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. 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...

  4. The autonomous acoustic buoy

    OpenAIRE

    Pellicer, Francisco; Reitsma, Robert; Agüera, Joaquín; Marinas, Alexandra

    2013-01-01

    The Acoustic Buoy is a project between the Laboratory of Applied Bioacoustics (LAB) and the Universitat Politècnica de Catalunya (UPC). In areas that the human activities produce high noise levels, such as oil exploration or construction, there is a need to monitor the environment for the presence of cetaceans. Another need is for fishing, to prevent endangered species from being killed. This can be done with an Autonomous Acoustic Buoy (AAB). Mooring or anchoring at to the seaflo...

  5. Buoy Dynamics in Subsurface Zones

    Directory of Open Access Journals (Sweden)

    Randy Guillen

    2009-01-01

    Full Text Available The objective of this paper is to find the tension acting on a line that anchors a buoy submerged just beneath the surface of the ocean. Since the problem statement only gives the geometric shapes and dimensions of the buoy, we must use calculus to find its volume and surface area through integration of the volumes and surfaces of revolution formed by the specific parts of the buoy along an axis. The volume and surface area determine the buoyancy force and force of gravity, the two forces acting on the buoy that affect the tension in the line. After calculating this data, we were able to conclude that the tension affecting the line would be approximately 78 kN if the buoy was made of 1% carbon steel with a thickness of 6.35 mm. This problem is useful in several engineering disciplines.

  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...

  7. Offshore Surveillance of Wave Buoys

    OpenAIRE

    Tyrberg, Simon

    2007-01-01

    To gain further knowledge about the motion of the wave buoys involved in the Islandsberg project for wave power, a surveillance system has been designed. The base for the system consists of a lattice tower to be placed on one of two islets southwest of Lysekil: Klammerskären. The distance from the islets to the wave energy research park and the wave buoys is between 150 and 300 meters. The tower will be 12 meters high and in it a network camera will be mounted, together with a small wind turb...

  8. 33 CFR 62.35 - Mooring buoys.

    Science.gov (United States)

    2010-07-01

    ... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false Mooring buoys. 62.35 Section 62.35 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY AIDS TO NAVIGATION UNITED STATES AIDS TO NAVIGATION SYSTEM The U.S. Aids to Navigation System § 62.35 Mooring buoys. Mooring Buoys are white with a blue horizontal...

  9. 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.

  10. 46 CFR 180.70 - Ring life buoys.

    Science.gov (United States)

    2010-10-01

    ... the ring life buoy. (3) Each floating waterlight installed after March 11, 1997, on a vessel carrying... 46 Shipping 7 2010-10-01 2010-10-01 false Ring life buoys. 180.70 Section 180.70 Shipping COAST...) LIFESAVING EQUIPMENT AND ARRANGEMENTS Ring Life Buoys and Life Jackets § 180.70 Ring life buoys. (a) A...

  11. 46 CFR 117.70 - Ring life buoys.

    Science.gov (United States)

    2010-10-01

    ... the body of the ring life buoy. (3) Each floating waterlight installed after March 11, 1997, on a... 46 Shipping 4 2010-10-01 2010-10-01 false Ring life buoys. 117.70 Section 117.70 Shipping COAST... Ring Life Buoys and Life Jackets § 117.70 Ring life buoys. (a) A vessel must have one or more ring...

  12. On the Optimization of Point Absorber Buoys

    Directory of Open Access Journals (Sweden)

    Linnea Sjökvist

    2014-05-01

    Full Text Available A point absorbing wave energy converter (WEC is a complicated dynamical system. A semi-submerged buoy drives a power take-off device (PTO, which acts as a linear or non-linear damper of the WEC system. The buoy motion depends on the buoy geometry and dimensions, the mass of the moving parts of the system and on the damping force from the generator. The electromagnetic damping in the generator depends on both the generator specifications, the connected load and the buoy velocity. In this paper a velocity ratio has been used to study how the geometric parameters buoy draft and radius, assuming constant generator damping coefficient, affects the motion and the energy absorption of a WEC. It have been concluded that an optimal buoy geometry can be identified for a specific generator damping. The simulated WEC performance have been compared with experimental values from two WECs with similar generators but different buoys. Conclusions have been drawn about their behaviour.

  13. Evaporation duct assessment from meteorological buoys

    Science.gov (United States)

    Hitney, Herbert V.

    2002-07-01

    The evaporation duct over the sea is usually assessed using bulk meteorological measurements. This paper investigates the utility of meteorological buoys as a source for these bulk measurements and compares evaporation duct assessments using two buoys in southern California waters separated by 128 km. A simple radio propagation experiment at 2.4 GHz between one of the buoys and the coast on an 18.2 km path is described. Observed propagation loss from this experiment is compared to modeled loss based on the meteorological measurements at each buoy. The purpose of this paper is to investigate radio propagation effects using established and accepted methods already described in the literature. Accordingly, no discussion of atmospheric surface layer meteorology affecting radio propagation is given.

  14. Anharmonic oscillations of a conical buoy

    CERN Document Server

    Oliveira, J Brochado; da Silva, J M Machado

    2011-01-01

    A study of the foating of a circular cone shaped buoy in an ideal fluid has revealed some new interesting results. Using reduced variables it is shown, that at a crossover value (3/4) of the ratio of the specific masses of the fluid and of the buoy, the anharmonicity of the oscillation is the highest and that, unexpectedly, above this crossover value the normalized period is constant.

  15. Buoy for linear wave energy converter

    Energy Technology Data Exchange (ETDEWEB)

    Gravraakmo, Halvar

    2011-07-01

    A wave energy converter (WEC) of point absorber type has been developed and tests have been conducted outside Lysekil. The project started in 2002 and linear permanent magnet generators together with a subsea substation and buoys of various geometric shapes have been built and tested. The system is based on a low number of mechanical moving parts and the power conversion from ocean waves to electricity maintaining the quality of the national grid is handled electrically, due to the long life span of electric components. Reliability is highly prioritized in this design. To monitor the test site, measurements of electric output are done on the generators and substation. Also measurements of acceleration in heave mode are done on the buoy itself together with measurements of force between the buoy and the generator. The measurements are transmitted through the public cellular network. Also a internet based camera is set up at the site to monitor the buoys of the WECs visually. The monitoring systems, both visual and quantitative have proven to work successfully. In order for a WEC to produce electricity at competitive prices, the generator must not be larger than necessary in order to save economically on production, transport and installation. However, the WEC must be dimensioned to withstand harsh sea states. High added mass will in some cases create harsh inertia forces on the generator and large inertia forces on the buoy which might shorten the life time of the system considerably. The magnitude of the unwanted forces can be reduced by taking account for added mass when choosing a buoy geometry. A toroidal buoy is found to have less added mass than a vertical cylindrical buoy with similar excitation force

  16. Sonar location system for freely floating buoys

    Science.gov (United States)

    Bird, I. G.

    1983-05-01

    A rf interrogated sonar location system for freely floating buoys is described. The location of an array of up to three buoys may be determined on an almost continuous basis within a radius of 500 m from a shipboard monitoring station. Location accuracy of typically ±0.5 m at 200-m range, low cost, and ease of operation are the major features of the system.

  17. Fluid Structure Interaction Analysis of Planar Buoy

    OpenAIRE

    Patel, Rakeshbhai; Hanif, Muhammad Adnan; Oad, Rajev Kumar

    2011-01-01

    Different types of wave energy convertors are being studied using the heave motion of floating bodies to generate electricity. In this thesis, we investigate the interaction of floating buoys from hydrodynamic point of view. The dynamic heave response of buoy under two different load cases and represented by single degree of freedom model is studied. The fluid-structure interactions based on 2-dimensional linear potential flow theory were modeled and simulated using finite element method. The...

  18. 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...

  19. 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...

  20. 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...

  1. 33 CFR 62.23 - Beacons and buoys.

    Science.gov (United States)

    2010-07-01

    ... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false Beacons and buoys. 62.23 Section... UNITED STATES AIDS TO NAVIGATION SYSTEM The U.S. Aids to Navigation System § 62.23 Beacons and buoys. (a... navigation. The primary components of the U.S. Aids to Navigation System are beacons and buoys. (b)...

  2. The Great Build-a-Buoy Challenge

    Science.gov (United States)

    Dickerson, Daniel; Hathcock, Stephanie; Stonier, Frank; Levin, Doug

    2012-01-01

    As Science, Technology, Engineering, and Mathematics (STEM) Education continues to become more visible in elementary school curricula, the need for activities that address STEM content is growing. Build-A-Buoy is one such activity. This activity was developed by Doug Levin in 2008 when he was an education coordinator for the NOAA Chesapeake Bay…

  3. CFD supported examination of buoy design for wave energy conversion

    Energy Technology Data Exchange (ETDEWEB)

    Yilmaz, Nadir; Trapp, Geoffrey E.; Gagan, Scott M.; Emmerich, Timothy R. [Department of Mechanical Engineering, New Mexico Institute of Mining and Technology (United States)], e-mail: nadir@nmt.edu, email: gtrapp@nmt.edu, email: sgag01@nmt.edu, email: temmeric@nmt.edu

    2011-07-01

    The work presented in this paper investigates an oscillating buoy power device (OD) as a potential wave energy converter. The wave interacts with the buoy, which is connected to a mechanical device which oscillates and converts spring force into mechanical power. For validation purposes, ellipsoidal buoy shapes of the five aspect ratios are used in this report as OD devices which are excited under the same wave conditions to validate the computational fluid dynamics (CFD) model against experimental data available in the literature. The analysis was performed using a Flow-3d CFD software package. Comparisons are made and results are presented based on buoy displacements which can be related to energy produced by the buoys. The aspect ratio approaching 1:1:1 (sphere) is found to produce the maximum displacement and consequently the highest possible energy conversion. The paper also discusses whether a flat circular plate shape buoy would capture 50% of the possible energy by comparison with the spherical buoy.

  4. Model Predictive Control of Buoy Type Wave Energy Converter

    OpenAIRE

    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 control...

  5. 46 CFR 28.115 - Ring life buoys.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 1 2010-10-01 2010-10-01 false Ring life buoys. 28.115 Section 28.115 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY UNINSPECTED VESSELS REQUIREMENTS FOR COMMERCIAL FISHING INDUSTRY VESSELS Requirements for All Vessels § 28.115 Ring life buoys. (a) Except as provided in paragraph (b) of this section and § 28.305, each...

  6. 33 CFR 144.01-25 - Ring life buoys.

    Science.gov (United States)

    2010-07-01

    ... 33 Navigation and Navigable Waters 2 2010-07-01 2010-07-01 false Ring life buoys. 144.01-25 Section 144.01-25 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) OUTER CONTINENTAL SHELF ACTIVITIES LIFESAVING APPLIANCES Manned Platforms § 144.01-25 Ring life buoys. (a) Each manned platform must have at...

  7. 33 CFR 401.14 - Anchor marking buoys.

    Science.gov (United States)

    2010-07-01

    ... 33 Navigation and Navigable Waters 3 2010-07-01 2010-07-01 false Anchor marking buoys. 401.14 Section 401.14 Navigation and Navigable Waters SAINT LAWRENCE SEAWAY DEVELOPMENT CORPORATION, DEPARTMENT OF TRANSPORTATION SEAWAY REGULATIONS AND RULES Regulations Condition of Vessels § 401.14 Anchor marking buoys. A highly visible anchor marking...

  8. 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 Section 90.248 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) SAFETY AND SPECIAL RADIO SERVICES PRIVATE LAND MOBILE RADIO SERVICES Non-Voice and Other Specialized Operations § 90.248 Wildlife and ocean buoy tracking. (a) The...

  9. Rip current monitoring using GPS buoy system

    Science.gov (United States)

    Song, DongSeob; Kim, InHo; Kang, DongSoo

    2014-05-01

    The occurrence of rip current in the Haeundae beach, which is one of the most famous beaches in South Korea, has been threatening beach-goers security in summer season annually. Many coastal scientists have been investigating rip currents by using field observations and measurements, laboratory measurements and wave tank experiments, and computer and numerical modeling. Rip current velocity is intermittent and may rapidly increase within minutes due to larger incoming wave groups or nearshore circulation instabilities. It is important to understand that changes in rip current velocity occur in response to changes in incoming wave height and period as well as changes in water level. GPS buoys have been used to acquire sea level change data, atmospheric parameters and other oceanic variables in sea for the purposes of vertical datum determination, tide correction, radar altimeter calibration, ocean environment and marine pollution monitoring. Therefore, we adopted GPS buoy system for an experiment which is to investigate rip current velocity; it is sporadic and may quickly upsurge within minutes due to larger arriving wave groups or nearshore flow uncertainties. In this study, for high accurate positioning of buy equipment, a Satellite Based Argumentation System DGPS data logger was deployed to investigate within floating object, and it can be acquired three-dimensional coordinate or geodetic position of buoy with continuous NMEA-0183 protocol during 24 hours. The wave height measured by in-situ hydrometer in a cross-shore array clearly increased before and after occurrence of rip current, and wave period also was lengthened around an event. These results show that wave height and period correlate reasonably well with long-shore current interaction in the Haeundae beach. Additionally, current meter data and GPS buoy data showed that rip current velocities, about 0.2 m/s, may become dangerously strong under specific conditions. Acknowledgement This research was

  10. Model Predictive Control of Buoy Type Wave Energy Converter

    DEFF Research Database (Denmark)

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

    2014-01-01

    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......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....... The straight forward solution to this maximization problem is achieved by maximizing the instantaneous range of motion of the buoy. The buoy as a single degree of freedom oscillator will undergo its maximum movements when it is in resonance with the sea state. Hence the best solution to the problem is achieved...

  11. 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...

  12. Determination of wave direction using an orbital following buoy

    Digital Repository Service at National Institute of Oceanography (India)

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

    Software has been developed in FORTRAN language using a personal computer for the determination of wave direction from time series measurements of heave, pitch and roll of an orbital following buoy. The method of digital band pass filtering describ...

  13. 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...

  14. Buoys and other devices for oil spill tracking

    Energy Technology Data Exchange (ETDEWEB)

    Fingas, Merv [Spill Science (Canada)], email: fingasmerv@shaw.ca

    2011-07-01

    This study presents an assessment of some of the existing oil spill tracking devices, mainly buoys, from 1970 up to the present time. The goal of this study is to evaluate the performance of oil tracking devices based on their design, deviation from the oil, and their accuracy in following spills as they move. A total of 33 different devices were tested, including oil sampling buoys, passive devices, buoys with incorporated radio tracking devices, and buoys for oceanographic purposes. Tests were held in different marine regions, with different oil types, and for varying test times. Results showed that deviations from the oil tracks varied between devices. It was suggested that testing time affects the buoy validation process, but that the kind of oil used has very little effect. Additionally, the testing process must be performed using real oil in regions where wind and current do not align. In conclusion, buoys fitted with satellite trackers were recommended, however those prepared for oceanographic purposes were not.

  15. NOAA marine environmental buoy data from the National Data Buoy Center for March 2004 (NODC 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...

  16. 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...

  17. Sea-Change in Ocean Observations on Moored Buoys from the National Data Buoy Center (NDBC)

    Science.gov (United States)

    Bouchard, R. H.; Elliott, J.; Pounder, D.; Kern, K.

    2014-12-01

    The presentation will provide the technical specifications, the systems engineering processes, and preliminary results from laboratory and field tests, as the National Data Buoy Center (NDBC) undertakes a fundamental and broad transformation (sea-change) of its ocean observing systems on moored buoys. This transformation is necessary to gain efficiencies in maintaining operational ocean observation networks and to increase their reliability, which will reduce maintenance costs. The presentation will also compare and contrast existing and planned systems. The Self-Contained Ocean Observations Payload (SCOOP) takes advantage of the advances in communications and small, efficient, multi-purpose sensors to reduce the size and costs of systems and expand the suite of available real-time ocean observations. The communications will allow NDBC to increase the precision and decrease the latency of the observations. The hallmark of SCOOP is the modularity of the payloads that allow NDBC to host specialized systems, for the oceanographic research community, which may include observing ocean acidification and algal blooms, and tracking marine life, alongside its standard suite of meteorological, oceanographic, and wave systems. SCOOP will include cameras, primarily to document vandalism incidents, but they can also serve to corroborate many of the automatic observations. The two-year integration project - focused on recapitalization of NDBC's network of Hurricane Weather buoys - is aided by NDBC's 40 years of experience with marine observations and its continually improving approach to testing. Testimony to the rigor of NDBC's development and test procedures is that the World Meteorological Organization and the Intergovernmental Ocean Commission have designated NDBC as the first Regional Marine Instrumentation Center (RMIC). Integral to the fielding of these new systems is a Mission Control Center (MCC) performing the real-time, specialized monitoring and analyses and

  18. 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.

  19. Prediksi Umur Kelelahan Struktur Keel Buoy Tsunami dengan Metode Spectral Fatigue Analysis

    Directory of Open Access Journals (Sweden)

    Angga Yustiawan

    2012-09-01

    Full Text Available Salah satu komponen dari Indonesia Tsunami Early Warning System (InaTEWS adalah surface buoy. Surface buoy selama beroperasi di laut akan menerima beban akibat gelombang yang relatif besar, bersifat dinamis dan acak, yang dapat menyebabkan beban berulang pada struktur keel buoy. Apabila terjadi secara terus-menerus, beban ini dapat mengakibatkan terjadinya kerusakan pada struktur keel dari surface buoy. Tujuan penelitian ini untuk mengetahui umur kelelahan struktur keel buoy tsunami dengan metode spectral fatigue analysis, dimana struktur keel buoy tsunami merupakan penghubung antara tali tambat (mooring line dengan surface buoy. Struktur keel buoy ini terbuat dari material poros bekas pakai. Untuk menentukan umur kelelahan struktur keel buoy ini, telah dilakukan pembuatan diagram sebaran gelombang (wave scatter diagram selama setahun pada koordinat 108.3417 BT dan 10.3998 LS. Selanjutnya dilakukan uji olah gerak buoy dan beban gelombang untuk mendapatkan fungsi transfer tegangan pada keel buoy. Pembuatan spektrum gelombang untuk masing-masing kondisi laut dilakukan untuk memperoleh respon tegangan pada struktur keel buoy. Hasil pengujian material berupa kurva SN digunakan sebagai basis dalam menentukan umur kelelahan. Hasil dari penelitian menunjukkan bahwa umur kelelahan struktur keel buoy tsunami akibat beban gelombang sekitar 11 tahun untuk berbagai kondisi laut (sea state di perairan yang ditinjau.

  20. LKB-Based Evaporation Duct Model Comparison with Buoy Data.

    Science.gov (United States)

    Babin, Steven M.; Dockery, G. Daniel

    2002-04-01

    A wave-riding catamaran with a mast-traveling sensor package (profiling buoy) was developed to make fine-scale atmospheric measurements within the first meter above the ocean surface. These measurements are used to generate time-averaged modified refractivity (M) profiles that are then compared with those determined from four evaporation duct models based on the surface layer theory of Liu, Katsaros, and Businger (LKB). Model inputs are derived from measurements from masts on the R/V Chessie and from a tethered sea surface temperature buoy. Because electromagnetic propagation is critically dependent on the M-profile slopes, different analytical techniques are employed to compare the curvature of the model profiles with that of the profiles measured by the profiling buoy. One comparison criterion was to use the rms M slope difference between the model and a curve fit to the buoy profile data. Another analytical technique was to use the rms M difference after mean M removal between the model and the buoy profiles. Using these criteria for comparison of these models with the data seems to indicate that the model-derived profiles may be missing some phenomena in the surface layer such as wave effects. Overall, however, the shapes of the measured M profiles showed log-linear characteristics near the surface. One interesting result is that each model was better at approximating the M-profile curvature for stable than for unstable conditions.

  1. 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.

  2. Numerical simulation of a floating buoy in surface waves

    Science.gov (United States)

    Altazin, Thomas; Golay, Frédéric; Fraunié, Philippe

    2016-04-01

    A numerical method based on volumic penalization is developed to track a floating body in a two phase flows (air and water). Fast computations on parallel computer are performed thanks to an adaptative mesh refinement following a numerical entropy criterion together with a variable time step depending on the mesh size. Applications concern the motion of a floating buoy in a surface wave field and the induced perturbation of the wave and atmospheric fields by the buoy. Presented cases concern a breaking wave and a second order Stokes wave as initial conditions. Acknowledgements : This research was supported by the Modtercom and CHEF projects of Region PACA, when applications on windage of floating buoys are related to the SUBCORAD LEFE-INSU project.

