WorldWideScience

Sample records for buoys

  1. National Data Buoy Center Buoy Locations

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Buoy table consists of location information, ownership, and general geographic descriptions of buoys and weather stations. In addition to buoys operated by the...

  2. NDBC Standard Meteorological Buoy Data

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) distributes meteorological data from moored buoys maintained by NDBC and others. Moored buoys are the weather sentinels of the...

  3. The universal buoy system

    Energy Technology Data Exchange (ETDEWEB)

    Mackintosh, Neil [Subsea Technology Services Inc., Houston, TX (United States); Bone, David [Ocean Resources Ltd., Dartmouth, Nova Scotia (Canada)

    2000-07-01

    This paper presents the evolution of a high stability buoys from the initial concept of a Sea Sentinel data acquisition buoy, to Mobil's Zafiro Flare buoy and the East Spar Sea Commander control buoy deployed offshore Australia 1996 and the Moss gas E-M field control buoy recently installed. Given the current economic climate in the offshore oil and gas industry, there is a need to exploit cost effective technologies for marginal field developments, involving long distant tie - backs [30 to 100 km]. Sea Commander provides an alternative solution for the safe, economic management of a remote sub sea production facility. This technology is applicable for both shallow and deep water developments. Ocean Resource/Mentor Sub sea have extended the range of the buoy solutions from control and chemical injection to reservoir pressure maintenance, water injection and power distribution/control of ESP's for well production boosting. Design concepts have also been developed for a complete process and sub sea storage facility for remote fields. A comparison of buoy based solutions compared with existing technologies will identify significant Capex advantages together with Opex reductions for both NPV and life cycle cost profiles. System availability and board ability will also be addressed. The buoy can be readily decommissioned/transported, therefore is ideally suited for multi-field deployment/amortisation. (author)

  4. Development of drifting buoys

    Digital Repository Service at National Institute of Oceanography (India)

    Nayak, M.R.; Peshwe, V.B.; Tengali, S.

    transmeters. This paper discusses the design aspects and performance characteristics of these buoys presenting a small fraction of the considerable data set acquired. The requiremnts for further inclusion of certain sensors and hardware are described...

  5. The universal buoy system (TUBS)

    Energy Technology Data Exchange (ETDEWEB)

    Bone, D.; Cousins, T.

    2000-07-01

    This paper will present the evolution of a high stability buoyant structure from the initial concept of a Sea Sentinel data acquisition buoy, to Mobil's Zafiro Flare buoy and the Sea Commander East Spar control buoy deployed offshore Australia which has been in successful operation since 1996 and the Mossgas E-M field control buoy currently being commissioned. Given the current economic climate in the offshore oil and gas industry, there is a need to exploit cost effective technologies for marginal field developments, involving long distant tie-backs [30 to 100 km]. The TUBS initiative provides an alternative solution for the safe, economic and management of a remote subsea production facility. This technology is applicable for both shallow and deepwater developments. (author)

  6. Mooring Line for an Oceanographic Buoy System

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A mooring line for an oceanographic buoy system includes four sections. The first section is a protected cable that is connectable to the buoy. The second section is...

  7. 33 CFR 62.23 - Beacons and buoys.

    Science.gov (United States)

    2010-07-01

    ... electronic navigation. Buoys vary in reliability because: (i) Buoy positions represented on nautical charts... not coincide with the dots or circles representing them on charts. (iii) Buoy positions are...

  8. Experimental design for drifting buoy Lagrangian test

    Science.gov (United States)

    Saunders, P. M.

    1975-01-01

    A test of instrumentation fabricated to measure the performance of a free drifting buoy as a (Lagrangian) current meter is described. Specifically it is proposed to distinguish between the trajectory of a drogued buoy and the trajectory of the water at the level of the drogue by measuring the flow relative to the drogue.

  9. Advanced Approach of Multiagent Based Buoy Communication

    Science.gov (United States)

    Gricius, Gediminas; Drungilas, Darius; Andziulis, Arunas; Dzemydiene, Dale; Voznak, Miroslav; Kurmis, Mindaugas; Jakovlev, Sergej

    2015-01-01

    Usually, a hydrometeorological information system is faced with great data flows, but the data levels are often excessive, depending on the observed region of the water. The paper presents advanced buoy communication technologies based on multiagent interaction and data exchange between several monitoring system nodes. The proposed management of buoy communication is based on a clustering algorithm, which enables the performance of the hydrometeorological information system to be enhanced. The experiment is based on the design and analysis of the inexpensive but reliable Baltic Sea autonomous monitoring network (buoys), which would be able to continuously monitor and collect temperature, waviness, and other required data. The proposed approach of multiagent based buoy communication enables all the data from the costal-based station to be monitored with limited transition speed by setting different tasks for the agent-based buoy system according to the clustering information. PMID:26345197

  10. Advanced Approach of Multiagent Based Buoy Communication

    Directory of Open Access Journals (Sweden)

    Gediminas Gricius

    2015-01-01

    Full Text Available Usually, a hydrometeorological information system is faced with great data flows, but the data levels are often excessive, depending on the observed region of the water. The paper presents advanced buoy communication technologies based on multiagent interaction and data exchange between several monitoring system nodes. The proposed management of buoy communication is based on a clustering algorithm, which enables the performance of the hydrometeorological information system to be enhanced. The experiment is based on the design and analysis of the inexpensive but reliable Baltic Sea autonomous monitoring network (buoys, which would be able to continuously monitor and collect temperature, waviness, and other required data. The proposed approach of multiagent based buoy communication enables all the data from the costal-based station to be monitored with limited transition speed by setting different tasks for the agent-based buoy system according to the clustering information.

  11. Evaluating Effectiveness of DART Buoy Networks

    CERN Document Server

    Percival, Donald B; Gica, Edison; Huang, Paul Y; Mofjeld, Harold O; Spillane, Michael C; Titov, Vasily V

    2016-01-01

    A performance measure for a DART tsunami buoy network has been developed. The measure is based on a statistical analysis of simulated forecasts of wave heights outside an impact site and how much the forecasts are degraded in accuracy when one or more buoys are inoperative. The analysis uses simulated tsunami height time series collected at each buoy from selected source segments in the Short-term Inundation Forecast for Tsunamis (SIFT) database and involves a set for 1000 forecasts for each buoy/segment pair at sites just offshore of selected impact communities. Random error-producing scatter in the time series is induced by uncertainties in the source location, addition of real oceanic noise, and imperfect tidal removal. Comparison with an error-free standard leads to root-mean-square errors (RMSEs) for DART buoys located near a subduction zone. The RMSEs indicate which buoy provides the best forecast (lowest RMSE) for sections of the zone, under a warning-time constraint for the forecasts of 3 hrs. The ana...

  12. Oceanographic measurements from the Texas Automated Buoy System (TABS)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Texas Automated Buoy System contains daily oceanographic measurements from seven buoys off the Texas coast from Brownsville to Sabine. The Texas General Land...

  13. IABP Drifting Buoy Pressure, Temperature, Position, and Interpolated Ice Velocity

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The International Arctic Buoy Programme (IABP) maintains a network of drifting buoys to provide meteorological and oceanographic data for real-time operational...

  14. Pacific Ocean buoy temperature date - TAO/TRITON database & National Buoy Data Center database

    Data.gov (United States)

    U.S. Environmental Protection Agency — Pacific Ocean buoy temperature data. This dataset is associated with the following publication: Carbone, F., M. Landis, C.N. Gencarelli, A. Naccarato, F. Sprovieri,...

  15. Dynamics of anchor last deployment of submersible buoy system

    Science.gov (United States)

    Zheng, Zhongqiang; Xu, Jianpeng; Huang, Peng; Wang, Lei; Yang, Xiaoguang; Chang, Zongyu

    2016-02-01

    Submersible buoy systems are widely used for oceanographic research, ocean engineering and coastal defense. Severe sea environment has obvious effects on the dynamics of submersible buoy systems. Huge tension can occur and may cause the snap of cables, especially during the deployment period. This paper studies the deployment dynamics of submersible buoy systems with numerical and experimental methods. By applying the lumped mass approach, a three-dimensional multi-body model of submersible buoy system is developed considering the hydrodynamic force, tension force and impact force between components of submersible buoy system and seabed. Numerical integration method is used to solve the differential equations. The simulation output includes tension force, trajectory, profile and dropping location and impact force of submersible buoys. In addition, the deployment experiment of a simplified submersible buoy model was carried out. The profile and different nodes' velocities of the submersible buoy are obtained. By comparing the results of the two methods, it is found that the numerical model well simulates the actual process and conditions of the experiment. The simulation results agree well with the results of the experiment such as gravity anchor's location and velocities of different nodes of the submersible buoy. The study results will help to understand the conditions of submersible buoy's deployment, operation and recovery, and can be used to guide the design and optimization of the system.

  16. Air-Sea Interaction Spar Buoy Systems

    Science.gov (United States)

    2009-01-01

    properties and local slope and pressure above the waves are key to understanding the wave generation problem on the ocean. Ocean Turbulence: Hot wire ...staff wires in storm-forced sea states. APPROACH We are building on the previous success of the ASIS buoy and better state-of-the-art...film anemometry has a special place in fluid dynamics research, but they cannot be easily deployed in open ocean conditions. On the other hand

  17. 47 CFR 90.248 - Wildlife and ocean buoy tracking.

    Science.gov (United States)

    2010-10-01

    ... 47 Telecommunication 5 2010-10-01 2010-10-01 false Wildlife and ocean buoy tracking. 90.248... SERVICES PRIVATE LAND MOBILE RADIO SERVICES Non-Voice and Other Specialized Operations § 90.248 Wildlife... tracking of, and the telemetry of scientific data from, ocean buoys and animal wildlife. (b)...

  18. Time Lapse Photography From Arctic Buoys

    Science.gov (United States)

    Valentic, T. A.; Matrai, P.; Woods, J. E.

    2013-12-01

    We have equipped a number of buoys with cameras that have been deployed throughout the Arctic. These systems need to be simple, reliable and low power. The images are transmitted over an Iridium satellite link and assembled into long running movies. We have captured a number of interesting events, observed the ice dynamics through the year and visits by local wildlife. Each of the systems have been deployed for periods of up to a year, with images every hour. The cameras have proved to be a great outreach tool and are routinely watched by number of people on our websites. This talk will present the techniques used in developing these camera systems, the methods used for reliably transmitting the images and the process for generating the movies.

  19. Response of surface buoy moorings in steady and wave flows

    Digital Repository Service at National Institute of Oceanography (India)

    Anand, N.M.; Nayak, B.U.; SanilKumar, V.

    A numerical model has been developed to evaluate the dynamics of surface buoy mooring systems under wave and current loading. System tension response and variation of tension in the mooring line at various depths have been evaluated for deep water...

  20. Directional waverider buoy in Indian waters - Experiences of NIO

    Digital Repository Service at National Institute of Oceanography (India)

    AshokKumar, K.; Diwan, S.G.

    Information on directional waves is extremely important in the design of harbour structures, such as breakwaters and jetties and to study the sediment transport pattern. Till recent days our country has been using waverider buoys which give all wave...

  1. NOAA marine environmental buoy data from the National Data Buoy Center for March 2004 (NCEI Accession 0001418)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Meteorological data were collected using buoy and other instruments from fixed platforms in the North Pacific Ocean and other locations. Data were collected and...

  2. Drifting buoy data from buoy casts in a world wide distribution as part of the Tropical Ocean Global Atmosphere (TOGA) from 1989-07-01 to 1989-07-31 (NODC Accession 8900227)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Drifting buoy data were collected using buoy casts in a world wide distribution from July 1, 1989, to July 31, 1989. Data were submitted by National Data Buoy Center...

  3. GNSS Buoy Array in the Ocean for Natural Hazard Mitigation

    Science.gov (United States)

    Kato, T.; Terada, Y.; Yamamoto, S. I.; Iwakiri, N.; Toyoshima, M.; Koshikawa, N.; Motohashi, O.; Hashimoto, G.; Wada, A.

    2015-12-01

    The GNSS buoy system for tsunami early warning has been developed in Japan. The system has been implemented as a national wave monitoring system and its record was used to update the tsunami warning at the 3.11 Tohoku-oki earthquake. The lessons learned in this experience was that the buoys are placed only less than 20km from the coast, which was not far enough for effective evacuation of people. We thus tried to improve the system for putting the buoy much farther from the coast. First, we tried to implement, different from current baseline mode RTK-GPS, a real-time PPP analysis strategy for positioning. In addition, we tried to use a two-way satellite data transmission in contrast with current surface radio system. We have made a series of experiments for this purpose in 2013 and 2014. A buoy of about 40km south of Shikoku, southwest Japan, was used for this purpose. GEONET data were used to obtain precise orbits and clocks of satellites. Then, the information was transferred to the GNSS buoy using LEX signal of QZSS satellite system. The received information on the buoy were used for real-time PPP analysis for every second. The obtained buoy position was then transmitted to the ground base, through an engineering test satellite, ETS-VIII. The received data was then disseminated to public through the internet. Both filtered short-term and long-term waves, were separately shown on the webpage. The success of these experiments indicates that the GNSS buoy can be placed at least more than 1,500 km from the ground based tracking network. Given this success, we would now be able to deploy a new GNSS buoy array system in the wide ocean. An array in the ocean can be used for ionospheric and atmospheric research in the same region as well as tsunami or ocean bottom crustal deformation monitoring through an application to the GNSS-acoustic system. We are now designing a regional GNSS buoy array in the western Pacific as a synthetic natural hazard mitigation system.

  4. Oceansat–2 and RAMA buoy winds: A comparison

    Indian Academy of Sciences (India)

    S Indira Rani; M Das Gupta

    2013-12-01

    Sea surface vector winds from scatterometers onboard satellites play an important role to make accurate Numerical Weather Prediction (NWP) model analysis over the data sparse oceanic region. Sea surface winds from Oceansat-2 scatterometer (OSCAT) over the Indian Ocean were validated against the Research Moored Array for African–Asian–Australian Monsoon Analysis and Prediction (RAMA) buoy winds to establish the accuracy of OSCAT winds. The comparison of OSCAT winds against RAMA buoy winds for a period of one year (2011) shows that the wind speeds and directions derived from OSCAT agree with RAMA buoy winds. The monthly mean wind speeds from both OSCAT and RAMA buoy show maximum value during the monsoon period as expected. In the complete annual cycle (2011), the monthly mean root mean square differences in the wind speed and wind direction were less than ∼2.5 ms−1 and ∼20°, respectively. The better match between the OSCAT and RAMA buoy wind is observed during Indian summer monsoon (June–September). During monsoon 2011, the root mean square differences in wind speed and wind direction were less than 1.9 ms−1 and 11°, respectively. Collocation of scatterometer winds against equatorial and off-equatorial buoys clearly brought out the monsoon circulation features. Collocation of Advanced Scatterometer (ASCAT) winds on-board European Space Agency (ESA) MeTop satellite with respect to RAMA buoy winds during monsoon 2011 also showed that the OSCAT wind statistics are comparable with that of ASCAT over the Indian Ocean, and indicates that the accuracy of both the scatterometers over the Indian Ocean are essentially the same.

  5. Model Predictive Control of Buoy Type Wave Energy Converter

    DEFF Research Database (Denmark)

    Soltani, Mohsen N.; Sichani, Mahdi T.; Mirzaei, Mahmood

    2014-01-01

    The paper introduces the Wavestar wave energy converter and presents the implementation of model predictive controller that maximizes the power generation. The ocean wave power is extracted using a hydraulic electric generator which is connected to an oscillating buoy. The power generator...... is an additive device attached to the buoy which may include damping, stiffness or similar terms hence will affect the dynamic motion of the buoy. Therefore such a device can be seen as a closed-loop controller. The objective of the wave energy converter is to harvest as much energy from sea as possible....... This approach is then taken into account and an MPC controller is designed for a model wave energy converter and implemented on a numerical example. Further, the power outtake of this controller is compared to the optimal controller as an indicator of the performance of the designed controller....

  6. Investigation on the Oscillating Buoy Wave Power Device

    Institute of Scientific and Technical Information of China (English)

    苏永玲; 游亚戈; 郑永红

    2002-01-01

    An oscillating buoy wave power device (OD) is a device extracting wave power by an oscillating buoy. Being excitedby waves, the buoy heaves up and down to convert wave energy into electricity by means of a mechanical or hydraulic de-vice. Compared with an Oscillating Water Column (OWC) wave power device, the OD has the same capture width ratio as the OWC does, but much higher secondary conversion efficiency. Moreover, the chamber of the OWC, which is the mostexpensive and difficult part to be built, is not necessary for the OD, so it is easier to construct an OD. In this paper, a nu-merical calculation is conducted for an optimal design of the OD firstly, then a model of the device is built and, a model testis carded out in a wave tank. The results show that the total efficiency of the OD is much higher than that of the OWC andthat the OD is a promising wave power device.

  7. Buoy Relay Method for Instantaneous Fluid Flow with Free Surface

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Several methods have been used to approximate free surface boundaries in finite-difference numerical simulations. Each of these methods has its advantages and disadvantages. This paper presents a new technique for the numerical solution of transient incompressible free surface fluid flows. This powerful method, which is based on the concepts of "Buoy positioning" and "Buoy relaying", successfully represents the free surface using a Lagrangian method on a Eulerian grid by directly solving the free surface evolution equation. The Eulerian finite-difference forms of the full Navier-Stokes equations are solved by the Successive over Relaxation (SOR) method with a set of buoys to keep track of the free surface. The capabilities of the analysis procedure are demonstrated through viscous free surface fluid flow examples. The method is simpler and more efficient than other methods especially in treating complicated free boundary configurations.

  8. 46 CFR 169.741 - Personal flotation devices and ring life buoys.

    Science.gov (United States)

    2010-10-01

    ... SCHOOL VESSELS Vessel Control, Miscellaneous Systems, and Equipment Markings § 169.741 Personal flotation devices and ring life buoys. Each personal flotation device and ring life buoy must be marked with the... 46 Shipping 7 2010-10-01 2010-10-01 false Personal flotation devices and ring life buoys....

  9. Multi buoy system observation for GPS/A seafloor positioning

    Science.gov (United States)

    Mukaiyama, H.; Ikuta, R.; Tadokoro, K.; Yasuda, K.; Watanabe, T.; Chiba, H.; Sayanagi, K.

    2014-12-01

    We are developing a method for observation of seafloor crustal deformation using kinematic GPS and acoustic ranging system. The system measures seafloor crustal deformation by determining position of benchmarks on the seafloor using a vessel which link-up GPS and acoustic signals. Acoustic ranging is used to measure distance between the vessel and the seafloor benchmarks. And kinematic GPS is used to locate the moving vessel every 0.2 seconds. Now we have deployed 4 seafloor benchmark units at Suruga Bay and 4 units at Kumano Basin both off-pacific coast Japan. At each survey site, three seafloor transponders are settled to define a benchmark unit. In this system, each measurement takes about ten hours and both sound speed structure and the benchmark unit positions were determined simultaneously for the each measurement using a tomographic technique. This tomographic technique was adopted based on assumption that the sound speed structure is horizontally layered and changes only in time, not in space. However, when sound speed structure has a heterogeneity, the assumption of a horizontal layering causes systematic error in the determination of seafloor benchmarks(Ikuta et al 2009AGU). So we are developing a new system using multi-buoy. Multi-buoy plays the role of vessel. Conducting observation using the buoys, we can estimate spatial variation of sound speed structures as a sloped structure every moment. With the single vessel system, we solve a kind of average sound speed over the different paths to the three seafloor transponders. Using the multi-buoy system, they can detect the lateral variation as difference of the average sound speeds obtained by different buoys, which improve the accuracy of the benchmark locations. In November 2013, Observation of seafloor crustal deformation using the buoys was held in Suruga Bay. In this study, we report the result of estimations of heterogeneous sound speed structures.

  10. A Buoy for Continuous Monitoring of Suspended Sediment Dynamics

    Directory of Open Access Journals (Sweden)

    Andreas Güntner

    2013-10-01

    Full Text Available Knowledge of Suspended Sediments Dynamics (SSD across spatial scales is relevant for several fields of hydrology, such as eco-hydrological processes, the operation of hydrotechnical facilities and research on varved lake sediments as geoarchives. Understanding the connectivity of sediment flux between source areas in a catchment and sink areas in lakes or reservoirs is of primary importance to these fields. Lacustrine sediments may serve as a valuable expansion of instrumental hydrological records for flood frequencies and magnitudes, but depositional processes and detrital layer formation in lakes are not yet fully understood. This study presents a novel buoy system designed to continuously measure suspended sediment concentration and relevant boundary conditions at a high spatial and temporal resolution in surface water bodies. The buoy sensors continuously record turbidity as an indirect measure of suspended sediment concentrations, water temperature and electrical conductivity at up to nine different water depths. Acoustic Doppler current meters and profilers measure current velocities along a vertical profile from the water surface to the lake bottom. Meteorological sensors capture the atmospheric boundary conditions as main drivers of lake dynamics. It is the high spatial resolution of multi-point turbidity measurements, the dual-sensor velocity measurements and the temporally synchronous recording of all sensors along the water column that sets the system apart from existing buoy systems. Buoy data collected during a 4-month field campaign in Lake Mondsee demonstrate the potential and effectiveness of the system in monitoring suspended sediment dynamics. Observations were related to stratification and mixing processes in the lake and increased turbidity close to a catchment outlet during flood events. The rugged buoy design assures continuous operation in terms of stability, energy management and sensor logging throughout the study period

  11. Field Evaluation of Ocean Wave Measurement With GPS Buoys

    Science.gov (United States)

    2010-09-01

    surface waves. In the experiment, conducted off the coast of California near Bodega Bay, clusters off Datawell and prototype GPS buoys were...receivers to measure ocean surface waves. In the experiment, conducted off the coast of California near Bodega Bay, clusters off Datawell and...the coast near Bodega Bay, CA. .............................................................................................17 Figure 4. R/P FLIP

  12. Precise-Orientation-Beamforming Scheme for Wireless Communications between Buoys

    Directory of Open Access Journals (Sweden)

    Zhihui Wu

    2016-01-01

    Full Text Available Utilizing wireless sensor network (WSN to monitor the marine environment is one of the major techniques in oceanographic monitoring, and how to increase the limited communication distance between the buoys in WSN has become a hot research issue. In this paper, a new technique called precise-orientation-beamforming (POB which uses the beamforming algorithm to increase the communication distance between buoys is presented. As was widely applied in the radar and sonar, the beamforming method was not used to extend the communication distance between buoys so far. The POB method overcomes the unstable position of buoys caused by waves by implementing the orientation filter. The whole process includes two steps: First, the real-time attitude of the antenna array is calculated by the orientation filter. With the known relative direction of the destination node to the antenna array, the second step is to control phased array antenna beamforming parameters, directing the beam at the destination node. The POB scheme has been simulated under the condition of regular waves. The results reveal that POB provides significant power gains and improves the distance between two communicating nodes effectively.

  13. UpTempO Buoys for Understanding and Prediction

    Science.gov (United States)

    2015-09-30

    paper was finally submitted to JGR in July (Steele and Ermold, 2015). We are very happy to report that it was recently accepted with minor revisions...buoy project is part of the over-all SIZRS project, where a group of scientists are working together to better understand the air-sea-ice coupling of

  14. Determination of wave direction using an orbital following buoy

    Digital Repository Service at National Institute of Oceanography (India)

    Fernandes, A.A.; Almeida, A.M.; Vaithiyanathan, R.; Vethamony, P.

    as computed simulated data. This is a preliminary report on program development. In the case of observed data, wave directions obtained with BUOY-D-P agreed within within plus or minus 5 degrees with the single available visual estimate of swell direction...

  15. Data circulation and services of the RON data buoy network

    Science.gov (United States)

    Picone, Marco; Morucci, Sara; Nardone, Gabriele

    2014-05-01

    This paper reviews the services of the Italian data buoy network (RON, Rete Ondametrica Nazionale). The RON run 15 directional moored buoys, real-time transmitting, uniformly distributed along the Italian coasts. Data have been collected since 1989 at 8 measurement stations; in 1999 two other stations were added and the remaining five buoys were moored in 2001. From 2010 all stations are equipped with meteorological instruments. Buoys collect the main physical parameters useful in defining the sea state such as significant and maximum wave height, peak and mean period, wave direction, sea surface temperature, air temperature, wind speed and direction, atmospheric pressure, relative humidity. The RON provides real-time of wave and meteorological parameters every 30 minutes. Buoys transmit data to shore stations within 15 NM and a small dataset via Inmarsat-D+. All shore stations are connected to the control centre based in Rome, using 2 Mbps xDSL channels, implementing a virtual private network. Very deeply procedures have been implemented in order to validate date: L1 and L2 algorithms have been applied in order to make data compliant with international standards. Data are monthly analysed and published in the Wave National Bulletin. Further investigations have been implemented, including statistical analysis, in order to define wave climate, extreme events, sea storms, storm surges, and related meteorological information. This kind of data is very useful for all tasks and scientific activities of national interest for the protection, enhancement and improvement for the marine environment. The technical and scientific support contributes to the better environmental governance, providing a wide range of information in several key areas such as: collection, processing, management and diffusion of marine data; protection of water resources and of marine and coastal areas; monitoring of marine environmental quality; prevention and mitigation of impacts of polluted

  16. Texas Automated Buoy System 1995-2005 and Beyond

    Science.gov (United States)

    Guinasso, N. L.; Bender, L. C.; Walpert, J. N.; Lee, L. L.; Campbell, L.; Hetland, R. D.; Howard, M. K.; Martin, R. D.

    2005-05-01

    TABS was established in l995 to provide data to assess oil spill movement along Texas coast for the Texas General Land Office Oil Spill Prevention and Response Program. A system of nine automated buoys provide wind and current data in near real time. Two of these buoys are supported by the Flower Garden Banks Joint Industry Program. A TABS web site provides a public interface to view and download the data. A real time data analysis web page presents a wide variety of useful data products derived from the field measurements. Integration efforts now underway include transfer of buoy data to the National Data Buoy Center for quality control and incorporation into the Global Telecommunications Stream. The TGLO ocean circulation nowcast/forecast modeling system has been in continuous operation since 1998. Two models, POM and ROMS, are used to produce forecasts of near-surface wind driven currents up to 48 hours into the future. Both models are driven using wind fields obtained from the NAM (formerly Eta) forecast models operated by NOAA NCEP. Wind and current fields are displayed on websites in both static and animated forms and are updated four times per day. Under funding from the SURA/SCOOP program we are; 1) revamping the system to conform with the evolving Data Management and Communications (DMAC) framework adopted by the NSF Orion and OCEAN.US IOOS programs, 2) producing model-data comparisons, and 3) integrating the wind and current fields into the GNOME oil trajectory model used by NOAA/Hazmat. Academic research is planned to assimilate near real-time observations from TABS buoys and some 30-40 ADCP instruments scheduled to be mounted on offshore oil platforms in early 2005. Texas Automated Buoy System (TABS) and its associated modeling efforts provide a reliable source of accurate, up-to-date information on currents along the Texas coast. As the nation embarks on the development of an Integrated Ocean Observing System (IOOS), TABS will be an active participant

  17. The wave buoy analogy - estimating high-frequency wave excitations

    DEFF Research Database (Denmark)

    Nielsen, Ulrik Dam

    2008-01-01

    The paper deals with the wave buoy analogy where a ship is considered as a wave buoy, so that measured ship responses are used as a basis to estimate wave spectra and associated sea state parameters. The study presented follows up on a previous paper, Nielsen [Nielsen UD. Response-based estimation...... of sea state parameters — influence of filtering. Ocean Engineering 2007;34:1797–810.], where time series of ship responses were generated from a known wave spectrum for the purpose of the inverse process — the estimation of the underlying wave excitations. Similar response generations and vice versa...... be estimated reasonably well, even considering high-frequency wave components of a wind sea wave spectrum....

  18. A Floating Ocean Energy Conversion Device and Numerical Study on Buoy Shape and Performance

    Directory of Open Access Journals (Sweden)

    Ruiyin Song

    2016-05-01

    Full Text Available Wave and current energy can be harnessed in the East China Sea and South China Sea; however, both areas are subject to high frequencies of typhoon events. To improve the safety of the ocean energy conversion device, a Floating Ocean Energy Conversion Device (FOECD with a single mooring system is proposed, which can be towed to avoid severe ocean conditions or for regular maintenance. In this paper, the structure of the FOECD is introduced, and it includes a catamaran platform, an oscillating buoy part, a current turbine blade, hydraulic energy storage and an electrical generation part. The numerical study models the large catamaran platform as a single, large buoy, while the four floating buoys were modeled simply as small buoys. Theoretical models on wave energy power capture and efficiency were established. To improve the suitability of the buoy for use in the FOECD and its power harvesting capability, a numerical simulation of the four buoy geometries was undertaken. The shape profiles examined in this paper are cylindrical, turbinate (V-shaped and U-shaped cone with cylinder, and combined cylinder-hemisphere buoys. Simulation results reveal that the suitability of a turbinate buoy is the best of the four types. Further simulation models were carried out by adjusting the tip radius of the turbinate buoy. Three performance criteria including suitability, power harvesting capability and energy capture efficiency were analyzed. It reveals that the turbinate buoy has almost the same power harvesting capabilities and energy capture efficiency, while its suitability is far better than that of a cylindrical buoy.

