Ocean Surface Currents in the northern Nordic Seas from a combination of multi-mission satellite altimetry and numerical modeling

Satellite altimetry is an important part of the Global Geodetic Observing System providing precise information on sea level on different spatial and temporal scales. Moreover, satellite altimetry-derived dynamic ocean topography heights enable the computation of ocean surface currents by applying the well-known geostrophic equations. However, in polar regions, altimetry observations are affected by seasonally changing sea-ice cover leading to a fragmentary data sampling.In order to overcome this problem, an ocean model is used to fill in data gaps. The aim is to obtain a homogeneous ocean topography representation that enables consistent investigations of ocean surface current changes. For that purpose, the global Finite Element Sea-ice Ocean Model (FESOM) is used. It is based on an unstructured grid and provides daily water elevations with high spatial resolution.The combination is done based on a Principal Component Analysis (PCA) after reducing both quantities by their constant and seasonal signals. In the main step, the most dominant spatial patterns of the modeled water heights as provided by the PCA are linked with the temporal variability of the estimated dynamic ocean topography elevations from altimetry. At the end, the seasonal signal as well as the absolute reference from altimetry is added back to the data set.This contribution describes the combination process as well as the generated final product: a daily, more than 17 years covering dataset of geostrophic ocean currents. The combination is done for the marine regions Greenland Sea, Barents Sea and the Fram Strait and includes sea surface height observations of the ESA altimeter satellites ERS-2 and Envisat. In order to evaluate the combination results, independent surface drifter observations, corrected for a-geostrophic velocity components, are used.

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Ocean Model Simulation of Southern Indian Ocean Surface Currents

Marine Geodesy ◽

10.1080/01490410701568467 ◽

2007 ◽

Vol 30 (4) ◽

pp. 345-354 ◽

Cited By ~ 2

Author(s):

Anshu Prakash Mishra ◽

S. Rai ◽

A. C. Pandey

Keyword(s):

Indian Ocean ◽

Model Simulation ◽

Ocean Surface ◽

Ocean Model ◽

Southern Indian Ocean ◽

Surface Currents ◽

Ocean Surface Currents

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Geostrophic Currents in the northern Nordic Seas from a Combination of Multi-Mission Satellite Altimetry and Ocean Modeling

10.5194/essd-2019-102 ◽

2019 ◽

Author(s):

Felix L. Müller ◽

Denise Dettmering ◽

Claudia Wekerle ◽

Christian Schwatke ◽

Marcello Passaro ◽

...

Keyword(s):

Sea Ice ◽

Spatial Patterns ◽

Temporal Variability ◽

Satellite Altimetry ◽

Principal Component ◽

Ocean Model ◽

Surface Currents ◽

Geostrophic Velocity ◽

Nordic Seas ◽

Along Track

Abstract. A deeper knowledge about geostrophic ocean surface currents in the northern Nordic Seas supports the understanding of ocean dynamics in an area affected by sea ice and rapidly changing environmental conditions. Monitoring these areas by satellite altimetry results in a fragmented and irregularly distributed data sampling and prevents the computation of homogeneous and highly resolved spatio-temporal datasets. In order to overcome this problem, an ocean model is used to fill in data when altimetry observations are missing. The present study provides a novel dataset based on a combination of along-track satellite altimetry derived dynamic ocean topography (DOT) elevations and simulated differential water heights (DWH) from the Finite Element Sea ice Ocean Model (FESOM). This innovative dataset differs from classical assimilation methods because it substitutes altimetry data with the model output, when altimetry fails or is not available. The combination approach is mainly based on a Principal Component Analysis (PCA) after reducing both quantities by their constant and seasonal signals. In the main step, the most dominant spatial patterns of the modeled differential water heights as provided by the PCA are linked with the temporal variability of the estimated DOT from altimetry by performing a Principal Component Synthesis (PCS). After the combination, the by altimetry obtained annual signal and a constant offset are re-added in order to reference the final data product to the altimetry height level. Surface currents are computed by applying the geostrophic flow equations to the combined topography. The resulting final product is characterized by the spatial resolution of the ocean model around 1 km and the temporal variability of the altimetry along-track derived DOT heights. The combined DOT is compared to an independent DOT product resulting in a positive correlation of about 80 % to provide more detailed information about short periodic and finer spatial structures. The derived geostrophic velocity components are evaluated by in-situ surface drifter observations. Summarizing all drifter observations in equal-sized bins and comparing the velocity components shows good agreement in spatial patterns, magnitude and flow direction. Mean differences of 0.004 m/s in the zonal and 0.02 m/s in the meridional component are observed. A direct pointwise comparison between the drifter trajectories and to the drifter location interpolated combined geostrophic velocity components indicates that about 94 % of all residuals are smaller than 0.15 m/s. The dataset is able to provide surface circulation information within the sea ice area and can be used to support a deeper comprehension of ocean currents in the northern Nordic Seas affected by rapid environmental changes in the 1995–2012 time period. The data is available at https://doi.org/10.1594/PANGAEA.900691 (Müller et al., 2019).

