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Estimating the Atlantic overturning at 26N using satellite altimetry [IUGG]

See http://eleanorfrajka.com/moc-from-space/ Slides from IUGG meeting in Prague: Estimating the Atlantic overturning circulation at 26N from satellite altimetry.

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Estimating the Atlantic overturning at 26N using satellite altimetry [IUGG]

  1. 1. Eleanor Frajka-Williams (Univ of Southampton) Grace (NASA/JPL) RRS Discovery 1 Estimating the Atlantic overturning at 26N using satellite altimetry [IUGG general assembly in Prague, Jun 2015] Questions? @EleanorFrajka
  2. 2. [Kulbrodt et al, 2007] Overturning circulation 2 RAPID-MOCHA project: Observations of the time-varying large-scale ocean circulation Funded by UK NERC, NSF and NOAA
  3. 3. 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 3 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]
  4. 4. [Frajka-Williams 2015] 4 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.
  5. 5. Data: RAPID transbasin transport 5 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. 6. Data: RAPID transbasin transport 6 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
  7. 7. Method Temporal:
 Remove seasonal cycle
 1.5 year Tukey filter 7 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
  8. 8. 8 AVISO SLA: RAPID UMO transport: [Frajka-Williams 2015] Regress RAPID UMO against SLA Method
  9. 9. 9 [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
  10. 10. 10 [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]
  11. 11. [Frajka-Williams 2015] From SLA: MOC* = EK + GS + UMO* Using SLA for UMO, determine MOC 11 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
  12. 12. 12 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
  13. 13. 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 13 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]
  14. 14. 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. 14 Why not just use SLA proxy?
  15. 15. 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] 15 Even so… Thank you! See: http://eleanorfrajka.com/moc-from-space Questions? @EleanorFrajka

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