Equatorial Atlantic Circulation and Tropical Climate Variability Peter
Equatorial Atlantic Circulation and Tropical Climate Variability Peter Brandt GEOMAR, Kiel, Germany
Equatorial Atlantic Circulation and Tropical Climate Variability With contributions from: Richard Greatbatch 1, Ju rgen Fischer 1, Sven-Helge Didwischuss 1, Andreas Funk 2, Alexis Tantet 1, 3, William Johns 4 1 GEOMAR Helmholtz-Zentrum fu r Ozeanforschung Kiel, Germany 2 WTD 71/FWG, Forschungsbereich fu r Wasserschall und Geophysik, Kiel, Germany 3 now at Institute for Marine and Atmospheric Research, Utrecht University, The Netherlands 4 RSMAS/MPO, University of Miami, USA 2
Outline 4 Introduction 4 Equatorial Deep Jets • ITCZ and tropical Atlantic • Equatorial basin modes variability (TAV) • TACE observing system • Interaction with EUC 4 Data & Methods 4 EUC Transport 4 EUC-TAV Relation • EUC during warm/cold events • Shear variability 4 Summary 4 Outlook
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Atlantic Marine ITCZ Complex 4 ITCZ position and rainfall intensity affect densely populated regions in West Africa Sahel JJA-Position Guinea MA-Position Sahel rainfall climatology Guinea rainfall climatology
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Rainfall and SST annual cycle Outlook
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Mechanisms of Tropical Atlantic Variability 4 Mechanisms influencing Variability of Tropical Atlantic SST Chang et al. , 2006 Outlook
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Tropical Atlantic Variability (TAV) modes 4 Zonal mode (Atlantic Nino) 4 Meridional mode (gradient mode) 4 ENSO influence 4 NAO influence Strong seasonality of Tropical Atlantic Variability makes understanding and prediction of tropical Atlantic variability a challenge. MERIDIONAL MODE ZONAL MODE Sutton et al. 2000
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Meridional Mode (March-April) 4 During spring the meridional SST gradient dominates TAV 4 Underlying mechanism is the Wind-Evaporation. SST (WES) Feedback Mechanism (Saravanan and Chang, 2004) Kushnir et al. 2006 Outlook
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Zonal Mode (June-August) 4 Zonal Mode is associated with rainfall variability, onset and strength of African Monsoon (Caniaux et al. 2011, Brandt et al. 2011) 4 Underlying mechanism is the Bjerknes feedback that is strong during boreal spring/summer (Keenlyside and Latif 2007) Kushnir et al. 2006 Summary Outlook
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Equatorial Atlantic Cold Tongue 4 Cold tongue develops during boreal summer 4 Interannual variability of ATL 3 SST index (3°S– 3°N, 20°W– 0°) much smaller than seasonal cycle Brandt et al. 2011 10
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Onset of Atlantic Cold Tongue and West African Monsoon Outlook 4 WAM onset follows the ACT onset by some weeks. 4 Significant correlation of ACT and WAM onsets 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 11
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Regression of SST and Wind onto ACT Onset WAM Onset Cold tongue SST; Wind forcing in the western equatorial Atlantic (zonal mode) Significant correlation with cold tongue SST (zonal mode) and SST in the tropical NE Atlantic (meridional mode) Brandt et al. 2011 12
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary SST Errors in Coupled Climate Models Outlook Dark gray model too warm Large errors in the eastern tropical Atlantic Jungclaus et al. 2006
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary 2006 -2011 Tropical Atlantic Climate Experiment Outlook 4 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. 4 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. 4 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. 14
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook TACE observational network Observing system during the TACE period including different 15 process studies, like e. g. the 23°W equatorial moorings
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Equatorial Mooring Array at 23°W 4 single mooring from June 2005 43 moorings from June 2006 to May 2011 Ship Section Mean Brandt, et al. 2013, submitted 16
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets EUC from Shipboard Measurements Summary Outlook 420 shipboard velocity sections are used to calculate the dominant variability pattern in terms of Hilbert EOFs 4 Sorted with respect to the seasonal cycle 17
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Reconstruction of Zonal Velocity Sections Outlook 4 Dominant variability pattern from ship sections 4 Pattern are regressed onto moored time series 4 Method validation by using the ship sections itself 4 Alternative: optimal width method 18
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Validation of EUC Transport Calculation using Ship Sections Outlook 19
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Eastward EUC Transport 4 General agreement between different methods 20
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook EUC Transport 4 Years with strong and weak annual cycle 4 Ship sections alone are hardly conclusive about seasonal cycle 21
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Pacific EUC Transport 4 Mean EUC Transport (solid) and EUC transport for strong El Niños (dashed) 4 Strongly reduced EUC transport during El Niños. EUC disappeared during 1982/83 El Niño (Firing et Johnson et al. 2002 al. 1983) What is the relation between Atlantic EUC transport 22 and tropical Atlantic variability?
