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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Effect of a Pacific sea-surface temperature anomaly on the circulation over North America: A numerical experiment with the GLAS model

A numerical experiment was carried out to determine the effect of sea surface temperature anomalies over the Pacific on the circulation over North America. The sea surface temperature (SST) anomaly pattern chosen for this study was similar to the one observed during January 1977. It is shown that a cold sea surface temperature anomaly over the Pacific produces a strong southward flow over the United States and colder temperature in eastern Canada and the United States, as it was observed during the 1977 winter. The results indicate that the SST anomaly over the Pacific can produce a significant downstream effect over the continental United States.

Shukla, J.↗
NASA NTRS1994

Evaporation and solar irradiance as regulators of sea surface temperature in annual and interannual changes

Seven years of net surface solar irradiance (S) derived from cloud information provided by the International Satellite Cloud Climatology Project (ISCCP) and 4 years of surface latent heat flux (E) derived from the observations of the special sensor microwave imager (SSM/I) were used to examine the relation between surface heat fluxes and sea surface temperature (T(sub s)) in their global geographical distribution, seasonal cycle, and interannual variation. The relations of seasonal changes imply that evaporation cooling is significant over most of the ocean and that solar heating is the main drive for the change of T(sub s) away from the equatorial wave guide where ocean dynamics may be more important. However, T(sub s) is not the most direct and significant factor in the seasonal changes of S and E over most of the ocean; the solar incident angle may be more important to S, and wind speed and air humidity are found to correlate better with E. Significant local correlations between anomalies of T(sub s) and S and between anomalies of T(sub s) and E are found in the central equatorial Pacific; both types of correlation are negative. The influence of ocean dynamics in changing T(sub s) in the tropical ocean cannot be ignored.

Liu, W. Timothy↗
NASA NTRS2018

Impact of Satellite Sea Surface Salinity Observations on ENSO Predictions from the GMAO S2S Forecast System

El Nino/Southern Oscillation (ENSO) has far reaching global climatic impacts and so extending useful ENSO forecasts would be of great benefit for society. However, one key variable that has yet to be fully exploited within coupled forecast systems is accurate estimation of near-surface ocean density. Satellite Sea Surface Salinity (SSS), combined with temperature, help to identify ocean density changes and associated mixing near the ocean surface. We assess the impact of satellite SSS observations for improving near-surface dynamics within ocean analyses and how these impact dynamical ENSO forecasts using the NASA GMAO (Global Modeling and Assimilation Office) Sub-seasonal to Seasonal (S2S_v2.1) coupled forecast system (Molod et al. 2018 - i.e. NASA's contribution to the NMME (National Multi-Model Ensemble) project). For all initialization experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF ( Local Ensemble Transform Kalman Filter) scheme similar to Penny et al., 2013. A separate reanalysis additionally assimilates Aquarius V5 (September 2011 to June 2015) and SMAP (Soil Moisture Active Passive) V4 (March 2015 to present) along-track data.We highlight the impact of satellite SSS on ocean reanalyses by comparing validation statistics of experiments that assimilate SSS versus our current prediction system that withholds SSS. We find that near-surface validation versus observed statistics for salinity are slightly degraded when assimilating SSS. This is an expected result due to known biases between SSS (measured by the satellite at approximately 1 centimeter) and in situ measurements (typically measured by Argo floats at 3 meters). On the other hand, a very encouraging result is that both temperature, absolute dynamic topography, and mixed layer statistics are improved with SSS assimilation. Previous work has shown that correcting near-surface density structure via gridded SSS assimilation can improve coupled forecasts. Here we present results of coupled forecasts that are initialized from the GMAO S2S reanalyses that assimilates/withholds along-track (L2) SSS. In particular, we contrast forecasts of the overestimated 2014 El Nino, the big 2015 El Nino, and the minor 2016 La Nina. For each of these ENSO scenarios, assimilation of satellite SSS improves the forecast validation. Improved SSS and density upgrades the mixed layer depth leading to more accurate coupled air/sea interaction.

