Control by the Iron Fist: Modeling Biogeochemical Cycling in the Equatorial Pacific
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Control by the Iron Fist: Modeling Biogeochemical Cycling in the Equatorial Pacific Figure 1: Gordon, Coale & Johnson 1997: Dissolved iron at 0, 140W with data from three cruises. Depth of EUC core varies temporally. The eastern equatorial Pacific is grazing- and iron-limited (Landry et al., 1997), but the supply of iron to this highly productive region is poorly constrained. Some evidence suggests a possible iron maximum in or just below the Equatorial Undercurrent (EUC) (Gordon et al., 1997). The biogeochemical model PISCES is applied to study the impact of candidate subsurface iron sources in the western equatorial Pacific. Iron in our simulations is rapidly scavenged from an eastward-moving plume, but exercises strong biogeochemical control on conditions in the eastern Pacific. EUC Model PISCES PO 4 3- Diatoms MicroZoo P.O.M D.O.M Si Iron Nano-phyto Meso Zoo NO 3 - NH 4 + Small Big Figure 2: Saved dynamical fields from the OPA general circulation model with climatlogical forcing were used to run the PISCES biogeochemical model. Model resolution is 0.5˚ meridional near Equator and 2˚ zonal. There are 31 vertical levels, with 12 in upper 120m OPA Abstract Figure 3: Western Equatorial Iron Perturbation 0 200 400 600 800 1000 1200 1400 1600 1800 2000 2200 0 1 2 3 4 5 6 7 8 TotalD issolvable Iron (nM )(<0.45um ) D ep th (m Mackey et al, 2002 control control Iron perturbation 270m 154°-158°E, 0.5°S-0.5°N Iron perturbation 180m Iron perturbation 180m Experiment Design Three biogeochemical model runs were conducted with different iron sources: a control run with model default iron sources and two runs with an elevated western source. The 270m source was fit to Mackey et al.’s total acid-soluble iron data with a maximum below the core of the Equatorial Undercurrent (EUC) and the 180m source was placed in the core of the model’s EUC with a magnitude equal to that of the 270m source. All experiments were run 20-30 years, sufficient time for tropical Pacific biogeochemical equilibrium. Lia Ossiander 1 ([email protected]), James Murray 1 , Thomas Gorgues 2 , Olivier Aumont 3 (1) School of Oceanography, University of Washington (2) Laboratoire d’Oceanographie et du Climat par Experimentation et Approche Numérique (3) Institut de Recherche pour le Développement 0.35 0.35 Fe (nM) Gordon et al. Fe (nM) 180m source Fe (nM) 270m source Fe (nM) control run Depth (m) Depth (m) Depth (m) Results Figure 5: Iron profiles at 140°W An iron “bulls-eye” is visible in the two source runs, similar to the maximum observed in dissolved iron by Gordon et al. The simulated maximum is greater, due in part to the inclusion of acid-soluble particulate iron data in the western iron source. The black lines denote isopycnal surfaces. The EUC is visible in the doming of isopycnals. Model iron travels eastward along isopycnals and reaches the mixed layer in the eastern Pacific, although it is rapidly scavenged enroute. positive anomaly negative anomaly Depth (m) Depth (m) Nanoplankton, control Diatom Biomass, control Longitude Longitude Longitude Diatoms, 270m source-control Nanoplankton, 270m source-control Longitude Figure 6: Zonal Ecosystem Response Nanoplankton and Diatom biomass (μg/L) in a vertical section along the Equator. The stimulation in primary productivity driven by the additional iron upwelling in the eastern Pacific is apparent in the anomaly plots on the right. Diatoms show an especially strong response with a three-fold increase in biomass. Diatoms are less vulnerable to grazing pressure. Nanoplankton experience a smaller net biomass increase, but also an altered vertical distribution due to light limitation. The PISCES model does not resolve the diurnal cycle. 