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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.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Assimilation of GPM-retrieved Ocean Surface Meteorology Data for Two Snowstorm Events during ICE-POP 2018

As a component of the National Aeronautics and Space Administration (NASA) Weather Focus Area and Global Precipitation Measurement (GPM) Ground Validation participation in the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic Winter Games (ICE-POP 2018) field research and forecast demonstration programs, hourly ocean surface meteorology properties were retrieved from the GPM microwave observations for January – March 2018. In this study, the retrieved ocean surface meteorological products – 2-m temperature, 2-m specific humidity, and 10-m wind speed were assimilated into a regional numerical weather prediction (NWP) framework to explore the application of these observations for two heavy snowfall events during the ICE-POP 2018: 27-28 February, and 7-8 March 2018. The Weather Research and Forecasting (WRF) model and the community Gridpoint Statistical Interpolation (GSI) were used to conduct high resolution simulations and data assimilation experiments. The results indicate that the data assimilation has a large influence on surface thermodynamic and wind fields in the model initial condition for both events. With cycled data assimilation, significantly positive influence of the retrieved surface observation was found for the March case with improved quantitative precipitation forecast and reduced error in temperature forecast. A slightly smaller yet positive impact was also found in the forecast of the February case.

assimilation↗
NASA NTRS1984

Measurements of ocean wave spectra and modulation transfer function with the airborne two frequency scatterometer

The directional spectrum and the microwave modulation transfer function of ocean waves can be measured with the airborne two frequency scatterometer technique. Similar to tower based observations, the aircraft measurements of the Modulation Transfer Function (MTF) show that it is strongly affected by both wind speed and sea state. Also detected are small differences in the magnitudes of the MTF between downwind and upwind radar look directions, and variations with ocean wavenumber. The MTF inferred from the two frequency radar is larger than that measured using single frequency, wave orbital velocity techniques such as tower based radars or ROWS measurements from low altitude aircraft. Possible reasons for this are discussed. The ability to measure the ocean directional spectrum with the two frequency scatterometer, with supporting MTF data, is demonstrated.

Weissman, D. E.↗
NASA NTRS1986

Measurements of ocean wave spectra and modulation transfer function with the airborne two-frequency scatterometer

The directional spectrum and the microwave modulation transfer function of ocean waves can be measured with the airborne two frequency scatterometer technique. Similar to tower based observations, the aircraft measurements of the Modulation Transfer Function (MTF) show that it is strongly affected by both wind speed and sea state. Also detected are small differences in the magnitudes of the MTF between downwind and upwind radar look directions, and variations with ocean wavenumber. The MTF inferred from the two frequency radar is larger than that measured using single frequency, wave orbital velocity techniques such as tower based radars or ROWS measurements from low altitude aircraft. Possible reasons for this are discussed. The ability to measure the ocean directional spectrum with the two frequency scatterometer, with supporting MTF data, is demonstrated.

Weissman, D. E.↗
NASA NTRS1998

An Assessment of SeaWiFS and MODIS Ocean Coverage

Ocean coverages of SeaWiFS and MODIS were assessed for three seasons by considering monthly mean values of surface winds speeds and cloud cover. Mean and maximum coverages combined SeaWiFS and MODIS by considering combined coverages for ten-degree increments of the MODIS orbital mean anomaly. From this analysis the mean and maximum combined coverages for SeaWiFS and MODIS were determined for one and four-day periods for spring, summer, and winter seasons. Loss of coverage due to Sun glint and cloud cover were identified for both the individual and combined cases. Our analyses indicate that MODIS will enhance ocean coverage for all three seasons examined. ne combined SeaWiFS/MODIS show an increase of coverage of 42.2% to 48.7% over SeaWiFS alone for the three seasons studied; the increase in maximum one day coverage ranges from 47.5% to 52.0%. The increase in four-day coverage for the combined case ranged from 31.0% to 35.8% for mean coverage and 33.1 % to 39.2% for maximum coverage. We computed meridional distributions of coverages by binning the data into five-degree latitude bands. Our analysis shows a strong seasonal dependence of coverage. In general the meridional analysis indicates that increase in coverages for SeaWiFS/MODIS over SeaWiFS alone are greatest near the solar declination.

