Satellite Observations of Mesoscale Eddy-Induced Ekman Pumping

AbstractThree mechanisms for self-induced Ekman pumping in the interiors of mesoscale ocean eddies are investigated. The first arises from the surface stress that occurs because of differences between surface wind and ocean velocities, resulting in Ekman upwelling and downwelling in the cores of anticyclones and cyclones, respectively. The second mechanism arises from the interaction of the surface stress with the surface current vorticity gradient, resulting in dipoles of Ekman upwelling and downwelling. The third mechanism arises from eddy-induced spatial variability of sea surface temperature (SST), which generates a curl of the stress and therefore Ekman pumping in regions of crosswind SST gradients. The spatial structures and relative magnitudes of the three contributions to eddy-induced Ekman pumping are investigated by collocating satellite-based measurements of SST, geostrophic velocity, and surface winds to the interiors of eddies identified from their sea surface height signatures. On average, eddy-induced Ekman pumping velocities approach O(10) cm day−1. SST-induced Ekman pumping is usually secondary to the two current-induced mechanisms for Ekman pumping. Notable exceptions are the midlatitude extensions of western boundary currents and the Antarctic Circumpolar Current, where SST gradients are strong and all three mechanisms for eddy-induced Ekman pumping are comparable in magnitude. Because the polarity of current-induced curl of the surface stress opposes that of the eddy, the associated Ekman pumping attenuates the eddies. The decay time scale of this attenuation is proportional to the vertical scale of the eddy and inversely proportional to the wind speed. For typical values of these parameters, the decay time scale is about 1.3 yr.

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what do we not know about the sea-surface wind stress1

Bulletin of the American Meteorological Society ◽

10.1175/1520-0477-49.3.247 ◽

1968 ◽

Vol 49 (3) ◽

pp. 247-253 ◽

Cited By ~ 23

Author(s):

E. B. Kraus

Keyword(s):

Drag Coefficient ◽

North Atlantic ◽

Surface Stress ◽

Surface Wind ◽

Sea Surface ◽

The North ◽

Sea Surface Wind ◽

The North Atlantic ◽

Simple Sampling ◽

Range Of Values

A simple sampling experiment gives a several octave range of values for the zonal surface stress obtainable from synoptic maps over the North Atlantic. Uncertainty about the value of the drag coefficient account for about half the variance. The different methods that have been used to specify this quantity are reviewed and an attempt is made to state explicitly the assumptions involved in each case.

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Short-Term Response of Chlorophyll-a Concentration to Change in Sea Surface Wind Field over Mesoscale Eddy

Estuaries and Coasts ◽

10.1007/s12237-019-00643-w ◽

2019 ◽

Vol 43 (3) ◽

pp. 646-660 ◽

Cited By ~ 3

Author(s):

Ji-Eun Park ◽

Kyung-Ae Park ◽

Chang-Keun Kang ◽

Young-Je Park

Keyword(s):

Chlorophyll A ◽

Wind Field ◽

Surface Wind ◽

Mesoscale Eddy ◽

Sea Surface ◽

Short Term ◽

Chlorophyll A Concentration ◽

Sea Surface Wind ◽

Surface Wind Field ◽

Term Response

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Summer Phytoplankton Blooms Induced by Upwelling in the Western South China Sea

Frontiers in Marine Science ◽

10.3389/fmars.2021.740130 ◽

2021 ◽

Vol 8 ◽

Author(s):

Ying Chen ◽

Haiyi Shi ◽

Hui Zhao

Keyword(s):

South China Sea ◽

South China ◽

Surface Wind ◽

Remote Sensing Data ◽

Sea Surface ◽

Ekman Transport ◽

Ekman Pumping ◽

Phytoplankton Blooms ◽

China Sea ◽

Western South China Sea

During summer, phytoplankton blooms occur frequently off the southeast Vietnam coast in the western South China Sea (WSCS). Using multi-source remote sensing data, such as sea surface temperature (SST), sea surface wind (SSW), aerosol optical thickness (AOT), sea level anomalies (SLA), and chlorophyll-a (Chl-a) data from 1998 to 2020 and in situ observations of analyzed data, we report the patterns of spatial variation of summer phytoplankton blooms in this region. The partial correlation and multiple stepwise linear regression analyses reveal that Ekman transport (ET) and Ekman pumping velocity (EPV) exert a greater impact on the summer phytoplankton blooms than the other environmental factors, suggesting that the phytoplankton blooms in the region may be mainly triggered by the enhanced nutrients by wind-induced upwelling and vertical mixing. AOT only weakly correlates with Chl-a concentration in the region, probably these prominent abundant nutrients in the region come from upwelling and convective-overturn. A northeastward jet causes the distribution of high Chl-a in the WSCS to be plume-shaped. A new finding in this study is that the northward current in this area may cause the northward deviation of phytoplankton blooms from the areas of upwelling.

