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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Supplementary notes on sea surface temperature anomalies and model-generated meteorological histories

In seasonal computations, the Mintz-Arakawa two-level model is found to be sensitive to a minor alteration in the computational program. Effects of the program change on monthly mean sea level pressure fields are small in the first month, but large in the second and third months, although the meteorological histories generated by both the original and modified programs are equally credible. The inherited effects of a transient (one month) sea surface temperature (SST) anomaly on the computed monthly mean sea level pressure fields over a period of a season are about as large in absolute magnitude as those generated in the model by a persistent (seasonal) SST anomaly. The effects of a transient SST anomaly in the North Pacific Ocean on monthly and seasonal temperature and precipitation in the eastern United States may be large enough to produce a change of one or two class intervals in these predicted weather elements. The model-generated precipitation in the equatorial region is also found to be sensitive to the sea surface temperature field in the North Pacific.

Spar, J.↗
NASA NTRS1977

Short pulse radar used to measure sea surface wind speed and SWH

A joint airborne measurement program is being pursued by NRL and NASA Wallops Flight Center to determine the extent to which wind speed and sea surface significant wave height (SWH) can be measured quantitatively and remotely with a short pulse (2 ns), wide-beam (60 deg), nadir-looking 3-cm radar. The concept involves relative power measurements only and does not need a scanning antenna, Doppler filters, or absolute power calibration. The slopes of the leading and trailing edges of the averaged received power for the pulse limited altimeter are used to infer SWH and surface wind speed. The interpretation is based on theoretical models of the effects of SWH on the leading edge shape and rms sea-surface slope on the trailing-edge shape. The models include the radar system parameters of antenna beam width and pulsewidth.

Hammond, D. L.↗
NASA NTRS2020

Skin Sea‐Surface Temperature from VIIRS on Suomi‐NPP—NASA Continuity Retrievals

Retrievals of skin Sea‐Surface Temperature (SSTskin) from the measurements of the Visible Infrared Imaging Radiometer Suite on the Suomi‐National Polar‐orbiting Partnership satellite are presented and discussed. The algorithms used to derive the SSTskin from the radiometric measurements are given in detail. A number of approaches to assess the accuracy and stability of the Visible Infrared Imaging Radiometer Suite (VIIRS) SSTskin retrievals are reported, and factors including latitude and season, and physical processes in the atmosphere and at the surface are discussed. We conclude that the Suomi National Polar‐orbiting Partnership (S‐NPP) VIIRS is capable of matching and improving upon the accuracies of SSTskin from the MODISs on Terra and Aqua, and that the VIIRS SSTskin fields have the potential to contribute to the extension of the satellitederived Climate Data Records of SST into the future.

sea‐surface temperature↗
NASA NTRS1999

Observations of Sea Surface Mean Square Slope During the Southern Ocean Waves Experiment

For the Southern Ocean Waves Experiment (SOWEX), conducted in June 1992 out of Hobart, Tasmania, the 36 GHz (8.3 mm) NASA Scanning Radar Altimeter (SRA) was shipped to Australia and installed on a CSIRO Fokker F-27 research aircraft instrumented to make comprehensive surface layer measurements of air-sea interaction fluxes. The sea surface mean square slope (mss), which is predominantly caused by the short waves, was determined from the backscattered power falloff with incidence angle measured by the SRA in the plane normal to the aircraft heading. On each flight, data were acquired at 240 m altitude while the aircraft was in a 7 deg roll attitude, interrogating off-nadir incidence angles from -15 deg through nadir to +29 deg. The aircraft turned azimuthally through 810 deg in this attitude, mapping the azimuthal dependence of the backscattered power falloff with incidence angle. Two sets of turning data were acquired on each day, before and after the aircraft measured wind stress at low altitude (12 m to 65 m). Wave topography and backscattered power for mss were also acquired during those level flight segments whenever the aircraft altitude was above the SRA minimum range of 35 m. A unique feature of this experiment was the use of a nadir-directed low-gain horn antenna (35 deg beamwidth) to acquire azimuthally integrated backscattered power data versus incidence angle before and after the turn data.