  19. System for Monitoring, Determining, and Reporting Directional Spectra of Ocean Surface Waves in Near Realtime from a Moored Buoy

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A moored buoy floating at the ocean surface and anchored to the seafloor precisely measures acceleration, pitch, roll, and Earth's magnetic flux field of the buoy...

  20. National Data Buoy Center (NDBC) National Backbone Contributions to the Integrated Ocean Observation System (IOOS)

    Science.gov (United States)

    2006-09-01

    II . METHODS In a letter to the governing body of each regional association, NDBC requested that a prioritized list of buoys be provided for the...The Bodega Bay (46013), Santa Maria (46011), Cape Saint Martin (46028), and Point Arena buoys were suggested as sites for salinity and ADCP

  1. An Autonomous Ozone Instrument for Atmospheric Measurements from Ocean Buoys

    Science.gov (United States)

    Hintsa, E. J.; Rawlins, W. T.; Sholkovitz, E. R.; Hosom, D. S.; Allsup, G. P.; Purcell, M. J.; Scott, D. R.; Mulhall, P.

    2002-05-01

    Tropospheric ozone is an oxidant, a greenhouse gas, and a pollutant. Because of its adverse health effects, there are numerous monitoring stations on land but none over the oceans. We have built an ozone instrument for deployment anywhere at sea from ocean buoys, to study ozone chemistry over the oceans, intercontinental transport of pollution, diurnal and seasonal cycles of ozone, and to make baseline and long-term time series measurements of ozone in remote locations. The instrument uses direct (Beer's Law) absorption of UV radiation in a dual-path cell, with ambient and ozone-free air alternately switched between the two paths, to measure ozone. Ozone can be measured at a rate of 1 Hz, with a precision of about 1 ppb at sea level. The air inlet and outlet have valves which close automatically under high wind conditions or rain to protect the ozone sensor. The instrument has been packaged for deployment at sea, and tested on a 3-meter discus buoy with other instruments in coastal waters in fall 2001. It can operate autonomously or be controlled via line-of-sight modem or a satellite link. We will present the details of the instrument, and laboratory and buoy test data from its first deployment, including a comparison with a nearby ozone monitoring station on land. We will also present an evaluation of the instrument's performance and describe plans for improvements. In summer 2002, the ozone measurement system will be operated at the Martha's Vineyard Coastal Observatory; in the future we anticipate deploying on the Bermuda Testbed Mooring, followed by use on the open ocean to measure long-range transport of ozone.

  2. Drifting buoy data observed during 1992 and assembled by the Responsible National Oceanographic Data Center (RNODC) for Drifting Buoy Data (NODC Accession 9300091)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Physical and meteorological data were collected from drifting buoys from a World-Wide distribution from 01 January 1992 to 31 December 1992. Data were processed by...

  3. Oceanographic profile Temperature and Salinity measurements collected during the Arctic Buoy Program using drifting buoy in the Arctic from 1985-1994 (NCEI Accession 0001497)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Between 1985 and 1994, the Polar Science Center at the University of Washington deployed 24 ARGOS data buoys in ice floes on the Arctic Ocean, from which six...

  4. Drifting buoy data observed during 1985 through 1989 and assembled by the Responsible National Oceanographic Data Center (RNODC) for Drifting Buoy Data (NODC Accession 9100057)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Physical and meteorological data were collected from drifting buoys from a World-Wide distribution from 2 January 1985 to 31 December 1989. Data were processed by...

  5. Preliminary Design Options for Meteor Burst Communications Systems Buoy Relays

    Science.gov (United States)

    1986-12-01

    the lithium - thionyl chloride cell exhibit specific energies of the order of 500 watt hours per kilogram, more than 50 percent higher than previous...Supply Buoy Design Type 90 Day Storage Weight Type Energy Type Size (lb) Remote Lithium 2.2 kWh Deployable 8" x 8" x 4’ 200 Battery Pendulous Master...however, that there are various typcs of lithium batteries presently being developed that have energy densities equal to’fuel cell power systems. It is

  6. An overview of a moored ocean data buoy programme

    Digital Repository Service at National Institute of Oceanography (India)

    Nayak, M.R.

    observation time. From this data the processor calculates the average wind speed, wind gust and the wind vector. 5.2. Relath'c humidity: is spot sampled at observation time. 5.3. Air temperature: is spot sampled at observation time. 5.4. Barometric pressure 5... by the vertical movement of the buoy, and by the wind. 5.4.2. Additionally, the ·barometric pressure tendency since last observation time or over a 3-hour period can also be calculated by the processor, if required. 5.5. Sea surface temperature: is spot sampled...

  7. System Identification and Control of a Joint-Actuated Buoy

    Science.gov (United States)

    2014-05-09

    metal gear digital servos. These servos are compact in size, measuring 1.65 x 0.83 x 1.57 in., and waterproof. They are able to move 60 degrees in 0.20...seconds with 157 oz.-in of torque at six volts. This was important for the buoy application because the ability to quickly and efficiently change the...Six Models 22 Each model has an inherent DC Gain, or the ratio of the relationship between the magnitudes of the output compared to the input [6

  8. A drifting GPS buoy for retrieving effective riverbed bathymetry

    Science.gov (United States)

    Hostache, R.; Matgen, P.; Giustarini, L.; Teferle, F. N.; Tailliez, C.; Iffly, J.-F.; Corato, G.

    2015-01-01

    Spatially distributed riverbed bathymetry information are rarely available but mandatory for accurate hydrodynamic modeling. This study aims at evaluating the potential of the Global Navigation Satellite System (GNSS), like for instance Global Positioning System (GPS), for retrieving such data. Drifting buoys equipped with navigation systems such as GPS enable the quasi-continuous measurement of water surface elevation, from virtually any point in the world. The present study investigates the potential of assimilating GNSS-derived water surface elevation measurements into hydraulic models in order to retrieve effective riverbed bathymetry. First tests with a GPS dual-frequency receiver show that the root mean squared error (RMSE) on the elevation measurement equals 30 cm provided that a differential post processing is performed. Next, synthetic observations of a drifting buoy were generated assuming a 30 cm average error of Water Surface Elevation (WSE) measurements. By assimilating the synthetic observation into a 1D-Hydrodynamic model, we show that the riverbed bathymetry can be retrieved with an accuracy of 36 cm. Moreover, the WSEs simulated by the hydrodynamic model using the retrieved bathymetry are in good agreement with the synthetic "truth", exhibiting an RMSE of 27 cm.

  9. Evidence that grey seals (Halichoerus grypus use above-water vision to locate baited buoys

    Directory of Open Access Journals (Sweden)

    Arne Fjälling

    2007-01-01

    Full Text Available Fishing gear in the Baltic is often raided by grey seals (Halichoerus grypus. The seals remove the fish and damage the nets, or entangle themselves and drown. In order to develop ways of mitigating the seals-fisheries conflict, it is important to know exactly how the seals locate the fishing gear. A field experiment was conducted in order to clarify whether seals use their vision above water to do this. Bait (herring; Clupea harengus was attached to the anchor lines of buoys of the type that is commonly used to mark the position of fishing gear. In all, 643 buoys were set. Some of the buoys (210 were also fitted with camera traps. Weather data were collected from official weather stations nearby. Bait loss (mean 18% was significantly correlated with buoy size (P = 0.002 and wind speed (P = 0.04. There was a significant association between bait loss and seal observations near the buoys (P = 0.05. Five photos of grey seals were obtained from the camera traps. No fish-eating birds, such as cormorants or mergansers, were ever observed near the buoys or caught on camera. It was concluded that a main cause of missing bait was scavenging by grey seals, and that they did use above-water vision to locate the buoys. It was also concluded that wind strength (i.e. wave action contributed tothe bait loss. The camera trap buoys had a somewhat lower bait loss than the other buoys (P = 0.054, which was attributed to a scaring effect. Neither the number of seal observations nor the bait loss differed significantly between the 2 study areas in the experiment (P = 0.43 and P = 0.83, respectively. Bait loss was not affected by the buoy colour (red, white, or grey; P = 0.87. We suggest that the findings of this experiment could be put into practice in a seal-disturbed area by deploying a number of decoy buoys, or by hiding live buoys below the surface of the water. This would increase the cost of foraging for the seals, and hence discourage them from exploiting

  10. Levelized Cost of Energy for a Backward Bent Duct Buoy

    Energy Technology Data Exchange (ETDEWEB)

    Bull, Diana; Jenne, D. Scott; Smith, Christopher S.; Copping, Andrea E.; Copeland, Guild

    2016-12-01

    The Reference Model Project, supported by the U.S. Department of Energy, was developed to provide publically available technical and economic benchmarks for a variety of marine energy converters. The methodology to achieve these benchmarks is to develop public domain designs that incorporate power performance estimates, structural models, anchor and mooring designs, power conversion chain designs, and estimates of the operations and maintenance, installation, and environmental permitting required. The reference model designs are intended to be conservative, robust, and experimentally verified. The Backward Bent Duct Buoy (BBDB) presented in this paper is one of three wave energy conversion devices studied within the Reference Model Project. Comprehensive modeling of the BBDB in a Northern California climate has enabled a full levelized cost of energy (LCOE) analysis to be completed on this device.

  11. NODC Standard Product: NOAA Marine environmental buoy database Webdisc (7 disc set) (NODC Accession 0090141)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This CD-ROM set contains the historic archive of meteorological and oceanographic data collected by moored buoys and C-MAN stations operated by the NOAA National...

  12. Physical and optical data collected from drifting buoys between May 1993 - December 1996 (NODC Accession 0000586)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Upwelling and downwelling irradiances were collected from surface optical drifter buoys off the California coast (NE Pacific limit-180) from 05 May 1993 to 06...

  13. PacIOOS Water Quality Buoy 03 (WQB-03): Kiholo Bay, Big Island, Hawaii

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The water quality buoys are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed points....

  14. PacIOOS Water Quality Buoy 04 (WQB-04): Hilo, Big Island, Hawaii

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The water quality buoys are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed points....

  15. PacIOOS Water Quality Buoy AW (WQB-AW): Ala Wai, Oahu, Hawaii

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The water quality buoys are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed points....

  16. NODC Standard Format Drifting Buoy (F156) Data (1975-1994) (NODC Accession 0014200)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data type contains time series ocean circulation data determined by tracking the movement of drifting buoys, drogues or other instrumented devices. Movement is...

  17. PacIOOS Water Quality Buoy KN (WQB-KN): Kilo Nalu, Oahu, Hawaii

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The water quality buoys are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed points....

  18. Seasonal Ice Mass-Balance Buoys: Adapting Tools to the Changing Arctic

    Science.gov (United States)

    2011-01-01

    drilled through the ice completely and are connected by umbilical cords to a central housing. One structure positions acoustic sonar units above and below...ice mass-balance buoy (IMB). Polashenski and others: Seasonal ice mass-balance buoys 19 IMB, connected by umbilical cords, is one example. The design...seasonal landfast ice just north of Barrow, Alaska. The location chosen was 1 km offshore on a flat undeformed pan of first-year ice approximately 1.6

  19. Effect of High-Frequency Sea Waves on Wave Period Retrieval from Radar Altimeter and Buoy Data

    Directory of Open Access Journals (Sweden)

    Xifeng Wang

    2016-09-01

    Full Text Available Wave periods estimated from satellite altimetry data behave differently from those calculated from buoy data, especially in low-wind conditions. In this paper, the geometric mean wave period T a is calculated from buoy data, rather than the commonly used zero-crossing wave period T z . The geometric mean wave period uses the fourth moment of the wave frequency spectrum and is related to the mean-square slope of the sea surface measured using altimeters. The values of T a obtained from buoys and altimeters agree well (root mean square difference: 0.2 s only when the contribution of high-frequency sea waves is estimated by a wavenumber spectral model to complement the buoy data, because a buoy cannot obtain data from waves having wavelengths that are shorter than the characteristic dimension of the buoy.

  20. Accuracy Assessment of GPS Buoy Sea Level Measurements for Coastal Applications

    Science.gov (United States)

    Chiu, S.; Cheng, K.

    2008-12-01

    The GPS buoy in this study contains a geodetic antenna and a compact floater with the GPS receiver and power supply tethered to a boat. The coastal applications using GPS include monitoring of sea level and its change, calibration of satellite altimeters, hydrological or geophysical parameters modeling, seafloor geodesy, and others. Among these applications, in order to understand the overall data or model quality, it is required to gain the knowledge of position accuracy of GPS buoys or GPS-equipped vessels. Despite different new GPS data processing techniques, e.g., Precise Point Positioning (PPP) and virtual reference station (VRS), that require a prioir information obtained from the a regional GPS network. While the required a prioir information can be implemented on land, it may not be available on the sea. Hence, in this study, the GPS buoy was positioned with respect to a onshore GPS reference station using the traditional double- difference technique. Since the atmosphere starts to decorrelate as the baseline, the distance between the buoy and the reference station, increases, the positioning accuracy consequently decreases. Therefore, this study aims to assess the buoy position accuracy as the baseline increases and in order to quantify the upper limit of sea level measured by the GPS buoy. A GPS buoy campaign was conducted by National Chung Cheng University in An Ping, Taiwan with a 8- hour GPS buoy data collection. In addition, a GPS network contains 4 Continuous GPS (CGPS) stations in Taiwan was established with the goal to enable baselines in different range for buoy data processing. A vector relation from the network was utilized in order to find the correct ambiguities, which were applied to the long-baseline solution to eliminate the position error caused by incorrect ambiguities. After this procedure, a 3.6-cm discrepancy was found in the mean sea level solution between the long (~80 km) and the short (~1.5 km) baselines. The discrepancy between a

  1. Gulf of Mexico Monitoring Via The Remotely Controlled CMR SailBuoy

    Science.gov (United States)

    Wienders, N.; Hole, L. R.; Peddie, D.

    2013-12-01

    The CMR SailBuoy is an unmanned ocean vessel capable of traveling the oceans for extended periods of time. It navigates the oceans autonomously - transmitting data at regular intervals using the Iridium network for two way communication. The SailBuoy can be used for a wide variety of ocean applications from measuring ocean and atmospheric parameters to tracking oil spills or acting as a communication relay station for subsea instrumentation. As part of the Deep-C project(Deep Sea to Coast Connectivity in the Eastern Gulf of Mexico), a two month campaign was carried out from March to May 2013 with the purpose of collecting sea surface data (temperature, salinity and oxygen) during the spring bloom. The campaign was unique in that the SailBouy was remotely controlled from Norway after being deployed from the RV Apalachee. The SailBuoy was deployed approximately 11 nautical miles (nm) south of Cape San Blas. During its mission she sailed approximately 840nm on a cruise track across the Gulf coast, from the Florida Panhandle to Louisiana. The SailBuoy project is part of Deep-C's physical oceanography research which seeks to, among other things, understand how particles and dissolved substances (such as oil) travel from the deep sea to the Louisiana, Mississippi, Alabama and Florida shorelines. This involves cross-shelf transport and upwelling mechanisms, which the SailBuoy is capable of measuring. An other focus was the sampling of the Mississippi river plume, which has been shown to influence the distribution of particles, oil, dissolved substances in the water, at least at the surface level. Sea surface salinity measurement via satellite do not provide, at the moment, sufficient resolution and accuracy and instead, the SailBuoy seems to be a very convenient instrument to track river plumes. In this presentation we describe the collected data and include comparisons with high resolution ocean model outputs. We also present further plans for SailBuoy campaigns.

  2. Mooring System of Ocean Turbulence Observation Based on Submerged Buoy

    Institute of Scientific and Technical Information of China (English)

    SONG Da-lei; SUN Jing-jing; XUE Bing; JIANG Qian-li; WU Bing-wei

    2013-01-01

    A comparison experiment has been taken in the Kiaochow Bay between a newly designed mooring turbulence observation instrument (MTOI) and microstructure profiler MSS60 made by Sea & Sun.The whole observing system is based on a submerged buoy,in which the turbulence observation instrument is embedded,with a streamline-shape floating body,which is made of buoyancy material of glass microsphere.For the movement of seawater and the cable shaking strongly anytime influence the behaviors of the floating body,the accelerate sensors are used for the vibration measurement in the instrument together with the shear probe sensor.Both the vibration data and the shear data are acquired by the instrument at the same time.During data processing,the vibration signals can be removed and leave the shear data which we really need.In order to prove the reliability of the new turbulence instrument MTOI,a comparison experiment was designed.The measuring conditions are the same both in time and space.By this way,the two groups of data are comparable.In this paper,the conclusion gives a good similarity of 0.93 for the two groups of shear data in dissipation rate.The processing of the data acquired by MTOI is based on the cross-spectrum analysis,and the dissipation rate of it matches the Nasmyth spectrum well.

  3. Typhoon generated surface gravity waves measured by NOMAD-type buoys

    Science.gov (United States)

    Collins, Clarence O., III

    This study examines wind-generated ocean surface waves as measured by NOMAD-type buoys during the ONR-sponsored Impact of Typhoons on the Ocean in the Pacific (ITOP) field experiment in 2010. 1-D measurements from two new Extreme Air-Sea Interaction (EASI) NOMAD-type buoys were validated against measurements from established Air-Sea Interaction Spar (ASIS) buoys. Also, during ITOP, 3 drifting Miniature Wave Buoys, a wave measuring marine radar on the R/V Roger Revelle, and several overpasses of JASON-1 (C- and Ku-band) and -2 (Ku-band) satellite altimeters were within 100 km of either EASI buoy. These additional measurements were compared against both EASI buoys. Findings are in line with previous wave parameter inter-comparisons. A corroborated measurement of mean wave direction and direction at the peak of the spectrum from the EASI buoy is presented. Consequently, this study is the first published account of directional wave information which has been successfully gathered from a buoy with a 6 m NOMAD-type hull. This result may be applied to improve operational coverage of wave direction. In addition, details for giving a consistent estimate of sea surface elevation from buoys using strapped down accelerometers are given. This was found to be particularly important for accurate measurement of extreme waves. These technical studies established a high level of confidence in the ITOP wave measurements. Detailed frequency-direction spectra were analyzed. Structures in the wave field were described during the close passages of 4 major tropical cyclones (TC) including: severe tropical storm Dianmu, Typhoon Fanapi, Super Typhoon Megi, and Typhoon Chaba. In addition, significant swell was measured from a distant 5th TC, Typhoon Malakas. Changes in storm direction and intensity are found to have a profound impact on the wave field. Measurements of extreme waves were explored. More extreme waves were measured during TCs which coincided with times of increased wave

  4. The validation of HY-2 altimeter measurements of a significant wave height based on buoy data

    Institute of Scientific and Technical Information of China (English)

    WANG Jichao; ZHANG Jie; YANG Jungang

    2013-01-01

    HY-2 has been launched by China on August 16, 2011 which assembles multi-microwave remote sensing payloads in a body and has the ability of monitoring ocean dynamic environments. The HY-2 satellite data need to be calibrated and validated before being put into use. Based on the in-situ buoys from the Nation-al Data Buoy Center (NDBC), Ku-band significant wave heights (SWH, hs) of HY-2 altimeter are validated. Eleven months of HY-2 altimeter Level 2 products data are chose from October 1, 2011 to August 29, 2012. Using NDBC 60 buoys yield 902 collocations for HY-2 by adopting collocation criteria of 30 min for tempo-ral window and 50 km for a spatial window. An overall RMS difference of the SWH between HY-2 and buoy data is 0.297 m. A correlation coefficient between these is 0.964. An ordinary least squares (OLS) regression is performed with the buoy data as an independent variable and the altimeter data as a dependent vari-able. The regression equation of hs is hs(HY-2)=0.891×hs(NDBC)+0.022. In addition, 2016 collocations are matched with temporal window of 30 min at the crossing points of HY-2 and Jason-2 orbits. RMS difference of Ku-band SWH between the two data sets is 0.452 m.

  5. WindSat satellite comparisons with nearshore buoy wind data near the U.S. west and east coasts

    Institute of Scientific and Technical Information of China (English)

    ZHANG Lei; SHI Hanqing; YU Hong; YI Xin

    2016-01-01

    Nearshore wind speeds retrieved by WindSat are validated by a comparison with the moored buoy observations near the U.S. west and east coasts. A 30 min and 25 km collection window is used for the WindSat wind data and buoy measurements from January 2004 to December 2014. Comparisons show that the overall root-mean-square error is better than 1.44 m/s near the U.S. coasts, and the result for the east coast is better than that for the west coast. The retrieval accuracy of the descending portions is slightly better than that of the ascending portions. Most buoy-to-buoy variations are not significantly correlated with the coastal topography, the longitude and the distance from the shore or satellite-buoy separation distance. In addition, comparisons between a polarimetric microwave radiometer and a microwave scatterometer are accomplished with the nearshore buoy observations from 2007 to 2008. The WindSat-derived winds tend to be lower than the buoy observations near the U.S. coasts. In contrast, the QuikSCAT-derived winds tend to be higher than the buoy observations. Overall, the retrieval accuracy of WindSat is slightly better than that of QuikSCAT, and these satellite-derived winds are sufficiently accurate for scientific studies.

  6. Dynamic Validation of Envisat ASAR Derived Ocean Swell Against Directional Buoy Measurements in Pacific Ocean

    Science.gov (United States)

    Wang, He; Mouche, Alexis; Husson, Romain; Chapron, Bertrand

    2016-08-01

    Advanced Synthetic Aperture Radar (ASAR) in wave mode aboard Envisat satellite from ESA provides the unique 10-years swell spectra dataset on a continuous and global basis for scientific community. In this paper, a method of a dynamical validation approach for SAR swell spectra is developed, in which the in situ buoy spectra are reconstructed, partitioned, and retro- propagated to the vicinity of satellite observation along the great circle based upon the linear wave theory. More than 40,000 ASAR-buoy swell partitions are dynamically collocated for the full mission of Envisat, making this study the first to provide detailed quality assessment for ASAR derived ocean swell spectra. Comparison results show a general statistics of 0.40 m, 44.99 m and 16.89 ̊ for swell height, peak wavelength and direction RMSE, indicating a good agreement with buoy in-situ in Pacific Ocean.

  7. The International Arctic Buoy Programme (IABP) - An International Polar Year Every Year

    Science.gov (United States)

    Hanna, M.; Rigor, I.; Ortmeyer, M.; Haas, C.

    2004-12-01

    A network of automatic data buoys to monitor synoptic-scale fields of sea level pressure (SLP), surface air temperature (SAT), and ice motion throughout the Arctic Ocean was recommended by the U.S. National Academy of Sciences in 1974. Based on the Academy's recommendation, the Arctic Ocean Buoy Program was established by the Polar Science Center, Applied Physics Laboratory (APL), University of Washington, in 1978 to support the Global Weather Experiment. Operations began in early 1979, and the program continued through 1990 under funding from various agencies. In 1991, the International Arctic Buoy Programme (IABP) succeeded the Arctic Ocean Buoy Program, but the basic objective remains - to maintain a network of drifting buoys on the Arctic Ocean to provide meteorological and oceanographic data for real-time operational requirements and research purposes including support to the World Climate Research Programme and the World Weather Watch Programme. The IABP currently has 37 buoys deployed on the Arctic Ocean. Most of the buoys measure SLP and SAT, but many buoys are enhanced to measure other geophysical variables such as sea ice thickness, ocean temperature and salinity. This observational array is maintained by the 20 Participants from 10 different countries, who support the program through contributions of buoys, deployment logistics, and other services. The observations from the IABP are posted on the Global Telecommunications System for operational use, are archived at the World Data Center for Glaciology at the National Snow and Ice Data Center (http://nsidc.org), and can also be obtained from the IABP web server for research (http://iabp.apl.washington.edu). The observations from the IABP have been essential for: 1.) Monitoring Arctic and global climate change; 2.) Forecasting weather and sea ice conditions; 3.) Forcing, assimilation and validation of global weather and climate models; 4.) Validation of satellite data; etc. As of 2003, over 450 papers have

  8. On theory and simulation of heaving-buoy wave-energy converters with control

    Energy Technology Data Exchange (ETDEWEB)

    Eidsmoen, H.

    1995-12-01

    Heaving-buoy wave-energy converters with control were studied. The buoy is small compared to the wavelength. The resonance bandwidth is then narrow and the energy conversion in irregular waves can be significantly increased if the oscillatory motion of the device can be actively controlled, and the power output from the converter will vary less with time than the wave power transport. A system of two concentric cylinders of the same radius, oscillating in heave only, is analysed in the frequency-domain. The mathematical model can be used to study a tight-moored buoy, as well as a buoy reacting against a submerged body. The knowledge of the frequency-domain hydrodynamic parameters is used to develop frequency-domain and time-domain mathematical models of heaving-buoy wave energy converters. The main emphasis is on using control to maximize the energy production and to protect the machinery of the wave-energy converter in very large waves. Three different methods are used to study control. (1) In the frequency-domain explicit analytical expressions for the optimum oscillation are found, assuming a continuous sinusoidal control force, and from these expressions the optimum time-domain oscillation can be determined. (2) The second method uses optimal control theory, using a control variable as the instrument for the optimisation. Unlike the first method, this method can include non-linearities. But this method gives numerical time series for the state variables and the control variable rather than analytical expressions for the optimum oscillation. (3) The third method is time-domain simulation. Non-linear forces are included, but the method only gives the response of the system to a given incident wave. How the different methods can be used to develop real-time control is discussed. Simulations are performed for a tight-moored heaving-buoy converter with a high-pressure hydraulic system for energy production and motion control. 147 refs., 38 figs., 22 tabs.

  9. The S1 buoy station, Po River delta: data handling and presentation

    Directory of Open Access Journals (Sweden)

    Alessandro COLUCCELLI

    2006-12-01

    Full Text Available The technical setting of the mete-oceanographic buoy at site S1 south of the Po River delta is presented. The station was deployed by Istituto di Scienze Marine (ISMAR of CNR of Bologna, in cooperation with the local Regional Government and Environmental Agencies (ARPA of E. Romagna, and ADRICOSM. The buoy mooring and data flow architecture is discussed, with some emphasis on the WWW data presentation. The possible integration with other remote stations, data and mete-oceanographic operational activities is also proposed.

  10. 33 CFR 74.20-1 - Buoy and vessel use costs.

    Science.gov (United States)

    2010-07-01

    ... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false Buoy and vessel use costs. 74.20-1 Section 74.20-1 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY AIDS TO NAVIGATION CHARGES FOR COAST GUARD AIDS TO NAVIGATION WORK Aids to Navigation Costs § 74.20-1...

  11. Power Production Analysis of the OE Buoy WEC for the CORES Project

    DEFF Research Database (Denmark)

    Lavelle, John; Kofoed, Jens Peter

    This report describes the analysis performed on the OE Buoy for the CORES project by the wave energy group at Aalborg University, Denmark. OE Buoy is a type of Oscillating Water Column (OWC) wave energy converter as part of the CORES project. This type of device is one of the most developed to ex...... meant that it was not possible to fully implement the method, as the efficiency data was too sparsely distributed as a function of Tz and Hs, but the method used here is based on the Equimar protocol to give an approximate estimate of the yearly power production....... which a total of 39 hours of power production data was collected. A data acquisition system was used to sample the sensors on board and the generator shaft power time-series data was used in the analysis here. A wave-rider buoy, located at the site of OE Buoy and operated by the Marine Institute Ireland....... This may then be used to estimate the yearly power production of the device at the test site location or another location, by using the long-term wave statistics for the given site. Additionally, the power production for a given scale of device may be estimated by applying the appropriate scaling...

  12. Comparison of wind data from QuikSCAT and buoys in the Indian Ocean

    Digital Repository Service at National Institute of Oceanography (India)

    Satheesan, K.; Sarkar, A.; Parekh, A.; RameshKumar, M.R.; Kuroda, Y.

    The performance of QuikSCAT-derived wind vectors is evaluated using in-situ data from moored buoys over the Indian Ocean. The results show that the mean differences for wind speed and wind direction are 0.37 ms sup(-1) and 5.8 degrees, root mean...

