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This Technical Note provides the design document, database specification, and database administration for the NIDAS Version 3.1 System Developed for the Naval Oceanographic Office.
Global pressure data are often needed for processing or interpreting modern geodetic and oceanographic measurements. The most common source of these data is the analysis or reanalysis products of various meteorological centers. Tidal signals in these products can be problematic for several reasons, including potentially aliased sampling of the semidiurnal solar tide as well as the presence of various modeling or timing errors. Building on the work of Van den Dool and colleagues, we lay out a strategy for handling atmospheric tides in (re)analysis data. The procedure also offers a method to account for ocean loading corrections in satellite altimeter data that are consistent with standard ocean-tide corrections. The proposed strategy has immediate application to the on-going Jason-1 and GRACE satellite missions.
For many years, merchant ships and the naval fleets of various countries have been the major source of data over and in the open ocean. Oceanographic research experiments and process studies in the field have also contributed to the climatological data bases for the global ocean, but, for the most part, these have been limited in duration and extent. However, over the last 10 years under the auspices of the World Climate Research Program and the International Geosphere Biosphere Program the role of the oceans in global and climate change has taken on increased significance. This has created a need for a considerably improved understanding of the seasonal, interannual, decadal and longer time-scale variability of the physical and biogeochemical attributes of the global ocean. As a result, over the past 10 years several major international field programs have been implemented and have had a tremendous impact on the number of in situ observations obtained for the global ocean. The Tropical Ocean Global Atmosphere (TOGA) program, the World Ocean Circulation Experiment (WOCE), and the Joint Global Ocean Flux Study (JGOFS) were designed with observational, modelling, and process study components aimed at analyzing different aspects of the ocean's role in the coupled climate system. In parallel with the field programs, continuous space-based observations of sea surface temperature, sea surface topography, and sea surface winds spanning nearly a decade or longer have become a reality. During this same time period, numerical ocean models and computational power have advanced to the point where the oceanographic observations, both in situ and remotely sensed, can be assimilated into numerical ocean models in order to provide a four-dimensional (x-y-z-t) depiction of the evolving state of the global ocean.
Remote sensing data collected with the airborne lidar oceanographic probing experiment (ALOPE) laser fluorosensor during the Superflux 1 and Superflux 2 experiments were analyzed using two techniques. A qualitative technique which requires no supplementary data provided a near-real-time estimate of relative abundance of the golden-brown and green phytoplankton color groups. Contour plots developed for the later mission are used to demonstrate the utility of this technique. A quantitative technique which requires supplementary data to define the attenuation coefficient provides chlorophyll a concentration by color group. The sum of the golden-brown and green chlorophyll a data yields total chlorophyll a values which may be compared with in situ data. As expected, the golden-brown population was dominant in the Chesapeake Bay and the Bay plume whereas the green population was dominant in shelf waters.
The Gravimetric Geodesy Investigation which will utilize altimeter and satellite-to-satellite tracking data from GEOS-C, ATS-F, and other spacecraft as appropriate to improve our knowledge of the earth's gravitational field is discussed. This investigation is interrelated with the study of oceanographic phenomena such as those associated with tides and currents, hence the latter are considered together with gravitational effects in the analysis of the data. The oceanographic effects, each of the order of a meter or two in amplitude and with still smaller uncertainties does not seriously hamper the altimeter gravimetric studies at the five meter level. Laser and satellite-to-satellite tracking data, when combined with the altimeter results, should provide the basis for such studies over wide areas of the ocean surface. Laser and conventional geodetic tracking data from ISAGEX and succeeding campaigns will provide a valuable framework for these analyses.
The author has identified the following significant results. This 15-month ERTS-1 investigation produced correlations between satellite, aircraft, menhaden fisheries, and environmental sea truth data from the Mississippi Sound. Selected oceanographic, meteorological, and biological parameters were used as indirect indicators of the menhaden resource. Synoptic and near real time sea truth, fishery, satellite imagery, aircraft acquired multispectral, photo and thermal IR information were acquired as data inputs. Computer programs were developed to manipulate these data according to user requirements. Preliminary results indicate a correlation between backscattered light with chlorophyll concentration and water transparency in turbid waters. Eight empirical menhaden distribution models were constructed from combinations of four fisheries-significant oceanographic parameters: water depth, transparency, color, and surface salinity. The models demonstrated their potential for management utilization in areas of resource assessment, prediction, and monitoring.
