1. National Oceanography Centre
RAPID-WATCH/MOCHA
Atlantic Meridional Overturning Circulation and Heat Flux Monitoring Array at 26.5°N
Gerard McCarthy
and
Stuart Cunningham
National Oceanography Centre
BINAFS. Stand straight, speak slowly and clearly. Face the audience. Thank you David. Good afternoon.
What I intend in this talk is to give a broad review of the array – methodology followd by results. I would like to thank all my co-authors, then immediately apologise to them for all the details I am likely to miss. However, everything I will present comes from published papers where all the details and much more analysis than I can discuss here is presented.
Chris Atkinson, Molly Baringer, Lisa Beal, Harry Bryden, Maria-Paz Chidichimo, Julie Collins, Stuart Cunningham, Aurélie Duchez, Joel Hirschi, William Johns, Helen Johnson, Torsten Kanzow, Jochem Marotzke, David Marshall, Gerard McCarthy, Chris Meinen, Aazani Mujahid, Darren Rayner, Zoltan Szuts, Eleanor Frajka-Williams

2. Outline How do we estimate the MOC at 26.5°N?
Basinwide transports in an Eddy-filled Ocean
Seasonal Variability at 26.5°N
Atlantic Ocean Heat Transport at 26.5°N
Recent Changes in the MOC at 26.5°N .

3. How do we estimate the MOC at 26.5°N?
Previous estimates of OHT transport have been derived from hydrographic sections. At 26.5°N these have given estimates between 1.1 to 1.4 PW with an uncertainty of about 0.3PW.
Variability of ocean heat transport is not well known but obviously is an important factor in long-term climate variability. So one goal of the RAPID array is to provide continuous estimates of the meridional heat flux.

4. Western Boundary Wedge Currents and the mid-ocean Dynamic Height and Bottom Pressure Array
Johns, W. E., L. M. Beal, M. O. Baringer, J. Molina, D. Rayner, S. A. Cunningham, and T. O. Kanzow (2008), Variability of shallow and deep western boundary currents off the Bahamas during : First results from the 26°N RAPID-MOC array, J. Phys. Oceanog., 38(3),
Principle of mid-ocean array is to calculate the profile of geostrophic velocity from boundary dynamic height moorings. WB : moorings WB2, WBH2, moorings on either side of the MAR to account for any deep flows on either side of the ridge; WB a series of moorings crawling up the slope. AABW. In addition to dynamic ht moorings we have an array of bottom pressure recorders measuring.
Describe plot: Shows the annual mean meridional component of velocity measured by current meters for the period March 2004 to May 2005.
Antilles current, part of the subtropical circulation which remains outside of the Carribean. It is a subsurface intensified current.
Below about 900m the flow is southward. This is the inshore edge of the DWBC. However flow is weak in the inshore region because a submarine ridge to the north deflects the DWBC offshore.
Rayner, D., et al. (2011), Monitoring the Atlantic Meridional Overturning Circulation, Deep Sea Research II, in press.

5. Overturning stream function
red dots
LHS: Equation ; transport-per-unit-depth for each of the components
RHS : The MOC is taken as the maximum of the overturning stream function. It is the maximum northward transport shallower than 1025m.
Gulf Stream transports from Florida Straits Cable measurements
Ekman transports from ECMWF ERA-Interim winds since demise of QuickScat
Zero Nett Mass transport as observed e.g. Bryden, H. L., et al.(2009) Ocean Science, 6,

6. Gulf Stream, MOC, Ekman & Upper Mid-Ocean Transports (10-day & 3-month, low-pass filtered) April 2004 to April 2009
Mean [Sv] GS
31.8±3.1
MOC
18.1±4.3
Ekman
2.9±3.0
UMO
-16.6±3.4
Describe plot: Timeseries are 10-day low pass, the black line through each timeseries is a 3-month low-pass filter. NOTE vertical lines are 1st April each year!
The MOC which is the transport in the upper 1100m (red). It is the sum of northward GS (blue), ekman (black) and southward upper mid-ocean thermocline recirculation (magenta). The components have similar variability and are essentially uncorrelated so the variance in the MOC is the sum of variances in the other components.
The latest section of timeseries is from April 2009 to 22 Dec The year April 2009 to April 2010 is highly anomalous. The MOC is only 12 Sv – 5 Sv less than the timeseries mean. Contributing to this is an anomalously high southward thermocline transport (where the typical seasonal cycle has vanished) and in the winter period extreme southward Ekman transports. These low Ekman transports correspond to a ….
MOC timeseries and related data products are available from
Data from individual instruments are available from