  13. Establishment of Motion Model for Wave Capture Buoy and Research on Hydrodynamic Performance of Floating-Type Wave Energy Converter

    Directory of Open Access Journals (Sweden)

    Gao Hongtao

    2015-09-01

    Full Text Available Floating-type wave energy converter has the advantages of high wave energy conversion efficiency, strong shock resistance ability in rough sea and stable output power. So it is regarded as a promising energy utilization facility. The research on hydrodynamic performance of wave capture buoys is the precondition and key to the wave energy device design and optimization. A simplified motion model of the buoys in the waves is established. Based on linear wave theory, the equations of motion of buoys are derived according to Newton’s second law. The factors of wave and buoys structural parameters on wave energy absorption efficiency are discussed in the China’s Bohai Sea with short wave period and small wave height. The results show that the main factor which affects the dynamic responses of wave capture buoys is the proximity of the natural frequency of buoys to the wave period. And the incoming wave power takes a backseat role to it at constant wave height. The buoys structural parameters such as length, radius and immersed depth, influence the wave energy absorption efficiency, which play significant factors in device design. The effectiveness of this model is validated by the sea tests with small-sized wave energy devices. The establishment methods of motion model and analysis results are expected to be helpful for designing and manufacturing of floating-type wave energy converter.

  14. Method for transferring data between at least one lagrangian buoy for measuring currents for ocean and costal environments and a base station, and lagrangian buoy for measuring currents for ocean and costal environments

    OpenAIRE

    Martínez-Ledesma, Miquel; Álvarez, Alberto; Vizoso, Guillermo; Tintoré, Joaquín

    2011-01-01

    [EN] Method for transferring data between at least one lagrangian buoy for measuring currents for ocean and coastal environments and a base station, which comprises capturing data by the buoy by means of the parameter-measuring sensors and the GPS receiver and storing said data in a first file which is segmented into packets of a maximum length defined by the SBD Iridium protocol for the subsequent sending thereof to the base station. The invention also relates to the lagrangian buoy for meas...

  15. An improvement of the GPS buoy system for detecting tsunami at far offshore

    Science.gov (United States)

    Kato, T.; Terada, Y.; Nagai, T.; Kawaguchi, K.; Koshimura, S.; Matsushita, Y.

    2012-12-01

    We have developed a GPS buoy system for detecting a tsunami before its arrival at coasts and thereby mitigating tsunami disaster. The system was first deployed in 1997 for a short period in the Sagami bay, south of Tokyo, for basic experiments, and then deployed off Ofunato city, northeastern part of Japan, for the period 2001-2004. The system was then established at about 13km south of Cape Muroto, southwestern part of Japan, since 2004. Five tsunamis of about 10cm have been observed in these systems, including 2001 Peru earthquake (Mw8.3), 2003 Tokachi-oki earthquake (Mw8.3), 2004 Off Kii Peninsula earthquake (Mw7.4), 2010 Chile earthquake (Mw8.8), and 2011 Tohoku-Oki earthquake (Mw9.0). These experiments clearly showed that GPS buoy is capable of detecting tsunami with a few centimeter accuracy and can be monitored in near real time by applying an appropriate filter, real-time data transmission using radio and dissemination of obtained records of sea surface height changes through internet. Considering that the system is a powerful tool to monitor sea surface variations due to wind as well as tsunami, the Ministry of Land, Infrastructure, Transport and Tourism implemented the system in a part of the Nationwide Ocean Wave information network for Ports and HArbourS (NOWPHAS) system and deployed the system at 15 sites along the coasts around the Japanese Islands. The system detected the tsunami due to the 11th March 2011 Tohoku-Oki earthquake with higher than 6m of tsunami height at the site Off South Iwate (Kamaishi). The Japan Meteorological Agency that was monitoring the record updated the level of the tsunami warning to the greatest value due to the result. Currently, the GPS buoy system uses a RTK-GPS which requires a land base for obtaining precise location of the buoy by a baseline analysis. This algorithm limits the distance of the buoy to, at most, 20km from the coast as the accuracy of positioning gets much worse as the baseline distance becomes longer

  16. Dynamic analysis of propulsion mechanism directly driven by wave energy for marine mobile buoy

    Science.gov (United States)

    Yu, Zhenjiang; Zheng, Zhongqiang; Yang, Xiaoguang; Chang, Zongyu

    2016-07-01

    Marine mobile buoy(MMB) have many potential applications in the maritime industry and ocean science. Great progress has been made, however the technology in this area is far from maturity in theory and faced with many difficulties in application. A dynamic model of the propulsion mechanism is very necessary for optimizing the parameters of the MMB, especially with consideration of hydrodynamic force. The principle of wave-driven propulsion mechanism is briefly introduced. To set a theory foundation for study on the MMB, a dynamic model of the propulsion mechanism of the MMB is obtained. The responses of the motion of the platform and the hydrofoil are obtained by using a numerical integration method to solve the ordinary differential equations. A simplified form of the motion equations is reached by omitting terms with high order small values. The relationship among the heave motion of the buoy, stiffness of the elastic components, and the forward speed can be obtained by using these simplified equations. The dynamic analysis show the following: The angle of displacement of foil is fairly small with the biggest value around 0.3 rad; The speed of mobile buoy and the angle of hydrofoil increased gradually with the increase of heave motion of buoy; The relationship among heaven motion, stiffness and attack angle is that heave motion leads to the angle change of foil whereas the item of speed or push function is determined by vertical velocity and angle, therefore, the heave motion and stiffness can affect the motion of buoy significantly if the size of hydrofoil is kept constant. The proposed model is provided to optimize the parameters of the MMB and a foundation is laid for improving the performance of the MMB.

  17. Wave Observations from Central California: SeaSonde Systems and In Situ Wave Buoys

    Directory of Open Access Journals (Sweden)

    Regan M. Long

    2011-01-01

    Full Text Available Wave data from five 12-13 MHz SeaSondes radars along the central California coast were analyzed to evaluate the utility of operational wave parameters, including significant wave height, period, and direction. Data from four in situ wave buoys served to verify SeaSonde data and independently corroborate wave variability. Hourly averaged measurements spanned distance is 150 km alongshore × 45 km offshore. Individual SeaSondes showed statistically insignificant variation over 27 km in range. Wave height inter-comparisons between regional buoys exhibit strong correlations, approximately 0.93, and RMS differences less than 50 cm over the region. SeaSonde-derived wave data were compared to nearby buoys over timescales from 15 to 26 months, and revealed wave height correlations =0.85−0.91 and mean RMS difference of 53 cm. Results showed that height RMS differences are a percentage of significant wave height, rather than being constant independent of sea state. Period and directions compared favorably among radars, buoys, and the CDIP model. Results presented here suggest that SeaSondes are a reliable source of wave information. Supported by buoy data, they also reveal minimal spatial variation in significant wave height, period, and direction in coastal waters from ~45 km × ~150 km in this region of the central California coast. Small differences are explained by sheltering from coastal promontories, and cutoff boundaries in the case of the radars.

  18. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during July 2016 (NCEI Accession 0156326)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  19. Meteorological, oceanographic, and buoy data from JAMSTEC from five drifting buoys, named J-CAD (JAMSTEC Compact Arctic Drifter) in the Arctic Ocean from 2000 to 2003 (NODC Accession 0002201)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In 1999, JAMSTEC and MetOcean Data System Ltd. developed a new drifting buoy, named J-CAD (JAMSTEC Compact Arctic Drifter), to conduct long-term observations in the...

  20. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2005-11 (NODC Accession 0002469)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  1. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during January 2016 (NCEI Accession 0142963)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  2. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during August 2016 (NCEI Accession 0156603)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  3. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2005-07 (NODC Accession 0002372)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  4. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2005-05 (NODC Accession 0002226)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  5. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2005-04 (NODC Accession 0002176)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  6. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2005-06 (NODC Accession 0002309)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  7. Drifting buoy and other data as part of the Outer Continental Drifting buoy and other data as part of the Outer Continental Shelf Environmental Assessment Program (OCSEAP) from 04 June 1976 to 01 October 1976 (NODC Accession 7700020)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Drifting buoy and other data was collected by the University of Washington (UW) as part of the Outer Continental Shelf Environmental Assessment Program (OCSEAP)....

  8. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during September 2014 (NCEI Accession 0122592)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  9. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2005-10 (NODC Accession 0002436)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  10. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2005-08 (NODC Accession 0002380)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  11. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during April 2015 (NCEI Accession 0128073)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  12. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during May 2016 (NCEI Accession 0153542)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  13. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2011-12 (NODC Accession 0083918)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  14. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during February 2016 (NCEI Accession 0145373)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  15. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2013-05 (NODC Accession 0108385)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  16. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during December 2014 (NODC Accession 0125264)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  17. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2012-02 (NODC Accession 0086627)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  18. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2012-04 (NODC Accession 0090312)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  19. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2013-06 (NODC Accession 0110477)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  20. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2011-04 (NCEI Accession 0072886)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  1. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2011-05 (NCEI Accession 0073426)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  2. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2013-08 (NODC Accession 0112958)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  3. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2011-07 (NCEI Accession 0074922)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  4. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during December 2015 (NCEI Accession 0140790)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  5. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during October 2014 (NODC Accession 0122591)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  6. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during July 2015 (NCEI Accession 0130916)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  7. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during November 2015 (NCEI Accession 0139254)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  8. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2011-11 (NODC Accession 0082371)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  9. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2013-07 (NODC Accession 0111971)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  10. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2012-01 (NODC Accession 0085139)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  11. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2012-05 (NODC Accession 0090313)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  12. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during September 2015 (NCEI Accession 0136935)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  13. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2012-03 (NODC Accession 0088199)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  14. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2014-07 (NODC Accession 0121505)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  15. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2013-03 (NODC Accession 0104424)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  16. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2014-03 (NODC Accession 0117682)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  17. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during January 2015 (NODC Accession 0125752)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  18. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2013-09 (NODC Accession 0113792)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  19. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during November 2014 (NODC Accession 0122594)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  20. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2013-11 (NODC Accession 0115123)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  1. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2012-08 (NODC Accession 0095593)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  2. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2011-06 (NCEI Accession 0074384)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  3. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2013-04 (NODC Accession 0106521)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  4. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during March 2015 (NODC Accession 0127371)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  5. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during September 2014 (NODC Accession 0122593)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  6. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2011-10 (NODC Accession 0079513)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  7. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during February 2015 (NODC Accession 0126669)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  8. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2011-02 (NCEI Accession 0071368)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  9. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2011-09 (NODC Accession 0078579)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  10. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2012-07 (NODC Accession 0095565)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  11. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during October 2015 (NCEI Accession 0137949)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  12. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during April 2016 (NCEI Accession 0150816)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  13. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2012-12 (NODC Accession 0101426)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  14. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2013-01 (NODC Accession 0103632)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  15. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during June 2016 (NCEI Accession 0155886)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  16. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during May 2015 (NCEI Accession 0129415)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  17. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2012-11 (NODC Accession 0099948)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  18. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2014-08 (NODC Accession 0122005)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  19. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2013-02 (NODC Accession 0104259)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  20. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2011-03 (NCEI Accession 0072077)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  1. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2014-04 (NODC Accession 0118539)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  2. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2012-06 (NODC Accession 0092557)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  3. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2014-02 (NODC Accession 0117491)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  4. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2012-09 (NODC Accession 0098547)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  5. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during August 2015 (NCEI Accession 0131704)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  6. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2011-01 (NCEI Accession 0070959)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  7. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2011-08 (NCEI Accession 0077456)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  8. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2014-06 (NODC Accession 0120329)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  9. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during June 2015 (NCEI Accession 0129884)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  10. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2012-10 (NODC Accession 0099428)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  11. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2013-12 (NODC Accession 0115760)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  12. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during March 2016 (NCEI Accession 0146738)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  13. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2014-01 (NODC Accession 0116427)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  14. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2014-05 (NODC Accession 0119474)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  15. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2013-10 (NODC Accession 0114407)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Data Buoy Center (NDBC) established the Coastal-Marine Automated Network (C-MAN) for the National Weather Service in the early 1980's. NDBC has...

  16. Drifting and moored buoy data observed during 2015 and assembled by the Global Data Assembly Center for Drifting Buoy Data (formerly Responsible National Oceanographic Data Center (RNODC)), Canada (NCEI Accession 0156004)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Buoy data is available in real time to platform operators via telecommunications providers and distributed on the Global Telecommunications System (GTS) of the World...

  17. Data from a Directional Waverider Buoy off Kailua Bay, Windward Oahu, Hawaii during August 2000 - July 2004 (NODC Accession 0001660)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Through various funding channels, the Department of Oceanography at the University of Hawaii (UH) has maintained a Datawell Mark 2 Directional Waverider Buoy roughly...

  18. Directional wave and temperature data from nine buoys in Gray's Harbor, Washington, 1994-2002 (NODC Accession 0000756)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Wave data were collected from 9 buoys in Grays Harbor, Washington, from 01 January 1994 to 24 July 2002. Data were collected as part of the Coastal Data Information...

  19. Data from a Directional Waverider Buoy off Waimea Bay, North Shore, Oahu during December 2001 - July 2004 (NODC Accession 0001626)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Through various funding channels, the Department of Oceanography at the University of Hawaii (UH) has maintained a Datawell Directional Waverider Buoy roughly 5 km...

  20. WATER TEMPERATURE and Other Data from DRIFTING BUOY From World-Wide Distribution from 19781122 to 19810113 (NODC Accession 8600071)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — 359 Drifting Surface Buoys were deployed in the Southern Hemisphere oceans from November 22, 1978 to January 13, 1981 as part of the First Global Atmospheric...

  1. Directional wave and temperature data from seven buoys at Point Reyes, CA, 1996-2002 (NODC Accession 0000760)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Wave data were collected from 7 buoys in Point Reyes, California, from 06 December 1996 to 25 July 2002. Data were collected as part of the Coastal Data Information...

  2. Analysis for the Deployment of Single-Point Mooring Buoy System Based on Multi-Body Dynamics Method

    Institute of Scientific and Technical Information of China (English)

    CHANG Zong-yu; TANG Yuan-guang; LI Hua-jun; YANG Jian-ming; WANG Lei

    2012-01-01

    Deployment of buoy systems is one of the most important procedures for the operation of buoy system.In the present study,a single-point mooring buoy system which contains surface buoy,cable segments with components,anchor and so on is modeled by applying multi-body dynamics method.The motion equations are developed in discrete node description and fully Cartesian coordinates.Then numerical method is used to solve the ordinary differential equations and dynamics simulations are achieved while anchor is casting from board.The trajectories and velocities of different nodes without current and with current in buoy system are obtained.The transient tension force of each part of the cable is analyzed in the process of deployment.Numerical results indicate that the transient payload increases to a peak value when the anchor is touching the seabed and the maximum tension force will vary with different floating configuration.This work is helpful for design and deployment planning of buoy system.

  3. Buoy observations of the influence of swell on wind waves in the open ocean

    Energy Technology Data Exchange (ETDEWEB)

    Violante-Carvalho, N.; Robinson, I.S. [University of Southampton (United Kingdom). Oceanography Centre; Ocampo-Torres, F.J. [CICESE, Ensenada (Mexico). Dpto. de Oceanografia Fisica

    2004-04-01

    The influence of longer (swell) on shorter, wind sea waves is examined using an extensive database of directional buoy measurements obtained from a heave-pitch-roll buoy moored in deep water in the South Atlantic. This data set is unique for such an investigation due to the ubiquitous presence of a young swell component propagating closely in direction and frequency with the wind sea, as well as a longer, opposing swell. Our results show, within the statistical limits of the regressions obtained from our analysis when compared to measurements in swell free environments, that there is no obvious influence of swell on wind sea growth. For operational purposes in ocean engineering this means that power-laws from fetch limited situations describing the wind sea growth can be applied in more realistic situations in the open sea when swell is present. (author)

  4. Design and Feasibility Demonstration of a Deployment System for a Rocket Launched Buoy

    Science.gov (United States)

    1979-09-06

    as described in Section 3.3. 3.2 Deployment Piston After early experiments with the standard Sonobuoy deployment piston it was decided to utilize a...syzt-em- desee 4 s not limited to the electronic buoy for which it was developed but is applicable to any quasi cylindrical payload to be deployed following a rocket launch from the MK 36 launching system. -12-

  5. Wireless Sensor Buoys for Perimeter Security of Military Vessels and Seabases

    Science.gov (United States)

    2015-12-01

    would enable the nodes to be mounted at a specified height above the surface of the water , which would account for the ocean swell and increase the...which limits the tipping of the buoy in high wind and ocean current conditions. The prototype had the anchor point location at the water surface line...to water evaporation after the wet concrete was mixed and poured. A 50 modification to the prototype replaced the concrete with a 10lb plate

  6. GPS inland water buoys for precise and high temporal resolution water level and movement monitoring

    Science.gov (United States)

    Apel, Heiko; Nghia Hung, Nguyen; Thoss, Heiko; Güntner, Andreas

    2010-05-01

    Monitoring of river and lake stages is one of the basic issues in understanding catchment hydrology and hydraulic systems. There are numerous techniques available for this, but in case of large water bodies technical as well as financial problems may restrict the use of traditional techniques. Therefore we explored the potential of GPS based altimetry for stage monitoring by developing small and easy to handle buoys with mounted high precision GPS devices. The advantages of the buoys are the freedom of positioning over the whole water body and their quick and easy deployment. The developed devices were tested in the Mekong Delta, Vietnam in two different locations: On the Mekong river where high currents over the flood season occur and in a small lake with hydraulic connections to a major channel with hardly any currents present. The collected GPS data were processed differentially and tested against standard pressure gauge data. The recorded stages proved to be of high quality and a valuable resource for flood monitoring and modeling. In addition to the stage data, the high-precision GPS positioning data could also be used for monitoring the movement of the buoys, from which alternating currents caused by ocean tides and flood waves could be detected, thus providing an additional information on the hydraulic system. We conclude that the developed buoys add well to the existing hydrological monitoring pool and are a goof option for the monitoring in large water bodies where a) traditional methods are technically difficult to deploy or are too costly, and b) where additional information about flow direction is needed.

  7. Monitoring High-Frequency Ocean Signals Using Low-Cost Gnss/imu Buoys

    Science.gov (United States)

    Huang, Yu-Lun; Kuo, Chung-Yen; Shih, Chiao-Hui; Lin, Li-Ching; Chiang, Kai-wei; Cheng, Kai-Chien

    2016-06-01

    In oceans there are different ocean signals covering the multi-frequencies including tsunami, meteotsunami, storm surge, as sea level change, and currents. These signals have the direct and significant impact on the economy and life of human-beings. Therefore, measuring ocean signals accurately becomes more and more important and necessary. Nowadays, there are many techniques and methods commonly used for monitoring oceans, but each has its limitation. For example, tide gauges only measure sea level relative to benchmarks and are disturbed unevenly, and satellite altimeter measurements are not continuous and inaccurate near coastal oceans. In addition, high-frequency ocean signals such as tsunami and meteotsunami cannot be sufficiently detected by 6-minutes tide gauge measurements or 10-day sampled altimetry data. Moreover, traditional accelerometer buoy is heavy, expensive and the low-frequency noise caused by the instrument is unavoidable. In this study, a small, low-cost and self-assembly autonomous Inertial Measurement Unit (IMU) that independently collects continuous acceleration and angular velocity data is mounted on a GNSS buoy to provide the positions and tilts of the moving buoy. The main idea is to integrate the Differential GNSS (DGNSS) or Precise Point Positioning (PPP) solutions with IMU data, and then evaluate the performance by comparing with in situ tide gauges. The validation experiments conducted in the NCKU Tainan Hydraulics Laboratory showed that GNSS and IMU both can detect the simulated regular wave frequency and height, and the field experiments in the Anping Harbor, Tainan, Taiwan showed that the low-cost GNSS buoy has an excellent ability to observe significant wave heights in amplitude and frequency.

  8. Surface circulation derived from drifting buoys in mid- and low-latitude Pacific

    Institute of Scientific and Technical Information of China (English)

    SU Jingzhi; LI Mingkui; HOU Yijun; YIN Baoshu; FANG Guohong

    2006-01-01

    A dataset of drifting buoys from the Marine Environmental Data Service of Canada was analyzed to map surface circulation of the Pacific. More information of the surface circulation than that acquired before was reported in this paper, showing clear and strong western boundary currents, equatorial currents, and subtropical gyres in the North and South Pacific regions in velocity field, with a more systematic structure in the North Pacific.

  9. Using Buoy and Radar Data to Study Sudden Wind Gusts Over Coastal Regions

    Science.gov (United States)

    Priftis, Georgios; Chronis, Themis; Lang, Timothy J.

    2017-01-01

    Significant sudden wind gusts can pose a threat to aviation near the coastline, as well as small (sailing) boats and commercial ships approaching the ports. Such cases can result in wind speed changes of more than an order of magnitude within 5 minutes, which can then last up to 20 minutes or more. Although the constellation of scatterometers is a good means of studying maritime convection, those sudden gusts are not easily captured because of the low time resolution. The National Data Buoy Center (NDBC) provides continuous measurements of wind speed and direction along the US coastal regions every 6 minutes. Buoys are platforms placed at specific places on the seas, especially along coastlines, providing data for atmospheric and oceanic studies. Next Generation Radars (NEXRADs), after the recent upgrade of the network to dual-pol systems, offer enhanced capabilities to study atmospheric phenomena. NEXRADs provide continuous full-volume scans approximately every 5 minutes and therefore are close to the time resolution of the buoy measurements. Use of single- Doppler retrievals might also provide a means of further validation.

  10. Detiding DART buoy data for real-time extraction of source coefficients for operational tsunami forecasting

    CERN Document Server

    Percival, Donald B; Eble, Marie C; Gica, Edison; Huang, Paul Y; Mofjeld, Harold O; Spillane, Michael C; Titov, Vasily V; Tolkova, Elena I

    2014-01-01

    U.S. Tsunami Warning Centers use real-time bottom pressure (BP) data transmitted from a network of buoys deployed in the Pacific and Atlantic Oceans to tune source coefficients of tsunami forecast models. For accurate coefficients and therefore forecasts, tides at the buoys must be accounted for. In this study, five methods for coefficient estimation are compared, each of which accounts for tides differently. The first three subtract off a tidal prediction based on (1) a localized harmonic analysis involving 29 days of data immediately preceding the tsunami event, (2) 68 pre-existing harmonic constituents specific to each buoy, and (3) an empirical orthogonal function fit to the previous 25 hrs of data. Method (4) is a Kalman smoother that uses method (1) as its input. These four methods estimate source coefficients after detiding. Method (5) estimates the coefficients simultaneously with a two-component harmonic model that accounts for the tides. The five methods are evaluated using archived data from eleven...

  11. The ODAS Italia 1 buoy: More than forty years of activity in the Ligurian Sea

    Science.gov (United States)

    Canepa, Elisa; Pensieri, Sara; Bozzano, Roberto; Faimali, Marco; Traverso, Pierluigi; Cavaleri, Luigi

    2015-06-01

    The Ligurian Sea plays a relevant role in driving both the circulation of the Western Mediterranean Sea and the weather and climate of the area. In order to better understand the peculiarities of this basin, the Oceanographic Data Acquisition System (ODAS) Italia 1 buoy was developed and deployed in the early '70s. Throughout the years, the buoy has been fitted with updated measuring and data acquiring systems. Since 2003 the buoy has been part of the Mediterranean Moored Multi-sensor Array network of fixed open ocean observatories with the W1-M3A identifier and presently constitutes one of the Mediterranean sites of the European FixO3 network. Recently, a deep-ocean sub-surface mooring line was, and is, deployed close to it in relation to specific projects. This multidisciplinary observing system is able to perform both long-term operational and ad-hoc monitoring from the lower atmosphere to the deep ocean. It is used for analysis of air-sea interaction processes, study of the physical proprieties of the water column, bio-geo-chemical monitoring of the sea, meteorological and oceanographic model evaluation, calibration of remotely sensed measurements, and development of innovative marine monitoring technologies. After reporting some historical notes and the description of the observing system, this paper summarises and reviews the main oceanographic and atmospheric studies performed during the last 15 years using the data acquired on board.

  12. Current components, physical, ocean circulation, wind circulation, and other data from moored buoys, CTD casts, drifting buoys, and in situ wind recorders from AIRCRAFT and other platforms from the North Atlantic Ocean and other locations as part of the Seasonal Response of the Equatorial Atlantic Experiment/Francais Ocean Et Climat Dans L'Atlantique Equatorial (SEQUAL/FOCAL) project from 25 January 1980 to 18 December 1985 (NODC Accession 8700111)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Current components, physical, ocean circulation, wind circulation, and other data were collected from moored buoys, CTD casts, drifting buoys, and in situ wind...

  13. Characterization of sea-ice kinematic in the Arctic outflow region using buoy data

    Directory of Open Access Journals (Sweden)

    Ruibo Lei

    2016-01-01

    Full Text Available Data from four ice-tethered buoys deployed in 2010 were used to investigate sea-ice motion and deformation from the Central Arctic to Fram Strait. Seasonal and long-term changes in ice kinematics of the Arctic outflow region were further quantified using 42 ice-tethered buoys deployed between 1979 and 2011. Our results confirmed that the dynamic setting of the transpolar drift stream (TDS and Fram Strait shaped the motion of the sea ice. Ice drift was closely aligned with surface winds, except during quiescent conditions, or during short-term reversal of the wind direction opposing the TDS. Meridional ice velocity south of 85°N showed a distinct seasonal cycle, peaking between late autumn and early spring in agreement with the seasonality of surface winds. Inertia-induced ice motion was strengthened as ice concentration decreased in summer. As ice drifted southward into the Fram Strait, the meridional ice speed increased dramatically, while associated zonal ice convergence dominated the ice-field deformation. The Arctic atmospheric Dipole Anomaly (DA influenced ice drift by accelerating the meridional ice velocity. Ice trajectories exhibited less meandering during the positive phase of DA and vice versa. From 2005 onwards, the buoy data exhibit high Arctic sea-ice outflow rates, closely related to persistent positive DA anomaly. However, the long-term data from 1979 to 2011 do not show any statistically significant trend for sea-ice outflow, but exhibit high year-to-year variability, associated with the change in the polarity of DA.

  14. Novel two-stage piezoelectric-based ocean wave energy harvesters for moored or unmoored buoys

    Science.gov (United States)

    Murray, R.; Rastegar, J.

    2009-03-01

    Harvesting mechanical energy from ocean wave oscillations for conversion to electrical energy has long been pursued as an alternative or self-contained power source. The attraction to harvesting energy from ocean waves stems from the sheer power of the wave motion, which can easily exceed 50 kW per meter of wave front. The principal barrier to harvesting this power is the very low and varying frequency of ocean waves, which generally vary from 0.1Hz to 0.5Hz. In this paper the application of a novel class of two-stage electrical energy generators to buoyant structures is presented. The generators use the buoy's interaction with the ocean waves as a low-speed input to a primary system, which, in turn, successively excites an array of vibratory elements (secondary system) into resonance - like a musician strumming a guitar. The key advantage of the present system is that by having two decoupled systems, the low frequency and highly varying buoy motion is converted into constant and much higher frequency mechanical vibrations. Electrical energy may then be harvested from the vibrating elements of the secondary system with high efficiency using piezoelectric elements. The operating principles of the novel two-stage technique are presented, including analytical formulations describing the transfer of energy between the two systems. Also, prototypical design examples are offered, as well as an in-depth computer simulation of a prototypical heaving-based wave energy harvester which generates electrical energy from the up-and-down motion of a buoy riding on the ocean's surface.

  15. A concept study for extraterrestrial sea exploration of Titan via Deployable And Versatile Instrument Device (DAVID) Buoys

    Science.gov (United States)

    Smith, Mary Katelyn

    Saturn's moon, Titan, has been a scientific marvel since Cassini's flyby discovered methane-ethane lakes in the northern hemisphere. Several science missions to explore these lakes have been proposed, but none have been launched. Using these previous mission designs, as well as the success of the Huygens probe, this paper will discuss the development of a deployable multi-buoy system with the intent of studying the methane-ethane lakes. The buoys will study the chemical makeup of the lakes, determine meteorology of Titan atmosphere, and map the depth and floor of the targeted lakes. This thesis is a concept study on the multi-buoy system that reviews briefly the concept and design.

  16. Comparison of retrieving methods of ocean wave periods from satellite altimeter with buoy measurements

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    For validating the results of retrieved mean wave period, four empirical algorithms established previously are introduced. Based on the data of over five years derived from TOPEX satellite altimeter for the entire East China Sea, ocean wave periods were calculated and statistical comparison among them was performed. The retrieved mean wave period obtained with our new distribution parameters showed better agreement with the wave period TB measured by buoy than that calculated by other three algorithms. The difference between the mean values of and that of TB is 0.16 s and the RMSE (root mean square error) of is the lowest value (0.48).

  17. General Analysis of Directional Ocean Wave Data from Heave Pitch Roll Buoys

    Directory of Open Access Journals (Sweden)

    Stephen F. Barstow

    1984-01-01

    Full Text Available Directional ocean wave data is usually analysed using the so-called linear model of the sea surface, but experience has shown that the results may deviate substantially from the predictions of the theory, in particular in the high frequency range. A general theory is presented here which includes the linear model as a special case. Properties of commonly used parameters under the influence of currents and non-linearities are easily explained within the general theory. Some results from the NORWAVE heave/pitch/roll data buoy operated offshore Norway are also presented.

