Search NASA⌕ Search

SEARCH · Search NASA

Results for “Gradient 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.

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

At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Estimation of intensity, footprint, and capacity of surface urban heat islands using a direction-enhanced adaptive synchronous extraction (DEASE) method

Here, the surface urban heat island (SUHI) effect, assessed through remotely sensed land surface temperature (LST), remains a focal point in urban climate research. Conventional indicators like SUHI intensity (SUHII) and footprint (SUHIF) capture peak values and spatial extent but fail to account for the cumulative thermal load—a critical dimension reflecting the total heat exposure imposed by spatially continuous warming, which directly limits a holistic assessment of ecological and societal impacts of the SUHI effect. Therefore, this study introduces an indicator termed SUHI capacity (SUHIC), designed to quantify the aggregated SUHI effect by integrating the magnitude of the warming signal across all affected areas, thereby enabling a more comprehensive evaluation of urban thermal environments. Furthermore, a direction-enhanced adaptive synchronous extraction (DEASE) method is proposed for the quantification of SUHIC. This method can dynamically identify the optimal background reference area based on the urban-rural LST gradients in various directions within the city, without relying on predefined mathematical models as previously. The results from 102 European cities first confirm that the directional variations in urban-rural LST gradients, and the DEASE method can effectively capture these distinctions for the simultaneous estimation of SUHII, SUHIF, and SUHIC. Secondly, the spatial patterns of absolute SUHIC values show strong associations with those of SUHIF (R2>0.86), while its relative values (normalized by the area of urban) align more closely with SUHII (R2 > 0.64). More importantly, SUHIC can serve as a crucial reference for assessing the urban thermal signal when SUHII and SUHIF diverge. The proposed method and framework contribute to standardizing the quantification of the SUHI effect.

Indicator↗
DOE OSTI2025

Light in the dark forest. Part I. An efficient optimal estimator for 3D Lyman-alpha forest power spectrum

The highly anisotropic nature of the Lyman-alpha (Lyα) forest data introduces a complex survey window function that complicates the measurement of the three-dimensional power spectrum ( P 3D ). In this paper, we present the first fully optimal estimator for P 3D , which exactly deconvolves the survey window function and marginalizes contaminated modes that distort the power spectrum. Our approach adapts optimal estimator techniques developed for the 2D cosmic microwave background data to the 3D case. To achieve computational feasibility, we employ the conjugate gradient method and implement the P 3 M formalism to handle large-scale and small-scale operations separately and efficiently. We validate our estimator using Monte Carlo mocks and Gaussian simulations, demonstrating its accuracy and computational efficiency. We confirm that mode marginalization eliminates distortions arising from quasar continuum errors and delivers robust power spectrum estimation, though it also inflates errors at large scales. This first implementation works in the flat-sky case; we discuss the remaining steps needed to generalize it to the curved-sky case. This formalism offers a foundation for the Lyα forest P 3D measurements and a new path toward cosmological constraints from the Lyα forest data.

Lyman alpha forest↗
DOE OSTI2024

Virtual tower measurements during the American WAKE ExperimeNt (AWAKEN)

Dual-Doppler lidar measurements were made during the American WAKE ExperimeNt to provide height-resolved measurements of wind speed and direction at multiple locations immediately south of the leading row turbines in the King Plains wind farm in Oklahoma. These so-called virtual tower measurements were performed to characterize the inflow into the wind farm and to assess possible upwind blockage effects due to the collective action of the wind farm. The campaign was conducted from 12 November 2022 to 17 October 2023, during which time 14 unique virtual tower locations were sampled with heights ranging from 240 to 490 m AGL. The wind retrieval algorithm provided estimates of the horizontal winds and their uncertainties with a vertical resolution of about 10 m, while also accounting for the tilt of the lidar platform. The virtual tower results are compared to collocated lidar wind profiling data at the A1 site, which was located roughly 2.4 rotor diameters south of the nearest turbine. The wind speed difference between the wind profiler and the virtual tower was found to be quite sensitive to atmospheric stability and wind direction below 250 m AGL. The largest differences were observed for inflow under stable conditions, where the profiler wind speeds were observed to be about 22% lower than the virtual tower near hub height. These results suggest that there are persistent horizontal gradients in the flow upwind of the wind farm which result in biased estimates using standard ground-based lidar wind profiling methods.