7. Gulf Stream, MOC, Ekman & Upper Mid-Ocean Transports (10-day & 3-month, low-pass filtered) April 2004 to Dec 22nd 2010
Mean [Sv] GS
31.6±3.1
MOC
17.2±4.9
Ekman
2.6±3.3
UMO
-16.9±3.5
Describe plot: Timeseries are 10-day low pass, the black line through each timeseries is a 3-month low-pass filter. NOTE vertical lines are 1st April each year!
The MOC which is the transport in the upper 1100m (red). It is the sum of northward GS (blue), ekman (black) and southward upper mid-ocean thermocline recirculation (magenta). The components have similar variability and are essentially uncorrelated so the variance in the MOC is the sum of variances in the other components.
The latest section of timeseries is from April 2009 to 22 Dec The year April 2009 to April 2010 is highly anomalous. The MOC is only 12 Sv – 5 Sv less than the timeseries mean. Contributing to this is an anomalously high southward thermocline transport (where the typical seasonal cycle has vanished) and in the winter period extreme southward Ekman transports. These low Ekman transports correspond to a ….
MOC timeseries and related data products are available from
Data from individual instruments are available from

8. Basinwide Transports in an Eddy-filled Ocean
Previous estimates of OHT transport have been derived from hydrographic sections. At 26.5°N these have given estimates between 1.1 to 1.4 PW with an uncertainty of about 0.3PW.
Variability of ocean heat transport is not well known but obviously is an important factor in long-term climate variability. So one goal of the RAPID array is to provide continuous estimates of the meridional heat flux.

9. RMS amplitude of SSH and dynamic height along 26.5°N
0 (km)
Kanzow, T., H. Johnson, D. Marshall, S. A. Cunningham, J. J.-M. Hirschi, A. Mujahid, H. L. Bryden, and W. E. Johns (2009), Basin-wide integrated volume transports in an eddy-filled ocean, J. Phys. Oceanog., 39(12), 3091–3110.
This plot shows dynamic height variability from moorings (crosses) and SSH variability (lines) from satelite measurements. The moorings are 25, 40 & 500km offshore from the Bahamas. The satellite periods are black for a long time series (green is it’s low pass equiv). The red and blue dashed color coded to match the mooring deployments.
We have the expected high variability offshore but near the coast there is an abrupt drop in variability which is captured by both the moorings and the satellite.
See also:
Bryden, H. L., A. Mujahid, S. A. Cunningham, and T. Kanzow (2009), Adjustment of the basin-scale circulation at 26°N to variations in Gulf Stream, deep western boundary current and Ekman transports as observed by the Rapid array, Ocean Science, 6,

10. Basin wide transports in an eddy-filled ocean
Conclusions
The eddy field at 26.5°N does not dominate MOC variability on interannual to decadal timescales, and does not pose as large a signal-to-noise problem for detection of secular trends.
SSH fluctuations increase from east to west, but decrease sharply within 100 km from Abaco shelf, in agreement with upper ocean transports.
Simple model experiments imply that the reduction in SSH variability is due to the rapid propagation of pressure anomalies along the boundary as waves.

11. Seasonal Variability at 26.5°N
Previous estimates of OHT transport have been derived from hydrographic sections. At 26.5°N these have given estimates between 1.1 to 1.4 PW with an uncertainty of about 0.3PW.
Variability of ocean heat transport is not well known but obviously is an important factor in long-term climate variability. So one goal of the RAPID array is to provide continuous estimates of the meridional heat flux.

