Bermuda BioOptics Project DecadePlus Perspective on Ocean Color

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

Bermuda Bio-Optics Project n Overview Science Goals Data Streams Accomplishments n A Look at the Time Series

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

Bermuda Bio-Optics Project Overview - Main Science Achievements n n n Light, primary productivity, and photosynthetic quantum yield Distribution and dynamics of CDOM (Sargasso Sea and global) Photochemistry and DMS cycling

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

Bermuda Bio-Optics Project Overview - Data Streams n n Concurrent data from the BATS Project Hydrography Carbon (inorganic, organic) Nutrients Primary Production C and N flux (sediment traps) Phytoplankton pigments (HPLC) Other BBOP data (not full time-series) AC-9 absorption coefficient profiles Lw(0+), ASD Field. Spec radiometer Lsun, Microtops sunphotometer

Bermuda Bio-Optics Project Overview - Data Streams n Radiometer calibration: in house, using NIST-traceable standards, participated in Sea. Wi. FS and SIMBIOS intercomparisons: Same engineer for entire project (Dave Menzies)

Bermuda Bio-Optics Project Radiometry – 14 year time series 441 nm (MER) 443 nm (SPMR)

Bermuda Bio-Optics Project Absorption Coefficient – 10 Year Time Series n n Absorption Coefficient Components CDOM Phytoplankton Detritus Phytoplankton absorption ratios (440/674 nm) Are there interannual or longer term trends in addition to already-documented seasonal patterns?

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

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

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

Absorption by Phytoplankton n n 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

Particle Absorption

Trends in Absorbing Components at BATS n n 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

Conclusions (so far) n n n 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

Acknowledgments n n n 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)