  18. Steps towards commercialization of new power buoy with pivoting arm LOPF

    DEFF Research Database (Denmark)

    2013-01-01

    direct measurements from the model device are: voltage output, the torque on the generator, the arm bending moment produced by the mooring line and the absolute angle of the pivoting float. These allowed to follow the conversion of power in the power train from mechanic to electric power......The fully instrumented Lever Operated Pivoting Float LOPF wave energy buoy model has gone through the first stage of testing in regular waves in scale 1:25 of the North Sea wave conditions, in the 3D deep wave basin at the Hydraulic and Coastal Engineering Laboratory of Aalborg University. Some...

  19. An Oceanographic Buoy for Multidisciplinary Education and Research in a Coastal Embayment Prone to Harmful Algal Blooms

    Science.gov (United States)

    Laine, E. P.; Roesler, C.; Teegarden, G.

    2005-12-01

    In the spring of 2006 a consortium of Bowdoin College, Bigelow Laboratory for Ocean Sciences, and Saint Joseph's College of Maine will begin the operation of an oceanographic buoy in Harpswell Sound, part of the Casco Bay region of coastal Maine. Funding for acquisition of the buoy has been provided by NSF's MRI program. The sensing buoy will measure physical climatic and oceanographic variables, as well as a suite of biogeochemical indicators (nutrients, chlorophyll, light absorption, etc.). The data collected will be publicly available in real time and will contribute to the overall Gulf of Maine Ocean Observing System (GoMOOS) monitoring program, a premier and ground-breaking effort in assessing the physical and biogeochemical characteristics of the Gulf of Maine. Harpswell Sound is known as an indicator region for harmful algal blooms (HABs) of toxic Alexandrium spp. microalgae, and is an ideal location to employ long-term, comprehensive, remote and real-time monitoring to characterize model systems that promote HABs, as well as system response to changing watershed use patterns and evolving cultural eutrophication. Data acquired with the buoy's sensors, both streaming in real-time and archived in larger sets, will be used in course work at Bowdoin College and Saint Joseph's College, and will be available for use by other post-secondary institutions. Immediate applications include use of data in course work to understand the influence of physical oceanographic processes on biological processes in three dimensions and through time from an Eulerian perspective. The influence of climatic events and the geological characteristics of the surrounding watershed will also be recorded and analyzed through earth science course work. Bowdoin College has a marine research station immediately adjacent on the shore of Harpswell Sound, facilitating complementary traditional monitoring opportunities, e.g. targeted and detailed sampling of interesting features indicated by the

  20. A User's Guide to the Tsunami Datasets at NOAA's National Data Buoy Center

    Science.gov (United States)

    Bouchard, R. H.; O'Neil, K.; Grissom, K.; Garcia, M.; Bernard, L. J.; Kern, K. J.

    2013-12-01

    The National Data Buoy Center (NDBC) has maintained and operated the National Oceanic and Atmospheric Administration's (NOAA) tsunameter network since 2003. The tsunameters employ the NOAA-developed Deep-ocean Assessment and Reporting of Tsunamis (DART) technology. The technology measures the pressure and temperature every 15 seconds on the ocean floor and transforms them into equivalent water-column height observations. A complex series of subsampled observations are transmitted acoustically in real-time to a moored buoy or marine autonomous vehicle (MAV) at the ocean surface. The surface platform uses its satellite communications to relay the observations to NDBC. NDBC places the observations onto the Global Telecommunication System (GTS) for relay to NOAA's Tsunami Warning Centers (TWC) in Hawai'i and Alaska and to the international community. It takes less than three minutes to speed the observations from the ocean floor to the TWCs. NDBC can retrieve limited amounts of the 15-s measurements from the instrumentation on the ocean floor using the technology's two-way communications. NDBC recovers the full resolution 15-s measurements about every 2 years and forwards the datasets and metadata to the National Geophysical Data Center for permanent archive. Meanwhile, NDBC retains the real-time observations on its website. The type of real-time observation depends on the operating mode of the tsunameter. NDBC provides the observations in a variety of traditional and innovative methods and formats that include descriptors of the operating mode. Datasets, organized by station, are available from the NDBC website as text files and from the NDBC THREDDS server in netCDF format. The website provides alerts and lists of events that allow users to focus on the information relevant for tsunami hazard analysis. In addition, NDBC developed a basic web service to query station information and observations to support the Short-term Inundation Forecasting for Tsunamis (SIFT

  1. Results from the DAMOCLES ice-buoy campaigns in the transpolar drift stream 2007–2009

    Directory of Open Access Journals (Sweden)

    M. Haller

    2013-07-01

    Full Text Available During the EU research project DAMOCLES 18 ice buoys were deployed in the region of the Arctic transpolar drift (TPD. Sixteen of them formed a square with 400 km side-length. The measurements lasted from 2007 to 2009. The properties of the TPD and the impact of synoptic weather systems on the ice drift are analysed. Compared to Nansen's drift with the vessel Fram the measured speed of the TPD is here almost twice as fast. Within the TPD, the speed increases by a factor of almost three from the North Pole to the Fram Strait region. The hourly buoy position fixes show that the speed is underestimated by 10–20% if positions were taken at only 1–3 days intervals as it is usually done for satellite drift estimates. The geostrophic wind factor Ui/Ug, i.e. the ratio of ice speed Ui and geostrophic wind speed Ug, in the TPD amounts to 0.012 on average, but with regional and seasonal differences. The constant Ui/Ug relation breaks down for Ug −1. The impact of synoptic weather systems is studied applying a composite method. Cyclones (anticyclones cause cyclonic (anticyclonic vorticity and divergence (convergence of the ice drift. The amplitudes are twice as large for cyclones as for anticyclones. The divergence caused by cyclones corresponds to a 0.1–0.5%/6 h open water area increase based on the composite averages, but reached almost 4% within one day during a strong August 2007 storm. This storm also caused a~long-lasting (over several weeks rise of Ui and Ui/Ug and changed the ice conditions in a way allowing ocean tidal motion to directly affect ice motion. The consequences of an increasing Arctic storm activity for the ice cover are discussed.

  2. Oceanographic profile temperature, salinity and pressure measurements collected using moored buoy in the Indian Ocean from 2001-2006 (NODC Accession 0002733)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature and salinity measurements in the Equatorial Indian from 2001 to 2006 from the TRITON (TRIANGLE TRANS-OCEAN BUOY NETWORK); JAPAN AGENCY FOR MARINE-EARTH...

  3. Temperature and salinity profile data collected by drifting buoy and XBT in the Worldwide Oceans from 18 October 1999 to 28 February 2000 (NODC Accession 0000115)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profile data were collected using moored buoy, profiling floats, and XBT casts in a world wide distribution from 18 October 1999 to 28 February 2000....

  4. Temperature, salinity, and other data from buoy casts in the Arctic Ocean, Barents Sea and Beaufort Sea from 1948 to 1993 (NODC Accession 9800040)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature, salinity, and other data were collected using buoy casts in the Arctic Ocean, Barents Sea and Beaufort Sea from 1948 to 1993. Data were collected by the...

  5. Temperature data from buoy casts in the North Atlantic Ocean from the COLUMBUS and HMAS SWAN from 01 August 1928 to 04 September 1932 (NODC Accession 0000242)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature data were collected using buoy casts from the COLUMBUS and HMAS SWAN from August 1, 1928 to September 4, 1932 in the North Atlantic Ocean. Data were...

  6. Temperature profile and wind speed data collected from buoy casts in the Gulf of Mexico from NOAA Ship RESEARCHER for 1977-07-26 (NCEI Accession 7800034)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profile and wind speed data were collected using buoy casts in the Gulf of Mexico from NOAA Ship RESEARCHER from 26 July 1977 to 26 July 1977. Data were...

  7. Current, temperature profile, and other data collected in TOGA Area - Pacific Ocean from drifting buoy from 01 March 1994 to 31 March 1994 (NODC Accession 9400055)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Current, temperature profile, and other data were collected using drifting buoy in the TOGA Area - Pacific Ocean. Data were collected from 01 March 1994 to 31 March...

  8. Drifting buoy and other data as part of the Outer Continental Shelf Environmental Assessment Program (OCSEAP) from 17 May 1976 to 23 December 1976 (NODC Accession 7800105)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Drifting buoy data was collected by the Atlantic Oceanographic and Meteorological Laboratory (AOML) as part of the Outer Continental Shelf Environmental Assessment...

  9. Temperature and salinity profile data collected by drifting buoy and XBT in the Worldwide Oceans from 09 October 1997 to 31 March 2000 (NODC Accession 0000116)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profile data were collected using moored buoy, profiling floats, and XBT casts in a world wide distribution from 09 October 1997 to 31 March 2000. Data...

  10. Visualization of a drifting buoy deployment on Lake St. Clair within the Great Lakes Waterway from August 12-15, 2002

    Science.gov (United States)

    Holtschlag, David J.; Syed, Atiq U.; Kennedy, Gregory W.

    2002-01-01

    Lake St. Clair is a 430 square mile lake between the state of Michigan and the province of Ontario, which forms part of the international boundary between the United States and Canada in the Great Lakes Basin. Lake St. Clair receives most of its inflow from Lake Huron through St. Clair River, which has an average flow of 182,000 cubic feet per second. The lake discharges to Detroit River, where it flows 32 miles to Lake Erie. Twelve drifting buoys were deployed on Lake St. Clair for 74 hours between August 12-15, 2002 to help investigate flow circulation patterns as part of a source water assessment study of the susceptibility of public water intakes. The buoys contained global positioning system (GPS) receivers to track their movements. Buoys were released in a transect between tethered buoys marking an 800-foot wide navigational channel in the north-central part of the lake just downstream of St. Clair River, and about 15.5 miles northeast of Detroit River. In addition, an acoustic Doppler current profiler (ADCP) was used to measure velocity profiles in a grid of 41 points that spanned the area through which the buoys drifted. Computer animations, which can be viewed through the Internet, were developed to help visualize the results of the buoy deployments and ADCP measurements.

  11. Feasibility study of a semi floating spar buoy wind turbine anchored with a spherical joint to the sea floor

    DEFF Research Database (Denmark)

    Sanz Martinez, Maria; Natarajan, Anand; Henriksen, Lars Christian

    2013-01-01

    The feasibility of a semi floating platform offshore wind turbine system is investigated at 120m water depth. The semi floating system consists of a 5MW wind turbine on a floater with mooring lines similar to a spar buoy and strongly anchored with a spherical joint to the sea soil. The stability...... of the newly designed floater and mooring assembly are analyzed from static and dynamic simulations of the wind turbine. The design loads on the universal joint on the sea floor are tuned with the needs for a ballast chamber. Using load simulations in the HAWC2 software, ultimate and equivalent fatigue loads...... are obtained and compared with the corresponding loads from the same wind turbine mounted on a spar buoy and as a land based wind turbine. The results show a reduction in the ultimate and equivalent fatigue loads for the new system....

  12. Optimization and Annual Average Power Predictions of a Backward Bent Duct Buoy Oscillating Water Column Device Using the Wells Turbine

    OpenAIRE

    Smith, Christopher; Willits, Steven; Bull, Diana; Fontaine, Arnold

    2014-01-01

    This paper presents work completed by The Applied Research Laboratory at The Pennsylvania State University, in conjunction with Sandia National Labs, on the optimization of the power conversion chain (PCC) design to maximize the Average Annual Electric Power (AAEP) output of an Oscillating Water Column (OWC) device. The design consists of two independent stages. First, the design of a floating OWC, a Backward Bent Duct Buoy (BBDB), and second the design of the PCC. The pneumatic power output ...

  13. SeaMon-HC Buoy. A specific real-time-lightweight-moored platform as a tool for fast hydrocarbon detection

    Science.gov (United States)

    Barrera, C.; Rueda, M. J.; Moran, R.; Llerandi, C.; Llinas, O.

    2009-04-01

    The present paper-work describes the design, last development stages and the derived results from a specific buoy platform for fast hydrocarbon detection in seawater. Under the name of SeaMon-HC, (Patent No. P200302219/8) the buoy represents a very chief tool for coastal monitoring, mainly surrounding areas with a high oil-spill risk level, like harbours, off-shore fish farming, beaches and so on. Nowadays, the Macaronesian area has nine units working in real-time, under the frame of the Red ACOMAR Network. The main innovative aspect from this buoy is the detection system. It's based in polymer technology, working as a resistance, who increase its value when the pollutant on water surface is detected. The response time from the sensor is a direct function of the hydrocarbon volatility level. For hydrocarbons with high volatility levels (like petrol), the sensor needs less time (around 3 minutes) than others with less volatility such as oils. SeaMon-HC is an autonomous, modular, reusable and a very low-cost development integrated by four subsystems (SS): SS-Flotation (different materials and shapes available); SS-Sensors (hydrocarbon detector and additional sensors -up to 15-, to solve specific sensor configuration requirements); SS-Power Supply (equipped in its basic configuration with a couple of solar modules and two 12V batteries) and the SS-Communication (based on a RF or GSM/GPRS modem technology, with a selectable communication frequency). All SeaMon-HC units, as well the rest of the ODAS buoys who joint together the Red ACOMAR Network, works in real-time, sending the collected information to the control centre that manages the communications, providing data, in a useful form (as a web site), to diverse socio-economic important sectors which make an exhaustive use of the littoral in the Macaronesian region. The access to the information by the users is done through a specific GIS software application.

  14. Studies of Arctic Tropospheric Ozone Depletion Events Through Buoy-Borne Observations and Laboratory Studies

    Science.gov (United States)

    Halfacre, John W.

    The photochemically-induced destruction of ground-level Arctic ozone in the Arctic occurs at the onset of spring, in concert with polar sunrise. Solar radiation is believed to stimulate a series of reactions that cause the production and release of molecular halogens from frozen, salty surfaces, though this mechanism is not yet well understood. The subsequent photolysis of molecular halogens produces reactive halogen atoms that remove ozone from the atmosphere in these so-called "Ozone Depletion Events" (ODEs). Given that much of the Arctic region is sunlit, meteorologically stable, and covered by saline ice and snow, it is expected that ODEs could be a phenomenon that occurs across the entire Arctic region. Indeed, an ever-growing body of evidence from coastal sites indicates that Arctic air masses devoid of O3 most often pass over sea ice-covered regions before arriving at an observation site, suggesting ODE chemistry occurs upwind over the frozen Arctic Ocean. However, outside of coastal observations, there exist very few long-term observations from the Arctic Ocean from which quantitative assessments of basic ODE characteristics can be made. This work presents the interpretation of ODEs through unique chemical and meteorological observations from several ice-tethered buoys deployed around the Arctic Ocean. These observations include detection of ozone, bromine monoxide, and measurements of temperature, relative humidity, atmospheric pressure, wind speed, and wind direction. To assess whether the O-Buoys were observing locally based depletion chemistry or the transport of ozone-poor air masses, periods of ozone decay were interpreted based on current understanding of ozone depletion kinetics, which are believed to follow a pseudo-first order rate law. In addition, the spatial extents of ODEs were estimated using air mass trajectory modeling to assess whether they are a localized or synoptic phenomenon. Results indicate that current understanding of the

  15. Snow thickness retrieval using SMOS satellite data: Comparison with airborne IceBridge and buoy measurements

    Science.gov (United States)

    Maaß, N.; Kaleschke, L.; Tian-Kunze, X.

    2015-12-01

    buoy data. Although the results from these comparisons have to be interpreted cautiously, mainly due to the different spatial resolutions of SMOS (35-50 km footprint) and the smaller-scale airborne (and buoy) data, SMOS and IceBridge often agree as to where we find transitions from large-scale areas of very thin snow to areas predominantly covered by thicker snow.

  16. Wave parameters comparisons between High Frequency (HF) radar system and an in situ buoy: a case study

    Science.gov (United States)

    Fernandes, Maria; Alonso-Martirena, Andrés; Agostinho, Pedro; Sanchez, Jorge; Ferrer, Macu; Fernandes, Carlos

    2015-04-01

    The coastal zone is an important area for the development of maritime countries, either in terms of recreation, energy exploitation, weather forecasting or national security. Field measurements are in the basis of understanding how coastal and oceanic processes occur. Most processes occur over long timescales and over large spatial ranges, like the variation of mean sea level. These processes also involve a variety of factors such as waves, winds, tides, storm surges, currents, etc., that cause huge interference on such phenomena. Measurement of waves have been carried out using different techniques. The instruments used to measure wave parameters can be very different, i.e. buoys, ship base equipment like sonar and satellites. Each equipment has its own advantage and disadvantage depending on the study subject. The purpose of this study is to evaluate the behaviour of a different technology available and presently adopted in wave measurement. In the past few years the measurement of waves using High Frequency (HF) Radars has had several developments. Such a method is already established as a powerful tool for measuring the pattern of surface current, but its use in wave measurements, especially in the dual arrangement is recent. Measurement of the backscatter of HF radar wave provides the raw dataset which is analyzed to give directional data of surface elevation at each range cell. Buoys and radars have advantages, disadvantages and its accuracy is discussed in this presentation. A major advantage with HF radar systems is that they are unaffected by weather, clouds or changing ocean conditions. The HF radar system is a very useful tool for the measurement of waves over a wide area with real-time observation, but it still lacks a method to check its accuracy. The primary goal of this study was to show how the HF radar system responds to high energetic variations when compared to wave buoy data. The bulk wave parameters used (significant wave height, period and

  17. Applications to marine disaster prevention spilled oil and gas tracking buoy system

    CERN Document Server

    2017-01-01

    This book focuses on the recent results of the research project funded by a Grant-in-Aid for Scientific Research (S) of the Japan Society for the Promotion of Science (No. 23226017) from FY 2011 to FY 2015 on an autonomous spilled oil and gas tracking buoy system and its applications to marine disaster prevention systems from a scientific point of view. This book spotlights research on marine disaster prevention systems related to incidents involving oil tankers and offshore platforms, approaching these problems from new scientific and technological perspectives. The most essential aspect of this book is the development of a deep-sea underwater robot for real-time monitoring of blowout behavior of oil and gas from the seabed and of a new type of autonomous surface vehicle for real-time tracking and monitoring of oil spill spread and drift on the sea surface using an oil sensor. The mission of these robots is to provide the simulation models for gas and oil blowouts or spilled oil drifting on the sea surface w...

  18. Rancang Bangun Maximum Power Point Tracking pada Panel Photovoltaic Berbasis Logika Fuzzy di Buoy Weather Station

    Directory of Open Access Journals (Sweden)

    Bayu Prima Juliansyah Putra

    2013-09-01

    Full Text Available Salah satu aplikasi yang sering digunakan dalam bidang energi terbarukan adalah panel photovoltaic. Panel ini memiliki prinsip kerja berdasarkan efek photovoltaic dimana lempengan logam akan menghasilkan energi listrik apabila diberi intensitas cahaya. Untuk menghasilkan daya keluaran panel yang maksimal, maka diperlukan suatu algoritma yang biasa disebut Maximum Power Point Tracking (MPPT.MPPT yang diterapkan pada sistem photovoltaic berfungsi untuk mengatur nilai tegangan keluaran panel sehingga titik ker-janya beroperasi pada kondisi maksimal. Algoritma MPPT pada panel ini telah dilakukan dengan menggunakan logika fuzzy melalui mikrokontroler Arduino Uno sebagai pem-bangkit sinyal Pulse Width Modulation (PWM yang akan dikirimkan menuju DC-DC Buck Boost Converter. Keluaran dari buck boost converterakan dihubungkan secara langsung dengan buoy weather station untuk menyuplai energi listrik tiap komponen yang berada di dalamnya. Untuk menguji performansi dari algoritma MPPT yang telah dirancang, maka sistem akan diuji menggunakan variasi beban antara metode direct-coupled dengan MPPT menggunakan logika fuzzy. Hasil pengujian menunjukkan bahwa MPPT dengan logika fuzzy dapat menghasilkan daya maksimum daripada direct-coupled. Pada sistem panel photovoltaic ini memiliki range efisiensi 33.07589 % hingga 74.25743 %. Daya mak-simal dapat dicapai oleh sistem untuk tiap variasi beban dan efisiensi maksimal dapat dicapai pada beban 20 Ohm dari hasil pengujian sistem MPPT.

  19. Modelling surface drifting of buoys during a rapidly-moving weather front in the Gulf of Finland, Baltic Sea

    Science.gov (United States)

    Gästgifvars, Maria; Lauri, Hannu; Sarkanen, Annakaisa; Myrberg, Kai; Andrejev, Oleg; Ambjörn, Cecilia

    2006-12-01

    The Gulf of Finland is an elongated estuary located in the north-eastern extremity of the Baltic Sea. This semi-enclosed sea-area is subject to heavy sea traffic, and is one of the main risk areas for oil accidents in the Baltic. The continuous development and validation of operational particle drift and oil-spill forecasting systems is thus seen to be essential for this sea-area. Here, the results of a three-day drift experiment in May 2003 are discussed. The field studies were performed using GPS-positioned surface floating buoys. The aim of this paper is to evaluate how well models can reproduce the drift of these buoys. Model simulations, both in forecast and hindcast modes, were carried out by three different 3D hydrodynamic models, the results of which are evaluated by comparing the calculated drifts with observations. These models were forced by HIRLAM (High Resolution Limited Area Model) and ECMWF (European Centre for Medium-Range Weather Forecasts) meteorological forecast fields. The simulated drift of the buoys showed a good agreement with observations even when, during the study period, a rapidly-changing wind situation was observed to affect the investigation area; in this situation the winds turned about 100 degrees in half an hour. In such a case it is a very complicated task to forecast the drifters' routes: there is a need to regularly update the meteorological forcing fields and to use these regularly-updated fields throughout the simulations. It is furthermore recommended that forecasts should be made using several circulation models and several meteorological forecasts, in order to get an overview of the accuracy of the forecasted drifts and related differences in between the forecasts.

  20. Simulation and Design of Buoy Communication%浮标通信的仿真与设计

    Institute of Scientific and Technical Information of China (English)

    张建忠; 秦建存

    2012-01-01

    The electric wave transmitting reliability of large capacity buoy communication is usually not ideal due to buoyage shake and sea surface multipath.And neglecting the choice of operation frequency and antenna work form causes low reliability of large capacity sea-surface microwave mobile communication.To facilitate electric wave propagation for buoy communication,simulations and test for different working frequencies were performed to study the theoretical characteristics of synthesize field density of communication distance in sea surface multi-path fading conditions.And it is proposed that 1~2GHz wave band,omni-directional antenna with vertical polarization,and directional antenna in the sea coast are suitable for buoy communication.%大容量浮标通信由于浮标体摇摆和多径的影响,其电波传播的可靠度通常不理想,而忽略工作频率的选择和天线工作形式的研究是浮标通信这种海面微波移动通信传输设计可靠度不高的一个重要原因。针对采用何种工作频段和天线工作方式有利于浮标通信电波传输,通过对几组不同工作频率在海面多径条件下相关通信距离的归一化合成场强理论特性进行仿真和测试,提出了采用1~2 GHz波段和垂直极化的浮标端全向天线和岸端定向天线工作方式更有利于浮标通信。

  1. The first demonstration of a microbial fuel cell as a viable power supply: Powering a meteorological buoy

    Energy Technology Data Exchange (ETDEWEB)

    Tender, Leonard M.; Gray, Sam A. [Center for Bio/Molecular Science and Engineering, Naval Research Laboratory Code 6900, Washington, DC 20375 (United States); Groveman, Ethan [Millburn High School, Millburn, NJ 07041 (United States); Lowy, Daniel A. [Nova Research, Inc., Alexandria, VA 22308 (United States); Kauffman, Peter [Northwest Metasystems, Inc., Bainbridge Island, WA 98110 (United States); Melhado, Julio [Neptune Sciences, Slidell, LA 70461 (United States); Tyce, Robert C.; Flynn, Darren (Department of Ocean Engineering, University of Rhode Island, Narragansett, RI 02882 USA); Petrecca, Rose; Dobarro, Joe (Rutgers University, Institute of Marine and Coastal Sciences, Marine Field Station, Tuckerton, NJ 08087 USA)

    2008-05-01

    Here we describe the first demonstration of a microbial fuel cell (MFC) as a practical alternative to batteries for a low-power consuming application. The specific application reported is a meteorological buoy (ca. 18-mW average consumption) that measures air temperature, pressure, relative humidity, and water temperature, and that is configured for real-time line-of-sight RF telemetry of data. The specific type of MFC utilized in this demonstration is the benthic microbial fuel cell (BMFC). The BMFC operates on the bottom of marine environments, where it oxidizes organic matter residing in oxygen depleted sediment with oxygen in overlying water. It is maintenance free, does not deplete (i.e., will run indefinitely), and is sufficiently powerful to operate a wide range of low-power marine-deployed scientific instruments normally powered by batteries. Two prototype BMFCs used to power the buoy are described. The first was deployed in the Potomac River in Washington, DC, USA. It had a mass of 230 kg, a volume of 1.3 m{sup 3}, and sustained 24 mW (energy equivalent of ca. 16 alkaline D-cells per year at 25 C). Although not practical due to high cost and extensive in-water manipulation required to deploy, it established the precedence that a fully functional scientific instrument could derive all of its power from a BMFC. It also provided valuable lessons for developing a second, more practical BMFC that was subsequently used to power the buoy in a salt marsh near Tuckerton, NJ, USA. The second version BMFC has a mass of 16 kg, a volume of 0.03 m{sup 3}, sustains ca. 36 mW (energy equivalent of ca. 26 alkaline D-cells per year at 25 C), and can be deployed by a single person from a small craft with minimum or no in-water manipulation. This BMFC is being further developed to reduce cost and enable greater power output by electrically connecting multiple units in parallel. Use of this BMFC powering the meteorological buoy highlights the potential impact of BMFCs to

  2. Selection of the optimum combination of responses for Wave Buoy Analogy - An approach based on local sensitivity analysis

    DEFF Research Database (Denmark)

    Montazeri, Najmeh; Nielsen, Ulrik Dam; Jensen, Jørgen Juncher

    2016-01-01

    One method to estimate the wave spectrum onboard ships is to use measured ship responses. In this method, known also as Wave Buoy Analogy, amongst various responses that are available from sensor measurements, a couple of responses (at least three) are usually utilized. Selec-tion of the best...... combination of ship responses is important. Optimally, this selection should not be implemented manually in onboard applications. Therefore, availability of an automatic response selection procedure would be a great advantage for decision support. In this paper, a local sensitivity analysis is applied...

  3. Distortion of Near-Surface Seawater Temperature Structure by a Moored-Buoy Hull and Its Effect on Skin Temperature and Heat Flux Estimates

    Directory of Open Access Journals (Sweden)

    Kentaro Ando

    2009-07-01

    Full Text Available Previous studies have suggested that the accuracy of temperature measurements by surface-moored buoys may be affected by distortions of the near-surface temperature structure by the buoy hull on calm, sunny days. We obtained the first definite observational evidence that the temperature near the hull was not horizontally homogeneous at the same nominal depth. We observed large temperature differences of 1.0 K or more between thermometers at 0.2 m depth. The distortion of the surface temperature field yielded an error in estimates of daytime net surface heat flux up to more than 30 Wm–2.

  4. Directional Bias of TAO Daily Buoy Wind Vectors in the Central Equatorial Pacific Ocean from November 2008 to January 2010

    Directory of Open Access Journals (Sweden)

    Ge Peng

    2014-07-01

    Full Text Available This article documents a systematic bias in surface wind directions between the TAO buoy measurements at 0°, 170°W and the ECMWF analysis and forecasts. This bias was of the order 10° and persisted from November 2008 to January 2010, which was consistent with a post-recovery calibration drift in the anemometer vane. Unfortunately, the calibration drift was too time-variant to be used to correct the data so the quality flag for this deployment was adjusted to reflect low data quality. The primary purpose of this paper is to inform users in the modelling and remote-sensing community about this systematic, persistent wind directional bias, which will allow users to make an educated decision on using the data and be aware of its potential impact to their downstream product quality. The uncovering of this bias and its source demonstrates the importance of continuous scientific oversight and effective user-data provider communication in stewarding scientific data. It also suggests the need for improvement in the ability of buoy data quality control procedures of the TAO and ECMWF systems to detect future wind directional systematic biases such as the one described here.