17 WIND ENERGY↗
NASA NTRS2018

Mangrove Canopy Height Globally Related to Precipitation and Cyclone Frequency

Mangrove wetlands are among the most productive and carbon-dense ecosystems in the world. Their structural attributes vary considerably across spatial scales, yielding large uncertainties in regional and global estimates of carbon stocks. Here, we present a global analysis of mangrove canopy height gradients and aboveground carbon stocks based on remotely sensed measurements and field data. Our study highlights that precipitation, temperature and cyclone frequency explain 74% of the global trends in maximum canopy height, with other geophysical factors influencing the observed variability at local and regional scales. We find the tallest mangrove forests in Gabon, equatorial Africa, where stands attain 62.8 m. The total global mangrove carbon stock (above- and belowground biomass, and soil) is estimated at 5.03 Pg, with a quarter of this value stored in Indonesia. Our analysis implies sensitivity of mangrove structure to climate change, and offers a baseline to monitor national and regional trends in mangrove carbon stocks.

Carbon cycle↗
NASA NTRS1994

Estimating central pressures of oceanic midlatitude cyclones

A method of determining surface pressures in oceanic storm systems using Earth Remote-Sensing Satellite (ERS-1) scatterometer data is employed to determine the lowest pressure in 25 storms. This method uses the surface winds as a lower boundary condition on a planetary boundary layer model to determine gradient winds and, thereby, pressure gradients. An optimization scheme referenced to a pressure outside the storm provides a pressure field and an estimate of the low pressure. The values are compared to European Center for Medium-Range Weather Forecasts (ECMWF) analyses in each case; there is good agreement, with some expected differences.

Brown, R. A.↗
NASA NTRS1995

Monthly atmospheric and oceanographic surface fields for the western North Atlantic: December 1986 - April 1989

Monthly atmospheric and oceanographic variables for the western North Atlantic Ocean from various sources are presented as contour or vector maps. These fields were assembled for a study of the upper ocean heat budget. Atmospheric fields include the net surface heat fluxes and wind stress derived from the 1000 mb winds from the European Center for Medium-range Weather Forecasting (ECMWF). Oceanographic fields include the sea surface height from the Geosat radar altimeter and sea surface temperature from the Advanced Very High Resolution Radiometer (AVHRR). An additional estimate of net surface heat flux is shown; this estimate was derived by assimilating winds, currents and ocean temperatures into a mixed layer model. The maps show a complex interplay of fluctuations in the winds and heat fluxes, and in the structure and temperature gradients of the Gulf Stream system. Some comments are offered on a comparison of the two heat flux estimates.

Caruso, Michael J.↗
NASA NTRS2021

Data Assimilation of Terrestrial Water Storage Observations to Estimate Precipitation Fluxes: A Synthetic Experiment

The Gravity Recovery and Climate Experiment (GRACE) mission and its Follow-On (GRACE-FO) mission provide unprecedented observations of terrestrial water storage (TWS) dynamics at basin to continental scales. Established GRACE data assimilation techniques directly adjust the simulated water storage components to improve the estimation of groundwater, streamflow, and snow water equivalent. Such techniques artificially add/subtract water to/from prognostic variables, thus upsetting the simulated water balance. To overcome this limitation, we propose and test an alternative assimilation scheme in which precipitation fluxes are adjusted to achieve the desired changes in simulated TWS. Using a synthetic data assimilation experiment, we show that the scheme improves performance skill in precipitation estimates in general, but that it is more robust for snowfall than for rainfall, and it fails in certain regions with strong horizontal gradients in precipitation. The results demonstrate that assimilation of TWS observations can help correct (adjust) the model’s precipitation forcing and, in turn, enhance model estimates of TWS, snow mass, soil moisture, runoff, and evaporation. A key limitation of the approach is the assumption that all errors in TWS originate from errors in precipitation. Nevertheless, the proposed approach produces more consistent improvements in simulated runoff than the established GRACE data assimilation techniques.

Data Assimilation↗
NASA NTRS1974

M558 radioactive tracer diffusion

This experiment was performed in Skylab 3 with two objectives in mind. First, the experimental self-diffusion coefficients for liquid zinc were to be determined in a convection-free environment. Secondly the reduction in convective mixing in earth gravity by going into the zero-gravity environment of space was to be estimated. The experiment was designed to utilize high temperatures and linear thermal gradients provided by the M518 Multipurpose Electric Furnace, and the radioactivity of zinc-65 of 245-day half-life to investigate self-diffusion in liquid zinc. The distribution of zinc-65 tracer, after melting, maintaining at soak temperature for 1 hour of soak time and then resolidifying, was obtained by sample sectioning. The concentration of activity of each section (microcurie-gram) was plotted against positions along the sample axial and radial position. Experimental data and theoretical results from solution of Fick's law of diffusion in one dimensional were compared. Samples tested on earth showed very rapid diffusion. Diffusion coefficient in unit gravity was 50 times the zero-gravity diffusion coefficient of Skylab.

