This is longer version of a similar talk from IUGG in Prague. The main differences are the addition of results for 16N and more evidence for why the altimetry-transport relationship works at these latitudes. Climate simulations predict a slowing of the AMOC in the coming years, while present day observations from boundary arrays demonstrate substantial variability on weekly- to interannual timescales. These arrays are necessarily limited to individual latitudes. How well does satellite altimetry replicate transbasin, full-depth ocean transports? Can we use satellite altimetry to extend our estimate of AMOC variability back in time (at 26N)? Do the spatial patterns of SSH variability help to broaden our view of AMOC strength beyond individual latitudes? This analysis complements in situ observational efforts to measure the MOC at multiple latitudes. http://www.rapid.ac.uk/ic15/programme.php

1. Estimating the Atlantic
overturning at 26N using
satellite altimetry
Eleanor Frajka-Williams (Univ of Southampton)
RRS Discovery
[RAPID/USAMOC meeting in Bristol, July 2015] Questions? @EleanorFrajka

2. [Kulbrodt et al, 2007]
The Meridional Overturning Circulation
(MOC)
RAPID-MOCHA project:
Observations of the time-varying
large-scale ocean circulation in the Atlantic
10 years of MOC (2004-2014)
Funded by UK NERC, NSF and NOAA

3. Single value (the MOC) or components (Gulf Stream, mid-ocean…)?
• Components & their variability help us understand where and why the
MOC is changing
• But the actual value of the MOC is also useful
Volume vs Heat transport
[Johns et al., 2011]
Different forcing mechanisms for
different timescales
• Eddies on 20-100 day timescales (e.g.
Clement et al. 2014; Frajka-Williams et al. 2013)
• Wind-variability on seasonal -
interannual timescales
(e.g. Zhao & Johns 2014, Yang 2015, Pillar et al. 2015,
Yeager 2015)
• Buoyancy-driven variability … longer
timescales?
What do we really want to know?

4. 1. Introduce a proxy for the MOC at 26N that recovers over 90% of the
interannual variability of the RAPID time series from 2004-2014.
2. Highlight a few important caveats
In this talk:
Paper in GRL 2015

5. Data: RAPID transbasin transport
MOC = EK + GS + UMO
For details of the method,
see McCarthy et al. 2015, Measuring the MOC
EK (meridional Ekman) from ERA-Interim
GS (Gulf Stream) from Florida Cable
UMO (upper mid-ocean transport, Bahamas to Africa)
from current meter & dynamic height moorings

6. Regress RAPID UMO against SLA
Temporal:
Remove seasonal cycle
1.5 year Tukey filter
Method:
RAPID upper mid-ocean
transport time series (UMO):
Focus on interannual
variability…
Spatial:
Smooth (5x10 deg):
Remove eddies…
AVISO Sea level anomaly (SLA):

7. Method:
RAPID upper mid-ocean
transport time series (UMO):
Regress RAPID UMO against SLA
AVISO Sea level anomaly (SLA):

8. [Frajka-Williams 2015]
UMO transport is proportional to thermocline
depth at the west.
Deeper (more negative) thermocline depth
means stronger (more negative) UMO transport.
2 cm rise in SLA results in a 1 Sv southward
intensification of UMO
SLA vs transbasin transport UMO

9. [Frajka-Williams 2015]
From SLA:
Using SLA for UMO, determine MOC
From RAPID:
MOC = EK + GS + UMO
MOC* since 1993
MOC* = EK + GS + UMO*
EK from ERA-Interim since 1979
GS from Florida Cable since 1982
UMO* from SLA since 1993

10. Why does this work?
at 26N, the west dominates interannual
variability of dynamic height, and
transbasin transport.
SLA proxy available at: http://eleanorfrajka.com/moc-from-space
Relatively simple vertical
structure at RAPID
East 26N
West 26N

11. This MOC* recovers over 90% of the variability of the RAPID MOC.
(note: the two are not independent since both use the same GS and Ek.)
Can we use SLA to investigate MOC changes beyond 2004-2014?
Does SLA inform our understanding of the spatial structure of MOC
variability?
[Frajka-Williams 2015]
Using SLA for UMO, determine MOC

