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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Global measurements of sea surface temperature, wind speed and atmospheric water content from satellite microwave radiometry

The Scanning Multichannel Microwave Radiometer (SMMR) was launched on the Seasat and Nimbus 7 satellites in 1978. The SMMR has the ability to measure sea surface temperature and wind speed with the aid of microwaves. In addition, the instrument was designed to measure water vapor and cloud liquid water with better spatial resolution than previous microwave radiometers, and to make sea-ice measurements with higher precision. A description is presented of the results of global analyses of sea surface temperature, wind speed, water vapor, and cloud liquid water, taking into account data provided by the SMMR on the Seasat satellite. It is found that the SMMR data show good self-consistency, and can usefully measure global distributions of sea surface temperatures, surface winds, water vapor, and cloud liquid water.

Njoku, E. G.↗
DOE OSTI2023

Global tropical cyclone precipitation scaling with sea surface temperature

Understanding the relationship between tropical cyclone (TC) precipitation and sea surface temperature (SST) is essential for both TC hazard forecasting and projecting how these hazards will change in the future due to climate change. This work untangles how global TC precipitation is impacted by present-day SST variability (known as apparent scaling) and by long-term changes in SST caused by climate change (known as climate scaling). A variety of datasets are used including precipitation and SST observations, realistic climate model simulations, and idealized climate model simulations. The apparent scaling rates depend on precipitation metric; examples shown here have ranges of 6.1 to 9.5% per K versus 5.9 to 9.8% per K for two different metrics. The climate scaling is estimated at about 5% per K, which is slightly less than the atmospheric moisture scaling based on thermodynamic principles of about 7% per K (i.e., the Clausius–Clapeyron scaling). The apparent scaling is greater than the climate scaling, which implies that the relationship between TC precipitation and present-day SST variability should not be used to project the long-term response of TC precipitation to climate change.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

The annual cycle of satellite-derived sea surface temperature in the southwestern Atlantic Ocean

The annual cycle of sea surface temperature (SST) in the southwestern Atlantic Ocean was estimated using four years (July 1984-July 1988) of NOAA Advanced Very High Resolution Radiometer observations. High resolution satellite observations at 1-km space and daily time resolution were grided at 100-km space and 5-day time intervals to develop an analysis dataset for determination of low frequency SST variability. The integral time scale, a measure of serial correlation, was found to vary from 40 to 60 days in the domain of interest. The existence of superannual trends in the SST data was investigated, but conclusive results could not be obtained. The annual cycle (and, in particular, the annual harmonic) explains a large proportion of the SST variability. The estimated amplitude of the cycle ranges between 5 deg and 13 deg C throughout the study area, with minima in August-September and maxima in February. The resultant climatology is compared with an arbitrary 5-day satellite SST field, and with the COADS/ICE SST climatology. It was found that the higher resolution satellite-based SST climatology resolves boundary current structure and has significantly better structural agreement with the observed field.

Podesta, Guillermo P.↗
NASA NTRS2021

Interrelationships of Sea Surface Salinity, Chlorophyll-α Concentration, and Sea Surface Temperature near the Antarctic Ice Edge

Satellite data can now provide a coherent picture of sea surface salinity (SSS), chlorophyll-α concentration (Chlα), sea surface temperature (SST), and sea ice cover across the Southern Ocean. The availability of these data at the basin scale enables novel insight into the physical and biological processes in an area that has historically been difficult to gather in situ data from. The analysis shows large regional and interannual variability of these parameters but also strong coherence across the Southern Ocean. The covariability of the parameters near the marginal ice zone shows a generally negative relationship between SSS and Chlα (r = −0.87). This may in part be attributed to the large seasonality of the variables, but analysis of data within the spring period (from November to December) shows similarly high correlation (r = −0.81). This is the first time that a large-scale robust connection between low salinity and high phytoplankton concentration during ice melt period has been quantified. Chlorophyll-α concentration is also well correlated with SST (r = 0.79) providing a potential indicator of the strength of the temperature limitation on primary productivity in the region. The observed correlation also varied regionally due to differences in ice melt patterns during spring and summer. Overall, this study provides new insights into the physical characteristics of the Southern Ocean as observed from space. In a continually warming and freshening Southern Ocean, the relationships observed here provide a key data source for testing ocean biogeochemical models and assessing the effect of sea ice–ocean processes on primary production.