Hackert, E.↗
NASA NTRSDate not supplied

Assessment of the Sentinel-6Michael Frielich extension to the TOPEX/Jason Sea Surface Height Climate Data Record referenced to ITRF2020

The recent launch of Sentinel-6 Michael Freilichoffers the possibility of continuing global mean sea level (GMSL) monitoring well into the currentdecade. In this presentation we report Sentinel-6/Jason-3inter-mission bias estimates based on direct sea surface height (SSH) collinear differences of near coincident measurements during the verification phase, and with comparisons to a global network of tide gauges. In an effort to provide a more consistent SSH time series and seamlesstransition to Sentinel-6, we have generated orbits for the entire time span based on the revised ITRF2020terrestrial reference frame.We reportthe efficacy ofcorrection algorithm revisions leading to the development of the NASA MEaSURE’s V6.0 sea surface height Climate Data Record(MEaSUREs -Integrated Multi-Mission Ocean Altimeter Data for Climate Research (MEaSUREs-SSH) | PO.DAAC / JPL / NASA).We provide an assessment of recent improvements to the accuracy of the 30+ year sea surface height time series, describe continuing calibration/validation activities, and evaluate the subsequent impact on current global mean sea level estimates, and the accounting of the ocean mass budget.

B D Beckley↗
NASA NTRS2019

Sea Surface Salinity Retrievals from Aquarius Using Neural Networks

Even though the Sea Surface Salinity (SSS) retrieved from Aquarius are generally very close to in-situ measurements, the level of similarity varies with the region and with the circumstances of the observations (wind speed, sea surface temperature, etc.). SSS is currently retrieved from the brightness temperatures measured by Aquarius and applying the current theoretical model for the propagation and emission of the natural thermal radiation. In this contribution we consider an alternative retrieval approach based on a Neural Network (NN) with the goal of improving the subsets of Aquarius SSS data that are in poorer agreement within-situ measurements. The subset considered here are the SSS retrieved at latitudes higher than 30 ̊. The output of the NN approach are compared against in-situ measurements using four statistical metrics (correlation coefficient, bias, RMSD and 5% trimmed range). The output of the NN and the nominal Aquarius SSS are compared against SSS values from in-situ measurements and from ocean models. From these comparisons it appears that the output of the NN matches the in-situ measurements better than the nominal Aquarius SSS.

Soldo, Yan↗
NASA NTRS1993

Comparison of remote sensing measurements with a two-scale polarimetric emission and scattering model for sea surfaces

Recently, it has been observed that the brightness temperatures of sea surfaces correlate with the azimuth angle of the ocean wind vector, indicating that ocean wind direction can not only be retrieved from the microwave backscatter, but also from the brightness temperature measurements. In this paper, comparison of the theoretical result calculated from a two-scale emission and scattering model with the Seasat and SSM/I model functions and aircraft measurements is presented and potential applications of microwave polarimetry are discussed. In our two-scale model, the modified reflectivities of large scale surfaces are calculated by extending the small perturbation method to the second order for small scale perturbation with anisotropic directional spectrum. It was found that the modified reflectivities derived from the second-order scattered field agree excellently well with the results obtained from a Monte Carlo simulation technique which numerically calculates the polarimetric reflectivities of one-dimensional random rough surfaces with a power-law spectrum. Without the second-order correction, the modified reflectivities of the rough surfaces are significantly over-estimated and sign errors are observed in the third and fourth Stokes parameters for thermal emissions. The surface spectrum parameters and two-scale cutoff are selected so that the calculated scattering and emission signatures agree with the reported model functions for Seasat and SSM/I. Subsequently, the polarimetric signatures of sea surfaces are illustrated to indicate the possibility of reducing the number of azimuthal looks required for spaceborne sensors in the remote sensing of ocean wind by using the polarimetric information. Furthermore, it is found that contrary to the dependence of backscattering coefficients on incidence angles, polarimetric brightness temperatures display a stronger wind direction dependence in the near nadir-looking direction than away from nadir. Finally, we discuss the potential of a single-look polarimetric radiometer for wind retrieval.