270m Source Control Levitus 180 m 180 m control control 270 m 270 m Levitus Levitus Figure 7: High Nitrate Low Chlorophyll Shift Surface nitrate concentrations (μM) for the control, 270 m iron source, and Levitus show that the addition of a western iron source reduces the magnitude and extent of HNLC conditions. The bottom left figure plots surface nitrate at the Equator for each of three model runs and Levitus. The control run achieves the high surface nitrate observed in the eastern Pacific, but overestimates nitrate over most of the central equatorial Pacific. 180°W 135°W 5°N 5°S 90°W Equatorial Pacific Box Budget Figure 8: Two approaches to calculate export flux, Transport Budget (Toggweiler and Carson, 1995) and PISCES biogeochemical sources and sinks Biology Biology Scavenging Scavenging Remineralization Remineralization dFe/dt = Physics + Netbiogeochem Biology = -1*(primary production Fe uptake – excretion) Biology = -1*(primary production Fe uptake – excretion) + + zooplankton exudation zooplankton exudation Scavenging = 0.005d Scavenging = 0.005d -1 -1 *(POC *(POC s + POC + POC l + BSi)*(Fe-FeL) + BSi)*(Fe-FeL) Remineralization = 0.1d Remineralization = 0.1d -1 -1 *(0.25 + 0.75e *(0.25 + 0.75e -(z-zmel)/1000 -(z-zmel)/1000 )*pFe )*pFe s 0.6 180°W 134°W 90°W 21.5 0.9 6.2 9.1 3.7 15.2 5. 3 7.3 3.4 3.4 14.3 22.2 17.7 14.0 35.9 34.9 21.8 7.3 -20 2.2 3.3 0.8 4.0 2.7 1.1 -12.4 45m 95m 142m 217m (-5.5) (1.5) (3.2) (2.3) (-5.5) (0.7) (2.6) (-12.4) 6.0 6.9 0.5 2.5 1.0 1.9 (-2.8) (-2.6) 1.0 11.8 18.5 272m [NO3] increas e 0.6 180°W 134°W 90°W 4.8 0.2 0.7 0.8 0.3 2.3 0. 5 0.2 0.4 0.1 3.0 3.7 1.4 0.8 2.9 4.1 3.3 1.5 -3.1 -0.9 -0.6 0.1 -0.6 -0.6 -0.2 -0.7 45m 95m 142m 217m (-0.1) (0.1) (0.2) (0.0) (-1.1) (0.0) (0.0) (0.1) 1.1 1.4 0.2 -0.3 0.0 0.3 (-0.6) (-0.7) 0.0 3.0 3.4 272m [Fe] increas e Figure 9: Transport terms and net biogeochemical flux Scavenging (mol Fe*mm -2 s -1 ) Biology (mol Fe*mm -2 s -1 ) Remineralization (mol Fe*m -2 s -1 ) Control 180m Source note difference in scales for scavenging Figure 10: Concentrations of Nitrate and Iron on 25.5 kg*m -3 on a zonal profile along the Equator. Although the EUC provides the new nutrients to the east, nitrate concentrations of the eastward- flowing EUC water (represented by the 25.5 isopycnal) are relatively low (see red arrows in Figures 8 & 9) and are progressively enriched by respiration of organic material. The opposite trend is seen for iron, especially for the high initial iron concentrations in the 180m iron source run. Acknowledgemen ts Merci beaucoup to Billy Kessler (NOAA, PMEL) for tips and tricks with Ferret and knowledge of equatorial Pacific dynamics. Graphics and analysis were made with the Ferret data analysis and visualization software developed at NOAA PMEL (http://ferret.pmel.noaa.gov/Ferret/). Funding for this project was provided by the University of Washington Program on Climate Change The central (180°W:134°W, 5°S:5°N) and eastern (134°W:90°W, 5°S:5°N) equatorial Pacific are divided into five vertical boxes for analysis, similar to the approach used by Toggweiler and Carson (1995) for nitrate. The zonal and vertical advective and diffusive fluxes into each box are depicted by arrows with the magnitude of the transport magnitude of the transport written in