Cynthia Garcia-Eidell↗
NASA NTRS1975

A 30-day forecast experiment with the GISS model and updated sea surface temperatures

The GISS model was used to compute two parallel global 30-day forecasts for the month January 1974. In one forecast, climatological January sea surface temperatures were used, while in the other observed sea temperatures were inserted and updated daily. A comparison of the two forecasts indicated no clear-cut beneficial effect of daily updating of sea surface temperatures. Despite the rapid decay of daily predictability, the model produced a 30-day mean forecast for January 1974 that was generally superior to persistence and climatology when evaluated over either the globe or the Northern Hemisphere, but not over smaller regions.

Spar, J.↗
NASA NTRS1985

Sea surface temperature from satellites: The impact of FGGE

Spacecraft instruments first launched at the beginning of the FGGE year are now producing sea surface temperature data accurate to about 1 C. At larger scales, the errors are dominated by systematic effects, some of which are instrumental, but most are geophysical, i.e., correlated with volcanic aerosols, atmospheric water vapor, clouds, and surface wind. Progress is being made to identify and eliminate such errors and thereby provide sea surface temperature data on a global basis consistently accurate to 0.5 C, which will be needed for studies of climate variability.

Bernstein, R. L.↗
DOE OSTI2024

The Shortwave Cloud-SST Feedback Amplifies Multi-Decadal Pacific Sea Surface Temperature Trends: Implications for Observed Cooling

Climate models struggle to produce sea surface temperature (SST) gradient trends in the tropical Pacific comparable to those seen recently in nature. Here, we find that the magnitude of the cloud-SST feedback in the subtropical Southeast Pacific is correlated across models with the magnitude of Eastern Pacific multi-decadal SST variability. A heat-budget analysis reveals coupling between cloud-radiative effects, circulation, and SST gradients in driving multi-decadal variability in the Eastern Pacific. Using this relationship and observed feedback estimates, we find that internal Eastern Pacific SST variability is underestimated in most models. Adjusting for model bias increases the likelihood of generating a cooling trend at least as large as observations in preindustrial control simulations by ~56% on average. If models underestimate climate “noise,” as our results suggest, this bias should be accounted for when attributing the relative importance of forced versus unforced changes in the climate.

58 GEOSCIENCES↗
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 NTRS2005

A Note on the Relationship of Temperature and Water Vapor over Oceans, as well as the Sea Surface Temperature Impact

This note follows up on a recent study by Shie et al. (2005) and extends the investigation of the domain-averaged moisture-temperature (Q-T) relationship from the Tropics (i.e., the previous study) to the tropical Pacific, Atlantic and Indian Oceans. The Q and T data examined in this study are obtained from the GEOS-3 [Goddard Earth Observing System Version-3] global re-analysis monthly products. Similar to what was found earlier in the Tropics, Q is also found to increase with T over the entire oceanic region; however, Q increases faster with T over oceans than over the Tropics. The Q-T distribution for the Tropics is in a quasi-linear relationship, which is embedded in a global Q-T distribution that is, however, in a more complex curvilinear relationship. The Q-T distribution over the oceanic regions seems to fall within the lower bound (ie., the relatively colder and driver regime) of the tropical Q-T distribution. T over oceans is also found increasing with SST (sea surface temperature), which seemingly implies that an air mass might have gained heat more readily from a warmer ocean as compared to a colder ocean. Q is also found to increase with SST in a manner that quantitatively resembles an earlier finding by Stevens (1990). We also found that relative humidity exhibits similar behaviors for oceanic and tropical regions, respectively, i.e., it increases with both SST and T over oceans and increases with T in the Tropics (Shie et al. 2005). All these similar features found between oceanic and tropical regions seem to inform us that oceans occupy most of the Tropics and so play a key role in determining what have happened in the Tropics.

Shie, C.-L.↗