Yueh, S. H.↗
NASA NTRS1985

Modeling sea-surface temperature and its variability

A brief review is presented of the temporal scales of sea surface temperature variability. Progress in modeling sea surface temperature, and remaining obstacles to the understanding of the variability is discussed.

Sarachik, E. S.↗
NASA NTRS1975

Use of Skylab EREP data in a sea-surface temperature experiment

The author has identified the following significant results. A sea surface temperature experiment was studied, demonstrating the feasibility of a procedure for the remote measurement of sea surface temperature which inherently corrects for the effect of the intervening atmosphere without recourse to climatological data. The procedure was applied to Skylab EREP S191 spectrometer data, and it is demonstrated that atmospheric effects on the observed brightness temperature can be reduced to less than 1.0 K.

Anding, D. C.↗
NASA NTRS1992

A global mean sea surface based upon GEOS 3 and Seasat altimeter data

A mean sea surface relative to the International Union of Geodesy 1980 Geodetic Reference System reference ellipsoid has been derived from Seasat and GEOS 3 altimeter measurements. This surface, called MSS-9012, has been computed on a grid of 1/8 deg resolution. The surface covers the global ocean between 70 deg N and 72 deg S. Comparisons are made between MSS-9012 and ocean bathymetry. The eastern extent of the Chain Fracture Zone in the Gulf of Guinea is more apparent in the altimetry than in the bathymetry data, as are many other features. The combination of data from the two satellites has successfully retrieved more information about the sea surface than was previously possible using only Seasat data.

Marsh, J. G.↗
NASA NTRS1993

Statistical dependence of albedo and cloud cover on sea surface temperature for two tropical marine stratocumulus regions

The relationship between sea surface temperature (SST) and albedo or cloud cover is examined for two tropical regions with high values of cloud radiative forcing and persistent marine stratocumulus (mSc)-one off the west coast of Peru, the other off the west coast of Angola. The data span five years, from December 1984 to November 1989. Albedos are from the Earth Radiation Budget Experiment (ERBE), cloud covers are from the International Satellite Cloud Climatology Project (ISCCP), and SSTS are from the Climate Analysis Center. Negative correlation coefficients between albedo and SST are found to be about -0.8 when the seasonal variation of the entire dataset is analyzed. The interannual variation and the spatial variation of individual months also yields correlation coefficients that are negative. The correlation between cloud cover and SST is found to be similar to but weaker than the correlation between albedo and SST, suggesting a decrease in cloud amount and a decrease in cloud albedo with increasing SST for these regions. The corresponding albedo sensitivity averages -0.018/K with local values reaching -0.04/K. These findings are valid from 19 C to 25 C for the Peru mSc and 22 C to 27 C for the Angola mSc. These temperatures approximately bound the domains over which mSc is the prevalent cloud type within each region. These results imply a potential positive feedback to global warming by marine stratocumulus that ranges from approximately 0.14 W/sq m/K to approximately 1 W/sq m/K, depending on whether or not our results apply to all marine stratocumulus. While these values are uncertain to at least +/- 50%, the sensitivity of albedo to sea surface temperature in the present climate may serve as a useful diagnostic tool in monitoring the performance of global climate models.