The Arctic Ocean remains one of the most poorly sampled regions on Earth, where improved in situ environmental monitoring is vital for advancing oceanographic and atmospheric studies. However, data collection efforts are constrained by the short operational lifespans and high costs of conventional systems. Drifting buoys powered by pendulum-driven wave energy harvesters offer a cost-effective alternative, yet earlier designs have neither been optimized for real-world wave conditions nor validated in the Arctic. In this study, we develop a self-powered drifting buoy that integrates a pendulum-driven triboelectric nanogenerator (TENG) system with a mechanical motion rectifier, a high-gear-ratio transmission, and power management circuits. Through coupled buoy–pendulum dynamic simulations and laboratory testing using a motion simulator, we identify an optimal pendulum mass of 1.6 kg (12.7% of total buoy weight) that maximizes energy output while maintaining buoy stability. Laboratory experiments achieved average power outputs of 12.7 mW under Arctic-like wave and temperature conditions. The system was successfully deployed in the Bering Sea, where it generated 11 J of energy in 3.1 m waves, marking the first Arctic deployment of a TENG-based drifting buoy for sea surface temperature monitoring. This work establishes a cost-effective framework for designing self-powered Arctic monitoring platforms and advances the feasibility of long-term environmental observations in real Arctic waters.
The offshore wind industry in the U.S. is gaining strong momentum to achieve sustainable energy goals, and the need for observations to provide resource characterization and model validation is greater than ever. Pacific Northwest National Laboratory (PNNL) operates two lidar buoys for the U.S. Department of Energy (DOE) in order to collect hub height wind data and associated meteorological and oceanographic information near the surface in areas of interest for offshore wind development. This work evaluates the performance of commonly used reanalysis products and spatial approximation techniques using lidar buoy observations off the coast of New Jersey and Virginia, USA. Reanalysis products are essential tools in order to set performance expectations and quantify the wind resource variability at a given site. Long-term accurate observations at typical wind turbine hub-heights have been lacking at offshore locations. Using wind speed observations from both lidar buoy deployments, biases and degrees of correspondence for the Modern Era Retrospective Analysis for Research and Applications-2 (MERRA-2), the North American Regional Reanalysis (NARR), and the analysis system of the Rapid Refresh (RAP) are examined both at hub height and near surface. Results provide insights on the performance and uncertainty of using reanalysis products for long-term wind resource characterization.
The development of hardware and software for an interactive, minicomputer based processing and display system for atmospheric and oceanographic information extraction and image data analysis is described. The major applications of the system are discussed as well as enhancements planned for the future.
Scalar aeromagnetic data obtained during the U.S. Naval Oceanographic Office (NOO)-Vector Magnetic Survey of the conterminous United States were upward continued by equivalent point source inversion and compared with POGO satellite magnetic anomaly and preliminary scalar MAGSAT data. Initial comparisons indicate that the upward continued NOO data is dominated by long wavelength (approximately equal to 1000 to 3000 km) anomalies which are not present in the satellite anomaly data. Thus, the comparison of the data sets is poor. Several possible sources for these differences are present in the data analysis chain. However, upon removal of these long wavelengths from the upward continued NOO data, a close comparison observed between the anomalies verifies that satellite magnetic anomaly data do portray the crustal component within a range of wavelengths from roughly 1000 km down to the resolution limit of the observations.
The 36-gigahertz surface contour radar and the airborne oceanographic lidar were used in the SIR-B underflight mission off the coast of Chile in October 1984. The two systems and some of their wave-measurement capabilities are described. The surface contour radar can determine the directional wave spectrum and eliminate the 180-degree ambiguity in wave propagation direction that is inherent in some other techniques such as stereophotography and the radar ocean wave spectrometer. The Airborne Oceanographic Lidar can acquire profile data on the waves and produce a spectrum that is close to the nondirectional ocean-wave spectrum for ground tracks parallel to the wave propagation direction.
There is obvious value in developing the means for measuring a number of subsurface oceanographic parameters using remotely sensed ocean color data. The first step in this effort should be the development of adequate theoretical models relating the desired oceanographic parameters to the upwelling radiances to be observed. A portion of a contributory theoretical model can be described by a modified single scattering approach based on a simple treatment of multiple scattering. The resulting quasisingle scattering model can be used to predict the upwelling distribution of spectral radiance emerging from the sea. The shape of the radiance spectrum predicted by this model for clear ocean water shows encouraging agreement with measurements made at the edge of the Sargasso Sea off Cape Hatteras.
The Kalman filter is a data-processing algorithm with a distinguished history in systems theory. Its application to oceanographic problems is in the embryo stage. The behavior of the filter is demonstrated in the context of an internal equatorial Rossby wave propagation problem.
The TOPEX Project is a proposed oceanographic mission to measure the topography of the sea surface for a period of three years. This mission is sponsored by the National Aeronautics and Space Administration and managed by the Jet Propulsion Laboratory. Measurements of topography are used to study ocean currents, tides, bathymetry and the oceanic geoid. Several of the primary goals of this mission are to process and verify the altimetric data, and distribute them within days to the science investigators. This paper describes the TOPEX end-to-end ground data system. In addition to controlling the TOPEX satellite, the ground data system has been designed to minimize the time from data acquisition to science processing and data distribution. A centralized design supports the favorable response time of the system and also allows for operational efficiencies. Networking of real time and non-real time elements of the data system provides for more effective data processing.
