Satellite gathers weather data from sensors on balloons
The collection of meteorological, oceanographic, and ice data by Nimbus-6 from floating platforms is briefly described.
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The collection of meteorological, oceanographic, and ice data by Nimbus-6 from floating platforms is briefly described.
The benefits of satellite-based radar altimetry for oceanographic research are discussed in connection with the Seasat Altimeter Data Seminar. After a general review of the oceanographic data collected by the Seasat and GEOS-3 satellites, a number of criteria are proposed for the successful operation of a satellite-based radar altimeter for oceanographic remote sensing applications. It is shown how the interpretation of altimeter return power waveforms can be used to calculate wind speed, ocean circulation and variability in wind, waves, and tides. A number of recommendations for improving the accuracy of radar altimeter data are given which may be incorporated in the design of the GEOSAT and TOPEX research satellites.
A data acquisition system using a Litton LTN-51 inertial navigation unit (INU) was tested and used for aircraft track recovery and for location and tracking from the air of targets at sea. The characteristic position drift of the INU is compensated for by sighting landmarks of accurately known position at discrete time intervals using a visual sighting system in the transparent nose of the Beechcraft 18 aircraft used. For an aircraft altitude of about 300 m, theoretical and experimental tests indicate that calculated aircraft and/or target positions obtained from the interpolated INU drift curve will be accurate to within 10 m for landmarks spaced approximately every 15 minutes in time. For applications in coastal oceanography, such as surface current mapping by tracking artificial targets, the system allows a broad area to be covered without use of high altitude photography and its attendant needs for large targets and clear weather.
Interrogation, recording and location system to be carried on Nimbus B satellite as data link for surface network stations recording geophysical, oceanographic and meteorological data
Large offshore structures used for the deployment of optical instruments can significantly perturb the intensity of the light field surrounding the optical measurement point, where different portions of the visible spectrum are subject to different shadowing effects. These effects degrade the quality of the acquired optical data and can reduce the accuracy of several derived quantities, such as those obtained by applying bio-optical algorithms directly to the shadow-perturbed data. As a result, optical remote sensing calibration and validation studies can be impaired if shadowing artifacts are not fully accounted for. In this work, the general in-water shadowing problem is examined for a particular case study. Backward Monte Carlo (MC) radiative transfer computations- performed in a vertically stratified, horizontally inhomogeneous, and realistic ocean-atmosphere system are shown to accurately simulate the shadow-induced relative percent errors affecting the radiance and irradiance data profiles acquired close to an oceanographic tower. Multiparameter optical data processing has provided adequate representation of experimental uncertainties allowing consistent comparison with simulations. The more detailed simulations at the subsurface depth appear to be essentially equivalent to those obtained assuming a simplified ocean-atmosphere system, except in highly stratified waters. MC computations performed in the simplified system can be assumed, therefore, to accurately simulate the optical measurements conducted under more complex sampling conditions (i.e., within waters presenting moderate stratification at most). A previously reported correction scheme, based on the simplified MC simulations, and developed for subsurface shadow-removal processing of in-water optical data taken close to the investigated oceanographic tower, is then validated adequately under most experimental conditions. It appears feasible to generalize the present tower-specific approach to solve other optical sensor shadowing problems pertaining to differently shaped deployment platforms, and also including surrounding structures and instrument casings.
Results from a flight test of a GPS carrier phase tracking receiver operated on a NASA Orion P-3 aircraft are presented. The trajectory of the aircraft relative to a second, fixed receiver has been determined. The test was made over water, and the GPS vertical trajectory is compared to airborne lidar measured altitude data from the NASA Airborne Oceanographic Lidar. The two data sets compare with a relative accuracy of 12 centimeters rms, under poor GPS satellite geometry for vertical positioning. Analysis indicates that 1 to 2 centimeters relative vertical positioning is achievable with carrier phase tracking receivers and good GPS geometry.
In general, terrestrial scenes remain stable in content from both temporal and spacial considerations. Ocean scenes, on the other hand, are constantly changing in content and position. The solar energy that enters the ocean waters undergoes a process of scattering and selective spectral absorption. Ocean scenes are thus characterized as low level radiance with the major portion of the energy in the blue region of the spectrum. Terrestrial scenes are typically of high level radiance with their spectral energies concentrated in the green-red regions of the visible spectrum. It appears that for the evaluation and calibration of ocean color remote sensing instrumentation, an ocean area whose optical ocean and atmospheric properties are known and remain seasonably stable over extended time periods is needed. The Tongue of the Ocean, a major submarine channel in the Bahama Banks, is one ocean are for which a large data base of oceanographic information and a limited amount of ocean optical data are available.