Woodward, Robert H.↗
NASA NTRS1988

A model of the tropical Pacific sea surface temperature climatology

A model for the climatological mean sea surface temperature (SST) of the tropical Pacific Ocean is developed. The upper ocean response is computed using a time dependent, linear, reduced gravity model, with the addition of a constant depth frictional surface layer. The full three-dimensional temperature equation and a surface heat flux parameterization that requires specification of only wind speed and total cloud cover are used to evaluate the SST. Specification of atmospheric parameters, such as air temperature and humidity, over which the ocean has direct influence, is avoided. The model simulates the major features of the observed tropical Pacific SST. The seasonal evolution of these features is generally captured by the model. Analysis of the results demonstrates the control the ocean has over the surface heat flux from ocean to atmosphere and the crucial role that dynamics play in determining the mean SST in the equatorial Pacific. The sensitivity of the model to perturbations in the surface heat flux, cloud cover specification, diffusivity, and mixed layer depth is discussed.

Seager, Richard↗
NASA NTRS1979

Seasat scanning multichannel microwave radiometer - Results of the Gulf of Alaska workshop

Scanning multichannel microwave radiometer results obtained by the Gulf of Alaska Seasat Experiment Workshop are reported. The Seasat SMMR provided data from five channels operating at 6.6, 10.7, 18, 21, and 37 GHz at vertical and horizontal polarizations. Two preliminary algorithms were used to retrieve geophysical parameters from the data: the Wentz algorithm (Bierman et al., 1978) based on a theoretically derived function for computing brightness temperatures and the Wilheit algorithm, based on statistical relationships between brightness temperatures and the geophysical parameters obtained from an ensemble of realistic sea-surface temperature values, wind speeds, atmospheric temperature profiles, water vapor profiles and cloud models. In spite of the immaturity of the data-processing algorithms, results are encouraging. For open ocean, rain-free cells of high-quality surface truth wind determinations display standard deviations of 3 m/sec about a bias of 1.5 m/sec. The sea-surface temperature exhibits a standard deviation of about 1.5 deg C about a bias of 3 to 5 deg C under a variety of meteorological conditions.

Lipes, R. G.↗
NASA NTRS2000

QuikSCAT Mission

The QuikSCAT Mission of the National Aeronautics and Space Administration (NASA) is planned for launch in Spring 1999, reducing the data gap in ocean-wind vector created by the loss of the NASA Scatterometer (NSCAT) on the Japanese Advanced Earth Observing Satellite (ADEOS) spacecraft. The NSCAT instrument ceased functioning when ADEOS failed on June 30, 1997. The follow-on scatterometer for monitoring ocean winds, called SeaWinds, is scheduled for launch on the Japanese ADEOS-II spacecraft in 2000. The Jet Propulsion Laboratory (JPL) has met the challenge to develop and integrate the instrument, ground system, and launch vehicle in less than a year. QuikSCAT will use pencil-beam-antennas in a conical-scan design which is more compact than the fixed fan-beam design of NSCAT. The antenna will radiate ku-band microwaves at 40 and 46 incident angle and measure the backscatter power across a continuous 1800 km swath. QuikSCAT is capable of providing wind-speed and wind-direction at 25 km resolution over 92 percent of the Earth's ice-free oceans every day, under both clear and cloudy conditions. Standard data products will be delivered to science users within 14-days, and fast data products will be available to operational users within two hours of data acquisition. QuikSCAT will be managed by JPL for the NASA's Office of Earth Science Enterprise. It will be launched from Vandenberg Air Force Base, aboard a Titan II vehicle. The satellite core-systems was built by Ball Aerospace Systems Division, Boulder, CO. The operation of QuikSCAT is expected to overlap with ERS-2 and SeaWinds. Spaceborne scatterometers have demonstrated a broad spectrum of scientific applications, including weather systems, wind-driven ocean circulation, land vegetation, polar ice morphology and dynamics, and Ocean-atmosphere-ice interaction.

