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Equatorial Atlantic Circulation and Tropical Climate Variability. Peter Brandt. GEOMAR, Kiel, Germany. Equatorial Atlantic Circulation and Tropical Climate Variability. With contributions from :

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Equatorial Atlantic Circulation and Tropical Climate Variability


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    1. EquatorialAtlanticCirculationand Tropical ClimateVariability Peter Brandt GEOMAR, Kiel, Germany

    2. EquatorialAtlanticCirculationand Tropical ClimateVariability Withcontributionsfrom: Richard Greatbatch1, Jürgen Fischer1, Sven-Helge Didwischuss1, Andreas Funk2, Alexis Tantet1,3, William Johns4 1GEOMAR Helmholtz-Zentrum für Ozeanforschung Kiel, Germany 2WTD 71/FWG, Forschungsbereich für Wasserschall und Geophysik, Kiel, Germany 3now at Institute for Marine andAtmospheric Research, Utrecht University, The Netherlands 4RSMAS/MPO, University of Miami, USA

    3. Outline • Introduction • ITCZ and tropical Atlantic variability (TAV) • TACE observing system • Data & Methods • EUC Transport • EUC-TAV Relation • EUC during warm/cold events • Shear variability • Equatorial Deep Jets • Equatorial basin modes • Interaction with EUC • Summary • Outlook

    4. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Atlantic Marine ITCZ Complex Sahel JJA-Position Guinea MA-Position Sahel rainfall climatology Guinea rainfall climatology ITCZ position and rainfall intensity affect densely populated regions in West Africa

    5. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Rainfall and SST annual cycle

    6. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Mechanisms of Tropical Atlantic Variability Chang et al., 2006 Mechanisms influencing Variability of Tropical Atlantic SST

    7. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Tropical Atlantic Variability (TAV) modes Strong seasonality of Tropical Atlantic Variability makes understanding and prediction of tropical Atlantic variability a challenge. MERIDIONAL MODE ZONAL MODE Sutton et al. 2000 Zonal mode (Atlantic Nino) Meridional mode (gradient mode) ENSO influence NAO influence

    8. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Meridional Mode (March-April) Kushnir et al. 2006 During spring the meridional SST gradient dominates TAV Underlying mechanism is the Wind-Evaporation-SST (WES) Feedback Mechanism (Saravanan and Chang, 2004)

    9. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Zonal Mode (June-August) Kushnir et al. 2006 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)

    10. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Equatorial Atlantic Cold Tongue Brandt et al. 2011 Cold tongue develops during boreal summer Interannual variability of ATL3 SST index (3°S–3°N, 20°W–0°) much smaller than seasonal cycle

    11. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Onset of Atlantic Cold Tongue and West African Monsoon WAM onset – northward migration of rainfall (10°W-10°E.) (Fontaine and Louvet, 2006) ACT onset – surface area (with T<25°C) threshold WAM onset follows the ACT onset by some weeks. Significant correlation of ACT and WAM onsets Caniaux et al. 2011, Brandt et al. 2011

    12. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Regression of SST and Wind onto ACT Onset Cold tongue SST; Wind forcing in the western equatorial Atlantic (zonal mode) WAM Onset Significantcorrelation with cold tongue SST (zonal mode) and SST in the tropical NE Atlantic (meridional mode) Brandt et al. 2011

    13. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook SST Errors in Coupled Climate Models Dark gray  model too warm Large errors in the eastern tropical Atlantic Jungclaus et al. 2006

    14. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook 2006-2011 Tropical AtlanticClimateExperiment 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.

    15. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook TACE observational network Observing system during the TACE period including different process studies, like e.g. the 23°W equatorial moorings

    16. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Equatorial Mooring Array at 23°W ShipSectionMean Brandt, et al. 2013, submitted singlemooringfrom June 2005 3 mooringsfrom June 2006 to May 2011

    17. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook EUC fromShipboardMeasurements 20 shipboardvelocitysectionsareusedtocalculatethe dominant variabilitypattern in termsof Hilbert EOFs Sortedwithrespecttotheseasonalcycle

    18. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Reconstructionof Zonal VelocitySections Dominant variabilitypatternfromshipsections Pattern areregressedontomoored time series Methodvalidationbyusingtheshipsectionsitself Alternative: optimal widthmethod

    19. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Validation of EUC Transport CalculationusingShipSections

    20. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Eastward EUC Transport General agreementbetween different methods

