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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Morning-evening differences in global and regional oceanic precipitation as observed by the SSM/I

For the present preliminary analysis of oceanic rainfall statistics, global oceanic SSM/I data were simply scanned for pixels which exhibited a 37 GHz polarization difference (vertically polarized brightness temperatures minus horizontally polarized brightness temperatures) of less than 15 K. Such a low polarization difference over the open ocean is a completely unambiguous indication of moderate to intense precipitation. Co-located brightness temperatures from all seven channels of the SSM/I were saved for each pixel so identified. Bad scans and geographically mislocated block of data were objectively identified and removed from the resulting data base. We collected global oceanic rainfall data for two time periods, each one month in length. The first period (20 July-19 August 1987) coincides with the peak of the Northern Hemisphere summer. The second period (13 January-12 February 1988) coincides with the Northern Hemisphere winter.

Petty, Grant W.↗
NASA NTRS2004

Patterns and Variability in Global Ocean Chlorophyll: Satellite Observations and Modeling

Recent analyses of SeaWiFS data have shown that global ocean chlorophyll has increased more than 4% since 1998. The North Pacific ocean basin has increased nearly 19%. These trend analyses follow earlier results showing decadal declines in global ocean chlorophyll and primary production. To understand the causes of these changes and trends we have applied the newly developed NASA Ocean Biogeochemical Assimilation Model (OBAM), which is driven in mechanistic fashion by surface winds, sea surface temperature, atmospheric iron deposition, sea ice, and surface irradiance. The model utilizes chlorophyll from SeaWiFS in a daily assimilation. The model has in place many of the climatic variables that can be expected to produce the changes observed in SeaWiFS data. This enables us to diagnose the model performance, the assimilation performance, and possible causes for the increase in chlorophyll. A full discussion of the changes and trends, possible causes, modeling approaches, and data assimilation will be the focus of the seminar.

Gregg, Watson↗
NASA NTRS2021

Probabilistic Machine Learning Estimation of Ocean Mixed Layer Depth from Dense Satellite and Sparse In-Situ Observations

The ocean mixed layer plays an important role in the coupling between the upper ocean and atmosphere across a wide range of time scales. Estimation of the variability of the ocean mixed layer is therefore important for atmosphere-ocean prediction and analysis. The increasing coverage of in situ Argo profile data allows for an increasingly accurate analysis of the mixed layer depth (MLD) variability associated with deviations from the seasonal climatology. However, sampling rates are not sufficient to fully resolve subseasonal (<90 day) MLD variability. Yet, many multivariate observations-based analyses include implicit modeled subseasonal MLD variability. One analysis method is optimal interpolation of in situ data, but the interior analysis can be improved by leveraging surface data with regression or variational approaches. Here, we demonstrate how machine learning methods and satellite sea surface temperature, salinity, and height facilitate MLD estimation in a pilot study of two regions: the mid-latitude southern Indian and the eastern equatorial Pacific Oceans. We construct multiple machine learning architectures to produce weekly 1/2° gridded MLD anomaly fields (relative to a monthly climatology) with uncertainty estimates. We test multiple traditional and probabilistic machine learning techniques to compare both accuracy and probabilistic calibration. We validate our methodology by applying it to ocean model simulations. We find that incorporating sea surface data through a machine learning model improves the performance of spatiotemporal MLD variability estimation compared to optimal interpolation of Argo observations alone. These preliminary results are a promising first step for the application of machine learning to MLD prediction.

Machine Learning↗
NASA NTRS2000

A neural network to retrieve the mesoscale instantaneous latent heat flux over oceans from SSM/I observations

The turbulent latent and sensible heat fluxes are necessary to study heat budget of the upper ocean or initialize ocean general circulation models. In order to retrieve the latent heat flux from satellite observations authors mostly use a bulk approximation of the flux whose parameters are derived from different instrument. In this paper, an approach based on artificial neural networks is proposed and compared to the bulk method on a global data set and 3 local data sets.

