer, our reservoir system outperforms existing PNA-based reservoir systems for the imitation of NARMA 2, NARMA 5, NARMA 7, and NARMA 10 time series data, and for the short-term and long-term prediction of the Mackey Glass time series data.

Ti, Changpeng↗
DOE OSTI2023

Reduced Energetic Disorders in Dion–Jacobson Perovskites for Efficient and Spectral Stable Blue LEDs

Metal halide perovskites have witnessed great success in green, red, and near-infrared light-emitting diodes (LEDs), yet blue LEDs still lag behind. Reducing undesired energetic disorders – broad n -phases and halide segregation – is considered as the most critical strategy to further improve the performances. Here, the study reports a newly designed and synthesized di-ammonium ligand with rigid π -conjugated rings and additional methyl groups to construct Dion–Jacobson (DJ) structure. Augmented coordination from the extra ammonium site and increased effective bulkiness from methyl groups lead to better distribution control over conventional mono-ammonium ligands. This enhances the radiative recombination of blue emissions in the film with homogeneous energy landscape and improved surface morphology, as evidenced by a series of imaging and mapping techniques. As a result, it demonstrates DJ perovskite LEDs (PeLEDs) with peak external quantum efficiencies of ≈4% at 484 nm and ≈11% at 494 nm, which are among the top reported for pure DJ phase-based PeLEDs in the corresponding wavelength regions. The results deepen the understanding of regulating energetic disorders in perovskite materials via molecular engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Rapid eco‐phenotypic feedback and the temperature response of biomass dynamics

Biomass dynamics capture information on population dynamics and ecosystem-level processes (e.g., changes in production over time). Understanding how rising temperatures associated with global climate change influence biomass dynamics is thus a pressing issue in ecology. The total biomass of a species depends on its density and its average mass. Consequently, disentangling how biomass dynamics responds to increasingly warm and variable temperatures ultimately depends on understanding how temperature influences both density and mass dynamics. Here, we address this issue by keeping track of experimental microbial populations growing to carrying capacity for 15 days at two different temperatures, and in the presence and absence of temperature variability. We develop a simple mathematical expression to partition the contribution of changes in density and mass to changes in biomass and assess how temperature responses in either one influence biomass shifts. Moreover, we use time-series analysis (Convergent Cross Mapping) to address how temperature and temperature variability influence reciprocal effects of density on mass and vice versa. We show that temperature influences biomass through its effects on density and mass dynamics, which have opposite effects on biomass and can offset each other. We also show that temperature variability influences biomass, but that effect is independent of any effects on density or mass dynamics. Last, we show that reciprocal effects of density and mass shift significantly across temperature regimes, suggesting that rapid and environment-dependent eco-phenotypic dynamics underlie biomass responses. Overall, our results connect temperature effects on population and phenotypic dynamics to explain how biomass responds to temperature regimes, thus shedding light on processes at play in cosmopolitan and abundant microbes as the world experiences increasingly warm and variable temperatures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Towards data-driven constitutive modelling for granular materials via micromechanics-informed deep learning

The analytical description of path-dependent elastic-plastic responses of a granular system is highly complicated because of continuously evolving microstructures and strain localisation within the system undergoing deformation. This study offers an alternative to the current analytical paradigm by developing micromechanics-informed machine-learning based constitutive modelling approaches for granular materials. A set of critical variables associated with the constitutive behaviour of granular materials are identified through an incremental stress-strain relationship analysis. Depending on the strategy to exploit the priori micromechanical knowledge, three different training strategies are explored. The first model uses only the measurable external variables to make stress predictions; the second model utilises a directed graph to link all the external strain sequences and internal microstructural evolution variables into a single prediction model comprised of a series of sub-mappings, and the third model explicitly integrates the physically important non-temporal properties with external strain paths into training through an enhanced Gated Recurrent Unit (GRU). These three models show satisfactory agreement with unseen test specimens based on multi-directional loading cases. The basic features and potential applications of each model are explained. Lastly, the key factors for constitutive training and limitations of the current work are also discussed in detail.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Suppressing the enhancement of stimulated Raman scattering in inhomogeneous plasmas by tuning the modulation frequency of a broadband laser

The stimulated Raman scattering (SRS) instability can inhibit the performance of laser driven inertial confinement fusion (ICF) implosions by scattering light into unwanted directions or by generating hot electrons that preheat the target fuel. In principle, ICF target designs can avoid parameter regimes conducive to large, linear SRS gains. In practice, kinetic inflation—the nonlinear enhancement of SRS due to electron trapping in the excited plasma wave—makes this difficult. Here we show that laser bandwidth in the form of frequency modulation can either decrease or increase the inflationary SRS (iSRS) threshold in inhomogeneous plasmas depending on the maximum chirp of the laser pulse. The threshold, mapped out by a series of particle-in-cell simulations, exhibits a minimum when the frequency change within the pulse cancels the spatial detuning due to density inhomogeneities along the trajectory of the scattered light. In conclusion, by tuning the pump laser parameters away from this minimum, the iSRS threshold can be larger than at zero bandwidth, providing a path to mitigating kinetic inflation in ignition relevant plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