  3. 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.

  4. 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

  5. A buoy for continuous monitoring of Suspended Sediment Dynamics.

    Science.gov (United States)

    Mueller, Philip; Thoss, Heiko; Kaempf, Lucas; Güntner, Andreas

    2013-01-01

    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. We conclude that

  6. 46 CFR 131.875 - Lifejackets, immersion suits, and ring buoys.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 4 2010-10-01 2010-10-01 false Lifejackets, immersion suits, and ring buoys. 131.875... OPERATIONS Markings for Fire Equipment and Emergency Equipment § 131.875 Lifejackets, immersion suits, and ring buoys. (a) Each lifejacket, immersion suit, and ring life buoy must be marked in block...

  7. Design and analysis of wave energy converter for a buoy

    International Nuclear Information System (INIS)

    This paper introduces the design method for the practical use of a wave energy converter (WEC), and the associated results are application to the commercially available WEC for buoys. Peak performance of WEC occurs at resonance with driving waves. This type of resonance occurs when one of the parameters in an oscillator varies periodically. The water column in a WEC oscillates under the effect of gravity and the compression of an air chamber. The analysis of WEC is developed by assuming independence of the buoy heaving motion and the motion of the water column within the center cylinder. Results of analysis are then compared with simulation data, and applied to designing a WEC for buoys. Also, the effect of the various parameters such as cylinder length, period, mass and wave height is analyzed for the optimum design of a WEC. Finally, the research results are applied to a wave simulator with operating LabView, and some ideas are presented to the design method of WEC for buoy with simulation experiment

  8. 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

  9. 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...... estimated reasonably well, even considering high-frequency wave components of a wind sea wave spectrum....

  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 Buoy and vessel use costs. (a) The buoy and...

  11. A study of the optimum draft of multiple resonance power buoys for maximizing electric power production

    Directory of Open Access Journals (Sweden)

    Kweon Hyuck-Min

    2014-12-01

    Full Text Available To maximize electric power production using wave energy extractions from resonance power buoys, the maximum motion displacement spectra of the buoys can primarily be obtained under a given wave condition. In this study, wave spectra observed in shoaling water were formulated. Target resonance frequencies were established from the arithmetic means of modal frequency bands and the peak frequencies. The motion characteristics of the circular cylindrical power buoys with corresponding drafts were then calculated using numerical models without considering PTO damping force. Results showed that the heave motions of the power buoys in shoaling waters with insufficient drafts produced greater amplification effects than those in deep seas with sufficient drafts.

  12. 78 FR 46410 - Requested Administrative Waiver of the Coastwise Trade Laws: Vessel TWO BUOYS ONE GULL...

    Science.gov (United States)

    2013-07-31

    ... GULL; Invitation for Public Comments AGENCY: Maritime Administration, Department of Transportation... the applicant the intended service of the vessel TWO BUOYS ONE GULL is: Intended Commercial Use...

  13. De-tiding Short Tsunami Records at DART Buoys

    Science.gov (United States)

    Tolkova, E.

    2008-12-01

    The tsunami forecast system being developed at the Pacific Marine Environmental Laboratory relies on a network of DART buoys to obtain real-time measurements of tsunami wave height. A tsunami wave in an open ocean is however often a few centimeters in amplitude or less. This signal is masked by the much more powerful tidal component, with typical amplitude of one meter or more. Therefore, for high-quality tsunami measurements, the tidal component of a DART record must be removed almost perfectly. For instance, for 1 meter amplitude of the tidal motion (70 cm root-mean-square (RMS) value), 99.998% of the total tidal variance needs be removed for the residual to stay under 3 mm (RMS). Two major approaches to detiding a record are either to predict a tide, or to filter it out. Tidal prediction employs a formalism of harmonic constituents. The constituents' phases and amplitudes have to be determined for each and every individual buoy, which optimally requires an analysis of a particular buoy's record for one or more years. Tidal predictions alone can not provide the desired accuracy. Digital filtering has the major difficulty of detecting a tsunami at the beginning of the event, when the tsunami record at a DART buoy is less than one full wave (a peak and a trough). Needless to say, from the point of view of real- time tsunami forecast, the first appearance of a tsunami wave peak on a DART record is when the precise measurement of the tsunami characteristics is essential. In this work, a de-tiding technique is presented, which can reliably detect a tsunami wave in a DART signal with a few mm accuracy from the very beginning of the tsunami record. The method is based on an empirical observation that sections of tidal records M-reading long regardless of when and where they were taken, can be expressed as a linear combination of several M-dimensional vectors derived via principal component analysis of DART records. Fitting a section of a DART record with these functions

  14. 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.

  15. 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...

  16. 46 CFR 169.741 - Personal flotation devices and ring life buoys.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 7 2010-10-01 2010-10-01 false Personal flotation devices and ring life buoys. 169.741 Section 169.741 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) NAUTICAL SCHOOLS SAILING SCHOOL VESSELS Vessel Control, Miscellaneous Systems, and Equipment Markings § 169.741 Personal flotation devices and ring life buoys....

  17. An overview of a moored ocean data buoy programme

    Digital Repository Service at National Institute of Oceanography (India)

    Nayak, M.R.

    PITs from Service ARGOS. France • develop electronics module, power pack ages using solar panels and rechargeable sealed batteries alongwith the associated mechanical components needed for hou sing the electronics • deploy the buoy at a place where... consists of a single-board CMOS 8085 based computer, an analog board using ADC 7109 and an EPROM card for data storage. The analog card will also carry the power control circu itry and digital sensor interface circuits. If required, in place of EPROM card...

  18. 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...

  19. 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...

  20. 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...

  1. Development of an autonomous sea ice tethered buoy for the study of ocean-atmosphere-sea ice-snow pack interactions: the O-buoy

    Directory of Open Access Journals (Sweden)

    T. N. Knepp

    2009-09-01

    Full Text Available A buoy based instrument platform (the "O-buoy" was designed, constructed, and field tested for year-round measurement of ozone, bromine monoxide, carbon dioxide, and meteorological variables over Arctic sea ice. The O-buoy operated in an autonomous manner with daily, bi-directional data transmissions using Iridium satellite communication. The O-buoy was equipped with three power sources: primary lithium-ion battery packs, rechargeable lead acid packs, and solar panels that recharge the lead acid packs, and can fully power the O-buoy during summer operation. This system was designed to operate under the harsh conditions present in the Arctic, with minimal direct human interaction, to aid in our understanding of the atmospheric chemistry that occurs in this remote region of the world. The current design requires approximately yearly maintenance limited by the lifetime of the primary power supply. The O-buoy system was field tested in Elson Lagoon, Barrow, Alaska from February to May 2009, and here we describe the design and present preliminary data.

  2. Comparison of heaving buoy and oscillating flap wave energy converters

    Science.gov (United States)

    Abu Bakar, Mohd Aftar; Green, David A.; Metcalfe, Andrew V.; Najafian, G.

    2013-04-01

    Waves offer an attractive source of renewable energy, with relatively low environmental impact, for communities reasonably close to the sea. Two types of simple wave energy converters (WEC), the heaving buoy WEC and the oscillating flap WEC, are studied. Both WECs are considered as simple energy converters because they can be modelled, to a first approximation, as single degree of freedom linear dynamic systems. In this study, we estimate the response of both WECs to typical wave inputs; wave height for the buoy and corresponding wave surge for the flap, using spectral methods. A nonlinear model of the oscillating flap WEC that includes the drag force, modelled by the Morison equation is also considered. The response to a surge input is estimated by discrete time simulation (DTS), using central difference approximations to derivatives. This is compared with the response of the linear model obtained by DTS and also validated using the spectral method. Bendat's nonlinear system identification (BNLSI) technique was used to analyze the nonlinear dynamic system since the spectral analysis was only suitable for linear dynamic system. The effects of including the nonlinear term are quantified.

  3. Fluid Structure Interaction Modeling of the Dynamic of a Semi Submerged Buoy

    OpenAIRE

    Hajwal, Shatha Hameed; Nasser, Hamza Zeidan

    2013-01-01

    This thesis presents a study of buoy systems for wave’s energy by focusing on the development of a model in which modeling of a wave energy conversation is in operation. Throughout the thesis, the buoyancy and motion of the submerged body has been used to describe the wave-buoy interaction. The mathematical model for an investigating buoyancy and the dynamic heave response of this buoy under the two different load cases be considered as a single degree of freedom, which have natural character...

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

    Directory of Open Access Journals (Sweden)

    Arne Fjälling

    2013-10-01

    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

  5. Perancangan Sistem Akuisisi Data Maritime Buoy Weather Station

    Directory of Open Access Journals (Sweden)

    Aditya Gautama Aji

    2013-03-01

    Full Text Available Saat ini, layanan sistem informasi mengenai data cuaca, prakiraan cuaca dan iklim secara makro, mudah didapatkan dari hasil analisa oleh BMKG melalui website. namun informasi cuaca yang diberikan pada website bmkg tersebut merupakan hasil dari keluaran sebuah program yang didasarkan pada interpolasi dan ekstrapolasi data cuaca dari berbagai posisi di Indonesia. Keluaran dari penelitian ini didaharpkan dapat menghasilkan sebuah Maritime Buoy Weather Station yang mampu mengindera lima variabel yang memperngaruhi cuaca seperti temperatur udara, tekanan udara, kecepatan angin, arah angin, dan kelembaban udara. Sistem yang telah dirancang memiliki spesifikasi yakni sensor temperatur udara memiliki ketidakpastian sebesar 0.0360C. Tekanan udara memiliki ketidakpastian sebesar 0.13 hPa, kecepatan angin memiliki ketidakpastian sebesar 0.017 m/s, Arah angin memiliki ketidakpastian sebesar 2.90, dan sensor kelembaban memiliki ketidakpastian pengkuran sebesar 0.07 %RH.

  6. 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.

  7. 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...

  8. 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....

  9. 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....

  10. 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....

  11. 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...

  12. Wind wave spectra gathered by anchored data buoys (NODC Accession 9900175)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Wind wave spectra data were collected using anchored data buoys in various place such as Coastal Waters of Western US, Gulf of Mexico, South Pacific Ocean, Great...

  13. 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...

  14. Investigation of Hydrodynamic Aspects of the Design of the Universal Buoyancy Concept (UBC) Loading Buoy

    OpenAIRE

    Knutsen, David Mikal

    2012-01-01

    A new loading and discharge concept for ships, referred to as the Universal Buoyancy Concept (UBC), is proposed as an effective alternative to land based infrastructure for distribution of primarily LNG. The UBC system consists of a slack moored stepped spar buoy equipped with pads for shipside vacuum attachment. The buoy is connected to shore based tank facilities with a flexible cryogenic riser, thus providing opportunity for offshore loading and discharge of cryogenic liquids. In the follo...

  15. Seafloor horizontal positioning from a continuously operating buoy-based GPS-acoustic array

    Science.gov (United States)

    Chadwell, C. D.; Brown, K. M.; Tryon, M. D.; Send, U.

    2009-12-01

    Seafloor horizontal positions in a global frame were estimated daily from an autonomous buoy operating continuously over several months. The buoy (GEOCE) was moored offshore San Diego in 100-m-deep waters above an array of 4 seafloor transponders. Dual-frequency GPS data were collected at 1-Hz at a main antenna on the buoy and at 3 shore stations to provide continuous 2-3 cm positions of the buoy main antenna. Two single-frequency antennas on the buoy along with the main antenna were used to estimate the buoy attitude and short-term velocity. At one minute intervals the two-way acoustic travel time was measured between the buoy and transponders. During this few second span when transmitting and receiving acoustic signals, 10-Hz attitude and velocity were collected to locate the position of the transducer mounted approximately 2 m below the water line. The GPS and acoustic data were recorded internally and transmitted to shore over a cell-phone link and/or a wireless Ethernet. GPS data were combined with the acoustic data to estimate the array location at 1 minute intervals. The 1-minute positions are combined to provide a daily estimate of the array position. The buoy is autonomous, solar-powered and in addition to the GPS and acoustic data collects air pressure, temperature, wind speed/direction as well as water level at the surface and conductivity and temperature along the mooring line from near the sea surface to just above the sea floor. Here we report results from the horizontal positioning effort from Phase I of the project in shallow waters. The project also includes a vertical deformation sensor and physical oceanographic monitoring. A deep water (nominally 1000 m) test is planned for 2010. This work is supported by NSF-OCE-0551363 of the Ocean Technology and Interdisciplinary Coordination Program.

  16. 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.

  17. 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.

  18. Data Buoy powered by a thermo-mechanical generator: results of a year's operation at sea

    International Nuclear Information System (INIS)

    The UK National Data Buoy is powered by a prototype thermo-mechanical generator. This power source delivers 20 to 25 watts electrical and requires several times less fuel than an equivalent propane-heated thermo-electric power source, so that fuel for 21/2 years' operation can be carried on the Buoy. The Buoy has been stationed in the North Sea off the East Coast of England since December 1975, and operating experience with the TMG in the succeeding year is described. Such problems as have been encountered have been mainly peripheral in nature, and the TMG has been running for about 90 percent of the maximum time possible. Operating experience with other similar generators are discussed, and recent development of a 60W TMG is outlined

  19. Control strategies to optimise power output in heave buoy energy convertors

    International Nuclear Information System (INIS)

    Wave energy converter (WEC) designs are always discussed in order to obtain an optimum design to generate the power from the wave. Output power from wave energy converter can be improved by controlling the oscillation in order to acquire the interaction between the WEC and the incident wave.The purpose of this research is to study the heave buoys in the interest to generate an optimum power output by optimising the phase control and amplitude in order to maximise the active power. In line with the real aims of this study which investigate the theory and function and hence optimise the power generation of heave buoys as renewable energy sources, the condition that influence the heave buoy must be understand in which to propose the control strategies that can be use to control parameters to obtain optimum power output. However, this research is in an early stage, and further analysis and technical development is require

  20. Earth resources technology satellite /ERTS/ data collection and transmission buoys for inland, neritic and oceanic waters

    Science.gov (United States)

    Chapman, W. S.; Yen, H. H.

    1974-01-01

    As a result of a consortium of several industries and organizations, an economical, versatile, and stable data collection and transmission buoy has been designed, developed, and deployed to gather and transmit water quality data to a ground receiving station at three-minute intervals and to the earth resources technology satellite (ERTS) as it passes over the deployed buoy every 12 hours. The buoy system, designed for both fresh and salt water application, gathers data inclusive of temperature measurement, conductivity, relative acidity, dissolved oxygen, current speed, and direction. The mechanical design philosophy used to determine and satisfy boundary conditions involving stability, ease of deployment, servicing and maintenance, minimal manufacturing costs, and fresh and salt water installation capability is discussed. The development of peripheral handling equipment and anchoring systems is described.

  1. 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.

  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.

    implemented through multi-national cooperative efforts. Continued commitment of financial, human, and ship time resources from several nations 14 16 28 38 47 82 60 87 109 142 0 20 40 60 80 100 120 140 160 2006 2007 2008 2009 2010 Buoys Sea Days * Indian... of an Indian Ocean Moored Buoy Array for Climate Studies McPhaden M.J. 1 , Y. Kuroda 2 and V. S. N. Murty 3 , 1 NOAA/Pacific Marine Environmental Laboratory, USA, 2 Japan Marine-Earth Science and Technology Agency, Japan, 3 National Institute...

  3. 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.

  4. Studying Buoy Motion for Wave Power. Experiments at the Lysekil Research Site

    Energy Technology Data Exchange (ETDEWEB)

    Tyrberg, Simon

    2009-05-15

    Since 2002, the Div. for Electricity at Uppsala University has been running the Lysekil project. The project is an attempt to construct and evaluate a technology for extracting electrical energy from the motion of ocean waves. The idea is to let this up-and-down motion drive a linear generator. A buoy moves thus in the waves, and is connected through a line to the generator at the sea floor. Three such wave energy converters, L1, L2, and L3, and a marine substation have been deployed in the ocean southwest of Lysekil on the Swedish west coast, at the Lysekil research site. Measuring equipment has also been deployed, together with a number of buoys for studying environmental impact. A measuring station has been installed on the nearby island of Hermanoe, and an observation tower has been built on the islet of Klammerskaer, south of the research site. This thesis describes the work on studying wave buoy motion and is based on five scientific papers, covering mainly two areas. Firstly, changes in water levels, and thereby changes in the equilibrium point for the buoy and generator, have been related to the ability of L1 to absorb energy. The results indicate that there is a correlation between water levels and energy absorption for L1 for the studied time period. When the water level deviates from average, the absorption values decrease. This is not unexpected, since the linear generator has a finite stroke. The effect is however noticeable primarily for water level deviations of more than 25 cm, and is only visible for those cases where either wave height or water level deviation is large. Secondly, the above mentioned observation tower has been designed and built. The tower is equipped with a network camera covering the research site, a wireless communication system and an energy system. The first acquired images of the buoy connected to L1, taken during the summer of 2008, have been analyzed, and buoy motion data has been extracted. The observation system has

  5. An autonomous drifting buoy system for long term pCO2 observation

    Science.gov (United States)

    Nakano, Y.; Fujiki, T.; Wakita, M.; Azetsu-Scott, K.; Watanabe, S.

    2009-04-01

    Many studies have been carried out around the world to understand what happens to carbon dioxide (CO2) once it is emitted into the atmosphere, and how it relates to long-term climate change. However, the sea surface pCO2 observations on volunteer observation ships and research vessels concentrated in the North Atlantic and North Pacific. To assess the spatial and temporal variations of surface pCO2 in the global ocean, new automated pCO2 sensor which can be used in platform systems such as buoys or moorings is strongly desired. We have been developing the small drifting buoy system (diameter 250-340 mm, length 470 mm, weight 15 kg) for pCO2 measurement, with the support of the Japan EOS Promotion Program (JEPP), the Ministry of Education, Culture, Sports, Science and Technology (MEXT). The objective is to provide simplified, automated measurements of pCO2 over all the world's oceans, an essential factor in understanding how the ocean responds to climate change. The measurement principle for the pCO2 sensor is based on spectrophotometry (e.g. Lefèvre et al., 1993; Degrandpre et al., 1995). The CO2 in the surrounding seawater equilibrates with the indicator solution across the gas permeable membranes. The equilibration process causes a change of pH in the indicator solution, which results in the change of optical absorbance. The pCO2 is calculated from the optical absorbance of the pH indicator solution equilibrated with CO2 in seawater through a gas permeable membrane. In our analytical system, we used an amorphous fluoropolymer tubing form of AF-2400 by DuPontTM for the gas permeable membrane due to its high gas permeability coefficients. The measurement system of the sensor consisted mainly of a LED light source, optical fibers, a CCD detector, and a downsized PC. The measured data were transmitted to the laboratory by satellite communication (Argos system). In the laboratory experiment, we obtained a high response time (less than 2 minutes) and a precision

  6. A Combined Radio and Underwater Wireless Optical Communication System based on Buoys

    Science.gov (United States)

    Song, Yuhang; Tong, Zheng; Cong, Bo; Yu, Xiangyu; Kong, Meiwei; Lin, Aobo

    2016-02-01

    We propose a system of combining radio and underwater wireless optical communication based on buoys for real-time image and video transmission between underwater vehicles and the base station on the shore. We analysis how the BER performance is affected by the link distance and the deflection angle of the light source using Monte Carlo simulation.

  7. High frequency monitoring of the coastal marine environment using the MAREL buoy.

    Science.gov (United States)

    Blain, S; Guillou, J; Tréguer, P; Woerther, P; Delauney, L; Follenfant, E; Gontier, O; Hamon, M; Leilde, B; Masson, A; Tartu, C; Vuillemin, R

    2004-06-01

    The MAREL Iroise data buoy provides physico-chemical measurements acquired in surface marine water in continuous and autonomous mode. The water is pumped 1.5 m from below the surface through a sampling pipe and flows through the measuring cell located in the floating structure. Technological innovations implemented inside the measuring cell atop the buoy allow a continuous cleaning of the sensor, while injection of chloride ions into the circuit prevents biological fouling. Specific sensors for temperature, salinity, oxygen and fluorescence investigated in this paper have been evaluated to guarantee measurement precision over a 3 month period. A bi-directional link under Internet TCP-IP protocols is used for data, alarms and remote-control transmissions with the land-based data centre. Herein, we present a 29 month record for 4 parameters measured using a MAREL buoy moored in a coastal environment (Iroise Sea, Brest, France). The accuracy of the data provided by the buoy is assessed by comparison with measurements of sea water weekly sampled at the same site as part of SOMLIT (Service d'Observation du Milieu LIToral), the French network for monitoring of the coastal environment. Some particular events (impact of intensive fresh water discharges, dynamics of a fast phytoplankton bloom) are also presented, demonstrating the worth of monitoring a highly variable environment with a high frequency continuous reliable system. PMID:15173911

  8. 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...

