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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Mercurian crater rim heights and some interplanetary comparisons

Rim height (Re) data have been gathered through shadow measurements for 30 fresh mercurian craters with diameters (D) between 2.6 and 39 km. Small mercurian craters (i.e., those less than about 16 km in diameter) have higher rims than do lunar craters of the same diameter; on the basis of Re/D measurements alone, however, mercurian craters larger than about 16 km appear to be indistinguishable from their lunar counterparts (those greater than about 21 km in diameter). Apparent crater depths (Ra, the crater depth measured from the initial target surface) derived from empirical data allude to a decrease in Ra/D with calculated modal impact velocity. This is consistent with the hypothesis that higher impact velocities place the effective depth of burst of the event closer to the surface, thus causing a shallower crater.

Cintala, M. J.↗
NASA NTRS2021

Probabilistic Machine Learning Estimation of Ocean Mixed Layer Depth from Dense Satellite and Sparse In-Situ Observations

The ocean mixed layer plays an important role in the coupling between the upper ocean and atmosphere across a wide range of time scales. Estimation of the variability of the ocean mixed layer is therefore important for atmosphere-ocean prediction and analysis. The increasing coverage of in situ Argo profile data allows for an increasingly accurate analysis of the mixed layer depth (MLD) variability associated with deviations from the seasonal climatology. However, sampling rates are not sufficient to fully resolve subseasonal (<90 day) MLD variability. Yet, many multivariate observations-based analyses include implicit modeled subseasonal MLD variability. One analysis method is optimal interpolation of in situ data, but the interior analysis can be improved by leveraging surface data with regression or variational approaches. Here, we demonstrate how machine learning methods and satellite sea surface temperature, salinity, and height facilitate MLD estimation in a pilot study of two regions: the mid-latitude southern Indian and the eastern equatorial Pacific Oceans. We construct multiple machine learning architectures to produce weekly 1/2° gridded MLD anomaly fields (relative to a monthly climatology) with uncertainty estimates. We test multiple traditional and probabilistic machine learning techniques to compare both accuracy and probabilistic calibration. We validate our methodology by applying it to ocean model simulations. We find that incorporating sea surface data through a machine learning model improves the performance of spatiotemporal MLD variability estimation compared to optimal interpolation of Argo observations alone. These preliminary results are a promising first step for the application of machine learning to MLD prediction.

Machine Learning↗
NASA NTRS2000

Vertical Distributions of PH3 in Saturn from Observations of Its 1-0 and 3-2 Rotational Lines

Far-infrared Fourier-transform spectrometer measurements of the 1-0 and 3-2 PH3 transitions in Saturn's disk near 267 and 800 GHz (8.9 and 26.7/cm), respectively, were analyzed simultaneously to derive a global mean profile for the PH3 vertical mixing ratio between 100 and 600 mbar total pressure. The far-infrared spectrum is relatively free from spectral interlopers, suffers minimal absorption or scattering by atmospheric particulates, and contains intrinsically weak PH3 lines that are sensitive to a range of atmospheric depths. The combined spectra are inconsistent with a uniform tropospheric mixing ratio, even with a stratospheric cut-off. They are consistent with a volume mixing ratio of PH3 that drops from 1.2 x 10(exp -5) at 645 mbar pressure to a value of 4.1 x 10(exp -7) at 150 mbar pressure, a decrease that is linear is log abundance vs log pressure. The mixing ratio could drop even more quickly at atmospheric pressures below 150 mbar and still be consistent with the data. The mixing ratio may well remain constant with depth for pressures above 630 mbar. The maximum PH3 mixing ratio in this model is consistent with a [P]/[H] ratio in the deep atmosphere that is about a factor of 10 higher than solar composition. Such a model is consistent with rapid mixing up to the radiative-convective boundary and transport by, for example, vertical waves just above this boundary. In the best fitting model, the eddy diffusion coefficient is approximately 10(exp 4) sq cm near 630 mbar, and it must increase with altitude. The predominant PH3 loss mechanisms are direct photolysis by UV radiation and scavenging by H atoms produced by the photolysis.