The oceans are an equal partner with the atmosphere in the global climate system. The World Ocean Circulation Experiment is presently being implemented to improve ocean models that are useful for climate prediction both by encouraging more model development but more importantly by providing quality data sets that can be used to force or to validate such models. WOCE is the first oceanographic experiment that plans to generate and to use multiparameter global ocean data sets. In order for WOCE to succeed, oceanographers must establish and learn to use more effective methods of assembling, quality controlling, manipulating and distributing oceanographic data.
This document provides an overview of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-Optical Archive and Storage System (SeaBASS), which will serve as a repository for numerous data sets of interest to the SeaWiFS Science Team and other approved investigators in the oceanographic community. The data collected will be those data sets suitable for the development and evaluation of bio-optical algorithms which include results from SeaWiFS Intercalibration Round-Robin Experiments (SIRREXs), prelaunch characterization of the SeaWiFS instrument by its manufacturer -- Hughes/Santa Barbara Research Center (SBRC), Marine Optical Characterization Experiment (MOCE) cruises, Marine Optical Buoy (MOBY) deployments and refurbishments, and field studies of other scientists outside of NASA. The primary goal of the data system is to provide a simple mechanism for querying the available archive and requesting specific items, while assuring that the data is made available only to authorized users. The design, construction, and maintenance of SeaBASS is the responsibility of the SeaWiFS Calibration and Validation Team (CVT). This report is concerned with documenting the execution of this task by the CVT and consists of a series of chapters detailing the various data sets involved. The topics presented are as follows: 1) overview of the SeaBASS file architecture, 2) the bio-optical data system, 3) the historical pigment database, 4) the SIRREX database, and 5) the SBRC database.
The present and future use of satellites to locate offshore platforms and relay data from in situ sensors to shore was examined. A system of the ARGOS type will satisfy the increasing demand for oceanographic information through data relay and platform location. The improved ship navigation provided by the Global Positioning System (GPS) will allow direct observation of currents from underway ships. Ocean systems are described and demand estimates on satellite systems are determined. The capabilities of the ARGOS system is assessed, including anticipated demand in the next decade.
The problem of data integration in oceanography is discussed. Recommendations are made for technique development and evaluation, understanding requirements, and packaging techniques for speed, efficiency and ease of use. The primary satellite sensors of interest to oceanography are summarized. It is concluded that imaging type sensors make image processing an important tool for oceanographic studies.
PC-SEAPAK is user-interactive software package specifically developed for analysis of data from satellites in oceanographic research. Program used to process and interpret data obtained from Nimbus-7/Coastal Zone Color Scanner (CZCS) and NOAA Advanced Very High Resolution Radiometer (AVHRR). PC-SEAPAK copyrighted product with all copyright vested in National Aeronautics and Space Administration.
NASA Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a web-based remote sensing and model data visualization and analysis system developed by the Goddard Earth Sciences Data and Information Services Center (GES DISC). This web-based tool facilitates data discovery, exploration and analysis of large amount of global and regional data sets, covering atmospheric dynamics, atmospheric chemistry, hydrology, oceanographic, and land surface. Data analysis functions include Lat-Lon map, time series, scatter plot, correlation map, difference, cross-section, vertical profile, and animation etc. Visualization options enable comparisons of multiple variables and easier refinement. Recently, new features have been developed, such as interactive scatter plots and maps. The performance is also being improved, in some cases by an order of magnitude for certain analysis functions with optimized software. We are working toward merging current Giovanni portals into a single omnibus portal with all variables in one (virtual) location to help users find a variable easily and enhance the intercomparison capability
Description of the major features of a multispectral scanner designed to perform overland and oceanographic surveys from space. The instrument uses an image plane conical scanner and contains independent spectrometers for land and ocean applications. The overland spectrometer has a spatial resolution of 200 ft and has six spectral bands in the atmospheric windows between 0.5 and 2.4 microns. The oceanographic spectrometer has a spatial resolution of 1200 ft and possesses 24 spectral bands equally spaced and in registration over the wavelength range from 0.4 to 0.8 micron. A thermal band of 600-ft resolution is used with a spectral range from 10.5 to 12.6 microns. The swath width of the scan is 100 nautical miles from an altitude of 500 nautical miles. The system has two modes of operation which are selectable by ground command. The six bands of overland data plus the thermal band data can be transmitted, or the 24 bands of oceanographic data plus data from two of the overland bands and the thermal band can be transmitted. The performance is described by the minimum detectable reflectance difference and the effects of sun angle and target reflectivity variations are discussed. The sensitivity is related to the variation of the ocean reflectivity in the presence of chlorophyll and to typical agricultural targets.