SSM/I latent heat flux air-sea interactions↗
NASA NTRS1983

On the wave number spectrum of oceanic mesoscale variability observed by the SEASAT altimeter

The wave number spectrum of mesoscale variability in various parts of the oceans is computed on the basis of sea surface height variations measured by the SEASAT altimeter in nearly repeat orbits during the last 24 days of its mission, and it is noted that oceanic spectrum characteristics are dependent on the energy level of the mesoscale variability. On the basis of an assumed horizontal isotropy of mesoscale variability, scalar-wave number spectra of sea surface height and geostrophic kinetic energy are presented and the dynamical implications of these spectra are discussed. A rigorous examination of the effects of residual geoid and atmospheric water vapor on the computed oceanic spectra indicates that the general characteristics of the spectra were not significantly affected by them.

Fu, L.-L.↗
NASA NTRS2023

The Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) Project: A Review

The Southern Ocean serves as the primary gateway through which the intermediate, deep, and bottom waters of the ocean interact with the surface ocean (and thus the atmosphere), and it has a profound influence on the oceanic uptake of anthropogenic carbon and heat as well as nutrient resupply from the abyss to the surface. Yet it has been the least observed and understood region of the world ocean. The Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) project was implemented in 2014 with a goal to help remedy this deficit in observations and understanding. The SOCCOM project is based on two major advances that have the potential to transform understanding of the Southern Ocean. The first is the development of new biogeochemical sensors mounted on autonomous profiling floats that allow sampling of ocean biogeochemistry in 3-dimensional space. Floats may detect processes with a temporal resolution that ranges from hours to years. The second is that the climate modeling community finally has the computational resources and physical understanding to develop fully coupled climate models that can represent crucial, mesoscale processes in the Southern Ocean, as well as corresponding models that assimilate observations to produce a state estimate. The observational component, based on deployment of profiling floats with oxygen, nitrate, pH and bio-optical sensors, is generating vast amounts of new biogeochemical data that provide a year-round view of the Southern Ocean from the surface to 2000 m. The modeling effort is applying these observations and enhancing our understanding of the current ocean, and reducing uncertainty in projections of future carbon and nutrient cycles and climate. After nine years of operation, including a project renewal in the sixth year, the SOCCOM project has deployed more than 260 profiling floats. These floats have collected over 27,000 vertical profiles throughout the Southern Ocean. A data-assimilating biogeochemical state estimate model has been implemented. Here, the design of the SOCCOM project is reviewed and the scientific results that have been obtained are described. The project’s capability to help meet the observing system priorities outlined for a notional UN Decade for Ocean Sciences Southern Ocean observing system is assessed.

Jorge L. Sarmiento↗
NASA NTRS1978

The inverse problem: Ocean tides derived from earth tide observations

Indirect mapping ocean tides by means of land and island-based tidal gravity measurements is presented. The inverse scheme of linear programming is used for indirect mapping of ocean tides. Open ocean tides were measured by the numerical integration of Laplace's tidal equations.

Kuo, J. T.↗
NASA NTRS2020

Hawai'i Water Resources: Utilizing NASA Earth Observations to Assess Ocean Conditions Leading to the Spread of the Nuisance Red Algae (Chondria tumulosa) in Papahānaumokuākea Marine National Monument, Hawai’i