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On Estimating the Surface Wind Stress over the Sea

Journal of Physical Oceanography ◽

10.1175/jpo-d-17-0267.1 ◽

2018 ◽

Vol 48 (7) ◽

pp. 1533-1541 ◽

Cited By ~ 7

Author(s):

Larry Mahrt ◽

Scott Miller ◽

Tihomir Hristov ◽

James Edson

Keyword(s):

Surface Stress ◽

Momentum Flux ◽

Friction Velocity ◽

Surface Wind ◽

Sea Surface ◽

Surface Wind Stress ◽

Relationship Of ◽

Marine Boundary Layers ◽

The Relationship ◽

Surface Momentum Flux

AbstractOur study analyzes measurements primarily from two Floating Instrument Platform (FLIP) field programs and from the Air–Sea Interaction Tower (ASIT) site to examine the relationship between the wind and sea surface stress for contrasting conditions. The direct relationship of the surface momentum flux to U2 is found to be better posed than the relationship between and U, where U is the wind speed and is the friction velocity. Our datasets indicate that the stress magnitude often decreases significantly with height near the surface due to thin marine boundary layers and/or enhanced stress divergence close to the sea surface. Our study attempts to correct the surface stress estimated from traditional observational levels by using multiple observational levels near the surface and extrapolating to the surface. The effect of stability on the surface stress appears to be generally smaller than errors due to the stress divergence. Definite conclusions require more extensive measurements close to the sea surface.

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The surface thermal signature and air–sea coupling over the Agulhas rings propagating in the South Atlantic Ocean interior

Ocean Science ◽

10.5194/os-10-633-2014 ◽

2014 ◽

Vol 10 (4) ◽

pp. 633-644 ◽

Cited By ~ 9

Author(s):

J. M. A. C. Souza ◽

B. Chapron ◽

E. Autret

Keyword(s):

Boundary Layer ◽

Atlantic Ocean ◽

Surface Temperature ◽

Atmospheric Boundary Layer ◽

Sea Surface Temperature ◽

Surface Wind ◽

Sea Surface ◽

Ekman Pumping ◽

Marine Atmospheric Boundary Layer ◽

Sst Anomalies

Abstract. The surface signature of Agulhas rings propagating across the South Atlantic Ocean is observed based on three independent data sets: Advanced Microwave Scanning Radiometer for the Earth Observing System/Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) (TMI/AMSR-E) satellite sea surface temperature, Argo profiling floats and a merged winds product derived from scatterometer observations and reanalysis results. A persistent pattern of cold (negative) sea surface temperature (SST) anomalies in the eddy core, with warm (positive) anomalies at the boundary, is revealed. This pattern contrasts with the classical idea of a warm core anticyclone. Taking advantage of a moving reference frame corresponding to the altimetry-detected Agulhas rings, modifications of the surface winds by the ocean-induced currents and SST gradients are evaluated using satellite SST and wind observations. As obtained, the averaged stationary thermal expression and mean eddy-induced circulation are coupled to the marine atmospheric boundary layer, leading to surface wind anomalies. Consequently, an average Ekman pumping associated with these mean surface wind variations consistently emerges. This average Ekman pumping is found to explain very well the SST anomaly signatures of the detected Agulhas rings. Particularly, this mechanism seems to be the key factor determining that these anticyclonic eddies exhibit stationary imprints of cold SST anomalies near their core centers. A residual phase with the maximum sea surface height (SSH) anomaly and wind speed anomaly is found to the right of the mean wind direction, apparently maintaining a coherent stationary thermal expression coupled to the marine atmospheric boundary layer.

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Exploring the Role of the “Ice–Ocean Governor” and Mesoscale Eddies in the Equilibration of the Beaufort Gyre: Lessons from Observations

Journal of Physical Oceanography ◽

10.1175/jpo-d-18-0223.1 ◽

2020 ◽

Vol 50 (1) ◽

pp. 269-277 ◽

Cited By ~ 1

Author(s):

Gianluca Meneghello ◽

Edward Doddridge ◽

John Marshall ◽

Jeffery Scott ◽

Jean-Michel Campin

Keyword(s):

Time Scales ◽

Mesoscale Eddy ◽

Sea Surface ◽

Height Anomaly ◽

Ekman Pumping ◽

Layer Model ◽

Beaufort Gyre ◽

Two Layer Model ◽

Sea Surface Height Anomaly

AbstractObservations of Ekman pumping, sea surface height anomaly, and isohaline depth anomaly over the Beaufort Gyre are used to explore the relative importance and role of (i) feedbacks between ice and ocean currents, dubbed the “ice–ocean governor,” and (ii) mesoscale eddy processes in the equilibration of the Beaufort Gyre. A two-layer model of the gyre is fit to observations and used to explore the mechanisms governing the gyre evolution from the monthly to the decennial time scale. The ice–ocean governor dominates the response on interannual time scales, with eddy processes becoming evident only on the longest, decadal time scales.

