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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Skylab earth resources experiment package /EREP/ - Sea surface topography experiment

The S-193 Skylab radar altimeter was operated in a round-the-world pass on Jan. 31, 1974. The main purpose of this experiment was to test and 'measure' the variation of the sea surface topography using the Goddard Space Flight Center (GSFC) geoid model as a reference. This model is based upon 430,000 satellite and 25,000 ground gravity observations. Variations of the sea surface on the order of -40 to +60 m were observed along this pass. The 'computed' and 'measured' sea surfaces have an rms agreement on the order of 7 m. This is quite satisfactory, considering that this was the first time the sea surface has been observed directly over a distance of nearly 35,000 km and compared to a computed model. The Skylab orbit for this global pass was computed using the Goddard Earth Model (GEM 6) and S-band radar tracking data, resulting in an orbital height uncertainty of better than 5 m over one orbital period.

Vonbun, F. O.↗
NASA NTRS2001

The Aquarius Mission: Sea Surface Salinity from Space

Aquarius is a new satellite mission concept to study the impact of the global water cycle on the ocean, including the response of the ocean to buoyancy forcing and the subsequent feedback of the ocean on the climate. The measurement objective of Aquarius is sea surface salinity, which reflects the concentration of freshwater at the ocean surface. Salinity affects the dielectric constant of sea water and, consequently, the radiometric emission of the sea surface to space. Rudimentary space observations with an L-band radiometer were first made from Skylab in the mid-70s and numerous aircraft missions of increasing quality and improved technology have been conducted since then. Technology is now available to carry out a global mission, which includes both an accurate L band (1.413 Ghz) radiometer and radar system in space and a global array of in situ observations for calibration and validation, in order to address key NASA Earth Science Enterprise questions about the global cycling of water and the response of the ocean circulation to climate change. The key scientific objectives of Aquarius examine the cycling of water at the ocean's surface, the response of the ocean circulation to buoyancy forcing, and the impact of buoyancy forcing on the ocean's thermal feedback to the climate. Global surface salinity will also improve our ability to model the surface solubility chemistry needed to estimate the air-sea exchange of CO2. In order to meet these science objectives, the NASA Salinity Sea Ice Working Group over the past three years has concluded that the mission measurement goals should be better than 0.2 practical salinity units (psu) accuracy, 100 km resolution, and weekly to revisits. The Aquarius mission proposes to meet these measurement requirements through a real aperture dual-polarized L band radiometer and radar system. This system can achieve the less than 0.1 K radiometric temperature measurement accuracy that is required. A 3 m antenna at approx. 600km altitude in a sun-synchronous orbit and 300 km swath can provide the desired 100 km resolution global coverage every week. Within this decade, it may be possible to combine satellite sea surface salinity measurements with ongoing satellite observations of temperature, surface height, air-sea fluxes; vertical profiles of temperature and salinity from the Argo program; and modern ocean/atmosphere modeling and data assimilation tools, in order to finally address the complex influence of buoyancy on the ocean circulation and climate.

Koblinsky, Chester↗
NASA NTRS1992

Experimental measurement and theoretical modeling of microwave scattering and the structure of the sea surface influencing radar observations from space

The electromagnetic (EM) bias 'epsilon' is an error present in radar altimetry of the ocean due to the nonuniform reflection from wave troughs and crests. The EM bias is defined as the difference between the mean reflecting surface and the mean sea surface. A knowledge of the EM bias is necessary to permit error reduction in mean sea level measurements by satellite radar altimeters. Direct measurements of the EM bias were made from a Shell Offshore oil production platform in the Gulf of Mexico for a six month period during 1989 and 1990. Measurements of the EM bias were made at 5 and 14 Ghz. During the EM bias experiments by Melville et al., a wire wave gauge was used to obtain the modulation of the high frequency waves by the low frequency waves. It became apparent that the EM bias was primarily caused by the modulation of the short waves. This was reported by Arnold et al. The EM bias is explained using physical optics scattering and an empirical model for the short wave modulation. Measurements of the short wave modulation using a wire wave gauge demonstrated a linear dependence of the normalized bias on the short wave modulation strength, M. The theory accurately predicts this dependence by the relation epsilon = -alphaMH sub 1/3. The wind speed dependence of the normalized bias is explained by the dependence of the short wave modulation strength on the wind speed. While other effects such as long wave tilt and curvature will have an effect on the bias, the primary cause of the bias is shown to be due to the short wave modulation. This report will present a theory using physical optics scattering and an empirical model of the short wave modulation to estimate the EM bias. The estimated EM bias will be compared to measurements at C and Ku bands.