Ukanwa, A. O.↗
NASA NTRS1979

The role of thermophysics in the design, optimization and understanding of semiconductor crystal growth in space

The compound semiconductor material PbSnTe has been investigated by NASA Langley Research Center as part of the Material Processing in Space (MPS) experiment in the framework of the Space Shuttle program. The long-range goal of the research is the improving of the performance of infrared detectors for use in remote sensing experiments. Three distinct techniques will be used in the low-g environment of space: two techniques involving bulk growth from melt and a vapor growth technique. In order to establish realistic estimates of the required time for experiments and to determine the thermal gradients that will be required to avoid constitutional supercooling, the diffusion coefficients must be accurately measured, however more data especially in the vapor-solid phase relations are needed.

Crouch, R. K.↗
NASA NTRS1988

Planetary astronomy: Rings, satellites, and asteroids

Studies of planetary rings focus on the dynamical processes that govern astronomically observable ring properties and structure. These investigations thus help reveal properties of the rings as well as probe the gravity fields of the planets. Satellite studies involve interpretation of orbital motion to extract information regarding the gravity fields of the outer planets and the physical properties of the satellites themselves. Asteroid lightcurve work is designed to investigate the large-scale shapes of the asteroids, as well as to reveal anomalous features such as major topography, possible satellites, or albedo variations. Work on the nature of viscous transport in planetary rings, emphasizing the role of individual particles' physical properties, has yielded a method for estimating both angular momentum and mass transport given an optical-thickness gradient. This result offers the prospect of ringlet instability, which may explain the square-profile ringlets in Saturn's C Ring. Thermal and reflected lightcurves of 532 Herculina have been interpreted to show that albedo variations cannot be the primary cause of variations. A lightcurve simulation has been developed to model complex asteroidal figures. Bamberga was observed during the December occultation as part of the joint LPL-Lowell program.

Greenberg, Richard↗
NASA NTRS1995

An analysis of the Antarctic Halogen Occultation Experiment trace gas observations

Analysis of the version 16 Halogen Occultation Experiment (HALOE) CH4 data shows that this long-lived trace gas is well correlated with potential vorticity (PV) computed from National Meteorological Center balanced winds. Analyzing late September and October 1992 data, we show that very low CH4 values are confined to the interior of a vortex edge defined by the maximum gradient in PV. The CH4 and HF time tendency is used to estimate the descent rate in the Antarctic vortex. After removing a component of the trend correlated with the HALOE sampling pattern, we compute the lower stratosphere vertical descent rates and net heaing rates in the spring Antarctic vortex. Our computations of the spring Antarctic vortex heating rates give -0.5 to -0.1 K/day. Over the winter season, the overall lower stratospheric descent rate averages about 1.8-1.5 km/month. These computations are in line with radiative transfer estimates of the heating and descent rate. The HALOE data thus appear to be consistent with the picture of an isolated lower stratospheric Antarctic vortex.

Schoeberl, Mark R.↗
NASA NTRS1998

Conditions for Aeronomic Applicability of the Classical Electron Heat Conduction Formula

Conditions for the applicability of the classical formula for heat conduction in the electrons in ionized gas are investigated. In a fully ionised gas ( V(sub en) much greater than V(sub ei)), when the mean free path for electron-electron (or electron-ion) collisions is much larger than the characteristic thermal scale length of the observed system, the conditions for applicability break down. In the case of the Venus ionosphere this breakdown is indicated for a large fraction of the electron temperature data from altitudes greater than 180 km, for electron densities less than 10(exp 4)/cc cm. In a partially ionised gas such that V(sub en) much greater than V(sub ei) there is breakdown of the formula not only when the mean free path of electrons greatly exceeds the thermal scale length, but also when the gradient of neutral particle density exceeds the electron thermal gradient. It is shown that electron heat conduction may be neglected in estimating the temperature of joule heated electrons by observed strong 100 Hz electric fields when the conduction flux is limited by the saturation flux. The results of this paper support our earlier aeronomical arguments against the hypothesis of planetary scale whistlers for the 100 Hz electric field signal. In turn this means that data from the 100 Hz signal may not be used to support the case for lightning on Venus.