Orton, G. S.↗
NASA NTRS2024

Enabling Advanced Snow Physics within Land Surface Models Through an Interoperable Model-Physics Coupling Framework

Accurate estimation of snow accumulation and melt is a critical part of decision-making in snow-dominated watersheds. In this study, we demonstrate a flexible methodology to couple a detailed snow model, Crocus, separately to two different land surface models (LSMs), Noah-MP and Noah. The original LSMs and the coupled models (Noah-MP-Crocus and Noah-Crocus) are used to simulate snow depth, snow water equivalent, and other water and energy states and fluxes. The results of simulations are compared against a wide range of independent gridded and point scale reference datasets. Our results show that coupling the detailed snow model, Crocus, with the LSMs improves the snow depth and snow water equivalent relative to independent observations. Overall, larger improvements are obtained with coupling Crocus to the Noah LSM, with the coupled Noah-Crocus configuration reducing the RMSE and bias of snow depth from 2-12% and 57-75%, respectively, relative to Snow Data Assimilation System (SNODAS) and snow product from the University of Arizona. On the other hand, smaller improvements are obtained by coupling Crocus with Noah-MP. The Coupled Noah-MP-Crocus reduces the snow depth bias but slightly degrades the RMSE of snow depth and snow water equivalent. The corresponding impacts in other water budget terms such as evapotranspiration, soil moisture, and streamflow, however, are mixed, pointing to the significant need to improve the coupling assumptions of these processes within land models. Overall, the interoperable coupling framework demonstrated here offers the opportunity to include more detailed snow physics and processes, and to advance data assimilation systems through improved exploitation of information from snow remote sensing instruments.

Snow model↗
NASA NTRS1975

Nearshore coastal mapping

Two test sites of different water quality and bottom topography were used to test for maximum water depth penetration using the Skylab S-192 MSS for measurement of nearshore coastal bathymetry. Sites under investigation lie along the Lake Michigan coastline where littoral transport acts to erode sand bluffs and endangers developments along 1,200 miles of shore, and on the west coast of Puerto Rico where unreliable shoal location and depth information constitutes a safety hazard to navigation. The S-192 and S-190A and B provide data on underwater features because of water transparency in the blue/green portion of the spectrum. Depth of 20 meters were measured with the S-192 in the Puerto Rico test site. The S-190B photography with its improved spatial resolution clearly delineates the triple sand bar topography in the Lake Michigan test site. Several processing techniques were employed to test for maximum depth measurement with least error. The results are useful for helping to determine an optimum spectral bandwidth for future space sensors that will increase depth measurements for different water attenuation conditions where a bottom reflection is detectable.

Polcyn, F. C.↗
NASA NTRS2011

Adaptive System Modeling for Spacecraft Simulation

This invention introduces a methodology and associated software tools for automatically learning spacecraft system models without any assumptions regarding system behavior. Data stream mining techniques were used to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). Evaluation on historical ISS telemetry data shows that adaptive system modeling reduces simulation error anywhere from 50 to 90 percent over existing approaches. The purpose of the methodology is to outline how someone can create accurate system models from sensor (telemetry) data. The purpose of the software is to support the methodology. The software provides analysis tools to design the adaptive models. The software also provides the algorithms to initially build system models and continuously update them from the latest streaming sensor data. The main strengths are as follows: Creates accurate spacecraft system models without in-depth system knowledge or any assumptions about system behavior. Automatically updates/calibrates system models using the latest streaming sensor data. Creates device specific models that capture the exact behavior of devices of the same type. Adapts to evolving systems. Can reduce computational complexity (faster simulations).