yellow. Meridional transports are relatively small, and are shown in parentheses in the lower left of each box. The nutrient budgets are at steady state, and the pink numbers in the upper right corner of each box show the net biogeochemical loss or gain of each biogeochemical loss or gain of each nutrient nutrient, calculated by the net physical transport in or out of the box. Red arrows highlight those boxes for which the nutrient concentration nutrient concentration increases along an isopycnal surface in the direction of flow increases along an isopycnal surface in the direction of flow. Isopycnal surfaces (matched to the depth of the boxes at 134°W) were used because the concentrations of all nutrients increases towards the east along a constant depth due to the eastward shoaling of the thermocline. Nitrate increases zonally, whereas iron does not (refer to Fig. 10). In the 180 m source run, the zonal transport of iron occurs shallower, due to the iron maximum directly in the core of EUC. Unlike in the control run, there is a net remineralization of iron in some of the shallower boxes. In contrast, nitrate is regenerated in all of the boxes below the euphotic zone in both the control and 180 m source run. Nitrate Control Run (10 4 mol/s) Iron Control Run (mol/s) References World Ocean Atlas 2001 CSIRO archive Figure 11: Iron biogeochemical source/sink terms along the Equator for the control and 180 m source run. The biogeochemical pathway of iron changes significantly between the control and 180 m source run, with the most dramatic shift in scavenging fluxes, which increase by more than an order of magnitude. Biological uptake is greatly increased near the surface in the source run, but decreases rapidly towards the base of euphotic zone and becomes a net positive source of iron by 140 m as a result of grazing-and bacterially-remediated remineralization. Remineralization from the small particulate iron pool exhibits a subsurface maximum just beneath the maximum biological uptake and also shows a corresponding increase in magnitude with the addition of a western iron source. Conclusions Data as to the distribution, sources, variability, and biogeochemical cycling of iron in the equatorial Pacific is quite sparse. In spite of (or because of?) this, modeling iron in the equatorial Pacific is a viable way to test the response of this productive ecosystem characterized by strong interannual variability. We’ve presented here the impact of hypothetical equatorial Pacific western-shelf iron sources within the PISCES biogeochemical model, and have shown: • A large western iron source can propagate across the Pacific basin, subject to large scavenging losses. • Iron availability exerts strong control on primary productivity and community structure. • The extent of HNLC conditions is regulated by iron. • Zonal transport in the EUC and upwelling are the primary nutrient pathways for new production in the eastern equatorial Pacific. • Nitrate is more efficiently recycled in the equatorial Pacific ecosystem than iron. • The fate of a western iron source is strongly dependent on scavenging rates. In the PISCES scavenging parameterization, iron scavenging is a dominant sink for the western source iron. 0.6 180°W 134°W 90°W 21.1 0.6 5.1 9.6 1.7 15.4 6. 4 3.7 3.3 0.44 12.5 19.7 14.2 5.3 27.5 31.4 18.7 4.6 -19.6 -1.1 2.7 1.2 4.9 3.5 -2.7 -7.5 45m 95m 142m 217m (-1.1) (0.2) (1.6) (1.5) (-5.1) (-0.3) (0.4) (-5.8) 4.7 6.5 0.1 0.9 0.9 2.0 (-2.6) (-2.9) 0.1 11.7 18.9 272m [NO3] increas e Nitrate 180 m Source Run (10 4 mol/s) 0.6 180°W 134°W 90°W 17.9 0.2 1.9 3.2 1.9 8.4 2. 