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At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Cloud forcing and the net longwave surface radiation

A method is suggested which determines the monthly mean longwave radiation at the surface over the oceans using currently available satellite data sets. An independent estimate of the frequency of occurrence of clouds or cloud top heights is not required. A climatological relationship between the LWCRF (longwave cloud radiation forcing) at the top of the atmosphere and surface may be substituted. This ratio is obtained from a GMC simulation but in principle could be obtained observationally, although global coverage is doubtful. A flow diagram shows the procedure used to obtain maps for the monthly mean net upward longwave flux at the surface.

HARSHVARDHAN↗
NASA NTRS1995

One-dimensional hybrid satellite track model for the Dynamics Explorer 2 (DE 2) satellite

A one-dimensional hybrid satellite track model has been developed to calculate the high-latitude thermospheric/ionospheric structure below the satellite altitude using Dynamics Explorer 2 (DE 2) satellite measurements and theory. This model is based on Emery et al. (1985) satellite track code but also includes elements of Roble et al. (1987b) global mean thermosphere/ionosphere model. A number of parameterizations and data handling techniques are used to input satellite data from several DE 2 instruments into this model. Profiles of neutral atmospheric densities are determined from the Mass Spectrometer Incoherent Scatter 1990 (MSIS-90) model and measured neutral temperatures. Measured electron precipitation spectra are used in an auroral model to calculate particle impact ionization rates below the satellite. These rates are combined with a solar ionization rate profile and used to solve the O(+) diffusion equation, with the measured electron density as an upper boundary condition. The calculated O(+) density distribution, as well as the ionization profiles, are then used in a photochemical equilibrium model to calculate the electron and molecular ion densities. The electron temperature is also calculated by solving the electron energy equation with an upper boundary condition determined by the DE 2 measurement. The model enables calculations of altitude profiles of conductivity and Joule heating rate along and below the satellite track. In a first application of the new model, a study is made of thermospheric and ionospheric structure below the DE 2 satellite for a single orbit which occurred on October 25, 1981. The field-aligned Poynting flux, which is independently obtained for this orbit, is compared with the model predictions of the height-integrated energy conversion rate. Good quantitative agreement between these two estimates has been reached. In addition, measurements taken at the incoherent scatter radar site at Chatanika (65.1 deg N, 147.4 deg W) during a DE 2 overflight are compared with the model calculations. A good agreement was found in lower thermospheric conductivities and Joule heating rate.

Deng, Wei↗
NASA NTRS1995

One-Dimensional Hybrid Satellite Track Model for the Dynamics Explorer 2 (DE 2) Satellite

A one-dimensional hybrid satellite track model has been developed to calculate the high-latitude thermospheric/ionospheric structure below the satellite altitude using Dynamics Explorer 2 (DE 2) satellite measurements and theory. This model is based on Emery et al. satellite track code but also includes elements of Roble et al. global mean thermosphere/ionosphere model. A number of parameterizations and data handling techniques are used to input satellite data from several DE 2 instruments into this model. Profiles of neutral atmospheric densities are determined from the MSIS-90 model and measured neutral temperatures. Measured electron precipitation spectra are used in an auroral model to calculate particle impact ionization rates below the satellite. These rates are combined with a solar ionization rate profile and used to solve the O(+) diffusion equation, with the measured electron density as an upper boundary condition. The calculated O(+) density distribution, as well as the ionization profiles, are then used in a photochemical equilibrium model to calculate the electron and molecular ion densities. The electron temperature is also calculated by solving the electron energy equation with an upper boundary condition determined by the DE 2 measurement. The model enables calculations of altitude profiles of conductivity and Joule beating rate along and below the satellite track. In a first application of the new model, a study is made of thermospheric and ionospheric structure below the DE 2 satellite for a single orbit which occurred on October 25, 1981. The field-aligned Poynting flux, which is independently obtained for this orbit, is compared with the model predictions of the height-integrated energy conversion rate. Good quantitative agreement between these two estimates has been reached. In addition, measurements taken at the incoherent scatter radar site at Chatanika (65.1 deg N, 147.4 deg W) during a DE 2 overflight are compared with the model calculations. A good agreement was found in lower thermospheric conductivities and Joule heating rate.