Arnold, David↗
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 NTRS1997

Monthly Maps of Sea Surface Height in the North Atlantic and Zonal Indices for the Gulf Stream Using TOPEX/Poseidon Altimeter Data

Monthly Maps of sea surface height are constructed for the North Atlantic Ocean using TOPEX/Poseidon altimeter data. Mean sea surface height is reconstructed using a weighted combination of historical, hydrographic data and a synthetic mean obtained by fitting a Gaussian model of the Gulf Stream jet to altimeter data. The resultant mean shows increased resolution over the hydrographic mean, and incorporates recirculation information that is absent in the synthetic mean. Monthly maps, obtained by adding the mean field to altimeter sea surface height residuals, are used to derive a set of zonal indices that describe the annual cycle of meandering as well as position and strength of the Gulf Stream.

GULF STREAM↗
NASA NTRS2018

The Impact of Satellite Sea Surface Salinity for Prediction of the Coupled Indo-Pacific System

Here we assess the impact of satellite sea surface salinity (SSS) observations on seasonal to interannual variability of tropical Indo-Pacific Ocean dynamics as well as on dynamical ENSO forecasts. The baseline experiment assimilates satellite sea level (SL), sea surface temperature (SST), and in situ subsurface temperature and salinity observations (Tz, Sz). These baseline experiments are then compared with experiments that additionally assimilate Aquarius (version 5.0 Lilly and Lagerloef, 2008) and SMAP (version 2.0 Meissner and Wentz, 2016) SSS. Twelve-month forecasts are initialized for each month from September 2011 to September 2017. We find that including satellite SSS significantly improves NINO3.4 sea surface temperature anomaly validation over 0-8 month forecast lead-times and removing the salty bias from SMAP data helps to extend useful forecasts out to 12 month lead-times.

SSS↗
NASA NTRS1990

Mean sea surface and variability of the Gulf of Mexico using Geosat altimetry data

Geosat Exact Repeat Mission (ERM) altimetric measurements of the sea surface height in the Gulf of Mexico are used to determine the mean sea surface height with respect to the ellipsoid and mesoscale variability along Geosat ground tracks in the gulf for the time period from November 8, 1986 to November 25, 1988. A mean surface generated using the Geosat ERM along-track mean is calculated and contrasted with a previously derived mean surface determined using GEOS 3 and Seasat crossover differences. This provides a first look at the variability in the mean between the time periods of 1987-1988 and 1975-1978. In addition, the along-track mesoscale variability time series has been produced from the Geosat ERM data set by using a robust orbit-error removal algorithm to determine the variability of the sea-surface height with respect to the along-track mean. Good qualitative and quantitative agreement with previous in situ observations in the region is found. This study demonstrates the potential of satellite altimetry for oceanographic studies of the Gulf of Mexico.

Leben, Robert R.↗
NASA NTRS1977

Sea-surface temperature and salinity mapping from remote microwave radiometric measurements of brightness temperature

A technique to measure remotely sea surface temperature and salinity was demonstrated with a dual frequency microwave radiometer system. Accuracies in temperature of 1 C and in salinity of part thousand for salinity greater than 5 parts per thousand were attained after correcting for the influence of extraterrestrial background radiation, atmospheric radiation and attenuation, sea-surface roughness, and antenna beamwidth. The radiometers, operating at 1.43 and 2.65 GHz, comprise a third-generation system using null balancing and feedback noise injection. Flight measurements from an aircraft at an altitude of 1.4 km over the lower Chesapeake Bay and coastal areas of the Atlantic Ocean resulted in contour maps of sea-surface temperature and salinity with a spatial resolution of 0.5 km.

Hans-Juergen, C. B.↗
NASA NTRS2020

Satellite Sea Surface Salinity Observations Impact on El Niño/Southern Oscillation Predictions: Case Studies from the NASA GEOS Seasonal Forecast System

El Niño/Southern Oscillation (ENSO) has far reaching global climatic impacts and so extending useful ENSO forecasts would have great societal benefit. However, one key variable that has yet to be fully exploited within coupled forecast systems is accurate estimation of near-surface ocean salinity. Satellite sea surface salinity (SSS), combined with temperature, help to improve the estimates of ocean density changes and associated near-surface mixing. For the first time, we assess the impact of satellite SSS observations for improving near-surface dynamics within ocean reanalyses and how these initializations impact dynamical ENSO forecasts using NASA’s coupled forecast system (GEOS-S2S-2). For all initialization experiments, all available sea level and in situ temperature and salinity observations are assimilated. Separate observing system experiments (OSE) additionally assimilate Aquarius, and SMAP, SMOS, and these datasets combined. We highlight the impact of satellite SSS on ocean reanalyses by comparing experiments with and without the application of SSS assimilation. Next, we compare case studies of coupled forecasts for the big 2015 El Niño, the 2017 La Niña, and the weak El Niño in 2018 that are initialized from GEOS-S2S-2 spring reanalyses that assimilate and withhold along-track SSS. For each of these ENSO-event case studies, assimilation of satellite SSS improves the forecast validation with respect to observed NINO3.4 anomalies (or at least reduces the forecast uncertainty). Satellite SSS assimilation improved characterization of the mixed layer depth leading to more accurate coupled air/sea interaction and better forecasts. These results further underline the value of satellite SSS assimilation into operational forecast systems.

