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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Observations on the Circulation in the Alboran Sea Using ERS1 Altimetry and Sea Surface Temperature Data

Data from the altimeter onboard the European Remote Sensing Satellite (ERS1) was used to study the circulation of the Alboran Sea between -6 to 0 degrees and 35 to 38 degrees North. The results indicate that combining sea surface temperature data and sea level data from altimetry hold promise for understanding the circulation of the Western Mediterranean.

remote sensing Alboran Sea altimetry Mediterranean↗
NASA NTRS2021

US Tropical Cyclone Activity in the 2030s Based on Projected Changes in Tropical Sea-Surface Temperature

We use a statistical tropical cyclone (TC) model, the North Atlantic Stochastic Hurricane Model (NASHM), in combination with sea-surface temperature (SST) projections from climate models, to estimate regional changes in US TC activity into the 2030s. NASHM is trained on historical variations in TC characteristics with two SST indices: global-tropical mean SST and the difference between tropical North-Atlantic (NA) SST and the rest of the global tropics, often referred to as “relative SST.” Testing confirms the model’s ability to reproduce historical US TC activity, as well as to make skillful predictions. When NASHM is driven by SST projections into the 2030s, overall NA annual TC counts increase, and the fractional increase is the greatest at the highest wind intensities. However, an eastward anomaly in mean TC tracks and an eastward shift in TC formation region result in a geographically-varied signal in US coastal activity. Florida’s Gulf coast is projected to see significant increases in TC activity, compared to the long-term historical mean, and these increases are fractionally greatest at the highest intensities. By contrast, the northwestern US Gulf and the US East Coast will see little change.

tropical cyclone (TC) model↗
NASA NTRS2009

A Robust Mechanical Sensing System for Unmanned Sea Surface Vehicles

The need for autonomous navigation and intelligent control of unmanned sea surface vehicles requires a mechanically robust sensing architecture that is watertight, durable, and insensitive to vibration and shock loading. The sensing system developed here comprises four black and white cameras and a single color camera. The cameras are rigidly mounted to a camera bar that can be reconfigured to mount multiple vehicles, and act as both navigational cameras and application cameras. The cameras are housed in watertight casings to protect them and their electronics from moisture and wave splashes. Two of the black and white cameras are positioned to provide lateral vision. They are angled away from the front of the vehicle at horizontal angles to provide ideal fields of view for mapping and autonomous navigation. The other two black and white cameras are positioned at an angle into the color camera's field of view to support vehicle applications. These two cameras provide an overlap, as well as a backup to the front camera. The color camera is positioned directly in the middle of the bar, aimed straight ahead. This system is applicable to any sea-going vehicle, both on Earth and in space.

Kulczycki, Eric A.↗
NASA NTRS2022

Seasonal and Interannual Variability of Tidal Mixing Signatures in Indonesian Seas from High-Resolution Sea Surface Temperature

With their complex narrow passages and vigorous mixing, the Indonesian seas provide the only low-latitude pathway between the Pacific and Indian Oceans and thus play an essential role in regulating Pacific-Indian Ocean exchange, regional air-sea interaction, and ultimately, global climate phenomena. While previous investigations using remote sensing and numerical simulations strongly suggest that this mixing is tidally driven, the impacts of monsoon and El Niño Southern Oscillation (ENSO) on tidal mixing in the Indonesian seas must play an important role. Here we use high-resolution sea surface temperature from June 2002 to June 2021 to reveal monsoon and ENSO modulations of mixing. The largest spring-neap (fortnightly) signals are found to be localized in the narrow passages/straits and sills, with more vigorous tidal mixing during the southeast (boreal summer) monsoon and El Niño than that during the northwest (boreal winter monsoon) and La Niña. Therefore, tidal mixing, which necessarily responds to seasonal and interannual changes in stratification, must also play a feedback role in regulating seasonal and interannual variability of water mass transformations and Indonesian throughflow. The findings have implications for longer-term variations and changes of Pacific–Indian ocean water mass transformation, circulation, and climate.