Liu, W. Timothy↗
NASA NTRS2021

Gravity Wave Weakening During the 2019 Antarctic Stratospheric Sudden Warming

A rare Antarctic stratospheric sudden warming (SSW) occurred on August 30, 2019, and was a minor warming event. We investigated variations in gravity wave (GW) activity before and after this Antarctic SSW event using two satellite measurements (AIRS and CIPS) and reanalysis data (GEOS-5 FP). GW activity over the Andes decreased after August 30, although the westerly wind was 40–60 m/s and cannot filter out GWs with small zonal phase speed. This decline over the Andes was probably caused by wave saturation. Zonal mean GW activity over Antarctica and the Southern Ocean likewise decreased, with a weakening of zonal wind. The zonal mean GW activity further decreased around September 8 which coincided with a reversal of the zonal mean zonal wind at 40 km. The decline in the zonal mean GW activity after August 30 was probably caused by wind filtering and polar night jet breaking.

Gravity waves↗
NASA NTRS2023

Level-1 Calibration Assessment of Spire’s LEMUR-2 GNSS-R Ocean Normalized Bistatic Radar Cross Section Estimates

An assessment of the ocean surface Level-1 Normalized Bistatic Radar Cross Section products provided by the two batch 1 ‘LEMUR-2’ GNSS-R receivers of Spire, Inc. is reported. The analysis uses datasets extending from DOY 345, 2020 to DOY 329, 2021. Initial assessments indicate a highly consistent overall inter-channel response with mean NBRCS differences estimated to be at the 1.00% level over a 7-12 m/s ECMWF reference wind speed range. Efforts to validate the observation systems’ aggregate response relative to ≈3 million co-located CYGNSS measurements suggest a highly complementary behavior with an overall NBRCS correlation of 79.03% highlighting the potential utility of ‘LEMUR-2’ measurements for ocean surface wind sensing and related applications. Non-physical NBRCS dependencies on various Level-1 calibration variables, also observed with GNSS-R previous systems, are nonetheless noted and are explored in detail.

Mohammad M. Al-Khaldi↗
NASA NTRS1989

Probabilities and statistics for backscatter estimates obtained by a scatterometer with applications to new scatterometer design data

The values of the Normalized Radar Backscattering Cross Section (NRCS), sigma (o), obtained by a scatterometer are random variables whose variance is a known function of the expected value. The probability density function can be obtained from the normal distribution. Models for the expected value obtain it as a function of the properties of the waves on the ocean and the winds that generated the waves. Point estimates of the expected value were found from various statistics given the parameters that define the probability density function for each value. Random intervals were derived with a preassigned probability of containing that value. A statistical test to determine whether or not successive values of sigma (o) are truly independent was derived. The maximum likelihood estimates for wind speed and direction were found, given a model for backscatter as a function of the properties of the waves on the ocean. These estimates are biased as a result of the terms in the equation that involve natural logarithms, and calculations of the point estimates of the maximum likelihood values are used to show that the contributions of the logarithmic terms are negligible and that the terms can be omitted.

