observing surface circulation of the western mediterranean

Observing surface circulation of the

Western Mediterranean with

satellite imagery

GeoHydrodynamics and Environment Research

Unit (GHER)

Svetlana Karimova

University of Liege

Surface circulation from space: general approaches

Single satellite image approach:

Visual analysis

Front / eddy detection

Satellite altimetry approach:

Fields of sea level anomaly (SLA)

Vector fields of surface currents

Finite Size Lyapunov Exponents

Multitemporal approach:

Feature detection

Maximum cross-correlation (MCC)

SAR approach:

Along-track interferrometry (ATI)

Doppler centroid

S. Karimova - Surface circulation of WMed - ISRSE-37

2

08.04.2015

Chl-a, VIIRS

Liguro-Provençal Basin (LPB)

Outline

Visual analysis of satellite imagery

SST and Chl-a front detection

Eddy detection in:

SST and SAR imagery

Sea level anomaly (SLA) fields

Vector fields of surface currents


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ENVISAT ASAR

12.10.2011

In this presentation, we will

discuss the folowing topics:

As a region of interest we are using:

Entire Western Mediterranean (WMed)

Western Western Mediterranean

(WWMed)

Liguro-Provençal Basin (LPB)

I. Seasonal variability of surface water stirring

Visual analysis of satellite imagery (especially of the fields of Chl-a) reveals different types of surface water stirring during the cold (December to March) and warm (April to

November) periods of year, presumably caused by different turbulence models (e.g. 2D and 3D) prevailing

during those periods (Karimova, 2017b).


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Cold season: December to March

Warm season: April to November

Surface water stirring during cold and warm seasons


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(Karimova, 2017c)

Cold season: December to March Warm season: April to November

Bright shading denotes higher values of Chl-a.

Mixed layer depth variability


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Switch between the

winter and summer

types of stirring,

which happens in

late March – early

July, corresponds

well to the beginning

of restratification of

the upper water

layer in WMed and

appearance of quite

shallow mixed layer.

Annual variation of MLD

at fixed points in WMed in

2013 (CMEMS reanalysis)

(Karimova, 2017c)

Chl-a and SST structure function


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Seasonal variability of water stirring, which is obvious upon a visual analysis of

imagery, is not so easy to capture statistically. Figures above: test sites for

calculating the structure function of Chl-a and SST fields during the cold and

warm periods (left) and corresponding structure functions (Karimova, 2017b).

II. Front detection

Front detection (e.g. via applying a Sobel operator) in the fields of SST and/or Chl-a with a subsequent averaging is

an easy way to extract locations of some persistent surface circulation patterns (Karimova, 2014).


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Seasonally average of the SST gradient in 2009 (MODIS Aqua)


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• Darker shades correspond to higher SST gradients.

JFM AMJ

JAS OND

(Karimova, 2017c)

Seasonally average of the Chl-a gradient in 2009 (MODIS Aqua)


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• Darker shades correspond to higher SST gradients.

JFM AMJ

JAS OND

(Karimova, 2017c)

III. Eddy detection

• In the present study, eddies in satellite imagery (thermal infrared and SAR) were detected manually. For that, I was searching for circular or elliptical patches with

a tendency to spirality, which is needed for defining the sign of eddy rotation (anticyclonic or cyclonic).

• No, it is not as subjective as many people think. After the first thousand of counted eddy manifestations, everyone would see them in the way I do. The

objective limitations like cloud cover, unfavourable wind conditions and lack of tracers are much harder to overcome.

• Analysis of the fields of SST was performed with a daily temporal resolution, so that (practically) all eddies seen in an image were detected, meaning that big

anticyclonic eddies could be counted several times.


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L3S SST image, 2008, day 229 12

Level 3 Super-collated (L3S) SST product

(SST-CNR-ROMA-IT via CMEMS)


The product is hardly

suitable for an

automatic procession

(e.g. front detection)

due to multiple

artefacts, but eddies

still can be seen.