Walsh, E. J.↗
NASA NTRSDate not supplied

Improving Ocean Reanalyses and ENSO Forecasts By Assimilation of Rain-Corrected Satellite Sea Surface Salinity Using the GMOA S2s Forecast System

The ENSO phenomenon has a significant global socio-economic impact and has been the key focus for improving coupled ocean-atmosphere forecasts. Assimilation of satellite altimetry and subsurface temperature and salinity from (mostly) Argo help improve the initialization of the thermocline, while satellite SST aids in constraining surface heat-fluxes, leading to improved coupled system sub-seasonal to seasonal forecasts. However, few studies have focused on improving the near-surface density and mixing through satellite sea surface salinity (SSS) assimilation. The few ocean models that assimilate satellite SSS, bias correct to normalize towards the near-surface Argo data for expediency. This assumption is likely inadequate in rainy regions, where buoyant water forms a fresh surface lens. In previous work, we showed that adjusting SSS to bulk salinity (Sb) using the Rain Impact Model (RIM) of Santos-Garcia et al., 2014 improves the near-surface density and mixed layer depth, leading to deeper thermocline and improved NINO3.4 SST forecasts. We now utilize the Soil Moisture and Ocean Salinity rain-corrected (SMOS_RC) SSS, available in SMOS-CATDS products, to represent Sb more accurately at the first model layer (e.g., 5 m). Rather than a diffusivity model as RIM, SMOS_RC uses a statistical correction dependent on Integrated Multi-satellitE Retrievals for GPM (IMERG) rain rates, established on observed SMOS SSS decreases related to Sb in the presence of rain (Supply et al., 2020). For all experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF scheme (Penny et al., 2013). One reanalysis additionally assimilates SMOS SSS data as is, and a separate reanalysis assimilates SMOS_RC. We assess the impact on near-surface and subsurface dynamics by validating against observations and explore how SSS assimilation (SMOS vs SMOS_RC) impacts ENSO forecasts using the NASA GMAO Sub-seasonal to Seasonal coupled forecast system (S2S-v3, Molod et al. 2020). We show that improved estimates of density and near-surface mixing led to more accurate coupled air/sea interaction and better ENSO forecasts. The increased SSS, resulting from the removal of the instantaneous rain effect, modifies the ocean state by enhancing mixing and deepening the thermocline.

Veronica Ruiz Xomchuk↗
NASA NTRS1982

Determination of sea surface temperatures from microwave and IR data

Microwave measurements from the Nimbus 7 SMMR were used to derive the atmospheric precipitable water, which was then used to obtain the atmospheric correction for use with AVHRR thermal IR measurements to obtain sea surface temperature (SST). The resulting SST's were compared with the NOAA operational sea surface temperature measurements, and the two sets of measurements were found to be in reasonable agreement. The average residuals between the two sets of measurements was 0.15 K with the NOAA operational SST's being slightly greater.

Rangaswamy, S.↗
NASA NTRS1974

Atmospheric response to variations in sea surface temperature

An extended range prediction experiment was performed with the GISS atmospheric model on a global data to test the sensitivity of the model to sea surface temperature (SST) variation over a two-week forecast period. The use of an initial observed SST field in place of the climatological monthly mean sea temperatures for surface flux calculations in the model was found to have a significant effect on the predicted precipitation over the ocean, with enhanced convection computed over areas where moderately large warm SST anomalies are found. However, there was no detectable positive effect of the SST anomaly field on forecast quality. The influence of the SST anomalies on the daily predicted fields of pressure and geopotential is relatively insignificant up to about one week compared with the growth of prediction error, and is no greater over a two-week period than that resulting from random errors in the initial meteorological state. The 14-day average fields of sea level pressure and 500-mb height predicted by the model, appear to be similarly insensitive to anomalies of sea surface temperature.

Spar, J.↗
NASA NTRS1992

The global structure of the annual and semiannual sea surface height variability from Geosat altimeter data

Two years of data from the Geosat Exact Repeat Mission are employed to study the annual and semiannual variability of sea-surface height on a global basis. The data are treated with atmospheric corrections and interpolations, and the orbit error of about 40 cm RMS is purged. The spatial variability of the Geosat data is constructed for particular frequencies, and the estimate of the M2 tidal error indicates that the error is aliased to 1.15 cycles/yr and has an unusual spatial pattern. Sine and cosine coefficients are derived for the annual and semiannual frequencies by means of a least squares fit yielding the amplitude and phase of the changes in sea-surface height. A 180-deg phase difference is noted between the Northern and Southern Hemispheres for the annual variability, and large-scale westward propagating waves are identified. The Geosat data also indicate the phase relationships between major current systems and the systems of variations at work in the Intertropical Convergence Zone.