This paper describes an established method for providing the oceanographic and meteorological communities with long-term, calibrated satellite-derived data sets for studies of the role of the ocean in global climate change. Data from different spacecraft and sensors are in seven yearly volumes of 1987 through 1993, and some 1994 data are included.
Scalar aeromagnetic data obtained by the U.S. Naval Oceanographic Office (NOO) Vector Magnetic Survey of the conterminous U.S. were screened for periods of intense diurnal magnetic activity and reduced to anomaly form, filtered, and continued upward. A number of correlations between the NOO, POGO and preliminary MAGSAT data are evident at satellite elevations, including a prominent transcontinental magnetic high which extends from the Anadarko Basin to the Cincinnati Arch. The transcontinental magnetic high is breached by negative anomalies located over the Rio Grande Rift and Mississippi River Aulacogen. Differentially reduced-to-pole NOO and POGO magnetic anomaly data show that the transcontinental magnetic high corresponds to a well-defined regional trend of negative free-air gravity and enhanced crustal thickness anomalies.
Earth science researchers and data engineers have a common problem: they often need to compare data files to see what is different between them. A lot of time is spent developing code to test differences. When it comes to comparing multidimensional data file formats like netCDFs (Network Common Data Form), this is particularly challenging and time-consuming, since there is frequently a need to evaluate the differences between dimension sizes, variable structures, and variable attributes, especially for regression testing. Since netCDFs are widely used in Earth science — with climate models, oceanographic or atmospheric reanalyses, and observational data — improved means of evaluating netCDF files can help enable a wide range of applications. We have developed a reusable open source approach through `ncompare`, which is a Python package for comparing netCDF structures [[https://github.com/nasa/ncompare]]. The `ncompare` tool compares the structure of two Network Common Data Form (NetCDF) files at the command line. It facilitates rapid comparisons by generating a formatted display of the matching and non-matching groups, variables, and associated metadata between two NetCDF datasets. The user has the option to colorize the terminal output for ease of viewing, and `ncompare` can optionally save comparison reports in text, comma-separated value (CSV), and/or Microsoft Excel formats. Despite the availability of tools (such as ncmpidiff or nccmp) that compare the values of variables, there was not previously a readily available, Python-based tool for rapid visual comparisons of group and variable structures, attributes, and chunking. `ncompare` was developed at NASA’s Atmospheric Science Data Center (ASDC) and is a collaboration with NASA Openscapes [[https://nasa-openscapes.github.io]] mentors across 11 of NASA’s data centers. Openscapes’ overarching vision is to support scientific researchers using NASA Earthdata as they migrate their workflows to the cloud. Relevant links: - https://github.com/nasa/ncompare - https://github.com/pyOpenSci/software-submission/issues/146 - https://nasa-openscapes.github.io
Until a decade ago, an often-quoted expression in oceanography is that very few observations are recorded throughout the ocean. Now, the sentiment is no longer valid in the uppermost 10% of the tropical Pacific Ocean nor at the surface of the global ocean. One of the remarkable legacies of the 1985-1994 Tropical Oceans Global Atmosphere (TOGA) Program is an in situ marine meteorological and upper oceanographic measurement array throughout the equatorial Pacific to monitor the development and maintenance of El Nino episodes. The TOGA Observing System, which initially consisted of moored- and drifting-buoy arrays, a network of commercial ships, and coastal and island stations, now includes a constellation of satellites and data-assimilating models to simulate subsurface oceanographic conditions. The El Nino and La Nina tropical Pacific Ocean observing system represents the initial phase of an integrated global ocean observing system. Remarkable improvements have been made in ocean model simulation of subsurface currents, but some problems persist. For example, the simulation of the South Equatorial Current (SEC) remains an important challenge in the 2S-2N Pacific equatorial wave guide. During El Nino the SEC at the equator is reduced and sometimes the direction is reversed, becoming eastward. Both conditions allow warm water stored in the western Pacific to invade the eastern region, creating an El Nino episode. Assimilation of data is a tenet of faith to correct simulation errors caused by deficiencies in surface fluxes (especially wind stress) and parameterizations of subgrid-scale physical processes. In the first of two numerical experiments, the Pacific SEC was simulated with and without assimilation of subsurface temperature data. Along the equator, a very weak SEC occurred throughout the eastern Pacific, independent of assimilation of data. However, as displayed in the diagram, in the western Pacific there was no satisfactory agreement between the two simulations. To help determine reliability of the simulated SEC in the western Pacific, current measurements recorded during the 9-19 October 1994 voyage of the French research vessel L'Atalante are also shown in the diagram. With data assimilation, the simulated SEC was in much better agreement with L'Atalante observations. The simulated SEC with data assimilation was far from perfect, in part because of the sparsity of subsurface temperature observations. In the next experiment, TOPEX/POSEIDON sea surface height data in combination with subsurface temperatures will be assimilated to assess further improvement of the simulation of the SEC.