SEARCH · Engineering Papers

Results for “height estimation”

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.

SourceResearch connectionFrom yearThrough year

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

At least 919 records · Page 51

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Divide and conquer: separating the two probabilities in seismic phase picking

There are two fundamental probabilities in the seismic phase picking process—the probability of the existence of a seismic phase (detection probability) and the probability associated with the phase arrival time estimation (timing probability). The nearly ubiquitous approach in developing deep learning phase picking models is to use a kernel, such as a truncated Gaussian, to mask the labelled phase arrival time and train a segmentation model. Once a model is trained, the times of the peaks in the output are taken as phase arrival times (picks), and the height of the peaks are taken as ‘probability’ of the picks. Here, we show that this ‘probability’ represents neither the detection nor the timing probability because this approach forces the output to follow the shape of the kernel. We introduce an approach using two models to estimate these two distinct probabilities. We use a binary classifier with a calibrated confidence to address the detection probability and a multiclass classifier to obtain a probability mass function to address the timing probability. This new approach can make the deep learning-based phase picking process more interpretable and provide options to logically control seismic monitoring workflows.

58 GEOSCIENCES↗

NASA NTRS2008

Comparison of CERES-MODIS Stratus Cloud Properties with Ground-Based Measurements at the DOE ARM Southern Great Plains Site

Overcast stratus cloud properties derived for the Clouds and the Earth's Radiant Energy system (CERES) Project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site from March 2000 through December 2004. Retrievals from ARM surface-based data were averaged over a 1-hour interval centered at the time of each satellite overpass, and the CERES-MODIS cloud properties were averaged within a 30-km x 30 km box centered on the ARM SGP site. Two datasets were analyzed: all of the data (ALL) which include multilayered, single-layered, and slightly broken stratus decks and a subset, single-layered unbroken decks (SL). The CERES-MODIS effective cloud heights were determined from effective cloud temperature using a lapse rate method with the surface temperature specified as the 24-h mean surface air temperature. For SL stratus, they are, on average, within the ARM radar-lidar estimated cloud boundaries and are 0.534 +/- 0.542 km and 0.108 +/- 0.480 km lower than the cloud physical tops and centers, respectively, and are comparable for day and night observations. The mean differences and standard deviations are slightly larger for ALL data, but not statistically different to those of SL data. The MODIS-derived effective cloud temperatures are 2.7 +/- 2.4 K less than the surface-observed SL cloud center temperatures with very high correlations (0.86-0.97). Variations in the height differences are mainly caused by uncertainties in the surface air temperatures, lapse rates, and cloud-top height variability. The biases are mainly the result of the differences between effective and physical cloud top, which are governed by cloud liquid water content and viewing zenith angle, and the selected lapse rate, -7.1 K km(exp -1). Based on a total of 43 samples, the means and standard deviations of the differences between the daytime Terra and surface retrievals of effective radius r(sub e), optical depth, and liquid water path for SL stratu are 0.1 +/- 1.9 micrometers (1.2 +/- 23.5%), -1.3 +/- 9.5 (-3.6 +/-26.2%), and 0.6 +/- 49.9 gm (exp -2) (0.3 +/- 27%), respectively, while the corresponding correlation coefficients are 0.44, 0.87, and 0.89. For Aqua, they are 0.2 +/- 1.9 micrometers (2.5 +/- 23.4%), 2.5 +/- 7.8 (7.8 +/- 24.3%), and 28.1 +/- 52.7 gm (exp -2) (17.2 +/- 32.2%), as well as 0.35, 0.96, and 0.93 from a total of 21 cases. The results for ALL cases are comparable. Although a bias in R(sub e) was expected because the satellite retrieval of effective radius only represents the top of the cloud, the surface-based radar retrievals revealed that the vertical profile of r(sub e) is highly variable with smaller droplets occurring at cloud top in some cases. The larger bias in optical depth and liquid water path for Aqua is due, at least partially, to differences in the Terra and Aqua MODIS visible channel calibrations. methods for improving the cloud-top height and microphysical property retrievals are suggested.