Pierson, Willard J., Jr.↗
NASA NTRS1997

Friction Velocity Estimation Using Dual-Frequency Altimeter Data

Global estimation of wind speeds near the sea-surface can be obtained using normalized radar cross sections sigma(o) from satellite-borne single-frequency altimeters. Indeed recent validation studies of Geosat altimeter-derived wind speeds show that several often cited semiempirical algorithms yield linear trends between wind-speeds from altimeter data and wind speeds from (a) ships of opportunity (Etcheto 1992), (b) buoys (Carter 1992), and (c) atmospheric models (Guillaume 1992). Although the linear trends are striking, there is considerable scatter since the range of standard deviations is from 1.5 to 3 m/s. In fact, the scatter of some particular measurements about the regressions is striking because they depart from the 'standard' by as much as +/- 5 m/s, which is large - even for full gale winds of 20 m/s. These anomalies can cause serious problems for gas exchange, heat, and aerosol estimates. They can also induce considerable errors in wind-driven oceanic circulation models and sea-surface wave models. This paper explores the possibility of improving the accuracy of wind speed estimation using dual-frequency altimeters.

Bliven, Larry F.↗
NASA NTRS1985

Seasat microwave wind and rain observations in severe tropical and midlatitude marine storms

Initial results of studies concerning Seasat measurements in and around tropical and severe midlatitude cyclones over the open ocean are presented, together with an assessment of their accuracy and usefulness. Complementary measurements of surface wind speed and direction, rainfall rate, and the sea surface temperature obtained with the Seasat-A Satellite Scatterometer (SASS), the Scanning Multichannel Microwave Radiometer (SMMR), and the Seasat SAR are analyzed. The Seasat data for the Hurrricanes Fico, Ella, and Greta and the QE II storm are compared with data obtained from aircraft, buoys, and ships. It is shown that the SASS-derived wind speeds are accurate to within 10 percent, and the directions are accurate to within 20 percent. In general, the SASS estimates tend to measure light winds too high and intense winds too low. The errors of the SMMR-derived measurements of the winds in hurricanes tend to be higher than those of the SASS-derived measurements.

Black, P. G.↗
NASA NTRS1989

Probabilities and statistics for backscatter estimates obtained by a scatterometer

Methods for the recovery of winds near the surface of the ocean from measurements of the normalized radar backscattering cross section must recognize and make use of the statistics (i.e., the sampling variability) of the backscatter measurements. Radar backscatter values from a scatterometer are random variables with expected values given by a model. A model relates backscatter to properties of the waves on the ocean, which are in turn generated by the winds in the atmospheric marine boundary layer. The effective wind speed and direction at a known height for a neutrally stratified atmosphere are the values to be recovered from the model. The probability density function for the backscatter values is a normal probability distribution with the notable feature that the variance is a known function of the expected value. The sources of signal variability, the effects of this variability on the wind speed estimation, and criteria for the acceptance or rejection of models are discussed. A modified maximum likelihood method for estimating wind vectors is described. Ways to make corrections for the kinds of errors found for the Seasat SASS model function are described, and applications to a new scatterometer are given.

Pierson, Willard J., Jr.↗
NASA NTRS2012

Polarimetric Retrievals of Surface and Cirrus Clouds Properties in the Region Affected by the Deepwater Horizon Oil Spill

In 2010, the Goddard Institute for Space Studies (GISS) Research Scanning Polarimeter (RSP) performed several aerial surveys over the region affected by the oil spill caused by the explosion of the Deepwater Horizon offshore platform. The instrument was deployed on the NASA Langley B200 aircraft together with the High Spectral Resolution Lidar (HSRL), which provides information on the distribution of the aerosol layers beneath the aircraft, including an accurate estimate of aerosol optical depth. This work illustrates the merits of polarization measurements in detecting variations of ocean surface properties linked to the presence of an oil slick. In particular, we make use of the degree of linear polarization in the glint region, which is severely affected by variations in the refractive index but insensitive to the waviness of the water surface. Alterations in the surface optical properties are therefore expected to directly affect the polarization response of the RSP channel at 2264 nm, where both molecular and aerosol scattering are negligible and virtually all of the observed signal is generated via Fresnel reflection at the surface. The glint profile at this wavelength is fitted with a model which can optimally estimate refractive index, wind speed and direction, together with aircraft attitude variations affecting the viewing geometry. The retrieved refractive index markedly increases over oil-contaminated waters, while the apparent wind speed is significantly lower than in adjacent uncontaminated areas, suggesting that the slick dampens high-frequency components of the ocean wave spectrum. The constraint on surface reflectance provided by the short-wave infrared channels is a cornerstone of established procedures to retrieve atmospheric aerosol microphysical parameters based on the inversion of the RSP multispectral measurements. This retrieval, which benefits from the ancillary information provided by the HSRL, was in this specific case hampered by prohibitive variability in atmospheric conditions (very inhomogeneous aerosol distribution and cloud cover). Although the results presented for the surface are essentially unaffected, we discuss the results obtained by typing algorithms in sorting the complex mix of aerosol types, and show evidence of oriented ice in cirrus clouds present in the area. In this context, polarization measurements at 1880 nm were used to infer ice habit and cirrus optical depth, which was found in the subvisual/threshold-visible regime, confirming the utility of the aforementioned RSP channel for the remote sensing of even thin cold clouds.

