Equatorial Atlantic Circulation - PowerPoint Presentation

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Equatorial Atlantic Circulation and Tropical ClimateVariability

Peter Brandt

GEOMAR, Kiel, Germany

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Equatorial Atlantic Circulation and Tropical Climate Variability

With contributions from:

Richard Greatbatch

1

, Jürgen Fischer1, Sven-Helge Didwischuss1, Andreas Funk2, Alexis Tantet1,3, William Johns41GEOMAR Helmholtz-Zentrum für Ozeanforschung Kiel, Germany2WTD 71/FWG, Forschungsbereich für Wasserschall und Geophysik, Kiel, Germany3now at Institute for Marine and Atmospheric Research, Utrecht University, The Netherlands4RSMAS/MPO, University of Miami, USA

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OutlineIntroductionITCZ and tropical Atlantic variability (TAV)TACE observing systemData & Methods

EUC TransportEUC-TAV RelationEUC during warm/cold eventsShear variability

Equatorial Deep Jets

Equatorial basin modes

Interaction with EUCSummaryOutlook

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Sahel rainfall climatology

MA-Position

JJA-Position

Sahel

Guinea

Guinea rainfall climatology

Atlantic Marine ITCZ Complex

ITCZ position and rainfall intensity affect densely populated regions in West Africa

Introduction

Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook

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Rainfall and SST annual cycle

Introduction

Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook

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Mechanisms of Tropical Atlantic VariabilityMechanisms influencing Variability of Tropical Atlantic SST

Chang et al., 2006

Introduction

Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook

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Tropical Atlantic Variability (TAV) modesZonal mode (Atlantic Nino)Meridional mode (gradient mode)ENSO influence

NAO influence

MERIDIONAL MODE

ZONAL MODE

Strong seasonality of Tropical Atlantic Variability makes understanding and prediction of tropical Atlantic variability a challenge. Sutton et al. 2000

Introduction

Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook

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Meridional Mode (March-April)During spring the meridional SST gradient dominates TAV

Underlying mechanism is the Wind-Evaporation-SST (WES) Feedback Mechanism (Saravanan and Chang, 2004)

Kushnir

et al.

2006Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook

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Zonal Mode (June-August)

Zonal Mode is associated with rainfall variability, onset and strength of African Monsoon (Caniaux et al. 2011, Brandt et al. 2011)Underlying mechanism is the Bjerknes feedback that is strong during boreal spring/summer (

Keenlyside

and Latif 2007)

Kushnir et al. 2006Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook

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Equatorial Atlantic Cold TongueCold tongue develops during boreal summerInterannual variability of ATL3 SST index (3°S–3°N, 20°W–0°) much smaller than seasonal cycle

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Brandt et al. 2011

Introduction

Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook

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Onset of Atlantic Cold Tongue and West African Monsoon WAM onset follows the ACT onset by some weeks.Significant correlation of

ACT and WAM onsets

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WAM onset – northward migration of rainfall (10°W-10°E.) (

Fontaine and

Louvet

, 2006

)

ACT onset – surface area (with T<25°C) threshold

Caniaux

et al.

2011, Brandt

et al.

2011

Introduction

Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook

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Regression of SST and Wind onto

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WAM

Onset

Significantcorrelation

with cold tongue SST (zonal mode) and

SST in the tropical

NE Atlantic

(meridional mode)

ACT

Onset

Cold tongue SST;

Wind forcing in the western equatorial Atlantic

(zonal

mode

)

Brandt et al. 2011

Introduction

Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook

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SST Errors in Coupled Climate ModelsJungclaus et al. 2006

Dark gray

 model too warm

Large errors in the eastern tropical Atlantic

Introduction

Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook

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2006-2011 Tropical Atlantic Climate Experiment

A focused observational and modeling effort in the tropical Atlantic to advance the predictability of climate variability in the surrounding region and to provide a basis for assessment and improvement of coupled models. TACE was envisioned as a program of enhanced observations and modeling studies spanning a period of approximately 6 years.

The results of TACE were expected to contribute to the design of a sustained observing system for the tropical Atlantic.

TACE focuses on the eastern equatorial Atlantic as it is badly represented in coupled and uncoupled climate models and is a source of low prediction skill on seasonal to interannual time scales

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Introduction

Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook

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TACE observational network

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Observing system during the TACE period including different

process studies, like e.g. the 23°W equatorial moorings

Introduction

Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook

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Equatorial Mooring Array at 23°Wsingle mooring from June 20053

mooringsfrom June 2006 to May 2011

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Ship

Section Mean

Brandt, et

al.

