use of xbt observations to assess meridional changes of moc in the

Use of XBT observations to assess meridional changes of MOC in the South Atlantic Ocean

Gustavo Goni (1), Shenfu Dong (1), Francis Bringas (1), Molly Baringer (1)

(1) NOAA/AOML, Miami, FL, USA

• Research funded by NASA, NOAA CPO and AOML• Most results published in Dong et al (2015)

5th XBT Science WorkshopTokyo, JapanOctober 2016

To investigate spatial (latitudinal) and temporal changes of the Meridional Overturning Circulation (MOC) and Meridional Heat Transport (MHT) in the South Atlantic Ocean using joint analysis of satellite and in situ observations.

Goal

• Most results published in Dong et al (2015)• Additional results posted at the AOML web site

Variability of MHT/MOC in the South Atlantic Ocean

• Obtain XBT-derived time series of MHT/MOC at 34.5°S

• Use XBT observations to assess altimetry-derived MHT/MOC estimates at 34.5°S

• Extend estimates to region (20°S-34.5°S)

• Assess temporal variability of MHT/MOC

• Assess temporal variability of Ekman and Geostrophic components

• Assess links between SAMOC and extreme weather

The upper ocean dynamics in the South Atlantic

Peterson and Stramma, 1991

Upper ocean dynamics in the South Atlantic Ocean

What is the XBT connection to this work ?

• XBTs provides most of the historical data needed to create dynamic height vs depth of isotherm statistics along 34.5S

• XBT transect AX18 provides the longest (since 2002) in situ time series of MHT/MOC at 35S, which is used to assess altimetric estimates

• XBTs continue to be the only in situ observing platform that will resolve mesoscale features in the boundaries.

SHA changes

EKE changes

SST changes

WSC changes

Non secular linear trends in the SA Ocean (1993-2010)

Sea Height Anomalies and Isotherm Depths

5°C 10°C 15°C

February 2005

Altimetry-derived temperature profiles

XBT T(z) profile

Altimetry T(z) profile

Difference (z)

Altimetry-derived MOC/MHT at 34.5°SAltimetry-XBT comparison

MOC (Sv) MHT (PW)XBT AX18 19.6±2.6 0.48±0.20Altimetry 19.2±2.8 0.51±0.22

Altimetry-derived MOC

• Mean MOC increases towards the center of the subtropical gyre (25-30°S)

• Variability is minimum at 30°S

• Maximum variability at 34.5°S

• Long period signals observed at all latitudes

Altimetry-derived MHT

• Mean MHT increases towards the north

• Variability is minimum at 30°S

• Maximum variability at 34.5°S

• Long period signals observed at all latitudes

MOC Negative since 2007

MOC dominated by Ekman until 2011MOC dominated by Geostrophy since 2011

MOC periods 5-10 year periods

MOC dominated by Ekman

MOC mostly negative before 2001MOC mostly positive after 2001

MOC dominated by Ekman before 20MOC dominated by Geostrophy since

Satellite altimetry allows to obtain an extended time series of MHT and MOC to 1993.

RMS difference between XBT and altimetry estimates are smaller than year-to-year changes in MHT and MOC.

Ekman (Geostrophic) component dominant before (since) 2011.

Results show that mean values of MHT decrease by approximately half between 20°S and 34°S.

Main Conclusions

Why is this type of work important ?Impact of the South Atlantic on global Rainfall

Lopez, H., S. Dong, S.-K. Lee, and G. Goni, 2016: The role of the South Atlantic Meridional Overturning Circulation variability on modulating interhemispheric atmospheric circulation and monsoons. J. Clim., 29(5):1831 - 1851, (doi:10.1175/JCLI-D-15-0491.1).

• Continue joint analysis of data (altimetry, XBT, and other in situ observations) for MHT and MOC studies.

• Investigate year-to-year variability (annual cycle removed) and possible MHT/MOC trends (linked to EKE, SH, SST, Wind variability?)

• Indexes for model comparisons, in collaboration with NOAA/GDFL

Current Plans

Thank you

Gustavo.Goni@noaa.gov