Global ocean current reconstruction from altimetric and microwave SST measurements

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.

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Antarctic Circumpolar Current Biases in a hierarchy of HadGEM3-GC3.1 Models

10.5194/egusphere-egu2020-11444 ◽

2020 ◽

Author(s):

Tomas Jonathan ◽

Helen Johnson ◽

David Marshall ◽

Mike Bell ◽

Patrick Hyder

Keyword(s):

Ocean Circulation ◽

Antarctic Circumpolar Current ◽

Reverse Flow ◽

Volume Transport ◽

Ekman Transport ◽

Global Ocean ◽

Ocean Current ◽

Density Profiles ◽

Southern Boundary ◽

Circumpolar Current

The Southern Ocean is a crucial part of the global ocean circulation. The unique bathymetry and lack of meridional boundary in conjunction with an equator to pole temperature gradient and strong westerly winds results in an eastward flowing Antarctic Circumpolar Current (ACC). The ACC is the strongest ocean current in the world (173.3 &#177; 10.7Sv), vital in transporting heat, carbon and nutrients between the major ocean basins.&#160;Using prototype UK CMIP6 (HadGEM3-GC3.1) simulations at 1&#176;, 1/4&#176; and 1/12&#176; spatial resolutions we illustrate the strong resolution dependence of the strength of the ACC through the Drake Passage. All three model resolutions exhibit a weak ACC compared to observations. The 1/4&#176; and 1/12&#176; models show a significant weakening over the first 50 years, stabilizing at 60Sv and 120Sv respectively.We analyse the source of the weaker volume transport by decomposing the ACC transport into components arising due to northern and southern boundary density profiles (relative to the bottom density), Ekman transport and depth-independent flow. We attribute the weaker ACC in the 1/4&#176; model to a lightening of the southern density profile and the formation of a reverse flow along the coast of Antarctica.Our decomposition highlights the significant contribution to the ACC&#8217;s volume transport and variability made by both northern and southern density profiles, as well as the depth-independent component of the flow.

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ENSO-Related Global Ocean Heat Content Variations

Journal of Climate ◽

10.1175/jcli-d-17-0861.1 ◽

2018 ◽

Vol 32 (1) ◽

pp. 45-68 ◽

Cited By ~ 5

Author(s):

Quran Wu ◽

Xuebin Zhang ◽

John A. Church ◽

Jianyu Hu

Keyword(s):

Heat Exchange ◽

El Niño ◽

El Nino ◽

Southern Oscillation ◽

Heat Content ◽

Vertical Direction ◽

Ocean Heat Content ◽

Global Ocean ◽

Ocean Current ◽

Enso Events

Abstract The modulation of the full-depth global integrated ocean heat content (GOHC) by El Niño–Southern Oscillation (ENSO) has been estimated in various studies. However, the quantitative results and the mechanisms at work remain uncertain. Here, a dynamically consistent ocean state estimate is utilized to study the large-scale integrated heat content variations during ENSO events for the global ocean. The full-depth GOHC exhibits a cooling tendency during the peak and decaying phases of El Niño, which is a result of the negative surface heat flux (SHF) anomaly in the tropics (30°S–30°N), partially offset by the positive SHF anomaly at higher latitudes. The tropical SHF anomaly acts as a lagged response to damp the convergence of oceanic heat transport, which redistributes heat from the extratropics and the subsurface layers (100–440 m) into the upper tropical oceans (0–100 m) during the onset and peak of El Niño. These results highlight the global nature of the oceanic heat redistribution during ENSO events, as well as how the redistribution process affects the full-depth GOHC. The meridional heat exchange across 30°S and 30°N is driven by ocean current anomalies, while multiple processes contribute to the vertical heat exchange across 100 m simultaneously. Heat advection due to unbalanced mass transport is distinguished from the mass balanced one, with significant contributions from the meridional and zonal overturning cells being identified for the latter in the vertical direction. Results presented here have implications for monitoring the planetary energy budget and evaluating ENSO’s global imprints on ocean heat content in different estimates.