Deng, Wei↗
NASA NTRS2000

Phase Screen Determination for the GeoSAR Interferometric Mapping Instrument

GeoSAR is a dual frequency airborne radar interferometric mapping instrument designed to obtain high resolution and high accuracy digital elevation models. The X-band inteferometric antennas are mounted beneath the fuselage with a separation distance of 2.6 m. Midway between the antennas along the aircraft centerline is a large fairing housing the Laser Baseline metrology System (LBMS) and Inertial Navigtion Units (INUs). The P-band antennas are mounted in wingtip pods approximately 10 m from the aircraft centerline. Multipath signals reflected from the LBMS fairing cause phase distortions corrupting the topograhic height measurements for both the X-band and P-band systems. In addition multipath off the wing affects the P-band phase measurements. In this paper we discuss a technique used to mitigate the amount of X-Band multipath and methods calibrating and correcting the phase for both X-Band and P-Band using a high accuracy DEM. Height differences between the interferometrically derived elevations and a photogrammetrically derived DEM are converted into phase differences. Multipath phase errors are sinusoidal with spatial frequency and amplitude related to the magnitude of reflection of the multipath reflection point and its distance from the interferometric antennas. These phase residuals are fitted using a Chebyshev polynomial sequence and used as a phase screen in the processor to correct the phase prior to height reconstruction. Based on the correction signal it is possible to estimate the location and magnitude of the multipath signal. This information can then be used to extend the domain of the phase screen over mapping angles not covered during the calibration passes. Keywords: SAR,interferometry,phase screen

Hensley, Scott↗
NASA NTRS2001

Crustal Displacements Due to Continental Water Loading

The effects of long-wavelength (> 100 km), seasonal variability in continental water storage on vertical crustal motions are assessed. The modeled vertical displacements (delta-r(sub M)) have root-mean-square (RMS) values for 1994-1998 as large as 8 mm with ranges up to 30 mm, and are predominantly annual in character. Regional strains are on the order of 20 nanostrain for tilt and 5 nanostrain for horizontal deformation. We compare delta-r(sub M) with observed Global Positioning System (GPS) heights (delta-r(sub O)) (which include adjustments to remove estimated effects of atmospheric pressure and annual tidal and non-tidal ocean loading) for 147 globally distributed sites. When the delta-r(sub O) time series are adjusted by delta-r(sub M), their variances are reduced, on average, by an amount equal to the variance of the delta-r(sub M). Of the delta-r(sub O) time series exhibiting a strong annual signal, more than half are found to have an annual harmonic that is in phase and of comparable amplitude with the annual harmonic in the delta-r(sub M). The delta-r(sub M) time series exhibit long-period variations that could be mistaken for secular tectonic trends or post-glacial rebound when observed over a time span of a few years.

vanDam, T.↗
NASA NTRS2005

Bulk Surface Momentum Parameters for Satellite-Derived Vegetation Fields

The bulk aerodynamic parameters associated with the absorption of surface momentum by vegetated landscapes are theoretically estimated within the context of Raupach's roughness sublayer formulation. The parameters include the bulk plant drag coefficient, maximum u*/U(sub h), sheltering coefficient, and canopy area density at onset of sheltering. Parameters are estimated for the four principal IGBP land cover classes within the U.S. Southern Great Plains: evergreen needleleaf forests, grasslands, croplands, and open shrublands. The estimation approach applies the Method of Moments to roughness data from several international field experiments and other published sources. The results provide the necessary land surface parameters for satellite-based estimation of momentum aerodynamic roughness length and zero-plane displacement height for seasonally variable vegetation fields employed in most terrestrial and atmospheric simulation models used today. Construction of sample displacement and roughness maps over the Southern United States using MODIS land products demonstrates the potential of this approach for regional to global applications.

Jasinski, Michael F.↗
NASA NTRS2011

Applications of the BIOPHYS Algorithm for Physically-Based Retrieval of Biophysical, Structural and Forest Disturbance Information

Canopy reflectance model inversion using look-up table approaches provides powerful and flexible options for deriving improved forest biophysical structural information (BSI) compared with traditional statistical empirical methods. The BIOPHYS algorithm is an improved, physically-based inversion approach for deriving BSI for independent use and validation and for monitoring, inventory and quantifying forest disturbance as well as input to ecosystem, climate and carbon models. Based on the multiple-forward mode (MFM) inversion approach, BIOPHYS results were summarized from different studies (Minnesota/NASA COVER; Virginia/LEDAPS; Saskatchewan/BOREAS), sensors (airborne MMR; Landsat; MODIS) and models (GeoSail; GOMS). Applications output included forest density, height, crown dimension, branch and green leaf area, canopy cover, disturbance estimates based on multi-temporal chronosequences, and structural change following recovery from forest fires over the last century. Good correspondences with validation field data were obtained. Integrated analyses of multiple solar and view angle imagery further improved retrievals compared with single pass data. Quantifying ecosystem dynamics such as the area and percent of forest disturbance, early regrowth and succession provide essential inputs to process-driven models of carbon flux. BIOPHYS is well suited for large-area, multi-temporal applications involving multiple image sets and mosaics for assessing vegetation disturbance and quantifying biophysical structural dynamics and change. It is also suitable for integration with forest inventory, monitoring, updating, and other programs.