5 1.9 0.3 5.0 12.2 7.3 5.2 12.9 13.1 7.7 1.7 -9.7 0.3 -0.4 0.2 -1.4 -1.9 0.0 -6.1 45m 95m 142m 217m (-0.7) (0.2) (0.2) (-0.5) (-2.2) (-0.7) (0.0) (-3.0) 1.5 1.4 0.3 0.1 0.5 0.6 (-0.8) (-1.4) 0.2 5.0 8.3 272m [Fe] increas e 4.7 Iron 180 m Source Run (mol/s) Gordon, R. M., Coale, K.H., and Johnson, K.S. (1997) Iron distributions in the equatorial Pacific: Implications for new production. Limnology and Oceanography 42(3): 419-431 Landry et al. (1997) Iron and grazing constraints on primary production in the central equatorial Pacific: An EqPac synthesis. Limnology and Oceanography 42(3): 405-418. Mackey, D.J., O’Sullivan, J.E., and Watson, R.J. (2002) Iron in the western Pacific: a riverine or hydrothermal source for iron in the Equatorial Undercurrent? Deep-Sea Research I 49:877-893 Toggweiler, J.R. and Carson, S. (1995) What are Upwelling Systems Figure 4: August 2006 planned cruise track Graduate Climate Conference April 7-9, 2006 We will measure dissolved iron concentrations along a series of meridional transects aligned with the TOGA-TAO array and collect a suite of physical, biological, and chemical measurements. Model experiments help define sampling targets. Field data will be used to
description
Control by the Iron Fist: Modeling Biogeochemical Cycling in the Equatorial Pacific. -12.4. -7.5. -6.1. -0.7. -19.6. -3.1. -9.7. -20. 3.7. 0.3. 1.9. 1.7. 0.44. 0.3. 0.1. 3.4. 3.7. 7.3. 0.2. 1.9. PISCES. (-0.1). (-5.5). (-0.7). (-1.1). 5.3. 14.0. 0.8. 5.2. (-5.8). - PowerPoint PPT Presentation
Transcript of Control by the Iron Fist: Modeling Biogeochemical Cycling in the Equatorial Pacific
Control by the Iron Fist: Modeling Biogeochemical Cycling in the Equatorial Pacific
Figure 1: Gordon, Coale & Johnson 1997: Dissolved iron at 0, 140W with data from three cruises. Depth of EUC core varies temporally.
The eastern equatorial Pacific is grazing- and iron-limited (Landry et al., 1997), but the supply of iron to this highly productive region is poorly constrained. Some evidence suggests a possible iron maximum in or just below the Equatorial Undercurrent (EUC) (Gordon et al., 1997). The biogeochemical model PISCES is applied to study the impact of candidate subsurface iron sources in the western equatorial Pacific. Iron in our simulations is rapidly scavenged from an eastward-moving plume, but exercises strong biogeochemical control on conditions in the eastern Pacific.
EUC
ModelPISCES
PO43-
Diatoms
MicroZoo
P.O.M
D.O.M
Si
IronNano-phyto
Meso Zoo
NO3-
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Small BigFigure 2: Saved dynamical fields from the OPA general circulation model with climatlogical forcing were used to run the PISCES biogeochemical model. Model resolution is 0.5˚ meridional near Equator and 2˚ zonal. There are 31 vertical levels, with 12 in upper 120m
OPA
Abstract
Figure 3: Western Equatorial Iron Perturbation
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Iron perturbation 180mIron perturbation 180m
Experiment Design
Three biogeochemical model runs were conducted with different iron sources: a control run with model default iron sources and two runs with an elevated western source. The 270m source was fit to Mackey et al.’s total acid-soluble iron data with a maximum below the core of the Equatorial Undercurrent (EUC) and the 180m source was placed in the core of the model’s EUC with a magnitude equal to that of the 270m source. All experiments were run 20-30 years, sufficient time for tropical Pacific biogeochemical equilibrium.