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Ocean surface dynamics derived from TerraSAR-X/TanDEM-X and hydrodynamic modeling

10.5194/egusphere-egu2020-9454 ◽

2020 ◽

Author(s):

Andreas Lehmann ◽

Steffen Suchandt

Keyword(s):

Hydrodynamic Model ◽

Ocean Surface ◽

Reanalysis Data ◽

Ocean Model ◽

Hydrodynamic Modeling ◽

Surface Currents ◽

Wind Fields ◽

Modeling Methodology ◽

Ocean Surface Currents ◽

The Baltic

Dynamical processes at the ocean surface are of high interest because they control the exchange processes between ocean and atmosphere. Furthermore, ocean surface drift determines the dispersion of heat, salt and material such as harmful substances or plastic litter. Still the measurement of ocean surface currents is a challenge because of wave and wave-breaking processes. Here we demonstrate the usefulness of TerraSAR-X/TanDEM-X data to determine ocean surface currents, wave and wind fields. Up to now there are no spatially resolved ocean surface currents measurements available, so that for the validation of surface currents a combined SAR and hydrodynamic modeling methodology is applied. Ocean surface currents are derived from SAR Along-track Interferometry, and the hydrodynamic model is a coupled wave sea ice-ocean model of the Baltic Sea. The model is driven by ERA-Interim atmospheric reanalysis data. Hydrodynamic model data are also used to support the geophysical interpretation of the multiparametrical information of the ocean surface provided by SAR.

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Geostrophic currents in the northern Nordic Seas from a combination of multi-mission satellite altimetry and ocean modeling

Earth System Science Data ◽

10.5194/essd-11-1765-2019 ◽

2019 ◽

Vol 11 (4) ◽

pp. 1765-1781 ◽

Cited By ~ 1

Author(s):

Felix L. Müller ◽

Denise Dettmering ◽

Claudia Wekerle ◽

Christian Schwatke ◽

Marcello Passaro ◽

...

Keyword(s):

Sea Ice ◽

Spatial Patterns ◽

Temporal Variability ◽

Satellite Altimetry ◽

Principal Component ◽

Ocean Model ◽

Surface Currents ◽

Geostrophic Velocity ◽

Nordic Seas ◽

Along Track

Abstract. A deeper knowledge about geostrophic ocean surface currents in the northern Nordic Seas supports the understanding of ocean dynamics in an area affected by sea ice and rapidly changing environmental conditions. Monitoring these areas by satellite altimetry results in a fragmented and irregularly distributed data sampling and prevents the computation of homogeneous and highly resolved spatio-temporal datasets. In order to overcome this problem, an ocean model is used to fill in data when altimetry observations are missing. The present study provides a novel dataset based on a combination of along-track satellite-altimetry-derived dynamic ocean topography (DOT) elevations and simulated differential water heights (DWHs) from the Finite Element Sea ice Ocean Model (FESOM) version 1.4. This innovative dataset differs from classical assimilation methods because it substitutes altimetry data with the model output when altimetry fails or is not available. The combination approach is mainly based on a principal component analysis (PCA) after reducing both quantities by their constant and seasonal signals. In the main step, the most-dominant spatial patterns of the modeled differential water heights as provided by the PCA are linked with the temporal variability in the estimated DOT from altimetry by performing a principal component synthesis (PCS). After the combination, the annual signal obtained by altimetry and a constant offset are re-added in order to reference the final data product to the altimetry height level. Surface currents are computed by applying the geostrophic flow equations to the combined topography. The resulting final product is characterized by the spatial resolution of the ocean model around 1 km and the temporal variability in the altimetry along-track derived DOT heights. The combined DOT is compared to an independent DOT product, resulting in a positive correlation of about 80 %, to provide more detailed information about short periodic and finer spatial structures. The derived geostrophic velocity components are evaluated by in situ surface drifter observations. Summarizing all drifter observations in equally sized bins and comparing the velocity components shows good agreement in spatial patterns, magnitude and flow direction. Mean differences of 0.004 m s−1 in the zonal and 0.02 m s−1 in the meridional component are observed. A direct pointwise comparison between the combined geostrophic velocity components interpolated onto the drifter locations indicates that about 94 % of all residuals are smaller than 0.15 m s−1. The dataset is able to provide surface circulation information within the sea ice area and can be used to support a deeper comprehension of ocean currents in the northern Nordic Seas affected by rapid environmental changes in the 1995–2012 time period. The data are available at https://doi.org/10.1594/PANGAEA.900691 (Müller et al., 2019).