Cole, K. D.↗
NASA NTRSDate not supplied

Development of TEMPO Products and Tools to Support Air Quality Management Decisions

The TEMPO mission has been observing air pollutants every hour during the daytime across its Field of Regard (FoR) covering greater North America since First Light on August 2, 2023. The highly anticipated public release of TEMPO data occurred on May 20, 2024, consisting of level 2 and level 3 trace gas data products of nitrogen dioxide, formaldehyde, and ozone. Our project at the NASA SPoRT Center is developing value-added products and tools to support the TEMPO mission and Early Adopters program with special attention on the air quality management community. The initial focus of this project is evaluating the TEMPO products over stakeholder target areas using Pandora and surface monitor observations. Methods for oversampling TEMPO data to 1 km resolution are being applied over the target areas to resolve fine-scale emission sources and pollutant gradients. Machine learning techniques using TEMPO, surface monitor, and model data to estimate surface-level nitrogen dioxide concentrations are being developed over the target areas. Our SPoRT viewer has been updated to include visualizations of the TEMPO products and an ArcGIS dashboard is being designed for enabling air quality management stakeholders to efficiently analyze TEMPO data. Training materials including user guides are being developed to ensure the effective and sustained use of TEMPO data in air quality management applications. The major outcome of this project is to support the inclusion of TEMPO data in exceptional event demonstrations by active engagement with stakeholders and ultimately enable more informed air quality management decisions in the future. This talk will provide an update on our project activities and showcase use cases of TEMPO data for monitoring different emission sources including wildland fire smoke.

air quality↗
NASA NTRSDate not supplied

Transitioning TEMPO Data for Air Quality Management Applications at the NASA SPoRT Center

The TEMPO mission has been observing air pollutants every hour during the daytime across its Field of Regard (FoR) covering greater North America since First Light on August 2, 2023. The highly anticipated public release of TEMPO data occurred on May 20, 2024, consisting of level 2 and level 3 trace gas data products of nitrogen dioxide, formaldehyde, and ozone. The NASA SPoRT Center is developing value-added products and tools to support the TEMPO mission and Early Adopters program with special attention on stakeholder from air agencies. One component of our work is focused on evaluating the TEMPO products over stakeholder target areas using Pandora and surface monitor observations to characterize the uncertainties and develop best practices for processing and analyzing TEMPO data. Methods for oversampling TEMPO data to 1 km resolution are being applied over the target areas to resolve fine-scale emission sources and pollutant gradients. Machine learning techniques using TEMPO, surface monitor, and model data to estimate surface-level nitrogen dioxide concentrations are being developed over the target areas. A SPoRT viewer for TEMPO has been launched for providing visualizations of the TEMPO products and an ArcGIS dashboard is being designed for enabling air agency stakeholders to efficiently analyze TEMPO data. Training materials including user guides are being developed to ensure the effective and sustained use of TEMPO data at our stakeholder agencies. One major goal of our TEMPO initiatives at SPoRT is to better enable the inclusion of TEMPO data in air quality management applications such as exceptional event demonstrations through our close engagement with stakeholders. This talk will provide an update on our SPoRT activities and showcase use cases of TEMPO data for monitoring different emission sources including wildland fire smoke.

Air Quality↗
NASA NTRS2017

Deriving Global OH Abundance and Atmospheric Lifetimes for Long-Lived Gases: A Search for CH3CCl3 Alternatives

An accurate estimate of global hydroxyl radical (OH) abundance is important for projections of air quality, climate, and stratospheric ozone recovery. As the atmospheric mixing ratios of methyl chloroform (CH3CCl3) (MCF), the commonly used OH reference gas, approaches zero, it is important to find alternative approaches to infer atmospheric OH abundance and variability. The lack of global bottom-up emission inventories is the primary obstacle in choosing a MCF alternative. We illustrate that global emissions of long-lived trace gases can be inferred from their observed mixing ratio differences between the Northern Hemisphere (NH) and Southern Hemisphere (SH), given realistic estimates of their NH-SH exchange time, the emission partitioning between the two hemispheres, and the NH versus SH OH abundance ratio. Using the observed long-term trend and emissions derived from the measured hemispheric gradient, the combination of HFC-32 (CH2F2), HFC-134a (CH2FCF3, HFC-152a (CH3CHF2), and HCFC-22 (CHClF2), instead of a single gas, will be useful as a MCF alternative to infer global and hemispheric OH abundance and trace gas lifetimes. The primary assumption on which this multispecies approach relies is that the OH lifetimes can be estimated by scaling the thermal reaction rates of a reference gas at 272 K on global and hemispheric scales. Thus, the derived hemispheric and global OH estimates are forced to reconcile the observed trends and gradient for all four compounds simultaneously. However, currently, observations of these gases from the surface networks do not provide more accurate OH abundance estimate than that from MCF.