Lia Ossiander1 ([email protected]), James Murray1, Thomas Gorgues2, Olivier Aumont3
(1) School of Oceanography, University of Washington (2) Laboratoire d’Oceanographie et du Climat par
Experimentation et Approche Numérique (3) Institut de Recherche pour le Développement
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Fe (nM) 270m sourceFe (nM) control run
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Figure 5: Iron profiles at 140°W
An iron “bulls-eye” is visible in the two source runs, similar to the maximum observed in dissolved iron by Gordon et al. The simulated maximum is greater, due in part to the inclusion of acid-soluble particulate iron data in the western iron source. The black lines denote isopycnal surfaces. The EUC is visible in the doming of isopycnals. Model iron travels eastward along isopycnals and reaches the mixed layer in the eastern Pacific, although it is rapidly scavenged enroute.
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Longitude LongitudeDiatoms, 270m source-control
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Figure 6: Zonal Ecosystem ResponseNanoplankton and Diatom biomass (μg/L) in a vertical section along the Equator. The stimulation in primary productivity driven by the additional iron upwelling in the eastern Pacific is apparent in the anomaly plots on the right. Diatoms show an especially strong response with a three-fold increase in biomass. Diatoms are less vulnerable to grazing pressure. Nanoplankton experience a smaller net biomass increase, but also an altered vertical distribution due to light limitation. The PISCES model does not resolve the diurnal cycle.
270m SourceControl
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180 m180 m
controlcontrol 270 m270 m
LevitusLevitus
Figure 7: High Nitrate Low Chlorophyll Shift
Surface nitrate concentrations (μM) for the control, 270 m iron source, and Levitus show that the addition of a western iron source reduces the magnitude and extent of HNLC conditions. The bottom left figure plots surface nitrate at the Equator for each of three model runs and Levitus. The control run achieves the high surface nitrate observed in the eastern Pacific, but overestimates nitrate over most of the central equatorial Pacific. The iron perturbations were upper-bound estimates for the magnitude of a western dissolved-iron source.
180°W 135°W
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Equatorial Pacific Box BudgetFigure 8: Two approaches to calculate export flux, Transport Budget (Toggweiler and Carson, 1995) and PISCES biogeochemical sources and sinks
BiologyBiology
ScavengingScavenging
RemineralizationRemineralization
dFe/dt = Physics + Netbiogeochem
Biology = -1*(primary production Fe uptake – excretion)Biology = -1*(primary production Fe uptake – excretion) + zooplankton exudation + zooplankton exudationScavenging = 0.005dScavenging = 0.005d-1-1*(POC*(POCss + POC + POCll + BSi)*(Fe-FeL) + BSi)*(Fe-FeL)
Remineralization = 0.1dRemineralization = 0.1d-1-1*(0.25 + 0.75e *(0.25 + 0.75e -(z-zmel)/1000-(z-zmel)/1000)*pFe)*pFess
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Figure 9: Transport terms and net biogeochemical flux
Scavenging(mol Fe*mm-2s-1)
Biology(mol Fe*mm-2s-1)
Remineralization(mol Fe*m-2s-1)
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note difference in scales for scavenging
Figure 10: Concentrations of Nitrate and Iron on 25.5 kg*m-3 on a zonal profile along the Equator.
Although the EUC provides the new nutrients to the east, nitrate concentrations of the eastward-flowing EUC water (represented by the 25.5 isopycnal) are relatively low (see red arrows in Figures 8 & 9) and are progressively enriched by respiration of organic material. The opposite trend is seen for iron, especially for the high initial iron concentrations in the 180m iron source run.
AcknowledgementsMerci beaucoup to Billy Kessler (NOAA, PMEL) for tips and tricks with Ferret and knowledge of equatorial Pacific dynamics.Graphics and analysis were made with the Ferret data analysis and visualization software developed at NOAA PMEL (http://ferret.pmel.noaa.gov/Ferret/).Funding for this project was provided by the University of Washington Program on Climate Change and the National Science Foundation grant OCE-0425721.