Dong, Xiquan↗

NASA NTRS2012

Mean Dynamic Topography of the Arctic Ocean

ICESat and Envisat altimetry data provide measurements of the instantaneous sea surface height (SSH) across the Arctic Ocean, using lead and open water elevation within the sea ice pack. First, these data were used to derive two independent mean sea surface (MSS) models by stacking and averaging along-track SSH profiles gathered between 2003 and 2009. The ICESat and Envisat MSS data were combined to construct the high-resolution ICEn MSS. Second, we estimate the 5.5-year mean dynamic topography (MDT) of the Arctic Ocean by differencing the ICEn MSS with the new GOCO02S geoid model, derived from GRACE and GOCE gravity. Using these satellite-only data we map the major features of Arctic Ocean dynamical height that are consistent with in situ observations, including the topographical highs and lows of the Beaufort and Greenland Gyres, respectively. Smaller-scale MDT structures remain largely unresolved due to uncertainties in the geoid at short wavelengths.

Arctic Ocean↗

DOE OSTI2024

Deep-learning-derived planetary boundary layer height from conventional meteorological measurements

Abstract. The planetary boundary layer (PBL) height (PBLH) is an important parameter for various meteorological and climate studies. This study presents a multi-structure deep neural network (DNN) model, which can estimate PBLH by integrating the morning temperature profiles and surface meteorological observations. The DNN model is developed by leveraging a rich dataset of PBLH derived from long-standing radiosonde records augmented with high-resolution micro-pulse lidar and Doppler lidar observations. We access the performance of the DNN with an ensemble of 10 members, each featuring distinct hidden-layer structures, which collectively yield a robust 27-year PBLH dataset over the southern Great Plains from 1994 to 2020. The influence of various meteorological factors on PBLH is rigorously analyzed through the importance test. Moreover, the DNN model's accuracy is evaluated against radiosonde observations and juxtaposed with conventional remote sensing methodologies, including Doppler lidar, ceilometer, Raman lidar, and micro-pulse lidar. The DNN model exhibits reliable performance across diverse conditions and demonstrates lower biases relative to remote sensing methods. In addition, the DNN model, originally trained over a plain region, demonstrates remarkable adaptability when applied to the heterogeneous terrains and climates encountered during the GoAmazon (Green Ocean Amazon; tropical rainforest) and CACTI (Cloud, Aerosol, and Complex Terrain Interactions; middle-latitude mountain) campaigns. These findings demonstrate the effectiveness of deep learning models in estimating PBLH, enhancing our understanding of boundary layer processes with implications for improving the representation of PBL in weather forecasting and climate modeling.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Deep-Learning-derived Boundary Layer Height from Meteorological Data over the SGP, GOAMAZON, CACTI

The planetary boundary-layer (PBL) height (PBLH) is an important parameter for various meteorological and climate studies. This study presents a multi-structure deep neural network (DNN) model, designed to estimate PBLH by integrating morning temperature profiles with surface meteorological observations. The DNN model is developed by leveraging a rich data set of PBLH derived from long-standing radiosonde records and augmented with high-resolution micropulse lidar and Doppler lidar observations. We access the performance of the DNN with an ensemble of 10 members, each featuring distinct hidden layer structures, which collectively yield a robust 27-year PBLH data set over the Southern Great Plains from 1994 to 2020. The influence of various meteorological factors on PBLH is rigorously analyzed through the importance test. Moreover, the DNN model's accuracy is evaluated against radiosonde observations and juxtaposed with conventional remote-sensing methodologies, including Doppler lidar, ceilometer, Raman lidar, and micropulse lidar. The DNN model exhibits reliable performance across diverse conditions and demonstrates lower biases relative to remote-sensing methods. In addition, the DNN model, originally trained over a plain region, demonstrates remarkable adaptability when applied to the heterogeneous terrains and climates encountered during the GoAmazon (tropical rainforest) and CACTI (middle-latitude mountain) campaigns. These findings demonstrate the effectiveness of deep learning models in estimating PBLH, enhancing our understanding of boundary-layer dynamics with implications for enhancing the representation of PBL in weather forecasting and climate modeling.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1974

Reflectance of vegetation, soil, and water

The author has identified the following significant results. Iron deficient and normal grain sorghum plants were sufficiently different spectrally in ERTS-1 band 5 CCT data to detect chlorotic sorghum areas 2.8 acres (1.1 hectares) or larger in size in computer printouts of the MSS data. The ratio of band 5 to band 7 or band 7 minus band 5 relates to vegetation ground cover conditions and helps to select training samples representative of differing vegetation maturity or vigor classes and to estimate ground cover or green vegetation density in the absence of ground information. The four plant parameters; leaf area index, plant population, plant cover, and plant height explained 87 to 93% of the variability in band 6 digital counts and from 59 to 90% of the variation in bands 4 and 5. A ground area 2244 acres in size was classified on a pixel by pixel basis using simultaneously acquired aircraft support and ERTS-1 data. Overall recognition for vegetables, immature crops and mixed shrubs, and bare soil categories was 64.5% for aircraft and 59.6% for spacecraft data, respectively. Overall recognition results on a per field basis were 61.8% for aircraft and 62.8% for ERTS-1 data.

