scholarly journals Characteristics of surface currents in Manado Bay, North Sulawesi, Indonesia

2021 ◽  
Vol 5 (1) ◽  
pp. 42-52
Author(s):  
Aulia Dyan Yohanlis ◽  
Mutiara Rachmat Putri
Keyword(s):  
Surface Current ◽  
Current Speed ◽  
Sea Surface ◽  
Marine Debris ◽  
Surface Currents ◽  
Hydrodynamic Simulation ◽  
Average Speed ◽  
Debris Accumulation ◽  
North Sulawesi ◽  
Current Flows

Manado Bay is a complex waterway located in Manado City, North Sulawesi, Indonesia. It is an entry point for the Indonesia Trough-Flow, and its circulation is affected by the seasonal winds. Manado City has no debris net on its river estuaries. Therefore, marine debris can easily be carried away by the ocean currents and accumulate in the tourism areas located along the coast of Manado Bay. Consequently, it is important to study the sea surface current circulation in Manado Bay to deal with marine debris accumulation. In the present study, we utilized the DELFT3D software to simulate the hydrodynamic circulation in Manado Bay from 2016-2017. We conducted a 2-dimension (2D) horizontal hydrodynamic simulation using tidal and wind forcing from European Centre for Medium-Range Weather (ECMWF). The simulation results indicate that the change in bathymetry and wind affect the sea surface currents. During the summer monsoon (June-August), the sea surface current flows from the northeast to the southwest with an average speed of 1.1 cm s-1. On the contrary, during the transitional monsoon 1 (September-November), the sea surface current flows from the southeast to the northwest with an average speed of 1.3 cm s-1. Meanwhile, in the winter monsoon (December-February), the sea surface current originated from the southwest flows to the east with an average velocity of 1.9 cm s-1. Then, it moves from west to east during transitional monsoon 2 (March-May) with an average speed of 1.5 cm s-1. The current speed increases whenthe water enters the strait between the Bunaken Islands due to refraction, diffraction, and shallowing effect. As current flows toward the shallower area, the current speed increases, compensating the water column reduction.

scholarly journals A Combined Balloon Photography and Buoy-Tracking Experiment for Mapping Surface Currents in Coastal Waters

2016 ◽  
Vol 33 (6) ◽  
pp. 1237-1250 ◽  
Author(s):  
Yasuyuki Miyao ◽  
Atsuhiko Isobe
Keyword(s):  
Field Experiments ◽  
Digital Camera ◽  
Surface Current ◽  
Marine Debris ◽  
Surface Currents ◽  
Stochastic Fluctuations ◽  
Observational Technique ◽  
The Seto Inland Sea ◽  
Ocean Surface Current ◽  
Estimated Error

AbstractA novel observational technique to map surface ocean currents at high spatial resolution in narrow regions is developed. Low-altitude remote sensing using a digital camera suspended from a vessel-towed balloon is used to track trajectories of floating buoys deployed on the ocean. Surface-current velocities are thereafter computed by sequentially moving buoy locations on photo images converted into ground (Cartesian) coordinates. Field experiments were conducted in July and August 2013 using a balloon towed by a research vessel on the Seto Inland Sea. The image-derived currents were compared with those derived from buoy locations recorded by GPS receivers attached to each floating buoy. It was found that surface currents computed using GPS data contain unrealistic values arising from stochastic fluctuations in those data. However, the image-derived currents reproduced well convergent flows and a cyclonic eddy that accumulated foam and marine debris, as actually observed during the surveys. This performance is attributed to the fact that the image processing acts as a filter to remove erroneous buoy locations in computing surface currents. The estimated error was 4.1 cm s−1, sufficiently small to measure snapshots of surface coastal currents with magnitudes greater than several tens of centimeters per second.

scholarly journals Improving the Altimeter-Derived Surface Currents Using Sea Surface Temperature (SST) Data: A Sensitivity Study to SST Products

2020 ◽  
Vol 12 (10) ◽  
pp. 1601 ◽  
Author(s):  
Daniele Ciani ◽  
Marie-Hélène Rio ◽  
Bruno Buongiorno Nardelli ◽  
Hélène Etienne ◽  
Rosalia Santoleri
Keyword(s):  
High Resolution ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Surface Current ◽  
Zonal Flow ◽  
Sensitivity Study ◽  
Sea Surface ◽  
Global Network ◽  
Altimeter Data ◽  
Surface Currents