12. Contribution of the upper mid-ocean western and eastern boundaries to the UMO seasonal cycle
±1.8 Sv,SE=1.0 Sv
±2.6 Sv, SE=0.5 Sv
SD 3.5 Sv, Range 7.0 Sv
SD 3.1 Sv, Range 6.2 Sv
Kanzow, T., et al. (2010), Seasonal variability of the Atlantic meridional overturning circulation at 26.5°N, J. Clim., 23(21), doi: /2010JCLI
Chidichimo, M. P., T. Kanzow, S. A. Cunningham, W. E. Johns, and J. Marotzke (2010), The contribution of eastern-boundary density variations to the Atlantic meridional overturning circulation at 26.5 N, Ocean Science, 6,
Atkinson, C. P., H. L. Bryden, J. J.-M. Hirschi, and T. Kanzow (2010), On the seasonal cycles and variability of Florida Straits, Ekman and Sverdrup transports at 26° N in the Atlantic Ocean, Ocean Science, 6(4), /os
TOP: Explain how isolate WB/EB contributions to MOC (fixed GS, EK and boundaries respecitvely)
Isolation of seasonal cycles of western and eastern boundary to MOC. Done by keeping the boundary density (alternatly east and west) and, ekman and gs fixed.
EB has larger and better defined seasonal cycle than the WB, so is a more important contribution to the seasonal cycle in the UMO and MOC than the WB.

13. Seasonal variability Conclusions
MOC seasonal cycle is 6.7 Sv peak-to-peak.
UMO contributes the most pronounced seasonal cycle of 5.9 Sv.
Seasonal cycle in UMO is caused by vertical density fluctuations at the Eastern Boundary forced by seasonal anomalies in the wind stress curl.

14. Atlantic Ocean Heat Transport at 26.5°N
Previous estimates of OHT transport have been derived from hydrographic sections. At 26.5°N these have given estimates between 1.1 to 1.4 PW with an uncertainty of about 0.3PW.
Variability of ocean heat transport is not well known but obviously is an important factor in long-term climate variability. So one goal of the RAPID array is to provide continuous estimates of the meridional heat flux.

15. Meridional Heat/Temperature Transport Variability
Template 0
Meridional Heat/Temperature Transport Variability
Net Heat Flux = 1.27 ± 0.30 PW (uncertainty 0.14 PW)
Contribution to the net heat transport variance (relative to the mid-ocean temperature)
FC=20%
EK=46%
WBW=8%
Gyre/eddy=1%
Mid-ocean=25%
Temperature transport (relative to 0°C)
Meridional Heat Transport (PW)
Previously 1.35
This plots shows temperature transports (relative to 0°C) for each of the contributions to the net heat flux. All components low-pass filtered with a 10-day cut off. The total heat transport (black) and gyre/eddy heat transport (light blue) are true heat fluxes independent of temperature reference.
Overall we expect the Eh variability to be dominated by the fluctuating velocity field and that is what we see. The timeseries of temperature transports are highly correlated to transport.
As for transport variability net heat flux variability is the root sum square of the temperature transport variability in each layer. Correlations – direct inference of their contributions to net Eh variability
Net heat flux is 1.35 PW and the uncertainty is 0.14PW which is a great reduction on error estimates for previous studies.
Johns, W. et al. (2011), Continuous, Array-based Estimates of Atlantic Heat Transport at 26.5°N, J. Clim., 24, pp. 2429–2449.

16. Meridional Heat Transport Conclusions
Template 0
The mean MHT (2004 to 2007) is 1.27 ± 0.3 PW.
Ekman contributes 46% of heat flux variability; Mid-ocean geostrophic fluctuations 25%.
Seasonal cycle 0.9 PW, dominated by the mid-ocean geostrophic variability. Maximum in summer/fall and minimum in March.
MHT is highly correlated with changes in strength of the MOC. The overturning accounts for 90% of the total MHT.