  9. 33 CFR 149.320 - What are the requirements for ring life buoys?

    Science.gov (United States)

    2010-07-01

    ... 33 Navigation and Navigable Waters 2 2010-07-01 2010-07-01 false What are the requirements for ring life buoys? 149.320 Section 149.320 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) DEEPWATER PORTS DEEPWATER PORTS: DESIGN, CONSTRUCTION, AND EQUIPMENT Lifesaving Equipment Manned Deepwater...

  10. 33 CFR 149.337 - What are the requirements for ring life buoys?

    Science.gov (United States)

    2010-07-01

    ... 33 Navigation and Navigable Waters 2 2010-07-01 2010-07-01 false What are the requirements for ring life buoys? 149.337 Section 149.337 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) DEEPWATER PORTS DEEPWATER PORTS: DESIGN, CONSTRUCTION, AND EQUIPMENT Lifesaving Equipment Unmanned Deepwater...

  11. Numerical modeling of a spherical buoy moored by a cable in three dimensions

    Science.gov (United States)

    Zhu, Xiangqian; Yoo, Wan-Suk

    2016-05-01

    Floating facilities have been studied based on the static analysis of mooring cables over the past decades. To analyze the floating system of a spherical buoy moored by a cable with a higher accuracy than before, the dynamics of the cables are considered in the construction of the numerical modeling. The cable modeling is established based on a new element frame through which the hydrodynamic loads are expressed efficiently. The accuracy of the cable modeling is verified with an experiment that is conducted by a catenary chain moving in a water tank. In addition, the modeling of a spherical buoy is established with respect to a spherical coordinate in three dimensions, which can suffers the gravity, the variable buoyancy and Froude-Krylov loads. Finally, the numerical modeling for the system of a spherical buoy moored by a cable is established, and a virtual simulation is proceeded with the X- and Y-directional linear waves and the X-directional current. The comparison with the commercial simulation code ProteusDS indicates that the system is accurately analyzed by the numerical modeling. The tensions within the cable, the motions of the system, and the relationship between the motions and waves are illustrated according to the defined sea state. The dynamics of the cables should be considered in analyzing the floating system of a spherical buoy moored by a cable.

  12. Numerical Modeling of a Spherical Buoy Moored by a Cable in Three Dimensions

    Science.gov (United States)

    Zhu, Xiangqian; Yoo, Wan-Suk

    2016-04-01

    Floating facilities have been studied based on the static analysis of mooring cables over the past decades. To analyze the floating system of a spherical buoy moored by a cable with a higher accuracy than before, the dynamics of the cables are considered in the construction of the numerical modeling. The cable modeling is established based on a new element frame through which the hydrodynamic loads are expressed efficiently. The accuracy of the cable modeling is verified with an experiment that is conducted by a catenary chain moving in a water tank. In addition, the modeling of a spherical buoy is established with respect to a spherical coordinate in three dimensions, which can suffers the gravity, the variable buoyancy and Froude-Krylov loads. Finally, the numerical modeling for the system of a spherical buoy moored by a cable is established, and a virtual simulation is proceeded with the X- and Y-directional linear waves and the X-directional current. The comparison with the commercial simulation code ProteusDS indicates that the system is accurately analyzed by the numerical modeling. The tensions within the cable, the motions of the system, and the relationship between the motions and waves are illustrated according to the defined sea state. The dynamics of the cables should be considered in analyzing the floating system of a spherical buoy moored by a cable.

  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. 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

  15. Snow depth on Arctic and Antarctic sea ice derived from autonomous (Snow Buoy) measurements

    Science.gov (United States)

    Nicolaus, Marcel; Arndt, Stefanie; Hendricks, Stefan; Heygster, Georg; Huntemann, Marcus; Katlein, Christian; Langevin, Danielle; Rossmann, Leonard; Schwegmann, Sandra

    2016-04-01

    The snow cover on sea ice received more and more attention in recent sea ice studies and model simulations, because its physical properties dominate many sea ice and upper ocean processes. In particular; the temporal and spatial distribution of snow depth is of crucial importance for the energy and mass budgets of sea ice, as well as for the interaction with the atmosphere and the oceanic freshwater budget. Snow depth is also a crucial parameter for sea ice thickness retrieval algorithms from satellite altimetry data. Recent time series of Arctic sea ice volume only use monthly snow depth climatology, which cannot take into account annual changes of the snow depth and its properties. For Antarctic sea ice, no such climatology is available. With a few exceptions, snow depth on sea ice is determined from manual in-situ measurements with very limited coverage of space and time. Hence the need for more consistent observational data sets of snow depth on sea ice is frequently highlighted. Here, we present time series measurements of snow depths on Antarctic and Arctic sea ice, recorded by an innovative and affordable platform. This Snow Buoy is optimized to autonomously monitor the evolution of snow depth on sea ice and will allow new insights into its seasonality. In addition, the instruments report air temperature and atmospheric pressure directly into different international networks, e.g. the Global Telecommunication System (GTS) and the International Arctic Buoy Programme (IABP). We introduce the Snow Buoy concept together with technical specifications and results on data quality, reliability, and performance of the units. We highlight the findings from four buoys, which simultaneously drifted through the Weddell Sea for more than 1.5 years, revealing unique information on characteristic regional and seasonal differences. Finally, results from seven snow buoys co-deployed on Arctic sea ice throughout the winter season 2015/16 suggest the great importance of local

  16. Development of a new Tsunami Monitoring System Using a GPS Buoy

    Science.gov (United States)

    Kato, T.; Terada, Y.; Nagai, T.; Shimizu, K.; Tomita, T.; Koshimura, S.

    2008-12-01

    A tsunami monitoring system using a GPS buoy has been developed for more than ten years. Real-time kinematic (RTK) GPS technology was used for this purpose. After a series of preliminary experimental studies, the third experiment was conducted offshore Ofunato city, northern Tohoku, Japan. GPS antenna was set at the top of the buoy and the 1-sec sampling data were transmitted to the ground base of about 1.6km distance together with other ancillary data. The data was processed at the ground base and the estimated 3D positions were disseminated through internet. This system operated for about three years of 2001-2003 and succeeded to detect two tsunamis of about 10cm amplitude; 2001 Peru earthquake and 2003 Tokachi earthquake, by applying a simple filtering technique. After this successful experiment, the fourth system was newly designed and was established about 12km south of Muroto Promontory, southwestern Japan in early April 2004. The buoy has experienced nearby passages of several typhoons with a maximum wave of about 20meter and has shown a total integrity for an operational use. On September 5th 2004, a large earthquake of Mw7.4 occurred about 200km east of the buoy. The GPS buoy successfully recorded the tsunami with about 10cm amplitude at the first peak arrival of about 10 minutes before its arrival at the nearest coast of Muroto Promontory. The simulated record has shown excellent consistency with the observed tsunami, suggesting high potential for predicting tsunami height at the coast before its arrival, if the record is efficiently implemented in the tsunami warning system. The system has been adopted as a national sea-surface monitoring project and has been deployed at several locations around the Japanese coasts for monitoring also wind-waves.

  17. 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

    2016-05-01

    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.

  18. 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...

  19. 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)....

  20. 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...

  1. 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...

  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 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...

  4. 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...

  5. 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...

  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. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  15. 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...

  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...

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  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 2013-01 (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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. 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 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...

  15. 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...

  16. Meteorological and oceanographic data collected from the National Data Buoy Center Coastal-Marine Automated Network (C-MAN) and moored (weather) buoys during 2005-09 (NODC Accession 0002415)

    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. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. NODC Standard Product: NOAA Marine environmental buoy database 1993 with Updates (19 disc set) (NODC Accession 0095199)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This set of CD-ROMs holds marine meteorological, oceanographic, and wave spectra data collected by moored buoys and C-MAN (Coastal-Marine Automated Network)...

  3. Winter Sea Ice Deformation Measured by Autonomous Buoys During the N-ICE2015 Cruise in the Arctic Ocean North of Svalbard

    Science.gov (United States)

    Itkin, P.; Spreen, G.; Gerland, S.

    2015-12-01

    The motion of the sea ice cover in the Arctic Ocean north of Svalbard is characterized by fast sea ice drift (10 to 70 km/day) during the winter season. The Norwegian Young sea ICE cruise (N-ICE2015) took place in that region from January till June 2015. During this period more than 40 buoys in nested arrays at the distance of 5 to 100 km apart from each other were deployed in 2 deployments (in January/February and in April/May). The buoy types include drifters, snow buoys, ice-mass balance buoys, radiation buoys and wave buoys. The buoys were deployed on the first- and second-year ice that was characteristic for the region. The sea ice dynamics measured by these buoy arrays are explored in relation to the changing atmospheric forcing and internal ice stress during the experiment. The deformation rates obtained from the buoy array are on average higher than measured by buoy experiments in other Arctic regions by earlier experiments. Our preliminary results show a strong connection of the deformation events to the atmospheric forcing. The high sea ice drift speed associated to strong winds is connected to high deformation rates, while the low speeds in the calm periods are connected to the low deformation rates. While it is known that the relationship between the deformation rate and the spatial scale over which it is measured can be represented by a power law (Stern and Lindsay, 2009, JGR), we find that the exponent is not constant over time and space during the experiment. For high ice drift speeds, associated with high wind speeds and a more loose ice cover, the exponent becomes more negative than for lower ice drift speeds and a compressed ice cover. Figure: Locations of buoy deployments and buoy types for all the buoys deployed during the N-ICE2015 cruise.

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

    OpenAIRE

    Gao Hongtao; Li Biao

    2015-01-01

    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 b...

  5. System of long- effect navigation buoy using in freezing area%冰区长效灯浮标系统

    Institute of Scientific and Technical Information of China (English)

    孔令臣; 刘祥玉; 阚卫明; 陈永红

    2014-01-01

    文章针对目前国内冰标存在的供电期短、助航效能不明显、保养维护周期短、航标作业量大等缺点,研制出新型长效灯浮标。其采用高性能锂电池和太阳能电池组合的供电系统,在原φ1.4 m冰标基础上,增大显形面积及焦面高度。长效灯浮标降低了能源维护周期,提高了助航效能,减少换标作业,降低单点标体成本,初步实现了我国北方冰冻港口灯浮标的长效化。%The-present-ice-navigation-buoy-exist-several-disadvantages,-such-as-short-term-power-supply,-inconspicuous-navi-gation-performance,-shortdated-maintenance-cycle,-large-arduous-buoy-operation-task.-In-view-of-these-disadvantages,-we-developed-a-new-type-of-long-effect-navigation-buoy-which-has-high-performance-lithium-and-solar-battery-power-in-its-power-supply-system;and-on-the-basis-of-the-original-φ1.4-meter-ice-navigation-buoy,-visualization-area-and-focal-plane-height-were-increased.-The-long-effect-navigation-buoy-reduced-energy-maintenance-cycles,-improved-the-navigation-efficiency,-lessened-arduous-buoy-operation-task-and-reduced-the-cost-of-buoy-on-single-point.-The-breach-made-sense-in-the-initial-realization-of-the-long-effect-navigation-buoy-using-in-the-frozen-port-in-northern-China.

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

    DEFF Research Database (Denmark)

    Lavelle, John; Kofoed, Jens Peter

    below. 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...... 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...... difficult to determine the efficiency function. The Equimar project deliverable 4.2 (3) describes a method for analysing and presenting the power production data in order to determine the yearly power production of the device at a given location and quantify its uncertainty. The limited amount of power...

  7. Validation of FOAM near-surface ocean current forecasts using Lagrangian drifting buoys

    Directory of Open Access Journals (Sweden)

    E. W. Blockley

    2012-07-01

    Full Text Available In this study, the quality of near-surface current forecasts from the FOAM ocean forecasting system is assessed using the trajectories of Lagrangian drifting buoys. A method is presented for deriving pseudo-Eulerian estimates of ocean currents from the positions of Surface Velocity Program drifters and the resulting data are compared to velocities observed by the global tropical moored buoy array. A quantitative analysis of the global FOAM velocities is performed for the period 2007 and 2008 using currents derived from over 3000 unique drifters (providing an average of 650 velocity observations per day. A potential bias is identified in the Southern Ocean which appears to be caused by wind-slip in the drifter dataset as a result of drogue loss. The drifter-derived currents are also used to show how the data assimilation scheme and a recent system upgrade impact upon the quality of FOAM current forecasts.

  8. Automatic data collection by a low-power microprocessor on the Italian buoy

    International Nuclear Information System (INIS)

    A low-power data acquisition system for stations not attended, marine platforms or buoys is presented here. The prototype has been installed on the oceanographic buoy ODAS Italia 1. The data acquisition system utilizes an IM6100 (INTERSIL) microprocessor with 2 k-words of random access memory (RAM) and 2 k-words of erasable programmable read-only memory (EPROM) (1 word = 12 bits). The program fo the acquisition of the data, the control of the device, the transmission to the earth receiving station and the reception of commands from the earth station is memorized in the read-only memories. It becomes operative when the power is turned on. (author)

  9. Automated calculation of surface energy fluxes with high-frequency lake buoy data

    Science.gov (United States)

    Woolway, R Iestyn; Jones, Ian D; Hamilton, David P.; Maberly, Stephen C; Muroaka, Kohji; Read, Jordan S.; Smyth, Robyn L; Winslow, Luke A.

    2015-01-01

    Lake Heat Flux Analyzer is a program used for calculating the surface energy fluxes in lakes according to established literature methodologies. The program was developed in MATLAB for the rapid analysis of high-frequency data from instrumented lake buoys in support of the emerging field of aquatic sensor network science. To calculate the surface energy fluxes, the program requires a number of input variables, such as air and water temperature, relative humidity, wind speed, and short-wave radiation. Available outputs for Lake Heat Flux Analyzer include the surface fluxes of momentum, sensible heat and latent heat and their corresponding transfer coefficients, incoming and outgoing long-wave radiation. Lake Heat Flux Analyzer is open source and can be used to process data from multiple lakes rapidly. It provides a means of calculating the surface fluxes using a consistent method, thereby facilitating global comparisons of high-frequency data from lake buoys.

  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. Continuous Wavelet Transform Analysis of Acceleration Signals Measured from a Wave Buoy

    Directory of Open Access Journals (Sweden)

    Laurence Zsu-Hsin Chuang

    2013-08-01

    Full Text Available Accelerometers, which can be installed inside a floating platform on the sea, are among the most commonly used sensors for operational ocean wave measurements. To examine the non-stationary features of ocean waves, this study was conducted to derive a wavelet spectrum of ocean waves and to synthesize sea surface elevations from vertical acceleration signals of a wave buoy through the continuous wavelet transform theory. The short-time wave features can be revealed by simultaneously examining the wavelet spectrum and the synthetic sea surface elevations. The in situ wave signals were applied to verify the practicality of the wavelet-based algorithm. We confirm that the spectral leakage and the noise at very-low-frequency bins influenced the accuracies of the estimated wavelet spectrum and the synthetic sea surface elevations. The appropriate thresholds of these two factors were explored. To study the short-time wave features from the wave records, the acceleration signals recorded from an accelerometer inside a discus wave buoy are analysed. The results from the wavelet spectrum show the evidence of short-time nonlinear wave events. Our study also reveals that more surface profiles with higher vertical asymmetry can be found from short-time nonlinear wave with stronger harmonic spectral peak. Finally, we conclude that the algorithms of continuous wavelet transform are practical for revealing the short-time wave features of the buoy acceleration signals.

  12. Continuous wavelet transform analysis of acceleration signals measured from a wave buoy.

    Science.gov (United States)

    Chuang, Laurence Zsu-Hsin; Wu, Li-Chung; Wang, Jong-Hao

    2013-01-01

    Accelerometers, which can be installed inside a floating platform on the sea, are among the most commonly used sensors for operational ocean wave measurements. To examine the non-stationary features of ocean waves, this study was conducted to derive a wavelet spectrum of ocean waves and to synthesize sea surface elevations from vertical acceleration signals of a wave buoy through the continuous wavelet transform theory. The short-time wave features can be revealed by simultaneously examining the wavelet spectrum and the synthetic sea surface elevations. The in situ wave signals were applied to verify the practicality of the wavelet-based algorithm. We confirm that the spectral leakage and the noise at very-low-frequency bins influenced the accuracies of the estimated wavelet spectrum and the synthetic sea surface elevations. The appropriate thresholds of these two factors were explored. To study the short-time wave features from the wave records, the acceleration signals recorded from an accelerometer inside a discus wave buoy are analysed. The results from the wavelet spectrum show the evidence of short-time nonlinear wave events. Our study also reveals that more surface profiles with higher vertical asymmetry can be found from short-time nonlinear wave with stronger harmonic spectral peak. Finally, we conclude that the algorithms of continuous wavelet transform are practical for revealing the short-time wave features of the buoy acceleration signals. PMID:23966188

  13. Oceanographic Multisensor Buoy Based on Low Cost Sensors for Posidonia Meadows Monitoring in Mediterranean Sea

    Directory of Open Access Journals (Sweden)

    Sandra Sendra

    2015-01-01

    Full Text Available There are some underwater areas with high ecological interest that should be monitored. Posidonia and seagrasses exert considerable work in protecting the coastline from erosion. In these areas, many animals and organisms live and find the grassland food and the protection against predators. It is considered a bioindicator of the quality of coastal marine waters. It is important to monitor them and maintain these ecological communities as clean as possible. In this paper, we present an oceanographic buoy for Posidonia meadows monitoring. It is based on a set of low cost sensors which are able to collect data from water such as salinity, temperature, and turbidity and from the weather as temperature, relative humidity, and rainfall, among others. The system is mounted in a buoy which keeps it isolated to possible oxidation problems. Data gathered are processed using a microcontroller. Finally the buoy is connected with a base station placed on the mainland through a wireless connection using a FlyPort module. The network performance is checked in order to ensure that no delays will be generated on the data transmission. This proposal could be used to monitor other areas with special ecological interest and for monitoring and supervising aquaculture activities.

  14. Characterization of ASCAT measurements based on buoy and QuikSCAT wind vector observations

    Directory of Open Access Journals (Sweden)

    A. Bentamy

    2008-03-01

    Full Text Available The new scatterometer Advanced SCATterometer (ASCAT onboard MetOp-A satellite provides surface wind speed and direction over global ocean with a spatial resolution of 25 km square over two swaths of 550 km widths. The accuracy of ASCAT wind retrievals is determined through various comparisons with moored buoys. The comparisons indicate that the remotely sensed wind speeds and directions agree well with buoy data. The root-mean-squared differences of the wind speed and direction are less than 1.72 m/s and 18°, respectively. At global scale, ASCAT winds are compared with surface winds derived from QuikSCAT scatterometer. The results confirm the buoy analyses, especially for wind speed ranging between 3 m/s and 20 m/s. For higher wind conditions, ASCAT is biased low. The ASCAT underestimation with respect to QuikSCAT winds is wind speed dependent. The comparisons based on the collocated scatterometer data collected after 17 October 2007 indicate that there are significant improvements compared to previous periods.

  15. Characterization of ASCAT measurements based on buoy and QuikSCAT wind vector observations

    Directory of Open Access Journals (Sweden)

    A. Bentamy

    2008-12-01

    Full Text Available The new scatterometer Advanced SCATterometer (ASCAT onboard MetOp-A satellite provides surface wind speed and direction over global ocean with a spatial resolution of 25 km square over two swaths of 550 km widths. The accuracy of ASCAT wind retrievals is determined through various comparisons with moored buoys. The comparisons indicate that the remotely sensed wind speeds and directions agree well with buoy data. The root-mean-squared differences of the wind speed and direction are less than 1.72 m/s and 18°, respectively. At global scale, ASCAT winds are compared with surface winds derived from QuikSCAT scatterometer. The results confirm the buoy analyses, especially for wind speed ranging between 3 m/s and 20 m/s. For higher wind conditions, ASCAT is biased low. The ASCAT underestimation with respect to QuikSCAT winds is wind speed dependent. The comparisons based on the collocated scatterometer data collected after 17 of October 2007 indicate that there are significant improvements compared to previous periods.