Measurements of ocean surface topography collected by satellite altimeters provide geostrophic estimates of the sea surface currents at relatively low resolution. The effective spatial and temporal resolution of these velocity estimates can be improved by optimally combining altimeter data with sequences of high resolution interpolated (Level 4) Sea Surface Temperature (SST) data, improving upon present-day values of approximately 100 km and 15 days at mid-latitudes. However, the combined altimeter/SST currents accuracy depends on the area and input SST data considered. Here, we present a comparative study based on three satellite-derived daily SST products: the Remote Sensing Systems (REMSS, 1/10 ∘ resolution), the UK Met Office OSTIA (1/20 ∘ resolution), and the Multiscale Ultra-High resolution SST (1/100 ∘ resolution). The accuracy of the marine currents computed with our synergistic approach is assessed by comparisons with in-situ estimated currents derived from a global network of drifting buoys. Using REMSS SST, the meridional currents improve up to more than 20% compared to simple altimeter estimates. The maximum global improvements for the zonal currents are obtained using OSTIA SST, and reach 6%. Using the OSTIA SST also results in slight improvements (≃1.3%) in the zonal flow estimated in the Southern Ocean (45 ∘ S to 70 ∘ S). The homogeneity of the input SST effective spatial resolution is identified as a crucial requirement for an accurate surface current reconstruction. In our analyses, this condition was best satisfied by the lower resolution SST products considered.

scholarly journals Satellite-Derived Surface Current Divergence in Relation to Tropical Atlantic SST and Wind

2007 ◽  
Vol 37 (5) ◽  
pp. 1357-1375 ◽  
Author(s):  
Robert W. Helber ◽  
Robert H. Weisberg ◽  
Fabrice Bonjean ◽  
Eric S. Johnson ◽  
Gary S. E. Lagerloef
Keyword(s):  
Atlantic Ocean ◽  
Velocity Component ◽  
Surface Current ◽  
Sea Surface ◽  
Surface Currents ◽  
Tropical Atlantic ◽  
Cold Tongue ◽  
Equatorial Atlantic ◽  
Zonal Velocity ◽  
Mass Divergence

Abstract The relationships between tropical Atlantic Ocean surface currents and horizontal (mass) divergence, sea surface temperature (SST), and winds on monthly-to-annual time scales are described for the time period from 1993 through 2003. Surface horizontal mass divergence (upwelling) is calculated using surface currents estimated from satellite sea surface height, surface vector wind, and SST data with a quasi-linear, steady-state model. Geostrophic and Ekman dynamical contributions are considered. The satellite-derived surface currents match climatological drifter and ship-drift currents well, and divergence patterns are consistent with the annual north–south movement of the intertropical convergence zone (ITCZ) and equatorial cold tongue evolution. While the zonal velocity component is strongest, the meridional velocity component controls divergence along the equator and to the north beneath the ITCZ. Zonal velocity divergence is weaker but nonnegligible. Along the equator, a strong divergence (upwelling) season in the central/eastern equatorial Atlantic peaks in May while equatorial SST is cooling within the cold tongue. In addition, a secondary weaker and shorter equatorial divergence occurs in November also coincident with a slight SST cooling. The vertical transport at 30-m depth, averaged across the equatorial Atlantic Ocean between 2°S and 2°N for the record length, is 15(±6) × 106 m3 s−1. Results are consistent with what is known about equatorial upwelling and cold tongue evolution and establish a new method for observing the tropical upper ocean relative to geostrophic and Ekman dynamics at spatial and temporal coverage characteristic of satellite-based observations.

scholarly journals Prediction of geostrophic currents using big weather data archive and neural networks for the Aegean Sea

2019 ◽  
Vol 9 (1) ◽  
pp. 10-20
Author(s):  
Timur İnan ◽  
Ahmet Fevzi BABA
Keyword(s):  
Neural Network ◽  
Surface Current ◽  
Aegean Sea ◽  
Current Data ◽  
Sea Surface ◽  
Weather Data ◽  
Time Of Arrival ◽  
Surface Currents ◽  
Data Archive ◽  
Wave Direction

