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Projects Mapping the DOC on the Eastern US coast

This project aims to map the distribution and variability of dissolved organic carbon (DOC) and estimate the photochemical production of carbon dioxide (CO2) on the Eastern US coast using satellite ocean color measurements. The study focuses on the impact of tropical rivers on carbon and nitrogen cycles in marine ecosystems and primary productivity.

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Projects Mapping the DOC on the Eastern US coast

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  1. PeopleAjit Subrmaniam (PI) (1-2)Rossana Del Vecchio (Co-PI) (1-2)Jim Nelson (Co-PI) (1)Douglas Capone (Co-PI) (2) Projects Mapping the DOC on the Eastern US coast Tropical Rivers impact on C and N cycles (marine ecosystems/primary productivity)

  2. Can the photochemical oxidation of carbon to CO2 on continental shelves be estimated from satellite ocean color measurements? Rossana Del Vecchio*, Neil V. Blough+, Stephanie Uz#, Joaquim Ballabrera*, Christopher W. Brown#, Ajit Subramaniam± *Earth System Science Interdisciplinary Center (ESSIC), University of Maryland, College Park, USA +Departement of Chemistry, University of Maryland, College Park, USA #National Oceanic and Atmospheric Administration (NOAA), USA ± Lamont Doherty Earth Observatory, Palisades, USA

  3. Introduction • Large amounts of carbon as dissolved organic carbon (DOC) are annually transferred from continents to the ocean through rivers. • DOC in the ocean can play a very important role in the global carbon cycle, being comparable to carbon in the atmosphere. • Yet, the spatial distribution and variability of carbon sources and sinks at regional to global scales is far from being precisely quantified.

  4. Background • In coastal environments influenced by riverine discharge, a significant fraction of DOC [the CDOM] is capable of absorbing visible and ultraviolet light and hence can be detected by ocean color satellite sensors. • However, the aCDOM to DOC ratio is highly variable spatially and seasonally ……… (ie sources and sinks of CDOM and DOC are uncoupled)……… complicating the DOC remote detection (Del Vecchio and Blough, 2004, Marine Chemistry)

  5. Background • During summertime stratification significant photochemical loss of CDOM absorption occurs in surface waters of the Middle Atlantic Bight (MAB) (Del Vecchio and Blough, 2004, Marine Chemistry)……… ………that is uncoupled to DOC photochemical loss.

  6. Scientific questions Is this seasonal change in CDOM absorption evident from ocean color measurements? • Knowing that the photochemical loss of CDOM absorption (~100%) is coupled to a photochemical oxidation of carbon to CO2 (~ 15%), can the photochemical oxidation of carbon to CO2 on continental shelves be estimated from satellite ocean color measurements?

  7. Methods • Employ the Johannessen et al. algorithm (2003) to convert L3 images of monthly averaged normalized water leaving radiance (nLw(l)) to aCDOM(l) images from 1997 to 2003 • Estimate the spatial/temporal CDOM absorption deficits (Da) caused by photobleaching ……… [Da=(aCDOMmonth-aCDOMref)/aCDOMref] • Convert Da to estimates of photochemical production of carbon to CO2 CO2 photoproduction = ∫ (aCDOMref-aCDOMmonth) * M where M = mld * 0.15 / a*CDOM (g of C/m2/integrated…...)

  8. Algorithm validation • In situ vs modeled aCDOM(323) (weekly average) March 2003 July 1998 September 1998 October 1999

  9. Algorithm validation • In situ vs modeled aCDOM(323) (monthly average) March 2003 July 1998 September 1998 October 1999

  10. Algorithm product: aCDOM(323)-1998 January February March April May June July August September October November December

  11. Algorithm product: aCDOM(323)-1999 January February March April May June July August September October November December

  12. Algorithm product: aCDOM(323)-2000 January February March April May June July August September October November December

  13. Algorithm product: aCDOM(323)-2001 January February March April May June July August September October November December

  14. Algorithm product: aCDOM(323)-2002 January February March April May June July August September October November December

  15. Algorithm product: aCDOM(323)-2003 January February March April May June July August September October November December

  16. Da(323) for 1998: spatial and seasonal distributionDa(323)=(aCDOMmonth-aCDOMref)/aCDOMref January February March April May June July August September October November December

  17. Da(323) for 1999: spatial and seasonal distributionDa(323)=(aCDOMmonth-aCDOMref)/aCDOMref January February March April May June July August September October November December

  18. Da(323) for 2000: spatial and seasonal distributionDa(323)=(aCDOMmonth-aCDOMref)/aCDOMref January February March April May June July August September October November December

  19. Da(323) for 2001: spatial and seasonal distributionDa(323)=(aCDOMmonth-aCDOMref)/aCDOMref January February March April May June July August September October November December

  20. Da(323) for 2002: spatial and seasonal distributionDa(323)=(aCDOMmonth-aCDOMref)/aCDOMref January February March April May June July August September October November December

  21. Da(323) for 2003: spatial and seasonal distributionDa(323)=(aCDOMmonth-aCDOMref)/aCDOMref January February March April May June July August September October November December

  22. CO2 photoproduction (g of C/m2/integrated…...) 1998: CO2 photoproduction = ∫ (aCDOMref-aCDOMmonth) * M January February March April May June July August September October November December

  23. CO2 photoproduction (g of C/m2/integrated…...) 1999: CO2 photoproduction = ∫ (aCDOMref-aCDOMmonth) * M January February March April May June July August September October November December

  24. CO2 photoproduction (g of C/m2/integrated…...) 2000: CO2 photoproduction = ∫ (aCDOMref-aCDOMmonth) * M January February March April May June July August September October November December

  25. CO2 photoproduction (g of C/m2/integrated…...) 2001: CO2 photoproduction = ∫ (aCDOMref-aCDOMmonth) * M January February March April May June July August September October November December

  26. CO2 photoproduction (g of C/m2/integrated…...) 2002: CO2 photoproduction = ∫ (aCDOMref-aCDOMmonth) * M January February March April May June July August September October November December

  27. CO2 photoproduction (g of C/m2/integrated…...) 2003: CO2 photoproduction = ∫ (aCDOMref-aCDOMmonth) * M January February March April May June July August September October November December

  28. Conclusions • The seasonal change in CDOM absorption attributable to photobleaching is evident in the ocean color measurements • Algorithm overestimates ‘off-summer’ months • CO2 photoproduction can be estimated from the absorption deficit observed in the ocean color measurements, but…… • Correct reference state • Hydrography • Advection of water masses with different end members • ……………………… Acknowledgements NASA, NSF, NOAA, ONR (past)

  29. Aknowledgement • NASA, NSF, NOAA

  30. Assumptions • Non-moving water masses • Constant Mixed Layer Depth • a*(355)=a*(323)

  31. MAB bathymetry

  32. DA(323) for 1998:spatial and seasonal distribution January February March April May June July August September October November December

  33. Photochemical C Flux for 1998(g of C/m2/month) January February March April May June July August September October November December

  34. Photochemical C Flux for 1999(g of C/m2/month) January February March April May June July August September October November December

  35. Photochemical C Flux for 2000(g of C/m2/month) January February March April May June July August September October November December

  36. Photochemical C Flux for 2001(g of C/m2/month) January February March April May June July August September October November December

  37. Photochemical C Flux for 2002(g of C/m2/month) January February March April May June July August September October November December

  38. Photochemical C Flux for 2003(g of C/m2/month) January February March April May June July August September October November December

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