On the path of the Gulf Stream
and the Atlantic Meridional
Overturning Circulation1 (AMOC)
Terrence Joyce2, WHOI
Rong Zhang, GFDL
1A manuscript of this title was recently published in J. Climate
2TJ is solely responsible for preparing this presentation, acknowledges support from PO NASA,
& has requested R. Zhang to present this at the US AMOC Science Meeting in June 2010.
Our motivation…
• AMOC variability is one of the central diagnostics
for understanding global climate change
• Until recently with the start of the RAPID moored
array at 26N in the Atlantic, we have not been able
to readily and accurately measure AMOC change
anywhere: repeat hydro sections are too ‘noisy’
• It would be desirable to find a good ‘proxy’ for
AMOC change that is readily measurable & can
be used for assessing models
Introduction - 1
The Gulf Stream path after it
separates from the western boundary
near Cape Hatteras tends towards
the ENE and is characterized by rings
and meanders. The dominant mode
of variability, however, is a meridional
shift of the entire path between 75
and 55oW. This was first shown in
Joyce, Deser and Spall (JCli 2001)
using ca. 50 years of subsurface
temperature data at 200m oriented
along the mean temporal position of
the “north wall” of the Gulf Stream.
This runs parallel to the large SST
gradient seen at the northern side of
the warm water in the Gulf Stream in
the satellite image at the right.
Introduction - 2
de Coëtlogon et al. (JPO, 2006)
examined the GS path variability
using our data-based source
(upper left), and 5 non-eddyresolving oceanic general
circulation models driven by
atmospheric fluxes derived from
the NCEP reanalysis. Like the
observations, the dominant EOF
of path variability (solid lines)
from the mean subsurface path
based on temperature (dashed
lines) was a mean ‘shift’ N/S of
the path. While the specific path
definition was different in the
models the temporal variability
of the lowest EOF is similar and
significantly correlated with the
observed path variability.
Introduction - 3
If the transport from 200:700m depth is
regressed against the GS path in each
of these models, the northward
excursions of the GS path are
associated with larger GS flows
(variability is in same direction as mean
GS). For southward paths, the GS
transport in decreased. Significant
correlations (90% level) are shown in
grey. In each model, the change in the
Atlantic Meridional Overturning
Circulation (AMOC), defined as the
mean annual max of the meridional
streamfunction north of 30N, was
estimated. Are changes in the AMOC
related to the path of the GS?
Introduction - 4
The answer is “yes”, although the
relationships are not robust. Time series
of the AMOC (solid line) and the GST
index (dashed) in the (left) model
simulation and (right) observations.
Ensemble means are used for MPI-OM
and MICOM. The correlation between
the two series is indicated. (from de
Coëtlogon et al., JPO, 2006). Almost
uniformly these models suggest that the
AMOC is larger when the GS path is
more northward.
In our original paper Joyce et al. (2001)
we developed a model in which a
delayed oscillator dynamics related the
strength of the DWBC and the GS at the
crossover point near Cape Hatteras. In
this model, a stronger DWBC would
‘advect’ the GS offshore leading to a
more southerly (not northerly) path.
However, this issue is far from settled…
The Principal component time
series of the lowest EOF of GS
path variability based on altimeter
data (north positive, upper), and
the PC of the leading EOF of the
joint SST and surface geostrophic
flow in the Slope Water (positive is
colder, more SW’ly flow, middle)
are plotted with their lagged
correlation. We find significant (at
90% level) correlations indicated
as grey dots (lower panel), where
significance is based on the
observed integral time scales of
the two correlated variables.
Adapted from Peña-Molino and
Joyce (2008). Thus a colder, more
SW’ly flow at the surface in the
Slope Water leads to a more
southerly GS path.
Hydro
cruises
Line W DWBC moored array
A mixed array of Moored
Profilers, VACMs, and Seacats
has been in the water since
2004, and is ongoing with
support from NSF as part of the
US AMOC Program.
DWBC composite section along Line W
Composite mean section
(distance, km, vs. depth, m)
across the Line W array starting
at 40N, 70W an extending along
an altimeter ground track across
the bathymetry. Dashed lines in
each panel are neutral density
surfaces, which are labeled in the
third panel. High oxygen and low
salinity ‘cores’ demark Labrador
Sea Water and GIN Sea
Overflow Water (no salinity
extremum), that make up North
Atlantic Deep Water (NADW),
which is found inshore and under
the GS on the section. The zero
normal velocity contour is in
white on the right panel. Adapted
from Joyce et al. (2005).
We see that an increase in the SW’ly flow at the surface
will increase the transport of the DWBC if the change has
a depth distribution like the mean flow (right panel).
