Sensing primary production from ocean color: Puzzle pieces and their status ZhongPing Lee University of Massachusetts Boston

An effort started half century ago … ~15 Gt/year From over 7000 measurements Global PP:

Longhurst et al (1995): Gt C year -1 Antoine et al (1996): Gt C year -1 Behrenfeld and Falkowski (1997): 43.5 Gt C year -1 ~3 times higher than estimates in the 50-60s’!

(Behrenfeld et al 2005) Large spatial differences from different sensing models

Puzzle pieces to sense PP in the ocean (Platt and Sathyendranath, 2007) 3. Phytoplankton index 2. Light at depth 4. Energy conversion (spectral attenuation) (nutrient) 1. Input energy

(Frouin et al 1989, 2003) PAR (Photosynthetic Available Radiation)

Spectral irradiance (Gregg and Carder 1990)

Q: How to get K d (λ) of varying water bodies? 2. Light at depth (spectral attenuation)

R rs Method 1: empirical R rs (λ 1 )/R rs (λ 2 ) Algorithms to get K d Current operational standard R rs [Chl] Method 2: empirical R rs (λ 1 )/R rs (λ 2 ) KdKd KdKd R rs a&bba&bb Method 3: semi-analytical KdKd (QAA)

(b: Method 2)(a: Method 1) (c: Method 3) (Lee et al. 2005) Oceanic & Coastal waters

Wavelength [nm] Spectral K d [m -1 ] IOPs-K d (490) [m -1 ] Profile K d (490) [m -1 ] The NOMAD set (1243 data points) Kd through IOPs

Profile-K d (490) [m -1 ] Ratio-derived K d (490) [m -1 ] IOP-based K d (490) [m -1 ] Profile-K d (490) [m -1 ] Different sun angles: Empirical ratioThrough IOPs How K d in the UVA/UVB varies globally? Challenges: Spectral Kd can be well derived based on physics!

(Behrenfeld and Falkowski, 1997) VGPM: Chl became the index!! 3. Phytoplankton index

Essence of Rrs-ratio derived Chl product: Simple ratio actually involves more than one variable!

(Szeto et al 2011, JGR) Simple ratio dismissed spatial/temporal variation!

Nature of ratio-derived “Chl” At the center of South Pacific Gyre May 2009, Global, MODIS Ratio-derived “Chl” is re-scaled total absorption coefficient! Rrs-ratio derived Chl [mg/m 3 ] Analytically derived a (443) [m -1 ] Rrs-ratio derived Chl [mg/m 3 ] Analytically derived a (443) [m -1 ]

(Behrenfeld and Falkowski 1997) 4. Energy conversion

(Platt et al, RSE, 2008) Variation of phytoplankton- (or chlorophyll-) specific absorption coefficient (a* ph ) contributes largely to the variation of P B opt.

Centered on Chl Centered on absorption Both P B opt and Chl have a* ph associated Increase uncertainty in PP No engagement of a* ph “Site-specific and previously published global models of primary production both perform poorly and account for less than 40% of the variance in ʃPP,” (Siegel et al 2001) “significant improvements in estimating oceanic primary production will not be forthcoming without considerable advance in our ability to predict temporal and spatial variability in P B opt ”. ( Behrenfeld and Falkowski 1997) Chl is NOT the direction to go.

PP estimation based on phytoplankton absorption ( a ph ): Ocean color a ph PP Phytoplankton index Quantum yield for photosynthesis Remotely sensible

(Marra et al 2007, Deep Sea Res.) R 2 = 0.84 R 2 = 0.78

R rs ( ) η (± Δη) U1U1 U2U2 U3U3 U4U4 (Lee et al. Appl. Opt., 2002) The Quasi-analytical algorithm (QAA)

a ph (λ) (m -1 ) (Lee et al 2004) Measured vs sensed a ph

(Lee et al. 1996) (Lee et al. 2010) Absorption-based PP compared with measured PP

Where is the global model for φ? Challenges: Which ‘ground truth’ we remote-sensors should aim at?

Summary: 1. A frame work for sensing primary production is well established. 2. Optical/light related parameters can now be well retrieved from satellite measurements, at least for oceanic waters. 3. Demands support and hard work to understand and quantify photo-physiological effects. 4. Demands true “ground truth”!

Questions?