scholarly journals Analysis of Abundance and Origin Possibility of Planktonic Foraminifera in Sulawesi Sea

2021 ◽  
Vol 925 (1) ◽  
pp. 012014
Author(s):  
D R Junita ◽  
L Gustiantini ◽  
A Sartimbul ◽  
L I Bernawis ◽  
S A Piranti
Keyword(s):  
Planktonic Foraminifera ◽  
Simulated Data ◽  
Ocean Model ◽  
Ocean Currents ◽  
Ocean Current ◽  
Core Sediment ◽  
Globigerinoides Ruber ◽  
Physical Conditions ◽  
Hybrid Coordinate Ocean Model ◽  
And Cluster Analysis

Abstract Foraminifera is very diverse and adaptive, both in its morphology and biology. It is a potential bioindicator to understand the ecological and physical conditions of the ancient and modern waters based on their distribution. It has been well confirmed that the abundance of foraminifera (as a fossil) in sediment can reflect the ocean conditions above (mixed layer to upper ocean) where it was deposited. Planktonic foraminifera however can be considered as passive particles, their movement is carried by ocean currents. In consequence, the foraminifera abundance may represent more wider ocean condition according to the ocean current pattern. This study aims to examine the role of ocean currents in the distribution of foraminifera in the Sulawesi Sea. Ten gravity core sediment samples from 73-3009 m water depth were retrieved by RV Geomarin III from the Marine Geological Institute, Indonesia. We conducted quantitative analysis, including calculation of abundance and cluster analysis. Two decades (1992-2012) of ocean current simulated data from the Hybrid Coordinate Ocean Model (HYCOM) is used in this analysis, extending from 115°E-140°E and 8°N-2°S. The result indicates that planktonic foraminifera is abundant in the Sulawesi Sea by 86.3%. There were several predominant planktonic species such as Globigerinoides ruber (22.6%), Globigerina bulloides (15.3%), and Neoglobuquadrina dutertrei (10.1%). The ocean current above the sample location is constantly moving eastward as a part of the NECC. The average currents velocity shows that foraminifera in sample site S-03 with depth 2064 m may originated from up to 1035 kilometers away from its recent location.

scholarly journals Oil spill trajectory prediction assessment using multi model ocean currents - case study of MT Dawn Oil spill 2017

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
SJ Prasad ◽  
TM Balakrishnan Nair ◽  
T Vijayalakshmi
Keyword(s):  
Oil Spill ◽  
Ocean Circulation ◽  
Ocean Model ◽  
Ocean Currents ◽  
Fuel Oil ◽  
Global Ocean ◽  
Ocean Current ◽  
Trajectory Prediction ◽  
Heavy Fuel Oil ◽  
Trajectory Model

Abstract 684276 An assessment was carried out to judge the performance of the modeled ocean currents in oil spill trajectory prediction. Ocean circulation is the key factor in determining the drift pattern of the spilled marine oil pollutant. General National Oceanic and Atmospheric Administration Operational Modeling Environment (GNOME), an oil spill trajectory model, in diagnostic mode was set for simulating drift pattern of Heavy Fuel Oil (HFO). On 28 January 2017, 0345 hrs, Indian Standard Time (IST), approximately 196.4 MT of HFO was spilled due to vessel collision. The oil spill model was set and run during 28-Jan-2017 to 05-Feb-2017 with 196 tons of HFO. Wind velocity fields were obtained from European Centre for Medium-Range Weather Forecasts (ECMWF). The modeled ocean currents were obtained from High resolution Operational Ocean Forecasting and reanalysis System (HOOFS) with two model set ups such as Indian ocean (IO) and Bay Of Bengal (BOB). Ocean current pattern were also obtained from Hybrid Co-ordinate Ocean Model (HYCOM) and Global Ocean Data Assimilation System (GODAS) based Modular Ocean Model (GM4P1). The oil drift patterns were simulated individually for the spillage due to MT Dawn vessel, by forcing GNOME with the above said wind and ocean currents. Radar data obtained for 29-Jan-2017, from Sentinel -1A was processed for detecting oil slicks. The respective drift patterns obtained were compared individually with the oil slick signatures of Sentinel -1A on 29-Jan-2017. It was found that the drift pattern obtained while using the ocean currents of HOOFS_BOB was in better agreement with that of the observed slicks. Unlike other oil drift patterns, offshore spread of the slicks are well captured while using the ocean currents of HOOFS_BOB. This paper illustrates the method of oil spill trajectory prediction using various ocean currents and validating the simulated drift with the ground truth. It also emphasize the need of using various modeled ocean currents in assessing the performance of oil spill trajectory model.