DWBC and GS path redux
•Beatriz Peña-Molino thesis is dealing with Line W data and
the relationship between the DWBC variability, Slope Water
flow, and the GS path change
•Suffice for now in accepting that the velocity variability in the
Slope Water is coherent throughout most of the water column
and that increases in SW’ly near surface flow are positively
correlated with SW’ly transport increases of LSW
•The issue of how changes of the DWBC and AMOC are
related near 38N is still open: if DWBC and AMOC variability
is anti-correlated or if larger upper level Slope Water flow is
associated with a decreased DWBC (and AMOC), there is no
inconsistency between the observations and the models
•However, the simplest explanation is that the observations
are not consistent with the previous model results
•Yet consider some new developments…
GFDL CM2.1 coupled
climate model study
What Zhang (2008) found is that
the T400 index (red) constructed
from the GFDL CM2.1 1000year control integration is
significantly (at 99% level)
correlated (r=0.84) with the
AMOC variability (black) at 40N.
Therefore, T400 emerges as a
“fingerprint” of the AMOC in the
coupled model. This result
means that a stronger AMOC is
associated with a more
southerly GS path in the model,
also suggested by the recent
Line W research, but exactly
opposite to the previous
modeling work already cited.
The modeling connundrum…
•It is unknown why the coupled GFDL model produces a result that is
opposite to the previous models
•None of these models is eddy-resolving
•None of the ‘forced’ ocean models is coupled to the atmosphere –
is an active coupling responsible?
•It is not clear how well-developed the DWBC is in these forced
models – clearly in some, there is no room for a northern recirculation gyre – the GS is right up against the continental slope. So
is a well-established DWBC to north of the GS crossover
dynamics necessary?
•It is suggested from observations, however, that a stronger
DWBC is associated with a more southerly GS path – and this
suggests the GFDL model may be ‘correct’
•The latter clearly shows our bias – that models that agree with
observations are better than those that don’t!
And a 2nd “observational” result
to consider…
Balmaseda et al. (GRL, 2007) have
made an ocean state estimation
(ORA-S3) on a 1x1 deg. grid for the
period 1959:2006. In this work, all
available subsurface T,S data have
been used as well as SST and
altimetric data in recent years. Also
included since 2003 are Argo
profile data. The forcing for this
model is the ECMWF ERA40
reanalysis updated using an
operational product since 2003. At
the right is the time-mean
meridional streamfunction of the
zonally-integrated AMOC in the
upper 3000m of the model
(Balmaseda, pers. comm.).
Time-varying AMOC will be extracted for the upper
1200m near the max. streamfunction depth.
AMOC and the GS path redux
The annual mean (negative)
GS index based on T200 and
the T400 index from Zhang
(2008) are re-plotted with the
AMOC index from the
Balmaseda et al. calculated
near the intergyre boundary
(37-38.5N). All indices have
recently been updated and
corrected for XBT/MBT bias
and fall rate errors. While T200
and T400 are significantly
correlated (at 95%), the
correlations with the AMOC
index are marginally correlated
in the period of overlap with no
lag/leads with the GS path
index. One other ocean
reanalysis product (GECCO)
does not appear to reproduce
a correlated signal with the
observed GS path.
GS path and T(400m)
In the lower panel we show
the leading EOF of 50 yr
variability of the observed
subsurface temperature at
400m (adapted from Zhang,
GRL 2008). It is everywhere
positive except in the region
of the GS. The T400 index
(PC1) of this EOF is
significantly correlated
(r=0.62) at 95% with the
negative of the observed
GS path index at 200m
(upper panel). Input files
[WOD9] have corrected
MBT/XBT data. From Joyce &
Zhang, J. Climate, 2010, 23, 3170–
3178.
Tsub EOF1
Summary
•
AMOC change is one key dynamic examined in virtually all IPCC class
models in terms of natural and forced climate variability – its decrease is
one key anthropogenic ‘fingerprint’.
•
Since we do not have a record of the AMOC over the past 50 years, & have
only recently begun monitoring at 26N, some useful ‘proxy’ would be
desirable.
•
Various models indicate a significant relationship exists between AMOC
variability and the GS path.
•
However, the sign of this relationship seems to be in serious doubt & more
work understanding model response is needed!
•
Line W observations support models where GS path is southerly(northerly)
when the AMOC/DWBC is strong(weak).
•
This runs against paleo thinking that a more southerly GS was present
during the LGM when the AMOC was reduced
•
GS path is an index which, along with T400, might be compared to various
numerical calculations and ocean state estimations regarding AMOC and
DWBC variability.