Chondria tumulosa, a newly discovered red alga, was observed in low abundance in 2016 but has since proliferated and is now smothering and decimating vast expanse of coral reefs in Manawai, located in Papahānaumokuākea Marine National Monument (PMNM). If the spread persists, the outbreak of this cryptogenic species could potentially cause region-wide ecosystem degradation. In coordination with the U.S. Fish and Wildlife Service, Marine National Monuments of the Pacific and the National Oceanographic and Atmospheric Administration (NOAA) Office of National Marine Sanctuaries’ Papahānaumokuākea Marine National Monument, this project created a tool to analyze oceanographic conditions (sea surface temperature (SST), chlorophyll-a, water velocity, salinity, turbidity) across the Monument that could potentially be driving the algal spread. The Google Earth Engine tool enabled the partners to visualize oceanographic conditions and gather time-series graphs utilizing Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS), Sentinel-3 Ocean and Land Colour Instrument (OLCI), Hybrid Coordinate Ocean Model (HYCOM) and NOAA's Climate Data Record in a user-friendly interface. The team used in situ SST data from subsurface temperature recorders provided by the partners to validate the tool's accuracy. Preliminary statistical analysis of MODIS data found warming trends in SST in Manawai as well as increased chlorophyll-a levels during the summer months in contrast to the control (non-infected) Lalo atoll. The tool did not aim to classify algal presence due to limited availability of higher resolution satellite imagery but instead enabled PMNM managers to monitor conditions that may be conducive to algal growth around the monument to make informed decisions and mitigation practices.

DEVELOP Project Summary↗
NASA NTRS1993

Ku-band ocean radar backscatter observations during SWADE

We present results obtained by an airborne Ku-band scatterometer during the Surface Wave Dynamics Experiment (SWADE). The specific objective of this study is to improve our understanding of the relationship between ocean radar backscatter and near surface winds. The airborne scatterometer, NUSCAT, was flown on the NASA Ames C-130 over an instrumented oceanic area near 37 deg N and 74 deg W. A total of 10 flights from 27 Feb. to 9 Mar. 1991 were conducted. Radar backscatter at incidence angles of 0 to 60 deg were obtained. For each incidence angle, the NUSCAT antenna was azimuthally scanned in multiple complete circles to measure the azimuthal backscatter modulations. Both horizontal and vertical polarization backscatter measurements were made. In some of the flights, the cross-polarization backscatter was measured as well. Internal calibrations were carried out throughout each of the flights. Preliminary results indicate that the radar was stable to +/-0.3 dB for each flight. In this paper, we present studies of the backscatter measurements over several crossings of the Gulf Stream. In these crossings, large air-sea temperature differences were encountered and substantial changes in the radar cross section were observed. We summarize the observations and compare them to the changes of several wind variables across the Gulf Stream boundary. In one of the flights, the apparent wind near the cold side of the Gulf Stream was very low (less than 3 m/s). The behavior of the radar cross sections at such low wind speeds and a comparison with models are presented. A case study of the effects of swell on the absolute cross section and the azimuthal modulation pattern is presented. Significant wave heights larger than m were observed during SWADE. The experimentally observed effects of the swell on the radar backscatter are discussed. The effects are used to assess the uncertainties in wind retrieval due to underlying waves. A summary of azimuthal modulation from our ten-flight of NUSCAT data is given. Wind velocities, air and sea surface temperature, ocean spectrum, and other variables measured from aircraft and buoys are also shown.

Nghiem, S. V.↗
NASA NTRS2016

Satellite Sea Ice Measurements in the Arctic Ocean

Satellite observations sustained since 1979 have been the primary source of information to reveal Arctic Ocean sea ice extent is diminishing rapidly. Sea ice is also thinning based on historical surface and near-surface records and more recent satellite retrievals. There is a new “normal” environment in the Arctic environment with substantial socio-economic impacts. A key question is: What are the spatial and temporal characteristics of the sea ice thickness distribution throughout the annual cycle, and what is the evolving inter-annual trend? Arctic Ocean sea ice conditions have been determined with passive microwave radiometer, active scatterometer and other satellite instrument measurements recorded by a continuing series of satellites. An important feature of the continuous time series measurements has been the overlap of each new satellite dataset with ongoing measurements so as to provide adequate time intervals for calibration and validation. Satellite instrument diversity has provided both coarse spatial resolution measurements over the entire Arctic Ocean for long-period time series and limited-duration fine spatial resolution data over selected regions for navigation and other applications. Satellite observations of Arctic Ocean sea ice will continue to increase in importance because predictability of sea ice is poor and societal interest is great. Unfortunately, however the sustainability of some critical elements of the current Arctic Ocean satellite measurement suite beyond 2020 remains uncertain, e.g., after the CryoSat-2 and ICESat-2 missions have concluded.