2013,

submitted

Introduction

Data & Methods

EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook

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EUC from Shipboard Measurements20 shipboard velocity

sections are used to calculate

the

dominant variability pattern in terms of Hilbert EOFsSorted with respect to the seasonal cycle17

Introduction

Data & Methods

EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook

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Reconstruction of Zonal Velocity SectionsDominant variability

pattern from ship sectionsPattern are regressed

onto

moored time seriesMethod validation by using the ship sections itselfAlternative: optimal width method18

Introduction

Data & Methods

EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook

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Validation of EUC Transport Calculation using Ship Sections

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Introduction

Data & Methods

EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook

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Eastward EUC TransportGeneral agreement between different methods

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Introduction Data & Methods

EUC Transport

EUC-TAV Relation Equatorial Deep Jets Summary Outlook

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EUC TransportYears with strong and weak annual cycle

Ship sections alone are hardly conclusive

about

seasonal cycle21Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook

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Pacific EUC TransportMean EUC Transport (solid) and EUC transport for strong El

Niños (dashed)Strongly reduced EUC transport during El Niños. EUC disappeared

during 1982/83

El

Niño (Firing et al. 1983)22

Johnson

et al.

2002

What is the relation between Atlantic EUC transport

and tropical Atlantic variability?

Introduction Data & Methods EUC Transport

EUC-TAV Relation

Equatorial Deep Jets Summary Outlook

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Interannual Variability: SST ATL3 and Wind West AtlanticRichter et al. (2012): canonical events have strong/weak winds prior to cold/warm events

Canonical cold event: 2005Canonical warm event: 2008Noncanonical cold event: 2009 (warmest spring with weak winds, but coldest SST in August)

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Introduction Data & Methods EUC Transport

EUC-TAV Relation Equatorial Deep Jets Summary Outlook

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Interannual Variability: SST ATL3 and EUC TransportCanonical cold/warm events

are associated with strong/weak EUC

EUC

during

2009 was weak and shows no variation during the strong cooling from May to July24

Introduction Data & Methods EUC Transport

EUC-TAV Relation

Equatorial Deep Jets Summary Outlook

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Interannual Variability: SST ATL3 and April/May 2009 AnomaliesAccording to Richter

et al.(2012) noncanonical events are driven

by

advection from northern hemisphere during strong meridional mode eventsSST and wind anomalies during April/May 2009 (Foltz et al. 2012)25

Introduction Data & Methods EUC Transport

EUC-TAV Relation

Equatorial Deep Jets Summary Outlook

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Regression

MapsStrong June EUC associated

with

anomalous cold Cold Tongue and southerly wind anomalies in the northern hemisphere  early onset of the West African Monsoon26

Brandt, et

al.

2013,

submitted

Introduction Data & Methods EUC Transport

EUC-TAV Relation

Equatorial Deep Jets Summary Outlook

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June EUC – Wind/SST Relation27

Introduction Data & Methods EUC Transport

EUC-TAV Relation

Equatorial Deep Jets Summary Outlook

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June EUC – Wind/SST Relation28

Introduction Data & Methods EUC Transport

EUC-TAV Relation

Equatorial Deep Jets Summary Outlook

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June EUC – Wind/SST Relation

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Regression maps reflect a canonical behavior

according to Richter et al. (2012)Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook

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Monthly Regressions of Zonal Velocity onto EUC TransportDuring all months: strengthening of the eastward EUC associated with strengthening of westward surface flow (strongest shear enhancement in June)

February: weak near surface flow variability, stronger changes in the south30

Introduction Data & Methods EUC Transport

EUC-TAV Relation

Equatorial Deep Jets Summary Outlook

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Seasonal Cycle of Upper Ocean Diapycnal Heat Flux

Strongest shear (1/s2) and diapycnal heat

flux

(W/m

2) during June31

Hummels et al. 2013

Introduction Data & Methods EUC Transport

EUC-TAV Relation

Equatorial Deep Jets Summary Outlook

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Deep Velocity Observations along 23°WEquatorial Deep Jets are a dominant flow feature below the Equatorial Undercurrent and oscillate with a period of about 4.5 years (Johnson and Zhang 2003, Brandt et al. 2011)

Introduction Data & Methods EUC Transport EUC-TAV Relation

Equatorial Deep Jets

Summary Outlook

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Equatorial Deep Jets and

Basin Mode OscillationsDownward phase

and

upward energy propagationEDJ are excited at depth and propagate toward the surface update from Brandt et al. 2011

Introduction Data & Methods EUC Transport EUC-TAV Relation

Equatorial Deep Jets

Summary Outlook

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Equatorial

Deep

Jets

Excitation

of

equatorial

basin

modes

(

Cane

and

Moore, 1981)

Vertical

Mode

Decomposition

Equatorial

Deep

Jets

Harmonic

analysis

Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets

Summary Outlook

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Equatorial Deep JetsGreatbatch et al. (2012): EDJ can be described by high-baroclinic, equatorial basin modes.How are the Jets forced?