Wiegand, C. L.↗

NASA NTRS1981

Characteristics of rain and rain systems

The description and measurement of the macroscopic and microscopic characteristics of rain and rain systems are discussed. The statistical relationships of these characteristics and their effect on polarization and attenuation are considered. Macroscopic characteristics include the size, distribution, and movements of rain cells, the height of melting layers, and the presence of ice crystals. Microscopic characteristics include the size distribution, density, and oblateness of rain drops and ice crystals. The estimation of a major propagation effect, specific attenuation, is described.

Source record↗

NASA NTRS1991

Satellite observations of polar lows by SSM/I, Geosat and TOVS

Satellite observations in high-latitude regions were used to detect polar lows and track their propagation and evolution. The Special Sensor Microwave/Imager (SSM/I) provided estimates of surface wind speed, integrated cloud liquid water, and water vapor contents over ocean; the Geosat radar altimeter measured surface wind speed and significant wave height; the TIROS-N Operational Vertical Sounder (TOVS) allowed the determination of temperature and humidity profiles in the atmosphere, as well as cloud information (cloud top pressure and temperature). The detection of polar lows at a very early stage, and their development, propagation, and decay is presented for a specific case occurring in the Norwegian Sea on 23-24 January 1988, using a combination of these three instruments, namely a passive and an active microwave sensor, and a vertical sounder (19 infrared, 1 visible, and 4 microwave channels). Advantage is taken of the time and coverage differences between these three satellite sensors for the observation of polar lows. A discussion of the results is given.

Claud, C.↗

NASA NTRS1995

Yohkoh/SXT x-ray synoptic maps of coronal brightness and temperature

The Yohkoh soft X-ray telescope (SXT) records on the order of 50 solar images per day in two different color filters. These provide material for the generation of synoptic maps, which compress the 3-dimensional data cube into two dimensions. We are creating synoptic maps from strips of data both at disk center and at different heights, including limb maps that are analogous to those produced by ground-based coronagraphs. The ratios of intensities in images taken in two filters provide estimates of the electron temperature in the range 1 - 3 x 10(exp 6) K. These are broad-band temperature maps; rather than maps created with discrete sampling as in the case of the coronal green and red lines. We discuss the properties of these maps and their application to the study of energy release in the corona.

Slater, G. L.↗

NASA NTRS2001

ICESat's Laser Measurements of Polar Ice, Atmosphere, Ocean, and Land

The Ice, Cloud and Land Elevation Satellite (ICESat) mission will measure changes in elevation of the Greenland and Antarctic ice sheets as part of NASA's Earth Observing System (EOS) of satellites. Time-series of elevation changes will enable determination of the present-day mass balance of the ice sheets, study of associations between observed ice changes and polar climate, and estimation of the present and future contributions of the ice sheets to global sea level rise. Other scientific objectives of ICESat include: global measurements of cloud heights and the vertical structure of clouds and aerosols; precise measurements of land topography and vegetation canopy heights; and measurements of sea ice roughness, sea ice thickness, ocean surface elevations, and surface reflectivity. The Geoscience Laser Altimeter System (GLAS) on ICESat has a 1064 nm laser channel for surface altimetry and dense cloud heights and a 532 nm lidar channel for the vertical distribution of clouds and aerosols. The accuracy of surface ranging is 10 cm, averaged over 60 m diameter laser footprints spaced at 172 m along-track. The orbital altitude will be around 600 km at an inclination of 94 deg with a 183-day repeat pattern. The onboard GPS receiver will enable radial orbit determinations to better than 5 cm, and star-trackers will enable footprints to be located to 6 m horizontally. The spacecraft attitude will be controlled to point the laser beam to within +/- 35 m of reference surface tracks at high latitudes. ICESat is designed to operate for 3 to 5 years and should be followed by successive missions to measure ice changes for at least 15 years.