Comparison of ADCP measurements to Kuroshio current flow simulations for ocean current turbines

2021 ◽  
pp. 147509022110236
Author(s):  
John Imamura ◽  
Ken Takagi ◽  
Shigeki Nagaya ◽  
Masayuki Shimizu
Keyword(s):  
Numerical Simulations ◽  
Time Domain ◽  
Current Flow ◽  
Measurement Data ◽  
Acoustic Doppler Current Profiler ◽  
Kuroshio Current ◽  
Ocean Model ◽  
Ocean Currents ◽  
Ocean Current ◽  
Flow Profile

Numerical simulations are compared to field measurements of ocean currents in the Tokara Strait in this work. The Kuroshio Current flows through this strait and an ongoing ocean current turbine device is under development to harness its energy. The usefulness for engineering design input of modeling flow conditions for a large domain in space and time motivates the use of the numerical simulations. Confidence in the accuracy of the simulations can be provided from this comparison to Acoustic Doppler Current Profiler (ADCP) observations during the summer of 2018 at four locations. Numerical simulations of ocean currents which overlap in time with the field observations are presented in an attempt to compare the data on a time-domain basis. The simulations were produced using a Princeton Ocean Model based JCOPE-T-Tokara500 model. The analysis describes the capability of the numerical model to match the flow profile throughout the water column in the time domain and on a statistical basis using histograms and rose diagrams. While instances of speed peaks in the measurement data possibly representing internal waves did not readily appear in the simulation, overall the analysis supports the continued use of simulation current flow for project design input.

Ultrastructure of Some Planktonic Formainifera

1974 ◽  
Vol 32 ◽  
pp. 190-191
Author(s):  
William H. Zucker
Keyword(s):  
Cell Biology ◽  
Water Mass ◽  
Planktonic Foraminifera ◽  
Uranyl Acetate ◽  
Ethanol Dehydration ◽  
Globigerinoides Ruber ◽  
Light Microscope Level ◽  
Globigerina Bulloides ◽  
Glutaraldehyde Solution ◽  
Diamond Knife

Planktonic foraminifera are widely-distributed and abundant zooplankters. They are significant as water mass indicators and provide evidence of paleotemperatures and events which occurred during Pleistocene glaciation. In spite of their ecological and paleological significance, little is known of their cell biology. There are few cytological studies of these organisms at the light microscope level and some recent reports of their ultrastructure.Specimens of Globigerinoides ruber, Globigerina bulloides, Globigerinoides conglobatus and Globigerinita glutinata were collected in Bermuda waters and fixed in a cold cacodylate-buffered 6% glutaraldehyde solution for two hours. They were then rinsed, post-fixed in Palade's fluid, rinsed again and stained with uranyl acetate. This was followed by graded ethanol dehydration, during which they were identified and picked clean of debris. The specimens were finally embedded in Epon 812 by placing each organism in a separate BEEM capsule. After sectioning with a diamond knife, stained sections were viewed in a Philips 200 electron microscope.

Disturbance learning controller design for unmanned surface vehicle using LSTM technique of recurrent neural network

2021 ◽  
pp. 1-11
Author(s):  
Sang-Ki Jeong ◽  
Dea-Hyeong Ji ◽  
Ji-Youn Oh ◽  
Jung-Min Seo ◽  
Hyeung-Sik Choi
Keyword(s):  
Neural Network ◽  
Control System ◽  
Flow Velocity ◽  
Recurrent Neural Network ◽  
Pid Controller ◽  
Short Term Memory ◽  
Ocean Currents ◽  
Ocean Current ◽  
Movement Speed ◽  
Marine Research

In this study, to effectively control small unmanned surface vehicles (USVs) for marine research, characteristics of ocean current were learned using the long short-term memory (LSTM) model algorithm of a recurrent neural network (RNN), and ocean currents were predicted. Using the results, a study on the control of USVs was conducted. A control system model of a small USV equipped with two rear thrusters and a front thruster arranged horizontally was designed. The system was also designed to determine the output of the controller by predicting the speed of the following currents and utilizing this data as a system disturbance by learning data from ocean currents using the LSTM algorithm of a RNN. To measure ocean currents on the sea when a small USV moves, the speed and direction of the ship’s movement were measured using speed, azimuth, and location (latitude and longitude) data from GPS. In addition, the movement speed of the fluid with flow velocity is measured using the installed flow velocity measurement sensor. Additionally, a control system was designed to control the movement of the USV using an artificial neural network-PID (ANN-PID) controller [12]. The ANN-PID controller can manage disturbances by adjusting the control gain. Based on these studies, the control results were analyzed, and the control algorithm was verified through a simulation of the applied control system [8, 9].