  5. The Detection of Change in the Arctic Using Satellite and Buoy Data

    Science.gov (United States)

    Comiso, Josefino C.; Yang, J.; Honjo, S.; Krishfield, R.; Koblinsky, Chester J. (Technical Monitor)

    2001-01-01

    The decade of the 1990s is the warmest decade of the last century while the year 1998 is the warmest year ever observed by modern techniques with 9 out of 12 months of the year being the warmest month. Since the Arctic is expected to provide early signals of a possible warming scenario, detailed examination of changes in the Arctic environment is important. In this study, we examined available satellite ice cover and surface temperature data, wind and pressure data, and ocean hydrographic data to gain insights into the warming phenomenon. The areas of open water in both western and eastern regions of the Arctic were found to follow a cyclical pattern with approximately decadal period but with a lag of about three years between the two regions. The pattern was interrupted by unusually large anomalies in open water area in the western region in 1993 and 1998 and in the eastern region in 1995. The big 1998 open water anomaly occurred at the same time when a large surface temperature anomaly was also occurring in the area and adjacent regions. The infrared temperature data show for the first time the complete spatial scope of the warming anomalies and it is apparent that despite the magnitude of the 1998 anomaly, it is basically confined to North America and the Western Arctic. The large increases in open water areas in the Western Sector form 1996 to 1998 were observed to be coherent with changing wind directions which was predominantly cyclonic in 1996 and anti-cyclonic in 1997 and 1998. Detailed hydrography measurements up to 500 m depth over the same general area in April 1996 and April 1997 also indicate significant freshening and warming in the upper part of the mixed layer suggesting increases in ice melt. Continuous ocean temperature and salinity data from ocean buoys confirm this result and show significant seasonal changes from 1996 to 1998, at depths of 8 m, 45 m, and 75 m. Long data records of temperature and hydrography were also examined and the potential

  6. Autonomous profiling buoy system: a new powerful tool for research and operational oceanography

    Science.gov (United States)

    Aracri, Simona; Borghini, Mireno; Canesso, Devis; Chiggiato, Jacopo; Durante, Sara; Griffa, Annalisa; Schroeder, Katrin; Sparnocchia, Stefania; Vetrano, Anna; Kitawaza, Yuji; Kawahara, Hisayoshi; Nakamura, Tetsuya

    2015-04-01

    annual transport. In summer, excluding few cases of current inversions, exchanges between the two basins are mostly interrupted. Here the use of the new profiler is discussed. The profiling buoy system can be mounted at any level of a moored chain, which doesn't need any surficial support, allowing the flexibility to monitor discontinuities and sharp changes along selected depth ranges, at the same time, transmitting real-time data for best integration in modern operational oceanography networks.

  7. SeaBuoySoft – an On-line Automated Windows based Ocean Wave height Data Acquisition and Analysis System for Coastal Field’s Data Collection

    Directory of Open Access Journals (Sweden)

    P.H.Tarudkar

    2014-12-01

    Full Text Available Measurement of various hydraulic parameters such as wave heights for the research and the practical purpose in the coastal fields is one of the critical and challenging but equally important criteria in the field of ocean engineering for the design and the development of hydraulic structures such as construction of sea walls, break waters, oil jetties, fisheries harbors, all other structures, and the ships maneuvering, embankments, berthing on jetties. This paper elucidates the development of “SeaBuoySoft online software system for coastal field‟s wave height data collection” for the coastal application work. The system could be installed along with the associated hardware such as a Digital Waverider Receiver unit and a Waverider Buoy at the shore. The ocean wave height data, transmitted by wave rider buoy installed in the shallow/offshore waters of sea is received by the digital waverider receiver unit and it is interfaced to the SeaBuoySoft software. The design and development of the software system has been worked out in-house at Central Water and Power Research Station, Pune, India. The software has been developed as a Windows based standalone version and is unique of its kind for the reception of real time ocean wave height data, it takes care of its local storage of wave height data for its further analysis work as and when required. The system acquires real time ocean wave height data round the clock requiring no operator intervention during data acquisition process on site.

  8. 溢油跟踪浮标水动力特性研究%Improving effectiveness of oil-spill tracking buoys

    Institute of Scientific and Technical Information of China (English)

    王天霖; 刘寅东

    2009-01-01

    This paper aims to optimize the design of oil-spill tracking buoys in order to improve their precision. The hydrodynamic principles governing a buoy tracking an oil film were studied and tracking errors analyzed. The balance equation for a buoy tracking an oil spill floating on the sea was estanblished, and a relational expression was obtained for wind drift, as well as those for surface current, temperature, sea conditions, and buoy geometry, such as its height above the sea surface, and so on. Given sea conditions and the properties of the oil film, the best design of buoy and tracking effect was then calculated. Effective tracking range for a given tracking accuracy, and tracking accuracy given different sea conditions were calculated for a MetOcean product, the Argosphere. The relationship between the buoy's tracking precision and the sea conditions it experiences was also discussed. This should provide guidance for the design of oil-spill tracking buoys.%为提高溢油浮标跟踪海上溢油油膜的精度,优化溢油浮标设计方案,针对溢油浮标跟踪油膜的水动力学机理问题进行研究,并在此基础上对跟踪误差进行了分析.建立了溢油跟踪浮标的水动力平衡方程并求解,得到的结果包含油膜风系数、表面海水漂流风生流系数以及海洋环境温度、风速、浮标几何形状、出水高度等影响溢油浮标跟踪效果的关键因素.根据溢油事故发生地的海况及溢油油膜本身的性质,有针对性地选择最优的浮标设计方案,以达到最佳的跟踪效果.以METOCEAN公司的Argosphere型溢油浮标为例进行了分析和计算,并讨论了浮标跟踪精度与工作海况之间的关系,对溢油跟踪浮标的设计具有指导意义.

  9. Moball-Buoy Network: A Near-Real-Time Ground-Truth Distributed Monitoring System to Map Ice, Weather, Chemical Species, and Radiations, in the Arctic

    Science.gov (United States)

    Davoodi, F.; Shahabi, C.; Burdick, J.; Rais-Zadeh, M.; Menemenlis, D.

    2014-12-01

    The work had been funded by NASA HQ's office of Cryospheric Sciences Program. Recent observations of the Arctic have shown that sea ice has diminished drastically, consequently impacting the environment in the Arctic and beyond. Certain factors such as atmospheric anomalies, wind forces, temperature increase, and change in the distribution of cold and warm waters contribute to the sea ice reduction. However current measurement capabilities lack the accuracy, temporal sampling, and spatial coverage required to effectively quantify each contributing factor and to identify other missing factors. Addressing the need for new measurement capabilities for the new Arctic regime, we propose a game-changing in-situ Arctic-wide Distributed Mobile Monitoring system called Moball-buoy Network. Moball-buoy Network consists of a number of wind-propelled self-powered inflatable spheres referred to as Moball-buoys. The Moball-buoys are self-powered. They use their novel mechanical control and energy harvesting system to use the abundance of wind in the Arctic for their controlled mobility and energy harvesting. They are equipped with an array of low-power low-mass sensors and micro devices able to measure a wide range of environmental factors such as the ice conditions, chemical species wind vector patterns, cloud coverage, air temperature and pressure, electromagnetic fields, surface and subsurface water conditions, short- and long-wave radiations, bathymetry, and anthropogenic factors such as pollutions. The stop-and-go motion capability, using their novel mechanics, and the heads up cooperation control strategy at the core of the proposed distributed system enable the sensor network to be reconfigured dynamically according to the priority of the parameters to be monitored. The large number of Moball-buoys with their ground-based, sea-based, satellite and peer-to-peer communication capabilities would constitute a wireless mesh network that provides an interface for a global

  10. Wave Buoy Server-Side Software Design%波浪浮标服务器端软件设计

    Institute of Scientific and Technical Information of China (English)

    吴子岳; 黄耀耀

    2012-01-01

    传统采用VHF通信的波浪浮标系统需要架设岸站接收机,采用GPRS无线通信解决方案的波浪浮标系统可以省去岸站接收机的费用,并且性能更加稳定可靠。本文主要介绍了服务器端通信模块的设计、数据处理处理模块的设计。软件的编辑使用VisualC++6.0软件,通信模块的设计采用MFC封装的CSocket类,CSocket类派生于完全封装了WindowsSocketsAPI函数的CAsyncSocket类,采用CSocket类可以更加方便地编写网络应用程序。数据处理模块采用了MATLAB与VisualC++混合编程,利用MATLAB留有的动态链接库DLL外部接口可以很方便地将MATLAB功能嵌入到VisualC++的MFC工程中,利用MATLAB与VisualC++混合编程可以方便地进行海浪频谱分析。%Wave buoy system with traditional VHF communication needs to set up offshore station to receive data,the expense can be saved after using GPRS wireless communication solution,moreover the performance of wave buoy system is more stable and reliable.This paper describes the software design on the server-side of wave buoy including communication module,data processing module.All the source codes are programmed based on tool software Visual C++ 6.0.Communication module is designed with class CSocket which is encapsulated by MFC.Class CSocket derives from class CAsyncSocket which completely encapsulates the Windows Sockets API functions.Class CSocket enhances the Convenience of network programming.Data processing module is designed with MATLAB and Visual C++ mixed programming.With the use of dynamic link library(DLL) the external interface left by MATLAB,the MATLAB function can be easily embedded into Visual C++ MFC project.Wave spectrum analysis can be easily handled by using MATLAB and Visual C++ mixed programming.

  11. Circulation and hydrological characteristics of the North Aegean Sea: a contribution from real-time buoy measurements

    Directory of Open Access Journals (Sweden)

    K. NITTIS

    2012-12-01

    Full Text Available In the framework of the POSEIDON Project, a network of open sea oceanographic buoys equipped with meteorological and oceanographic sensors has been operational in the Aegean Sea since 1998. The analysis of upper-ocean physical data (currents at 3m, temperature and salinity at 3-40m depths collected during the last 2 years from the stations of the North Aegean basin indicates a strong temporal variability of flow field and hydrological characteristics in both synoptic and seasonal time scales. The northern part of the basin is mainly influenced by the Black Sea Water outflow and the mesoscale variability of the corresponding thermohaline fronts, while the southern stations are influenced by the general circulation of the Aegean Sea with strong modulations caused by the seasonally varying atmospheric forcing.

  12. Development of a Regional Coral Observation Method by a Fluorescence Imaging LIDAR Installed in a Towable Buoy

    Directory of Open Access Journals (Sweden)

    Masahiko Sasano

    2016-01-01

    Full Text Available Coral bleaching and mortality is predicted to increase under global climate change. A new observation technique is required to monitor regional coral conditions. To this end, we developed a light detection and ranging (LIDAR system installed in a towable buoy for boat observations, which acquires continuous fluorescent images of the seabed during day-time. Most corals have innate fluorescent proteins in their tissue, and they emit fluorescence by ultraviolet excitation. This fluorescence distinguishes living coral from dead coral skeleton, crustose coralline algae, and sea algae. This paper provides a proof of concept for using the LIDAR system and fluorescence to map coral distribution within 1 km scale and coral cover within 100 m scale for a single reef in Japan.

  13. Uncertainty quantification and inference of Manning's friction coefficients using DART buoy data during the Tōhoku tsunami

    KAUST Repository

    Sraj, Ihab

    2014-11-01

    Tsunami computational models are employed to explore multiple flooding scenarios and to predict water elevations. However, accurate estimation of water elevations requires accurate estimation of many model parameters including the Manning\\'s n friction parameterization. Our objective is to develop an efficient approach for the uncertainty quantification and inference of the Manning\\'s n coefficient which we characterize here by three different parameters set to be constant in the on-shore, near-shore and deep-water regions as defined using iso-baths. We use Polynomial Chaos (PC) to build an inexpensive surrogate for the G. eoC. law model and employ Bayesian inference to estimate and quantify uncertainties related to relevant parameters using the DART buoy data collected during the Tōhoku tsunami. The surrogate model significantly reduces the computational burden of the Markov Chain Monte-Carlo (MCMC) sampling of the Bayesian inference. The PC surrogate is also used to perform a sensitivity analysis.

  14. Variability of surface velocity in the Kuroshio Current and adjacent waters derived from Argos drifter buoys and satellite altimeter data

    Institute of Scientific and Technical Information of China (English)

    MA Chao; WU Dexing; LIN Xiaopei

    2009-01-01

    By combining Argos drifter buoys and TOPEX/POSEIDON altimeter data, the time series of sea-surface velocity fields in the Kuroshio Current (KC) and adjacent regions are established. And the variability of the KC from the Luzon Strait to the Tokara Strait is studied based on the velocity fields. The results show that the dominant variability period varies in different segments of the KC" The primary period near the Luzon Strait and to the east of Taiwan Island is the intra-seasonal time scale; the KC on the continental shelf of the ECS is the steadiest segment without obvious periodicity, while the Tokara Strait shows the period of seasonal variability. The diverse periods are caused by the Rossby waves propagating from the interior ocean, with adjustments in topography of island chain and local wind stress.

  15. Temperature profile data from moored buoy in the Gulf of Alaska as part of the Trans-Alaska Pipeline System project, from 1989-06-10 to 1989-10-25 (NODC Accession 9900193)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profile data were collected using moored buoy in the Gulf of Alaska from June 10, 1989 to October 25, 1989. Data were submitted by Dr. Chirk Chu from the...

  16. Drifting buoy and other data from drifting platforms in the Bering Sea as part of the Outer Continental Shelf Environmental Assessment Program (OCSEAP) from 17 January 1981 to 20 June 1981 (NODC Accession 8200120)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Drifting buoy data was collected from drifting platforms in the Bering Sea by the Flow Research Company as part of the Outer Continental Shelf Environmental...

  17. Drifting buoy and other data from the Beaufort Sea and other locations as part of the Outer Continental Shelf Environmental Assessment Program (OCSEAP) from 03 March 1977 to 05 April 1977 (NODC Accession 7700543)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Drifting buoy data was collected from the Beaufort Sea and other locations by the University of Washington (UW) as part of the Outer Continental Shelf Environmental...

  18. Drifting buoy and other data from the Arctic Ocean and other locations as part of the Outer Continental Shelf Environmental Assessment Program (OCSEAP) from 02 November 1975 to 03 June 1976 (NODC Accession 7601626)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Drifting buoy data was collected by the University of Washington - Seattle (UW) as part of the Outer Continental Shelf Environmental Assessment Program (OCSEAP)....

  19. Drifting buoy and other data from the Beaufort Sea and other locations as part of the Outer Continental Shelf Environmental Assessment Program (OCSEAP) from 04 April 1977 to 03 July 1977 (NODC Accession 7700780)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Drifting buoy data was collected from the Beaufort Sea by the University of Washington (UW) as part of the Outer Continental Shelf Environmental Assessment Program...

  20. CTD, current meter, meteorological buoy, and bottle data from the Gulf of Mexico from the ALPHA HELIX and other platforms in support of LATEX A from 18 March 1993 to 23 September 1993 (NODC Accession 9400149)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CTD, current meter, meteorological buoy, and bottle data were collected from the Gulf of Mexico from the ALPHA HELIX and other platforms. Data were collected by...

  1. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); NWHI, FFS; Long: -166.27183, Lat: 23.85678 (WGS84); Sensor Depth: 1.00m; Data Range: 20040919-20050411.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Enhanced (CREWS-ENH) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  2. Current meter and temperature profile data from current meter and buoy casts in the TOGA area of Pacific Ocean from 27 April 1993 to 09 June 1994 (NODC Accession 9700042)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Current meter and temperature profile data were collected using current meter and buoy casts in the TOGA area of Pacific Ocean from 27 April 1993 to 09 June 1994....

  3. Bacteriology, wind wave spectra, and benthic organism data from moored buoy casts and other instruments in the Gulf of Mexico during the Brine Disposal project, 01 February 1978 - 03 May 1979 (NODC Accession 7900247)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bacteriology, wind wave spectra, and benthic organism data were collected using moored buoy casts and other instruments in the Gulf of Mexico from February 1, 1978...

  4. CRED Sea Surface Temperature (SST) Buoy; PRIA, KIN; Long: -162.34213, Lat: 06.39241 (WGS84); Sensor Depth: 0.33m; Data Range: 20040402-20060329.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  5. Upper ocean currents and sea surface temperatures (SST) from Satellite-tracked drifting buoys (drifters) as part of the Global Drifter Program for Hawaii region 1980/02/01 - 2009/03/31 (NODC Accession 0063296)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Satellite-tracked drifting buoys ("drifters") collect measurements of upper ocean currents and sea surface temperatures (SST) around the world as part of the Global...

  6. CRED Sea Surface Temperature (SST) Buoy; CNMI, GUA; Long: 144.80048, Lat: 13.52900 (WGS84); Sensor Depth: 0.19m; Data Range: 20070513-20090405.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  7. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Environmental Data Logger (EDL); PRIA, PAL; Long: -162.10280, Lat: 05.88468 (WGS84); Sensor Depth: 0.00m; Data Range: 20060325-20080401.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Enhanced (CREWS-ENH) buoys are equipped to sea surface measure water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  8. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Environmental Data Logger (EDL); PRIA, PAL; Long: -162.10282, Lat: 05.88467 (WGS84); Sensor Depth: 0.00m; Data Range: 20040330-20060325.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Enhanced (CREWS-ENH) buoys are equipped to sea surface measure water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  9. Drifting buoy and other data from the Beaufort Sea as part of the Outer Continental Shelf Environmental Assessment Program (OCSEAP) from 05 November 1975 to 01 October 1976 (NODC Accession 7700019)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Drifting buoy and other data was collected from the Beaufort Sea by the University of Washington (UW) as part of the Outer Continental Shelf Environmental Assessment...

  10. CRED Sea Surface Temperature (SST) Buoy; NWHI, NEC; Long: -164.69775, Lat: 23.57152 (WGS84); Sensor Depth: 0.33m; Data Range: 20030714-20030825.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  11. Temperature, current meter, and other data from moored buoy from the HUMBOLDT as part of the GARP (Global Atmospheric Research Program) Atlantic Tropical Experiment (GATE) project, 28 July 1974 - 18 August 1974 (NODC Accession 7601676)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature, current meter, and other data were collected using moored buoy from the HUMBOLDT from July 28, 1974 to August 18, 1974. Data were submitted by US Coast...

  12. CRED Sea Surface Temperature (SST) Buoy; NWHI, KUR; Long: -178.34327, Lat: 28.41817 (WGS84); Sensor Depth: 0.19m; Data Range: 20080929-20090916.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  13. CRED Sea Surface Temperature (SST) Buoy; NWHI, KUR; Long: -178.34319, Lat: 28.41816 (WGS84); Sensor Depth: 0.33m; Data Range: 20040706-20060917.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  14. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); NWHI, KUR; Long: -178.34455, Lat: 28.41863 (WGS84); Sensor Depth: 1.00m; Data Range: 20020922-20030316.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  15. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); NWHI, KUR; Long: -178.34457, Lat: 28.41858 (WGS84); Sensor Depth: 1.00m; Data Range: 20041006-20060916.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  16. CRED Sea Surface Temperature (SST) Buoy; NWHI, KUR; Long: -178.34322, Lat: 28.41813 (WGS84); Sensor Depth: 0.19m; Data Range: 20090916-20100918.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  17. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Supplemental Sea Surface Temperature Recorder (SBE39); NWHI, KUR; Long: -178.34453, Lat: 28.41852 (WGS84); Sensor Depth: 1.00m; Data Range: 20060918-20080929.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  18. Real-time current, wave, temperature, salinity, and meteorological data from Gulf of Maine Ocean Observing System (GoMOOS) buoys, 11/30/2003 - 12/7/2003 (NODC Accession 0001259)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Gulf of Maine Ocean Observing System (GoMOOS) collected real-time data with buoy-mounted instruments (e.g., accelerometers and Acoustic Doppler Current...

  19. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Environmental Data Logger (EDL); NWHI, KUR; Long: -178.34453, Lat: 28.41852 (WGS84); Sensor Depth: 0.00m; Data Range: 20060917-20080929.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  20. Physical and fluorescence data collected using moored buoy casts as part of the IDOE/POLYMODE (International Decade of Ocean Exploration / combination of USSR POLYGON project and US MODE) from 07 December 1975 to 03 January 1977 (NODC Accession 7700569)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Physical and fluorescence data were collected using moored buoy from May 4, 1975 to December 18, 1975. Data were submitted by Massachusetts Institute of Technology;...

  1. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); NWHI, MID; Long: -177.34402, Lat: 28.21788 (WGS84); Sensor Depth: 1.00m; Data Range: 20011022-20020325.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Enhanced (CREWS-ENH) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  2. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Environmental Data Logger (EDL); NWHI, MAR; Long: -170.63382, Lat: 25.44643 (WGS84); Sensor Depth: 0.00m; Data Range: 20051016-20060907.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  3. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); PRIA, PAL; Long: -162.10289, Lat: 05.88463 (WGS84); Sensor Depth: 1.00m; Data Range: 20080401-20100410.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Enhanced (CREWS-ENH) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  4. CRED Sea Surface Temperature (SST) Buoy; AMSM, TAU; Long: -169.50890, Lat: -14.24409 (WGS84); Sensor Depth: 0.33m; Data Range: 20060304-20080229.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  5. CRED Sea Surface Temperature (SST) Buoy; CNMI, GUA; Long: 144.79778, Lat: 13.51902 (WGS84); Sensor Depth: 0.33m; Data Range: 20030924-20040531.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  6. CRED Sea Surface Temperature (SST) Buoy; AMSM, TUT; Long: -170.72200, Lat: -14.28428 (WGS84); Sensor Depth: 0.33m; Data Range: 20020306-20020523.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  7. CRED Sea Surface Temperature (SST) Buoy; NWHI, LIS; Long: -173.91600, Lat: 25.96770 (WGS84); Sensor Depth: 0.33m; Data Range: 20050614-20060925.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  8. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Supplemental Sea Surface Temperature Recorder (SBE39); NWHI, MAR; Long: -170.63378, Lat: 25.44642 (WGS84); Sensor Depth: 1.00m; Data Range: 20060915-20080918.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  9. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); NWHI, MAR; Long: -170.63382, Lat: 25.44652 (WGS84); Sensor Depth: 1.00m; Data Range: 20021001-20030321.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  10. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Environmental Data Logger (EDL); CNMI, SAI; Long: 145.72285, Lat: 15.23750 (WGS84); Sensor Depth: 0.00m; Data Range: 20030819-20050921.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Enhanced (CREWS-ENH) buoys are equipped to sea surface measure water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  11. Drifting buoy and other data from the Arctic Ocean in support of the Outer Continental Shelf Environmental Assessment Program (OCSEAP) from 04 June 1976 to 27 November 1976 (NODC Accession 7700205)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Drifting buoy data were collected from the Arctic Ocean by the University of Washington in support of the Outer Continental Shelf Environmental Assessment Program...

  12. Drifting buoy and other data from the Gulf of Alaska as part of the Outer Continental Shelf Environmental Assessment Program (OCSEAP) from 21 October 1976 to 11 November 1976 (NODC Accession 7700740)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Drifting buoy data was collected from the Gulf of Alaska by the Atlantic Oceanographic and Meteorological Laboratory (AOML) as part of the Outer Continental Shelf...

  13. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); CNMI, SAI; Long: 145.72288, Lat: 15.23746 (WGS84); Sensor Depth: 1.00m; Data Range: 20050921-20060525.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Enhanced (CREWS-ENH) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  14. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Environmental Data Logger (EDL); NWHI, FFS; Long: -166.27183, Lat: 23.85678 (WGS84); Sensor Depth: 0.00m; Data Range: 20020911-20030718.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Enhanced (CREWS-ENH) buoys are equipped to sea surface measure water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  15. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Supplemental Sea Surface Temperature Recorder (SBE39); NWHI, FFS; Long: -166.27183, Lat: 23.85678 (WGS84); Sensor Depth: 1.00m; Data Range: 20040622-20040809.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Enhanced (CREWS-ENH) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  16. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); NWHI, FFS; Long: -166.27183, Lat: 23.85678 (WGS84); Sensor Depth: 1.00m; Data Range: 20011017-20020120.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Enhanced (CREWS-ENH) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  17. Drifting buoy and other data from the Chukchi Sea as part of the Outer Continental Shelf Environmental Assessment Program (OCSEAP) from 27 June 1977 to 07 November 1977 (NODC Accession 7800005)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Drifting buoy data was collected from the Chukchi Sea by the University of Washington (UW) as part of the Outer Continental Shelf Environmental Assessment Program...

  18. Drifting buoy and other data from the Arctic Ocean and Beaufort Sea as part of the Outer Continental Shelf Environmental Assessment Program (OCSEAP) from 04 November 1975 to 01 October 1976 (NODC Accession 7700114)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Drifting buoy data was collected from the Arctic Ocean and Beaufort Sea by the University of Washington (UW) as part of the Outer Continental Shelf Environmental...

  19. Physical profile and meteorological data from CTD casts during cruises to service the TAO/TRITON buoys in the equatorial Pacific from 02 March 2002 to 22 November 2002 (NODC Accession 0000945)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Physical profile data and meteorological data were collected from CTD casts in the equatorial Pacific Ocean during cruises to to service the TAO/TRITON buoy array....

  20. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Environmental Data Logger (EDL); NWHI, PHR; Long: -175.81612, Lat: 27.85325 (WGS84); Sensor Depth: 0.00m; Data Range: 20020918-20030811.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  1. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Environmental Data Logger (EDL); NWHI, KUR; Long: -178.34455, Lat: 28.41863 (WGS84); Sensor Depth: 0.00m; Data Range: 20030806-20041005.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  2. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Environmental Data Logger (EDL); NWHI, FFS; Long: -166.27183, Lat: 23.85678 (WGS84); Sensor Depth: 0.00m; Data Range: 20040919-20050411.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Enhanced (CREWS-ENH) buoys are equipped to sea surface measure water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  3. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Environmental Data Logger (EDL); NWHI, PHR; Long: -175.81590, Lat: 27.85408 (WGS84); Sensor Depth: 0.00m; Data Range: 20011026-20020917.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  4. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Environmental Data Logger (EDL); NWHI, LIS; Long: -173.91608, Lat: 25.96767 (WGS84); Sensor Depth: 0.00m; Data Range: 20010920-20020612.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  5. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Environmental Data Logger (EDL); NWHI, MAR; Long: -170.63382, Lat: 25.44643 (WGS84); Sensor Depth: 0.00m; Data Range: 20040924-20051015.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  6. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Environmental Data Logger (EDL); NWHI, FFS; Long: -166.27183, Lat: 23.85678 (WGS84); Sensor Depth: 0.00m; Data Range: 20050411-20060904.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Enhanced (CREWS-ENH) buoys are equipped to sea surface measure water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  7. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Environmental Data Logger (EDL); NWHI, KUR; Long: -178.34457, Lat: 28.41858 (WGS84); Sensor Depth: 0.00m; Data Range: 20041005-20060917.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  8. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Environmental Data Logger (EDL); NWHI, MAR; Long: -170.63378, Lat: 25.44642 (WGS84); Sensor Depth: 0.00m; Data Range: 20060907-20080918.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  9. CRED Sea Surface Temperature (SST) Buoy; NWHI, PHR; Long: -175.81592, Lat: 27.85393 (WGS84); Sensor Depth: 0.19m; Data Range: 20080922-20090923.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  10. CRED Sea Surface Temperature (SST) Buoy; AMSM, TUT; Long: -170.72245, Lat: -14.28436 (WGS84); Sensor Depth: 0.33m; Data Range: 20040223-20060219.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  11. CRED Sea Surface Temperature (SST) Buoy; AMSM, TUT; Long: -170.72266, Lat: -14.28457 (WGS84); Sensor Depth: 0.33m; Data Range: 20080220-20100222.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  12. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Environmental Data Logger (EDL); NWHI, MAR; Long: -170.63382, Lat: 25.44652 (WGS84); Sensor Depth: 0.00m; Data Range: 20030824-20040922.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  13. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Supplemental Sea Surface Temperature Recorder (SBE39); NWHI, MAR; Long: -170.63382, Lat: 25.44643 (WGS84); Sensor Depth: 1.00m; Data Range: 20051020-20060907.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  14. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Supplemental Sea Surface Temperature Recorder (SBE39); NWHI, KUR; Long: -178.34455, Lat: 28.41863 (WGS84); Sensor Depth: 1.00m; Data Range: 20040629-20041005.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  15. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); NWHI, PHR; Long: -175.81593, Lat: 27.85397 (WGS84); Sensor Depth: 1.00m; Data Range: 20040927-20060912.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  16. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); NWHI, KUR; Long: -178.34455, Lat: 28.41863 (WGS84); Sensor Depth: 1.00m; Data Range: 20030807-20040415.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  17. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); NWHI, FFS; Long: -166.27183, Lat: 23.85678 (WGS84); Sensor Depth: 1.00m; Data Range: 20020423-20020910.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Enhanced (CREWS-ENH) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  18. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Supplemental Sea Surface Temperature Recorder (SBE39); NWHI, MAR; Long: -170.63382, Lat: 25.44652 (WGS84); Sensor Depth: 1.00m; Data Range: 20020424-20020802.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  19. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); NWHI, FFS; Long: -166.27183, Lat: 23.85678 (WGS84); Sensor Depth: 1.00m; Data Range: 20050413-20060904.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Enhanced (CREWS-ENH) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  20. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Supplemental Sea Surface Temperature Recorder (SBE39); PRIA, PAL; Long: -162.10282, Lat: 05.88467 (WGS84); Sensor Depth: 1.00m; Data Range: 20040330-20060325.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Enhanced (CREWS-ENH) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  1. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); NWHI, KUR; Long: -178.34453, Lat: 28.41852 (WGS84); Sensor Depth: 1.00m; Data Range: 20060917-20080929.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  2. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Environmental Data Logger (EDL); NWHI, PHR; Long: -175.81593, Lat: 27.85397 (WGS84); Sensor Depth: 0.00m; Data Range: 20040927-20060912.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  3. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Supplemental Sea Surface Temperature Recorder (SBE39); PRIA, PAL; Long: -162.10289, Lat: 05.88463 (WGS84); Sensor Depth: 1.00m; Data Range: 20080401-20090515.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Enhanced (CREWS-ENH) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  4. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Environmental Data Logger (EDL); NWHI, PHR; Long: -175.81612, Lat: 27.85325 (WGS84); Sensor Depth: 0.00m; Data Range: 20030812-20040926.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  5. CRED Sea Surface Temperature (SST) Buoy; AMSM, TUT; Long: -170.76332, Lat: -14.36675 (WGS84); Sensor Depth: 0.19m; Data Range: 20060226-20070406.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  6. CRED Sea Surface Temperature (SST) Buoy; AMSM, TUT; Long: -170.83339, Lat: -14.32838 (WGS84); Sensor Depth: 0.19m; Data Range: 20050806-20060221.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  7. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Environmental Data Logger (EDL); NWHI, FFS; Long: -166.27183, Lat: 23.85678 (WGS84); Sensor Depth: 0.00m; Data Range: 20030826-20040809.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Enhanced (CREWS-ENH) buoys are equipped to sea surface measure water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  8. CRED Sea Surface Temperature (SST) Buoy; Maug, Commonwealth of the Northern Mariana Islands; Long: 145.23196, Lat: 20.02909 (WGS84); Sensor Depth: 0.19m; Data Date Range: 20090428-20110418.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  9. CRED Sea Surface Temperature (SST) Buoy; NWHI, LAY; Long: -171.74242, Lat: 25.77248 (WGS84); Sensor Depth: 0.19m; Data Range: 20060910-20071203.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  10. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Environmental Data Logger (EDL); NWHI, FFS; Long: -166.27183, Lat: 23.85678 (WGS84); Sensor Depth: 0.00m; Data Range: 20030718-20030826.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Enhanced (CREWS-ENH) buoys are equipped to sea surface measure water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  11. Physical and chemical data collected using CTD and buoy casts from NOAA Ship RESEARCHER and another platform from 1974-06-27 to 1974-07-18 (NCEI Accession 7601653)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Physical and chemical data were collected using CTD and buoy casts from NOAA Ship RESEARCHER and NOAA Ship OCEANOGRAPHER from 27 June 1974 to 18 July 1974. Data were...