12. To date, MOC interannual variability dominated by wind-forcing
(debatable, but evidence suggests yes).
• This is consistent with model-based studies (e.g., Yeager 2015; Pillar et
al. 2015; Yang et al. 2015; Zhao and Johns 2014)
RAPID observations demonstrate that most of the interannual variability
originates in Ekman and UMO transport.
• Sea level reconstruction works because the UMO-SLA relationship is
strong.
Buoyancy-driven variability occurs on longer time scales ?
(e.g., Yeager 2015; Pillar et al. 2015)
• Under buoyancy forcing/on longer timescales, not clear that UMO-SLA
relationship would work.
• Details in the SLA - steric height relationship more likely to change on
longer timescales
First, a couple caveats…

13. Caveats aside…
[Frajka-Williams 2015]
SLA proxy for MOC suggests
• Moderate reduction (1 Sv) in the AMOC between 1994- & 2004- decades
• Strong (0.5 Sv/year) trend from 2004- decade is not continued back in time
SLA proxy available at: http://eleanorfrajka.com/moc-from-space

14. Caveats aside…
[Frajka-Williams 2015]
SLA proxy available at: http://eleanorfrajka.com/moc-from-space
SLA proxy for MOC suggests
• Moderate reduction (1 Sv) in the AMOC between 1994- & 2004- decades
• Strong (0.5 Sv/year) trend from 2004- decade is not continued back in time

15. MOVE 16N: 15 years of observations,
w/slightly different measurement
principle than 26N:
• Western basin only: from eastern
edge of Caribbean to mid-Atlantic
ridge
• Primary observations below 1000
m
• Geostrophic reference level of
1200 m
Does this work elsewhere?
SLA proxy available at: http://eleanorfrajka.com/moc-from-space
Note: At RAPID we used the transbasin UMO transport (top 1000m, after
applying barotropic compensation)

16. Why does this work?
at 16N, the west (mostly) dominates
interannual variability of dynamic height,
and transbasin transport.
SLA proxy available at: http://eleanorfrajka.com/moc-from-space
Relatively simple vertical
structure at MOVE
MAR 16N
West 16N

17. Using the MOVE time series between the islands and the MAR, filter and
compare with spatially-smoothed, filtered SSH.
SLA proxy available at: http://eleanorfrajka.com/moc-from-space
Does this work elsewhere? MOVE 16N

18. [Frajka-Williams
SLA proxy available at: http://eleanorfrajka.com/moc-from-space
Potential to use SLA (& GRACE) to
help connect the dots between
latitudes in the Atlantic.
Synergies between latitudes/datasets

19. [Frajka-Williams
SLA proxy available at: http://eleanorfrajka.com/moc-from-space
Potential to use SLA (& GRACE) to
help connect the dots between
latitudes in the Atlantic.
Maybe even on longer timescales?
Synergies between latitudes/datasets
1990 1995 2000 2005 2010
−3
−2
−1
0
1
2
Using the SSHA at 30N and −75W
Transport[Sv]
SSHA proxy UMO
−2 0 2
−0.26
−0.24
−0.22
−0.2
R=0.81
UMO transport [Sv]
SSHA[m]
30 year NEMO 1/12 run

20. [Frajka-Williams
SLA proxy available at: http://eleanorfrajka.com/moc-from-space
Potential to use SLA (& GRACE) to
help connect the dots between
latitudes in the Atlantic.
What about:
• longer timescales?
• more depth structure?
• outside the subtropics?
• regions with less steep
topography?
• transports that rely less on
dynamic height?
Thank you!
Synergies between latitudes/datasets

21. Potential to use SLA (& GRACE) to
help connect the dots between
latitudes in the Atlantic.
What about:
• longer timescales?
• more depth structure?
• outside the subtropics?
• regions with less steep
topography?
• transports that rely less on
dynamic height?
Thank you!
[Frajka-Williams
SLA proxy available at: http://eleanorfrajka.com/moc-from-space
Synergies between latitudes/datasets
New project: MerMEED at 26N
Mechanisms responsible for mesoscale
eddy energy dissipation
Small boat fieldwork, mixing, gliders
Will be looking for a postdoc!