Eric Hackert↗
DOE OSTI2021

Sea Surface Salinity Reemergence in an Updated North Atlantic In Situ Salinity Dataset

Monthly sea surface salinity (SSS) fields are constructed from observations, using objective mapping on a 1° x 1° grid in the Atlantic between 30°S and 50°N in the 1970-2016 period in an update of the dataset of Reverdin et al. Data coverage is heterogeneous, with increased density in 2002 when Argo floats become available, high density along Voluntary Observing Ship lines, and low density south of 10°S. Using lag correlation, the seasonal reemergence of SSS anomalies is investigated between 20° and 50°N in 5° x 5° boxes during the 1993-2016 period, both locally and remotely following the displacements of the deep mixed-layer waters estimated from virtual float trajectories derived from the daily AVISO surface geostrophic currents. Although SSS data are noisy, local SSS reemergence is detected in about half of the boxes, notably in the northeast and southeast, while little reemergence is seen in the central and part of the eastern subtropical gyre. In the same period, sea surface temperature (SST) reemergence is found only slightly more frequently, reflecting the short data duration. However, taking geostrophic advection into account degrades the detection of remote SSS and even SST reemergence. When anomalies are averaged over broader areas, robust evidence of a second and third SSS reemergence peak is found in the northeastern and southeastern parts of the domain, indicating long cold-season persistence of large-scale SSS anomalies, while only a first SST reemergence is seen. Finally, an oceanic reanalysis is used to confirm that the correlation analysis indeed reflects the reemergence of subsurface salinity anomalies.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1985

Production of global sea surface temperature fields for the Jet Propulsion Laboratory workshop comparisons

Sea surface temperature (SST) is measured from space by the advanced very high resolution radiometer (AVHRR), scanning multichannel microwave radiometer (SMMR), high resolution infrared sounder (HIRS) and VISSR atmospheric sounder (VAS). Typical accuracies have been reported from 0.5 C regionally to 2.0 C on a global basis. To evaluate the accuracy of the satellite-derived sea surface temperatures, a series of three workshops was organized to provide uniform data reduction and analysis. The analytical techniques used to intercompare satellite and in situ measurements are described in detail. Selected results showed the overall average rms errors were in the range 0.5-1.0 C.

Hilland, J. E.↗
NASA NTRS1983

Equatorial long waves in geostationary satellite observations and in a multichannel sea surface temperature analysis

Geostationary satellite observations of a zonally oriented sea surface temperature front in the eastern equatorial Pacific were made between 1975 and 1981. Long waves appeared along the front mainly during the summer and fall, except during 1976, the year of an El Nino. The waves have averaged periods of 25 days and wavelengths of 1000 km. At the end of 1981, the long waves also were detected in a new sea surface temperature analysis based on multichannel infrared measurements from a polar-orbiting satellite. This quantitative analysis may improve the ability to resolve low-frequency equatorial wave motions from satellite observations.

Legeckis, R.↗
NASA NTRS2012

Estimating Sea Surface Salinity and Wind Using Combined Passive and Active L-Band Microwave Observations

Several L-band microwave radiometer and radar missions have been, or will be, operating in space for land and ocean observations. These include the NASA Aquarius mission and the Soil Moisture Active Passive (SMAP) mission, both of which use combined passive/ active L-band instruments. Aquarius s passive/active L-band microwave sensor has been designed to map the salinity field at the surface of the ocean from space. SMAP s primary objectives are for soil moisture and freeze/thaw detection, but it will operate continuously over the ocean, and hence will have significant potential for ocean surface research. In this innovation, an algorithm has been developed to retrieve simultaneously ocean surface salinity and wind from combined passive/active L-band microwave observations of sea surfaces. The algorithm takes advantage of the differing response of brightness temperatures and radar backscatter to salinity, wind speed, and direction, thus minimizing the least squares error (LSE) measure, which signifies the difference between measurements and model functions of brightness temperatures and radar backscatter. The algorithm uses the conjugate gradient method to search for the local minima of the LSE. Three LSE measures with different measurement combinations have been tested. The first LSE measure uses passive microwave data only with retrieval errors reaching 1 to 2 psu (practical salinity units) for salinity, and 1 to 2 m/s for wind speed. The second LSE measure uses both passive and active microwave data for vertical and horizontal polarizations. The addition of active microwave data significantly improves the retrieval accuracy by about a factor of five. To mitigate the impact of Faraday rotation on satellite observations, the third LSE measure uses measurement combinations invariant under the Faraday rotation. For Aquarius, the expected RMS SSS (sea surface salinity) error will be less than about 0.2 psu for low winds, and increases to 0.3 psu at 25 m/s wind speed for warm waters (25 C). To achieve the required 0.2 psu accuracy, the impact of sea surface roughness (e.g. wind-generated ripples) on the observed brightness temperature has to be corrected to better than one tenth of a degree Kelvin. With this algorithm, the accuracy of retrieved wind speed will be high, varying from a few tenths to 0.6 m/s. The expected direction accuracy is also excellent (less than 10 ) for mid to high winds, but degrades for lower speeds (less than 7 m/s).