scholarly journals The features of the coastal fronts in the Eastern Guangdong coastal waters during the downwelling-favorable wind period

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chaoyu Yang ◽  
Haibin Ye
Keyword(s):  
Coastal Waters ◽  
Meteorological Data ◽  
Pearson Correlation ◽  
Ocean Model ◽  
Ekman Pumping ◽  
Zonal Distribution ◽  
Factors Affecting ◽  
China Sea ◽  
Hybrid Coordinate Ocean Model ◽  
The Mean

AbstractA coastal front was detected in the eastern Guangdong (EGD) coastal waters during a downwelling-favorable wind period by using the diffuse attenuation coefficient at 490 nm (Kd(490)). Long-term satellite data, meteorological data and hydrographic data collected from 2003 to 2017 were jointly utilized to analyze the environmental factors affecting coastal fronts. The intensities of the coastal fronts were found to be associated with the downwelling intensity. The monthly mean Kd(490) anomalies in shallow coastal waters less than 25 m deep along the EGD coast and the monthly mean Ekman pumping velocities retrieved by the ERA5 dataset were negatively correlated, with a Pearson correlation of − 0.71. The fronts started in October, became weaker and gradually disappeared after January, extending southwestward from the southeastern coast of Guangdong Province to the Wanshan Archipelago in the South China Sea (SCS). The cross-frontal differences in the mean Kd(490) values could reach 3.7 m−1. Noticeable peaks were found in the meridional distribution of the mean Kd(490) values at 22.5°N and 22.2°N and in the zonal distribution of the mean Kd(490) values at 114.7°E and 114.4°E. The peaks tended to narrow as the latitude increased. The average coastal surface currents obtained from the global Hybrid Coordinate Ocean Model (HYCOM) showed that waters with high nutrient and sediment contents in the Fujian and Zhejiang coastal areas in the southern part of the East China Sea could flow into the SCS. The directions and lengths of the fronts were found to be associated with the flow advection.

Multi-AUV Underwater Cooperative Search Algorithm based on Biological Inspired Neurodynamics Model and Velocity Synthesis

2015 ◽  
Vol 68 (6) ◽  
pp. 1075-1087 ◽  
Author(s):  
Xiang Cao ◽  
Daqi Zhu
Keyword(s):  
Autonomous Underwater Vehicle ◽  
Search Algorithm ◽  
Integrated Approach ◽  
Underwater Vehicle ◽  
Ocean Currents ◽  
Ocean Current ◽  
Cooperative Search ◽  
Search Path ◽  
Negative Effect ◽  
Underwater Target

Ocean currents impose a negative effect on Autonomous Underwater Vehicle (AUV) underwater target searches, which lengthens the search paths and consumes more energy and team effort. To solve this problem, an integrated algorithm is proposed to realise multi-AUV cooperative search in dynamic underwater environments with ocean currents. The proposed integrated algorithm combines the Biological Inspired Neurodynamics Model (BINM) and Velocity Synthesis (VS) method. Firstly, the BINM guides a team of AUVs to achieve target search in underwater environments; BINM search requires no specimen learning information and is thus easier to apply to practice, but the search path is longer because of the influence of ocean current. Next the VS algorithm offsets the effect of ocean current, and it is applied to optimise the search path for each AUV. Lastly, to demonstrate the effectiveness of the proposed integrated approach, simulation results are given in this paper. It is proved that this integrated algorithm can plan shorter search paths and thus the energy consumption is lower compared with BINM.