Peddle, Derek R.↗
DOE OSTI2023

Validation of turbulence intensity as simulated by the Weather Research and Forecasting model off the US northeast coast

We report turbulence intensity (TI) is often used to quantify the strength of turbulence in wind energy applications and serves as the basis of standards in wind turbine design. Thus, accurately characterizing the spatiotemporal variability in TI should lead to improved predictions of power production. Nevertheless, turbulence measurements over the ocean are far less prevalent than over land due to challenges in instrumental deployment, maintenance, and operation. Atmospheric models such as mesoscale (weather prediction) and large-eddy simulation (LES) models are commonly used in the wind energy industry to assess the spatial variability of a given site. However, the TI derivation from atmospheric models has not been well examined. An algorithm is proposed in this study to realize online calculation of TI in the Weather Research and Forecasting (WRF) model. Simulated TI is divided into two components depending on scale, including sub-grid (parameterized based on turbulence kinetic energy (TKE)) and grid resolved. The sensitivity of sea surface temperature (SST) on simulated TI is also tested. An assessment is performed by using observations collected during a field campaign conducted from February to June 2020 near the Woods Hole Oceanographic Institution Martha's Vineyard Coastal Observatory. Results show that while simulated TKE is generally smaller than the lidar-observed value, wind speed bias is usually small. Overall, this leads to a slight underestimation in sub-grid-scale estimated TI. Improved SST representation subsequently reduces model biases in atmospheric stability as well as wind speed and sub-grid TI near the hub height. Large TI events in conjunction with mesoscale weather systems observed during the studied period pose a challenge to accurately estimating TI from models. Due to notable uncertainty in accurately simulating those events, this suggests summing up sub-grid and resolved TI may not be an ideal solution. Efforts in further improving skills in simulating mesoscale flow and cloud systems are necessary as the next steps.

17 WIND ENERGY↗
DOE OSTI2026

WINDPROF: Merged Best-Estimate Wind Profile Data – Nantucket (WFIP3 Campaign)

WINDPROF provides 10-minute wind and turbulence profiles, integrating Doppler lidars, wind profiling radars, and sonic anemometers across Northeast U.S. coastal/offshore sites during the WFIP3 campaign. Key data include wind speed, direction, vertical velocity, and turbulence parameters, with standardized quality control (e.g., instrument-specific thresholds and inter-instrument validation). Profiles are interpolated to a height grid (20 m spacing below 100 m; 30 m above) and include comprehensive uncertainty estimates. The Nantucket dataset covers February 2024–September 2025, offering reproducible methods for atmospheric research, model validation, and wind energy studies.

17 WIND ENERGY↗
DOE OSTI2026

WINDPROF: Merged Best-Estimate Wind Profile Data – Block Island (WFIP3 Campaign)

WINDPROF provides 10-minute wind and turbulence profiles, integrating Doppler lidars, wind profiling radars, and sonic anemometers across Northeast U.S. coastal/offshore sites during the WFIP3 campaign. Key data include wind speed, direction, vertical velocity, and turbulence parameters, with standardized quality control (e.g., instrument-specific thresholds and inter-instrument validation). Profiles are interpolated to a height grid (20 m spacing below 100 m; 30 m above) and include comprehensive uncertainty estimates. The Block Island dataset covers February 2024–September 2025, offering reproducible methods for atmospheric research, model validation, and wind energy studies.