Inertial Instability (Hua et al. 1997, d’Orgeville et al. 2004, Eden and Dengler

2008)

Destabilization of

Rossby-gravity waves (Ascani et al. 2006, d’Orgeville et al. 2007, Hua et al. 2008, Ménesguen et al. 2009)Upward energy propagation toward the surface hindered by the EUC (e.g. McPhaden et al. 1986) or tunneling through the shear zone (Brown & Sutherland 2007)?

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Deep Ocean Dynamics | Introduction Equatorial Deep Jets

Introduction Data & Methods EUC Transport EUC-TAV Relation

Equatorial Deep Jets

Summary Outlook

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Surface Geostrophic Velocity

4.5-year cycle of the geostrophic equatorial zonal surface velocity (from sea level anomalies 15°W-35°W)Corresponding signal of the ATL3 SST index (3°S–3°N, 20°W–0°)

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Eastward surface flow anomaly corresponds to warm eastern equatorial Atlantic.

Brandt et al. 2011

Introduction Data & Methods EUC Transport EUC-TAV Relation

Equatorial Deep Jets

Summary Outlook

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EDJ interaction with the EUC?Consistent downward phase propagation below the EUC4.5-year cycle also North, South and above the EUC core Phases suggest meridional displacement of the EUC core with the EDJ cycle

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Introduction Data & Methods EUC Transport EUC-TAV Relation

Equatorial Deep Jets

Summary Outlook

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EDJ interaction with the EUC?Consistent downward phase propagation below the EUC4.5-year cycle also North, South and above the EUC core Phases suggest meridional displacement of the EUC core with the EDJ cycle

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Introduction Data & Methods EUC Transport EUC-TAV Relation

Equatorial Deep Jets

Summary Outlook

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SummaryInterannual EUC transport variability largely in agreement with zonal mode variabilityThere are noncanonical events likely associated with meridional mode events during boreal spring

4.5-yr EDJ oscillations dominate depth range below the EUC: high-baroclinic, equatorial basin modesPossible interaction of basin mode and EUC (time series are hardly long enough) Improved numerical simulations are required for the understanding of physical processes responsible for EDJ affecting SST and TAV

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Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets

Summary

Outlook

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Summer (JJA) Sea Surface temperature bias pattern for CMIP5White stipples indicate where models are consistently wrongPersistent errors in climate models

with little sign of reduction

Toniazzo

and Woolnough, 2013 Despite improved process understanding, model errors remained large resulting in poor TA climate prediction. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook

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Climate Modelling/PredictionState-of-the-art climate models still show large errors in the SE AtlanticPossible sources: atmospheric

convection, clouds, aerosols, but similarly oceanic processes (Xu et al. 2013) like:

Advection from equatorial region, too weak

stratification

Not resolved coastal upwelling processesSeveral initiatives to improve ocean data base in the SE Atlantic and to reduce model biasEU PREFACE (PI Noel Keenlyside) German SACUS (PI Peter Brandt)NSF Proposal (PI Ping Chang)

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Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary

Outlook

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Closing knowledge gaps – enhanced observationsGulf of Guinea and Eastern Boundary Upwelling regions

Glider campaigns and cruises in 2014, 2015, and 2016, various seasonsEnhanced ARGO floats in Eastern Atlantic

8E6S, PIRATA mooring

Current meter at 0E,eq

Mooring 20SIntroduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook

Current

meter mooring array was deployed at 11°S

off Angola

during Meteor cruise in

J

uly

2013

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AcknowledgementsThis study was supported by the German Federal Ministry of Education and Research as part of the co-operative projects “NORDATLANTIK” and “RACE” and by the German Science Foundation (DFG) as part of the Sonderforschungsbereich 754 “Climate-Biogeochemistry Interactions in the Tropical Ocean”. Moored velocity observations were acquired in cooperation with the PIRATA project.

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