Prediction of sea and weather environment variables like wind speed, wind direction, wave height, wave direction, sea surface current direction and magnitude has always been an important subject in marine engineering as they effect on ship speed and effect the time of arrival to destination point as well. In this study, we propose a neural network that can predict the latitudinal and longitudinal components of sea surface currents in the Aegean Sea. The system can predict the sea surface currents components using the wind components which are gathered from the INMARSAT weather report system. The neural network is trained using the historical data which is gathered from UCAR historical weather database and historical surface current data which is gathered from IFREMER database. Keywords: Sea surface current, weather report, prediction, neural network, big data archive.

scholarly journals Distinct Influence of Air–Sea Interactions Mediated by Mesoscale Sea Surface Temperature and Surface Current in the Arabian Sea

2017 ◽  
Vol 30 (20) ◽  
pp. 8061-8080 ◽  
Author(s):  
Hyodae Seo
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Wind Stress ◽  
Arabian Sea ◽  
Spatial Scales ◽  
Surface Current ◽  
Sea Surface ◽  
Surface Currents ◽  
Ekman Pumping ◽  
Wind Stress Curl

Abstract During the southwest monsoons, the Arabian Sea (AS) develops highly energetic mesoscale variability associated with the Somali Current (SC), Great Whirl (GW), and cold filaments (CF). The resultant high-amplitude anomalies and gradients of sea surface temperature (SST) and surface currents modify the wind stress, triggering the so-called mesoscale coupled feedbacks. This study uses a high-resolution regional coupled model with a novel coupling procedure that separates spatial scales of the air–sea coupling to show that SST and surface currents are coupled to the atmosphere at distinct spatial scales, exerting distinct dynamic influences. The effect of mesoscale SST–wind interaction is manifested most strongly in wind work and Ekman pumping over the GW, primarily affecting the position of GW and the separation latitude of the SC. If this effect is suppressed, enhanced wind work and a weakened Ekman pumping dipole cause the GW to extend northeastward, delaying the SC separation by 1°. Current–wind interaction, in contrast, is related to the amount of wind energy input. When it is suppressed, especially as a result of background-scale currents, depth-integrated kinetic energy, both the mean and eddy, is significantly enhanced. Ekman pumping velocity over the GW is overly negative because of a lack of vorticity that offsets the wind stress curl, further invigorating the GW. Moreover, significant changes in time-mean SST and evaporation are generated in response to the current–wind interaction, accompanied by a noticeable southward shift in the Findlater Jet. The significant increase in moisture transport in the central AS implies that air–sea interaction mediated by the surface current is a potentially important process for simulation and prediction of the monsoon rainfall.

scholarly journals Unsupervised Reconstruction of Sea Surface Currents from AIS Maritime Traffic Data Using Trainable Variational Models

2021 ◽  
Vol 13 (16) ◽  
pp. 3162
Author(s):  
Simon Benaïchouche ◽  
Clément Legoff ◽  
Yann Guichoux ◽  
François Rousseau ◽  
Ronan Fablet
Keyword(s):  
State Of The Art ◽  
Climate Modeling ◽  
Spatial Scales ◽  
Surface Current ◽  
Ocean Dynamics ◽  
Sea Surface ◽  
Surface Currents ◽  
Ship Routing ◽  
Variational Models ◽  
Art Methods

The estimation of ocean dynamics is a key challenge for applications ranging from climate modeling to ship routing. State-of-the-art methods relying on satellite-derived altimetry data can hardly resolve spatial scales below ∼100 km. In this work we investigate the relevance of AIS data streams as a new mean for the estimation of the surface current velocities. Using a physics-informed observation model, we propose to solve the associated the ill-posed inverse problem using a trainable variational formulation. The latter exploits variational auto-encoders coupled with neural ODE to represent sea surface dynamics. We report numerical experiments on a real AIS dataset off South Africa in a highly dynamical ocean region. They support the relevance of the proposed learning-based AIS-driven approach to significantly improve the reconstruction of sea surface currents compared with state-of-the-art methods, including altimetry-based ones.

scholarly journals Observations of Surface Currents and Tidal Variability Off of Northeastern Taiwan from Shore-Based High Frequency Radar