The central (180°W:134°W, 5°S:5°N) and eastern (134°W:90°W, 5°S:5°N) equatorial Pacific are divided into five vertical boxes for analysis, similar to the approach used by Toggweiler and Carson (1995) for nitrate. The zonal and vertical advective and diffusive fluxes into each box are depicted by arrows with the magnitude of the transportmagnitude of the transport written in yellow. Meridional transports are relatively small, and are shown in parentheses in the lower left of each box. The nutrient budgets are at steady state, and the pink numbers in the upper right corner of each box show the net biogeochemical loss or gain of each nutrientbiogeochemical loss or gain of each nutrient, calculated by the net physical transport in or out of the box. Red arrows highlight those boxes for which the nutrient nutrient concentration increases along an isopycnal surface in the direction of flowconcentration increases along an isopycnal surface in the direction of flow. Isopycnal surfaces (matched to the depth of the boxes at 134°W) were used because the concentrations of all nutrients increases towards the east along a constant depth due to the eastward shoaling of the thermocline. Nitrate increases zonally, whereas iron does not (refer to Fig. 10). In the 180 m source run, the zonal transport of iron occurs shallower, due to the iron maximum directly in the core of EUC. Unlike in the control run, there is a net remineralization of iron in some of the shallower boxes. In contrast, nitrate is regenerated in all of the boxes below the euphotic zone in both the control and 180 m source run.
Nitrate Control Run (104 mol/s) Iron Control Run (mol/s)
References
World Ocean Atlas 2001 CSIRO archive
Figure 11: Iron biogeochemical source/sink terms along the Equator for the control and 180 m source run.The biogeochemical pathway of iron changes significantly between the control and 180 m source run, with the most dramatic shift in scavenging fluxes, which increase by more than an order of magnitude. Biological uptake is greatly increased near the surface in the source run, but decreases rapidly towards the base of euphotic zone and becomes a net positive source of iron by 140 m as a result of grazing-and bacterially-remediated remineralization. Remineralization from the small particulate iron pool exhibits a subsurface maximum just beneath the maximum biological uptake and also shows a corresponding increase in magnitude with the addition of a western iron source.
ConclusionsData as to the distribution, sources, variability, and biogeochemical cycling of iron in the equatorial Pacific is quite sparse. In spite of (or because of?) this, modeling iron in the equatorial Pacific is a viable way to test the response of this productive ecosystem characterized by strong interannual variability. We’ve presented here the impact of hypothetical equatorial Pacific western-shelf iron sources within the PISCES biogeochemical model, and have shown:• A large western iron source can propagate across the Pacific basin, subject to large scavenging losses. • Iron availability exerts strong control on primary productivity and community structure.• The extent of HNLC conditions is regulated by iron.• Zonal transport in the EUC and upwelling are the primary nutrient pathways for new production in the eastern equatorial Pacific.• Nitrate is more efficiently recycled in the equatorial Pacific ecosystem than iron.• The fate of a western iron source is strongly dependent on scavenging rates. In the PISCES scavenging parameterization, iron scavenging is a dominant sink for the western source iron.
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Iron 180 m Source Run (mol/s)
Gordon, R. M., Coale, K.H., and Johnson, K.S. (1997) Iron distributions in the equatorial Pacific: Implications for new production. Limnology and Oceanography 42(3): 419-431
Landry et al. (1997) Iron and grazing constraints on primary production in the central equatorial Pacific: An EqPac synthesis. Limnology and Oceanography 42(3): 405-418.
Mackey, D.J., O’Sullivan, J.E., and Watson, R.J. (2002) Iron in the western Pacific: a riverine or hydrothermal source for iron in the Equatorial Undercurrent? Deep-Sea Research I 49:877-893
Toggweiler, J.R. and Carson, S. (1995) What are Upwelling Systems Contributing to the Ocean’s Carbon and Nutrient Budgets? Upwelling in the Ocean: Modern Processes and Ancient Records 337-360.
Figure 4: August 2006 planned cruise track
Graduate Climate ConferenceApril 7-9, 2006
We will measure dissolved iron concentrations along a series of meridional transects aligned with the TOGA-TAO array and collect a suite of physical, biological, and chemical measurements. Model experiments help define sampling targets. Field data will be used to better constrain model input.