  16. A Low-Cost Sensor Buoy System for Monitoring Shallow Marine Environments

    Directory of Open Access Journals (Sweden)

    Juan A. López

    2012-07-01

    Full Text Available Monitoring of marine ecosystems is essential to identify the parameters that determine their condition. The data derived from the sensors used to monitor them are a fundamental source for the development of mathematical models with which to predict the behaviour of conditions of the water, the sea bed and the living creatures inhabiting it. This paper is intended to explain and illustrate a design and implementation for a new multisensor monitoring buoy system. The system design is based on a number of fundamental requirements that set it apart from other recent proposals: low cost of implementation, the possibility of application in coastal shallow-water marine environments, suitable dimensions for deployment and stability of the sensor system in a shifting environment like the sea bed, and total autonomy of power supply and data recording. The buoy system has successfully performed remote monitoring of temperature and marine pressure (SBE 39 sensor, temperature (MCP9700 sensor and atmospheric pressure (YOUNG 61302L sensor. The above requirements have been satisfactorily validated by operational trials in a marine environment. The proposed buoy sensor system thus seems to offer a broad range of applications.

  17. 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.

  18. Surface heat budget over the Weddell Sea: Buoy results and model comparisons

    Science.gov (United States)

    Vihma, Timo; Uotila, Juha; Cheng, Bin; Launiainen, Jouko

    2002-02-01

    The surface heat budget over the Weddell Sea ice cover in 1996 was studied on the basis of data from Argos buoys equipped with meteorological sensors. In addition, a thermodynamic sea ice model, satellite-based data on the sea ice concentration, sonar results on ice thickness distribution, and output from large-scale meteorological models were all utilized. Applying the buoy data, the sensible heat flux over sea ice was calculated by Monin-Obukhov theory using the gradient method, and the latent heat flux was obtained by the bulk method. A second estimate for the surface fluxes was obtained from the thermodynamic sea ice model, which was forced by the buoy observations. The results showed a reasonable agreement. The dominating component in the heat budget over ice was the net longwave radiation, which had a mean annual cooling effect of -28 W m-2. This was balanced by the net shortwave radiation (annual mean 13 W m-2), the sensible (13 W m-2) and latent (-3 W m-2) heat fluxes, and the conductive heat flux through the ice (5 W m-2). The regional surface fluxes over the fractured ice cover were estimated using the buoy data and Special Sensor Microwave Imager (SSMI)-derived ice concentrations. In winter the regional surface sensible heat flux was sensitive to the ice concentration and thickness distribution. The estimate for the area-averaged formation rate of new ice in leads in winter varies from 0.05 to 0.21 m per month depending on the SSMI processing algorithm applied. Countergradient fluxes occurred 8-10% of the time. The buoy observations were compared with the operational analyses of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the reanalyses of the National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR). The 2 m air temperature and surface temperature were 3.5° and 4.4°C too high, respectively, in the ECMWF and 3.2° and 3.0°C too low in the NCEP/NCAR fields, but the models reproduced the

  19. 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...

  20. Assimilation of wave spectra from pitch-and-roll buoys in a North Sea wave model

    Science.gov (United States)

    Voorrips, A. C.; Makin, V. K.; Hasselmann, S.

    1997-03-01

    A technique for the assimilation of spectral wave observations in wave models is presented and tested. The method uses the concept of spectral partitioning to project the entire wave spectrum onto a few essential mean parameters. Model and observed partition parameters are assimilated using an optimal interpolation (OI) technique. After data reduction, obtained by the partitioning, the cost of the assimilation is negligible compared to the cost of the model run itself. Therefore the optimal interpolation of partitions (OI-P) method is a very attractive assimilation technique for operational wave forecasting. The paper focuses on the assimilation of pitch-and-roll buoy spectra in a North Sea version of the WAM wave model. Treatment of the (non-fully two-dimensional) buoy spectra is discussed. Appropriate choices for the OI weight functions are made. The problem of correlating wave partitions in different spectra is addressed, which is essential for obtaining a robust and efficient system. In order to assess the influence of spectral wave observations on the analysis of the sea state, the method is compared to a second scheme, optimal interpolation of integral parameters (OI-I), which can only be used to assimilate observations of significant wave height and mean wave period. First, tests with synthetic data are described, which illustrate advantages of the partitioning method over the OI-I scheme. Also, the inherent limitations of OI are shown in both methods. Experiments with buoy observations for actual North Sea conditions show the benefits of the system, especially when several wave systems are present at the same time.

  1. 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.

  2. Buoy and Generator Interaction with Ocean Waves: Studies of a Wave Energy Conversion System

    Energy Technology Data Exchange (ETDEWEB)

    Lindroth, Simon

    2011-07-01

    On March 13th, 2006, the Div. of Electricity at Uppsala Univ. deployed its first wave energy converter, L1, in the ocean southwest of Lysekil. L1 consisted of a buoy at the surface, connected through a line to a linear generator on the seabed. Since the deployment, continuous investigations of how L1 works in the waves have been conducted, and several additional wave energy converters have been deployed. This thesis is based on ten publications, which focus on different aspects of the interaction between wave, buoy, and generator. In order to evaluate different measurement systems, the motion of the buoy was measured optically and using accelerometers, and compared to measurements of the motion of the movable part of the generator - the translator. These measurements were found to correlate well. Simulations of buoy and translator motion were found to match the measured values. The variation of performance of L1 with changing water levels, wave heights, and spectral shapes was also investigated. Performance is here defined as the ratio of absorbed power to incoming power. It was found that the performance decreases for large wave heights. This is in accordance with the theoretical predictions, since the area for which the stator and the translator overlap decreases for large translator motions. Shifting water levels were predicted to have the same effect, but this could not be seen as clearly. The width of the wave energy spectrum has been proposed by some as a factor that also affects the performance of a wave energy converter, for a set wave height and period. Therefore the relation between performance and several different parameters for spectral width was investigated. It was found that some of the parameters were in fact correlated to performance, but that the correlation was not very strong. As a background on ocean measurements in wave energy, a thorough literature review was conducted. It turns out that the Lysekil project is one of quite few projects that

  3. 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.

  4. Comparison of ECMWF surface meteorology and buoy observations in the Ligurian Sea

    Directory of Open Access Journals (Sweden)

    R. Bozzano

    2004-01-01

    Full Text Available Since numerical weather prediction (NWP models are usually used to force ocean circulation models, it is important to investigate their skill in reproducing surface meteorological parameters in open sea conditions. Near-surface meteorological data (air temperature, relative humidity, barometric pressure, wind speed and direction have been acquired from several sensors deployed on an offshore large spar buoy in the Ligurian Sea (Northern Mediterranean Sea from February to December 2000. The buoy collected 7857 valid records out of 8040 during 335 days at sea.

    These observations have been compared with data from NWP models and specifically, the outputs of the ECMWF analysis in the two grid points closest to the buoy position. Hourly data acquired by the buoy have been undersampled to fit the data set of the model composed by values computed at the four synoptic hours. For each mentioned meteorological parameter an analysis has been performed by evaluating instantaneous synoptic differences, distributions, daily and annual variations and related statistics. The comparison shows that the model reproduces correctly the baric field while significant differences result for the other variables, which are more affected by local conditions. This suggests that the observed discrepancies may be due to the poor resolution of the model that probably is not sufficient to appropriately discriminate between land and ocean surfaces in a small basin such as the Ligurian Sea and to take into account local peculiarities.

    The use of time- and space-averaged model data reduces the differences with respect to the in situ observations, thus making the model data usable for analysis with minor requirements about time and space resolution.

    Although this comparison is strongly limited and we cannot exclude measurement errors, its results suggest a great caution in the

  5. Design of underwater video attached to buoy for observing shallow water substrate

    Science.gov (United States)

    Dingtian, Y.; Wenxi, C.; Delu, P.

    2007-01-01

    Knowledge of shallow water substrate is very important for protection and management of coastal ecosystem. Traditional methods for observing shallow water substrate was by sending diver to photography and recorded with eye, which was laborious and money taking. In order to obtain the easier way to study the shallow water substrate, an underwater video system was designed. Underwater video sensor, optical sensor, sonar sensor, tiltometer, GPS system, and ascending and descending system were all attached to the buoy system, and data was gathered and processed by the computer on the ship. The obtained data could be used for analyzing substrate type, activity of benthos and ground truth data for satellite remote sensing.

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

    DEFF Research Database (Denmark)

    Margheritini, Lucia; Steenstrup, Per Resen

    2013-01-01

    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...... 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...

  7. 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...... 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....

  8. KIC InnoEnergy Project Neptune: development of a floating LiDAR buoy for wind, wave and current measurements

    OpenAIRE

    Schuon, Frieder; González, Daniel; Rocadenbosch Burillo, Francisco; Bischoff, Oliver; Jané, R.

    2012-01-01

    The KIC-InnoEnergy project “NEPTUNE” develops a floating Lidar buoy and a hindcast- and forecast model for wind- wave- and current measurements of offshore wind farms. In this paper just the lidar buoy is presented and discussed: Main challenges, the design ideas and the steps to develop, test and prototype this product, which – according to the KIC-InnoEnergy project idea – should be commercialized after the project end, foreseen for the end of 2014. KIC-InnoEnergy is funded from the Europea...

  9. An Integer Precise Point Positioning technique for sea surface observations using a GPS buoy

    Science.gov (United States)

    Fund, F.; Perosanz, F.; Testut, L.; Loyer, S.

    2013-04-01

    GPS data dedicated to sea surface observation are usually processed using differential techniques. Unfortunately, the precision of resulting kinematic positions is baseline-length dependent. So, high precision sea surface observations using differential GPS techniques are limited to coasts, lakes, and rivers. Recent improvements in GPS satellite products (orbits, clocks, and phase biases) make phase ambiguity fixing at the zero difference level achievable and opens up the observation of the sea surface without geographical constraints. This paper recalls the concept of the Integer Precise Point Positioning technique and discusses the precision of GPS buoy positioning. A sequential version of the GINS software has been implemented to achieve single epoch GPS positioning. We used 1 Hz data from a two week GPS campaign conducted in the Kerguelen Islands. A GPS buoy has been moored close to a radar gauge and 90 m away from a permanent GPS station. This infrastructure offers the opportunity to compare both kinematic Integer Precise Point Positioning and classical differential GPS positioning techniques to in situ radar gauge data. We found that Precise Point Positioning results are not significantly biased with respect to radar gauge data and that horizontal time series are consistent with differential processing at the sub-centimetre precision level. Nevertheless, standard deviations of height time series with respect to radar gauge data are typically [4-5] cm. The dominant driver for noise at this level is attributed to errors in tropospheric estimates which propagate into position solutions.

  10. Tsunami records due to the 2010 Chile Earthquake observed by GPS buoys established along the Pacific coast of Japan

    Science.gov (United States)

    Kato, T.; Terada, Y.; Nagai, T.; Koshimura, S.

    2010-12-01

    The twelve GPS buoys that have been established along the Pacific coast of Japan succeeded to record the tsunami due to the 2010 Central Chile Earthquake (Mw8.8) that occurred on 06:34:14, 27th of February 2010 (UTC) according to USGS, which is on 15:34:14 of the same day by the Japanese Standard Time (JST). We have developed GPS buoy for detecting tsunami for over 12 years, considering that early detection of tsunami serves for mitigating tsunami disaster. The current GPS buoy is now operational at about 10km west of Cape Muroto, southwest Japan. The Ministry of Land, Infrastructure, Transport and Tourism has implemented the similar system with eleven GPS buoys along the Pacific coast of Japan as a part of the Nationwide Ocean Wave information network for Ports and HArbourS (NOWPHAS) system. All of these GPS buoys are located within 20km from the coast. The 2010 Central Chile earthquake generated significant tsunami. The tsunami travelled across the Pacific Ocean and reached the Japanese coasts in about one day. We present the records of tsunamis that have been registered at these GPS buoys. The presentation tries to compare the records with numerically simulated data. The record of experimental GPS buoy operated nearby Muroto is low-pass filtered with 120seconds of cut-off to segregate the long wave length tsunami from higher frequency wind waves. The effect of tide is also removed from the filtered record. The obtained record is visualized through internet facility (http://www.tsunamigps.com/gpsreal.php). The tsunami due to the Chile earthquake arrived at the GPS buoy at around 3:22PM of 28th February (JST), which is nearly one day after the earthquake. The first peak of tsunami is about 12 centimeter above the mean sea surface height. The second peak arrives about one hour and 46 minutes later with about 20cm height, which is the highest peak among the series of the tsunami waves. The later phases of recognizable tsunami waves continued about one day after the

  11. 33 CFR 149.560 - How must buoys used to define traffic lanes be marked and lighted?

    Science.gov (United States)

    2010-07-01

    ... 33 Navigation and Navigable Waters 2 2010-07-01 2010-07-01 false How must buoys used to define traffic lanes be marked and lighted? 149.560 Section 149.560 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) DEEPWATER PORTS DEEPWATER PORTS: DESIGN, CONSTRUCTION, AND EQUIPMENT Aids to Navigation Lights on...

  12. Design of the dual-buoy wave energy converter based on actual wave data of East Sea

    Directory of Open Access Journals (Sweden)

    Kim Jeongrok

    2015-07-01

    Full Text Available A new conceptual dual-buoy Wave Energy Converter (WEC for the enhancement of energy extraction efficiency is suggested. Based on actual wave data, the design process for the suggested WEC is conducted in such a way as to ensure that it is suitable in real sea. Actual wave data measured in Korea’s East Sea (position: 36.404 N° and 129.274 E° from May 1, 2002 to March 29, 2005 were used as the input wave spectrum for the performance estimation of the dual-buoy WEC. The suggested WEC, a point absorber type, consists of two concentric floating circular cylinders (an inner and a hollow outer buoy. Multiple resonant frequencies in proposed WEC affect the Power Ttake-off (PTO performance of the WEC. Based on the numerical results, several design strategies are proposed to further enhance the extraction efficiency, including intentional mismatching among the heave natural frequencies of dual buoys, the natural frequency of the internal fluid, and the peak frequency of the input wave spectrum.

  13. Development of a GPS buoy system for monitoring tsunami, sea waves, ocean bottom crustal deformation and atmospheric water vapor

    Science.gov (United States)

    Kato, Teruyuki; Terada, Yukihiro; Nagai, Toshihiko; Koshimura, Shun'ichi

    2010-05-01

    We have developed a GPS buoy system for monitoring tsunami for over 12 years. The idea was that a buoy equipped with a GPS antenna and placed offshore may be an effective way of monitoring tsunami before its arrival to the coast and to give warning to the coastal residents. The key technology for the system is real-time kinematic (RTK) GPS technology. We have successfully developed the system; we have detected tsunamis of about 10cm in height for three large earthquakes, namely, the 23 June 2001 Peru earthquake (Mw8.4), the 26 September 2003 Tokachi earthquake (Mw8.3) and the 5 September 2004 earthquake (Mw7.4). The developed GPS buoy system is also capable of monitoring sea waves that are mainly caused by winds. Only the difference between tsunami and sea waves is their frequency range and can be segregated each other by a simple filtering technique. Given the success of GPS buoy experiments, the system has been adopted as a part of the Nationwide Ocean Wave information system for Port and HArborS (NOWPHAS) by the Ministry of Land, Infrastructure, Transport and Tourism of Japan. They have established more than eight GPS buoys along the Japanese coasts and the system has been operated by the Port and Airport Research Institute. As a future scope, we are now planning to implement some other additional facilities for the GPS buoy system. The first application is a so-called GPS/Acoustic system for monitoring ocean bottom crustal deformation. The system requires acoustic waves to detect ocean bottom reference position, which is the geometrical center of an array of transponders, by measuring distances between a position at the sea surface (vessel) and ocean bottom equipments to return the received sonic wave. The position of the vessel is measured using GPS. The system was first proposed by a research group at the Scripps Institution of Oceanography in early 1980's. The system was extensively developed by Japanese researchers and is now capable of detecting ocean

  14. A Preliminary Study of a Buoy System for Acquisition, Transmission, and Management of Hydrological Data Obtained from In-situ Measurements

    Science.gov (United States)

    Elliott, J. M.

    1972-01-01

    The requirements for a system of remotely located, data collection buoys are considered first for a prototype system to be used in conjunction with the Earth Resources Technology Satellite (ERTS-A), and then for a more advanced system. The necessary sensor characteristics for compatibility with the ERTS-A data collection platforms are considered, as well as possible sites for location of the prototype buoys. The advanced system is considered from the standpoint of continuous data collection both through satellite data relay and ground telemetry systems. Management of the data from a buoy system is analyzed, especially with regard to the advanced system.

  15. 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

  16. Determining slack tide with a GPS receiver on an anchored buoy

    Directory of Open Access Journals (Sweden)

    M. Valk

    2014-07-01

    Full Text Available In this paper we present a novel method to determine the time of occurrence of tidal slack with a GPS receiver mounted on an anchored buoy commonly used to delineate shipping lanes in estuaries and tidal channels. Slack tide occurs when the tide changes direction from ebb to flood flow or from flood to ebb. The determination of this point in time is not only useful for shipping and salvaging, it is also important information for calibrating tidal models, for determining the maximum salt intrusion and for the further refinement of the theory on tidal propagation. The accuracy of the timing is well within 10 min and the method – able to operate in real time – is relatively cheap and easy to implement on a permanent basis or in short field campaigns.

  17. Validation Of MERIS-Derived Turbidity And Par Attenuation Using Autonomous Buoy Data

    Science.gov (United States)

    Vanhellemont, Quinten; Greenwood, Naomi; Ruddick, Kevin

    2013-12-01

    Ocean colour remote sensing is becoming well- established for the monitoring of coastal waters. However, validation of satellite-derived products remains problematic, as matchups of in situ data and cloud-free satellite data are costly and difficult to obtain with ship-based measurements. We present a validation of several MERIS algorithms for turbidity (T) and attenuation of photosynthetically active radiation (KPAR), using measurements from three autonomous buoys in coastal waters, two in the North Sea, and one in the Irish sea. In situ data were combined with marine reflectance spectra and level 2 products from multiple processing versions. The merged dataset contains several hundreds of matchups and allows for flexible testing of retrieval algorithms for T and KPAR. Autonomous systems prove to be powerful tools for validating satellite data in dynamic coastal waters, where changes occur quickly both in space and time.

  18. Improvement of economy of wave power generation by Backward Bent Duct Buoy (BBDB)

    International Nuclear Information System (INIS)

    Floating type wave power generator KAIMEI test by JAMSTEC certified mooring safety, long life of turbine and generator and cable line, but conversion efficiency from wave power to air-output was poor. This paper describes Backward Bent Duct Buoy (BBDB) which has high conversion efficiency, and it has frontward movement in wave by function of bent duct. In addition, improvement of turbine and generator solved technical problems, double rotor Wells turbine and Heller's Generator are introduced. High wave power locals on high latitude area, and east coast of ocean, for example, North-West of USA has very high wave power. BBDB is designed and power cost is calculated by water tank data, and sea test data and cost estimations by several sources and sea wave data. Power cost by BBDB on high wave area is estimated to be cheap enough for commercial use

  19. Perancangan Sistem Prediktor Daya Pada Panel Photovoltaic di Buoy Weather Station

    Directory of Open Access Journals (Sweden)

    Aini Prisilia Susanti

    2013-09-01

    Full Text Available Buoy weather station merupakan stasiun informasi cuaca yang banyak dijumpai di pelabuhan, khususnya di Surabaya. Untuk mengoperasikannya diperlukan sumber daya listrik berupa panel photovoltaic. Efek fotolistrik pada PV mampu merubah energi cahaya menjadi energi listrik. Besarnya daya yang dihasilkan tergantung dari intensitas matahari, temperatur permukaan, dan keadaan geografis setempat. Untuk memprediksi daya keluaran per setengah jam yang dihasilkan oleh panel PV maka digunakan metode jaringan syaraf tiruan dengan algoritma backpropagation pada software Matlab. Variabel yang digunakan berupa data daya yang diperoleh dari tegangan dan arus yang dihasilkan oleh panel PV di daerah Surabaya. Data daya selama 3 hari per setengah jam tersebut dijadikan data input dan target pada Matlab. Hasil terbaik perancangan sistem prediksi daya keluaran panel PV menggunakan JST pada Matlab yaitu Mean Square Error (MSE sebesar 0,0113 dan akurasi ketepatan prediksi sebesar 99,81%.

  20. Determining slack tide with a GPS receiver on an anchored buoy

    Science.gov (United States)

    Valk, M.; Savenije, H. H. G.; Tiberius, C. C. J. M.; Luxemburg, W. M. J.

