decoupling of iron and phosphate in the global ocean
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Decoupling of Iron and Phosphate in the Global Ocean. Payal Parekh MIT/WHOI Joint Program April 18, 2003 In collaboration with Mick Follows, Ed Boyle and John Marshall. Thesis Aims. Develop a mechanistic model of iron cycling to : reproduce observed [Fe] - PowerPoint PPT PresentationTRANSCRIPT
Decoupling of Iron and Phosphate in the Global Ocean
Payal ParekhMIT/WHOI Joint Program
April 18, 2003In collaboration with Mick Follows, Ed Boyle and John
Marshall
Thesis Aims
• Develop a mechanistic model of iron cycling to:– reproduce observed [Fe]– predict rates of biogeochemical processes– understand controls on Fe in upwelled waters
– gain insight on decoupling of Fe and PO4
Motivation: Understand iron’ s role in possible pCO2 drawdown.
High Nutrient, Low Chlorophyll Regions
Longitude
Latit
ude
Conkright et al. (1994)
µM
Chlorophyll Distribution
SeaWiFS image
Could Lack of Iron be the Culprit?• Sources of Iron to surface
waters: – Upwelling– Aeolian Dust Flux
mg F
e m -2 yr -1
Gao et al. (2001)
Link between dust flux and pCO2?
Age (kyr)
Dust F
lux (mg m
-2 yr -1)A
tmos
pher
ic C
O2 (p
pm)
Iron Addition Experiment
SOIREE – S. Ocean
Why are Fe and PO4 decoupled?
R=Fe:PO4 biological uptake ratio
Iron Biogeochemistry
biologicalloop
dissolvedFe
(< 0.4 m)
biogenic export
lateral transportand mixing
DUST
refractory dustupwelling andvertical mixing
mixed layer bottom
surface
remineralization
sediment-water interface
lateral transport
scavenging& desorption
mixing
sedimentary deposition
scavenging& desorption
Fe’ + L’ FeLFe’ + L’ FeL
Fe’ + L’ FeLFe’ + L’ FeL
Figure from Bergquist
Iron Observations
Surface 1000m
Compiled from the literature and Boyle (unpub).
Is it possible to reproduce and understand controls on observed deep water Fe distributions?
• Perform sensitivity tests to constrain rates of biogeochemical processes using an idealized multi box model
• Test iron parameterization in the MITGCM, resolve intrabasinal differences and vertical profile of iron
Box Model Simulations
• Volume transport chosen to fit Radiocarbon, Broecker/Peng (86,87)• Tracers: PO4, DOP, Fe• Biological Uptake: µ*[Fe/(Fe+Ks)]
– Michaelis-Menten kinetics – Fe, light limited
Iron Parameterization
• K= binding strength of ligand
• Log(K) ranges 9.5-13.2
• FeL=K[Fe’][L’]
• LT=L’+FeL
• LT = 1 nM, based on Rue/Bruland (1995) and others
Results: Complexation Case
Ksc yr-1
log
K
Atlantic
S. Ocean
Indo-Pac.
0.6 nM
0.3 nM
0.4 nM
Summary: Box Model Results
• Iron parameterization successfully reproduces deep water Fe gradients
• Sensitivity study constrains scavenging rate over wide range of K (ligand binding strengths).
Explorations with an Ocean General Circulation Model
• Same parameterization as in box model• Forced seasonally with Gao et al. (2001) dust
flux estimate
Modeled Fe
• Fe exceeds solubility (Liu and Millero, 2002) in surface waters
• Successfully reproduces observed Fe gradients at depth
Surface
935m
Observations: PO4
Conkright et al. (1994)
Surface
1000m
Modeled PO4
• Fe limitation term [µ*(Fe/Fe+Ks)] successfully reproduces HNLC region– Previously, models either restored to surface or adjusted export time scale
• Model has difficulty in subtropical Pacific surface waters (nutrient trapping)• Deep water PO4 agrees well with observations
Surface
1000m
Fe*: Measure of decoupling between Fe and PO4
• Fe* = Fe-RPO4
• Interpretation of Fe*:– Positive Fe*: Adequate Fe to support
biological utilization of PO4
– Negative Fe*: Deficit in Fe
• Fe:PO4 ratio (R) must be specified
Fe*: Zonally averaged section in the Atlantic
• Positive at surface in northern hemisphere• As NADW travels southward, scavenging depletes Fe*• AAIW/AABW both negative due to low aeolian dust flux in S. Ocean
Calculated residence time for
GCM: 285 yr
Calculated residence time for
GCM: 285 yr
Fe*: Indo-Pacific
• Positive Fe* at surface between 25-40° N
• Decoupling of Fe and PO4 greatest in deep, old waters of N. Pacific.
North Pacific vs. North Atlantic
• Both basins have high dust flux and are regions of upwelling
• Why is the N. Pacific Fe limited?