Eddies detected in SST (WMed)


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Time coverage:o 2008

o 2014

1624 samples 522 samples

Data source:o SST L3S

(Karimova, 2017c)

Spatial scale of SST eddies (WMed)

Monthly averages of eddy diameters support the

observation about different types of surface

stirring during winter and summer (markers)

even though in winter we observe much fewer

eddies due to the cloud conditions (lines).

Mean eddy diameter:

• Anticyclonic eddies – 76.3 km

• Cyclonic eddies – 54.6 km


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(Karimova, 2017c)


15Eddies detected in SST (WWMed)

Time coverage:o 2011-2013

1489 samples 782 samples

Data source:o SST L3S

(Karimova, 2017c)

Spatial scale of SST eddies (WWMed)

Mean eddy diameter:

• Anticyclonic eddies – 83.5 km

• Cyclonic eddies – 53.6 km


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Monthly average of eddy diameters

(above). Similar to the WMed region,

during the warm period eddies were

bigger than during the cold period. (Karimova, 2017c)

Locations of tracked eddies (WWMed)


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(Karimova, 2017c)

Since the same

eddy could be

registered several

times upon the

analysis performed,

we could track the

movements of the

centres of such

eddies. Especially

well once can

notice the locations

where AC eddies

stay for especially

long time.

Straight lines are

connecting the

subsequent positions

of an eddy centre for

AC and C eddies.

Liguro-Provençal Basin (LPB) 18

SST L3C AVHRR

24.08.2013


The smallest

region of

interest in

the present

study is the

Liguro-

Provençal

Basin.

This time, a

Level 3

Collated

(L3C) SST

product

was used

for an eddy

detection.

Eddies found in SST (LPB) 19


Time coverage:

o 2014-2016

Data source:

o SST L3C

(Karimova, 2017c)

Spatial scale of SST eddies (LPB) 20

Number of samples:

• Anticyclonic eddies - 580

• Cyclonic eddies - 564


Monthly average of the eddy diameters.

(Karimova, 2017c)

Locations of tracked eddies (LPB)

◊ AC

o C


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09.08.2015

SST MODIS

(Karimova, 2017c)

The area attributed to the Western Corsican Current seems particularly eddy active.

IV. Why not altimetry?

Altimetry-derived products such as the fields of sea level anomaly (SLA) are successfully used for mesoscale eddy detection in the open ocean (via contours of SLA or/and Okubo-Weiss parameter, geometry

of surface current vectors, etc.).

But would that be a good way to detect eddies in such a small marine basin as WMed? Unfortunately, with such a technique, we

would detect only the biggest eddies in the study area.


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Ratios between AC and C eddiesat different spatial scales


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Due to the excess of big cyclonic eddies typical for the altimetry-based algorithms, the

resulting statistics provided by such algorithms report on similar numbers of AC and C

eddies, which is totally unrealistic according to what is observed in satellite imagery

(Karimova, 2017d).

V. Submesoscale eddies

Submesoscale eddies (d<15 km) need satellite imagery with a particularly high spatial resolution to be seen. Synthetic aperture

radar (SAR) imagery are perfectly suited for manifesting submesoscale eddies (Karimova, Gade, 2013; 2016).

In the present study, we used Envisat ASAR images to detect eddies visible due to surfactant films (‘black’ eddies, example

above) and wave/current interactions (‘white’ eddies).


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Eddies in SAR

“Black” eddies, milder winds

“White” eddies,

stronger winds(Karimova, Gade, 2013)

Manifestation of

phenomena in SAR

significantly

depends on the

near-surface wind

speed.

Submesoscale eddies (d < 15 km)


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Data source: Envisat ASAR WS

(75 m)

Time coverage:o 2009-

2011

(Karimova, 2017c)

(almost all eddies are cyclonic)

MLD corresponding to submesoscale eddies


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Mixed layer depths (MLD) corresponding to

‘black’ and ‘white’ submesoscale eddies

seen in SAR imagery (CMEMS reanalysis).