17 WIND ENERGY↗
NASA NTRS1997

Estimation of Bare Surface Soil Moisture and Surface Roughness Parameter Using L-Band SAR Image Data

An algorithm based on a fit of the single-scattering Integral Equation Method (IEM) was developed to provide estimation of soil moisture and surface roughness parameter (a combination of rms roughness height and surface power spectrum) from quasi-polarized synthetic aperture radar (SAR) measurements. This algorithm was applied to a series of measurements acquired at L-band (1.25 GHz) from both AIRSAR (Airborne Synthetic Aperture Radar operated by Jet Propulsion Laboratory) and SIR-C (Spaceborne Imaging Radar-C) over a well-managed watershed in southwest Oklahoma. It was found that the two co-polarized backscattering coefficients and their combinations would provide the best input to the algorithm for estimation of soil moisture and roughness parameter. Application of the inversion algorithm to the co-polarized measurements of both AIRSAR and SIR-C resulted in estimated values of soil moisture and roughness parameter for bare and short-vegetated fields that compared favorably with those sampled on the ground. The root-mean-square (rms) errors of the comparison were found to be 3.4% and 1.9 dB for soil moisture and surface roughness parameter, respectively.

Shi, Jian-Cheng↗
NASA NTRS1998

Relating Vegetation Aerodynamic Roughness Length to Interferometric SAR Measurements

In this paper, we investigate the feasibility of estimating aerodynamic roughness parameter from interferometric SAR (INSAR) measurements. The relation between the interferometric correlation and the rms height of the surface is presented analytically. Model simulations performed over realistic canopy parameters obtained from field measurements in boreal forest environment demonstrate the capability of the INSAR measurements for estimating and mapping surface roughness lengths over forests and/or other vegetation types. The procedure for estimating this parameter over boreal forests using the INSAR data is discussed and the possibility of extending the methodology over tropical forests is examined.

Saatchi, Sassan↗
NASA NTRS2002

Lightning Return-Stroke Current Waveforms Aloft, From Measured Field Change, Current, and Channel Geometry

Direct current measurements are available near the attachment point from both natural cloud-to-ground lightning and rocket-triggered lightning, but little is known about the rise time and peak amplitude of return-stroke currents aloft. We present, as functions of height, current amplitudes, rise times, and effective propagation velocities that have been estimated with a novel remote-sensing technique from data on 24 subsequent return strokes in six different lightning flashes that were triggering at the NASA Kennedy Space Center, FL, during 1987. The unique feature of this data set is the stereo pairs of still photographs, from which three-dimensional channel geometries were determined previously. This has permitted us to calculate the fine structure of the electric-field-change (E) waveforms produced by these strokes, using the current waveforms measured at the channel base together with physically reasonable assumptions about the current distributions aloft. The computed waveforms have been compared with observed E waveforms from the same strokes, and our assumptions have been adjusted to maximize agreement. In spite of the non-uniqueness of solutions derived by this technique, several conclusions seem inescapable: 1) The effective propagation speed of the current up the channel is usually significantly (but not unreasonably) faster than the two-dimensional velocity measured by a streak camera for 14 of these strokes. 2) Given the deduced propagation speed, the peak amplitude of the current waveform often must decrease dramatically with height to prevent the electric field from being over-predicted. 3) The rise time of the current wave front must always increase rapidly with height in order to keep the fine structure of the calculated field consistent with the observations.

Willett, J. C.↗
NASA NTRS1983

Remote sensing of soil moisture - Recent advances

Recent advancements in microwave remote sensing of soil moisture include a method for estimating the dependence of the soil dielectric constant on its texture, the use of a percent of field capacity to express soil moisture magnitudes independently of soil texture, methods of estimating soil moisture sampling depth, and models for describing the effect of surface roughness on microwave response in terms of surface height variance and horizontal correlation length, as well as the verification of radiative transfer model predictions of microwave emission from soils and methods for the estimation of vegetation effects on the microwave response to soil moisture. Such researches have demonstrated that it is possible to remotely sense soil moisture in the 0-5 cm soil surface layer, and simulation studies have indicated how remotely sensed surface soil moisture may be used to estimate evapotranspiration rates and root-zone soil moisture.

Schmugge, T. J.↗
NASA NTRS1979

Estimation of mean sea surfaces in the North Atlantic, the Pacific and the Indian Ocean using GEOS-3 altimeter data

The sea surface heights above the reference ellipsoid were determined for several regions of the world's ocean using data from the radar altimeter on board the GEOS-3 satellite in conjunction with precise orbital position information derived from laser data. The resolution of the estimated sea surfaces varied from 0.25 degrees off the east coast of the United States to about 2 degrees in the Indian Ocean near Australia. The rms crossover discrepancy after adjustment varied from 30 cm to 70 cm depending on geographic location. Comparison of the altimeter derived mean sea surface in the North Atlantic with the 5 x 5 ft GEM-8 detailed gravimetric geoid indicated a relative consistency of better than one meter.