Thomas, Justin↗
NASA NTRS1990

Cirrus cloud properties derived from satellite radiances during FIRE

The sensitivity of the retrieved cloud properties to the cloud radiative transfer model is explored using satellite data taken during the First ISCCP Regional Experiment (FIRE). Several different scattering phase functions are used to create a set of models which relate cloud optical depth to bidirectional reflectance. These models are employed in the analysis of data taken nearly simultaneously from two different satellites over regions containing cirrus clouds. The interpretation of the reflectances using the various models is evaluated through intercomparisons of the results from both satellites and through comparisons with lidar data. The preliminary results indicate that, compared to water-droplet scattering models, ice-crystal scattering models provide a more precise and physically consistent interpretation of visible and infrared radiances for determining cirrus cloud properties.

Minnis, Patrick↗
NASA NTRS1996

Hierarchical and Parallelizable Direct Volume Rendering for Irregular and Multiple Grids

A general volume rendering technique is described that efficiently produces images of excellent quality from data defined over irregular grids having a wide variety of formats. Rendering is done in software, eliminating the need for special graphics hardware, as well as any artifacts associated with graphics hardware. Images of volumes with about one million cells can be produced in one to several minutes on a workstation with a 150 MHz processor. A significant advantage of this method for applications such as computational fluid dynamics is that it can process multiple intersecting grids. Such grids present problems for most current volume rendering techniques. Also, the wide range of cell sizes (by a factor of 10,000 or more), which is typical of such applications, does not present difficulties, as it does for many techniques. A spatial hierarchical organization makes it possible to access data from a restricted region efficiently. The tree has greater depth in regions of greater detail, determined by the number of cells in the region. It also makes it possible to render useful 'preview' images very quickly (about one second for one-million-cell grids) by displaying each region associated with a tree node as one cell. Previews show enough detail to navigate effectively in very large data sets. The algorithmic techniques include use of a kappa-d tree, with prefix-order partitioning of triangles, to reduce the number of primitives that must be processed for one rendering, coarse-grain parallelism for a shared-memory MIMD architecture, a new perspective transformation that achieves greater numerical accuracy, and a scanline algorithm with depth sorting and a new clipping technique.

Wilhelms, Jane↗
NASA NTRS1982

Mars - Gravity data analysis of the crater Antoniadi

Topography and gravity information for this 370-km crater are analyzed to determine a depth of compensation with an Airy isostatic model. A least squares fit to the gravity profile gives an estimate of 115 km for the depth of compensation. It is noted that Antoniadi is the only large Martian crater for which both topographic and gravity data are available for analysis. The goal here is to reduce these geophysical data for additional information on the internal structure of Mars. The results show that if Antoniadi had fully isostatically adjusted, the additional mass material would have been about 100 km below the surface. This is regarded as another data point for geophysicists developing the internal structure of Mars.

Sjogren, W. L.↗
NASA NTRS2011

Global Assimilation of Multi-Sensor Snow Observations for Improved Characterization of Snow Processes

Snow conditions on the land surface are recognized to be key components of the global hydrological cycle as they play a critical role in the determination of local and regional climate. In many mid-latitude and high-latitude regions, the seasonal water storage and associated spring snowmelt dominate the local hydrology. The contribution to the runoff and moisture conditions from snow is vital in supporting agriculture and in determining water resources management practices. Consequently, accurate characterization of snow properties becomes important for both end-use applications and weather and climate research. Recently a joint effort between the u.S. Air Force and NASA has enabled a blended, multi-sensor snow product known as the AFWA NASA Snow Algorithm (ANSA). This global snow dataset has been generated by utilizing the Earth Observation System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer for EOS (AMSR-E) datasets. ANSA product includes estimates of snow cover extent, snow water equivalent (SWE) and SWE-derived snow depth fields. The MODIS-based products enable snow cover mappings under cloud-free conditions whereas the passive microwave data from AMSR-E provides measurements under cloudy conditions. These remotely-sensed snow observations are further augmented with the information from ground-based snow measurements through data fusion techniques. The resulting ANSA products are employed in the NASA Land Information System (LIS) data assimilation framework, which provides a comprehensive environment for integrating community land surface models, ground and satellite-based observations, and ensemble-based data assimilation tools. LIS incorporates the multisensor ANSA snow retrievals with the land surface model estimates to generate spatially and temporally continuous estimates of snow states, through data assimilation. A suite of experiments to assimilate ANSA snow cover, SWE and snow depth estimates with different land surface models in LIS are conducted and the resulting estimates of snow conditions are evaluated against a number of in-situ observational datasets, over several regions of the world. These evaluations are used to compare and contrast the advantages and disadvantages of these multi-sensor snow observations.