  12. Wind wave spectra and other data from moored buoy in the East/West Coast of United States, South Pacific Ocean, Gulf of Mexico, and Great Lakes from 01 March 2000 to 31 March 2000 (NODC Accession 0000150)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Wind wave spectra and other data were collected using moored buoy in the East/West Coast of United States, South Pacific Ocean, Gulf of Mexico, and Great Lakes. Data...

  13. Wind wave spectra and other data from moored buoy in the East/West Coast of United States, South Pacific Ocean, Gulf of Mexico, and Great Lakes from 01 April 2000 to 30 April 2000 (NODC Accession 0000156)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Wind wave spectra and other data were collected using moored buoy in the East/West Coast of United States, South Pacific Ocean, Gulf of Mexico, and Great Lakes. Data...

  14. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Supplemental Sea Surface Temperature Recorder (SBE39); NWHI, LIS; Long: -173.91608, Lat: 25.96767 (WGS84); Sensor Depth: 1.00m; Data Range: 20011020-20011225.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  15. Bacteriology data from moored buoy casts and other instruments in the Delaware Bay and North Atlantic Ocean during the Ocean Continental Shelf (OCS-Mid Atlantic Ocean) project, 05 November 1976 - 16 August 1977 (NODC Accession 7800207)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bacteriology data were collected using moored buoy casts and other instruments in the Delaware Bay and North Atlantic Ocean from November 5, 1976 to August 16, 1977....

  16. Physical profile data collected in the Equatorial Pacific during cruises to service the TAO/TRITON array, a network of deep ocean moored buoys, February 23 - December 16, 2005 (NODC Accession 0002644)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — During 2005, CTD data were collected in the equatorial Pacific Ocean during cruises to service the TAO/TRITON array, a network of deep ocean moored buoys to support...

  17. Temperature, current meter, and other data from moored buoy as part of the GARP (Global Atmospheric Research Program) Atlantic Tropical Experiment (GATE) project, 30 July 1974 - 14 August 1974 (NODC Accession 7601675)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature, current meter, and other data were collected using moored buoy from the CAPRICORNE from July 30, 1974 to August 14, 1974. Data were collected as part of...

  18. CRED Sea Surface Temperature (SST) Buoy; CNMI, MAU; Long: 145.23217, Lat: 20.02920 (WGS84); Sensor Depth: 0.33m; Data Range: 20030903-20050911.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  19. CRED Sea Surface Temperature (SST) Buoy; AMSM, TUT; Long: -170.83355, Lat: -14.32838 (WGS84); Sensor Depth: 0.33m; Data Range: 20060221-20080221.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  20. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Environmental Data Logger (EDL); PRIA, PAL; Long: -162.10283, Lat: 05.88468 (WGS84); Sensor Depth: 0.00m; Data Range: 20020315-20021024.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Enhanced (CREWS-ENH) buoys are equipped to sea surface measure water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  1. CRED Sea Surface Temperature (SST) Buoy; AMSM, TAU; Long: -169.50891, Lat: -14.24402 (WGS84); Sensor Depth: 0.33m; Data Range: 20080301-20100312.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  2. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Supplemental Sea Surface Temperature Recorder (SBE39); AMSM, ROS; Long: -168.16025, Lat: -14.55134 (WGS84); Sensor Depth: 1.00m; Data Range: 20060307-20070902.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  3. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Supplemental Sea Surface Temperature Recorder (SBE39); NWHI, FFS; Long: -166.27183, Lat: 23.85678 (WGS84); Sensor Depth: 1.00m; Data Range: 20050411-20060904.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Enhanced (CREWS-ENH) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  4. CRED Sea Surface Temperature (SST) Buoy; NWHI, LAY; Long: -171.74250, Lat: 25.77240 (WGS84); Sensor Depth: 0.33m; Data Range: 20040924-20060910.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  5. CRED Sea Surface Temperature (SST) Buoy; NWHI, LIS; Long: -173.91583, Lat: 25.96762 (WGS84); Sensor Depth: 0.19m; Data Range: 20081004-20090910.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  6. Wind wave spectra and other data from moored buoy in the East/West Coast of United States, South Pacific Ocean, Gulf of Mexico, and Great Lakes from 01 February 2000 to 29 February 2000 (NODC Accession 0000140)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Wind wave spectra and other data were collected using moored buoy in the East/West Coast of United States, South Pacific Ocean, Gulf of Mexico, and Great Lakes. Data...

  7. CRED Sea Surface Temperature (SST) Buoy; NWHI, LIS; Long: -173.91588, Lat: 25.96764 (WGS84); Sensor Depth: 0.19m; Data Range: 20090910-20100922.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data from Coral Reef Ecosystem Division (CRED), NOAA Pacific Islands Fisheries Science Center (PIFSC) Sea Surface Temperature (SST) Buoys provide a time series of...

  8. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Environmental Data Logger (EDL); NWHI, KUR; Long: -178.34455, Lat: 28.41863 (WGS84); Sensor Depth: 0.00m; Data Range: 20020922-20030806.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  9. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Environmental Data Logger (EDL); AMSM, ROS; Long: -168.16025, Lat: -14.55134 (WGS84); Sensor Depth: 0.00m; Data Range: 20060307-20080312.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  10. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Supplemental Sea Surface Temperature Recorder (SBE39); NWHI, PHR; Long: -175.81595, Lat: 27.85396 (WGS84); Sensor Depth: 0.91m; Data Range: 20060915-20080828.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CREWS Standard (CREWS-STD) buoys are equipped to measure sea surface water temperature and conductivity (Sea-Bird Model SBE37-SM, Sea-Bird Electronics, Inc.,...

  11. 海上溢油跟踪定位浮标参数分析及技术优化研究%The Research of Parameter Analysis and Optimization of Coastal Surface drifting Oil-spill Tracking Buoy

    Institute of Scientific and Technical Information of China (English)

    杨瑞; 刘寅东; 顾群; 王云强

    2014-01-01

    To improve the accuracy of oil-spill tracking buoy by optimizing the design of buoy , the oil-spill buoy parameters including size , weight and location are studied based on the hydrodynamic principles governing buoy tracking oil -film.The results show that it is possible that the best design of buoy and tracking effect is calculated to reach the accuracy of oil -spill buoy tracking oil-film according to geographic position and the properties of the oil-film.%为提高溢油浮标跟踪海上溢油油膜的精度,基于溢油浮标跟踪油膜的水动力学机理,对溢油浮标的尺寸、重量、海域位置等参数进行分析及优化,研究表明,可以根据浮标应用地理位置、海况及溢油油膜本身的性质,有针对性地选择最优的浮标设计参数,以提高溢油跟踪预测的准确性。

  12. Observations of vertical tidal motions of a floating iceberg in front of Shirase Glacier, East Antarctica, using a geodetic-mode GPS buoy

    Science.gov (United States)

    Aoyama, Yuichi; Kim, Tae-Hee; Doi, Koichiro; Hayakawa, Hideaki; Higashi, Toshihiro; Ohsono, Shingo; Shibuya, Kazuo

    2016-06-01

    A dual-frequency GPS receiver was deployed on a floating iceberg downstream of the calving front of Shirase Glacier, East Antarctica, on 28 December 2011 for utilizing as floating buoy. The three-dimensional position of the buoy was obtained by GPS every 30 s with a 4-5-cm precision for ca. 25 days. The height uncertainty of the 1-h averaged vertical position was ∼0.5 cm, even considering the uncertainties of un-modeled ocean loading effects. The daily evolution of north-south (NS), east-west (EW), and up-down (UD) motions shows periodic UD variations sometimes attaining an amplitude of 1 m. Observed amplitudes of tidal harmonics of major constituents were 88%-93% (O1) and 85%-88% (M2) of values observed in the global ocean tide models FES2004 and TPXO-8 Atlas. The basal melting rate of the iceberg is estimated to be ∼0.6 m/day, based on a firn densification model and using a quasi-linear sinking rate of the iceberg surface. The 30-s sampling frequency geodetic-mode GPS buoy helps to reveal ice-ocean dynamics around the calving front of Antarctic glaciers.

  13. Proof-of-Concept Trajectory Designs for a Multi-Spacecraft, Low-Thrust Heliocentric Solar Weather Buoy Mission

    Science.gov (United States)

    Muller, Ronald; Franz, Heather; Roberts, Craig; Folta, Dave

    2005-01-01

    A new solar weather mission has been proposed, involving a dozen or more small spacecraft spaced at regular, constant intervals in a mutual heliocentric circular orbit between the orbits of Earth and Venus. These solar weather buoys (SWBs) would carry instrumentation to detect and measure the material in solar flares, solar energetic particle events, and coronal mass ejections as they flowed past the buoys, serving both as science probes and as a radiation early warning system for the Earth and interplanetary travelers to Mars. The baseline concept involves placing a mothercraft carrying the SWBs into a staging orbit at the Sun-Earth L1 libration point. The mothercraft departs the L1 orbit at the proper time to execute a trailing-edge lunar flyby near New Moon, injecting it into a heliocentric orbit with its perihelion interior to Earth s orbit. An alternative approach would involve the use of a Double Lunar Swingby (DLS) orbit, rather than the L1 orbit, for staging prior to this flyby. After injection into heliocentric orbit, the mothercraft releases the SWBs-all equipped with low-thrust pulsed plasma thrusters (PPTs)-whereupon each SWB executes a multi-day low-thrust finite bum around perihelion, lowering aphelion such that each achieves an elliptical phasing orbit of different orbital period from its companions. The resulting differences in angular rates of motion cause the spacecraft to separate. While the lead SWB achieves the mission orbit following an insertion burn at its second perihelion passage, the remaining SWBs must complete several revolutions in their respective phasing orbits to establish them in the mission orbit with the desired longitudinal spacing. The complete configuration for a 14 SWB scenario using a single mothercraft is achieved in about 8 years, and the spacing remains stable for at least a further 6 years. Flight operations can be simplified, and mission risk reduced, by employing two mothercraft instead of one. In this scenario: the

  14. Optimization and Annual Average Power Predictions of a Backward Bent Duct Buoy Oscillating Water Column Device Using the Wells Turbine.

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Christopher S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bull, Diana L [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Willits, Steven M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Fontaine, Arnold A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2014-08-01

    This Technical Report presents work completed by The Applied Research Laboratory at The Pennsylvania State University, in conjunction with Sandia National Labs, on the optimization of the power conversion chain (PCC) design to maximize the Average Annual Electric Power (AAEP) output of an Oscillating Water Column (OWC) device. The design consists of two independent stages. First, the design of a floating OWC, a Backward Bent Duct Buoy (BBDB), and second the design of the PCC. The pneumatic power output of the BBDB in random waves is optimized through the use of a hydrodynamically coupled, linear, frequency-domain, performance model that links the oscillating structure to internal air-pressure fluctuations. The PCC optimization is centered on the selection and sizing of a Wells Turbine and electric power generation equipment. The optimization of the PCC involves the following variables: the type of Wells Turbine (fixed or variable pitched, with and without guide vanes), the radius of the turbine, the optimal vent pressure, the sizing of the power electronics, and number of turbines. Also included in this Technical Report are further details on how rotor thrust and torque are estimated, along with further details on the type of variable frequency drive selected.

  15. Indian Ocean surface winds from NCMRWF analysis as compared to QuikSCAT and moored buoy winds

    Indian Academy of Sciences (India)

    B N Goswami; E N Rajagopal

    2003-03-01

    The quality of the surface wind analysis at the National Centre for Medium Range Weather Forecasts (NCMRWF), New Delhi over the tropical Indian Ocean and its improvement in 2001 are examined by comparing it with in situ buoy measurements and satellite derived surface winds from NASA QuikSCAT satellite (QSCT) during 1999, 2000 and 2001. The NCMRWF surface winds su ered from easterly bias of 1.0-1.5 ms-1 in the equatorial Indian Ocean (IO) and northerly bias of 2.0-3.0 ms-1 in the south equatorial IO during 1999 and 2000 compared to QSCT winds. The amplitude of daily variability was also underestimated compared to that in QSCT. In particular, the amplitude of daily variability of NCMRWF winds in the eastern equatorial IO was only about 60% of that of QSCT during 1999 and 2000. The NCMRWF surface winds during 2001 have significantly improved with the bias of the mean analyzed winds considerably reduced everywhere bringing it to within 0.5 ms-1 of QSCT winds in the equatorial IO. The amplitude and phase of daily and intraseasonal variability are very close to that in QSCT almost everywhere during 2001. It is shown that the weakness in the surface wind analysis during 1999 and 2000 and its improvement in 2001 are related to the weakness in simulation of precipitation by the forecast model in the equatorial IO and its improvement in 2001.

  16. Wave Energy Estimation by Using A Statistical Analysis and Wave Buoy Data near the Southern Caspian Sea

    Institute of Scientific and Technical Information of China (English)

    A.R.Zamani; M.A.Badri

    2015-01-01

    Statistical analysis was done on simultaneous wave and wind using data recorded by discus-shape wave buoy. The area is located in the southern Caspian Sea near the Anzali Port. Recorded wave data were obtained through directional spectrum wave analysis. Recorded wind direction and wind speed were obtained through the related time series as well. For 12-month measurements (May 25 2007-2008), statistical calculations were done to specify the value of nonlinear auto-correlation of wave and wind using the probability distribution function of wave characteristics and statistical analysis in various time periods. The paper also presents and analyzes the amount of wave energy for the area mentioned on the basis of available database. Analyses showed a suitable comparison between the amounts of wave energy in different seasons. As a result, the best period for the largest amount of wave energy was known. Results showed that in the research period, the mean wave and wind auto correlation were about three hours. Among the probability distribution functions, i.e Weibull, Normal, Lognormal and Rayleigh, “Weibull” had the best consistency with experimental distribution function shown in different diagrams for each season. Results also showed that the mean wave energy in the research period was about 49.88 kW/m and the maximum density of wave energy was found in February and March, 2010.

  17. Development and Application of Wireless RF Remote Control Hydrological Buoy Throwing Device%无线射频遥控浮标投掷器的研制和应用

    Institute of Scientific and Technical Information of China (English)

    邢杰炜

    2012-01-01

    The traditional buoy thrower is hand-driven, with low efficiency, poor reliability. The wireless RF remote control hydrological buoy throwing device control the DC speed-down micro-moto by remote controlling buoy thrower's switch, The buoy hanging rod runs syn?chronously. When the pole float rotates from horizontal direction to the vertical direction, the buoy falls. More floats can be thrown with same operation method. Alternating current electromotor can provide power for float throwers that cause the device running effectively and reliably.%传统浮标投掷器采用手动刀割型式,效率低、可靠性较差.本文所述的无线射频遥控浮标投掷器,采用遥控浮标投掷器中的开关来控制直流减速电机运转,使浮标悬挂杆同步转动,当浮标悬挂杆由水平转动到垂直方向时,浮标在重力作用下掉落.依次操作,可以连续投放多个浮标.浮标投放设施的运行以交流电动机作为牵引动力,从而实现浮标法测流设施的高效、可靠运转.

  18. Design of Solar LED Anchor Light System on Marine Measurement Buoys%海洋测量浮标太阳能LED锚灯系统的设计

    Institute of Scientific and Technical Information of China (English)

    唐原广; 朱明垒

    2012-01-01

    The anchor lights on the buoy are always incandescent light source,which are power consumption and short life span. In order to improve the quality of anchor light and reduce the workload of manual maintenance and labor intensity .design a low power consumption and cost-effective solar LED anchor light used on marine measurement buoys. By the use of solar panels for charging,the system realizes the main function of solar battery power control,battery control,light-sensitive circuit control and LED anchor light control through the central controller. The circuit is simple and practical. LED anchor light is of good quality .glowing far and flashing effect is good .providing a reliable security guarantee for the buoy.%一直以来浮标上用的锚灯都以白炽灯为光源,但是白炽灯功耗大、寿命短.为进一步提高航标灯的质量,减轻工人维护劳动强度和工作量,设计了一种低功耗且性价比高的可用于海洋测量浮标的太阳能LED锚灯.该锚灯通过中央控制器实现太阳能电池电源控制、蓄电池充电控制、感光电路控制以及LED锚灯控制等主要功能,并利用太阳能电池板进行充电,电路简洁、实用.LED锚灯灯管质量好、发光射程远、闪烁效果良好、性能稳定,可以更好地为浮标提供可靠的安全保证.

  19. Surface and basal sea ice melt from autonomous buoy arrays during the 2014 sea ice retreat in the Beaufort/Chukchi Seas

    Science.gov (United States)

    Maksym, T. L.; Wilkinson, J.; Hwang, P. B.

    2014-12-01

    As the Arctic continues its transition to a seasonal ice cover, the nature and role of the processes driving sea ice retreat are expected to change. Key questions revolve around how the coupling between dynamics and thermodynamic processes and potential changes in the role of melt ponds contribute to an accelerated seasonal ice retreat. To address these issues, 44 autonomous platforms were deployed in four arrays in the Beaufort Sea in March, 2014, with an additional array deployed in August in the Chukchi Sea to monitor the evolution of ice conditions during the seasonal sea ice retreat. Each "5-dice" array included four or five co-sited ice mass balance buoys (IMB) and wave buoys with digital cameras, and one automatic weather station (AWS) at the array center. The sensors on these buoys, combined with satellite imagery monitoring the large-scale evolution of the ice cover, provide a near-complete history of the processes involved in the seasonal melt of sea ice. We present a preliminary analysis of the contributions of several key processes to the seasonal ice decay. The evolution of surface ponding was observed at several sites with differing ice types and surface morphologies. The records of surface melt and ice thickness demonstrate a key role of ice type in driving the evolution of the ice cover. Analysis of the surface forcing and estimates of solar energy partitioning between the surface and upper ocean is compared to the surface and basal mass balance from the IMBs. The role of ice divergence and deformation in driving sea ice decay - in particular its role in accelerating thermodynamic melt processes - is discussed.

  20. Resesrch of Data Fusion Based on VectorBuoy%矢量浮标测量数据融合处理方法研究

    Institute of Scientific and Technical Information of China (English)

    马锦垠; 薛飞; 吕海涛

    2016-01-01

    研究了矢量浮标测量数据的融合算法及其在水下目标定位中的应用,提出了一种基于软决策融合的矢量浮标融合算法,结合矢量浮标式水下目标定位系统应用情况,给出了融合系统检测性能的计算机仿真结果,表明采用数据融合算法后可大幅度提高水下目标的定位精度。%Data fusion of vector buoy and application for underwater target positioning system were studied, and a data fusion of vector buoy based on soft decision was designed.Computer simulation results of the fusion system detection performance were given combined with application of underwater target positioning system,which shows that after the data fusion algorithm using can greatly improve the positioning accuracy of underwater targets.

  1. Proactive managers buoy satisfaction.

    Science.gov (United States)

    2010-10-01

    The ED leaders at St. Clair Hospital in Pittsburgh, PA, say that"managing by walking around"was one of the keys to their earning a ranking from Press Ganey as the no. 1 ED in patient satisfaction for EDs with more than 50,000 annual visits. The director selects and talks with random patients, following up on their care and making sure they're satisfied. Staff members are asked specific questions based on the Press Ganey priority indices. If there are patient complaints about a staff member, confidential meetings are held to discuss ways to improve.

  2. Lateral Buoys - USACE IENC

    Data.gov (United States)

    Department of Homeland Security — These inland electronic navigation charts (IENCs) were developed from available data used in maintenance of navigation channels. Users of these IENCs should be aware...

  3. Evaluation of HY-2A Scatterometer Wind Vectors Using Data from Buoys, ERA-Interim and ASCAT during 2012–2014

    Directory of Open Access Journals (Sweden)

    Jianyong Xing

    2016-05-01

    Full Text Available The first Chinese operational Ku-band scatterometer on board Haiyang-2A (HY-2A, launched in August 2011, is designed for monitoring the global ocean surface wind. This study estimates the quality of the near-real-time (NRT retrieval wind speed and wind direction from the HY-2A scatterometer for 36 months from 2012 to 2014. We employed three types of sea-surface wind data from oceanic moored buoys operated by the National Data Buoy Center (NDBC and the Tropical Atmospheric Ocean project (TAO, the European Centre for Medium Range Weather Forecasting (ECMWF reanalysis data (ERA-Interim, and the advanced scatterometer (ASCAT to calculate the error statistics including mean bias, root mean square error (RMSE, and standard deviation. In addition, the rain effects on the retrieval winds were investigated using collocated Climate Prediction Center morphing method (CMORPH precipitation data. All data were collocated with the HY-2A scatterometer wind data for comparison. The quality performances of the HY-2A NRT wind vectors data (especially the wind speeds were satisfactory throughout the service period. The RMSEs of the HY-2A wind speeds relative to the NDBC, TAO, ERA-Interim, and ASCAT data were 1.94, 1.73, 2.25, and 1.62 m·s−1, respectively. The corresponding RMSEs of the wind direction were 46.63°, 43.11°, 39.93°, and 47.47°, respectively. The HY-2A scatterometer overestimated low wind speeds, especially under rainy conditions. Rain exerted a diminishing effect on the wind speed retrievals with increasing wind speed, but its effect on wind direction was robust at low and moderate wind speeds. Relative to the TAO buoy data, the RMSEs without rain effect were reduced to 1.2 m·s−1 and 39.68° for the wind speed direction, respectively, regardless of wind speed. By investigating the objective laws between rain and the retrieval winds from HY-2A, we could improve the quality of wind retrievals through future studies.

  4. Comparisons between buoy-observed, satellite-derived, and modeled surface shortwave flux over the subtropical North Atlantic during the Subduction Experiment

    Energy Technology Data Exchange (ETDEWEB)

    Waliser, Duane E. [Institute for Terrestrial and Planetary Atmospheres, State University of New York, Stony Brook (United States); Weller, Robert A. [Woods Hole Oceanographic Institution, Woods Hole, Massachusetts (United States); Cess, Robert D. [Institute for Terrestrial and Planetary Atmospheres, State University of New York, Stony Brook (United States)

    1999-12-27

    Two years of surface shortwave flux data, from five buoys in the subtropical North Atlantic Ocean during the Subduction Experiment, were used to examine shortwave absorption in the atmosphere, and its partitioning between the clear and cloudy sky. Robust methods were used to isolate the clear-sky shortwave observations so that they could be directly compared to values derived using a single-column version of the National Center for Atmospheric Research Community Climate Model radiation code. The model-derived values agreed with the observations to within 0.5% mean relative error. Additional analysis showed that the model-data clear-sky surface shortwave differences showed no systematic relationship with respect to column water vapor amount. These results indicate that clear-sky absorption of shortwave radiation appears to be well modeled by current theory. Model-derived clear-sky surface shortwave values were combined with the observed (all-sky) values to determine the surface shortwave cloud forcing. The mean of these series were combined with 5-year mean Earth Radiation Budget Experiment derived top of the atmosphere (TOA) cloud forcing values to estimate the surface to TOA cloud forcing ratio. The resulting values range between 1.25 and 1.59. These values, along with the agreement between modeled and observed clear-sky surface shortwave, support the suggestion that our current theoretical radiative transfer models do not properly account for the amount of shortwave energy absorbed by the cloudy atmosphere. Mean values from the 2-year shortwave flux time series were compared to mean values from two climatologies derived from bulk parameterizations that utilize ship-based cloud reports. These comparisons show that the Oberhuber climatology underestimates the surface shortwave flux by {approx}20% ({approx}40 W m-2), while the Esbensen and Kushnir climatology underestimates the flux by {approx}4% ({approx}8 W m-2). The observed mean values were also compared to five

  5. Place-based Learning Collaboration: Promoting climate, ocean and data literacy by hosting a CO2 buoy from NOAA's Pacific Marine Environmental Lab at the Exploratorium

    Science.gov (United States)

    Miller, M. K.; Sabine, C. L.; Maenner, S.; Sutton, A.; Raleigh, C.

    2015-12-01

    The Exploratorium's new museum site on the San Francisco waterfront is a unique location for place-based learning about climate impacts on the ocean. With access to the Bay and surrounding environment, and strong partnerships with a national network of NOAA scientists and local researchers, the museum can serve as an educational node for a variety of atmosphere and ocean observing networks. The most visible and iconic instrument at the museum's Pier 15 location is a CO2 buoy from NOAA's Pacific Marine Environmental Lab in Seattle. Part of an international network of real-time ocean acidification sensors, the NOAA buoy streams temperature, salinity, atmospheric and surface water CO2 data from the Exploratorium location to NOAA. Near real-time and archived ocean and atmosphere carbon data is displayed in the museum's Bay Observatory along with other water quality, weather, and air quality conditions. Displaying both the instruments and the data they provide gives the public a better understanding of where climate data comes from, how scientists make meaning from time series data, and the value of long-term observation in understanding climate change and the ways that humans impact the environment. However, creating interactive exhibits from environmental data presents many challenges, including interpreting complex earth systems and biological and human interactions. What is the impact of the adjacent urban center and the estuary on the Bay's carbon content? How do we tease out long-term trends from the local variability? How do we connect the place-based learning to global processes and impacts? We'll address some of these challenges in the presentation and include the importance of collaborative partnerships between informal education institutions and researchers in place-based education about climate and environmental change.