    2014-07-01

    In this paper we present a novel method to determine the time of occurrence of tidal slack with a GPS receiver mounted on an anchored buoy commonly used to delineate shipping lanes in estuaries and tidal channels. Slack tide occurs when the tide changes direction from ebb to flood flow or from flood to ebb. The determination of this point in time is not only useful for shipping and salvaging, it is also important information for calibrating tidal models, for determining the maximum salt intrusion and for the further refinement of the theory on tidal propagation. The accuracy of the timing is well within 10 min and the method - able to operate in real time - is relatively cheap and easy to implement on a permanent basis or in short field campaigns.

  1. Theory and application of calibration techniques for an NDBC directional wave measurements buoy

    Science.gov (United States)

    Steele, K. E.; Lau, J. C.-K.; Hsu, Y.-H. L.

    1985-01-01

    The National Data Buoy Center (NDBC) of the National Oceanic and Atmospheric Administration (NOAA) deployed a 10-m-diameter discus-type hull in the Pacific Ocean some 185 km southwest of Los Angeles, CA, in April 1984. Aboard this hull was an electronic system capable of acquiring, processing, and transmitting to shore directional wave measurements. For this system to produce accurate data, a number of factors had to be taken into account. These factors included noise, amplitude and phase alterations due to mechanical and electrical components, and magnetic fields arising from the hull. Comprehensive calibration and verification techniques were developed and applied to ensure data quality. The system configuration is described with emphasis on the methods used in the data processing to correct for the various factors. Examples of the resulting corrected data are given.

  2. The M3A multi-sensor buoy network of the Mediterranean Sea

    Directory of Open Access Journals (Sweden)

    K. Nittis

    2006-08-01

    Full Text Available A network of three multi-sensor timeseries stations able to deliver real time physical and biochemical observations of the upper thermocline has been developed for the needs of the Mediterranean Forecasting System during the MFSTEP project. They follow the experience of the prototype M3A system that was developed during the MFSPP project and has been tested during a pilot pre-operational period of 22 months (2000–2001. The systems integrate sensors for physical (temperature, salinity, turbidity, current speed and direction as well as optical and chemical observations (dissolved oxygen, chlorophyll-a, PAR, nitrate. The south Aegean system (E1-M3A follows a modular design using independent mooring lines and collects biochemical data in the upper 100 m and physical data in the upper 500 m of the water column. The south Adriatic buoy system (E2-M3A uses similar instrumentation but on a single mooring line and also tests a new method of pumping water samples from relatively deep layers, performing analysis in the protected ''dry'' environment of the buoy interior. The Ligurian Sea system (W1-M3A is an ideal platform for air-sea interaction processes since it hosts a large number of meteorological sensors while its ocean instrumentation, with real time transmission capabilities, is confined in the upper 50 m layer. Despite their different architecture, the three systems have common sampling strategy, quality control and data management procedures. The network operates in the Mediterranean Sea since autumn 2004 collecting timeseries data for calibration and validation of the forecasting system as well for process studies of regional dynamics.

  3. The M3A multi-sensor buoy network of the Mediterranean Sea

    Directory of Open Access Journals (Sweden)

    F. Zanon

    2007-05-01

    Full Text Available A network of three multi-sensor timeseries stations able to deliver real time physical and biochemical observations of the upper thermocline has been developed for the needs of the Mediterranean Forecasting System during the MFSTEP project. They follow the experience of the prototype M3A system that was developed during the MFSPP project and has been tested during a pilot pre-operational period of 22 months (2000–2001. The systems integrate sensors for physical (temperature, salinity, turbidity, current speed and direction as well as optical and chemical observations (dissolved oxygen, chlorophyll-a, PAR, nitrate. The south Aegean system (E1-M3A follows a modular design using independent mooring lines and collects biochemical data in the upper 100 m and physical data in the upper 500 m of the water column. The south Adriatic buoy system (E2-M3A uses similar instrumentation but on a single mooring line and also tests a new method of pumping water samples from relatively deep layers, performing analysis in the protected "dry" environment of the buoy interior. The Ligurian Sea system (W1-M3A is an ideal platform for air-sea interaction processes since it hosts a large number of meteorological sensors while its ocean instrumentation, with real time transmission capabilities, is confined in the upper 50 m layer. Despite their different architecture, the three systems have common sampling strategy, quality control and data management procedures. The network operates in the Mediterranean Sea since autumn 2004 collecting timeseries data for calibration and validation of the forecasting system as well for process studies of regional dynamics.

  4. 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.

  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. 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...

  7. Current meter and temperature profile data from current meter and buoy casts in the North Pacific Ocean from 01 October 1997 to 31 August 1998 (NODC Accession 9800144)

    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 North Pacific Ocean from 01 October 1997 to 31 August 1998. Data...

  8. 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....

  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. Fall Freeze-up of Sea Ice in the Beaufort-Chukchi Seas Using ERS-1 SAR and Buoy Data

    Science.gov (United States)

    Holt, B.; Winebrenner, B.; D., Nelson E.

    1993-01-01

    The lowering of air temperatures below freezing in the fall indicates the end of summer melt and the onset of steady sea ice growth. The thickness and condition of ice that remains at the end of summer has ramifications for the thickness that that ice will attain at the end of the following winter. This period also designates a shifting of key fluxes from upper ocean freshening from ice melt to increased salinity from brine extraction during ice growth. This transitional period has been examined in the Beaufort and Chukchi Seas using ERS-1 SAR imagery and air temperatures from drifting buoys during 1991 and 1992. The SAR imagery is used to examine the condition and types of ice present in this period. Much of the surface melt water has drained off at this time. Air temperatures from drifting buoys coincident in time and within 100 km radius of the SAR imagery have been obtained...

  11. Analysis of floating debris behaviour in the Nakdong River basin of the southern Korean peninsula using satellite location tracking buoys.

    Science.gov (United States)

    Jang, Seon Woong; Kim, Dae Hyun; Seong, Ki Taek; Chung, Yong Hyun; Yoon, Hong Joo

    2014-11-15

    Most land-based debris enters the ocean via rivers during the rainy season. The Nakdong River system, the largest river entering the South Sea of Korea, discharges 3000 tons of debris per year. We deployed small tracking buoys with satellite location transmitters to monitor river-borne floating debris movement. The buoys moved for various distances depending on the change in flux in different regions. A hot spot was expected to contain a large accumulation of floating debris. The central and lower parts of the eastern downstream region were identified as important regions. The results of this study provide information related to the movement of debris that can be used when establishing a method for collection of floating debris from rivers and streams. The study contributes to efforts to decrease the amount of floating debris in oceans and the costs associated with debris removal by improving the effectiveness of preventative measures. PMID:25261180

  12. 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.

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

    OpenAIRE

    Masahiko Sasano; Motonobu Imasato; Hiroya Yamano; Hiroyuki Oguma

    2016-01-01

    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 dis...

  14. ASSIMILATION OF REAL-TIME DEEP SEA BUOY DATA FOR TSUNAMI FORECASTING ALONG THAILAND’S ANDAMAN COASTLINE

    Directory of Open Access Journals (Sweden)

    Seree Supharatid

    2008-01-01

    Full Text Available The occurrence of 2004 Indian Ocean tsunami enhanced the necessity for a tsunami early warning system for countries bordering the Indian Ocean, including Thailand. This paper describes the assimilation of real-time deep sea buoy data for tsunami forecasting along Thailand’s Andaman coastline. Firstly, the numerical simulation (by the linear and non-linear shallow water equations was carried out for hypothetical cases of tsunamigenic earthquakes with epicenters located in the Andaman micro plate. Outputs of the numerical model are tsunami arrival times and the maximum wave height that can be expected at 58 selected communities along Thailand Andaman coastline and two locations of DART buoys in the Indian Ocean. Secondly, a “neural” network model (GRNN was developed to access the data from the numerical computations for subsequent construction of a tsunami database that can be displayed on a web-based system. This database can be updated with the integration from two DART buoys and from several GRNN models.

  15. 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

  16. Accuracy in GPS/Acoustic positioning on a moored buoy moving around far from the optimal position

    Science.gov (United States)

    Imano, M.; Kido, M.; Ohta, Y.; Takahashi, N.; Fukuda, T.; Ochi, H.; Hino, R.

    2015-12-01

    For detecting the seafloor crustal deformation and Tsunami associated with large earthquakes in real-time, it is necessary to monitor them just above the possible source region. For this purpose, we have been dedicated in developing a real-time continuous observation system using a multi-purpose moored buoy. Sea-trials of the system have been carried out near the Nanakai trough in 2013 and 2014 (Takahashi et al., 2014). We especially focused on the GPS/Acoustic measurement (GPS/A) in the system for horizontal crustal movement. The GPS/A on a moored buoy has a critical drawback compared to the traditional ones, in which the data can be stacked over ranging points fixed at an optimal position. Accuracy in positioning with a single ranging from an arbitrary point is the subject to be improved in this study. Here, we report the positioning results in the buoy system using data in the 2014 sea-trial and demonstrate the improvement of the result. We also address the potential resolving power in the positioning using synthetic tests. The target GPS/A site consists of six seafloor transponders (PXPs) forming a small inner- and a large outer-triangles. The bottom of the moored cable is anchored nearly the center of the triangles. In the sea-trial, 11 times successive ranging was scheduled once a week, and we plotted positioning results from different buoy position. We confirmed that scatter in positioning using six PXPs simultaneously is ten times smaller than that using individual triangle separately. Next, we modified the definition of the PXP array geometry using data obtained in a campaign observation. Definition of an array geometry is insensitive as far as ranging is made in the same position, however, severely affects the positioning when ranging is made from various positions like the moored buoy. The modified PXP array is slightly smaller and 2m deeper than the original one. We found that the scatter of positioning results in the sea-trial is reduced from 4m to 1

  17. The Mobile Buoy: An Autonomous Surface Vehicle for Integrated Ocean-Atmosphere Studies

    Science.gov (United States)

    Orton, P. M.; McGillis, W. R.; Moisan, J. R.; Higinbotham, J. R.; Schirtzinger, C.

    2009-05-01

    A solar-powered Autonomous Surface Vessel (ASV) called OASIS (Ocean-Atmosphere Sensor Integration System) has been developed that makes measurements spanning the ocean mixed layer and lower atmospheric surface layer. An OASIS ASV can be remotely commanded to act as a boat, drifter, or untethered buoy (when programmed to keep at a station). OASIS has performed cross-shelf transect surveys within the mid-Atlantic Bight (63 km), Gulf of Maine, and additional field tests to develop techniques to map harmful algal blooms. One example of the utility of the OASIS ASV is with carbon dioxide (CO2) fluxes - predicting future climate change will require that scientists understand what controls exchanges of carbon dioxide between the atmosphere and ocean interior. OASIS measurements from the Gulf of Maine transect included surface ocean CO2 partial pressures from 320 to 670 μatm, air-sea CO2 sea-to-air fluxes from -3.2 to +12.2 mmol m2 d-1, upper ocean currents (0-50 m depth), surface ocean fluorescence, temperature and salinity, and several additional measurements. We are also installing a cabled, autonomous ocean mixed- layer hydrographic profiling system for future deployments. The complete integration of atmosphere and ocean measurements onboard an autonomous navigating vehicle is a key advance for ocean observation technology and observational science programs. ASVs have great potential for ocean and climate studies, and can become a major component of earth observation systems in the coming decades.

  18. Blending sequential scanning multichannel microwave radiometer and buoy data into a sea ice model

    Science.gov (United States)

    Thomas, D. R.; Rothrock, D. A.

    1989-08-01

    A method is presented for determining the concentrations of open water and of several ice types using multichannel satellite passive microwave data. The method uses the Kalman filter and provides the "best fit" to a time series of data. A crucial element of the procedure is a physical model of how the concentrations of ice types change with time in response to freezing, melting, aging of one ice type to another, and creation of open water by divergence of the ice cover. A measurement model relates the state of the ice cover to the multivariate microwave data. The procedure offers three distinct advantages over algorithms that interpret separately data from each instant in time: it provides a framework for incorporating additional data into the diagnosis of ice concentrations, it takes into account the known uncertainty in the microwave observations and the pure type signatures, and it allows the resolution of ice types with ambiguous signatures. Two examples are presented which make use of scanning multichannel microwave radiometer data and surface temperature and ice velocity data from drifting buoys to estimate the concentrations of open water, first-year, second-year, and older multiyear ice for a Lagrangian region of ice. Two other examples include melt ponds in place of second-year ice. Some of the parameters in the physical model (melt rates) and in the measurement model (signature of second-year ice or of frozen melt ponds) are unknown. Reasonable, but arbitrary, values of the unknown parameters are used in the examples.

  19. 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.

  20. Temperature profile and current meter data collected using drifting buoy and profiling buoy casts from the Atlantic Ocean as part of the International Decade of Ocean Exploration / Mid-Ocean Dynamics Experiment (IDOE/MODE) project from 01 September 1972 to 01 April 1974 (NODC Accession 7400622)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profile east-west current component, north-south current component, and other data were collected using drifting buoy and profiling float casts from the...

  1. Near real-time monitoring of flow velocity and direction in the floating ice tongue of the Shirase Glacier using low-cost GPS buoys

    Science.gov (United States)

    Aoyama, Yuichi; Doi, Koichiro; Shibuya, Kazuo; Ohta, Harumi; Tsuwa, Iuko

    2013-02-01

    The horizontal velocity vector of ice flow on the floating ice tongue of the Shirase Glacier, East Antarctica, was determined using two GPS buoys located on its east and west sides. The GPS buoys consisted of a single-frequency GPS receiver module and an Iridium satellite communication system. The instantaneous horizontal position of each GPS buoy was automatically obtained every 30 minutes, and the data were immediately transmitted to the National Institute of Polar Research (NIPR), Tokyo, Japan, via a satellite link. The location data demonstrated that the floating ice tongue moved primarily in a linear manner during the monitoring period between February and April, 2010. The speed and azimuth of the eastern buoy were (5.779 ± 0.004 m/day, N1.4°E ± 0.5°), respectively, while for the western buoy the speed and azimuth were (7.005 ± 0.006 m/day, N13.1°W ± 0.6°), respectively. Short-term variations about the mean speed and azimuth of the ice flow, with a period of 3-10 days, were also identified.

  2. Temperature profile and other data collected using moored buoy in the Pacific Ocean (30-N to 30-S) as part of the International Decade of Ocean Exploration / North Pacific Experiment (IDOE/NORPAX) project from 06 November 1977 to 24 March 1978 (NODC Accession 8200053)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Air pressure, current, wind and temperature time series data were collected from moored buoys from TOGA Area in Pacific (30 N to 30 S). Buoy data from the...

  3. Ocean Wave Parameters Retrieval from TerraSAR-X Images Validated against Buoy Measurements and Model Results

    Directory of Open Access Journals (Sweden)

    Weizeng Shao

    2015-09-01

    Full Text Available An ocean surface wave retrieval algorithm, Parameterized First-guess Spectrum Method (PFSM, which was initially developed for C-band Synthetic Aperture Radar (SAR, is modified to extract wave parameters from X-band TerraSAR-X (TS-X images. Wave parameters, including significant wave height (SWH and mean wave period (MWP were extracted from nine TS-X HH-polarization images and were compared to in situ buoy measurements. The range of these wave retrievals is from 1 to 5 m of SWH and from 2 to 10 s of MWP. The retrieval accuracy could reach 80%. After that, a total of 16 collected TS-X HH-polarization images were used to invert wave parameters and then the retrieval results were compared to the operational WAVEWATCH-III wave model results. The SAR and in situ buoy wave comparison shows a 0.26 m Root-Mean-Square Error (RMSE of SWH and a 19.8% of Scatter Index (SI. The SAR and WAVEWATCH-III model comparison yields slightly worse results with an RMSE of 0.43 m of SWH and a 32.8% of SI. For MWP, the SAR and buoy comparison shows the RMSE is 0.45 s with an SI of 26%, which is better than the results from the SAR and WAVEWATCH-III model comparison. Our results show that the PFSM algorithm is suitable to estimate wave parameters from X-band TS-X data.

  4. Comparison Of High Winds Retrieved From RADARSAT 2 SAR Data With In Situ Buoy Data And QuikScat Wind Vectors

    Science.gov (United States)

    Xie, Tao; Perrie, Will

    2010-04-01

    Selected SAR images of high wind speeds have been obtained from RADARSAT-2 co-located with in situ observations from the HurricaneWatch program. In this presentation we use these RADARSAT-2 SAR images to retrieve ocean surface wind speeds, using CMOD_IFR, and modified algorithms. We compare these SAR- derived winds with in situ buoy data and QuikScat wind vectors. Results shows that SAR-derived wind speeds from CMOD5 are closer to the in situ buoy wind speeds than CMOD_IFR2 or CMOD4 winds. Moreover, these SAR-derived wind speeds are underestimates of the actual wind fields, especially in high wind conditions, whereas QuikScat wind vectors are overestimates. We also find that the wind speed discrepancies between buoy measurements and SAR-derived winds occurring in unstable atmosphere boundary conditions may be larger than those occurring in stable conditions.

  5. 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...

  6. Virtual radar ice buoys – a method for measuring fine-scale dynamic properties of sea ice

    Directory of Open Access Journals (Sweden)

    J. Karvonen

    2015-09-01

    Full Text Available Here we present an algorithm for continuous ice dynamics estimation based on coastal and ship radar data. The ice dynamics are estimated based on automatically selected ice targets in the images. These targets are here called virtual buoys (VB's and are tracked based on an optical flow method. To maintain continuous ice drift tracking new VB's are added after a~given number of VB's have been lost i.e. they can not be tracked reliably any more. Some tracking results and some computed derived quantities for a~few test cases are presented.

  7. 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.

  8. Comparison and analysis of Envisat ASAR ocean wave spectra with buoy data in the northern Pacific Ocean

    Institute of Scientific and Technical Information of China (English)

    REN Qifeng; ZHANG Jie; MENG Junmin; SONG Pingjian

    2011-01-01

    The validation and assessment of Envisat advanced synthetic aperture radar (ASAR) ocean wave spectra products are important to their application in ocean wave numerical predictions. Six-year ASAR wave spectra data are compared with one-dimensional (1D) wave spectra of 55 co-located moored buoy observations in the northern Pacific Ocean. The ASAR wave spectra data are firstly quality control filtered and spatio-temporal matched with buoy data. The comparisons are then performed in terms of 1D wave spectra, significant wave height (SWH) and mean wave period (MWP) in different spatio-temporal offsets respectively. SWH comparison results show the evident dependence of SWH biases on wind speed and the ASAR SWH saturation effect. The ASAR wave spectra tend to underestimate SWH at high wind speeds and overestimate SWH at low wind speeds. MWP comparison results show that MWP has a systematic bias and therefore it should be bias-modified before used. The comparisons of 1D wave spectra show that both wave spectra agree better at low frequencies than at high frequencies, which indicates the ASAR data cannot resolve the high frequency waves.

  9. Tsunami records due to the 2010 Chile Earthquake observed by GPS buoys established along the Pacific coast of Japan

    Science.gov (United States)

    Kato, Teruyuki; Terada, Yukihiro; Nishimura, Hitoyoshi; Nagai, Toshihiko; Koshimura, Shun'ichi

    2011-06-01

    A GPS buoy operating about 10 km west of Cape Muroto, southwest Japan, recorded the tsunami due to the 2010 Central Chile Earthquake ( M w 8.8) that occurred on 27 February, 2010. The tsunami due to the Chile Earthquake arrived at the GPS buoy almost one day after the earthquake. The first peak of the tsunami was about 12 cm above the mean sea level. The second peak arrived about one hour and 46 minutes later and was about 20 cm higher than the mean sea level, which was the highest peak among the series of the tsunami waves. The later phases of recognizable tsunami waves continued for about one day after the first arrival of the tsunami. Comparison of these tsunami records with numerically-predicted tsunami suggests that the observed tsunami arrived about 30 minutes later than the arrival time predicted by the numerical simulation. If we manually shift the record on the time series, we find that a longer term of about 1 hour period components fit very well whereas a shorter term of 10-30 minutes of tsunami components shows significant phase shifts. This difference of phase shifts might be due to the effect of dispersion of the tsunami wave.

  10. 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.

  11. 33 CFR 149.565 - What are the required characteristics and intensity of lights on buoys used to define traffic lanes?