Since most eddies are observed in

SAR during the warm period of

year, when the near-surface

windspeed conditions are better

for seeing surfactant films

(Karimova, Gade, 2016a, 2016b),

it is no surprise that about 62% of

“black“ eddies were observed at

MLD not exceeding 30 m, and

about 46% of them at MLD not

exceeding 20 m.

Thus, one should aware that

mixed layer instabilities (MLI) are

not necessary the only mechanism

for submesoscale eddies to be

generated.

Conclusions

• Satellite imagery provides a wealth of data on surface circulation in the Western Mediterranean (WMed).

• WMed and its subbasins demonstrated high eddy activity at both meso- and submesoscales.

• Among mesoscales, there is clear seasonal variability of the type of surface water stirring with the minimum of big-eddy activity observed during the cold period of year (December to March) and the maximum, during the warm period (April to November).

• Seasonal changes in submesoscale eddy activity seem different in different regions (first of all, in the northern and southern parts of WMed). In any case, quite a lot of submesoscale vorticies are observed during summer with very shallow mixed layers.

• Algorithms for an automatic eddy detection in altimetry derivedscalar and vector fields tend to overestimate the number of cyclonic eddies.


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References-1

• Karimova, S., Gade M., 2013. Submesoscale eddies seen by spaceborne radar. Proc.

EMEC 10 – MEDCOAST 2013. 30 Oct - 03 Nov 2013, Marmaris, Turkey. Dalyan, Mugla,

Turkey. Vol. I. P. 665-676.

• Karimova, S., 2014. Hydrological fronts seen in visible and infrared MODIS imagery of

the Black Sea. International Journal of Remote Sensing, 35(16), 6113-6134.

• Karimova, S., Gade M., 2016a. Eddies in the Western Mediterranean seen by

spaceborne radar. Proc. IGARSS 2016. 10-15 July 2016, Beijing, China.

• Karimova, S., Gade M., 2016b. Improved statistics of submesoscale eddies in the

Baltic Sea retrieved from SAR imagery. International Journal of Remote Sensing,

37(10), 2394-2414.

• Nencioli, F., Dong, C., Dickey, T., Washburn, L., and McWilliams, J.C., 2010. A

vector geometry-based eddy detection algorithm and its application to a high-

resolution numerical model product and high-frequency radar surface velocities in the

Southern California Bight, J. Atmos. Ocean. Tech., 27, 564–579.


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References-2

• Karimova, S., 2016. Observation of the surface circulation of the Mediterranean Sea from space.

Proc. ESA Living Planet Symposium 2016. 9-13 May 2016, Prague, Czech Republic. SP-740.

• Karimova, S., 2017a. Performance of gridded and along-track altimetry products in eddy

manifestation in the Western Mediterranean. Proc. IGARSS 2017. 23-28 July 2017, Fort Worth,

Texas, USA.

• Karimova, S., 2017b. Multisensor and multitemporal satellite observations of surface circulation

in the Western Mediterranean. Proc. 4th Int. Conf. “Applied Aspects of Geology, Geophysics, and

Geoecology with Using Modern Informational Technologies”, 15-19 May 2017, Maykop, Russia.

• Karimova, S., 2017c. Observing surface circulation of the Western Mediterranean Basin

with satellite imagery. The International Archives of the Photogrammetry, Remote Sensing

and Spatial Information Sciences. Vol. XLII-3/W2, 2017, 37th Int. Symposium on Remote

Sensing of Environment, 8–12 May 2017, Tshwane, South Africa. P. 97-104. DOI:

10.5194/isprs-archives-XLII-3-W2-97-2017.

• Karimova, S., 2017d. Observations of asymmetric turbulent stirring in inner and marginal seas

using satellite imagery. International Journal of Remote Sensing, 38:6, 1642-1664, DOI:

10.1080/01431161.2017.1285078.


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Acknowledgements

• This research is supported by the University of Liege and the EU in the context of the FP7-PEOPLE-COFUND-BeIPDproject.

• The study was performed with the use of information provided by the AVISO+, CLS, CMEMS, CNR, ESA,ERDDAP, GlobCurrent, NASA, and SOCIB.


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observing surface circulation of the western mediterranean

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