Auxiliary Material Submission for
"Southern Ocean wind-driven entrainment enhances satellite chlorophyll-a through the summer"
Journal of Geophysical Research, Oceans, 2014 (2014JC010203)
AUTHORS AND AFFILIATIONS
Magdalena M. Carranza and Sarah T. Gille
Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, USA.
INTRODUCTION
The supplementary material contains plots showing the slopes of a linear regression model for
statistically significant correlation maps shown in the main body of the paper. The linear regression
model used to fit anomalies of the variables was forced to intercept zero, such that a change in the
predicted variable is determined entirely by the slope. In all figures we shade areas where correlations
are not significant at the 90% level. For Chl-a anomalies, we use the time series of the difference
between observed Chl-a and the climatological mean instead of anomalies expressed as a percentage
(see Section 2.1) to report slopes in Chl-a units and ease the interpretation.
On synoptic storm scales, a 0.5-1.5 degree C decrease in SST is expected for a wind speed increase of 10
m/s relative to the climatological monthly mean in most areas of the Southern Ocean (Fig. 1). In the
same manner, an increase of the MLD of 20-50 m (depending on location) is expected for every 10 m/s
increase in wind speed (Fig. 2a), whereas a 5-15 m increase in the MLD is expected for every 100 W/m^2
in heat loss (Fig. 2b). A deepening of the MLD leaves an imprint on the SST, and for every degree C of
cooling we may expect a deepening of the MLD as large as 10 m (Fig. 2c). Slopes for Chl-a vs wind speed,
Qnet and SST show more spatial variability. For instance, wind speed show the largest slopes in the
Atlantic Sub-Antarctic Zone (SAZ) where a wind speed anomaly of 10 m/s could lead to an increase in
Chl-a of 0.1 mg/m^3 (Fig. 3a), and the same increase in Chl-a is expected for a cooling of 1 degree C over
the northern Patagonian shelf, South Africa's shelf and downstream of Kerguelen (Fig. 4b).
FIGURE CAPTIONS
------------------------------------------------------------- Figure S1 -------------------------------------------------------------2014JC010203R-ps01.eps
Slopes of a linear regression model between daily anomalies of wind speed and SST for summer (DJF)
data of 2002-2011. Anomalies were spatially smoothed and high-pass filtered in the time domain to
highlight the effect of atmospheric synoptic storms (i.e spatial scales >350 km and timescales < 10 days).
Dotted areas indicate the correlation is not significant at the 90% level. The mean positions of the STF,
SAF and PF are shown in black contours.
------------------------------------------------------------- Figure S2 -------------------------------------------------------------2014JC010203R-ps02.eps
Slopes of a linear regression model between daily anomalies of (a) MLD and wind speed, (b) MLD and
Qnet, and (c) MLD and SST. Because MLD data is sparse, here we do not smooth out or filter the data in
time. Cross-hatched areas indicate the correlation is not significant at the 90% level. The mean positions
of the STF, SAF and PF are shown in black contours.
------------------------------------------------------------- Figure S3 -------------------------------------------------------------2014JC010203R-ps03.eps
Slopes of a linear regression model between high-pass filtered daily anomalies of (a) Chl-a and wind
speed and (b) Chl-a and Qnet, considering spatial scales larger than 350 km and timescales of less than
10 days that highlight the effect of atmospheric storms. Dotted areas indicate the correlation is not
significant to the $90\%$ level. The mean positions of the STF, SAF and PF are shown in black contours.
------------------------------------------------------------- Figure S4 -------------------------------------------------------------2014JC010203R-ps04.eps
Slopes of a linear regression model between (a) weekly anomalies of Chl-a and SST, and (b) high-pass
filtered daily anomalies of Chl-a and SST, controlling for the effect of Qnet, and considering spatial scales
larger than 350 km x 350 km. Dotted areas indicate the correlation is not significant to the 90% level.
The mean positions of the STF, SAF and PF are shown in \deleted{dashed} black contours.