    Science.gov (United States)

    2010-07-01

    ... 33 Navigation and Navigable Waters 2 2010-07-01 2010-07-01 false What are the required characteristics and intensity of lights on buoys used to define traffic lanes? 149.565 Section 149.565 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) DEEPWATER PORTS DEEPWATER PORTS: DESIGN, CONSTRUCTION, AND...

  12. 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.

  13. 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

  14. 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.

  15. Mapping near-inertial variability in the SE Bay of Biscay from HF radar data and two offshore moored buoys

    Science.gov (United States)

    Rubio, A.; Reverdin, G.; Fontán, A.; González, M.; Mader, J.

    2011-10-01

    HF radar surface current data together with data from two operational offshore oceanographic buoys located over the slope are used to map the variability associated with the near-inertial waves, during a target year (2009), in the SE Bay of Biscay. The results obtained show the complex 4D distribution of inertial oscillations in this area. We find a very pronounced horizontal structure across the area with ranges of a factor 5 in near-inertial kinetic energy. This pattern presents also strong seasonal variability, with a peak in KE closer to the shelf-break in summer, whereas winter maximum is weaker and located further to the north-east. The mooring data indicate more trapping near the surface in summer. These patterns are discussed in relation to the known seasonal differences in atmospheric/buoyancy forcing and the characteristics of the sub-inertial surface velocity field.

  16. Characterization Of Ocean Wind Vector Retrievals Using ERS-2 High-Resolution Long-Term Dataset And Buoy Measurements

    Science.gov (United States)

    Polverari, F.; Talone, M.; Crapolicchio, R. Levy, G.; Marzano, F.

    2013-12-01

    The European Remote-sensing Satellite (ERS)-2 scatterometer provides wind retrievals over Ocean. To satisfy the needs of high quality and homogeneous set of scatterometer measurements, the European Space Agency (ESA) has developed the project Advanced Scatterometer Processing System (ASPS) with which a long-term dataset of new ERS-2 wind products, with an enhanced resolution of 25km square, has been generated by the reprocessing of the entire ERS mission. This paper presents the main results of the validation work of such new dataset using in situ measurements provided by the Prediction and Research Moored Array in the Tropical Atlantic (PIRATA). The comparison indicates that, on average, the scatterometer data agree well with buoys measurements, however the scatterometer tends to overestimates lower winds and underestimates higher winds.

  17. 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.

  18. 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.

  19. 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...

  20. 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...

  1. 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...

  2. 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)....

  3. 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...

  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. 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.,...

  6. CRED Sea Surface Temperature (SST) Buoy; AMSM, TUT; Long: -170.56228, Lat: -14.28372 (WGS84); Sensor Depth: 0.33m; Data Range: 20060218-20080223.

    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. 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...

  8. CRED Sea Surface Temperature (SST) Buoy; AMSM, TUT; Long: -170.56228, Lat: -14.28372 (WGS84); Sensor Depth: 0.33m; Data Range: 20020729-20040217.

    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, LIS; Long: -173.91610, Lat: 25.96767 (WGS84); Sensor Depth: 0.33m; Data Range: 20030724-20041009.

    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: -170.72200, 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...

  11. 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...

  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; AMSM, TUT; Long: -170.76310, Lat: -14.36667 (WGS84); Sensor Depth: 0.19m; Data Range: 20070616-20080115.

    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 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...

  15. 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...

  16. CRED Sea Surface Temperature (SST) Buoy; PRIA, WAK; Long: 166.62210, Lat: 19.30740 (WGS84); Sensor Depth: 0.19m; Data Range: 20070501-20090118.

    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 Sea Surface Temperature (SST) Buoy; PRIA, PAL; Long: -162.06183, Lat: 05.88278 (WGS84); Sensor Depth: 0.19m; Data Range: 20060324-20070514.

    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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. CRED Sea Surface Temperature (SST) Buoy; PRIA, PAL; Long: -162.04044, Lat: 05.87450 (WGS84); Sensor Depth: 0.19m; Data Range: 20080402-20091124.

    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 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.,...

  7. 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...

  8. 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...

  9. 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...

  10. Drifting buoy and other data from the Bering Sea as part of the Outer Continental Shelf Environmental Assessment Program (OCSEAP) from 13 September 1975 to 25 September 1975 (NODC Accession 7600632)

    Data.gov (United States)

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

  11. Drifting buoy and other data from the Bering Sea as part of the Outer Continental Shelf Environmental Assessment Program (OCSEAP) from 27 May 1977 to 07 January 1978 (NODC Accession 7800692)

    Data.gov (United States)

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

  12. 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...

  13. Drifting buoy and other data from the Gulf of Alaska as part of the Outer Continental Shelf Environmental Assessment Program (OCSEAP) from 26 October 1980 to 27 March 1981 (NODC Accession 8200115)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Drifting buoy data was collected from the Gulf of Alaska by the Science Application INC (SAI) as part of the Outer Continental Shelf Environmental Assessment...

  14. 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...

  15. 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...

  16. 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...

  17. 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.,...

  18. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); NWHI, PHR; Long: -175.81595, Lat: 27.85396 (WGS84); Sensor Depth: 0.91m; Data Range: 20060915-20080922.

    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 Sea Surface Temperature (SST) Buoy; AMSM, TUT; Long: -170.56228, Lat: -14.28372 (WGS84); Sensor Depth: 0.33m; Data Range: 20020212-20020522.

    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. 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...

  1. 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....

  2. 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...

  3. 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;...

  4. 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....

  5. 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.,...

  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: 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.,...

  7. 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...

  8. CRED Sea Surface Temperature (SST) Buoy; CNMI, PAG; Long: 145.75743, Lat: 18.12728 (WGS84); Sensor Depth: 0.33m; Data Range: 20050906-20070604.

    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, MID; Long: -177.34402, Lat: 28.21788 (WGS84); Sensor Depth: 0.33m; Data Range: 20020920-20030727.

    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, TAU; Long: -169.41890, Lat: -14.23567 (WGS84); Sensor Depth: 0.33m; Data Range: 20020214-20020317.

    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, 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...

  12. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); NWHI, MAR; Long: -170.63382, Lat: 25.44643 (WGS84); Sensor Depth: 1.00m; 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.,...

  13. 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.,...

  14. 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.,...

  15. 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.,...

  16. 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 November 1999 to 30 November 1999 (NODC Accession 0000120)

    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....

  17. 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....

  18. 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 December 2000 to 30 December 2000 (NODC Accession 0000128)

    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....

  19. Significant Wave Heights, Periods, and Directions, and Air and Sea Temperature Data from a Directional Waverider Buoy off Diamond Head, Oahu during March-April 2000 (NODC Accession 0000475)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A directional waverider buoy located about one nautical mile south of Diamond Head, Oahu, provided an approximately 10-day time series of wave characteristics and...

  20. 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,...

  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: 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.,...

  2. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Environmental Data Logger (EDL); AMSM, ROS; Long: -168.16018, Lat: -14.55140 (WGS84); Sensor Depth: 0.00m; Data Range: 20040208-20060307.

    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) Standard Buoy, Supplemental Sea Surface Temperature Recorder (SBE39); AMSM, ROS; Long: -168.16018, Lat: -14.55140 (WGS84); Sensor Depth: 1.00m; Data Range: 20020224-20020420.

    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) 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.,...

  5. 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.,...

  6. 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.,...

  7. 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.,...

  8. 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.,...

  9. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); PRIA, PAL; Long: -162.10283, Lat: 05.88468 (WGS84); Sensor Depth: 1.00m; Data Range: 20020315-20021023.

    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.,...

  10. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); 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.,...

  11. 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.,...

  12. 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.,...

  13. 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.,...

  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: 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.,...

  15. 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.,...

  16. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); CNMI, SAI; Long: 145.72285, Lat: 15.23750 (WGS84); Sensor Depth: 1.00m; Data Range: 20040622-20050227.

    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. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); AMSM, ROS; Long: -168.16025, Lat: -14.55134 (WGS84); Sensor Depth: 1.00m; 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.,...

  18. 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.,...

  19. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Supplemental Sea Surface Temperature Recorder (SBE39); NWHI, PHR; Long: -175.81590, Lat: 27.85408 (WGS84); Sensor Depth: 1.00m; Data Range: 20020505-20020810.

    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. 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.,...

  1. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); NWHI, PHR; Long: -175.81612, Lat: 27.85325 (WGS84); Sensor Depth: 1.00m; Data Range: 20020918-20030314.

    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, 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.,...

  3. 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.,...

  4. 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.,...

  5. 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.,...

  6. 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.,...

  7. 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.,...

  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 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.,...

  10. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); AMSM, ROS; Long: -168.16018, Lat: -14.55140 (WGS84); Sensor Depth: 1.00m; Data Range: 20040209-20041002.

    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. 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.,...

  12. 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.,...

  13. 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.,...

  14. 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: 20030721-20030823.

    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, 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.,...

  16. 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.,...

  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. CRED Coral Reef Early Warning System (CREWS) Enhanced Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); 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.,...

  19. 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.,...

  20. 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.,...

  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: 20020724-20020920.

    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); AMSM, ROS; Long: -168.16018, Lat: -14.55140 (WGS84); Sensor Depth: 0.00m; Data Range: 20020224-20040208.

    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: -162.10280, Lat: 05.88468 (WGS84); Sensor Depth: 1.00m; Data Range: 20060326-20080401.

    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) 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.,...

  5. 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.,...

  6. CRED Coral Reef Early Warning System (CREWS) Standard Buoy, Sea Surface Temperature and Conductivity Recorder (SBE37); NWHI, MAR; Long: -170.63382, Lat: 25.44643 (WGS84); Sensor Depth: 1.00m; Data Range: 20040924-20051014.

    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.,...

  7. 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.,...

  8. 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...

  9. CRED Sea Surface Temperature (SST) Buoy; NWHI, LAY; Long: -171.74252, Lat: 25.77290 (WGS84); Sensor Depth: 0.33m; Data Range: 20030724-20040923.

    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; NWHI, MID; Long: -177.34402, Lat: 28.21788 (WGS84); Sensor Depth: 0.33m; Data Range: 20030729-20041001.

    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; NWHI, NEC; Long: -164.69775, Lat: 23.57152 (WGS84); Sensor Depth: 0.33m; Data Range: 20050410-20060108.

    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 Sea Surface Temperature (SST) Buoy; AMSM, TUT; Long: -170.83335, Lat: -14.32823 (WGS84); Sensor Depth: 0.33m; Data Range: 20020228-20020531.

    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, LIS; Long: -173.91608, Lat: 25.96768 (WGS84); Sensor Depth: 0.33m; Data Range: 20020917-20030723.

    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 Sea Surface Temperature (SST) Buoy; AMSM, TUT; Long: -170.72200, Lat: -14.28428 (WGS84); Sensor Depth: 0.33m; Data Range: 20020729-20031227.

    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...

  15. CRED Sea Surface Temperature (SST) Buoy; AMSM, TUT; Long: -170.72247, Lat: -14.28437 (WGS84); Sensor Depth: 0.33m; Data Range: 20060220-20080219.

    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...

  16. CRED Sea Surface Temperature (SST) Buoy; NWHI, NEC; Long: -164.69775, Lat: 23.57152 (WGS84); Sensor Depth: 0.33m; Data Range: 20020911-20030713.

    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 Sea Surface Temperature (SST) Buoy; PRIA, JAR; Long: -159.97426, Lat: -00.37555 (WGS84); Sensor Depth: 0.33m; Data Range: 20080327-20090223.

    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...

  18. CRED Sea Surface Temperature (SST) Buoy; NWHI, LAY; Long: -171.74252, Lat: 25.77290 (WGS84); Sensor Depth: 0.33m; Data Range: 20020915-20030722.

    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, 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...

  20. CRED Sea Surface Temperature (SST) Buoy; CNMI, GUA; Long: 144.80047, Lat: 13.52900 (WGS84); Sensor Depth: 0.33m; Data Range: 20051005-20070513.

    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...

  1. CRED Sea Surface Temperature (SST) Buoy; AMSM, TUT; Long: -170.56225, Lat: -14.28368 (WGS84); Sensor Depth: 0.33m; Data Range: 20080223-20090420.

    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 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...

  3. 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...

  4. 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....

  5. 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 May 2000 to 31 May 2000 (NODC Accession 0000169)

    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....

  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 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....

  7. Research on detection model of passive directional buoys%被动定向浮标探潜模型研究

    Institute of Scientific and Technical Information of China (English)

    战和; 杨日杰; 金中原

    2016-01-01

    In Anti-Submarine Warfare, passive directional sonar buoy is a main method to detect submarine. When two directional buoys have detected the same underwater target at the same time, its position could be fixed. A model about how to lay the supplementary passive directional buoys is researched to fix the position of underwater target in the condition that one and only one directional buoy in the original array has affirmed the existence of underwater target, but could not fix its position. According to the motion features of both underwater target and antisubmarine aircraft, sup-plementary dropping model of passive directional buoy is established in consideration that all possible situations may occur in practice. By simulation, the detection efficiency of the model is analyzed and the applicability is proved. All of these provide a theoretical foundation for tactical uses of passive directional buoys.%反潜战中,被动定向声呐浮标是一种主要的探潜手段,两枚被动定向浮标同时发现目标即可对其进行定位。研究了初始浮标阵中仅有一枚浮标能够发现目标但不能实现定位的情况下,如何通过补投被动定向浮标对目标进行定位的模型问题。根据水下目标和反潜机的运动特点,将实际中所有可能出现的情况进行了分类讨论,建立了被动定向浮标的补投模型。通过仿真分析了模型的探测效能,验证了模型的正确性和可用性,为被动定向浮标的战术使用提供了一定的理论基础。

  8. An experimental study of the effect of mooring systems on the dynamics of a SPAR buoy-type floating offshore wind turbine

    Directory of Open Access Journals (Sweden)

    Hong Sinpyo

    2015-05-01

    Full Text Available An experimental study of the effect of mooring systems on the dynamics of a SPAR buoy-type floating offshore wind turbine is presented. The effects of the Center of Gravity (COG, mooring line spring constant, and fair-lead location on the turbine’s motion in response to regular waves are investigated. Experimental results show that for a typical mooring system of a SPAR buoy-type Floating Offshore Wind Turbine (FOWT, the effect of mooring systems on the dynamics of the turbine can be considered negligible. However, the pitch decreases notably as the COG increases. The COG and spring constant of the mooring line have a negligible effect on the fairlead displacement. Numerical simulation and sensitivity analysis show that the wind turbine motion and its sensitivity to changes in the mooring system and COG are very large near resonant frequencies. The test results can be used to validate numerical simulation tools for FOWTs.

  9. An experimental study of the effect of mooring systems on the dynamics of a SPAR buoy-type floating offshore wind turbine

    Science.gov (United States)

    Hong, Sinpyo; Lee, Inwon; Park, Seong Hyeon; Lee, Cheolmin; Chun, Ho-Hwan; Lim, Hee Chang

    2015-09-01

    An experimental study of the effect of mooring systems on the dynamics of a SPAR buoy-type floating offshore wind turbine is presented. The effects of the Center of Gravity (COG), mooring line spring constant, and fair-lead location on the turbine's motion in response to regular waves are investigated. Experimental results show that for a typical mooring system of a SPAR buoy-type Floating Offshore Wind Turbine (FOWT), the effect of mooring systems on the dynamics of the turbine can be considered negligible. However, the pitch decreases notably as the COG increases. The COG and spring constant of the mooring line have a negligible effect on the fairlead displacement. Numerical simulation and sensitivity analysis show that the wind turbine motion and its sensitivity to changes in the mooring system and COG are very large near resonant frequencies. The test results can be used to validate numerical simulation tools for FOWTs.

  10. 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.

  11. Optimal station arrangement of multi-buoy positioning system%多浮标定位系统最优布站分析

    Institute of Scientific and Technical Information of China (English)

    孙国振; 董真杰; 连丽婷

    2013-01-01

    In multi-station and multi-buoy positioning systems, the system positioning error is influenced by different station arrangement methods and the number of buoy stations. The optimal objective function of the positioning sys-tem was deduced from the error function. The improvement method for sonar positioning accuracy in limited condi-tions was proposed. By analyzing the basic station arrangement and the relationship between precision and station ar-rangement, three kinds of station arrangement methods were compared according to the proposed method. Experi-mental results showed consistent performance as the actual situation. The relationships between the precision and the number of buoy stations, the radius of buoy station and station location were discussed from simulation, indicating that the proposed method could achieve the best arrangement of buoy stations and the best radius of the stations.%针对多基地、多浮标定位系统,不同的布站方式、布站数量对系统定位误差均有一定影响。从定位误差方程推导出定位误差最优目标函数,探讨了在有限的条件下如何提高系统定位精度,给出了精度与布站数、布站距离、布站位置之间的关系。通过分析基本布站方式,以及布站方式与精度之间的关系,根据得到的分析方法,对三种布站方式进行了精度分析,得到了与实际情况相符的结果。通过Matlab仿真,给出了3~8个浮标与定位精度的效果图示,分析了布站数与定位范围、布站半径与布站面积之间的关系,并得到最佳布站方式及布站半径,在实际应用中具有较好的参考价值和指导意义。

  12. 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.

  13. The seasonal variation of undercurrent and temperature in the equatorial Pacific jointly derived from buoy measurement and assimilation analysis

    Institute of Scientific and Technical Information of China (English)

    SUN Jilin; CHU Peter; LIU Qinyu

    2004-01-01

    Based on the TOGA-TAO buoy chain observed data in the equatorial Pacific and the assimilation analysis results from SODA(simple ocean data assimilation analysis), the role of the meridional cells in the subsurface of the tropical Pacific was discussed. It was found that, the seasonal varying direction of EUC(the quatorial Undercurrent)in the Peacific is westwards beginning from the eastern equatorial Pacific in the boreal spring. The meridional cell south of the equator plays important role on this seasonal change of EUC.On the other hand, although the varying direction is westwards,the seasonal variation of temperature in the same region gets its minimum values in the boreal anttmm beginning from the eastern equatorial Pacific.The meridional cell north of the equator is most responsible for the seasonal temperature variation in the eastern equatorial Pacific while the meridional cell south of the equator mainly controls the seasonal temperature change in the central Pacific. It is probably true that the asymmetry by the equator is an important factor influencing the seasonal cycle of EUC and temperature in the tropical Pacific.

  14. 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.

  15. Modeling and simulation the probability of searching submarine based on passive buoy array%被动浮标阵对潜搜索概率建模与仿真

    Institute of Scientific and Technical Information of China (English)

    罗光成; 杨日杰; 张丹

    2011-01-01

    浮标搜潜是1种主要的航空探潜方式,投放浮标的数量及阵形决定着搜潜效能.由于机载浮标数量有限,正确地计算当前阵型的搜索概率尤为重要.以应召搜潜为背景,结合被动浮标作战使用,对水下潜艇分布规律进行分析,建立了被动浮标阵的对潜探测概率模型,并仿真分析潜艇分布规律对模型探测概率的影响,为部队训练被动浮标的使用提供了参考.%Sonobuoy anti-submarine is a major method for the air anti-submarine,and the number of buoys in launching determine the efficiency of searching submarine. Due to the limited number of airborne buoy.it is important to calculate correctly the formation of the search probability. As a background of summoned searching submarine, this paper has combined with the passive buoy using to analysis the distribution of submarine underwater, and established a passive buoy arrays for submarine detection probability model,and analyzed the efficiency of submarine distribution and model probability of detecting. It provided a reference of passive buoy for troop training.

  16. 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.

  17. A system for ocean ambient noise measurement based on subsurface buoy%基于潜标的海洋环境噪声测量系统

    Institute of Scientific and Technical Information of China (English)

    吕云飞; 张殿伦; 邹吉武; 兰华林; 孙大军

    2009-01-01

    This paper aims to design the system of ocean ambient noise measurement, the system is deployed with subsurface buoy, low frequency ambient noise of shallow water is measured by vector hydrophone. Vector hydrophone measures pressure and all three orthogonal components of particle velocity at a single point in space,the measured signal is preprocessed and sampled, the sampled data can be self-stored in subsurface buoy or transmitted to shore station by buoy. The method of noise measurement is discussed, the results of the sea trials show that the system is feasible and reliable.%对海洋环境噪声测量系统技术进行了研究,设计和实现了一种基于潜标的海洋环境噪声测量系统,并进行了海上试验.该系统采用潜标的布放方式,利用矢量水听器测量浅海海洋环境噪声场的低频噪声.矢量水听器同步测量声场空间一点处的声压和质点振速三个正交分量, 测量信号经预处理后,对信号进行数模变换,得到的噪声数据可以在潜标中自记录或通过水面浮标传输到岸站存储.对噪声测量方法进行的分析和海上试验的结果表明,该系统稳定可靠,能正确地拾取海洋环境噪声.