17. Recent Changes in the MOC at 26.5°N
Previous estimates of OHT transport have been derived from hydrographic sections. At 26.5°N these have given estimates between 1.1 to 1.4 PW with an uncertainty of about 0.3PW.
Variability of ocean heat transport is not well known but obviously is an important factor in long-term climate variability. So one goal of the RAPID array is to provide continuous estimates of the meridional heat flux.

18. Gulf Stream, MOC, Ekman & Upper Mid-Ocean Transports (10-day & 3-month, low-pass filtered) April 2004 to Dec 22nd 2010
Mean [Sv] GS
31.6±3.1
MOC
17.2±4.9
Ekman
2.6±3.3
UMO
-16.9±3.5
Describe plot: Timeseries are 10-day low pass, the black line through each timeseries is a 3-month low-pass filter. NOTE vertical lines are 1st April each year!
The MOC which is the transport in the upper 1100m (red). It is the sum of northward GS (blue), ekman (black) and southward upper mid-ocean thermocline recirculation (magenta). The components have similar variability and are essentially uncorrelated so the variance in the MOC is the sum of variances in the other components.
The latest section of timeseries is from April 2009 to 22 Dec The year April 2009 to April 2010 is highly anomalous. The MOC is only 12 Sv – 5 Sv less than the timeseries mean. Contributing to this is an anomalously high southward thermocline transport (where the typical seasonal cycle has vanished) and in the winter period extreme southward Ekman transports. These low Ekman transports correspond to a ….
MOC timeseries and related data products are available from
Data from individual instruments are available from

19. Gulf Stream, MOC, Ekman & Upper Mid-Ocean Transports (10-day & 3-month, low-pass filtered) April 2004 to Dec 22nd 2010
Extreme Lows in NAO, Winter 09/10 and 10/11
Jung, T. et al. (2011), Origin and predictability of the extreme negative NAO winter of 2009/10, Geophysical Res. Lett., 38, L07701.
Wang, C. et al. (2010), The record-breaking cold temperatures during the winter of 2009/2010 in the Northern Hemisphere, Atmoshperic Sci. Lett., 11,
Describe plot: Timeseries are 10-day low pass, the black line through each timeseries is a 3-month low-pass filter. NOTE vertical lines are 1st April each year!
The MOC which is the transport in the upper 1100m (red). It is the sum of northward GS (blue), ekman (black) and southward upper mid-ocean thermocline recirculation (magenta). The components have similar variability and are essentially uncorrelated so the variance in the MOC is the sum of variances in the other components.
The latest section of timeseries is from April 2009 to 22 Dec The year April 2009 to April 2010 is highly anomalous. The MOC is only 12 Sv – 5 Sv less than the timeseries mean. Contributing to this is an anomalously high southward thermocline transport (where the typical seasonal cycle has vanished) and in the winter period extreme southward Ekman transports. These low Ekman transports correspond to a ….
NAO Index

20. Component Transports and Layer Transports April 2004 to Dec 22nd 2010
Lower NADW (Blue line, Lower panel) declines in winter 2009/2010 at the same time as MOC and Ekman event (Red and Black lines, Upper panel)
Decline in the Lower NADW evident from historical hydrography (Bryden et al. [2005]
) and it is a water mass expected to decline first with MOC decline (Doshcher et al. [1994])
LNADW shows a reaction to the extreme Ekman event and corresponding MOC event. LNADW transport was historically much higher: 1957 – 14.8, 1981 – 9.0, 1992 – 10.4, 1998 – 6.1, 2004 – 6.9.

21. CONCLUSIONS
The RAPID array is delivering twice daily estimates of the strength and structure of the AMOC since 2004.
AMOC mean is 17.2±4.9 Sv, but in the year of 2009/10 was only 12.0 Sv, and during the winter was southward on occasion due to extremely negative NAO.
Variability due to eddies diminishes towards the boundaries where the RAPID measurements are made
Seasonal variability in the AMOC is nearly 7 Sv. Wind stress curl at the eastern boundary drives the anomalies.
Heat Flux is 1.35 PW, of which 90% is carried in the AMOC.