Jacobs, Gregg A.↗
DOE OSTI2020

The Southern hemisphere midlatitude circulation response to rapid adjustments and sea surface temperature driven feedbacks

Rapid adjustments – the response of meteorology to external forcing while sea surface temperatures (SST) and sea ice are held fixed – can affect the midlatitude circulation and contribute to long-term forced circulation responses in climate simulations. This study examines rapid adjustments in the Southern hemisphere (SH) circulation using nine models from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), which perform fixed SST and coupled ocean experiments for five perturbations: a doubling of carbon dioxide (2xCO2), a tripling of methane (3xCH4), a five-fold increase in sulphate aerosol (5xSO4), a ten-fold increase in black carbon aerosol (10xBC) and a 2% increase in solar constant (2%Sol). In the coupled experiments, the SH eddy-driven jet shifts poleward and strengthens for forcings that produce global warming (and vice versa for 5xSO4), with the strongest response found in austral summer. In austral winter, the responses project more strongly onto a change in jet strength. For 10xBC, which induces strong shortwave absorption, the multi-model mean (MMM) rapid adjustment in DJF jet latitude is ~75% of the change in the coupled simulations. For the other forcings, which induce larger SST changes, the effect of SST-mediated feedbacks on the SH circulation is larger than the rapid adjustment. Nevertheless, for these perturbations the magnitude of the MMM jet shift due to the rapid adjustment is still around 25-33% of that in the coupled experiments. The results demonstrate the need to understand the mechanisms for rapid adjustments in the midlatitude circulation, in addition to the effect of changing SSTs.

Wood, Thomas↗
NASA NTRSDate not supplied

Improving Ocean Reanalyses and ENSO Forecasts By Assimilation of Rain Corrected Satellite Sea Surface Salinity Using the GMAO S2S Forecast System

During the past years, we have seen that the La Nina to El Nino transition has had a significant global socio-economic impact and so has been the key focus for improving coupled ocean-atmosphere forecasts. Assimilation of satellite altimetry and subsurface temperature and salinity from (mostly) Argo help to improve the initialization of the thermocline, while satellite Sea Surface Temperature (SST) aids in constraining surface heat-fluxes, leading to improved subseasonal to seasonal forecasts of the coupled system. However, few studies have focused on improving the fresh-water flux and near-surface density and mixing through assimilation of satellite sea surface salinity (SSS). For expediency, the few ocean models that do assimilate SSS bias-correct the satellite SSS data to normalize towards the near-surface Argo data. However, in rainy regions, where buoyant water sits as a fresh lens at the surface, this assumption is likely inadequate. In previous work, we have shown that adjusting SSS data to bulk salinity (Sb) using the Rain Impact Model (RIM) of Santos-Garcia et al., 2014 has improved the near-surface density and mixed layer depth, leading to deeper thermocline and improved the NINO3.4 SST forecasts. Now we utilize the Soil Moisture/Ocean Salinity, Rain Corrected (SMOS_RC) SSS product provided by the Centre Aval de Traitement des données SMOS (CATDS CPDC) to represent the Sb more accurately at first model layer (in our case 5 m). Rather than using a diffusivity model as with RIM, SMOS_RC relies on an observed relationship between the spatial heterogeneity of SMOS SSS and instantaneous rain rate (RR) (Supply et al., 2020). In order to test the impact of SMOS_RC versus SMOS, we compare two reanalyses over the period 2014 to 2021. For both reanalysis experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF scheme (Penny et al., 2013). One reanalysis additionally assimilates SMOS SSS data as is (i.e., with the fresh bias), and a separate reanalysis is performed assimilating the SMOS_RC data. We assess the impact for near-surface and subsurface dynamics within ocean reanalyses by validating against observations and explore how SSS assimilation (SMOS versus SMOS_RC) impacts dynamical ENSO forecasts using the NASA GMAO Sub-seasonal to Seasonal coupled forecast system (GEOS S2S-3, Molod et al., 2020, Hackert et al., 2023). We will show that improved SSS estimates and near-surface density and mixing led to more accurate coupled air/sea interaction and better ENSO forecasts.

Eric Hackert↗
NASA NTRS1972

A multispectral technique to determine sea surface temperature using Nimbus 2 data.

Three channels of the Nimbus 2 five-channel Medium Resolution Infrared Radiometer have been employed in the development of a technique to determine sea surface temperature. Two of the channels in the 0.2-4.0 and 6.4-6.9 micron spectral regions are used to indicate a cloud-free line of sight and the third, a high signal-to-noise window channel (10-11 microns), measures the equivalent blackbody temperature (Tbb) which is a function of the thermal emission from the sea surface and the intervening atmosphere. Equivalent blackbody temperatures and normalized reflectance thresholds were established using frequency distributions from the 6.4-6.9 and 0.2-4.0 micron channels, respectively, to determine the existence of cloud-free conditions. The window Tbb's were compared with ship ocean temperature measurements for a one-month period over the western North Atlantic. This comparison revealed a plus or minus 1.5 K dispersion about the mean difference between the ship temperatures and window Tbb's between 31-34 N.