Polarization↗
NASA NTRS2018

Sea State Based Estimation of White Cap Fraction: Implications for Primary Marine Aerosol Fluxes

Oceanic whitecaps (hereafter, W) or the characteristic whiteness of the sea foam is an important feature for predicting exchange of gases, sea spray aerosols (SSAs), heat and momentum transfer between the ocean and the atmosphere at the air-sea interface. Due to its increased surface emission and brightness temperature, whitecaps are critical for satellite retrievals of ocean albedo, ocean color, ocean surface wind vectors from satellite borne radiometer and microwave instruments. Most of the existing models predict W using wind speed and sea surface temperature (SST). However, numerous publications have pointed out that there are large uncertainties in the predicted W and using parameterizations based on wind-wave state can improve the precision of the predicted W. Here, we integrate the University of Miami Wave Model - 2.0 (UMWM) in Goddard Earth Observing System (GEOS) and use wave diagnostics to predict W. We choose the year 2006 for our global UMWM/GEOS runs because of the availability of W dataset from satellite observations. We run UMWM/GEOS at 0.5o x 0.5o by replaying to MERRA2 meteorology and evaluate the wave diagnostics using measurements from fixed buoys and satellite altimeters. We use three different parameterizations for W based on: 1) Reynolds number, 2) wave dissipation energy, and 3) volume of air entrained by breaking waves. We compare our results of W with previous studies and also with the satellite based observational dataset. Predicting W is important for understanding the processes at the air-sea interface. Therefore, this work is a step further in improving the uncertainties in the aerosol and atmospheric chemistry modules of the global models.

Oceanic Whitecaps↗
NASA NTRS1991

Azimuthal Anisotropy In Radar Backscatter From The Ocean

Minima offset from nominal crosswind directions. Report describes experimental and theoretical study of azimuthal anisotropy in radar backscatter from surface of ocean. Important objective of this and related studies to enhance ability to sense speed and direction of surface wind remotely by use of airborne or spaceborne radar.

Li, F. K.↗
NASA NTRS1981

Winds over the ocean as measured by the scatterometer on Seasat

An analysis is presented of the relative accuracy of Seasat scatterometer measurements of the wind speeds and directions at 19.5 m altitude as compared to ground truth measurements taken by surface ships and instrumented buoys. Attention is given to the JASIN, QE II, and GOASEX surface data. The validity of 2-30 min averages taken from surface stations spread out over a wide area and serving as a basis for defining wind field averages over the 50 km resolution of SASS is examined. Satisfactory wind speeds were found to be available from SASS readings in the wind speed range 6-14 m/sec. The use of 25 SASS readings around a grid point was determined to reduce scatter to 0.25 m/sec when used in numerical weather prediction modeling. Improvements to the SASS techniques by the Seasat successor, NOSS, are discussed, and inclusion of momentum, heat, and water turbulent fluxes by NOSS is noted.

Pierson, W. J.↗