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Coincident observations, with QuikSCAT and ASCAT, of the effects of rain-induced sea surface stress during hurricanes Gustav and Ike

OCEANS 2009 ◽

10.23919/oceans.2009.5422242 ◽

2009 ◽

Author(s):

David E. Weissman ◽

Mark A. Bourassa

Keyword(s):

Surface Stress ◽

Sea Surface

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Deep Learning of Sea Surface Temperature Patterns to Identify Ocean Extremes

Remote Sensing ◽

10.3390/rs13040744 ◽

2021 ◽

Vol 13 (4) ◽

pp. 744

Author(s):

J. Xavier Prochaska ◽

Peter C. Cornillon ◽

David M. Reiman

Keyword(s):

Deep Learning ◽

Surface Temperature ◽

Sea Surface Temperature ◽

Sea Surface ◽

Space Distribution ◽

Western Boundary ◽

Learning Modules ◽

Ocean Science ◽

The Many ◽

Future Work

We performed an out-of-distribution (OOD) analysis of ∼12,000,000 semi-independent 128 × 128 pixel2 sea surface temperature (SST) regions, which we define as cutouts, from all nighttime granules in the MODIS R2019 Level-2 public dataset to discover the most complex or extreme phenomena at the ocean’s surface. Our algorithm (ULMO) is a probabilistic autoencoder (PAE), which combines two deep learning modules: (1) an autoencoder, trained on ∼150,000 random cutouts from 2010, to represent any input cutout with a 512-dimensional latent vector akin to a (non-linear) Empirical Orthogonal Function (EOF) analysis; and (2) a normalizing flow, which maps the autoencoder’s latent space distribution onto an isotropic Gaussian manifold. From the latter, we calculated a log-likelihood (LL) value for each cutout and defined outlier cutouts to be those in the lowest 0.1% of the distribution. These exhibit large gradients and patterns characteristic of a highly dynamic ocean surface, and many are located within larger complexes whose unique dynamics warrant future analysis. Without guidance, ULMO consistently locates the outliers where the major western boundary currents separate from the continental margin. Prompted by these results, we began the process of exploring the fundamental patterns learned by ULMO thereby identifying several compelling examples. Future work may find that algorithms such as ULMO hold significant potential/promise to learn and derive other, not-yet-identified behaviors in the ocean from the many archives of satellite-derived SST fields. We see no impediment to applying them to other large remote-sensing datasets for ocean science (e.g., SSH and ocean color).

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Estimating the Continental Response to Global Warming Using Pattern-Scaled Sea Surface Temperatures and Sea Ice

Journal of Climate ◽

10.1175/jcli-d-16-0032.1 ◽

2016 ◽

Vol 29 (24) ◽

pp. 9125-9139 ◽

Cited By ~ 1

Author(s):

Adeline Bichet ◽

Paul J. Kushner ◽

Lawrence Mudryk

Keyword(s):

Global Warming ◽

Sea Ice ◽

General Circulation ◽

Circulation Model ◽

Tropical Indian Ocean ◽

Sea Surface ◽

Climate Projections ◽

Western Boundary ◽

Sea Ice Concentration ◽

Continental Climate

Abstract Better constraining the continental climate response to anthropogenic forcing is essential to improve climate projections. In this study, pattern scaling is used to extract, from observations, the patterned response of sea surface temperature (SST) and sea ice concentration (SICE) to anthropogenically dominated long-term global warming. The SST response pattern includes a warming of the tropical Indian Ocean, the high northern latitudes, and the western boundary currents. The SICE pattern shows seasonal variations of the main locations of sea ice loss. These SST–SICE response patterns are used to drive an ensemble of an atmospheric general circulation model, the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, version 5 (CAM5), over the period 1980–2010 along with a standard AMIP ensemble using observed SST—SICE. The simulations enable attribution of a variety of observed trends of continental climate to global warming. On the one hand, the warming trends observed in all seasons across the entire Northern Hemisphere extratropics result from global warming, as does the snow loss observed over the northern midlatitudes and northwestern Eurasia. On the other hand, 1980–2010 precipitation trends observed in winter over North America and in summer over Africa result from the recent decreasing phase of the Pacific decadal oscillation and the recent increasing phase of the Atlantic multidecadal oscillation, respectively, which are not part of the global warming signal. The method holds promise for near-term decadal climate prediction but as currently framed cannot distinguish regional signals associated with oceanic internal variability from aerosol forcing and other sources of short-term forcing.

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