1. IOP Algorithm Workshop @ Ocean Optics XIX, 7 Oct 2008, PJW NASA/SSAI IOP Algorithm Workshop @ OOXIX Jeremy Werdell NASA Ocean Biology Processing Group 7 Oct 2008

2. IOP Algorithm Workshop @ Ocean Optics XIX, 7 Oct 2008, PJW NASA/SSAI attendees: Antoine Mangin (ACRI)Odile Hembise Fanton d’Andon (ACRI) Bryan Franz (NASA)Paula Bontempi (NASA) Catherine Brown (LOV)Samantha Lavender (U. Plymouth) Emmanuel Boss (U. Maine)Sean Bailey (NASA) Gene Feldman (NASA)Stephane Maritorena (UCSB) Hubert Loisel (U. Littoral)Takafumi Hirata (PML) Jeremy Werdell (NASA)Tim Moore (NURC) Jill Schwarz (NIWA)Tim Smyth (PML) Mark Dowell (JRC)Vittorio Brando (CSIRO) Mike Behrenfeld (OSU)Yannick Huot (LOV) ZhongPing Lee (MSU) unable to attend:Andre Morel (LOV), Paul Lyon (NRL)

3. IOP Algorithm Workshop @ Ocean Optics XIX, 7 Oct 2008, PJW NASA/SSAI SAA = semi-analytical algorithm what we attempted to do: extend the IOCCG SAA survey by (1)evaluating application of SAA algorithms to satellite radiometry (2)reviewing & consolidating SAA construction workshop motivation & goal: achieve community consensus on an effective algorithmic approach for producing global-scale, remotely sensed SAA IOP products desirable features: combination of accuracy and geographic coverage flexible, multi-sensor implementation computational efficiency to support operational environment open source software and accompanying LUTs associated SAA uncertainties algorithm “shoot out”

4. IOP Algorithm Workshop @ Ocean Optics XIX, 7 Oct 2008, PJW NASA/SSAI pre-workshop achievements (Mar - Sep) - dialog & discussion 1.air-sea transmission, Rrs  rrs(0 - ) 2.calculation of Rrs (bandpass correction, f/Q) 3.temperature & salinity dependence of aw & bbw 4.spectral data products to be considered (adg, bb, etc.) 5.evaluation metrics & SAA failure conditions 6.inversion methods & linearization issues 7.calculation of uncertainties 8.SAA product validation & sensitivity analyses 9.strategies to produce level-3 products http://oceancolor.gsfc.nasa.gov/forum/oceancolor/board_show.pl?bid=24

5. IOP Algorithm Workshop @ Ocean Optics XIX, 7 Oct 2008, PJW NASA/SSAI pre-workshop achievements (Mar - Sep) - analyses 1.in situ-to-in situ & satellite-to-in situ match-ups 2.global (level-3) comparisons 3.spatial coverage (level-2) comparisions 4.sensitivities to parameterization & noisy input 5.sensitivity to inversion method 6.level-2 vs. level-3 inversion http://oceancolor.gsfc.nasa.gov/MEETINGS/OOXIX/IOP/analyses.html

6. IOP Algorithm Workshop @ Ocean Optics XIX, 7 Oct 2008, PJW NASA/SSAI satellite provides R rs ( ) a ( ) and b b ( ) are desired products construction (& deconstruction) of an SAA … total a and b b are sums of coefficients for all components in seawater each coefficient expressed as product of magnitude and spectral shape

7. IOP Algorithm Workshop @ Ocean Optics XIX, 7 Oct 2008, PJW NASA/SSAI satellite provides R rs ( ) a ( ) and b b ( ) are desired products construction (& deconstruction) of an SAA … Spectral Optimization: * define shape functions for (e.g.) b bp ( ), a dg ( ), a ph ( ) * solution via L-M, matrix inversion, etc. * ex: RP95, HL96, GSM 1 Spectral Deconvolution: * partially define shape functions for b bp ( ), a dg ( ) * piece-wise solution: b bp ( ), then a( ), then a dg ( ) + a ph ( ) * ex: QAA, PML, NIWA 2 Bulk Inversion: * no predefined shapes * piece-wise solution: b bp ( ), then a( ), via (empirical) K d ( ) via RTE * ex: LS01 3 correlated uncorrelated

8. IOP Algorithm Workshop @ Ocean Optics XIX, 7 Oct 2008, PJW NASA/SSAI our STARTING point: * dynamic bbp retrieval * dynamic aph spectral model * IOP-based f/Q tables * Raman scattering * fluorescence * T/S dependence on aw & bbw * optical water class parameterization * uncertainties & propagation of error metrics defined to evaluate progress consensus to refine spectral optimization to initiate process … Spectral Optimization: * define shape functions for (e.g.) b bp ( ), a dg ( ), a ph ( ) * optimization via L-M

9. IOP Algorithm Workshop @ Ocean Optics XIX, 7 Oct 2008, PJW NASA/SSAI discussion of uncertainties & their calculation: Wang et al. 2005 GlobColour Lee et al. 2008 (OOXIX personal communication) uncertainties associated with: * input Rrs * models & shape functions

10. IOP Algorithm Workshop @ Ocean Optics XIX, 7 Oct 2008, PJW NASA/SSAI generalized IOP model (GIOP) in l2gen specify sensor wavelengths to fit –e.g., 412,443,490,510,555 –e.g., 412,490,555 select a ph form and set params –tabulated:, a p *( ) –gaussian: ,  select a dg form and set params – exponential: , S select b bp form and set params –power law: ,  –power law: ,  via Hoge & Lyon –power law: ,  via QAA select Rrs[0-] to bb/(a+bb) –quadratic: g1, g2 –f/Q: (tbd) specify inversion method –Levenburg-Marquart –Amoeba (downhill simplex) –Lower-Upper Decomposition –Singular-Value Decomposition specify output products –a ( ), a ph ( ), a dg ( ), b b ( ), b bp ( )  = any sensor wavelength(s) –C a (given a p * at  ) –  (dynamic model params) –internal flags

11. IOP Algorithm Workshop @ Ocean Optics XIX, 7 Oct 2008, PJW NASA/SSAI summary: 1.consensus was reached on the way forward 2.NASA will implement the GIOP w/i next 3-6 months & begin producing global time-series of IOPs for all missions for which we’re responsible 3.the group will continue our dialog, review results of data processing, & make recommendations for improvements 4.NASA will reintroduce refinements & reprocess the data 5.once we have agreement that products are as good as (currently) possible, full mission reprocessing(s) will be initiated 6.all code will be available via SeaDAS 7.NASA will implement code for optical water class mapping & evaluate how to implement this with class-based SAA parameterization

12. IOP Algorithm Workshop @ Ocean Optics XIX, 7 Oct 2008, PJW NASA/SSAI http://oceancolor.gsfc.nasa.gov/MEETINGS/OOXIX/IOP http://oceancolor.gsfc.nasa.gov/forum/oceancolor/forum_show.pl