A New Solar Radiation Penetration Scheme for Use in Ocean Mixed Layer Studies: An Application to the Black Sea Using a Fine-Resolution Hybrid Coordinate Ocean Model (HYCOM)*

2005 ◽  
Vol 35 (1) ◽  
pp. 13-32 ◽  
Author(s):  
A. Birol Kara ◽  
Alan J. Wallcraft ◽  
Harley E. Hurlburt
Keyword(s):  
Solar Radiation ◽  
Optical Depth ◽  
Black Sea ◽  
Ocean Circulation ◽  
Mixed Layer ◽  
Ocean Model ◽  
The Black Sea ◽  
Atmospheric Forcing ◽  
Model Simulations ◽  
Hybrid Coordinate Ocean Model

Abstract A 1/25° × 1/25° cos(lat) (longitude × latitude) (≈3.2-km resolution) eddy-resolving Hybrid Coordinate Ocean Model (HYCOM) is introduced for the Black Sea and used to examine the effects of ocean turbidity on upper-ocean circulation features including sea surface height and mixed layer depth (MLD) on annual mean climatological time scales. The model is a primitive equation model with a K-profile parameterization (KPP) mixed layer submodel. It uses a hybrid vertical coordinate that combines the advantages of isopycnal, σ, and z-level coordinates in optimally simulating coastal and open-ocean circulation features. This model approach is applied to the Black Sea for the first time. HYCOM uses a newly developed time-varying solar penetration scheme that treats attenuation as a continuous quantity. This scheme includes two bands of solar radiation penetration, one that is needed in the top 10 m of the water column and another that penetrates to greater depths depending on the turbidity. Thus, it is suitable for any ocean general circulation model that has fine vertical resolution near the surface. With this scheme, the optical depth–dependent attenuation of subsurface heating in HYCOM is given by monthly mean fields for the attenuation of photosynthetically active radiation (kPAR) during 1997–2001. These satellite-based climatological kPAR fields are derived from Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) data for the spectral diffuse attenuation coefficient at 490 nm (k490) and have been processed to have the smoothly varying and continuous coverage necessary for use in the Black Sea model applications. HYCOM simulations are driven by two sets of high-frequency climatological forcing, but no assimilation of ocean data is then used to demonstrate the importance of including spatial and temporal varying attenuation depths for the annual mean prediction of upper-ocean quantities in the Black Sea, which is very turbid (kPAR > 0.15 m−1, in general). Results are reported from three model simulations driven by each atmospheric forcing set using different values for the kPAR. A constant solar-attenuation optical depth of ≈17 m (clear water assumption), as opposed to using spatially and temporally varying attenuation depths, changes the surface circulation, especially in the eastern Black Sea. Unrealistic sub–mixed layer heating in the former results in weaker stratification at the base of the mixed layer and a deeper MLD than observed. As a result, the deep MLD off Sinop (at around 42.5°N, 35.5°E) weakens the surface currents regardless of the atmospheric forcing used in the model simulations. Using the SeaWiFS-based monthly turbidity climatology gives a shallower MLD with much stronger stratification at the base and much better agreement with observations. Because of the high Black Sea turbidity, the simulation with all solar radiation absorbed at the surface case gives results similar to the simulations using turbidity from SeaWiFS in the annual means, the aspect of the results investigated in this paper.

scholarly journals Detection of Fronts as a Metric for Numerical Model Accuracy

2019 ◽  
Vol 36 (8) ◽  
pp. 1547-1561
Author(s):  
Elizabeth M. Douglass ◽  
Andrea C. Mask
Keyword(s):  
Numerical Model ◽  
Region Of Interest ◽  
Ocean Model ◽  
Minimum Size ◽  
Model Output ◽  
Oceanic Fronts ◽  
Hybrid Coordinate Ocean Model ◽  
Quantitative Metrics ◽  
Coastal Ocean Model ◽  
Along Track

AbstractAs numerical modeling advances, quantitative metrics are necessary to determine whether the model output accurately represents the observed ocean. Here, a metric is developed based on whether a model places oceanic fronts in the proper location. Fronts are observed and assessed directly from along-track satellite altimetry. Numerical model output is then interpolated to the locations of the along-track data, and fronts are detected in the model output. Scores are determined from the percentage of observed fronts correctly simulated in the model and from the percentage of modeled fronts confirmed by observations. These scores depend on certain parameters such as the minimum size of a front, which will be shown to be geographically dependent. An analysis of two models, the Hybrid Coordinate Ocean Model (HYCOM) and the Navy Coastal Ocean Model (NCOM), is presented as an example of how this metric might be applied and interpreted. In this example, scores are found to be relatively stable in time, but strongly dependent on the mesoscale variability in the region of interest. In all cases, the metric indicates that there are more observed fronts not found in the models than there are modeled fronts missing from observations. In addition to the score itself, the analysis demonstrates that modeled fronts have smaller amplitude and are less steep than observed fronts.

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