  6. Modeling air/sea flux parameters in a coastal area: A comparative study of results from the TOGA COARE model and the NOAA Buoy model

    Science.gov (United States)

    Sopkin, Kristin; Mizak, Connie; Gilbert, Sherryl; Subramanian, Vembu; Luther, Mark; Poor, Noreen

    Because estuaries and coastal regions are particularly susceptible to nutrient over-enrichment due to their close proximity to source-rich regions, a goal of the BRACE study was to improve estimates of nitrogen air/sea transfer rates in the Tampa Bay Estuary. Our objective was to critically evaluate two air/sea gas exchange models to determine their efficacy for use in a coastal region, with the ultimate goal of improving nitrogen exchange estimates in Tampa Bay. We used meteorological data and oceanographic parameters collected hourly at an instrumented tower located in Middle Tampa Bay, Florida. The data was used to determine the friction velocity and the turbulent flux of heat and moisture across the air/sea interface and then compared with modeled parameters at the same offshore site. On average both models underpredicted sensible heat flux and there was considerable scatter in the data during stable conditions, indicating that nitrogen gas exchange rates may also be underestimated. Model improvement, however, was observed with friction velocity comparisons. Model inter-comparisons of sensible heat flux and friction velocity suggest excellent agreement between the TOGA COARE and the NOAA Buoy models, but model estimated heat transfer coefficients and latent heat fluxes did not agree as well. Based on our analysis, we conclude that both models are suitable for use in a coastal environment to estimate nitrogen air/sea gas exchange, although the NOAA Buoy model requires fewer meteorological inputs. However, if the purpose is to conduct more sophisticated microscale modeling of air/sea interactions, we recommend the TOGA COARE model.

  7. Temperature and pressure data collected using drifting buoy and profiling floats from the North Atlantic Ocean in part of the IDOE/POLYMODE (International Decade of Ocean Exploration / combination of USSR POLYGON project and US MODE) from 10 January 1975 to 31 May 1981 (NODC Accession 8700121)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature and pressure data were collected using drifting buoy and profiling floats from CHAIN, GILLISS, OCEANUS, and ENDEAVOR from the North Atlantic Ocean from...

  8. Temperature profile and current meter data collected using moored buoy and profiling floats in the North Atlantic Ocean as part of the International Decade of Ocean Exploration / Mid-Ocean Dynamics Experiment (IDOE/MODE) project from 03 October 1972 to 13 July 1973 (NODC Accession 7500548)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature, pressure, east-west current component, north-south current component, fluorescence, and other data were collected using moored buoy and profiling...

  9. Partial pressure (or fugacity) of carbon dioxide, salinity and other variables collected from Surface underway observations using Barometric pressure sensor, Carbon dioxide (CO2) gas analyzer and other instruments from the Drifting Buoy in the Indian Ocean, South Atlantic Ocean and others from 2001-11-20 to 2007-05-08 (NODC Accession 0117495)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NODC Accession 0117495 includes Surface underway, biological, chemical, meteorological and physical data collected from Drifting Buoy in the Indian Ocean, South...

  10. Temperature and upwelling / downwelling irradiance data from drifting buoy in the Southern Oceans as part of the Joint Global Ocean Flux Study/Southern Ocean (JGOFS/Southern Ocean) project, from 1994-12-25 to 1998-06-28 (NODC Accession 9900183)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature and upwelling / downwelling irradiance data were collected using drifting buoy in the Southern Oceans from December 25, 1994 to June 28, 1998. Data were...

  11. Dissolved inorganic carbon, total alkalinity, pH, and other variables collected from time series and profile observations using CTD, Niskin bottle,and other instruments near CenGOOS buoy off the coast of Mississippi in the Gulf of Mexico from 2012-10-15 to 2014-04-22 (NCEI Accession 0131199)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This archival package contains time series profile (discrete bottle) data that were collected at the GenGOOS buoy off the coast of Mississippi. The CenGOOS 3-m...

  12. Dissolved inorganic carbon, total alkalinity, pH, dissolved oxygen, and nutrients collected from profile, discrete sampling, and time series observations using CTD, Niskin bottle, and other instruments from R/V Gulf Challenger near a buoy off the coast of New Hampshire, U.S. in the Gulf of Maine from 2011-01-11 to 2015-11-18 (NCEI Accession 0142327)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — UNH, in conjunction with NOAA's Pacific Marine Environmental Laboratory, has been operating a buoy off the coast of New Hampshire since 2006. These data include...

  13. Measuring bioavailable metals using diffusive gradients in thin films (DGT) and transplanted seaweed (Fucus vesiculosus), blue mussels (Mytilus edulis) and sea snails (Littorina saxatilis) suspended from monitoring buoys near a former lead-zinc mine in West Greenland.

    Science.gov (United States)

    Søndergaard, Jens; Bach, Lis; Gustavson, Kim

    2014-01-15

    Measuring loads of bioavailable metals is important for environmental assessment near mines and other industrial sources. In this study, a setup of monitoring buoys was tested to assess loads of bioavailable metals near a former Pb-Zn mine in West Greenland using transplanted seaweed, mussels and sea snails. In addition, passive DGT samplers were installed. After a 9-day deployment period, concentrations of especially Pb, Zn and Fe in the species were all markedly elevated at the monitoring sites closest to the mine. Lead concentrations in all three species and the DGT-Pb results showed a significant linear correlation. Zinc and Fe concentrations were less correlated indicating that the mechanisms for Zn and Fe accumulation in the three species are more complex. The results show that there is still a significant load of metals from the mine and that such buoys can be an adequate method to assess present loads of bioavailable metals.

  14. Processing System of 3-meter-buoy U Disk Data%3m浮标U盘数据处理系统

    Institute of Scientific and Technical Information of China (English)

    张超; 唐明辰

    2015-01-01

    As an important part of the marine automatic monitoring system,the 3-meter data buoy plays an important role in the ocean condition monitoring,marine meteorological forecast and marine environmental protection. As U disk of storing buoy raw data,in which stores the original sampling data of the various hydrological and meteorological elements,are important materials for study of marine fea-tures and data statistics. In order to realize the visualization processing and analysis of buoy U data,design and implement the system. The application development is using C programming language based on the powerful Visual Studio 2008 alongside with using the Access 2003 and ADO database technology to store and process the data has been caught. Furthermore,using the BCG interface library makes the user interface more optimized and data more visible. The software can not only create the visual text documents,but also connect to the database to query and display the hydrometeorological parameters,due to the advantage of Visual Studio 2008,which can read and gener-ate data in Office Excel form. The system uses MATLAB in advantages on mathematical graphics,to plot the hydrometeorological graph. After testing and debugging,the system can successfully and stably read and analyze the data from the USB drive,plot the data and gener-ate the proper Excel files,which are easy to be visualized and read by the users,as expected. All these interfaces and visualizations are done by using hybrid programming method.%直径为3m的海洋资料浮标作为海洋自动监测系统的重要环节,在海况监测、海洋气象预报、海洋环境保护等方面发挥着重要作用。作为存储浮标原始数据的U盘存储器,其中存储了各个水文、气象要素的原始采样数据,是研究海洋特性和数据统计的重要资料。为了实现对浮标U盘中数据的可视化处理和分析,设计和实现了该系统。系统设计采用功能强大的Visual Studio 2008

  15. Comparison of AVHRR and ECMWF ERA-Interim data with buoy observational data for sea surface temperature over the Southern Coast of the Caspian Sea

    Science.gov (United States)

    Ghafarian, Parvin; Pegahfar, Nafiseh

    2016-07-01

    Sea surface temperature plays an important role in formation or intensification of many atmospheric phenomena such as tropical storms, lake-effect snow and sea breeze. Also, this variable is one of the input data in atmospheric, climate and oceanic models and also used climate change interpretation. According to the sparse location of observational stations over the ocean basins and seas, so satellite products can play an important role over such areas. The southern coast of the Caspian Sea (CS) is a prone area to experience some extreme challenging events forming due to sea surface temperature (SST) variation. In this research, SST data obtained by the AVHRR (Advanced Very High Resolution Radiometer) and those modeled by ECMWF data have been compared with observational data from buoy instrument. The horizontal resolution of AVHRR data is 0.125 degree, while that is 0.75 degree for ECMWF. The comparison process has been done in various seasons especially for some stormy days in winter and spring led to the lake-effect snow and waterspout. Analysis has been done applying nearest-neighbor interpolation and statistical methods. Our findings indicated that SST measured by AVHRR, comparing with ECMWF data, is more close to the observational data.

  16. 浅析系船浮筒锚链的静力计算问题%Discussion on Static Calculation of Mooring Buoy Anchor Chain

    Institute of Scientific and Technical Information of China (English)

    杨长义; 陈玺文

    2012-01-01

    Static calculation method is used to research suspended chain of buoy mooring system. Stress analysis is conducted respectively for single anchor chain system and multiple anchor chains system. A simplified calculation formula is proposed, which satisfy the requirements of single and multiple anchor chain systems. Then the simplified formula is verified based on the project example, which shall provide the reference for stress analysis and calculation of the similar projects.%采用静力计算方法对浮筒系泊系统的悬链进行研究,针对单锚链和多锚链系统进行受力分析,提出适用于单锚链和多锚链的简化计算公式,并根据实际工程案例进行简化计算公式的验证,可为类似工程的受力分析和计算提供参考.

  17. Third Field Test of Satellite-Tracked Surface Drifting Buoys for Simulating the Movement of Spilled Oil on the Sea Surface. Cruise Report

    Energy Technology Data Exchange (ETDEWEB)

    Reed, M.

    1995-12-18

    This report describes experiments with drifting buoys as potential simulators of drifting oil spills. Two drifter types were deployed to test how well they could follow oil slicks. One was a sphere of diameter 30 cm, the other was a flattened spheroid of 37 cm horizontal diameter and 20 cm vertical diameter. Both were equipped with ARGOS transmitters, and were ballasted to float at their equators. A third type, the CODE drifter, was deployed to track the motion of water in the top meter of the water column. The CODE drifters consisted of a central vertical cylinder one meter long, four inch diameter, with four vertical sails radiating at right angles to the central shaft. The spheres and the spheroids followed the surface oil movement very well. The movement of the thick portion of the drifting oil should therefore be very well represented by the mean ARGOS trajectories. The CODE drifters proved very useful as markers for the dispersed and dissolved hydrocarbon cloud, and should become a standard part of the sampling procedures. The drifters would be much more useful in real-time spill situations if they could use GPS-VHF for real-time mapping. The track evaluations were done by the U.S. Minerals Management Service. 13 refs., 2 figs., 1 table

  18. Numerical simulation and experimental analysis for a Risers Uphold Sub-Surface Buoy (BSR); Simulacao numerica e ensaio experimental da Boia de Sub-superficie de Suporte de Risers - BSSR

    Energy Technology Data Exchange (ETDEWEB)

    Araujo, Jairo B. de; Almeida, Jose Carlos L. de [PETROBRAS, Rio de Janeiro, RJ (Brazil); Rangel, Marcos; Fernandes, Antonio C.; Santos, Melquisedec F. dos; Sales Junior, Joel Sena [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia (COPPE)

    2004-07-01

    This paper presents results, numeric and experimental, due to installation operation of a Risers Uphold Sub-Surface Buoy, (BSR). This kind of installation developed by PETROBRAS is unique in the world. The work of BSR installation was based on a numeric pre analysis to verify the system and determine the main parameters to be experimentally verified. The second phase of the work was the experimental analysis in a deep water ocean basin. s. The work describes the BSR and their main accessories, the experimental environment and the model constructed in aluminum in a 1:12 scale and the main results. (author)

  19. 基于BGAN的大型海洋浮标岸站接收系统设计%Design of large marine buoy shore station data receiving system based on the BGAN

    Institute of Scientific and Technical Information of China (English)

    王朋朋; 赵士伟; 孙庆国; 刘咏; 杨健; 陈文广

    2014-01-01

    设计基于BGAN的大型海洋浮标岸站接收系统,主要实现与浮标系统的通讯、采集数据的实时显示、存储、转发和部分数据的分析功能,以及对系统通讯参数、运行参数进行远程控制功能。该系统主要基于客户端/服务器模式,采用Visual C++语言,通过CSocket网络编程方法和多线程技术,利用高速海事卫星实现基于TCP/IP协议的高速网络通信,解决大型浮标快速传输大容量数据的问题。该系统已经完成编写和测试,最终能够接收声阵列数据、声指纹数据和浮标状态数据,并预留开发了气象、水文要素数据接口,能够根据用户需求自行调整,达到项目设计要求。%A large marine buoy shore station data receiving system were founded based on the BGAN to realize the communication to the buoy system, data real-time display, storage, transmission and data analysis function, and the system communication parameters, operation parameters for remote control function. Using VC++ language and TCP/IP protocol, based on a client/server model, through network programming method of CSocket and multi -threading technology, and high-speed maritime satellite, the system achieved large-capacity data network transmission between the buoy system and the shore station. The system has been tested,and was able to receive the acoustic array data, the acoustic fingerprint data and the buoy state data. Moreover,the system reserved the data interface of the meteorological and the hydrological,which could adjust by the user demand automatically,and finally it has met the design requirements of the project.

  20. 水上溢油应急装备跟踪定位浮标关键技术研究%Research on the key technology of tracking location buoy of the marine oil spill emergency equipment

    Institute of Scientific and Technical Information of China (English)

    杨瑞; 顾群; 王玉林; 夏启兵

    2014-01-01

    This paper introduces the oil spill damage and current situation of emergency response technology home and abroad, provides solutions on oil spill tracking location buoy technology aiming at solve the difficulty of marine oil spill tracking and locating. This paper suggests utilizing the platform of“Beidou”satellite to fulfill the all time tracking and monitoring function on oil spill. It is tested by sea trial that oil spill tracking and locating buoy is an effective tool for oil spill emergency response.%文中介绍了近年来国内外溢油事故危害及应急技术现状,针对当前海上溢油难以跟踪定位的难题,提出了溢油跟踪定位浮标技术解决方案,采用北斗卫星定位通信为平台,实现海上溢油的全过程、全天候的实时跟踪、监测功能,通过海上试验验证,溢油跟踪定位浮标为海上溢油事故应急快速反应提供了一种有力工具。

  1. Direct Drive Wave Energy Buoy

    Energy Technology Data Exchange (ETDEWEB)

    Rhinefrank, Kenneth [Columbia Power Technologies, Inc., Charlottesville, VA (United States); Lamb, Bradford [Columbia Power Technologies, Inc., Charlottesville, VA (United States); Prudell, Joseph [Columbia Power Technologies, Inc., Charlottesville, VA (United States); Hammagren, Erik [Columbia Power Technologies, Inc., Charlottesville, VA (United States); Lenee-Bluhm, Pukha [Columbia Power Technologies, Inc., Charlottesville, VA (United States)

    2016-08-22

    This Project aims to satisfy objectives of the DOE’s Water Power Program by completing a system detailed design (SDD) and other important activities in the first phase of a utility-scale grid-connected ocean wave energy demonstration. In early 2012, Columbia Power (CPwr) had determined that further cost and performance optimization was necessary in order to commercialize its StingRAY wave energy converter (WEC). CPwr’s progress toward commercialization, and the requisite technology development path, were focused on transitioning toward a commercial-scale demonstration. This path required significant investment to be successful, and the justification for this investment required improved annual energy production (AEP) and lower capital costs. Engineering solutions were developed to address these technical and cost challenges, incorporated into a proposal to the US Department of Energy (DOE), and then adapted to form the technical content and statement of project objectives of the resulting Project (DE-EE0005930). Through Project cost-sharing and technical collaboration between DOE and CPwr, and technical collaboration with Oregon State University (OSU), National Renewable Energy Lab (NREL) and other Project partners, we have demonstrated experimentally that these conceptual improvements have merit and made significant progress towards a certified WEC system design at a selected and contracted deployment site at the Wave Energy Test Site (WETS) at the Marine Corps Base in Oahu, HI (MCBH).

  2. Direct Drive Wave Energy Buoy

    Energy Technology Data Exchange (ETDEWEB)

    Rhinefrank, Kenneth E. [Columbia Power Technologies, Inc.; Lenee-Bluhm, Pukha [Columbia Power Technologies, Inc.; Prudell, Joseph H. [Columbia Power Technologies, Inc.; Schacher, Alphonse A. [Columbia Power Technologies, Inc.; Hammagren, Erik J. [Columbia Power Technologies, Inc.; Zhang, Zhe [Columbia Power Technologies, Inc.

    2013-07-29

    The most prudent path to a full-scale design, build and deployment of a wave energy conversion (WEC) system involves establishment of validated numerical models using physical experiments in a methodical scaling program. This Project provides essential additional rounds of wave tank testing at 1:33 scale and ocean/bay testing at a 1:7 scale, necessary to validate numerical modeling that is essential to a utility-scale WEC design and associated certification.

  3. Special Purpose Buoys - USACE IENC

    Data.gov (United States)

    Department of Homeland Security — These inland electronic Navigational charts (IENCs) were developed from available data used in maintenance of Navigation channels. Users of these IENCs should be...

  4. 3D location of node in underwater sensor networks based on buoy%基于浮标的3D水声传感器网络节点定位

    Institute of Scientific and Technical Information of China (English)

    吕长艳; 刘广钟

    2013-01-01

    The location of the node is the basis of the application of UWSN . In order to improve the node location accuracy and prolong the network life cycle , this paper proposes a localization scheme for underwater 3D acoustic sensor network , which uses surface buoy nodes as the reference nodes . The result shows that the scheme increases localization accuracy and reduces energy consumption .%节点位置的确定是水下无线传感器网络的应用基础。为了提高节点定位精度并延长网络生命周期,提出一种使用海面浮标节点作为参考节点的水下传感器网络节点定位算法。仿真结果表明该方法提高了节点定位的精度,并在一定程度上减少了能耗。

  5. 基于模糊整数规划的水质浮标光伏/蓄电池动力源配置优化%Collaborative optimization of photovoltaic/battery power source for water quality buoy based on fuzzy integer programming

    Institute of Scientific and Technical Information of China (English)

    张慧妍; 李爽; 于家斌; 王小艺; 许继平

    2015-01-01

    孤岛型可再生能源供电,是解决水质监测用浮标动力来源的有效途径之一。根据水质浮标系统的特点,综合系统的经济性与环境条件,协同浮标本体成本及浮力、容积、天气因素等约束条件,构建了水质浮标动力源用光伏/蓄电池优化模型。针对制造过程中约束条件与预期值可能出现偏差这一实际问题,提出采用模糊整数规划算法进行求解,实现优化配置光伏/蓄电池动力源的目的。最后,提出对最大连续阴雨天数进行灵敏度分析,考察天气因素对所设计系统稳定性的影响。算例结果表明所提优化配置方法的有效性与可靠性,该方法不仅能够给出综合最优的动力源配置方案,还有利于结合安置地的环境条件,尽量避免主观设定关键参数,辅助水质监测用设备的高效研究与应用。%Renewable stand-alone energy power generation system is one of the effective ways which solve the problem of electric power supply for water quality monitoring buoy. Due to its unique application background and operating characteristics, there are still some problems to be considered and solved in the current design. In our work, the first step was to build a construction cost optimization model for PV-battery energy power with the constraints of the cost and dimension parameters and operating environments. That was, the model comprehensively and synergistically constructed an economical and reliable independent power supply model for water monitoring buoy under 5 conditions of buoy ontology cost, buoyancy, volume and weather etc. Furthermore, it was also vital to find the solutions of this model for getting the optimal design parameters of the renewable stand-alone energy power source for the water monitoring buoy. Firstly, the maximum continuous rainy days in the operating location was set by an RBF (radial basis function)neural network method. The 3 inputs were light intensity

  6. The Words That Buoy the European Impulse.

    Science.gov (United States)

    Hogenraad, Robert; Tousignant, Nathalie; Castano, Emanuele; Bestgen, Yves; Dumoulin, Michel

    With a view on analyzing the deeper trends in the European discourse that will shape the European Union's (EU's) future, a study examined 121 speeches made by EU political leaders over the period 1985-1997 and concorded and statisticized which words were used, how often, where, and when with the help of a computer-aided content analysis engine.…

  7. Member states buoy up beleagured EMBL

    CERN Multimedia

    Balter, M

    1999-01-01

    EMBL's governing council, made up of delegates from the lab's 16 member countries, agreed in principle to meet the costs of a multimillion-dollar pay claim, the result of a recent ruling by the ILO in Geneva (1 page).

  8. Worldwide Buoy Technology Survey. Volume 1. Report

    Science.gov (United States)

    1991-02-01

    Marine et de la Belgium Navigation Interieure Chile Direccion General Valparaiso, Capt. Estanislau Territorio Maritimo Chile Sabeckis Arre Y Marina...Sumary : Appendix A, Section A.3.2 2.4.3 ChiLe The ’Direccion General Territorio Kariziso y Marina Mercante* is responsible for aids to navigation in Chile...John C. Daidola i A.3.2 2 SINMARY NOTES FROM INTERVIEW DIRECCION GENERAL TERRITORIO MARITIMO Y MARINA MERCANTE VALPARAISO, CHILE PERSON INTERVIEWED

  9. Sea ice temperature and mass balance measurements from ice mass-balance buoy in the central Arctic Ocean%海水物质平衡浮标对北冰洋中心区海冰温度与物质平衡的观测

    Institute of Scientific and Technical Information of China (English)

    李娜; 刘骥平; 张占海; 崔琳; 雷瑞波

    2011-01-01

    利用中国第3次北极科学考察所布放海冰物质平衡浮标(Ice Mass-Balance buoy,IMB)的观测数据,分析了北冰洋中心区多年冰2008年8月-2009年7月温度与物质平衡的变化特征.结果表明,冰温廓线呈现明显的季节变化,秋季降温过程从海冰表面开始向冰体内部传播.海冰底部的生长/消融率受海水温度控制,随水温的降低,在2月初达到的最大值为1.7 cm/d;在2008年10月中旬至2009年6月下旬为海冰的生长期内,海冰底部平均生长率为0.6 cm/d,海冰底部厚度增长量为160.3 cm;海冰底部的消融较海冰表面约有1个月的滞后.分析海面风场对海冰漂移的影响显示,海冰漂移速率约为风速的2.13%.%As the integrator of both the surface heat budget and the ocean heat flux, the mass balance of sea ice is a key climate-change indicator.A set of IMB (Ice Mass-balance Buoy) was deployed in the central Arctic Ocean during the 3rd arctic research expedition of China.Analysis of 11 months'data from August 2008 to July 2009 shows that aseasonal cycle is obvious on the temperature of sea ice.With the air temperature decreases, a cold front propagates down through the ice in the fall.The growth/ablation rate of sea ice bottom is mainly controled by water temperature below, and reaches its maximum 1.7 cm/d in the early February.Growth season of sea ice bottom lasts from the middle October in 2008 to the end June in 2009,with an average bottom growth rate of 0.6 cm/d and total sea ice growth of 160.3 cm.Bottom melting begins in the early July, being one-month lag when comparing with surface melting.Correlation analysis between the daily ice drift and the 10m wind gives a correlation coefficient of 0.14(99% significance), ice moves at 2.13% of the wind speed.

  10. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Relative Humidity

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Relative Humidity data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  11. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Relative Humidity

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly Relative Humidity data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  12. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Relative Humidity

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Relative Humidity data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  13. Development of the Sensor for Environmental Assessment (SEA Buoy)

    Science.gov (United States)

    2014-01-01

    loss, monostatic and bistatic reverberation, and temperature versus depth profiles of a predefined ocean area to better predict acoustic detection...in the effective use of active and passive acoustics in Air ASW. 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT SAR

  14. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Temperature

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Temperature data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean, http://www.pmel.noaa.gov/tao/rama/),...

  15. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Salinity

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Salinity data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean, http://www.pmel.noaa.gov/tao/rama/), and...

  16. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Wind

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly Wind data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean, http://www.pmel.noaa.gov/tao/rama/), and...

  17. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Precipitation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly Precipitation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  18. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Position

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly Position data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean, http://www.pmel.noaa.gov/tao/rama/),...

  19. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Temperature

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Temperature data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  20. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Air Temperature

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Air Temperature data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  1. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Salinity

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Salinity data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean, http://www.pmel.noaa.gov/tao/rama/), and...

  2. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Position

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Position data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean, http://www.pmel.noaa.gov/tao/rama/),...

  3. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Precipitation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Precipitation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  4. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Precipitation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Precipitation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  5. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Heat Content

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Heat Content data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  6. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Temperature

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Temperature data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean, http://www.pmel.noaa.gov/tao/rama/),...

  7. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Dynamic Height

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly Dynamic Height data (a measure of the elevation of the sea level, calculated by integrating the specific volume anomaly of the sea water...

  8. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Longwave Radiation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Incoming Longwave Radiation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  9. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Salinity

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Salinity data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean, http://www.pmel.noaa.gov/tao/rama/),...

  10. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Position

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Position data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean, http://www.pmel.noaa.gov/tao/rama/), and...

  11. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Currents

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Currents data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean, http://www.pmel.noaa.gov/tao/rama/),...

  12. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, ADCP

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Acoustic Doppler Current Profiler (ADCP) water currents data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA...

  13. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, ADCP

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Acoustic Doppler Current Profiler (ADCP) water currents data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian...

  14. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Longwave Radiation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Incoming Longwave Radiation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  15. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Heat Content

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Heat Content data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean, http://www.pmel.noaa.gov/tao/rama/),...

  16. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Air Temperature

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Air Temperature data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  17. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Wind Stress

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Wind Stress data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  18. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Wind

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Wind data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean, http://www.pmel.noaa.gov/tao/rama/), and...

  19. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Dynamic Height

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Dynamic Height data (a measure of the elevation of the sea level, calculated by integrating the specific volume anomaly of the sea water...

  20. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Wind

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Wind data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean, http://www.pmel.noaa.gov/tao/rama/), and...

  1. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Longwave Radiation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly Incoming Longwave Radiation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  2. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Buoyancy Flux

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Buoyancy Flux data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  3. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Heat Content

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly Heat Content data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  4. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Buoyancy Flux

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Buoyancy Flux data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  5. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Wind Stress

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly Wind Stress data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  6. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Temperature

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly Temperature data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  7. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Currents

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Currents data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean, http://www.pmel.noaa.gov/tao/rama/), and...

  8. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Currents

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Currents data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean, http://www.pmel.noaa.gov/tao/rama/), and...

  9. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Evaporation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly Evaporation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  10. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Evaporation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Evaporation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean, http://www.pmel.noaa.gov/tao/rama/),...

  11. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Evaporation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Evaporation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean, http://www.pmel.noaa.gov/tao/rama/),...

  12. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Evaporation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Evaporation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  13. Small Flux Buoy for Characterizing Marine Surface Layers

    Science.gov (United States)

    2013-06-01

    wind direction or speed. They are also frequently found in fetch-limited offshore coastal flow. Young developing waves are dominated by the growth...approximately 9 kg. Cables from the sensors are routed to the mast by an umbilical arrangement. The length of the cables is long enough to prevent...from the umbilical cable using a separate small float and a weight. Depths were selected within the first 50 cm of the water column for the purpose of

  14. Buoyed by Divestment Victories, Activists Protest CIA Recruiting.

    Science.gov (United States)

    Greene, Elizabeth

    1987-01-01

    Inspired by victories in the South African divestment movement and fueled by the Iran-Contra affair, student activists are intensifying the perennial crusade to ban Central Intelligence Agency (CIA) recruiters from campuses, but other students dislike the interference and the CIA says that job-seekers are increasing. (MSE)

  15. Gas vesicles in actinomycetes : old buoys in novel habitats?

    NARCIS (Netherlands)

    Keulen, Geertje van; Hopwood, David A.; Dijkhuizen, Lubbert; Sawers, R. Gary

    2005-01-01

    Gas vesicles are gas-filled prokaryotic organelles that function as flotation devices. This enables planktonic cyanobacteria and halophilic archaea to position themselves within the water column to make optimal use of light and nutrients. Few terrestrial microbes are known to contain gas vesicles. G

  16. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Wind

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Wind data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean, http://www.pmel.noaa.gov/tao/rama/), and...

  17. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Dynamic Height

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Dynamic Height data (a measure of the elevation of the sea level, calculated by integrating the specific volume anomaly of the sea water...

  18. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Precipitation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Precipitation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  19. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, ADCP

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly Acoustic Doppler Current Profiler (ADCP) water currents data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA...

  20. SpaceBuoy: A University Nanosat Space Weather Mission Solicitation

    Science.gov (United States)

    2010-05-17

    with Harvard Smithsonian’s Center for Astrophysics , NASA/Ames, and other institutions. Our very active (more than 30 flights in four years) high...in Montana and Oregon, public talks were given to pre- elementary school children and their parents, and several middle school groups across the

  1. Buoys and Springs - Building Connections Between Math and Physics

    Science.gov (United States)

    Tenhoff, Amanda C.; Gerenz, Adam J.; Jalkio, Jeffrey A.

    2016-12-01

    Students often tend to compartmentalize material learned in school. While we see this phenomenon within our own classes, it is even more apparent that students have difficulty making connections between their math and physics courses. We believe that hands-on experiments are particularly useful in helping students make these connections. In this paper we present several possible experiments that use buoyancy to help students grasp both the similarities between different forces and the physical interpretation of the integration and differentiation techniques learned in their math classes. These experiments can also be used to introduce computational methods and 3D printing.

