Southern Ocean Surface Measurements
and the Upper Ocean Heat Balance
Janet Sprintall
Sarah Gille
Shenfu Dong
Scripps Institution of Oceanography, UCSD
Challenges in the Southern Ocean
Western Boundary Currents Southern Ocean
data rich
data poor
sampling possible all year round very few winter observations
heat transport from low to high
latitudes
circumpolar SST probably
means little net heat transport
ocean heat transport primarily
geostrophic
strong westerlies drive strong
meridional Ekman transport
fairly reliable, validated surface
heat flux products
heat flux products with very
large uncertainties
Talk Outline:
1. Status of shipboard observations in the Southern Ocean
2. Science Applications:a. Variability in the Antarctic Polar Front
b. The upper ocean heat budget in the Southern Ocean
3. Conclusions: Implications for data sampling requirements in the
Southern Ocean
Southern Ocean HR-XBT Measurements
USA-SIO; Aust-CSIRO;
NZ-NIWA; France
www-hrx.ucsd.edu
NOAA-AOML
www.aoml.noaa.gov/phod/hdenxbt/high_density_home.html
IX21
IX15
PX50
PX14
AX18
AX25
PX08
IX28
Italian CLIMA
PX81
AX22
U.S-Chinese
moon.ldgo.columbia.edu/~xiaojun/xbt/
Drake Passage Measurements
Depth averaged
ADCP velocity
wind speed (m/s)
pCO2 (atm)
salinity (psu)
XBT temperature
PIs: Sprintall (XBT); Takahashi, Sweeney (pCO2); Chereskin, Firing (ADCP)
Science Application:
1. Variability in the Antarctic Polar Front*
MODIS (Infrared)
Lots of cloudy or bad data
AMSR-E (Microwave)
AMSR-E: cloud penetration
*Dong, Sprintall & Gille, Location of the Antarctic Polar Front from AMSR-E Satellite
Sea Surface Temperature measurements, J. Phys. Oceanogr., in press, 2006.
Comparison of the PF Location from XBT and AMSR-E SST
 Subsurface Polar Front
from XBT (northern extent
of the 2°C isotherm at 100300m depth)
 Surface Polar Front
from AMSR-E
(southernmost location of
an SST gradient above
1.5x10-2°C km-1)
Mean Polar Front Location
AMSR-E (2002-05)
Dong et al. (2006)
AVHRR SST (1987 – 1993)
Moore et al. (1999)
Deep ocean basin with weak bottom slope: large PF variability
What controls the Polar Front Variability?
1. Response of PF location to
meridional shifts in the wind field
(∂PF/∂t ~ ∂(x)/∂t)
wind
wind
PF
coherence
60% > 95%CI
phase
PF
phase
negative phase: shift in latitude of maximum zonal
wind stress leads meridional shift in PF
histogram
of phase
Science Application:
2. Southern Ocean Upper Ocean Heat Budget*
Domain Averaged Surface Layer Heat Balance
(weekly resolution on 1°x1° grid)
Tm Qnet  q(hm)
weT
2

 um  Tm   Tm 
t
ocphm
hm
* Dong, Gille and Sprintall, Heat budget of the Southern Ocean, in prep, 2006
Horizontal Advection
Tm Qnet  q(hm)
weT
2

 um  Tm   Tm 
t
ocphm
hm

geostrophic advection (AVISO SSHa plus GRACE)
Ekman advection (COAPS wind stress)
Tm mixed layer temperature AMSR-E SST
Imbalance of the Heat Budget Analysis
Tm Qnet  q(hm)
weT

 um  Tm   2Tm 
t
ocphm
hm

Largest
imbalance in winter
(~100 W m-2)
“Best Case” rms of the imbalance is 146 Wm-2 (0.031°C/day)
(NCEP1 air-sea heat fluxes; ARGO density MLD; diffusion =500 m2s-2;
spatially-variable ∆T from ARGO)
Sensitivity: 1. Surface heat flux products
Spatial rms of Qnet (Wm-2)
(1 Jan 2000 - 31 August 2002)
NCEP1-NCEP2
RMS of heat balance:
NCEP1: 146 Wm-2
NCEP2: 148 Wm-2
(June 02 - Dec 05)
NCEP1-ECMWF
NCEP1-SOC
(monthly clim)

Tm Qnet  q(hm)
weT

 um  Tm   2Tm 
t
ocphm
hm
Sensitivity: 2. Mixed Layer Depth (hm)
Tm Qnet  q(hm)
weT

 um  Tm   2Tm 
t
ocphm
hm
hm from ARGO float data (∆=0.03kg/m3)
Variable hm

Time-Mean hm
Sensitivity: 2. Mixed Layer Depth (hm)
Tm Qnet  q(hm)
weT

 um  Tm   2Tm 
t
ocphm
hm

RMS of Heat Balance for Various MLD:
1. Argo Floats climatology (Jun 02 - Dec 05):
- density diff 0.03kgm-3: 0.031°C/day (146 Wm-2) “best” case
- temp diff 0.2°C:
0.033°C/day (157 Wm-2)
2. de Boyer Montegut et al. (2004) climatology:
- density diff 0.03kgm-3:
insufficient data
- temp diff 0.2°C:
0.037°C/day (151 Wm-2)
3. WOA 2001 climatology:
- density diff 0.125kgm-3: 0.038°C/day (235 Wm-2)
NB: Density MLD criteria uses variable
∆T in entrainment term; temperature
MLD criteria uses ∆T=0.02°C.
T Qnet q(h )
w T
Sensitivity:

 u T   2T 
t
ch
h
3. ∆T across the base of the MLD
Annual Average ∆T from Argo floats
m
m
e
m
o p m
m
m
m

• many studies use ∆T=0.2°C (eg. Qiu and Kelly, 1993)
• for ∆T=0.2, rms of imbalance is 159 Wm-2 cf “best” case of 146 Wm-2.
• largest improvement in Indian Ocean where ∆T can be negative: salinity matters!
• differences in ∆T are largest in fall and winter when entrainment is strongest
Spatial Variability in the Imbalance of the Heat Budget
• Largest imbalance north of ACC: hm is large & temperature gradient is strong
• complex upper ocean processes not well resolved by existing measurements
Regional Heat Budget: The Agulhas Retroflection
March Average
(x10-6 °Cs-1)
cooling
warming
• strong SST gradient and large meanders in Agulhas region
• reanalysis Qnet has long length scales, while we & advection have smaller scales: net effect on
imbalance is small scale structure.
• large imbalances related to small-scale coupling of the wind field and SST?
(e.g O’Neill et al. (2003) find wind stress curl (divergence) related to cross (down) wind components of SST gradient)
Conclusions: Implications for data sampling requirements
1. Shipboard Measurements
- met & pCO2 sampling opportunity: need identified PIs.
2. Science Application: Polar Front Variability
- weekly and daily SST fields resolve similar PF locations
- winds are important! Global forcing fields from satellite.
- winds more energetic at higher frequencies
3. Science Application: Upper Ocean Heat Balance
- large uncertainties in all terms!
- Qnet varies enormously. Need validation with in situ data
and winter time measurements
- salinity matters! Need Argo floats for MLD and ∆T
- need spatial resolution ~0.25° for small-scale coupling
- weekly and daily SST fields give similar heat balance
What controls the Polar Front Variability?
2. Response of PF Transport to
changes in zonal wind stress
du/dt (~ u==dT/dy) and x
wind
coherence
70% > 95%CI
ACC
phase
wind
ACC
histogram
of phase
negative phase: change in zonal wind stress
leads to changes in PF transport
Southern Ocean Heat Balance by Basin