Marsh, J. G.↗
NASA NTRS2010

Assessment of the Jason-2 Extension to the TOPEX/Poseidon, Jason-l Sea-Surface Height Time Series for Global Mean Sea Level Monitoring

The Jason-2 (OSTM) follow-on mission to Jason-I provides for the continuation of global and regional mean sea level estimates along the ground-track of the initial phase of the TOPEX/Poseidon mission. During the first several months, Jason-I and Jason-2 flew in formation separated by only 55 seconds, enabling the isolation of intermission instrument biases through direct collinear differencing of near simultaneous observations. The Jason-2 Ku-band range bias with respect to Jason-I is estimated to be -84 +/- 9 mm, based on the orbit altitudes provided on the Geophysical Data Records. Modest improved agreement is achieved with the GSFC replacement orbits, which further enables the isolation of subtle 1 cm) instrument-dependent range correction biases. Inter-mission bias estimates are confirmed with an independent assessment from comparisons to a 64-station tide-gauge network, also providing an estimate of the stability of the 17-year time series to be less than 0.1 mm/yr +/- 0.4 mm/yr. The global mean sea level derived from the multi-mission altimeter sea-surface height record from January 1993 through September 2009 is 3.3 +/- 0.4 mm/yr. Recent trends over the period from 2004 through 2008 are smaller and estimated to be 2.0 +/- 0.4 mm/yr.

Beckley, B. D.↗
NASA NTRS1990

Dynamic sea surface topography, gravity, and improved orbit accuracies from the direct evaluation of Seasat altimeter data

A gravitational model incorporating Seasat altimetry, surface gravimetry, and satellite tracking data has been determined in terms of global spherical harmonics complete to degree and order 50. This model, PGS-3337, uses altimeter data as a dynamic observation of the satellite's height above the sea surface. A solution for the ocean's dynamic topography is recovered simultaneously with the orbit parameters, gravity, and ocean tidal terms. The recovered dynamic topography reveals the global long wavelength circulation of the oceans with a resolution of 2000 km and is very similar to the mean upper ocean dynamic height derived from historical ship observations. The PGS-3337 geoid has an uncertainty of 60 cm rms globally but 25 cm rms over the ocean because of the altimeter measurements. Seasat orbits determined in this solution have an estimated accuracy for the radial position of 20 cm rms. The difference between the altimeter observed sea height and the geoid plus dynamic topography model is 30 cm rms. Contained in these residuals are the sea height variability, as well as errors from the geoid, orbits, tidal models, and altimeter range measurement. This performance level is 2 to 3 times better than that achieved with previous Goddard gravitational models.

Marsh, J. G.↗
NASA NTRS2000

Estimating Forest Vertical Structure from Multialtitude, Fixed-Baseline Radar Interferometric and Polarimetric Data

Parameters describing the vertical structure of forests, for example tree height, height-to-base-of-live-crown, underlying topography, and leaf area density, bear on land-surface, biogeochemical, and climate modeling efforts. Single, fixed-baseline interferometric synthetic aperture radar (INSAR) normalized cross-correlations constitute two observations from which to estimate forest vertical structure parameters: Cross-correlation amplitude and phase. Multialtitude INSAR observations increase the effective number of baselines potentially enabling the estimation of a larger set of vertical-structure parameters. Polarimetry and polarimetric interferometry can further extend the observation set. This paper describes the first acquisition of multialtitude INSAR for the purpose of estimating the parameters describing a vegetated land surface. These data were collected over ponderosa pine in central Oregon near longitude and latitude -121 37 25 and 44 29 56. The JPL interferometric TOPSAR system was flown at the standard 8-km altitude, and also at 4-km and 2-km altitudes, in a race track. A reference line including the above coordinates was maintained at 35 deg for both the north-east heading and the return southwest heading, at all altitudes. In addition to the three altitudes for interferometry, one line was flown with full zero-baseline polarimetry at the 8-km altitude. A preliminary analysis of part of the data collected suggests that they are consistent with one of two physical models describing the vegetation: 1) a single-layer, randomly oriented forest volume with a very strong ground return or 2) a multilayered randomly oriented volume; a homogeneous, single-layer model with no ground return cannot account for the multialtitude correlation amplitudes. Below the inconsistency of the data with a single-layer model is followed by analysis scenarios which include either the ground or a layered structure. The ground returns suggested by this preliminary analysis seem too strong to be plausible, but parameters describing a two-layer compare reasonably well to a field-measured probability distribution of tree heights in the area.

Treuhaft, Robert N.↗