Indonesian seas↗
NASA NTRS1981

Dependence of sea-surface microwave emissivity on friction velocity as derived from SMMR/SASS

The sea-surface microwave emissivity is derived using SMMR brightness temperatures and SASS inferred friction velocities for three North Pacific Seasat passes. The results show the emissivity increasing linearly with friction velocity with no obvious break between the foam-free and foam regimes up to a friction velocity of about 70 cm/sec (15 m/sec wind speed). For horizontal polarization the sensitivity of emissivity to friction velocity greatly increases with frequency, while for vertical polarization the sensitivity is much less and is independent of frequency. This behavior is consistent with two-scale scattering theory. A limited amount of high friction velocity data above 70 cm/sec suggests an additional increase in emissivity due to whitecapping.

Wentz, F. J.↗
NASA NTRS1984

Sea surface temperatures from VAS MSI data

A procedure is developed for estimating sea surface temperatures from multispectral image data acquired from the VISSR atmospheric sounder on the geostationary GOES satellites. Theoretical regression equations for two and three infrared window channels are empirically tuned using clear field of view satellite radiances matched with reports of SST from NOAA fixed environmental buoys. The empirical regression equations are then used to produce daily regional analyses of SST. Monthly mean SST's for the western North Atlantic and the eastern equatorial Pacific during March and July 1982 were produced for use in the SST Intercomparison Workshop Series. Workshop results showed VAS SST's have a scatter of 0.8-1.0 C and a slight warm bias with respect to the other measurements of SST. The VAS SST's show no discernible bias in the region of El Chichon volcanic aerosol cloud.

Bates, J. J.↗
NASA NTRS1985

Large-scale sea surface temperature variability from satellite and shipboard measurements

A series of satellite sea surface temperature intercomparison workshops were conducted under NASA sponsorship at the Jet Propulsion Laboratory. Three different satellite data sets were compared with each other, with routinely collected ship data, and with climatology, for the months of November 1979, December 1981, March 1982, and July 1982. The satellite and ship data were differenced against an accepted climatology to produce anomalies, which in turn were spatially and temporally averaged into two-degree latitude-longitude, one-month bins. Monthly statistics on the satellite and ship bin average temperatures yielded rms differences ranging from 0.58 to 1.37 C, and mean differences ranging from -0.48 to 0.72 C, varying substantially from month to month, and sensor to sensor.

Bernstein, R. L.↗
NASA NTRS1985

Large-scale sea surface temperature variability from satellite and shipboard measurements

A series of satellite sea surface temperature intercomparison workshops were conducted under NASA sponsorship at the Jet Propulsion Laboratory. Three different satellite data sets were compared with each other, with routinely collected ship data, and with climatology, for the months of November 1979, December 1981, March 1982, and July 1982. The satellite and ship data were differenced against an accepted climatology to produce anomalies, which in turn were spatially and temporally averaged into two-degree latitude-longitude, one-month bins. Monthly statistics on the satellite and ship bin average temperatures yielded rms differences ranging from 0.58 to 1.37 C, and mean differences ranging from -0.48 to 0.72 C, varying substantially from month to month, and sensor to sensor.

Bernstein, R. L.↗
NASA NTRS1992

An analysis of the relationship between cloud anomalies and sea surface temperature anomalies in a global circulation model

The relationship between the sea surface temperature anomalies (SSTAs) and the anomalies of the monthly mean cloud cover (including the high-level, low-level, and total cloud cover), the outgoing longwave radiation, and the reflected solar radiation was analyzed using a least absolute deviations regression at each grid point over the open ocean for a 6-yr period. The results indicate that cloud change in association with a local 1-C increase in SSTAs cannot be used to predict clouds in a potential future world where all the oceans are 1-C warmer than at present, because much of the observed cloud changes are due to circulation changes, which in turn are related not only to changes in SSTAs but to changes in SSTA gradients. However, because SSTAs are associated with changes in the local ocean-atmosphere moisture and heat fluxes as well as significant changes in circulation (such as ENSO), SSTAs can serve as a surrogate for many aspects of global climate change.