Halpern, David↗
NASA NTRS1992

Observation of mesoscale ocean features in the northeast Pacific using Geosat radar altimetry data

Mesoscale circulation in the Gulf of Alaska is studied by means of processed Geosat radar altimetry results with comparisons to observations of mesoscale eddies and surface circulation. The first set of Geosat data is treated by sea-surface height (SSH) binning in 1-deg latitude x 2-deg longitude boxes and analyzed by complex empirical orthogonal functions and 2D spectral analysis. The second set is taken from ascending Geosat tracks and analyzed as a time series. The Geosat data are compared to observational data including mesoscale eddies and fluctuations in mean surface circulation as well as sea-surface signals generated by numerical models. The data demonstrate the feasibility of a westward propagation of sea-level anomalies, and the Geosat SSH data are found to agree well with model solutions of seasonal variations in sea level in the northeast Pacific.

Matthews, Paul E.↗
NASA NTRS1992

Automated in situ observations of upper ocean biogeochemistry, bio-optics, and physics and their potential use for global studies

The processes controlling the flux of carbon in the upper ocean have dynamic ranges in space and time of at least nine orders of magnitude. These processes depend on a broad suite of inter-related biogeochemical, bio-optical, and physical variables. These variables should be sampled on scales matching the relevant phenomena. Traditional ship-based sampling, while critical for detailed and more comprehensive observations, can span only limited portions of these ranges because of logistical and financial constraints. Further, remote observations from satellite platforms enable broad horizontal coverage which is restricted to the upper few meters of the ocean. For these main reasons, automated subsurface measurement systems are important for the fulfillment of research goals related to the regional and global estimation and modeling of time varying biogeochemical fluxes. Within the past few years, new sensors and systems capable of autonomously measuring several of the critical variables have been developed. The platforms for deploying these systems now include moorings and drifters and it is likely that autonomous underwater vehicles (AUV's) will become available for use in the future. Each of these platforms satisfies particular sampling needs and can be used to complement both shipboard and satellite observations. In the present review, (1) sampling considerations will be summarized, (2) examples of data obtained from some of the existing automated in situ sampling systems will be highlighted, (3) future sensors and systems will be discussed, (4) data management issues for present and future automated systems will be considered, and (5) the status of near real-time data telemetry will be outlined. Finally, we wish to make it clear at the outset that the perspectives presented here are those of the authors and are not intended to represent those of the United States JGOFS program, the International JGOFS program, NOAA's C&GC program, or other global ocean programs.

Dickey, Tommy D.↗
NASA NTRS1993

The earth's radiation budget and its relation to atmospheric hydrology. III - Comparison of observations over the oceans with a GCM

The ability of the Colorado State University general circulation model (GCM) to simulate interactions between the hydrological cycle and the radiative processes on earth was examined by comparing various sensitivity relationships established by the model with those observed on earth, and the observed and calculated seasonal cycles of the greenhouse effect and cloud radiative forcing. Results showed that, although the GCM model used was able to simulate well some aspects of the observed sensitivities, there were many serious quantitative differences, including problems in the simulation of the column vapor in the tropics and an excessively strong clear-sky greenhouse effect in the mid-latitudes. These differences led to an underestimation by the model of the sensitivity of the clear-sky greenhouse to changes in sea surface temperature.

Stephens, Graeme L.↗
NASA NTRS1996

Altimeter Observations of Baroclinic Oceanic Inertia-Gravity Wave Turbulence

For a wide range of nonlinear wave processes - from capillary to planetary waves - theory predicts the existence of Kolmogorov-type spectral cascades of energy and other conserved quantities occuring via nonlinear resonant wave-wave interactions. So far, observations of wave turbulence (WT) have been limited to small-scale processes such as surface gravity and capillary-gravity waves.

wave processees capillary waves planetary waves Ko↗