Yueh, Simon H.↗
NASA NTRS1982

Aircraft measurement of sea surface temperature during the West Coast Experiment

During the West Coast Experiment in March 1977, a test was conducted to ascertain the effectiveness of using remote sensing techniques to estimate sea surface temperature (SST) from infrared (IR) emissions of the sea surface. Aircraft flights were made over three buoys moored in southern California coastal waters, and data was collected of sea surface emissions at thermal IR wavelengths (7.95-13.5 micrometers). SST obtained from the remote sensing measurements were compared with in situ SST measured with thermistors mounted on the buoys. The remotely determined SST were from 1.4-2.9 C lower than the in situ measurements. Several factors are discussed that could account for the differences.

Schieldge, J. P.↗
NASA NTRS2019

Sea Surface Salinity Distribution in the Southern Ocean as Observed from Space

Large-scale spatial and temporal variabilities of sea surface salinity (SSS) in the Southern Ocean from 2011 to 2017 were studied using products derived from microwave sensors on board Aquarius, Soil Moisture and Ocean Salinity (SMOS), and Soil Moisture Active and Passive (SMAP) satellites. Four products, three from Aquarius and one from SMOS, were evaluated and shown to be generally consistent within 0.3 to 0.6 psu and agree favorably with in situ measurements. However, although the Aquarius products show consistent seasonality of SSS with high values of 34.45 psu in October and low values of 33.40 psu in May, theSMOS and SMAP products lack such seasonal variations. This may be caused by larger uncertainties in the SMOS and SMAP data due in part to the lack of concurrent scatterometer measurements that is used to correct for roughness effects. The four products provide similar spatial distributions of SSS with root mean square difference from 0.25 to 0.58 psu. Differences among Aquarius products are mainly due to varying salinity retrieval algorithms, smoothing, and masking of sea ice, while the SMOS product showed the highest SSS deviation that is likely due to the bias adjustment done on the data set. Our analyses show that SSS in the Southern Ocean region has significant meridional variations with the lowest SSS near the ice edge and highest at lower latitudes. The SSS is also lowest in summer indicating the predominant influence of sea ice and glacial melt, but it stays low near ice edges even during the growth season. Salinity together with temperature is the key parameters that control the state and circulation of the World's oceans. The large‐scale distribution of the sea surface salinity of the Southern Ocean is quantified for the first time using Aquarius, Soil Moisture and Ocean Salinity, and Soil Moisture Active and Passive satellite microwave data. Seasonal and interannual changes in the distribution as affected by the sea ice cover, surface temperature, and precipitation are evaluated. Comparative studies were done, using four different products that are publicly available, in conjunction with in situ observations to gain insights into the true nature of the distribution and how consistently the sea surface salinity is depicted by the different products. There are general consistencies in the products, and discrepancies are attributed to different algorithms, smoothing techniques, and sea ice masking. Aquarius data are shown to have higher accuracy than Soil Moisture and Ocean Salinity and Soil Moisture Active and Passive products in part because of having concurrent scatterometer that provides accurate correction to roughness effects.

Garcia-Eidell, Cynthia↗
NASA NTRS1975

Sea surface determination from space: The GSFC geoid

The determination of the sea surface/geoid and its relative variation were investigated and results of the altimeter experiment on Skylab to test the geoid are discussed. The spaceborne altimeter on Skylab revealed that the sea surface of the world's oceans can be measured with an accuracy in the meter range. Surface variations are discussed as they relate to those computed from satellite orbital dynamics and ground based gravity data. The GSFC geoid was constructed from about 400,000 satellite tracking data (range, range rate, angles) and about 20,000 ground gravity observations. One of the last experiments on Skylab was to measure and/or test this geoid over almost one orbit. It was found that the computed water surface deviates between 5 to 20 m from the measured one. Further outlined are the influence of orbital errors on the sea surface, and numerical examples are given based upon real tracking data. Orbital height error estimates were computed for geodetic type satellites and are found to be in the order of 0.2 to 5 meters.

Vonbun, F. O.↗