Peterson, Thomas C.↗
NASA NTRS1998

Validation of the Version 1 NOAA/NASA Pathfinder Sea Surface Temperature Data Set

A high-resolution, global satellite-derived sea surface temperature (SST) data set called Pathfinder, from the Advanced Very High Resolution Radiometer (AVHRR) aboard the NOAA Polar Orbiters, is available from the Jet Propulsion Laboratory Physical Oceanography Distributed Active Archive Center (JPL PO.DAAC). Suitable for research as well as education, the Pathfinder SST data set is a result of a collaboration between the National Oceanographic and Atmospheric Administration (NOAA), the National Aeronautics and Space Administration (NASA) and investigators at several universities. NOAA and NASA are the sponsors of the Pathfinder Program, which takes advantage of currently archived Earth science data from satellites. Where necessary, satellite sensors have been intercalibrated, algorithms improved and processing procedures revised, in order to produce long time-series, global measurements of ocean, land and atmospheric properties necessary for climate research. Many Pathfinder data sets are available to researchers now, nearly a decade before the first launch of NASA's Earth Observing System (EOS). The lessons learned from the Pathfinder programs will facilitate the processing and management of terabytes of data from EOS. The Oceans component of Pathfinder has undertaken to reprocess all Global Area Coverage (GAC) data acquired by the 5-channel AVHRRs since 1981. The resultant data products are consistent and stably calibrated [Rao, 1993a, Rao, 1993b, Brown et al., 1993], Earth-gridded SST fields at a variety of spatial and temporal resolutions.

Smith, Elizabeth A.↗
NASA NTRS2010

An Examination of the Hadley Sea-Surface Temperature Time Series for the Nino 3.4 Region

The Hadley sea-surface temperature (HadSST) dataset is investigated for the interval 1871-2008. The purpose of this investigation is to determine the degree of success in identifying and characterizing El Nino (EN) southern (ENSO) extreme events, both EN and La Nina (LN) events. Comparisons are made against both the Southern Oscillation Index for the same time interval and with published values of the Oceanic Nino Index for the interval since 1950. Some 60 ENSO extreme events are identified in the HadSST dataset, consisting of 33 EN and 27 LN events. Also, preferential associations are found to exist between the duration of ENSO extreme events and their maximum anomalous excursion temperatures and between the recurrence rate for an EN event and the duration of the last known EN event. Because the present ongoing EN is a strong event, it should persist 11 months or longer, inferring that the next EN event should not be expected until June 2012 or later. Furthermore, the decadal sum of EN-related months is found to have increased somewhat steadily since the decade of 1920-1929, suggesting that the present decade (2010-2019) possibly will see about 3-4 EN events, totaling about 37 +/- 3 EN-related months (i.e., months that meet the definition for the occurrence of an EN event).

Wilson, Robert M.↗
NASA NTRS1983

Numerical simulation of the atmospheric response to equatorial Pacific sea surface temperature anomalies

There exists observational and modeling evidence to the effect that sea surface temperature (SST) anomalies in the equatorial Pacific have a significant effect upon wintertime climate in the Pacific/North American sector of the hemisphere. In connection with the emergence of a more definitive observational basis for designing general circulation model (GCM) experiments to investigate the atmospheric response to equatorial SST anomalies, it was recommended to conduct a series of GCM experiments. The present study involves a series of extended (1-2 month) integrations.Attention is given to a review of previous GCM experiments, the plan for the present study, the general circulation model and its simulation of the winter and summer circulation described by Shukla et al. (1981), tropical precipitation, upper level flow, low-level circulation and temperature, and the tropical tropospheric temperature.

Shukla, J.↗
NASA NTRS1983

Three-way partitioning of sea surface temperature measurement error

Given any set of three 2 degree binned anomaly sea surface temperature (SST) data sets by three different sensors, estimates of the mean square error of each sensor estimate is made. The above formalism performed on every possible triplet of sensors. A separate table of error estimates is then constructed for each sensor.

Chelton, D.↗