estimating the atlantic overturning at 26n using satellite altimetry [iugg]
TRANSCRIPT
Eleanor Frajka-Williams (Univ of Southampton)
Grace (NASA/JPL)
RRS Discovery
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Estimating the Atlantic overturning at 26N using satellite altimetry
[IUGG general assembly in Prague, Jun 2015]
Questions? @EleanorFrajka
[Kulbrodt et al, 2007]
Overturning circulation
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RAPID-MOCHA project: Observations of the time-varying large-scale ocean circulation
Funded by UK NERC, NSF and NOAA
Single value (the MOC) or components? • Components help us understand where and why the MOC is changing • But the actual value of the MOC is also important
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What do we really want to know?
Volume or Heat transport?
MOC timescales of variability: • Eddies on 20-100 day timescales (Clement et al. 2014; Frajka-Williams et al. 2013) • Wind-variability on interannual timescales (Yang & Johns 2014)
• Buoyancy-driven variability …?[Johns et al., 2011]
[Frajka-Williams 2015]
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In this talk:Introduce a proxy for the MOC at 26N
that recovers over 90% of the interannual variability of
the RAPID time series from 2004-2014.
Tell you why it doesn’t replace the in situ observations.
Data: RAPID transbasin transport
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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
Data: RAPID transbasin transport
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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
Method
Temporal:Remove seasonal cycle1.5 year Tukey filter
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AVISO Sea level anomaly (SLA):
RAPID upper mid-ocean transport time series (UMO):
Focus on the interannual variability…
Remove eddies…Spatial:Smooth (5x10 deg):
Regress RAPID UMO against SLA
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AVISO SLA: RAPID UMO transport:
[Frajka-Williams 2015]
Regress RAPID UMO against SLA
Method
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[Frajka-Williams 2015]
[Frajka-Williams 2015]
UMO transport is proportional to thermocline depth at the west.
Deeper (more negative) thermocline depth means stronger (more negative) UMO transport.
SLA vs transbasin transport UMO
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[Frajka-Williams 2015]
UMO transport is proportional to thermocline depth at the west.
2 cm change in SLA results in a 1 Sv change in UMO
SLA vs transbasin transport UMO
[Frajka-Williams 2015]
[Frajka-Williams 2015]
From SLA: MOC* = EK + GS + UMO*
Using SLA for UMO, determine MOC
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From RAPID: MOC = EK + GS + UMO
EK from ERA-Interim since 1979 GS from Florida Cable since 1982 UMO* from SLA since 1993
[Frajka-Williams 2015]MOC* since 1993
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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 just use SLA to investigate longer term MOC changes?
[Frajka-Williams 2015]
Using SLA for UMO, determine MOC
Single value (the MOC) or components? • Components help us understand where and why the MOC is changing • But the actual value of the MOC is also important
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Recall: What do we really want to know?
Volume or Heat transport?
MOC timescales of variability: • Eddies on 20-100 day timescales (Clement et al. 2014; Frajka-Williams et al. 2013) • Wind-variability on interannual timescales (Yang & Johns 2014)
• Buoyancy-driven variability …?[Johns et al., 2011]
To date, MOC interannual variability has been dominated by wind-forcing (debatable, but evidence suggests yes).
This is consistent with model-based studies (e.g., Yeager 2015; Pillar et al. 2015)
• RAPID observations demonstrate that most of the interannual variability originates in Ekman & UMO transport. • SLA reconstruction works because 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 the UMO-SLA relationship would be as strong.
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Why not just use SLA proxy?
The SLA proxy provides a 20-year proxy for MOC variability.
IF the SLA-UMO relationship is stationery,then we can use it to look at lower frequency MOC changes.
Suggests that: • Trend over 2004-2014 does not
continue back in time • Moderate reduction (1 Sv) between
1994 decade & 2004 decade[Frajka-Williams 2015]
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Even so…
Thank you! See: http://eleanorfrajka.com/moc-from-space Questions? @EleanorFrajka