Resolving the seasonal cycle of mixed layer physics and phytoplankton biomass in the SAZ using high- resolution glider data Seb Swart, Sandy Thomalla &

Resolving the seasonal cycle of mixed layer physics and phytoplankton biomass in the

SAZ using high-resolution glider data

Seb Swart, Sandy Thomalla & Pedro Monteiro

Chl-a seasonal cycle

Thom

alla

et

al., 2

011

Complex balance between light and nutrient limitation that drives higher production in SAZ

>> Sub-seasonal variability of MLD modulates this balance

Joub

ert

et

al.,

subm

itte

d

Recent work highlights importance of seasonal to sub-seasonal forcing of ML

on PP (Levy, Klein, 2009; Thomalla et al., 2011; Fauchereau et

al., 2011)

The overall Chl variance that is explained by the seasonal cycle (0-100%) was computed as the variance explained by the regression of Chl onto a

repetition of the mean seasonal cycle.

SAZ

High res in situ MLD summer progression

and variability

17 transects of XBTs to derive

MLD

Light - Fe threshold(Jourbert et al.,

submitted)

SA

Z

Underway chl-a south of Africa

Well stratified, punctuated by short winter mix

Summer highly reproducible but winter not

Dominated by heat fluxes.

STZ

APZ MLDs are deep (±100m)

MLD is seasonal = 57%

57%

17%

What do gridded datasets tell us?

Monthly EN3-derived Brunt-Vaisala Frequency and MLD

14% Weak seasonal cycle = 14% Variable MLDs & weak strat. Assoc with high wind var =

2.5 m.s-1

SAZ

HYPOTHESIS

High rates of PP in SAZ are a direct result of MLD variability at submeso-subseasonal scales (around a threshold depth) that allows for alleviation of both light and Fe limitations at appropriate time scales for phytoplankton growth

Sw

art

et

al.,

2012

…At present we cannot do this without continuously sampling autonomous platforms!

Unless these time scales (sub-seasonal) are correctly defined in terms physical – biogeochemical coupling, models will not accurately reproduce the seasonal cycle and hence predict future climate states

Gough Is.

STF

SAF

APF

Gough/Tristan Transect

Goo

dHop

e Li

ne

Cape Town

Bathym

etry (meters)

= Glider deployment & ship CTD station

= ship based underway measurements

±2000 nm away…

SO SEASONAL CYCLE EXPERIMENT

September 2012 – March 2013

SG573

SG574

SG543

SG575

SG542

Surface – 1000m1.4 km horiz res

2532 dives = 5064 profiles537 days of sampling + ship process study

FLUOR

TEMP

SPRINGBLOOM PRIMING PERIOD

SUMMERBLOOM SUSTAINING

PERIOD

FLUOR

BVF

Tf

Cycl

one

Cycl

one

edge

Fron

t ed

ge

Intrus

ion

Subm

eso

fila

men

t

-edd

y

Strat. (BVF)

0-100m & 100-300m

MLD

Fluor

Temp

DensityPoster by S. Nicholson et al:

PP sensitivities to submeso dyn and subseas atm forcing

FLUOR

BVF

WindR=0.52

Density

MLD

Fluor

Strat. (BVF)

Spring – Summer MLD progression…a reminder of scales

5-hrly Glider

Monthly EN3

CFSR 7-day

1. Bloom initiations vary depending on the criteria used to define them.

Different bloom initiations can be explained by different mechanisms (e.g. Sverdrup’s critical depth, Taylor and Ferrari’s turbulent convection, Mahadevan’s eddy driven stratification) >> The response of the bloom onset to interannual and climatic change will depend strongly on which mechanism prevails, eg. wind/features

2. In Spring, feature driven changes to the mixed drives early stratification and bloom initiations>> If climate models don’t include lateral processes they will overestimate bloom initiation dates

3. In Summer, wind driven adjustments to the mixed layer plays an important role in sustaining the summer phytoplankton bloom by relieving Fe and light limitation at the appropriate time scales>> Highlight the importance of interplay between meso-submesoscale features versus wind-buoyancy processes in characterising the ML, productivity, timing of the bloom and carbon export

Conclusions

Many thanks to the following people and collaborators!

Geoff Shilling, Craig Lee &Eric D’Asaro at APL, UW

Derek &Andre at STS / SOERDC

Grant Pitcher & Andre Du Randt, DAFF

Stewart Bernard, Marjo Krug & Andy Rabagliati, CSIR

Gavin Tutt, DEA

IMT, SANAP, UCT, DEA & DAFF