  18. A Simple, Buoy Deployable Instrument for Accurate Dissolved Carbon Dioxide and Dissolved Inorganic Carbon Measurements in Freshwater and Marine Ecosystems

    Science.gov (United States)

    Browne, B. A.; Wyss, J. R.; Bowling, J. M.; Schueller, D. J.; Sherman, J. F.

    2007-05-01

    The need for better knowledge of (1) the oceanic sink for anthropogenic CO2, (2) the impact of anthropogenic CO2 on the oceanic CaCO3 system and (3) lake and stream metabolism in freshwater ecosystems is driving growing interest in real-time technologies to measure pCO2 and dissolved inorganic carbon (DIC). To be useful, these technologies must meet stringent data quality requirements of marine and freshwater biogeochemical research initiatives such as the Joint Global Ocean Flux Study, the Coral Reef Environmental Observatory Network, the National Ecological Observatory Network, and the Global Lake Ecological Observatory Network. In this presentation, we introduce new methodology and a device for unaccompanied measurement of pCO2 and DIC on research buoys or ocean/freshwater vessels. This small-scale, essentially "plug and play" device (shoe box size) has limited power requirements (≤1.8 amps) for continuous or discontinuous (e.g., one reading per hour) measurements and does not bio-foul. DIC and pCO2 can be measured in sequence using one infrared detector or in parallel using two. The accuracy and precision (Training requirements are minimal, providing flexibility for deployments on multiple vessel types. The device works by induction of ebullition. A hydrostatic pressure drop upstream of a pump causes a temporary condition of gas oversaturation. The collection cell downstream of the pump then acts like an overpressurized soda bottle. As pressure is released within the collection cell, the dissolved gas streams passively and reliably into the infrared detector(s), at a nominal rate of 7 mL per minute, carrying CO2 into the cell essentially at its in-situ partial pressure. To measure DIC, a valve allows for the addition of acid to the sampling line upstream of the pump converting all DIC to CO2 prior to reaching the collection cell. With the acid valve on, DIC is measured. With the acid valve off, pCO2 is measured. We will present data illustrating the accuracy

  19. From earthquake size to far-field tsunami amplitude: development of a simple formula and application to DART buoy data

    Science.gov (United States)

    Okal, Emile A.; Reymond, Dominique; Hébert, Hélène

    2014-01-01

    We derive a simple formula relating tsunami amplitude in the far field to seismic moment, distance and azimuth from propagating rupture. Our formula is obtained from a comparison of a set of 4650 Pacific-wide simulations, computed for a series of sources spread over 10 subduction zones and four order of magnitudes in seismic moments. Our simulations are run both for a real grid reproducing the true bathymetry of the Pacific Basin and for an idealized one featuring a constant depth of 4000 m and no shorelines. This enables us to study and model separately the influence on the final amplitude of a tsunami wave of effects such as directivity and irregular bathymetry. The contribution of source size directivity and propagation over the sphere are studied using the constant-depth simulations. The influence of distance does not require any dispersive term and is properly modelled by geometrical spreading on the sphere. The directivity term, described classically in the frequency domain by Ben-Menahem & Rosenman can be approximated in the time domain by a moment-dependent linear regression as a function of azimuth. Finally, and after an allowance is made for the effect of receiver bathymetry using Green's law, the effect of irregular bathymetry is found to be generally defocusing, and can be modelled as a linear regression with distance. Once an estimate of the seismic moment of the parent earthquake is known, and under the assumption of a subduction mechanism along a fault of known azimuth, the resulting formula allows to forecast far-field tsunami amplitudes on the high seas. We use a data set of 116 tsunami amplitudes recorded at 51 past and present DART buoys following 21 tsunamigenic events to compare the estimates predicted by our algorithm to the amplitudes actually recorded. The average values of the residuals are 0.00 ± 0.25 logarithmic units, and 0.02 ± 0.20 at distances greater than 20°. An important aspect of our algorithm is that it correctly predicts the

  20. Wind waves spectra and other data collected using moored buoy in the Great Lakes, Gulf of Mexico, South Pacific and East/West coast of US from 01 June 2000 to 30 June 2000 (NODC Accession 0000217)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Wind wave spectra and other data were collected using moored buoys in the Great lakes, Gulf of Mexico, South Pacific and East/West coast of US from June 01, 2000 to...

  1. Buoying Design Skills

    Science.gov (United States)

    Bliss, Angela; Bell, Elizabeth; Spence, Lundie

    2013-01-01

    Oranges, flying disks, pool noodles, and polyvinyl chloride (PVC) pipe may seem like items discarded after a Rube Goldberg experiment, but in fact, these objects were used in teaching science, technology, engineering, and math (STEM). This article describes a project in which The Center of Ocean Sciences Education Excellence SouthEast (COSEE SE)…

  2. 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.

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

    International Nuclear Information System (INIS)

    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 ∼20% (∼40 W m-2), while the Esbensen and Kushnir climatology underestimates the flux by ∼4% (∼8 W m-2). The observed mean values were also compared to five satellite

  4. Assessing the performance of the Cretan Sea ecosystem model with the use of high frequency M3A buoy data set

    Directory of Open Access Journals (Sweden)

    G. Triantafyllou

    Full Text Available During the Mediterranean Forecasting System Pilot Project a buoy was deployed in the Cretan Sea and for the first time high-frequency physical and biogeochemical data were collected over an extended period, providing a unique opportunity for the evaluation of an ecosystem model. The model both tuned and validated in the Cretan Sea in the past, is explored and quantified. In addition, the optimal parameter set is determined while the effects of high-frequency forcing are explored. The model results are satisfactory, especially at the upper part of the water column, while the inability of 1-D modelling in fully exploring the hydrodynamics of the particular area is depicted and further developments are suggested.

    Key words. Oceanography; general (numerical modeling – Oceanography; biological and chemical (ecosystems and ecology

  5. 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...

  6. Temperature profile and other data collected using current meter, profiling floats, and drifting buoy from the Atlantic Ocean as part of the IDOE/POLYMODE (International Decade of Ocean Exploration / combination of USSR POLYGON project and US MODE) from 18 July 1977 to 18 October 1979 (NODC Accession 8100508)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature, pressure, and other data were collected using current meter, profiling floats, and drifting buoy in the Atlantic Ocean from July 18, 1977 to October...

  7. Temperature profile and pressure data collected using moored buoy from the Atlantic Ocean with support from the IDOE/POLYMODE (International Decade of Ocean Exploration / combination of USSR POLYGON project and US MODE) from 04 May to 18 December 1975 (NODC Accession 7601247)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profile and pressure data were collected using moored buoy from the Atlantic Ocean from May 4, 1975 to December 18, 1975. Data were submitted by...

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. Physical and chemical data from CTD, current meter, and buoy casts from the XIANG YANG HONG 14 and NOAA Ship OCEANOGRAPHER in the TOGA area of Pacific Ocean (30 N to 30 S) from 25 January 1987 to 24 October 1987 (NODC Accession 8700356)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Physical and chemical data were collected using current meter, CTD, and buoy casts in the TOGA area of the Pacific Ocean from NOAA Ship OCEANOGRAPHER and R/V...

  13. ASBAT 近岸风场产品与近岸浮标观测风场对比%Evaluation of ASBAT Boastal Wind Product Using Nearshore Buoy Data

    Institute of Scientific and Technical Information of China (English)

    谢小萍; 魏建苏; 黄亮

    2014-01-01

    The new scatterometer advanced scatterometer (ASCAT)on board MetOp-A satellite provides surface wind speed and direction over global ocean.Providing accurate nearshore wind data from satellites is chal-lenging because satellite data are unavailable very close to shore due to the contaminating effect of the land.Besides,land-sea breezes and shore topography produce small space scale and time-scale wind varia-tions that can be smoothed by the satellite’s space averaging and aliased by the satellite’s twice-a-day sam-pling.The complexity of nearshore winds is one of the prime causes that the regions are so important.For example,over one-third of the total marine fish catch occurs within nearshore zone. The accuracy of ASCAT coastal wind product is determined through various comparisons with buoys. The nearshore buoys used in the comparisons locate in US West Coast and China Coast.As the time inter-val of US West Coast buoy wind is 10-minute interval and the spatial resolution of ASCAT wind product is 12.5 km,a scatterometer wind and a buoy wind measurement are considered to be collocated if the distance between the wind vector cell center and the buoy location is less than 12.5 km and if the acquisition time difference is less than 5 minutes in US West Coast.As the time interval of China Coast buoy wind is 1 hour,the acquisition time difference is less than 30 minutes in China Coast.The buoy winds at a given an-emometer height are converted to 10 m neutral winds in order to enable a good comparison with the 10 m scatteromter winds.The time ranges of wind data used for comparison from US West Coast buoys and China Coast buoys are the whole year of 2012 and the first half year of 2012 individually. It shows that the accuracy of the wind speed of ASCAT product is high and the accuracy of the wind direction of ASCAT product is influenced by several factors,such as the distance from coast,wind speed and wind direction.The overall wind speed correlation coefficient

  14. 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. PMID:24253021

  15. MEMS 矢量水听器用于潜标系统的可行性%Feasibility of MEMS vector hydrophone application in submerged buoy system

    Institute of Scientific and Technical Information of China (English)

    韩建军; 张国军; 张文栋; 郭静; 刘源

    2016-01-01

    In this paper,MEMS vector hydrophone is proposed to apply in submerged buoy system,and a large number of experiments are done to verify its feasibility.The MEMS vector hydrophone,a kind of under-water acoustic sensor,has lots of advantages,such as small size,low cost,better consistency and high sensitiv-ity.When applied in submerged buoy system,it can sharply reduce the array aperture and can effectively detect the vector information of the marine sound field.Mainly,it can obtain good spatial gain and solve the problem of bulky volume of sonar equipment when applied in the field of low and very low frequency.The prototype of the submerged buoy system has undergone a number of indoor debugging and outdoor tests.After the prelimi-nary treatment of the trial data,the results show that this system can effectively detect the acoustic field vector signal in range of 20-1000 Hz under ocean.The MEMS vector hydrophone sensitivity can reach -176 dB and has a good “8”-shaped directivity pattern.%提出将 MEMS 矢量水听器应用于潜标系统,并进行了大量实验验证其可行性。MEMS 矢量水听器是一种新型水下声学传感器,它具有体积小、成本低、一致性高和高灵敏度等优点。将水听器应用于潜标系统,可以大幅降低阵列孔径,进而有效地监测海洋声场的矢量信息。矢量水听器矢量通道的指向性与频率无关,在低频和甚低频同样可以获得良好的空间增益,应用在低频和甚低频领域中,可以有效地解决声纳设备体积庞大的问题。经过对系统样机进行多次室内驻波桶调试和外场湖试与海试,结果表明,该系统能有效检测海底20~1000 Hz 范围内的声场矢量信号,水听器此时的灵敏度可达-176 dB,且具有良好的“8”字型指向性。实验结果证明了 MEMS 矢量水听器应用在潜标系统中进行海洋声场矢量信息探测的可行性,为 MEMS矢量水听器在水下目标探测领域的

  16. 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.

  17. Comparison of different wind products and buoy wind data with seasonality and interannual climate variability in the southern Bay of Biscay (2000-2009)

    Science.gov (United States)

    Alvarez, Inés; Gomez-Gesteira, Moncho; deCastro, Maite; Carvalho, David

    2014-08-01

    Ocean surface winds are essential factors in determining oceanographic and atmospheric processes that can affect ocean circulation and wave generation. Accurate surface wind datasets are needed, therefore, to enable the proper analysis of these processes. Wind data from six databases (National Centers for Environmental Prediction reanalysis (NCEP Reanalysis II), European Centre for Medium-Range Weather Forecasts (ECMWF) re-analysis (ERA-Interim), Modern-Era Retrospective-analysis for Research and Applications (MERRA), NCEP Climate Forecast System Reanalysis (CFSR), QuikSCAT and Cross-Calibrated Multi-Platform (CCMP)) were compared with wind measured in situ by four ocean buoys at the southern limit of the Bay of Biscay. The study covered the period 2000-2009 in such a way that the extent of the time series reduced the margin of error and allowed the disaggregation of the wind data using velocity bins and direction sectors. Statistical results confirmed that datasets with finer spatial resolution (lower than 0.5°×0.5°) gave better results, especially in near-shore areas. A more complete analysis was, therefore, carried out using the finer resolution datasets (QuikSCAT, CCMP and CFSR). This comparison showed that all the datasets were less accurate at low wind speeds (Navidad by wind stress. Correlations between NAO and north and east wind components were low showing that NAO could not be used as a proxy for local wind stress in the southern Bay of Biscay.

  18. Fully nonlinear time-domain simulation of a backward bent duct buoy floating wave energy converter using an acceleration potential method

    Science.gov (United States)

    Lee, Kyoung-Rok; Koo, Weoncheol; Kim, Moo-Hyun

    2013-12-01

    A floating Oscillating Water Column (OWC) wave energy converter, a Backward Bent Duct Buoy (BBDB), was simulated using a state-of-the-art, two-dimensional, fully-nonlinear Numerical Wave Tank (NWT) technique. The hydrodynamic performance of the floating OWC device was evaluated in the time domain. The acceleration potential method, with a full-updated kernel matrix calculation associated with a mode decomposition scheme, was implemented to obtain accurate estimates of the hydrodynamic force and displacement of a freely floating BBDB. The developed NWT was based on the potential theory and the boundary element method with constant panels on the boundaries. The mixed Eulerian-Lagrangian (MEL) approach was employed to capture the nonlinear free surfaces inside the chamber that interacted with a pneumatic pressure, induced by the time-varying airflow velocity at the air duct. A special viscous damping was applied to the chamber free surface to represent the viscous energy loss due to the BBDB's shape and motions. The viscous damping coefficient was properly selected using a comparison of the experimental data. The calculated surface elevation, inside and outside the chamber, with a tuned viscous damping correlated reasonably well with the experimental data for various incident wave conditions. The conservation of the total wave energy in the computational domain was confirmed over the entire range of wave frequencies.

  19. Research on Performance of Sonar Buoy Equipment Affected by Bit Error Rates of Communication%通信误码率对浮标声纳系统DOA估计性能的影响

    Institute of Scientific and Technical Information of China (English)

    张宇; 杨益新; 田丰

    2014-01-01

    浮标声纳受到功耗、体积和硬件复杂度等因素的限制,通常将接收数据通过无线信道发送到终端设备进行处理。由于多径传播、衰落特性以及多普勒效应等众多因素的干扰,信号在无线通信传递中会产生误码并影响最终系统性能。针对复杂传输信道环境下的浮标声纳系统,研究了误码率对系统的多目标方位估计性能的影响,并通过计算机仿真给出了误码率允许的门限。%Due to the limitations of volume,hardware complexity and power consumption,sonar buoy equipment transmits receives signals through wireless channel to the processing terminal on airplane or ship. The multipath effects,fading characteristics,and Doppler spread of communication channel will cause bit error and finally influence the performance of sonar signal processing. In this paper,is focused the DOA estimation performance of sonar buoy under various bit error rates of communication system. The BER threshold of DOA estimation is obtained via Monte Carlo simulation to guide the design of whole sonar buoy systems.

  20. 水性阻尼材料在潜标湍流仪中减振效果研究%Damping effect of water damping material used in turbulence instruments in submersible buoys

    Institute of Scientific and Technical Information of China (English)

    王书新; 栾新; 宋大雷; 王永芳; 苏兆龙; 闫启志

    2014-01-01

    简述湍流仪国内外发展现状及剪切探头测量原理,据潜标湍流仪观测数据分析影响湍流仪测量结果的振动因素,探讨减少噪声污染方法。针对由系缆传递振动造成的噪声提出应用低温水性阻尼材料减震方法,减振实验数据分析结果表明,增加阻尼材料可有效降低振动对测量精度影响。%The submersible buoy with turbulence instrument is an effective and a long-term observation platform of the turbulence in deep sea and plays an important role in marine scientific research.The current development of turbulence instruments at home and abroad and shear probe measurement principle were briefly introduced.According to the measurement data by turbulence instruments in submersible buoys,the factors affecting the measurement results of turbulence instruments were analyzed.The methods to reduce noise pollution were discussed.Aiming at the reduction of noise caused by the vibration of cable transmission,the application of low temperature water damping material was proposed.The experimental data indicate that adding damping material can effectively reduce the influence of vibration on the measurement accuracy.

  1. MOBY, A Radiometric Buoy for Performance Monitoring and Vicarious Calibration of Satellite Ocean Color Sensors: Measurement and Data Analysis Protocols. Chapter 2

    Science.gov (United States)

    Clark, Dennis K.; Yarbrough, Mark A.; Feinholz, Mike; Flora, Stephanie; Broenkow, William; Kim, Yong Sung; Johnson, B. Carol; Brown, Steven W.; Yuen, Marilyn; Mueller, James L.

    2003-01-01

    The Marine Optical Buoy (MOBY) is the centerpiece of the primary ocean measurement site for calibration of satellite ocean color sensors based on independent in situ measurements. Since late 1996, the time series of normalized water-leaving radiances L(sub WN)(lambda) determined from the array of radiometric sensors attached to MOBY are the primary basis for the on-orbit calibrations of the USA Sea-viewing Wide Field-of-view Sensor (SeaWiFS), the Japanese Ocean Color and Temperature Sensor (OCTS), the French Polarization Detection Environmental Radiometer (POLDER), the German Modular Optoelectronic Scanner on the Indian Research Satellite (IRS1-MOS), and the USA Moderate Resolution Imaging Spectrometer (MODIS). The MOBY vicarious calibration L(sub WN)(lambda) reference is an essential element in the international effort to develop a global, multi-year time series of consistently calibrated ocean color products using data from a wide variety of independent satellite sensors. A longstanding goal of the SeaWiFS and MODIS (Ocean) Science Teams is to determine satellite-derived L(sub WN)(labda) with a relative combined standard uncertainty of 5 %. Other satellite ocean color projects and the Sensor Intercomparison for Marine Biology and Interdisciplinary Oceanic Studies (SIMBIOS) project have also adopted this goal, at least implicitly. Because water-leaving radiance contributes at most 10 % of the total radiance measured by a satellite sensor above the atmosphere, a 5 % uncertainty in L(sub WN)(lambda) implies a 0.5 % uncertainty in the above-atmosphere radiance measurements. This level of uncertainty can only be approached using vicarious-calibration approaches as described below. In practice, this means that the satellite radiance responsivity is adjusted to achieve the best agreement, in a least-squares sense, for the L(sub WN)(lambda) results determined using the satellite and the independent optical sensors (e.g. MOBY). The end result of this approach is to

  2. 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...

  3. Direct Drive Wave Energy Buoy

    Energy Technology Data Exchange (ETDEWEB)

    Rhinefrank, Ken [Columbia Power Technologies, Corvallis, OR (United States)

    2011-11-02

    Presentation from the 2011 Water Peer Review in which principal investigator discusses project progress and results for this project which will be used to inform the utility-scale design process, improve cost estimates, accurately forecast energy production and to observe system operation and survivability.

  4. 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.

  5. Direct Drive Wave Energy Buoy

    Energy Technology Data Exchange (ETDEWEB)

    Rhinefrank, Kenneth; Prudell, Joseph; Hammagren, Erik; Lenee-Bluhm, Pukha

    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).

  6. The Catalog of Event Data of the Operational Deep-ocean Assessment and Reporting of Tsunamis (DART) Stations at the National Data Buoy Center

    Science.gov (United States)

    Bouchard, R.; Locke, L.; Hansen, W.; Collins, S.; McArthur, S.