  2. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, ADCP

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Acoustic Doppler Current Profiler (ADCP) water currents data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian...

  3. Stationary Tether Device for Buoy Apparatus and System for Using

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A rigid, neutrally buoyant hydrodynamicaly-faired tether and associated fastening hardware that loosely holds a bathymetric float at a predetermined distance from a...

  4. Direct Drive Wave Energy Buoy – 33rd scale experiment

    Energy Technology Data Exchange (ETDEWEB)

    Rhinefrank, Kenneth E. [Columbia Power Technologies, Inc.; Lenee-Bluhm, Pukha [Columbia Power Technologies, Inc.; Prudell, Joseph H. [Columbia Power Technologies, Inc.; Schacher, Alphonse A.; Hammagren, Erik J.; Zhang, Zhe [Columbia Power Technologies, Inc.

    2013-07-29

    Columbia Power Technologies (ColPwr) and Oregon State University (OSU) jointly conducted a series of tests in the Tsunami Wave Basin (TWB) at the O.H. Hinsdale Wave Research Laboratory (HWRL). These tests were run between November 2010 and February 2011. Models at 33rd scale representing Columbia Power’s Manta series Wave Energy Converter (WEC) were moored in configurations of one, three and five WEC arrays, with both regular waves and irregular seas generated. The primary research interest of ColPwr is the characterization of WEC response. The WEC response will be investigated with respect to power performance, range of motion and generator torque/speed statistics. The experimental results will be used to validate a numerical model. The primary research interests of OSU include an investigation into the effects of the WEC arrays on the near- and far-field wave propagation. This report focuses on the characterization of the response of a single WEC in isolation. To facilitate understanding of the commercial scale WEC, results will be presented as full scale equivalents.

  5. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Wind Stress

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Wind Stress data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean, http://www.pmel.noaa.gov/tao/rama/),...

  6. UpTempO Buoys for Understanding and Prediction

    Science.gov (United States)

    2012-09-30

    McLaughlin, S. Nishino, R. Pickart, B. Rabe, B. Rudels, I. Semiletov, U. Schauer, N. Shakhova, K. Shimada, V. Sokolov , M. Steele, J. Toole, T...Schauer, N. Shakhova, K. Shimada, V. Sokolov , M. Steele, J. Toole, T. Weingartner, W. Williams, R. Woodgate, M. Yamamoto-Kawai, and S. Zimmermann, NOAA Arctic Report Card: Update for 2012 (Ocean), in review, 2012.

  7. Instrumented Full Scale Tests of a Drifting Buoy and Drogue

    Science.gov (United States)

    1975-12-01

    of very high accuracy (better than 200 feet) owing to the phase-tracking system employed. Both an automatic Epsco and a Simrad/Internav Loran C system...from.the output of a Simrad/Internav LORAN C navi- gator. A similar Epsco system was also employed while coupled to a separate antenna. The Epsco unit gave

  8. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Position

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Position data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean, http://www.pmel.noaa.gov/tao/rama/), and...

  9. Moored surface buoy observations of the diurnal warm layer

    KAUST Repository

    Prytherch, J.

    2013-09-01

    An extensive data set is used to examine the dynamics of diurnal warming in the upper ocean. The data set comprises more than 4700 days of measurements at five sites in the tropics and subtropics, obtained from surface moorings equipped to make comprehensive meteorological, incoming solar and infrared radiation, and high-resolution subsurface temperature (and, in some cases, velocity) measurements. The observations, which include surface warmings of up to 3.4°C, are compared with a selection of existing models of the diurnal warm layer (DWL). A simple one-layer physical model is shown to give a reasonable estimate of both the magnitude of diurnal surface warming (model-observation correlation 0.88) and the structure and temporal evolution of the DWL. Novel observations of velocity shear obtained during 346 days at one site, incorporating high-resolution (1 m) upper ocean (5-15 m) acoustic Doppler current profile measurements, are also shown to be in reasonable agreement with estimates from the physical model (daily maximum shear model-observation correlation 0.77). Physics-based improvements to the one-layer model (incorporation of rotation and freshwater terms) are discussed, though they do not provide significant improvements against the observations reported here. The simplicity and limitations of the physical model are used to discuss DWL dynamics. The physical model is shown to give better model performance under the range of forcing conditions experienced across the five sites than the more empirical models. ©2013. American Geophysical Union. All Rights Reserved.

  10. NOAA marine environmental buoy data from the National Data Buoy Center for 2001-09 (NODC Accession 0000595)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Wind wave spectra and meteorological data were collected from the US East/West coasts, South Pacific, Gulf of Mexico, Great Lakes, and other locations. Data were...

  11. NOAA marine environmental buoy data from the National Data Buoy Center for 2002-02 (NODC Accession 0000634)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Wind wave spectra and meteorological data were collected from the US East/West coasts, South Pacific, Gulf of Mexico, Great Lakes and other locations. Data were...

  12. NOAA marine environmental buoy data from the National Data Buoy Center for 2001-08 (NODC Accession 0000588)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Wind wave spectra and meteorological data were collected from the US East/West coasts, South Pacific, Gulf of Mexico, Great Lakes and other locations. Data were...

  13. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Relative Humidity

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Relative Humidity data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  14. Assessment of wave modeling results with buoy and altimeter deep water waves for a summer monsoon

    Digital Repository Service at National Institute of Oceanography (India)

    Sudheesh, K.; Vethamony, P.; Babu, M.T.; Jayakumar, S.

    stream_size 63122 stream_content_type text/plain stream_name INCHOE_Proc_2004_1_184.pdf.txt stream_source_info INCHOE_Proc_2004_1_184.pdf.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 G49G56G52 G65G83... G83G69G83G83G77G69G78G84G32G79G70G32G87G65G86G69G32G77G79G68G69G76G73G78G71G32G82G69G83G85G76G84G83G32G87G73G84G72 G66G85G79G89G32G65G78G68G32G65G76G84G73G77G69G84G69G82G32G68G69G69G80G32G87G65G84G69G82G32G87G65G86G69G83G32G70G79G82G32G65 G83G85G77G...

  15. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Sea Surface Salinity

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Sea Surface Salinity data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  16. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Wind Stress

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Wind Stress data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean, http://www.pmel.noaa.gov/tao/rama/),...

  17. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Barometric (Air) Pressure

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly Barometric (Air) Pressure data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  18. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Net Longwave Radiation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Net Longwave Radiation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  19. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Net Longwave Radiation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Net Longwave Radiation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  20. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Heat Flux Due To Rain

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Heat Flux Due To Rain data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  1. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Latent Heat Flux

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Latent Heat Flux data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  2. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Sigma-Theta

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Sigma-Theta (Potential Density Anomaly) data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  3. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Downgoing Shortwave Radiation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Downgoing Shortwave Radiation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  4. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Potential Density Anomaly

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Potential Density Anomaly (sigma-theta) data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  5. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Sea Surface Temperature

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Sea Surface Temperature (SST) data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  6. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Sigma-Theta

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Sigma-Theta (Potential Density Anomaly) data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  7. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, 20C Isotherm Depth

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day 20C Isotherm Depth data (the depth at which the ocean temperature is 20C) from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/),...

  8. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Potential Density Anomaly

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Potential Density Anomaly (sigma-theta) data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  9. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Latent Heat Flux

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly Latent Heat Flux data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  10. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, 20C Isotherm Depth

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly 20C Isotherm Depth data (the depth at which the ocean temperature is 20C) from the TAO/TRITON (Pacific Ocean,...

  11. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Sigma-Theta

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Sigma-Theta (Potential Density Anomaly) data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  12. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Air Temperature

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Air Temperature data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  13. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Net Shortwave Radiation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly Net Shortwave Radiation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  14. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Latent Heat Flux

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Latent Heat Flux data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  15. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Buoyancy Flux

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Buoyancy Flux data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  16. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Net Longwave Radiation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly Net Longwave Radiation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  17. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Sea Surface Temperature

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Sea Surface Temperature (SST) data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  18. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Total Heat Flux

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly Total Heat Flux data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  19. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Total Heat Flux

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Total Heat Flux data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  20. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Heat Flux Due To Rain

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Heat Flux Due To Rain data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  1. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Barometric (Air) Pressure

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Barometric (Air) Pressure data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  2. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Sea Surface Salinity

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Sea Surface Salinity data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  3. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Downgoing Shortwave Radiation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly Downgoing Shortwave Radiation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  4. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Sigma-Theta

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly Sigma-Theta (Potential Density Anomaly) data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  5. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Total Heat Flux

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Total Heat Flux data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  6. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Downgoing Shortwave Radiation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Downgoing Shortwave Radiation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  7. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Barometric (Air) Pressure

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Barometric (Air) Pressure data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  8. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Barometric (Air) Pressure

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Barometric (Air) Pressure data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  9. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, 20C Isotherm Depth

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly 20C Isotherm Depth data (the depth at which the ocean temperature is 20C) from the TAO/TRITON (Pacific Ocean,...

  10. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Heat Flux Due To Rain

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly Heat Flux Due To Rain data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  11. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Net Shortwave Radiation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Net Shortwave Radiation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  12. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Net Shortwave Radiation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Net Shortwave Radiation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  13. NOAA Marine Environmental Buoy Data for September 2003 (NODC Accession 0001307)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Meteorological and wave data were collected using accelerometer, meteorological sensors, and thermistor casts in the Coastal Waters of Western U.S. and other seas....

  14. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Evaporation Minus Precipitation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Evaporation Minus Precipitation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  15. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Evaporation Minus Precipitation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Evaporation Minus Precipitation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  16. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Evaporation Minus Precipitation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Evaporation Minus Precipitation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  17. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Evaporation Minus Precipitation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly Evaporation Minus Precipitation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  18. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Latent Heat Flux

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Latent Heat Flux data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  19. Experimental Hydromechanical Performance Evaluation of a Submarine Towed Communications Buoy Model.

    Science.gov (United States)

    1976-04-01

    DISTRIRUTION STATEMENT (of the ebelract enfe-od In Block 20. If different from Report) IS. SUPPLEMENTARY NOTES 19. KEY WORDS (Continue. orn reverse ...tIdo if necessary and Identfify b" block number) Submarine Communications 0.ABSTRACT (Continue orn reverse side If neceseary and Identify by block number...Cable Angle Pendulo ’,s Potentiometer :L20 degrees ±t0.2 degrees Pitch Angle Pendulous f’otentiometer :05 degrees ±0.15 degrees Roll Angle Pendulous

  20. Buoyed on All Sides: A Network of Support Guides Teacher Leaders in High-Needs Schools

    Science.gov (United States)

    Suescun, Marisa; Romer, Toby; MacDonald, Elisa

    2012-01-01

    The idea of teacher leadership holds an immense and intuitive appeal. Most educators agree that teacher leaders are essential to fostering a climate of authentic and robust leadership and learning across a school. Teacher leadership is peer leading at its most authentic, demanding, and empowering. While the value of teacher leadership may be…

  1. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Downgoing Shortwave Radiation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Downgoing Shortwave Radiation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  2. Development of an Indian Ocean moored buoy array for climate studies

    Digital Repository Service at National Institute of Oceanography (India)

    McPhaden, M.J.; Kuroda, Y.; Murty, V.S.N.

    of measurements to societal benefit. Chief among the principles is the need to distributed data openly in a timely manner. There is a preference for communication of data in real time to make it available at climate analysis and prediction centers.... This is essential to demonstrate the value of IndOOS and capture the potential societal benefits. 1. Introduction The Indian Ocean is unique among the three tropical ocean basins in that it is blocked at 25°N by the Asian land mass. Seasonal heating over...

  3. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Sea Surface Salinity

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has monthly Sea Surface Salinity data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  4. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, 20C Isotherm Depth

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily 20C Isotherm Depth data (the depth at which the ocean temperature is 20C) from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/),...

  5. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Heat Flux Due To Rain

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Heat Flux Due To Rain data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  6. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Longwave Radiation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has 5-day Incoming Longwave Radiation data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  7. TAO/TRITON, RAMA, and PIRATA Buoys, Quarterly, Sensible Heat Flux

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has quarterly Sensible Heat Flux data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  8. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Sea Surface Temperature

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Sea Surface Temperature (SST) data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  9. The Velocity Field in the Northeast Atlantic from Satellite-Tracked Drifting Buoys

    Science.gov (United States)

    1993-09-01

    September 1993 Author: ’ý Paolo Giann Approved By: Jeffrey D. aduan , Thesis Advisor Curtis Collins, Second Reader Curtis Collins, Chairman...the drifter trajectories both to understand them as a source of noise to the observation of mean currents and in their own right as agents of

  10. Parametric estimation in the wave buoy analogy - an elaborated approach based on energy considerations

    DEFF Research Database (Denmark)

    Montazeri, Najmeh; Nielsen, Ulrik Dam

    2014-01-01

    the ship’s wave-induced responses based on different statistical inferences including parametric and non-parametric approaches. This paper considers a concept to improve the estimate obtained by the parametric method for sea state estimation. The idea is illustrated by an analysis made on full-scale...

  11. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Total Heat Flux

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Total Heat Flux data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  12. Rancang Bangun Maximum Power Point Tracking pada Panel Photovoltaic Berbasis Logika Fuzzy di Buoy Weather Station

    OpenAIRE

    Bayu Prima Juliansyah Putra; Aulia Siti Aisjah; Syamsul Arifin

    2013-01-01

    Salah satu aplikasi yang sering digunakan dalam bidang energi terbarukan adalah panel photovoltaic. Panel ini memiliki prinsip kerja berdasarkan efek photovoltaic dimana lempengan logam akan menghasilkan energi listrik apabila diberi intensitas cahaya. Untuk menghasilkan daya keluaran panel yang maksimal, maka diperlukan suatu algoritma yang biasa disebut Maximum Power Point Tracking (MPPT).MPPT yang diterapkan pada sistem photovoltaic berfungsi untuk mengatur nilai tegangan keluaran panel se...

  13. Software and Support Development for an Environmental Data Buoy System for Predicting Surf-Zone Characteristics

    Science.gov (United States)

    1981-02-28

    stable to one millivolt or less .i ith the system .error never exceeding this amount. ’ Also- during this time.’ period tdere were no failures or...system are already CMOS. However, those that are not all have a corresponding CMOS version, most of the time pin -for- pin interchangeable. These...calculations an improved breaker calculation can be made based upon the following: •F Rb=H Kf K K b Sfr s K .98 Kr [ Cos(@b) SK = tanh2• hL) I+ sth4T hi/L

  14. Description and Field Evaluation of the Broad-Band Underwater Recording Buoy System

    Science.gov (United States)

    2005-12-01

    expériences de transmission acoustique. Importance des résultats Une nouvelle capacité d’enregistrement acoustique sous-marin large bande a été produite...HMCS Ville de Quebec in Bedford Basin, Nova Scotia. These measurements were severely compromised by the fact that the ship was not able to

  15. Study of the directional spectrum of ocean waves using array, buoy and radar measurements

    Digital Repository Service at National Institute of Oceanography (India)

    Fernandes, A.A.

    . At the Pt. Mugu site of Esteva?s 5-gauge polygonal array, designed by Leon E. Borgman, swell of 16s and 8s was observed. Since Esteva?s array had five gauges,5C3 = 10 different combinations of gauge triads are possible giving 10 independent estimates of wave...

  16. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Potential Density Anomaly

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Potential Density Anomaly (sigma-theta) data from the TAO/TRITON (Pacific Ocean, http://www.pmel.noaa.gov/tao/), RAMA (Indian Ocean,...

  17. Arctic Ocean Drift Tracks from Ships, Buoys and Manned Research Stations, 1872-1973

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Thirty-four drift tracks in the Arctic Ocean pack ice are collected in a unified tabular data format, one file per track. Data are from drifting ships, manned...

  18. General Analysis of Directional Ocean Wave Data from Heave Pitch Roll Buoys

    Directory of Open Access Journals (Sweden)

    Donald M. Wiberg

    1984-04-01

    Full Text Available There are many practical applications of lattice form recursive linear least square algorithms (called lattices for short in signal processing, communications, and control systems. The goal of this tutorial is to help practicing engineers to decide if lattices are appropriate for their particular projects.

  19. Measurements of the Air-Sea Interface from an Instrumented Small Buoy

    Science.gov (United States)

    2011-09-01

    at three levels to characterize the vertical variation of the wind. The 3- cup anemometer sensor is a plug-in HOBO weather station wind sensor. It...this configuration, the anemometers are located at three levels together with the temperature and humidity sensors inside radiation shields 8 at...experiment that would allow them to measure simultaneously at the same location. The anemometers and the HOBO temperature and RH sensors were placed

  20. The Feasibility of Sodar Wind Profile Measurements from an Oceanographic Buoy

    Science.gov (United States)

    2006-09-01

    with cup anemometer measurements (Jorgenson et. al., 2004). The main difficulty in the CW approach is how to determine range. The ZephIR uses a...Doppler LIDAR – Comparison with Cup Anemometers at RISØ. Proc. European Wind Energy Conference, Delft, April 2004, pp. 1–6. Pierce, Allan D. (1981...misalignment of winds and currents. One way to improve the model in the future would be to equip ASIS with an anemometer , a downward-looking ADCP, and a GPS

  1. Temperature profile data from moored buoy, profiling floats, TAO buoy, and XBT casts in a world-wide distribution from 14 April 2000 to 20 February 2001 (NODC Accession 0000406)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profile data were collected from multiple ships from April 14, 2000 to February 20, 2001. Data were submitted by Marine Environmental Data Service (MEDS)...

  2. Temperature profile data from moored buoy, profiling floats, TAO buoy, and XBT casts in a world-wide distribution from 21 October 2000 to 31 January 2001 (NODC Accession 0000405)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profile data were collected from multiple ships from October 21, 2000 to January 31, 2001. Data were submitted by Marine Environmental Data Service...

  3. Drifting buoy data from SVP Drifting Argos Buoys, deployed by the NOAA Coral Reef Ecosystems Division (CRED) near Guam and the Commonwealth of the Northern Marianas Islands, 2003-2006 (NODC Accession 0067473)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data collection includes data from multiple SVP drifters deployed in the region of the Marianas Archipelago to assess ocean currents and sea surface...

  4. Buoy-Deployed Seeding: A New Low-Cost Technique for Restoration of Submerged Aquatic Vegetation From Seed

    Science.gov (United States)

    2006-04-01

    was developed to take advantage of the natural ability of mature reproductive shoots of eelgrass (Zostera marina ) to release seeds over a period of...suppliers. It is important to contact an aquaculture supplier to place an order for nets months prior to expected deployment. Failure to do so may...anchorage in exposed sites. The mesh size of the nets can be changed to accommodate plants with larger seeds than Z. marina (e.g., Posidonia). Other

  5. CRED SVP Drifting Buoy Argos_ID 24753 Data in American Samoa, 200307-200407 (NODC Accession 0067474)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CRED SVP drifter Argos_ID 24753 was deployed in the region of American Samoa to assess ocean currents and sea surface temperature. SVP drifter data files contain...

  6. Validation of High Frequency Radar Used in Ocean Surface Current Mapping via in-situ Drifting Buoys

    Science.gov (United States)

    2008-09-01

    research vessels, the R/V John Martin from Moss Landing Marine Laboratories and the R/V Mussel Point (Figure 6) from the Bodega Bay Marine Laboratory. The...radar observations of surface circulation off Bodega Bay (northern California, USA). J. Geophys. Res., 110, C10020, doi:10.1029/2005JC002959. Kim

  7. 77 FR 65816 - Safety Zone; Large Cruise Ships; Lower Mississippi River, Southwest Pass Sea Buoy to Mile Marker...

    Science.gov (United States)

    2012-10-31

    ... Security Management Directive 023-01 and Commandant Instruction M16475.lD, which guide the Coast Guard in... categorically excluded from further review under paragraph 34(g) of Figure 2-1 of the Commandant Instruction. An... those agreed upon arrangements. (ii) Moored vessels or vessels anchored in a designated anchorage...

  8. Directional wave and temperature data from six buoys at Diablo Canyon, CA, 1997-2002 (NODC Accession 0000761)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Coastal Data Information Program (CDIP) is an extensive network for monitoring waves along the coastlines of the United States, with a strong emphasis on our...

  9. A Hyperspectral Tethered Spectral Radiometer Buoy: Ocean Color Algorithm Development in Estuaries, Coastal Waters, and Marginal Seas

    Science.gov (United States)

    1998-09-30

    of seagrasses, seaweeds and sediments to the inversely modeled benthic reflectance signature. These models were tested against multispectral...sediment transport would significantly improve the state’s effectiveness with regards to point source and non-point source pollution, aquaculture

  10. Data from a directional waverider buoy off Waimea Bay, North Shore, Oahu during December 2001 - July 2004 (NODC Accession 0001626)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Coastal Data Information Program (CDIP) is an extensive network for monitoring waves along the coastlines of the United States, with a strong emphasis on our...

  11. Data from a directional waverider buoy off Kailua Bay, Windward Oahu during August 2000 - July 2004 (NODC Accession 0001660)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Coastal Data Information Program (CDIP) is an extensive network for monitoring waves along the coastlines of the United States, with a strong emphasis on our...

  12. Directional wave and temperature data from seven buoys at Harvest, CA, 1995-2002 (NODC Accession 0000766)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Coastal Data Information Program (CDIP) is an extensive network for monitoring waves along the coastlines of the United States, with a strong emphasis on our...

  13. Estimating the Underwater Diffuse Attenuation Coefficient with a Low-Cost Instrument: The KdUINO DIY Buoy

    Directory of Open Access Journals (Sweden)

    Raul Bardaji

    2016-03-01

    Full Text Available A critical parameter to assess the environmental status of water bodies is the transparency of the water, as it is strongly affected by different water quality related components (such as the presence of phytoplankton, organic matter and sediment concentrations. One parameter to assess the water transparency is the diffuse attenuation coefficient. However, the number of subsurface irradiance measurements obtained with conventional instrumentation is relatively low, due to instrument costs and the logistic requirements to provide regular and autonomous observations. In recent years, the citizen science concept has increased the number of environmental observations, both in time and space. The recent technological advances in embedded systems and sensors also enable volunteers (citizens to create their own devices (known as Do-It-Yourself or DIY technologies. In this paper, a DIY instrument to measure irradiance at different depths and automatically calculate the diffuse attenuation Kd coefficient is presented. The instrument, named KdUINO, is based on an encapsulated low-cost photonic sensor and Arduino (an open-hardware platform for the data acquisition. The whole instrument has been successfully operated and the data validated comparing the KdUINO measurements with the commercial instruments. Workshops have been organized with high school students to validate its feasibility.

  14. Estimating the Underwater Diffuse Attenuation Coefficient with a Low-Cost Instrument: The KdUINO DIY Buoy

    NARCIS (Netherlands)

    Bardaji, R.; Sánchez, A.-M.; Simon, C.; Wernand, M.R.; Piera, J.

    2016-01-01

    A critical parameter to assess the environmental status of water bodies is the transparency of the water, as it is strongly affected by different water quality related components (such as the presence of phytoplankton, organic matter and sediment concentrations). One parameter to assess the water tr

  15. Verification of Geosat sea surface topography in the Gulf Stream extension with surface drifting buoys and hydrographic measurements

    Science.gov (United States)

    Willebrand, J.; KäSe, R. H.; Stammer, D.; Hinrichsen, H.-H.; Krauss, W.

    1990-03-01

    Altimeter data from Geosat have been analyzed in the Gulf Stream extension area. Horizontal maps of the sea surface height anomaly relative to an annual mean for various 17-day intervals were constructed using an objective mapping procedure. The mean sea level was approximated by the dynamic topography from climatological hydrographic data. Geostrophic surface velocities derived from the composite maps (mean plus anomaly) are significantly correlated with surface drifter velocities observed during an oceanographie experiment in the spring of 1987. The drifter velocities contain much energy on scales less than 100 km which are not resolved in the altimetric maps. It is shown that the composite sea surface height also agrees well with ground verification from hydrographic data along sections in a triangle between the Azores, Newfoundland, and Bermuda, except in regions of high mean gradients.

  16. Optimizing observational networks combining gliders, moored buoys and FerryBox in the Bay of Biscay and English Channel

    Science.gov (United States)

    Charria, Guillaume; Lamouroux, Julien; De Mey, Pierre

    2016-10-01

    Designing optimal observation networks in coastal oceans remains one of the major challenges towards the implementation of future efficient Integrated Ocean Observing Systems to monitor the coastal environment. In the Bay of Biscay and the English Channel, the diversity of involved processes (e.g. tidally-driven circulation, plume dynamics) requires to adapt observing systems to the specific targeted environments. Also important is the requirement for those systems to sustain coastal applications. Two observational network design experiments have been implemented for the spring season in two regions: the Loire River plume (northern part of the Bay of Biscay) and the Western English Channel. The method used to perform these experiments is based on the ArM (Array Modes) formalism using an ensemble-based approach without data assimilation. The first experiment in the Loire River plume aims to explore different possible glider endurance lines combined with a fixed mooring to monitor temperature and salinity. Main results show an expected improvement when combining glider and mooring observations. The experiment also highlights that the chosen transect (along-shore and North-South, cross-shore) does not significantly impact the efficiency of the network. Nevertheless, the classification from the method results in slightly better performances for along-shore and North-South sections. In the Western English Channel, a tidally-driven circulation system, added value of using a glider below FerryBox temperature and salinity measurements has been assessed. FerryBox systems are characterised by a high frequency sampling rate crossing the region 2 to 3 times a day. This efficient sampling, as well as the specific vertical hydrological structure (which is homogeneous in many sub-regions of the domain), explains the fact that the added value of an associated glider transect is not significant. These experiments combining existing and future observing systems, as well as numerical ensemble simulations, highlight the key issue of monitoring the whole water column in and close to river plumes (using gliders for example) and the efficiency of the surface high frequency sampling from FerryBoxes in macrotidal regions.

  17. Survey of Technology with Possible Applications to United States Coast Guard Buoy Tenders. Volume 1. Technology Assessment.

    Science.gov (United States)

    1987-09-01

    performance. Zig - zag tests show SWATH ships have half the overshoot of conventional ships. At slow speeds, the widely separated propulsion units aid...Ii S2 2-13 C, Lb 0 00 2-14 ’rkpl I% -W N~ louw W ME ’ K’.MM w~~b Af’- w~t W pw -.J 1 W ’W SS U. C ’U . 2-15 Mill ll WRII9PqWWmWIK"-wPFll7TW W.F K...Evaluation of a Compound Cycle Engine for Shipboard Gensets," Report No. DTNSRDC-PASD-CR-1886. 6.19 Mills , R.G., "Innovative Technology on Steam

  18. CRED SVP Drifting Buoy Argos_ID 35648 Data Pago Pago, American Samoa, 200203-200204 (NODC Accession 0067474)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CRED SVP drifter Argos_ID 35648 was deployed in the region of American Samoa to assess ocean currents and sea surface temperature. SVP drifter data files contain...

  19. Sword, Shield and Buoys: A History of the NATO Sub-Committee on Oceanographic Research, 1959–19731

    Science.gov (United States)

    Turchetti, Simone

    2012-01-01

    In the late 1950s the North-Atlantic Treaty Organization (NATO) made a major effort to fund collaborative research between its member states. One of the first initiatives following the establishment of the alliance's Science Committee was the creation of a sub-group devoted to marine science: the Sub-committee on Oceanographic Research.This paper explores the history of this organization, charts its trajectory over the 13 years of its existence, and considers its activities in light of NATO's naval defence strategies. In particular it shows how the alliance's naval commands played a key role in the sub-committee's creation due to the importance of oceanographic research in the tracking of enemy submarines. The essay also scrutinizes the reasons behind the committee's dissolution, with a special focus on the changing landscape of scientific collaboration at NATO. The committee's fall maps onto a more profound shift in the alliance's research agenda, including the re-organization of defence research and the rise of environmentalism. PMID:23935209

  20. Sword, Shield and Buoys: A History of the NATO Sub-Committee on Oceanographic Research, 1959-1973.

    Science.gov (United States)

    Turchetti, Simone

    2012-08-01

    In the late 1950s the North-Atlantic Treaty Organization (NATO) made a major effort to fund collaborative research between its member states. One of the first initiatives following the establishment of the alliance's Science Committee was the creation of a sub-group devoted to marine science: the Sub-committee on Oceanographic Research.This paper explores the history of this organization, charts its trajectory over the 13 years of its existence, and considers its activities in light of NATO's naval defence strategies. In particular it shows how the alliance's naval commands played a key role in the sub-committee's creation due to the importance of oceanographic research in the tracking of enemy submarines. The essay also scrutinizes the reasons behind the committee's dissolution, with a special focus on the changing landscape of scientific collaboration at NATO. The committee's fall maps onto a more profound shift in the alliance's research agenda, including the re-organization of defence research and the rise of environmentalism.