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Bermuda Bio-Optics Project

Bermuda Bio-Optics Project. Norm Nelson, Dave Siegel Institute for Computational Earth System Science, UCSB. Decade-Plus Perspective on Ocean Color. Bermuda Bio-Optics Project. Overview Science Goals Data Streams Accomplishments A Look at the Time Series.

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Bermuda Bio-Optics Project

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  1. Bermuda Bio-Optics Project Norm Nelson, Dave Siegel Institute for Computational Earth System Science, UCSB Decade-Plus Perspective on Ocean Color

  2. Bermuda Bio-Optics Project • OverviewScience GoalsData StreamsAccomplishments • A Look at the Time Series

  3. Bermuda Bio-Optics ProjectOverview - Main Science Goals • Understand processes controlling underwater light environment in the Sargasso Sea • Algorithm development(With Stéphane Maritorena) • Calibration and validation of ocean color sensors

  4. Bermuda Bio-Optics ProjectOverview - Main Science Achievements • Light, primary productivity, and photosynthetic quantum yield • Distribution and dynamics of CDOM(Sargasso Sea and global) • Photochemistry and DMS cycling

  5. Bermuda Bio-Optics ProjectOverview - Data Streams • Time-series co-located with BATS(32N 64W), starting in 1991Also - frequent regional studies • Core Measurements:Ed, Es, Lu(7-14l, BSI & Satlantic radiometers)[chl a] (fluorometric)Since 1994:ap,ad(QFT)acdom(conventional UV-Vis spectroscopy)

  6. Bermuda Bio-Optics ProjectOverview - Data Streams • Concurrent data from the BATS ProjectHydrographyCarbon (inorganic, organic)NutrientsPrimary ProductionC and N flux (sediment traps)Phytoplankton pigments (HPLC) • Other BBOP data (not full time-series)AC-9 absorption coefficient profilesLw(0+), ASD FieldSpec radiometerLsun, Microtops sunphotometer

  7. Bermuda Bio-Optics ProjectOverview - Data Streams • Radiometer calibration: in house, using NIST-traceable standards, participated in SeaWiFS and SIMBIOS intercomparisons: Same engineer for entire project (Dave Menzies)

  8. Bermuda Bio-Optics ProjectRadiometry – 14 year time series 441 nm (MER) 441 nm (MER) 443 nm (SPMR)

  9. Bermuda Bio-Optics ProjectAbsorption Coefficient – 10 Year Time Series • Absorption Coefficient ComponentsCDOMPhytoplanktonDetritusPhytoplankton absorption ratios (440/674nm) • Are there interannual or longer term trends in addition to already-documented seasonal patterns?

  10. BATS CDOM Profile STMW Surface Bleached Layer STMW (18° Water) Main Thermocline

  11. CDOM exhibits seasonal and interannual variability Possible teleconnection to climate oscillators (NAO shown)

  12. Control of CDOM at BATS • Annual: Balance between local production and solar bleaching • Interannual: Multi-year accumulation at depth and ‘resetting’ by deeper winter mixing (similar to DOC patterns)

  13. Absorption by Phytoplankton • Phytoplankton pigments dominate absorption (detrital contribution small, correlated with phytoplankton) • Strong seasonal cycle related to spring bloom • Seasonal change in absorption properties related to photoadaptation and seasonal succession of phytoplankton species • Primary production variability has been linked to climate oscillators such as ENSO

  14. Particle Absorption

  15. Trends in Absorbing Components at BATS • CDOM abundance governed in part by physical processes possibly teleconnected to climate oscillators • Phytoplankton abundance and species succession has not varied along the same time scales

  16. Conclusions (so far) • The BBOP time series is enabling us to observe and diagnose ocean color variations occurring on climate-oscillator time scales. • CDOM abundance apparently responds on these time scales • So far we are not seeing this in a dramatic way with the phytoplankton community

  17. Acknowledgments • Ocean Biology and Biogeochemistry Program, NASA • Collaborators I’ve not mentioned (there are many, thank you) • BBOP and BATS Project technicians, engineers, and students over the years (I could fill several slides)

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