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Ocean-wide sensor array provides new look at global ocean current

Nature ◽

10.1038/d41586-018-02113-y ◽

2018 ◽

Vol 554 (7693) ◽

pp. 413-414

Author(s):

Jeff Tollefson

Keyword(s):

Sensor Array ◽

Global Ocean ◽

Ocean Current ◽

New Look

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Feedback of mesoscale ocean currents on atmospheric winds in high-resolution coupled models and implications for the forcing of ocean-only models

10.5194/os-2017-24 ◽

2017 ◽

Cited By ~ 3

Author(s):

Rafael Abel ◽

Claus W. Böning ◽

Richard J. Greatbatch ◽

Helene T. Hewitt ◽

Malcolm J. Roberts

Keyword(s):

Climate Model ◽

Global Climate Model ◽

Surface Wind ◽

Ocean Currents ◽

Global Ocean ◽

Ocean Current ◽

Western Boundary ◽

Coupling Coefficients ◽

Coupled Models ◽

Near Surface

Abstract. The repercussions of surface ocean currents for the near-surface wind and the air-sea momentum flux are investigated in two versions of a global climate model with eddying ocean. The focus is on the effect of mesoscale ocean current features at scales of less than 150 km, by considering high-pass filtered, monthly-mean model output fields. We find a clear signature of a mesoscale oceanic imprint in the wind fields over the energetic areas of the oceans, particularly along the extensions of the western boundary currents and the Antarctic Circumpolar Current. These areas are characterized by a positive correlation between mesoscale perturbations in the curl of the surface currents and the wind curl. The coupling coefficients are spatially non-uniform and show a pronounced seasonal cycle. The positive feedback of mesoscale current features on the near-surface wind acts in opposition to their damping effect on the wind stress. A tentative incorporation of this feedback in the surface stress formulation of an eddy-permitting global ocean-only model leads to a gain in the kinetic energy of up to 10 %, suggesting a fundamental shortcoming of present ocean model configurations.

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Improvement of Ocean State Estimation by Assimilating Mapped Argo Drift Data

The Scientific World JOURNAL ◽

10.1155/2014/975618 ◽

2014 ◽

Vol 2014 ◽

pp. 1-6

Author(s):

Shuhei Masuda ◽

Nozomi Sugiura ◽

Satoshi Osafune ◽

Toshimasa Doi

Keyword(s):

State Estimation ◽

Current Data ◽

Global Ocean ◽

Ocean Current ◽

Oceanic Circulation ◽

Synthesis System ◽

Wind Stress Curl ◽

Data Synthesis ◽

Ocean State Estimation ◽

The Impact

We investigated the impact of assimilating a mapped dataset of subsurface ocean currents into an ocean state estimation. We carried out two global ocean state estimations from 2000 to 2007 using the K7 four-dimensional variational data synthesis system, one of which included an additional map of climatological geostrophic currents estimated from the global set of Argo floats. We assessed the representativeness of the volume transport in the two exercises. The assimilation of Argo ocean current data at only one level, 1000 dbar depth, had subtle impacts on the estimated volume transports, which were strongest in the subtropical North Pacific. The corrections at 10°N, where the impact was most notable, arose through the nearly complete offset of wind stress curl by the data synthesis system in conjunction with the first mode baroclinic Rossby wave adjustment. Our results imply that subsurface current data can be effective for improving the estimation of global oceanic circulation by a data synthesis.