Zwally, H. J.↗

NASA NTRS2002

Overview of ACE-Asia Spring 2001 Investigations On Aerosol-Radiation Interactions

ACE-Asia's extensive measurements from land, ocean, air and space quantified aerosol-radiation interactions. Results from each platform type, plus satellite-suborbital combinations, include: 1. Time series of multiwavelength aerosol optical depth (ADD), Angstrom exponent (alpha), single-scattering albedo (SSA), and size distribution from AERONET radiometry at 13 stations. In China and Korea AOD and alpha were strongly anticorrelated (reflecting transient dust events); dust volume-size modes peaked near 8 microns diameter; and SSA(dust) greater than SSA(pollution). 2. Calculations and measurements of photosynthetically active radiation and aerosols in China yield 24-h average downward surface radiative forcing per AOD(500 nm) of -27 W/sq m (400-700 nm). 3. The Hawaii-Japan cruise sampled a gradient with AOD(500 nm) extremes of 0.1 and 1.1. Shipboard measurements showed that adding dust to pollution increased SSA(550 nm, 55% RH), typically from -0.91 to approx. 0.97. Downwelling 8-12 micron radiances showed aerosol effects, especially in the major April dust event, with longwave forcing estimated at -5 to 15 W/sq m. 4. Extinction profiles from airborne sunphotometry and total-direct-diffuse radiometry show wavelength dependence often varying strongly with height, reflecting layering of dust-dominated over pollution-dominated aerosols. Comparing sunphotometric extinction profiles to those from in situ measurements (number and composition vs size, or scattering and absorption) shows layer heights agree, but extinction sometimes differs. 5. Airborne solar spectral flux radiometry yields absorption spectra for layers. Combining with AOD spectra yields best-fit aerosol single scattering albedo spectra. 6. Visible, NIR and total solar fluxes combined with AOD give radiative forcing efficiencies at surface and aloft.

Russell, P. B.↗

NASA NTRS2003

ICESat's Laser Measurements of Polar Ice, Atmosphere, Ocean, and Land

NASA's Ice, Cloud and Land Elevation Satellite (ICESat) mission is designed to measure changes in elevation of the Greenland and Antarctic ice sheets beginning in January 2003. Time-series of elevation changes will enable determination of the present- day mass balance of the ice sheets, study of associations between observed ice changes and polar climate, and estimation of the present and future contributions of the ice sheets to global sea level rise. Other scientific objectives of ICESat include: global measurements of cloud heights and the vertical structure of clouds and aerosols; precise measurements of land topography and vegetation canopy heights; and measurements of sea ice roughness, sea ice thickness, ocean surface elevations, and surface reflectivity. The Geoscience Laser Altimeter System (GLAS) on ICESat has a 1064 nm laser channel for surface altimetry and dense cloud heights and a 532 nm lidar channel for the vertical distribution of clouds and aerosols. Differences between the characteristics of laser and radar altimetry, such as effective depth of the backscattered signal, elevation accuracy, and footprint location, and their relevance to inter-relating measurements from ERS, Envisat, ICESat, and Cryosat are discussed. Preliminary ICESat results obtained during the calibration and validation period of ICESat are described. ICESat is designed to operate for 3 to 5 years and should be followed by successive missions to measure ice changes for at least 15 years.

Zwally H. Jay↗

NASA NTRS2003

ICESat's Laser Measurements of Polar Ice and Atmospheres

Zwally, H. Jay↗

NASA NTRS2004

Underestimation of Deep Convective Cloud Tops by Thermal Imagery

The most common method of ascertaining cloud heights from space is from thermal brightness temperatures. Deep cumulus clouds of high water content are expected to radiate as black bodies. Here, cloud tops are estimated from several sensors: GOES-8, the Moderate Resolution Imaging Spectroradiometer (MODIS), the Moderate resolution Imaging Sensor (MISR), and the Goddard Cloud Physics Lidar (CPL), all collected during the CRYSTAL Florida Area Cirrus Experiment (CRYSTAL-FACE). Thermally derived cloud tops are consistently approx. 1km too low compared with independent measurements, no matter how thick the clouds are, even when the finite optical extinctions near cloud top and in thin overlying cirrus are taken into account. The bias appears to get worse for the tallest clouds. Cloud material is often present 2 km or more above the apparent cloud top. This mysterious discrepancy appears to be satellite-independent.