Kumar, Sujay↗
NASA NTRS2015

Comparison of Venous Return Characteristics with Right Ventricular Mechanics During Cephalic Fluid Shift

For my summer internship project, I organized a pilot study to analyze the effects of a cephalic fluid shift on venous return and right ventricular mechanics to increase right ventricular and venous knowledge. To accomplish this pilot study, I wrote a testing protocol, obtained Institutional Review Board (IRB) approval, completed subject payment forms, lead testing sessions, and analyzed the data. This experiment used -20deg head down tilt (20 HDT) as the ground based simulation for the fluid shift that occurs during spaceflight and compared it to data obtained from the seated and supine positions. Using echocardiography, data was collected for the right ventricle, hepatic vein, internal jugular vein, external jugular vein, and inferior vena cava. Additionally, non-invasive venous pressure measurements, similar to those soon to be done in-orbit, were collected. It was determined that the venous return from below the heard is increased during 20 HDT, which was supported by increased hepatic vein velocities, increased right ventricular inflow, and increased right ventricular strain at 20 HDT relative to seated values. Jugular veins in the neck undergo an increase in pressure and area, but no significant increase in flow, relative to seated values when a subject is tilted 20 HDT. Contrary to the initial expectations based on this jugular flow, there was no significant increase in central venous pressure, as evidenced by no change in Doppler indices for right arterial pressure or inferior vena cava diameter. It is suspected that these differences in pressure are due to the hydrostatic pressure indifference point shifting during tilt; there is a potential for a similar phenomenon with microgravity. This data will hopefully lead to a more in-depth understanding of the response of the body to microgravity and how those relate to the previously mentioned cardiovascular risk of fluid shift that is associated with spaceflight. These results were presented in greater detail to the Cardiovascular Laboratory and the Space Life Science Summer Institute, which helped me prepare for future graduate school research presentations. This internship allowed me to apply and expand the anatomy, physiology, and mechanics information I learned during my undergraduate degree in Biomedical Engineering to the cardiovascular system with the unique zero gravity perspective. Additionally, I was able to develop skills with data analysis techniques involving speckle tracking for ventricular strain and Doppler waveforms for blood velocities. Additionally, I was able to expand upon my previous work in the Cardiovascular Laboratory by writing a literature review on a data analysis project I completed last summer. Ultimately, this internship and venous relationship comparison project provided me with a significant learning experience and additional skill sets, which are applicable to my goals of attaining a Ph.D. in biomedical engineering with a focus on tissue engineering and the cardiovascular system.

Elliott, Morgan↗
NASA NTRS1987

Polar stratospheric optical depth observed between 1978 and 1985

Observations of the stratospheric optical depth at 1.0 micron obtained for high latitudes are presented for a 7-year period. Weekly averaged data determined from measurements made by the Stratospheric Aerosol Measurement experiment from October 1978-1985 show that the overall yearly values in both polar regions are controlled by volcanic perturbations, with most volcanic effects being experienced in Arctic latitudes. Conservatively, peak values found in the Antarctic region were approximately 0.02 and in the Arctic region about 0.55. Probable values for these regions are estimated to be 0.26 and 0.11, respectively. The weekly averaged data also show the seasonal fluctuations due to microphysical and dynamical processes. Comparison of the optical depth record with a weekly averaged 50-mbar temperature record indicates that polar stratospheric clouds are present in the southern high latitudes each year near this level from early June to early September. A depression observed in the optical depth record each austral spring season is believed to be the result of the downward displacement of particles caused by subsidence and sedimentation during the course of winter. Following the breakup of the vortex, optical depth values increase as aerosol is transported poleward. These features are noted to be present in the Arctic region as well, but on a smaller scale because of the satellite sampling methodology and the averaging scheme employed.