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A Deep Learning Model for Forecasting Velocity Structures of the Loop Current System in the Gulf of Mexico

Forecasting ◽

10.3390/forecast3040056 ◽

2021 ◽

Vol 3 (4) ◽

pp. 934-953

Author(s):

Ali Muhamed Ali ◽

Hanqi Zhuang ◽

James VanZwieten ◽

Ali K. Ibrahim ◽

Laurent Chérubin

Keyword(s):

Deep Learning ◽

Gulf Of Mexico ◽

Short Term Memory ◽

Numerical Models ◽

Current System ◽

Ocean Modeling ◽

Global Ocean ◽

Ocean Current ◽

Loop Current

Despite the large efforts made by the ocean modeling community, such as the GODAE (Global Ocean Data Assimilation Experiment), which started in 1997 and was renamed as OceanPredict in 2019, the prediction of ocean currents has remained a challenge until the present day—particularly in ocean regions that are characterized by rapid changes in their circulation due to changes in atmospheric forcing or due to the release of available potential energy through the development of instabilities. Ocean numerical models’ useful forecast window is no longer than two days over a given area with the best initialization possible. Predictions quickly diverge from the observational field throughout the water and become unreliable, despite the fact that they can simulate the observed dynamics through other variables such as temperature, salinity and sea surface height. Numerical methods such as harmonic analysis are used to predict both short- and long-term tidal currents with significant accuracy. However, they are limited to the areas where the tide was measured. In this study, a new approach to ocean current prediction based on deep learning is proposed. This method is evaluated on the measured energetic currents of the Gulf of Mexico circulation dominated by the Loop Current (LC) at multiple spatial and temporal scales. The approach taken herein consists of dividing the velocity tensor into planes perpendicular to each of the three Cartesian coordinate system directions. A Long Short-Term Memory Recurrent Neural Network, which is best suited to handling long-term dependencies in the data, was thus used to predict the evolution of the velocity field in each plane, along each of the three directions. The predicted tensors, made of the planes perpendicular to each Cartesian direction, revealed that the model’s prediction skills were best for the flow field in the planes perpendicular to the direction of prediction. Furthermore, the fusion of all three predicted tensors significantly increased the overall skills of the flow prediction over the individual model’s predictions. The useful forecast period of this new model was greater than 4 days with a root mean square error less than 0.05 cm·s−1 and a correlation coefficient of 0.6.

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Ocean current and wave effects on wind stress drag coefficient over the global ocean

Geophysical Research Letters ◽

10.1029/2006gl027849 ◽

2007 ◽

Vol 34 (1) ◽

Cited By ~ 36

Author(s):

A. Birol Kara ◽

E. Joseph Metzger ◽

Mark A. Bourassa

Keyword(s):

Drag Coefficient ◽

Wind Stress ◽

Global Ocean ◽

Ocean Current ◽

Wave Effects

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Genomic evidence for global ocean plankton biogeography shaped by large-scale current systems

10.1101/867739 ◽

2019 ◽

Cited By ~ 7

Author(s):

Daniel J. Richter ◽

Romain Watteaux ◽

Thomas Vannier ◽

Jade Leconte ◽

Paul Frémont ◽

...

Keyword(s):

Large Scale ◽

Community Dynamics ◽

Environmental Data ◽

Global Ocean ◽

Ocean Current ◽

Regional Heterogeneity ◽

Size Dependent ◽

Physical Context ◽

Technological Advances ◽

Basin Scale

AbstractBiogeographical studies have traditionally focused on readily visible organisms, but recent technological advances are enabling analyses of the large-scale distribution of microscopic organisms, whose biogeographical patterns have long been debated. Here we assessed the global structure of plankton geography and its relation to the biological, chemical and physical context of the ocean (the ‘seascape’) by analyzing metagenomes of plankton communities sampled across oceans during the Tara Oceans expedition, in light of environmental data and ocean current transport. Using a consistent approach across organismal sizes that provides unprecedented resolution to measure changes in genomic composition between communities, we report a pan-ocean, size-dependent plankton biogeography overlying regional heterogeneity. We found robust evidence for a basin-scale impact of transport by ocean currents on plankton biogeography, and on a characteristic timescale of community dynamics going beyond simple seasonality or life history transitions of plankton.

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