Sherwood, Steven C.↗

NASA NTRS2011

On the Role of Dust in the Lunar Ionosphere

Evidence suggests that electron concentrations above the dayside lunar surface can be significantly higher than expected from either the photo-ionization of exospheric neutrals or any other well-known process. The Luna 19 mission performed dual-frequency radio occultation experiments in order to determine electron column concentrations above the lunar limb as a function of tangent height (shown in the figure below), The resulting electron concentration profiles surprisingly indicated a peak of approx.500-1000/cu cm and scale heights of approx. 10-30 km. It has been suggested that electrically charged exospheric dust could contribute to these electron cnhancemcnts2 , Here we describe how to estimate the electrons produced by photo-charged dust, which is then used to predict electron concentrations from exospheric dust distribution models that are based on the "excess brightness" observed in Apollo 15 coronal photographs. The results indicate that radio occultation measurements likely provide a valuable perspective on the role of dust in the lunar environment.

Stubbs, Timothy J.↗

NASA NTRS1984

A model for the estimation of the surface fluxes of momentum, heat and moisture of the cloud topped marine atmospheric boundary layer from satellite measurable parameters

A model is developed for the estimation of the surface fluxes of momentum, heat, and moisture of the cloud topped marine atmospheric boundary layer by use of satellite remotely sensed parameters. The parameters chosen for the problem are the integrated liquid water content, q sub li, the integrated water vapor content, q sub vi, the cloud top temperature, and either a measure of the 10 meter neutral wind speed or the friction velocity at the surface. Under the assumption of a horizontally homogeneous, well-mixed boundary layer, the model calculates the equivalent potential temperature and total water profiles of the boundary layer along with the boundary layer height from inputs of q sub li, q sub vi, and cloud top temperature. These values, along with the 10m neutral wind speed or friction velocity and the sea surface temperature are then used to estimate the surface fluxes. The development of a scheme to parameterize the integrated water vapor outside of the boundary layer for the cases of cold air outbreak and California coastal stratus is presented.

Allison, D. E.↗

DOE OSTI2022

BISON fuel performance modeling optimization for experiment X447 and X447A using axial swelling and cladding strain measurements

With the recent need to qualify new reactor designs such as the Versatile Test Reactor (VTR), fuel performance calculations need to be performed to determine safety criteria of the proposed designs. In order to validate the fuel performance results obtained by a fuel performance code, BISON, for new reactor designs, legacy fuel from EBR-II and FFTF MFF with Post -Irradiation Examination (PIE) data need to be used as validation cases to benchmark models. Here in this work, BISON has been paired with the Fuels Irradiation & Physics Database (FIPD) and IFR Materials Information System (IMIS) to supply PIE data for comparison with simulations of EBR-II experiments X447/X447A. X447/X447A were assessed by implementing models for Fuel Cladding Chemical Interaction (FCCI) within BISON and optimizing the friction coefficient between the fuel surface and the cladding, the anisotropic swelling factor, and the HT9 first thermal creep scalar (which scales the first term in the HT9 creep equation) to best match the PIE axial fuel swelling height and cladding profilometry for all pins in X447/X447A. The optimal values were found using a generic algorithm developed to select different values for the three parameters until end criteria was met and error couldn’t be reduced further. The BISON-simulated cladding profilometry was evaluated using Standard Error of the Estimate (SEE) to account for the profile shape of the cladding profilometry. Optimal values for the friction coefficient, anisotropic fuel swelling factor, and HT9 first thermal creep scalar were found to best fit the BISON simulation results to the PIE measurements found in IMIS and FIPD. Improvements to current models are suggested to account for the underprediction of fuel swelling at low burnups and the overprediction of fuel swelling at higher burnups observed for the axial fuel swelling height. Although two pins in EBR-II X447/X447A (DP70 and DP75) were known to fail due to FCCI, none of the pins simulated in BISON reached a cumulative damage fraction (CDF) above 0.008 with FCCI correlations coupled in the BISON simulations. The error estimate generated for all pins in X447/X447A using optimal values was 209 µm, which is deemed acceptable.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1974

Parameter estimation for terrain modeling from gradient data

A method is developed for modeling terrain surfaces for use on an unmanned Martian roving vehicle. The modeling procedure employs a two-step process which uses gradient as well as height data in order to improve the accuracy of the model's gradient. Least square approximation is used in order to stochastically determine the parameters which describe the modeled surface. A complete error analysis of the modeling procedure is included which determines the effect of instrumental measurement errors on the model's accuracy. Computer simulation is used as a means of testing the entire modeling process which includes the acquisition of data points, the two-step modeling process and the error analysis. Finally, to illustrate the procedure, a numerical example is included.

Dangelo, K. R.↗