Lifetime↗
NASA NTRS1974

Passive stabilization of the Long Duration Exposure Facility (LDEF)

The results of a study on the application of the magnetically anchored rate damper to gravity gradient stabilization of the Long Duration Exposure Facility (LDEF) are presented. The analyses and simulations required to investigate the use of an existing viscous magnetic rate damper for rate stabilizing the LDEF spacecraft were performed. The following tasks were included: linear performance estimates, capture and damper requirements, and performance prediction. Each of these tasks was performed for two gravity gradient stabilization configurations; an axisymmetric configuration for two-axis (pitch and roll) stability; and a non-axisymmetric configuration for three-axis stability. The results are presented by stabilization configuration.

Das, A.↗
NASA NTRS1990

Analysis and improved design considerations for airborne pulse Doppler radar signal processing in the detection of hazardous windshear

High resolution windspeed profile measurements are needed to provide reliable detection of hazardous low altitude windshear with an airborne pulse Doppler radar. The system phase noise in a Doppler weather radar may degrade the spectrum moment estimation quality and the clutter cancellation capability which are important in windshear detection. Also the bias due to weather return Doppler spectrum skewness may cause large errors in pulse pair spectral parameter estimates. These effects are analyzed for the improvement of an airborne Doppler weather radar signal processing design. A method is presented for the direct measurement of windspeed gradient using low pulse repetition frequency (PRF) radar. This spatial gradient is essential in obtaining the windshear hazard index. As an alternative, the modified Prony method is suggested as a spectrum mode estimator for both the clutter and weather signal. Estimation of Doppler spectrum modes may provide the desired windshear hazard information without the need of any preliminary processing requirement such as clutter filtering. The results obtained by processing a NASA simulation model output support consideration of mode identification as one component of a windshear detection algorithm.

Lee, Jonggil↗
DOE OSTI2025

Best estimate of the planetary boundary layer height from multiple remote sensing measurements

Remote sensing measurements have been widely used to estimate the planetary boundary layer height (PBLHT). Each remote sensing approach offers unique strengths and faces different limitations. In this study, we use machine learning (ML) methods to produce a best-estimate PBLHT (PBLHT-BE-ML) by integrating four PBLHT estimates derived from remote sensing measurements at the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory. Three ML models – random forest (RF) classifier, RF regressor, and light gradient-boosting machine (LightGBM) – were trained on a dataset from 2017 to 2023 that included radiosonde, various remote sensing PBLHT estimates, and atmospheric meteorological conditions. Evaluations indicated that PBLHT-BE-ML from all three models improved alignment with the PBLHT derived from radiosonde data (PBLHT-SONDE), with LightGBM demonstrating the highest accuracy under both stable and unstable boundary layer conditions. Feature analysis revealed that the most influential input features at the SGP site were the PBLHT estimates derived from (a) potential temperature profiles retrieved using Raman lidar (RL) and atmospheric emitted radiance interferometer (AERI) measurements (PBLHT-THERMO), (b) vertical velocity variance profiles from Doppler lidar (PBLHT-DL), and (c) aerosol backscatter profiles from micropulse lidar (PBLHT-MPL). The trained models were then used to predict PBLHT-BE-ML at a temporal resolution of 10 min, effectively capturing the diurnal evolution of PBLHT and its significant seasonal variations, with the largest diurnal variation observed over summer at the SGP site. We applied these trained models to data from the ARM Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) field campaign (EPC), where the PBLHT-BE-ML, particularly with the LightGBM model, demonstrated improved accuracy against PBLHT-SONDE. Analyses of model performance at both the SGP and EPC sites suggest that expanding the training dataset to include various surface types, such as ocean and ice-covered areas, could further enhance ML model performance for PBLHT estimation across varied geographic regions.

Zhang, Damao [Pacific Northwest National Laborator↗