    2007-12-01

    DART systems are a critical component of the tsunami warning system as they provide the only real-time, in situ, tsunami detection before landfall. DART systems consist of a surface buoy that serves as a position locater and communications transceiver and a Bottom Pressure Recorder (BPR) on the seafloor. The BPR records temperature and pressure at 15-second intervals to a memory card for later retrieval for analysis and use by tsunami researchers, but the BPRs are normally recovered only once every two years. The DART systems also transmit subsets of the data, converted to an estimation of the sea surface height, in near real-time for use by the tsunami warning community. These data are available on NDBC's webpages, http://www.ndbc.noaa.gov/dart.shtml. Although not of the resolution of the data recorded to the BPR memory card, the near real-time data have proven to be of value in research applications [1]. Of particular interest are the DART data associated with geophysical events. The DART BPR continuously compares the measured sea height with a predicted sea-height and when the difference exceeds a threshold value, the BPR goes into Event Mode. Event Mode provides an extended, more frequent near real-time reporting of the sea surface heights for tsunami detection. The BPR can go into Event Mode because of geophysical triggers, such as tsunamis or seismic activity, which may or may not be tsunamigenic. The BPR can also go into Event Mode during recovery of the BPR as it leaves the seafloor, or when manually triggered by the Tsunami Warning Centers in advance of an expected tsunami. On occasion, the BPR will go into Event Mode without any associated tsunami or seismic activity or human intervention and these are considered "False'' Events. Approximately one- third of all Events can be classified as "False". NDBC is responsible for the operations, maintenance, and data management of the DART stations. Each DART station has a webpage with a drop-down list of all

  7. Levels of Cd, Cu, Pb and V in marine sediments in the vicinity of the Single Buoy Moorings (SBM3) at Mina Al Fahal in the Sultanate of Oman.

    Science.gov (United States)

    Al-Husaini, Issa; Abdul-Wahab, Sabah; Ahamad, Rahmalan; Chan, Keziah

    2014-06-15

    Recently in the Sultanate of Oman, there has been a rapid surge of coastal developments. These developments cause metal contamination, which may affect the habitats and communities at and near the coastal region. As a result, a study was conducted to assess the level of metal contamination and its impact on the marine sediments in the vicinity of the Single Buoy Moorings 3 (SBM3) at Mina Al Fahal in the Sultanate of Oman. Marine subtidal sediment samples were collected from six different stations of the SBM3 for the period ranging from June 2009 to April 2010. These samples were then analyzed for their level and distribution of the heavy metals of cadmium (Cd), copper (Cu), lead (Pb) and vanadium (V). Overall, low concentrations of all four heavy metals were measured from the marine sediments, indicating that the marine at SBM3 is of good quality. PMID:24775070

  8. Levels of Cd, Cu, Pb and V in marine sediments in the vicinity of the Single Buoy Moorings (SBM3) at Mina Al Fahal in the Sultanate of Oman

    International Nuclear Information System (INIS)

    Highlights: • Assessed metal contamination in the SBM3 marine sediments of Mina Al Fahal, Oman. • Examined heavy metal concentration levels of Cd, Cu, Pb and V. • Mean concentration in the sediments, from highest to lowest, is V > Cu > Pb > Cd. • Highest concentration of V due to waste discharges from nearby heavy tanker traffic. • ICP-OES found low concentrations of all four heavy metals; SMB3 region in good quality. - Abstract: Recently in the Sultanate of Oman, there has been a rapid surge of coastal developments. These developments cause metal contamination, which may affect the habitats and communities at and near the coastal region. As a result, a study was conducted to assess the level of metal contamination and its impact on the marine sediments in the vicinity of the Single Buoy Moorings 3 (SBM3) at Mina Al Fahal in the Sultanate of Oman. Marine subtidal sediment samples were collected from six different stations of the SBM3 for the period ranging from June 2009 to April 2010. These samples were then analyzed for their level and distribution of the heavy metals of cadmium (Cd), copper (Cu), lead (Pb) and vanadium (V). Overall, low concentrations of all four heavy metals were measured from the marine sediments, indicating that the marine at SBM3 is of good quality

  9. Using grouper fish as bio-indicator of Cd, Cu, Pb and V in the vicinity of a single buoy mooring (SBM3) at Mina Al Fahal in the Sultanate of Oman.

    Science.gov (United States)

    Abdul-Wahab, S A; Al-Husaini, I S; Rahmalan, A

    2013-12-01

    This paper investigated metal contamination in muscle tissue of the grouper (Epinephelus coioides) in the vicinity of a single buoy mooring (SBM3) at the Sultanate of Oman. The fish samples were analyzed for cadmium (Cd), copper (Cu), lead (Pb) and vanadium (V). The mean concentrations of Cd, Cu, Pb and V in the fish samples were 0.05 ± 0.004, 0.34 ± 0.013, 0.20 ± 0.018 and 0.03 ± 0.006 mg/kg, respectively. The results were compared with the corresponding permissible concentration limits according to the Sultanate of Oman (0.05, 3.28, 0.3 and 1.4 mg/kg for Cd, Cu, Pb and V, respectively) and the European Commission (0.05 mg/kg for Cd and 0.3 mg/kg for Pb). It was found that none of the overall mean metal concentrations exceeded the corresponding Omani legislation or European Commission limits. However, the overall mean concentration of Cd was identical to the maximum permissible limit of 0.05 mg/kg that has been established by both Commissions, and the limits were exceeded for mean Cd levels in fish at two of the six sampling stations at SBM3. In general, this study indicated that the fishes at SBM3 were not highly contaminated with these metals. PMID:24145924

  10. Design for opreating interface of sonar buoy system simulator based on VC++ and OpenGL%基于VC++和OpenGL声纳浮标系统模拟器操作界面设计

    Institute of Scientific and Technical Information of China (English)

    王承祥; 鞠建波; 陶晨辰

    2012-01-01

    从声纳浮标模拟器的操作界面需求入手,设计了一种可移植的操作界面的软件框架,对声纳操作界面进行了仿真.重点介绍了操作界面所需要的各个模块,以及为每个模块设计的基于C++语言的软件开发类库,可以利用模块类库实现声纳浮标搜潜模拟器的界面需求,使模拟器界面和实际装备完全一致,使模拟器起到教学和训练的作用.%Proceeding from the need of operating interface of sonar buoy system simulator, a kind of software frame of the transplantable operating interface was designed to simulate the sonar operating interface. The every module that is needed for operating interface and the VC+H+-based software development class libraries designed for every module are emphatically introduced. The requirement for operating interface can be satisfied by utilizing this class libraries, which make the operating interface of simulator consistent with the real equipment, so the simulator can play a role of teaching and training.

  11. Collaborative optimization of photovoltaic/battery power source for water quality buoy based on fuzzy integer programming%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

    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

  12. The characteristic analysis of ambient sea noise spectrum based on submersible buoy%基于潜标测量的海洋环境噪声谱特性分析

    Institute of Scientific and Technical Information of China (English)

    笪良龙; 王超; 卢晓亭; 韩梅; 邓小花

    2014-01-01

    利用海洋环境噪声测量潜标系统对南海典型海域开展了为期3个月的海洋环境噪声测量,16通道海洋环境噪声测量系统每小时测量两分钟噪声信号。数据处理结果表明,800~5000 Hz范围内,噪声谱与风速相关性最好,且风速越大相关性越好,噪声谱与风速的相关性好于与浪高的相关性。风关噪声谱级在海水中部基本不随接收深度发生变化,但由于测量水听器阵长度未能覆盖整个水深,因此未给出海面和海底处谱级变化规律。在400 Hz以上的高频段整个风速范围内噪声谱级都随风速发生变化,且噪声谱级与对数风速具有很好的线性关系。%Ambient sea-noise data were collected for three month period ,using submersible buoy system in the South China Sea .Broad-band ambient-noise signals from the sixteen hydrophones were amplified and recorded for 2min every 1h .The results of data processing show a strong wind dependence in the upper frequency bands from ap-proximately 800 Hz to 5 kHz ,and the greater the wind speed ,the better the correlation .The noise is correlated more with wind speed than with wave height . The wind-generated spectrum level producing virtually constant noise intensity in the midwater ,however ,due to the length of the hydrophone failed to cover the entire depth ,the distribution of the noise at the near-surface and near-bottom unable to given .In the frequencies above 400 Hz am-bient-noise spectrum level ranged with the entire wind speeds .In addition it was found that the ambient-noise spec-trum shown to be linearly dependent upon the logarithm of wind speed .

  13. Stockyard equipment buoyed by commodity prices

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2011-03-15

    Recent contract signings by heavy plant manufacturers show that the market for stockyard equipment is holding its own, despite continued economic uncertainty worldwide. Development by major manufacturers of stacker/reclaimers and bucket wheel excavators are reported. 1 photo.

  14. Reserves hike to buoy Bontang LNG

    International Nuclear Information System (INIS)

    This paper reports that a redetermination of reserves in an Indonesian production sharing contract (PSC) will boost liquefied natural gas sales for an Indonesian joint venture (IJV) of Lasmo plc, Union Texas (South East Asia) Inc., Chinese Petroleum Corp. (CPC), and Japex Rantau Ltd. The Indonesian reserves increase involves the Sanga PSC operated by Virginia Indonesia Co., a 50-50 joint venture of Lasmo and Union Texas. Union Texas holds a 38% interest in the IJV and Lasmo 37.8%, with remaining interests held by CPC and Japex. meantime, in US LNG news: Shell LNG Co. has shelved plans to buy an added interest in the LNG business of Columbia Gas System Inc. Panhandle Eastern Corp. units Trunkline Gas Co., Trunkline LNG Co., and Panhandle Eastern Pipe Line Co. (PEPL) filed settlement agreements with the Federal Energy Regulatory Commission to recover from customers $243 million in costs associated with Panhandle's Trunkline LNG operation at Lake Charles, Louisiana

  15. 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.…

  16. Hefty tests buoy Philippine oil sector

    International Nuclear Information System (INIS)

    This paper reports that Alcorn International Inc., Houston, has disclosed a test of another hefty oil flow off Philippines. Alcorn last month completed its third high flowing delineation well in the West Linapacan area off Palawan Island. Development of West Linapacan field will help boost lagging Philippines oil production, which fell 31% in 1991 from 1990 levels. Philippines Office of Energy Affairs (OEA) also outlined other aspects of the country's oil and gas activity in 1991. Recent drilling successes have redirected the country's focus north to the West Linapacan area from older Northwest Palawan oil fields. Meantime, two geophysical survey and exploration contracts (GSECs) were awarded in 1991, and two service contracts (SCs) were relinquished during the year. Several seismic program were completed last year, and in agreement between Australia and Philippines will yield added seismic data during the next 3 years

  17. Chinese Investment BuoysAfrica's Economy

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    According to Xinhua News Agency,athough Africa is a diverse continent,containing a variety of countries and cultures,the representatives of African countries do have one thing in common:their desire to attract Chinese investment.“We look forward to Chinese enterprises'investments.Chinese investment helps us to fund the construction of transportation and medical infrastructure,” Bernadette Artivor,executive director of the Namibia Investment Center,said on September 8.Artivor made the remark at the High-Level Symposium for China-Africa Investment and Cooperation,an event held as part of the 15th China International Fair for Investment and Trade (CIFIT) which opened in southeast Chinas coastal city of Xiamen.

  18. 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).

  19. 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.

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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,...

  5. 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,...

  6. Demand for petrochem feedstock to buoy world LPG industry

    International Nuclear Information System (INIS)

    This paper reports that use of liquefied petroleum gas as petrochemical feedstock will increase worldwide, providing major growth opportunities for LPG producers. World exports of liquefied petroleum gas will increase more slowly than production as producers choose to use LPG locally as chemical feedstock and export in value added forms such as polyethylene. So predicts Poten and Partners Inc., New York. Poten forecasts LPG production in exporting countries will jump to 95 million tons in 2010 from 45 million tons in 1990. However, local and regional demand will climb to 60 million tons/year from 23 million tons/year during the same period. So supplies available for export will rise to 35 million tons in 2010 from 22 million tons in 1990

  7. Natural gas to buoy Trinidad and Tobago petroleum sector

    International Nuclear Information System (INIS)

    Trinidad and Tobago's petroleum sector remains at a crossroads. While heavily reliant on oil and gas for domestic energy consumption and hard currency export earnings, the small Caribbean island nation faces some tough choices in reviving its hydrocarbon sector in the 1990s. Exploration and production of crude oil have stagnated in recent years, and domestic refinery utilization remains low at 36%. However, substantial natural gas reserves in Trinidad and Tobago offer the promise of a burgeoning natural gas based economy with an eye to liquefied natural gas and gas based petrochemical exports. Any solutions will involve considerable outlays by the government as well as a sizable infusion of capital by foreign companies. Therein lie some of the hard choices. The article describes the roles of oil and gas, foreign investment prospects, refining status, refining problems, gas sector foreign investment, and outlook for the rest of the 1990's

  8. Radiotracer study off Haldia river buoy in Hooghly river

    International Nuclear Information System (INIS)

    Glass powder labelled with radioactive scandium-46 was used as tracer to study the movement of sediment on the Hooghly river bed in the Port of Calcutta. Three detection programmes spread over three months indicated that the direction of sediment transport is towards south-west during the period of October-December '92. Countrate balance method was applied to quantitatively estimate the sediment discharge rate and is of the order of 215-250 kg/d per metre width of the bed. (author). 3 refs., 2 figs., 1 tab

  9. 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,...

  10. Acoustic oceanographic buoy data report Makai Ex 2005

    OpenAIRE

    Jesus, S.M.; Silva, A.; F. Zabel

    2005-01-01

    Rep 04/05 - SiPLAB 17/Nov/2005 University It is now well accepted in the underwater acoustic scientific community that below, say, 1 kHz acoustic propagation models are accurate enough to be able to predict the received acoustic field up to the point of allowing precise and reliable source tracking in range and depth with only limited environmental information. This results from a large number of studies both theoretical and with real data, carried out in the last 20 year...

  11. 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.

  12. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Salinity

    Data.gov (United States)

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

  13. 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,...

  14. 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.

  15. 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,...

  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, 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/),...

  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, 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,...

  20. 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...

  1. 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,...

  2. A Buoy for Continuous Monitoring of Suspended Sediment Dynamics

    OpenAIRE

    Andreas Güntner; Lucas Kaempf; Heiko Thoss; Philip Mueller

    2013-01-01

    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 r...

  3. 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,...

  4. 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/),...

  5. 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,...

  6. 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,...

  7. 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,...

  8. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Currents

    Data.gov (United States)

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

  9. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Air Temperature

    Data.gov (United States)

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

  10. 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...

  11. 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,...

  12. 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...

  13. 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...

  14. 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...

  15. 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,...

  16. 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,...

  17. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Sensible Heat Flux

    Data.gov (United States)

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

  18. TAO/TRITON, RAMA, and PIRATA Buoys, Daily, Sensible Heat Flux

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset has daily Sensible 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, 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,...

  20. 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...

  1. 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.

    77G69G82G32G77G79G78G83G79G79G78 G75G46G32G83G117G100G104G101G101G115G104G44G32G80G46G32G86G101G116G104G97G109G111G110G121G42G44G32G77G46G32G84G46G32G66G97G98G117G32G97G110G100G32G83G46G32G74G97G121G97G107G117G109G97G114 G78G97G116G105G111G110G97G108G...G116G104G101G114G101G102G111G114G101G44G32G97G108G108G32G116G104G101 G97G108G116G105G109G101G116G101G114G32G83G87G72G32G118G97G108G117G101G115G32G97G114G101G32G111G114G103G97G110G105G115G101G100G32G105G110G32G48G46G55G53G176G32G120G32G48G46G55G53G176...

  2. 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.

  3. Past Buoy Lines: Exploring Metaphors, Boundaries, and Poetic Possibilities in Giftedness Research

    Science.gov (United States)

    Richardson, Pamela

    2009-01-01

    This piece is a poetic and narrative inquiry (Leggo, 2004) into the conceptual, physical, and emotional underpinnings of research methodology in the field of gifted education. First, the author explores the metaphorical possibility of swimming rather than standing in the field of inquiry and how relationships to self, environment, and other would…

  4. Endorsement Of SMOS Brightness Temperature Using In-Situ Buoy Data Over Indian Ocean

    Science.gov (United States)

    Calla, O. P. N.; Dadhich, Harendra Kumar; Singhal, Shruti

    2013-12-01

    The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite mission has been launched in November 2009 with the aim at providing global and regular observations of Soil Moisture over land and Ocean Salinity over ocean in which they are variables in order to understand and predict the evolution of the water cycle on our planet. In particular, it provides over the oceans, synoptic sea surface salinity (SSS) measurements with frequent temporal coverage and good spatial resolution. This paper aims to validate the SMOS BT with the estimated BT using Radiative Transfer Model (RTM). There are many challenges in measuring SSS from space and obtaining a targeted accuracy of 0.1 psu on a 200 km grid over a 10-day period. The accuracy of the retrieved SSS is better when the correct observation of BT has been made by SMOS. So, now it has become essential to ratify the BT values of SMOS.

  5. The acoustic oceanographic buoy telemetry system: an advanced sonobuoy that meets acoustic rapid environmental assessment requirements

    OpenAIRE

    De Silva, A.; F. Zabel; C. Martins

    2007-01-01

    In the past few years Rapid Environmental Assessment (REA), applied to shallow waters, has become one of the most challenging topics in ocean acoustics. The REA concept evolved after the cold war when the outset of regional conflicts shifted the potential operational areas from open ocean towards littoral areas, and has been identified by NATO as a new warfare requirement.

  6. Clean-air legislation will buoy U.S. gas processing

    International Nuclear Information System (INIS)

    This paper reports on the effects of recent U.S. clean-air legislation on NGL demand and pricing. Demand for all NGL products will be firm throughout the 1990s. Increased requirements for butane as methyl tertiary butyl ether (MTBE) feedstock will strengthen butane prices. Higher base-load requirements for propane in new NGL-based olefin plants will also have a positive impact on propane prices

  7. Sub-inertial variability in the Cretan Sea from the M3A buoy

    Directory of Open Access Journals (Sweden)

    V. Cardin

    Full Text Available One year of continuous records of temperature, salinity data at various depths, and currents obtained from by an upward looking acoustic Doppler current profiler (ADCP moored at a site in the Cretan Sea were analyzed. Temperature and salinity data revealed the influence of a multi-scale circulation pattern prevailing in this area. This pattern consists of mesoscale cyclonic and anticyclonic vortices moving together as a dipole, and inducing downwelling and upwelling in the water column. The dipole movements, which control the circulation in the area, have been evidenced from horizontal current variability in the upper 250 m. The basin-scale circulation also shows a prominent seasonal variability. The Empirical Orthogonal Function analysis applied to either zonal or meridional components of the currents, confirmed the prevalence of a depth-independent mode over the baroclinic-like one for the whole period of measurements and for both current components. Nevertheless, the depth-dependent structure indicated the out-of-phase behaviour of the upper 250 m layer with respect to the deeper one. The first mode of the temperature EOF analysis, which accounts for most of the variance, represents the seasonal heating of the water column being principally associated with the surface mixed layer at the level of the seasonal thermocline.

    Key words. Oceanography: physical (currents, eddies and mesoscale processes, general circulation

  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. 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.

    s. 2.6 RESULTS AND DISCUSSION Software in FORTRAN Language, constructed on the ?black-box? principle, has been developed to determine wave direction from measurements of surface elevation at the 15-gauge array at North Carolina, USA using the phase...

  10. Tidal Power Generation System Appropriate for Boarding on a Floating Buoy

    Energy Technology Data Exchange (ETDEWEB)

    Tanaka, D.; Inagaki, A.; Oba, S [DMW Corporation, Mishima (Japan); Kanemoto, T. [Kyushu Institute of Technology, Kitakyushu (Japan)

    2007-07-01

    To cope with the warming global environment, the hydropower should occupy the attention of the electric power generation system as clean and cool energy sources. In such a situation, the tidal current has scarcely been utilized for the power generation. The authors have proposed and developed a new type of generator with counter-rotating rotors instead of the usual mechanism. This paper discusses the effects of the blade profiles on the hydraulic performances. As a result, the design materials for the solidity of the axial flow runners suitable for the given water circumstances are induced from above discussions.

  11. Multi-buoy Wave Energy Converter : Electrical Power Smoothening from Array Configuration

    OpenAIRE

    Jansson, Elisabet

    2016-01-01

    This master thesis is done within the Energy Systems Engineering program at Uppsala University and performed for CorPower Ocean. Wave energy converters (WECs) are devices that utilize ocean waves for generation of electricity. The WEC developed by CorPower Ocean is small and intended to be deployed in an array. Placed in an array the different WECs will interact hydrodynamically and the combined power output is altered. The aim of this thesis is to model and investigate how the array configur...

  12. TAO/TRITON, RAMA, and PIRATA Buoys, Monthly, Sea Surface Temperature

    Data.gov (United States)

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

  13. 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,...

  14. 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,...

  15. 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/),...

  16. 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,...

  17. 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,...

  18. 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,...

  19. 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,...

  20. TAO/TRITON, RAMA, and PIRATA Buoys, 5-Day, Net Longwave Radiation

    Data.gov (United States)

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