2021 ◽  
Vol 13 (17) ◽  
pp. 3438
Author(s):  
Yu-Ru Chen ◽  
Jeffrey D. Paduan ◽  
Michael S. Cook ◽  
Laurence Zsu-Hsin Chuang ◽  
Yu-Jen Chung
Keyword(s):  
High Frequency ◽  
Tide Gauge ◽  
Surface Current ◽  
Sea Surface ◽  
Field Pattern ◽  
Surface Currents ◽  
High Frequency Radar ◽  
Synoptic Variability ◽  
Four Seasons ◽  
Frequency Components

A network of high-frequency radars (HFRs) has been deployed around Taiwan. The wide-area data coverage is dedicated to revealing near real-time sea-surface current information. This paper investigates three primary objectives: (1) describing the seasonal current synoptic variability; (2) determining the influence of wind forcing; (3) describing the tidal current field pattern and variability. Sea surface currents derived from HFR data include both geostrophic components and wind-driven components. This study explored vector complex correlations between the HFR time series and wind, which was sufficient to identify high-frequency components, including an Ekman balance among the surface currents and wind. Regarding the characteristics of mesoscale events and the tidal field, a year-long high-resolution surface dataset was utilized to observe the current–eddy–tide interactions over four seasons. The harmonic analysis results derived from surface currents off of northeastern Taiwan during 2013 are presented. The results agree well with the tidal parameters estimated from tide-gauge station observations. The analysis shows that this region features a strong, mixed, mainly semidiurnal tide. Continued monitoring by a variety of sensors (e.g., satellite and HFR) would improve the understanding of the circulation in the region.

scholarly journals Honing in on bioluminescent milky seas from space

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Steven D. Miller ◽  
Steven H. D. Haddock ◽  
William C. Straka ◽  
Curtis J. Seaman ◽  
Cynthia L. Combs ◽  
...  
Keyword(s):  
Scientific Inquiry ◽  
Water Mass ◽  
Marine Ecosystem ◽  
Sea Surface ◽  
Surface Currents ◽  
Maritime Continent ◽  
Low Light ◽  
Composition Formation ◽  
Mass Isolation ◽  
New Generation

AbstractMilky seas are a rare form of marine bioluminescence where the nocturnal ocean surface produces a widespread, uniform and steady whitish glow. Mariners have compared their appearance to a daylit snowfield that extends to all horizons. Encountered most often in remote waters of the northwest Indian Ocean and the Maritime Continent, milky seas have eluded rigorous scientific inquiry, and thus little is known about their composition, formation mechanism, and role within the marine ecosystem. The Day/Night Band (DNB), a new-generation spaceborne low-light imager, holds potential to detect milky seas, but the capability has yet to be demonstrated. Here, we show initial examples of DNB-detected milky seas based on a multi-year (2012–2021) search. The massive bodies of glowing ocean, sometimes exceeding 100,000 km2 in size, persist for days to weeks, drift within doldrums amidst the prevailing sea surface currents, and align with narrow ranges of sea surface temperature and biomass in a way that suggests water mass isolation. These findings show how spaceborne assets can now help guide research vessels toward active milky seas to learn more about them.

scholarly journals Gap Filling of the CALYPSO HF Radar Sea Surface Current Data through Past Measurements and Satellite Wind Observations

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Adam Gauci ◽  
Aldo Drago ◽  
John Abela
Keyword(s):  
Oil Spills ◽  
Surface Current ◽  
Radar Data ◽  
Current Data ◽  
Hf Radar ◽  
Sea Surface ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
Spatial Coverage ◽  
Essential Components

High frequency (HF) radar installations are becoming essential components of operational real-time marine monitoring systems. The underlying technology is being further enhanced to fully exploit the potential of mapping sea surface currents and wave fields over wide areas with high spatial and temporal resolution, even in adverse meteo-marine conditions. Data applications are opening to many different sectors, reaching out beyond research and monitoring, targeting downstream services in support to key national and regional stakeholders. In the CALYPSO project, the HF radar system composed of CODAR SeaSonde stations installed in the Malta Channel is specifically serving to assist in the response against marine oil spills and to support search and rescue at sea. One key drawback concerns the sporadic inconsistency in the spatial coverage of radar data which is dictated by the sea state as well as by interference from unknown sources that may be competing with transmissions in the same frequency band. This work investigates the use of Machine Learning techniques to fill in missing data in a high resolution grid. Past radar data and wind vectors obtained from satellites are used to predict missing information and provide a more consistent dataset.

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