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1 Interannual Variability Interannual Variability of Satellite-Derived of Satellite-Derived Sea Surface Temperature Sea Surface Temperature in the Western North Atlantic in the Western North Atlantic Shelf and Slope, 1985-1999 Shelf and Slope, 1985-1999 M.S. Thesis Presentation M.S. Thesis Presentation Anne-Marie E.G. Brunner- Suzuki June 15 th , 2007

1 Interannual Variability of Satellite-Derived Sea Surface Temperature in the Western North Atlantic Shelf and Slope, 1985-1999 M.S. Thesis Presentation

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Page 1: 1 Interannual Variability of Satellite-Derived Sea Surface Temperature in the Western North Atlantic Shelf and Slope, 1985-1999 M.S. Thesis Presentation

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Interannual Variability Interannual Variability of Satellite-Derived of Satellite-Derived

Sea Surface Temperature Sea Surface Temperature in the Western North Atlantic in the Western North Atlantic Shelf and Slope, 1985-1999Shelf and Slope, 1985-1999

M.S. Thesis Presentation M.S. Thesis Presentation

Anne-Marie E.G. Brunner-SuzukiJune 15th, 2007

Page 2: 1 Interannual Variability of Satellite-Derived Sea Surface Temperature in the Western North Atlantic Shelf and Slope, 1985-1999 M.S. Thesis Presentation

Introduction and Background

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Western North Atlantic Shelf and Slope

Adapted from Chapman and Beardsley (1989). ; a) Smith et al.(1987); b) Collin and Dunbar(1964); c) Petrie and Anderson (1983); d) Drinkwater et al.(1979); e) Smith (1963); f) Rump et al. (1985); g) Beardsley

et al. (1985)

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The Slope Sea

Transition zone between coastal waters and open ocean waters originating from the sub-polar and sub-tropical gyre

meet and interact water mass variability associated with NAO variability

Adapted fromCsanady and Hamilton (1988)

G76: Gatien, 1976PD93: Petrie and Drinkwater 1993ML57: McLellan 1957

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North Atlantic Oscillation (NAO)

From: http://www.gomoos.org/nao/page5.html

Positive NAO

Negative NAO

High NAO:

•Decreased Labrador Current transport•LSW to Cabot Strait•Slope Sea dominated by WSW•Northern Gulf Stream North WallMyers et al., 1989; Petrie and Drinkwater, 1993; Han, 2002

Low NAO:

•Increased Labrador Current transport•LSW as far south as MAB•Southern Gulf Stream North Wall (Gatien, 1976; Flagg et al., 1998; Rossby, 1999; Greene and Pershing, 2001)

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Preliminary SST results

Positive NAONegative NAO

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NAOhigh low

increasedLabrador Current

transport decreased

Labrador Current transport

Warm, salty, nitrate-rich

WSW in Slope Sea

Cold, fresh, nitrate-depleted

LSW in Slope Sea

Gatien, 1976; Petrie and Drinkwater, 1993

Townsend, et al. 2004

Gulf Streammore northern

Gulf Streammore southern

Joyce,Gangopadhyay

Increased Chla Decreased ChlaSchollaert, et al.

2004

Increased Calanus f. Decreased Calanus f.Greene

etal., 2003

Motivation or why it is interesting

Page 8: 1 Interannual Variability of Satellite-Derived Sea Surface Temperature in the Western North Atlantic Shelf and Slope, 1985-1999 M.S. Thesis Presentation

Hypothesis

Interannual variability

of SSTin the westernNorth Atlantic

Southwestward extentof

Labrador Current

Interannual Variability of

Local Forcings(Wind, Qnet)

NAO

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Data and Methods

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Data• 15 years of satellite-derived Sea Surface Temperature (SST) from the Advanced Very High Resolution Radiometer

• ADCP temperature data at M/V Oleander provided by Dr. C. Flagg• Shipboard SST data at the Halifax section from the BIO database

•Gulf Stream North Wall and shelf slope frontal positions provided by Dr. K.Drinkwater and Dr. R.Pettipas.

• Local forcing is estimated using National Center for Environmental Prediction (NCEP) gridded reanalysis products:

• net heatflux Qnet(Qnet = sensible + latent + shortwave + longwave)

• windmagnitude (W)(W= sqrt (u^2+v^2))

Page 11: 1 Interannual Variability of Satellite-Derived Sea Surface Temperature in the Western North Atlantic Shelf and Slope, 1985-1999 M.S. Thesis Presentation

Methods I Compute quality controlled, monthly SST, W

and Qnet anomalies:monthly anomalies were computed, by subtracting individual long-term means from the 180 monthly means.