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Interannual Variability: SST ATL 3 and Wind West Atlantic 4 Richter et al. (2012): canonical events have strong/weak winds prior to cold/warm events 4 Canonical cold event: 2005 4 Canonical warm event: 2008 4 Noncanonical cold event: 2009 (warmest spring with weak winds, but coldest SST in August) 23
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Interannual Variability: SST ATL 3 and EUC Transport 4 Canonical cold/warm events are associated with strong/weak EUC 4 EUC during 2009 was weak and shows no variation during the strong cooling from May to July 24
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Interannual Variability: SST ATL 3 and April/May 2009 Anomalies 4 According to Richter et al. (2012) noncanonical events are driven by advection from northern hemisphere during strong meridional mode events 4 SST 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 Regression Maps 4 Strong June EUC associated with anomalous cold Cold Tongue and southerly wind anomalies in the northern hemisphere early onset of the West African Monsoon Brandt, et al. 2013, submitted 26
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook June EUC – Wind/SST Relation 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 Regression maps reflect a canonical behavior according to Richter et al. (2012) 29
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Monthly Regressions of Zonal Velocity onto EUC Transport Outlook 4 During all months: strengthening of the eastward EUC associated with strengthening of westward surface flow (strongest shear enhancement in June) 4 February: weak near surface flow variability, stronger changes in the south 30
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Seasonal Cycle of Upper Ocean Diapycnal Heat Flux Outlook 4 Strongest shear (1/s 2) and diapycnal heat flux (W/m 2) during June Hummels et al. 2013 31
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Deep Velocity Observations along 23°W 4 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)
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets and Basin Mode Oscillations 4 Downward phase and upward energy propagation 4 EDJ are excited at depth and propagate toward the surface update from Brandt et al. 2011 Summary Outlook
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Excitation of equatorial basin modes (Cane and Moore, 1981) Outlook Equatorial Vertical Mode Decomposition Deep Jets Harmonic analysis Equatorial Deep Jets
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Ocean Deep Dynamics Jets | Introduction Summary. Equatorial Outlook Deep Jets Equatorial Deep Jets 4 Greatbatch et al. (2012): EDJ can be described by high-baroclinic, equatorial basin modes. 4 How are the Jets forced? 1. Inertial Instability (Hua et al. 1997, d’Orgeville et al. 2004, Eden and Dengler 2008) 2. Destabilization of Rossby-gravity waves (Ascani et al. 2006, d’Orgeville et al. 2007, Hua et al. 2008, Ménesguen et al. 2009) 4 Upward energy propagation toward the surface hindered by the EUC (e. g. Mc. Phaden et al. 1986) or tunneling through the shear zone (Brown & Sutherland 2007)? 35
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Surface Geostrophic Velocity 44. 5 -year cycle of the geostrophic equatorial zonal surface velocity (from sea level anomalies 15°W 35°W) 4 Corresponding signal of the ATL 3 SST index (3°S– 3°N, 20°W– 0°) 4 Eastward surface flow anomaly corresponds to warm eastern equatorial Brandt et al. 2011 Atlantic. 36
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook EDJ interaction with the EUC? 4 Consistent downward phase propagation below the EUC 44. 5 -year cycle also North, South and above the EUC core 4 Phases suggest meridional displacement of the EUC core with the EDJ cycle 37
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook EDJ interaction with the EUC? 4 Consistent downward phase propagation below the EUC 44. 5 -year cycle also North, South and above the EUC core 4 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 Summary 4 Interannual EUC transport variability largely in agreement with zonal mode variability 4 There are noncanonical events likely associated with meridional mode events during boreal spring 44. 5 -yr EDJ oscillations dominate depth range below the EUC: high-baroclinic, equatorial basin modes 4 Possible interaction of basin mode and EUC (time series are hardly long enough) 4 Improved numerical simulations are required for the understanding of physical processes responsible for EDJ affecting SST and TAV 39
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 CMIP 5 White stipples indicate where models are consistently wrong 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 Climate Modelling/Prediction 4 State-of-the-art climate models still show large errors in the SE Atlantic 4 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 4 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) 41
Introduction Data & Methods EUC Transport EUC-TAV Relation Equatorial Deep Jets Summary Outlook Closing knowledge gaps – enhanced observations Gulf of Guinea and Eastern Boundary Upwelling regions Glider campaigns and cruises in 2014, 2015, and 2016, various seasons Enhanced ARGO floats in Eastern Atlantic 8 E 6 S, PIRATA mooring Current meter at 0 E, eq Mooring 20 S Current meter mooring array was deployed at 11°S off Angola during Meteor cruise in July 2013
Acknowledgements 4 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”. 4 Moored velocity observations were acquired in cooperation with the PIRATA project. 43
- Slides: 43