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Influence of land - ocean exchange on carbonate mineral saturation state Joe Salisbury, Mark Green, Doug Vandemark, Chris Hunt, Dwight Gledhill, Wade McGillis,

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Presentation on theme: "Influence of land - ocean exchange on carbonate mineral saturation state Joe Salisbury, Mark Green, Doug Vandemark, Chris Hunt, Dwight Gledhill, Wade McGillis,"— Presentation transcript:

1 Influence of land - ocean exchange on carbonate mineral saturation state
Joe Salisbury, Mark Green, Doug Vandemark, Chris Hunt, Dwight Gledhill, Wade McGillis, Chris Sabine 1

2 Outline Comments on variability of  in coastal regions and potential errors in its estimation. Preliminary results: Understanding  variability in the Amazon Plume with the help of satellite data 2

3 Terrestrial influence on  in coastal regions
via endmember mixing of alkalinity, Ca++, DIC affects in-plume DIC dynamics via subsidies of freshwater, OC, nutrients, buoyancy To the extent that land interactions influence net community productivity…. 3

4  [Ca++] [CO3--] Ksp*
Background: Carbonate mineral saturation state (): [Ca++] [CO3--]  Ksp* Need to know the solubility (Mucci), concentration of Ca (salinity) and CO3 (from 2 carbonate parameters) 4

5 Background: Total alkalinity (AT):
Carbonate alkalinity TA = [HCO3-] + 2[CO32-] + [B(OH)4-] + [OH-] + other NCA To estimate carbonate concentration we need 2 carbonate parameters. One is often carbonate alkalinity, but we typically have total alkalinity which is: One such carbonate parameter is TA, which is Note DIC dynamics and saturation state should be related. As more CO2 enters the water, the equilibrium is shifted 5

6 Non-carbonate fraction of riverine total alkalinity
(New England and the Canadian Maritimes) C. Hunt, J. Salisbury, D. Vandemark (in revision) Contributions of organic alkalinity from watersheds may also confound omega estimates in coastal waters.

7 Median USGS Stream data since 2000

8 Suggested variability in the land endmember
Show the spatial variability of in stream concentrations of constituents that would affect the estimate of omega. with the idea that high concentrations will express themselves as high fluxes through the watershed and to the coast Median USGS Stream data since 2000

9 Median USGS Stream data since 2000

10 Median USGS Stream data since 2000

11 Main Points: --Riverine constituents that affect W in coastal waters are likely to have considerable spatial variability. --Caution advised when using TA as a carbonate parameter for the estimation of W near the coast.

12 Part 2. New work on W dynamics in the Amazon Plume
Satellite-aided tracking of fCO2, TA and Ca++ Ocean color POC & PIC NIR & microwave SST  Microwave SSS

13 Hot new topic: Salinity from space !!!
Microwave C band. The great Kahuna of all land-ocean interaction sites: We can presumable track a lot of information relevant to the retrieval of omega if we know the salinity.

14 Endmembers: We mixed DIC and TA across AMSR-E salinity space.
0 psu was fixed median watershed TA and pH Stallard and Edmond (1983) pH and Ca++ from the GEMS-Glori dataset. 35psu allowed to vary using Takahashi monthly climatology of pCO2 (median of all values psu) and TA from Lee et al, 2006 Omega_ar variability in the Amazon Plume from mixing of TA, Ca++ and TCO2

15 Modified from Zhai, et al., 2008
Tracking the biological perturbation of CO2 with ocean color satellite data Biomass accumulation rate Carbon to chlorophyll ratio Biomass loss rate Net change from mixing Net change in PIC But of course omega is modulated by net community productivity via net uptake of DIC and PIC. Modified from Zhai, et al., 2008

16 Mixing (TA, Ca++, pCO2) Mixing with modeled net DIC uptake Omega_ar variability from mixing (left) and combine mixing and biology (right)

17 Some conclusions 1. The use of TA as a carbonate parameter may cause overestimates in omega in coastal regions 2. Productive coastal ecosystems are subjected to variability from net community production and land. We rarely account for biological processes 3. Satellites may provide crucial datasets for unraveling these issues 17

18 Acknowledgments 18

19 The contribution of Borate alkalinity may be important at the mouths of high alkalinity systems. And NCA may be important at the mouths of acidic rivers

20 Global discharge and eutrophication patterns are changing rapidly
Most discharge is acidic relative to the receiving ocean Most aquaculture and shellfish harvest within 3km coast and most fisheries on continental shelves Arctic ecosystems may be at a threshold (cold and high discharge) Global annual discharge can cover continental shelves >1meter deep 20

21  [Ca++] [CO3--] Ksp
Background: Calcite mineral saturation state (): Ca++ and CO3-- : calcifying organisms need these [Ca++] [CO3--]  Ksp Solubility a function of temperature and “salinity” Need to know the solubility (Mucci), concentration of Ca (salinity) and CO3 (from 2 carbonate parameters) Ω is a measure of the product of the concentrations of CO32- and Ca2+ ions relative to the amount of aragonite that can be dissolved at a given temperature, salinity and pressure. 21

22 - Climatology of pCO2 (Takahashi et al, 2007)
Climatology of SST in plume (NODC) TA from salinity and SST (Lee et al., 2006) Ca++ from Riley and Tongudai. 1967 USGS median TA and pH and Ca++ values from downstream stations Plume SST from NODC The contribution of Borate alkalinity may be important at the mouths of high alkalinity systems. And NCA may be important at the mouths of acidic rivers


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