Contrasting inherent optical properties and carbon metabolism in four northeastern (USA) estuary-plume systems

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Contrasting inherent optical properties and
carbon metabolism in four northeastern (USA)
estuary-plume systems D. Vandemark, NASA/GSFC
UNH J. Salisbury, C. Hunt, J. Campbell, Univ.
of New Hampshire W. McGillis, Columbia University
- LDEO
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• Program Goals
• Examine freshwater control upon Gulf of Maine
  coastal waters in terms of carbonate, nutrient,
  and productivity dynamics
• Develop techniques to retrieve metabolic
  information from inherent optical properties and
  eventually from satellite measurements

• This talk first observations
• Contrast amongst four river systems
• Empirically relate bio-optical metabolic terms
  using clustering analysis

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• Observational program
• UNH/COOA NOAA-sponsored (COTS)
• Flo-thru suite physical fluor. IOP
  metabolic (pCO2,O2) variables
• Discrete sampling and phys. IOP profiling
  along salinity gradient
• Four rivers sampled seasonally in Gulf of Maine
• Hudson river also sampled 7/1-7/2, 2004 (see
  McGillis)

2004 COOA Gulf of Maine measurement program
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COOA shipboard measurements
R/V Gulf Challenger majority of 2004 data set
Camden Belle -26 riverine sampling vessel
Profiler AC-9, AC-S, fl_CDOM,CHL,PEB, and CTD
Fast-rate CO2 equilibrator
Infrared CO2 gas analyzer
Flo-thru O2, fl_Chl, fl_CDOM, beam_c, T, S
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Four rivers in four days
- summer climatology
Acadia

• varied watersheds, 3 of GoMaines largest
  sources
• Sampled plumes -gt 0 psu, 27-30 July 2004

Boston
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Four rivers in four days
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Contrasts between rivers July 2004
CDOM surrogate for DOC
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Contrasts between rivers July 2004
Relatively high DIN loads
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Contrasts between rivers July 2004
120 110 100 90 80 70
Atm
BOUNDS Merrimac autotrophic Pleasant
strongly heterotrophic
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Study in progress

• Diverse watersheds conditions in optical,
  trophic, and gas flux terms
• Some consistency with modeled basin attributes
• Coming work - conservative mixing vs. localized
  processing along salinity gradient and vs. season
• including profile discrete data nutrients,
  TA, pH, DIC, DOC, DON, POC, HPLC

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Covariance between surface variables
Merrimac River
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Classification via clustering analysis - end
goal is to link satellite retrievals to ecosystem
metabolism
4 Observables T, fl_CDOM, fl_CHL, c660 i 1,n
Objective clustering n30000 (S lt 31 psu)
Metabolic indicator? O2 pCO2
Present result 22 classes
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Surface variables under study redtraining set
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Clustering results n22 (classes sorted by pCO2)