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Impacts of Changed Ice-Ocean Stress on the North Atlantic Ocean: Role of Ocean Surface Currents

Frontiers in Marine Science ◽

10.3389/fmars.2021.628892 ◽

2021 ◽

Vol 8 ◽

Author(s):

Yang Wu ◽

Zhaomin Wang ◽

Chengyan Liu

Keyword(s):

Atlantic Ocean ◽

Sea Ice ◽

North Atlantic ◽

North Atlantic Ocean ◽

Ocean Surface ◽

Surface Currents ◽

Stress Calculation ◽

The North ◽

Ocean Surface Currents ◽

The North Atlantic

The importance of considering ocean surface currents in ice-ocean stress calculation in the North Atlantic Ocean and Arctic sea ice is investigated for the first time using a global coupled ocean-sea ice model. Considering ocean surface currents in ice-ocean stress calculation weakens the ocean surface stress and Ekman pumping by about 7.7 and 15% over the North Atlantic Ocean, respectively. It also significantly reduces the mechanical energy input to ageostrophic and geostrophic currents, and weakens the mean and eddy kinetic energy by reducing the energy conversion rates of baroclinic and barotropic pathways. Furthermore, the strength of the Atlantic Meridional Overturning Circulation (AMOC), the Nordic Seas MOC, and the North Atlantic subpolar gyre are found to be reduced considerably (by 14.3, 31.0, and 18.1%, respectively). The weakened AMOC leads to a 0.12 PW reduction in maximum northward ocean heat transport, resulting in a reduced surface heat loss and lower sea surface temperature over the North Atlantic Ocean. This reduction also leads to a shrink in sea ice extent and an attenuation of sea ice thickness. These findings highlight the importance of properly considering both the geostrophic and ageostrophic components of ocean surface currents in ice-ocean stress calculation on ocean circulation and climate studies.

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Dynamic ocean topography of the northern Nordic seas: a comparison between satellite altimetry and ocean modeling

The Cryosphere ◽

10.5194/tc-13-611-2019 ◽

2019 ◽

Vol 13 (2) ◽

pp. 611-626 ◽

Cited By ~ 5

Author(s):

Felix L. Müller ◽

Claudia Wekerle ◽

Denise Dettmering ◽

Marcello Passaro ◽

Wolfgang Bosch ◽

...

Keyword(s):

Sea Ice ◽

Satellite Altimetry ◽

Ocean Model ◽

Irregular Sampling ◽

Ocean Modeling ◽

Nordic Seas ◽

Comparison Results ◽

Ocean Topography ◽

Annual Signal ◽

Good Agreement

Abstract. The dynamic ocean topography (DOT) of the polar seas can be described by satellite altimetry sea surface height observations combined with geoid information as well as by ocean models. The altimetry observations are characterized by an irregular sampling and seasonal sea ice coverage complicating reliable DOT estimations. Models display various spatiotemporal resolutions but are limited to their computational and mathematical context and introduced forcing models. In the present paper, ALES+ retracked altimetry ranges and derived along-track DOT heights of ESA's Envisat and water heights of the Finite Element Sea Ice-Ocean Model (FESOM) are compared to investigate similarities and discrepancies. The goal of the present paper is to identify to what extent pattern and variability of the northern Nordic seas derived from measurements and model agree with each other, respectively. The study period covers the years 2003–2009. An assessment analysis regarding seasonal DOT variabilities shows good agreement and confirms the dominant impact of the annual signal in both datasets. A comparison based on estimated regional annual signal components shows 2–3 times stronger amplitudes of the observations but good agreement of the phase. Reducing both datasets by constant offsets and the annual signal reveals small regional residuals and highly correlated DOT time series (Pearson linear correlation coefficient of at least 0.67). The highest correlations can be found in areas that are ice-free and affected by ocean currents. However, differences are visible in sea-ice-covered shelf regions. Furthermore, remaining constant artificial elevations in the observational data can be attributed to an insufficient representation of the used geoid. In general, the comparison results in good agreement between simulated and altimetry-based descriptions of the DOT in the northern Nordic seas.

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