Oreopoulos, Lazaros↗
NASA NTRS2011

Sea Surface Salinity and Wind Retrieval Algorithm Using Combined Passive-Active L-Band Microwave Data

Aquarius is a combined passive/active L-band microwave instrument developed to map the salinity field at the surface of the ocean from space. The data will support studies of the coupling between ocean circulation, the global water cycle, and climate. The primary science objective of this mission is to monitor the seasonal and interannual variation of the large scale features of the surface salinity field in the open ocean with a spatial resolution of 150 kilometers and a retrieval accuracy of 0.2 practical salinity units globally on a monthly basis. The measurement principle is based on the response of the L-band (1.413 gigahertz) sea surface brightness temperatures (T (sub B)) to sea surface salinity. To achieve the required 0.2 practical salinity units accuracy, the impact of sea surface roughness (e.g. wind-generated ripples and waves) along with several factors on the observed brightness temperature has to be corrected to better than a few tenths of a degree Kelvin. To the end, Aquarius includes a scatterometer to help correct for this surface roughness effect.

ocean salinity↗
NASA NTRS1972

Feasibility of microwave holography for imaging the sea surface

The possibility of imaging the sea surface in three dimensions by means of microwave holography from a low-flying aircraft is considered. Data cover a brief feasibility study and a review of some computer experiments in which it was demonstrated that it is possible to compute three-dimensional images of objects from raw holographic data recorded on magnetic tape. These experiments used synthetic data.

Wells, W.↗
NASA NTRS1988

Comparison of measured and predicted sea surface spectra of short waves

Reliable sea surface slope time series, using a laseroptical receiver system deployed on a wave follower, are analyzed to yield slope frequency spectra of the ocean surface up to 300 Hz. The results show significant differences when compared with the Pierson and Stacy (1973) model. An epirical model is proposed in this paper that is consistent with the observed slope spectra. The newly proposed model is compared with other more recently advanced shortwave spectral models.

Shemdin, O. H.↗
DOE OSTI2024

Impacts of projected changes in sea surface temperature on ozone pollution in China toward carbon neutrality

The global sea surface temperatures (SSTs) are expected to change diversely in the future under different climate scenarios, which will affect the near-surface ozone (O 3 ) distribution and concentration by influencing meteorological states and large-scale atmospheric circulation. Many countries have planned to reach carbon neutrality by the mid-21st century. Here in this study, the impacts of global and regional SST changes on near-surface O 3 concentrations in China in the middle of the 21st century under the carbon-neutral scenario (Shared Socioeconomic Pathway 1-1.9), compared with the high-emission scenario (Shared Socioeconomic Pathway 5-8.5), and possible physical and chemical mechanisms are investigated using the Community Earth System Model version 1 (CESM1). Under future climate change, the changes in SSTs in the carbon-neutral scenario relative to the high-emission scenario lead to a dipole change in near-surface O 3 concentrations in eastern and western China, with a significant decrease of 0.79 ppbv in the eastern China and a significant increase of 1.05 ppbv in the western China. The cooling of North Pacific Ocean under the carbon-neutral scenario causes a decrease in near-surface O 3 concentrations by 0.48 ppbv in eastern China due to the weakened chemical production and an increase by 0.74 ppbv in western China attributed to the enhanced O 3 transport from Eurasia. Cooling of Southern Hemisphere oceans leads to anomalous upward air motions over eastern China, which weaken the vertical transport of high-altitude O 3 to the surface. Our results suggest that future changes in SSTs in the carbon-neutral scenario will positively benefit O 3 air quality improvement in the polluted eastern China, with the North Pacific and Southern Hemisphere oceans playing important roles.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1978

Estimation of the sea surface's two-scale backscatter parameters

The relationship between the sea-surface normalized radar cross section and the friction velocity vector is determined using a parametric two-scale scattering model. The model parameters are found from a nonlinear maximum likelihood estimation. The estimation is based on aircraft scatterometer measurements and the sea-surface anemometer measurements collected during the JONSWAP '75 experiment. The estimates of the ten model parameters converge to realistic values that are in good agreement with the available oceanographic data. The rms discrepancy between the model and the cross section measurements is 0.7 db, which is the rms sum of a 0.3 db average measurement error and a 0.6 db modeling error.

Wentz, F. J.↗