Collecting data and understanding data structures traditionally are the first steps that a user must take, before the core investigation can begin. This is a time-consuming and challenging task, especially when science objectives require users to deal with large multi-sensor data that are usually in different formats and internal structures. The Goddard Earth Sciences Data and Information Services Center (GES DISC) has created the GES DISC Interactive Online Visualization and ANalysis Infrastructure, Giovanni, to enable Web-based visualization and analysis of satellite remotely sensed meteorological, oceanographic, and hydrologic data sets, without users having to download data. The current operational Giovanni interfaces provide the capability to process a number of important satellite measurements, such as (1) ozone and other trace gases from TOMS, OMI, HALOE, and MLS; (2) air temperature, water vapor, and geopotential height from AIRS; (3) aerosols from MODIS TerrdAqua, and GOCART model; (4) precipitation from TRMM and ground measurements; (5) chlorophyll and other ocean color products from SeaWiFS and MODIS Aqua; and (6) sea surface temperature from MODIS Aqua. Depending on the input data structure, the system provides simple statistical analysis and creates time-averaged area plot, area-averaged time series, animations, Hovmoller latitude vs. time and longitude vs. time plots, as well as vertical profiles. The inter-comparison interfaces allow a user to compare observations from different instruments, to conduct anomaly analysis, and to study basic relationships between physical parameters. Giovanni handles data with different temporal and spatial resolutions and, thus, enables both regional and global long-term climate research and short-term special events investigation, as well as data validations and assessments. Because of its simplicity of usage, Giovanni is powerful and versatile, able to assist a wide range of users, from the discipline scientists conducting preliminary research in various fields, to students in the classroom learning about weather, climate, and other natural phenomena. Giovanni can be accessed from: http://disc. esfc.nasa.gov/techlab/giovanni/index.shtml
The methodology of interpretation of remote sensing data and its oceanographic applications are described. The elements of image interpretation for different types of sensors are discussed. The sensors utilized are the multispectral scanner of LANDSAT, and the thermal infrared of NOAA and geostationary satellites. Visual and automatic data interpretation in studies of pollution, the Brazil current system, and upwelling along the southeastern Brazilian coast are compared.
De-aliased SEASAT SASS vector winds obtained during the GOASEX (Gulf of Alaska SEASAT Experiment) program were processed to obtain superobservations centered on a one degree by one degree grid. The results provide values for the combined effects of mesoscale variability and communication noise on the individual SASS winds. Each grid point of the synoptic field provides the mean synoptic east-west and north-south wind components plus estimates of the standard deviations of these means. These superobservations winds are then processed further to obtain synoptic scale vector winds stress fiels, the horizontal divergence of the wind, the curl of the wind stress and the vertical velocity at 200 m above the sea surface, each with appropriate standard deviations for each grid point value. The resulting fields appear to be consistant over large distances and to agree with, for example, geostationary cloud images obtained concurrently. Their quality is far superior to that of analyses based on conventional data.
Reservations were expressed concerning the sum of squares wind recovery algorithm and the power law model function. The SAS sum of squares (SOS) method for recovering winds from backscatter data leads to inconsistent results when V pol and H pol winds are compared. A model function that does not use a power law and that accounts for sea surface temperature is needed and is under study both theoretically and by means of the SASS mode 4 data. Aspects of the determination of winds by means of scatterometry and of the utilization of vector wind data for meteorological forecasts are elaborated. The operational aspect of an intermittent assimilation scheme currently utilized for the specification of the initial value field is considered with focus on quantifying the absolute 12-hour linear displacement error of the movement of low centers.