Mccormick, M. P.↗
NASA NTRS2006

Aerosol Lidar and MODIS Satellite Comparisons for Future Aerosol Loading Forecast

Knowledge of the concentration and distribution of atmospheric aerosols using both airborne lidar and satellite instruments is a field of active research. An aircraft based aerosol lidar has been used to study the distribution of atmospheric aerosols in the California Central Valley and eastern US coast. Concurrently, satellite aerosol retrievals, from the MODIS (Moderate Resolution Imaging Spectroradiometer) instrument aboard the Terra and Aqua satellites, were take over the Central Valley. The MODIS Level 2 aerosol data product provides retrieved ambient aerosol optical properties (e.g., optical depth (AOD) and size distribution) globally over ocean and land at a spatial resolution of 10 km. The Central Valley topography was overlaid with MODIS AOD (5x5 sq km resolution) and the aerosol scattering vertical profiles from a lidar flight. Backward air parcel trajectories for the lidar data show that air from the Pacific and northern part of the Central Valley converge confining the aerosols to the lower valley region and below the mixed layer. Below an altitude of 1 km, the lidar aerosol and MODIS AOD exhibit good agreement. Both data sets indicate a high presence of aerosols near Bakersfield and the Tehachapi Mountains. These and other results to be presented indicate that the majority of the aerosols are below the mixed layer such that the MODIS AOD should correspond well with surface measurements. Lidar measurements will help interpret satellite AOD retrievals so that one day they can be used on a routine basis for prediction of boundary layer aerosol pollution events.

DeYoung, Russell↗
NASA NTRS2003

Time-Variable Gravity Signal due to Extratropic Pacific Water Mass Redistribution

Using the satellite-laser-ranging (SLR) data, Cox and Chao [2002] reported the detection of a large post-1998 anomaly (in the form of a positive jump) in the time series of Earth s lowest-degree gravity harmonic 52, or the dynamic oblateness. Among several groups now examining the mass redistribution in the global geophysical fluids in search of the cause(s), we report here a temporally coinciding anomalies found in the extratropic north + south Pacific basins. Clearly seen in the leading EOFPC mode for extratropic Pacific, these anomalies occurred in sea-surface height, sea-surface temperature, and temperature- and salinity-depth profiles. We based our analysis on two different data sources: TOPEX/Poseidon altimetry, and the ECCO ocean general circulation model output assimilating T/P data. The magnitude of these changes, when converted to equivalent J2 change, appears to be a few times too small to explain the observed J2 directly. These findings, and the fact that the anomalies occurred following the strong 1997-98 El Nino, suggest strong geophysical connection of the interannual-to-decadal variation of 52 with the Pacific Decadal Oscillation (PDO) and the ultimate global-change processes that cause PDO. More work is underway, and additional independent data sources are examined, paying close attention to the fact that the J2 anomaly has been reversing back to normal since 2001. These include: (1) cryospheric contributions (melting of glaciers and ice sheets); (2) land hydrological contributions; (3) polar sea influences ( e g , via deep flow); (4) fluid flow in Earth's core; (5) time-variable gravity signals from SLR in higher harmonic degree/order, including J3,J4, (2,1), and (2,2) coefficients, considering their lower signal-to-noise ratios; (6) Earth rotation data in terms of length-of-day and polar motion.