Shenk, W. E.↗
NASA NTRS1984

Satellite-Derived Sea Surface Temperature: Workshop-2

Global accuracies and error characteristics of presently orbiting satellite sensors are examined. The workshops are intended to lead to a better understanding of present capabilities for sea surface temperature measurement and to improve measurement concepts for the future. Data from the Advanced Very High Resolution Radiometer AVHRR and Scanning Multichannel Microwave Radiometer is emphasized. Some data from the High Resolution Infrared Sounder HIRS and AVHRR are also examined. Comparisons of satellite data with ship and eXpendable BathyThermograph XBT measurement show standard deviations in the range 0.5 to 1.3 C with biases of less than 0.4 C, depending on the sensor, ocean region, and spatial/temporal averaging. The Sea Surface Temperature SST anomaly maps show good agreement in some cases, but a number of sensor related problems are identified.

Njoku, E. G.↗
NASA NTRS1988

The dependence of sea surface slope on atmospheric stability and swell conditions

A tower-mounted optical device is used to measure the two-orthogonal components of the sea surface slope. The results indicate that an unstable stratification at the air-sea interface tends to enhance the surface roughness. The presence of a long ocean swell system steers the primary direction of shortwave propagation away from wind direction, and may increase or reduce the mean square slope of the sea surface.

Hwang, Paul A.↗
NASA NTRS1999

Sea Surface Slope Statistics for Intermediate and Shore Scale Ocean Waves Measured Using a Low-Altitude Aircraft

Ocean surface remote sensing techniques often rely on scattering or emission linked to shorter- scale gravity-capillary ocean wavelets. However, it is increasingly apparent that slightly longer wavelengths of O(10 to 500 cm) are vital components in the robust sea surface description needed to link varied global remote sensing data sets. This paper describes a sensor suite developed to examine sea surface slope variations in the field using an aircraft flying at very low altitude (below 30 m) and will also provide preliminary measurements detailing changes in slope characteristics versus sea state and friction velocity. Two-dimensional surface slope is measured using simultaneous range measurements from three compact short-range laser altimeters mounted in an equilateral triangle arrangement with spacing of about 1 m. In addition, all three lasers provide independent wave elevation profiles after GPS-aided correction for aircraft altitude. Laser range precision is 1 cm rms while vertical motion correction is 15 cm rms. The measurements are made along-track at approximately 1 m intervals setting the spatial scale of the measurement to cover waves of intermediate to long scale. Products available for this array then include surface elevation, two-dimensional slope distribution, and the cross- and along-track 1-D slope distributions. To complement the laser, a down-looking mm-wave radar scatterometer is centered within the laser array to measure radar backscatter simultaneously with the laser slope. The radar's footprint is nominally 1 m in diameter. Near-vertical radar backscatter is inversely proportional to the small-scale surface slope variance and to the tilt of the underlying (laser-measured) surface facet. Together the laser and radar data provide information on wave roughness from the longest scales down to about 1 cm. These measurements are complemented by aircraft turbulence probe data that provides robust surface flux information.

Vandemack, Douglas↗
DOE OSTI2020

On the Correspondence between Seasonal Forecast Biases and Long-Term Climate Biases in Sea Surface Temperature

In this paper, the correspondence between mean sea surface temperature (SST) biases in retrospective seasonal forecasts (hindcasts) and long-term climate simulations from five global climate models is examined to diagnose the degree to which systematic SST biases develop on seasonal time scales. The hindcasts are from the North American Multi-Model Ensemble and the climate simulations are from the Coupled Model Intercomparison Project. The analysis suggests that most robust climatological SST biases begin to form within 6 months of a realistically initialized integration, although the growth rate varies with location, time, and model. In regions with large biases, interannual variability and ensemble spread is much smaller than the climatological bias. Additional ensemble hindcasts of the Community Earth System Model with a different initialization method suggest that initial conditions do matter for the initial bias growth, but the overall global bias patterns are similar after 6 months. A hindcast approach is more suitable to study biases over the tropics and sub-tropics than over the extra-tropics because of smaller initial biases and faster bias growth. The rapid emergence of SST biases makes it likely that fast processes with times scales shorter than the seasonal time scales in the atmosphere and upper ocean are responsible for a substantial part of the climatological SST biases. Studying the growth of biases may provide important clues to the causes and ultimately the amelioration of these biases. Further, initialized seasonal hindcasts can profitably be used in the development of high-resolution coupled ocean-atmosphere models.

54 ENVIRONMENTAL SCIENCES↗