Aeolian Fe flux (mg Fe m-2 yr-1)
Fe* below the mixed layer
• Aeolian dust flux is not enough to compensate for the low Fe, high PO4 waters of the old, upwelled waters in the N. Pacific
Fe* at 290m
GCM Simulations: Summary
• Mechanistic parameterization of Fe that includes complexation and scavenging reproduces deepwater Fe gradients
• The model exceeds solubility (Liu and Millero, 2002) at the surface in high dust flux regions
• Fe* is a useful tracer for understanding how/why Fe and PO4 become decoupled in HNLC regions
Utility of mechanistic Fe model
• A mechanistic Fe model allows for exploration of important climate questions, such as Does increased dust flux lead to increased efficiency of the biological pump and subsequent drawdown in pCO2?
Surface PO4 Sensitivity to Increased Dust Flux: Preliminary Results
• ‘Paleo’ dust estimate from Mahowald et al. (1999)• Dust flux greater nine times globally• 63 fold increase in the Southern Ocean
Southern Ocean Surface PO4 Response
• Drawdown of ~ 0.5 µM
• Due to low surface PO4,
results should be viewed as a lower bound estimate
• Watson et al. (2000) estimated 0.6 µM drawdown of PO4 - ~ 30 ppm drawdown
PO4
(µM)
Δ PO4
Thesis Conclusions
• Developed a mechanistic model of Iron cycling for the global ocean:– Sensitivity study using box model suggests iron
scavenging rate ranges between 0.1-2 yr-1 log(K) between 10-13
– Complexation and scavenging description successfully reproduces deep water Fe gradients in the GCM
– Fe* is a useful tracer for understanding the decoupling of Fe and PO4
• Dust flux is not enough to compensate the low Fe* of upwelled waters in HNLC regions
• A nine fold increase in dust flux results in ~ 0.5 µM drawdown of PO4
Research Recommendations
• A pressing need for Fe measurements, especially in the deep waters
• Identification of source(s), sink(s) and chemical characterization of Fe-binding ligands
• Experiments aimed at studying processes affecting Fe in surface waters
Works in Progress
• Improving surface iron distribution in model– in collaboration with M. Follows, E. Boyle
• Coupling iron model with a more sophisticated ecosystem model – in collaboration with S. Dutkiewicz, M. Follows
• Exploring more closely iron cycling in the S. Ocean – in collaboration with T. Ito, J. Marshall
Acknowledgements
• J. Marshall for inviting me to join his group• M. Follows for being a patient and encouraging advisor• E. Boyle for sharing his insights on iron chemistry and
the intricacies of making iron measurements• J. Moffett for enlightening me on iron’s role in ocean
ecology• M. Bacon for pointing me to the parallels between iron
and thorium• T. Voelker for acting like a committee member and being
a supportive female faculty member of the Joint Program
Acknowledgements
• S. Dutkiewicz and T. Ito for many stimulating discussions on ocean biogeochemistry
• J. Campin for teaching me how to program (and debug) in FORTRAN
• C. Hill for introducing me to the joys of running on parallel computers
• M. Losch and D. Ferreira for sharing with me their encyclopedic knowledge of MATLAB
• The folks on the upper floors of the Green Building for their friendship and assistance at various times for various tasks
Acknowledgements
• Thesis Crisis Intervention Committee: Bridget Bergquist, Mick Follows, Chris Hill, Taka Ito, Alex Rae, Steph Dutkiewicz , Ariane Verdy, Fanny Monteiro, Oren Weinrib
• Friends that fed and housed me during the dark days of thesis writing: Anke, Jen and Pedro, Fernanda, Nico, Anne, Vijay family, Patrick, Ariane, Fanny
• To the many friends (old and new) I have made at MIT, WHOI and around the city for reminding me that there is a world beyond the Green building
• The MIT/WHOI Joint Program in Oceanography• To my family for their love and support
Funding Acknowledgement
• NASA Global Change Fellowship
Scavenging/Desorption Case
• Thorium, a metal with similar properties to Fe, is known to desorb from particles (Bacon and Anderson, 1982).
• Perhaps Fe is also involved in this process.
Scav/Desorption Results
Scav. Rate (yr-1)
k b y
r-1)
Atlantic
S. Ocean
Indo-Pac
Observations: Iron
Compiled from literature, unpub. results from E. Boyle
Surface
1000m
Below 2500m
GCM Simulations
• In the context of the more sophisticated physical description of the MITGCM, net scavenging and desorption case are not adequate to describe the iron cycle
• Complexation case agrees well with measurements below the surface– explains role of transport and scavenging in
decoupling Fe and PO4
Iron Observations: Surface
Compiled from literature and Boyle (unpub.)
Iron Observations: At depth
1000m
Z> 2500m
Compiled from literature, Boyle (unpub.)
Net Scavenging Case
• Simplest Description• Net scavenging term (K_sc) is the sum of the
various geochemical processes Fe is involved in• Biological export is Fe, light limited
Results: Scavenging Case
• For 0.004 < knetsc < 0.006, observed gradients are produced• Description does not resolve various biogeochemical processes
Iron Biogeochemistry
Figure courtesy of B. Bergquist
Comparison of observed and modeled profiles
Atlantic:10°N, 45°WPacific: 3°S, 140°W
Boyle et al. (unpub.)Johnson et al. (1997)