Apply data to a bathymetry-following grid:spatially smoothing of the data by applying a coarse (628 bins) grid following shelf and slope

Validate data with in situ data

Conduct an Empirical Orthogonal Function (EOF) analyses for SST, Qnet and Wind to determine IAV of SST

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Methods IIPerform a regression analysis between the resulting EOF modes and Hurrell’s North Atlantic Oscillation (NAO) seasonal index

Perform a cross-correlation analysis

Create a composited SSTA data setCompare sections along the shelf and slope to identify cold events

Compute propagation speedsConduct a Complex EOF analysis to study propagating signals for SSTA

The goal was to identify and quantify cold intrusions into the Slope Sea.

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Results

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Bathymetry following Grid

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AVHRR SST and in situ SSTHalfiax 27 M/V Oleander

RMS: 1.02 deg.C (83%) RMS: 1.34deg.C (81%)

In situ data are instantaneous, single measurements. AVHRR are monthly averages. Satellite measure skin temperature, ADCP at 6m depth, shipboard data are below surface; also data availability influences the results.

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Results were evaluated using North's Rule of Thumb,

a Monte Carlo test and spatial dependency test.

Spatial EOF SST anomaly results

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Principal Component

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Regression Analysis

Explained variance at zero lag between NAO and SST EOF modes 1-4 is low.

R-Values

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Cross-correlation

The maximum influence of Qnet anomalies or W-anomalies onto SST anomalies is only 5%.

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Onshelf-Offshelf Comparison

7 sections along the shelf results from the EOF-noise reduced composited data

Different r-values Different dominant

frequencies Red are onshelf

regions, Black are offshelf

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Adapted from Drinkwater et al. (1999).

11 22

33 44

55 66

The classic 1997/1998 “Cold Event”

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Cold Events

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Bathymetry following Grid

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Cold Events 6cm/s – 20cm/s (here) 3cm/s (Houghton and Visbeck, 2002) 4cm/s (Mountain 2003; Bisagni et al, 2006) - shelf 7cm/s (Chapman and Beardsley, 1989) - shelfbreak 3;13cm/s ( Belkin, 2004) – observed only north of

the Grand Banks; (1970s;1990s) mean current speed 9cm/s (Lazier and Wright, 1993; Pickart et al., 1999) -slope 12cm/s (Fratantoni and Pickart, in press) - slope 15cm/s (Flagg et al., 2006) - slopesynoptic current speeds 35cm/s (Pickart et al., 1999; Flagg et al., 2006)

Propagation Speed

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Complex EOF 1

arrow length: amplitudearrow direction: phase

amplitude

phase

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Complex EOF 2

arrow length: amplitudearrow direction: phase

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Summary

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Summary Low correlation and significance levels suggest

other mechanisms besides climate-related variability of surface forcing from winds and net heat flux related to the NAO are important in the shelf-slope region of the western North Atlantic ocean.

Other mechanisms include horizontal advection and may include vertical mixing and may play a large role in controlling interannual variability of SST.

Propagation speeds of different “cold events” range from 6cm/s to 20cm/s, thus being on the order of mean current speeds in the slope region.

The 2nd CEOF mode suggests faster propagation

speeds in the Slope Sea, than onshelf.

Most observed “cold events” are first seen offshore, than onshore, suggesting that the slope is driving the shelf. However, not so during 1992.

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CEOF 1 exhibits northeastward propagation of SSTA, possibly indicating the importance of the separation of the Gulf Stream from the shelf break.

CEOF/EOF 2 is related to the cold intrusions from the north and it is negative during offshore positions of the shelf slope front.

Results indicate, that observed SST IAV results from propagating temperature anomalies and is not caused by local forcings.

The intrusion of LSW into the Slope Sea is important for the ecosystem of the North American continental shelf and Slope Sea as it is thought to influence biological production through a nitrate-controlled bottom-up control mechanism; i.e. inter- and intra-annual physical forcing controls the dynamics of phytoplankton and zooplankton and higher trophic levels.

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Acknowledgments Dr.P.Cornillon (AVHRR data), Dr.C.Flagg (ADCP data),

Dr.R.Pettipas (digitized SSF, GSNW position) for providing valuable data.

Source of funding: NSF Grants OCE-0217122 and OCE-0227679 under the joint NSF/NOAA US-GLOBEC Northwest Atlantic Georges Bank Program.

My advisor Dr. J.J.Bisagni and my Thesis Committee Dr.A.Bower, Dr.A.Gangopadhyay, Dr.M.Zhou for their guidance and kind support in the course of this research.

My fellow graduate students and many faculty at SMAST and UMassD

My friends at SMAST and other places in this world My parents G.+Dr.C.Brunner and siblings J., C., F.Brunner

and many other family members My husband N.Suzuki

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Thank you all for your attention!

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