    21. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook EUC Transport Yearswith strong andweakannualcycle Shipsectionsalonearehardlyconclusiveaboutseasonalcycle

    22. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Pacific EUC Transport Johnson et al. 2002 What is the relation between Atlantic EUC transport and tropical Atlantic variability? Mean EUC Transport (solid) and EUC transportfor strong ElNiños (dashed) Strongly reduced EUC transport during El Niños. EUC disappeared during 1982/83 El Niño (Firing et al. 1983)

    23. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Interannual Variability: SST ATL3 and Wind West Atlantic Richter et al. (2012): canonical events have strong/weak winds prior to cold/warm events Canonical cold event: 2005 Canonical warm event: 2008 Noncanonical cold event: 2009 (warmest spring with weak winds, but coldest SST in August)

    24. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Interannual Variability: SST ATL3 andEUC Transport Canonicalcold/warm eventsareassociatedwith strong/weak EUC EUC during 2009 was weakandshowsnovariationduringthe strong coolingfrom May toJuly

    25. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Interannual Variability: SST ATL3 andApril/May 2009 Anomalies Accordingto Richter et al.(2012) noncanonicaleventsaredrivenbyadvectionfrom northern hemisphereduring strong meridional modeevents SST and wind anomaliesduring April/May 2009 (Foltz et al. 2012)

    26. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Regression Maps Brandt, et al. 2013, submitted Strong June EUC associatedwithanomalouscoldColdTongueandsoutherly wind anomalies in the northern hemisphere earlyonsetofthe West African Monsoon

    27. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook June EUC – Wind/SST Relation

    28. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook June EUC – Wind/SST Relation

    29. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook June EUC – Wind/SST Relation Regression maps reflect a canonical behavior according to Richter et al. (2012)

    30. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook MonthlyRegressionsof Zonal Velocityonto EUC Transport During 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 south

    31. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Seasonal Cycle ofUpperOcean Diapycnal HeatFlux Hummels et al. 2013 Strongestshear (1/s2) and diapycnal heatflux (W/m2) during June

    32. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Deep Velocity Observations along 23°W Equatorial 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)

    33. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Equatorial Deep Jets and Basin Mode Oscillations update from Brandt et al. 2011 Downwardphaseandupwardenergypropagation EDJ areexcitedatdepthandpropagatetowardthesurface

    34. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Excitationofequatorialbasinmodes (Caneand Moore, 1981) EquatorialDeepJets Vertical Mode Decomposition Harmonicanalysis EquatorialDeepJets

    35. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Deep Ocean Dynamics | Introduction Equatorial Deep Jets Equatorial Deep Jets • Greatbatch 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’Orgevilleet 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)?

    36. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Surface Geostrophic Velocity • Eastward surface flow anomaly corresponds to warm eastern equatorial Atlantic. Brandt et al. 2011 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°)

    37. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook EDJ interactionwiththe EUC? Consistent downward phase propagation below the EUC 4.5-year cycle also North, South and above the EUC core Phases suggest meridional displacement of the EUC core with the EDJ cycle

    38. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook EDJ interactionwiththe EUC? Consistent downward phase propagation below the EUC 4.5-year cycle also North, South and above the EUC core Phases suggest meridional displacement of the EUC core with the EDJ cycle

    39. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Summary Interannual EUC transport variability largely in agreement with zonal mode variability There 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 modes Possible 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

    40. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Persistent errors in climate models with little sign of reduction Summer (JJA) Sea Surface temperature bias pattern for CMIP5 White stipples indicate where models are consistently wrong ToniazzoandWoolnough, 2013 Despite improved process understanding, model errors remained large resulting in poor TA climate prediction.

    41. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Climate Modelling/Prediction • State-of-the-art climate models still show large errors in the SE Atlantic • Possible 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 processes • Several initiatives to improve ocean data base in the SE Atlantic and to reduce model bias • EU PREFACE (PI Noel Keenlyside) • German SACUS (PI Peter Brandt) • NSF Proposal (PI Ping Chang)

    42. Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Closing knowledge gaps – enhanced observationsGulf of Guinea and Eastern Boundary Upwelling regions Glider campaigns and cruises in 2014, 2015, and 2016, various seasons Enhanced ARGO floats in Eastern Atlantic 8E6S, PIRATA mooring Current meter at 0E,eq Mooring 20S Currentmeter mooring array was deployed at 11°S off Angola during Meteor cruise inJuly 2013

    43. Acknowledgements This 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.