Chao, B. F.↗
NASA NTRSDate not supplied

RSP Data Status, Updates and Plans from the Team

•All radiance (L1C), aerosol and cloud (L2) products are in the archive. •Revised calibration performed at GSFC in July 2021 applied to reprocessing. •Clouds have smaller drops and higher optical depths (larger droplet number concentrations) in winter than in summer. Cloud top droplet size distributions tend to be narrow with roughly 80% having an effective variance of less than 0.07. This is relevant to how well bulk auto-conversion parameterizations are likely to work at cloud top (order of magnitude effects) and also to assumptions used in the remote sensing of droplet number (~ 10% effect). Real refractive index and effective radius retrievals are consistent with hygroscopic growth of aerosols Real refractive index and effective variance retrievals imply the presence of an insoluble fraction of aerosols Future work on clouds will look at differences in cloud top drizzle formation and auto-conversion rates between the different campaigns and at how well mixed phase clouds can be detected (if at all) from sensors such as VIIRS and PACE OCI.

Research Scanning Polarimeter↗
NASA NTRS2015

Completing the Feedback Loop: The Impact of Chlorophyll Data Assimilation on the Ocean State

In anticipation of the integration of a full biochemical model into the next generation GMAO coupled system, an intermediate solution has been implemented to estimate the penetration depth (1Kd_PAR) of ocean radiation based on the chlorophyll concentration. The chlorophyll is modeled as a tracer with sources-sinks coming from the assimilation of MODIS chlorophyll data. Two experiments were conducted with the coupled ocean-atmosphere model. In the first, climatological values of Kpar were used. In the second, retrieved daily chlorophyll concentrations were assimilated and Kd_PAR was derived according to Morel et al (2007). No other data was assimilated to isolate the effects of the time-evolving chlorophyll field. The daily MODIS Kd_PAR product was used to validate the skill of the penetration depth estimation and the MERRA-OCEAN re-analysis was used as a benchmark to study the sensitivity of the upper ocean heat content and vertical temperature distribution to the chlorophyll input. In the experiment with daily chlorophyll data assimilation, the penetration depth was estimated more accurately, especially in the tropics. As a result, the temperature bias of the model was reduced. A notably robust albeit small (2-5 percent) improvement was found across the equatorial Pacific ocean, which is a critical region for seasonal to inter-annual prediction.

MERRA-OCEAN↗
NASA NTRS1975

Temperatures and thermophysical properties of the lunar outermost layer

Comparisons of calculated diurnal and eclipse temperatures of the lunar outermost layer are made with earth-based infrared and millimeter data. The thermophysical model upon which the calculations are based incorporates variable physical properties. The thermal conductivity is a function of both density (depth) and temperature; the specific heat is a function of temperature; the density is a function of depth; and the dielectric constant and loss tangent are functions of density (depth). Laboratory measurements and Apollo-sample results are incorporated in the property data. Calculational cases are based largely upon different density profiles. The model is consistent with the data, and the comparisons of theoretical and observational temperatures are very favorable. For such comparisons, further sophistication of the thermophysical model of the outermost layer is probably not justified.

Jones, W. P.↗
NASA NTRS2012

The Algorithm Theoretical Basis Document for the GLAS Atmospheric Data Products

The purpose of this document is to present a detailed description of the algorithm theoretical basis for each of the GLAS data products. This will be the final version of this document. The algorithms were initially designed and written based on the authors prior experience with high altitude lidar data on systems such as the Cloud and Aerosol Lidar System (CALS) and the Cloud Physics Lidar (CPL), both of which fly on the NASA ER-2 high altitude aircraft. These lidar systems have been employed in many field experiments around the world and algorithms have been developed to analyze these data for a number of atmospheric parameters. CALS data have been analyzed for cloud top height, thin cloud optical depth, cirrus cloud emittance (Spinhirne and Hart, 1990) and boundary layer depth (Palm and Spinhirne, 1987, 1998). The successor to CALS, the CPL, has also been extensively deployed in field missions since 2000 including the validation of GLAS and CALIPSO. The CALS and early CPL data sets also served as the basis for the construction of simulated GLAS data sets which were then used to develop and test the GLAS analysis algorithms.

Palm, Stephen P.↗