# Presentation: 632613

## IOP Algorithm Workshop  @  OOXIX

- Jeremy Werdell
- NASA Ocean Biology Processing Group
- 7 Oct 2008

## 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)

## SAA = semi-analytical algorithm

- what we attempted to do:
- extend the IOCCG SAA survey by
- evaluating application of SAA algorithms to satellite radiometry
- 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

**Notes:**
Needed for our own operational processing purposes; hoped that other int’l agencies would find use; use collaboration(s) to develop consistency amongst various space agencies

## pre-workshop achievements (Mar - Sep) - dialog & discussion

- air-sea transmission, Rrs  rrs(0-)
- calculation of Rrs (bandpass correction, f/Q)
- temperature & salinity dependence of aw & bbw
- spectral data products to be considered (adg, bb, etc.)
- evaluation metrics & SAA failure conditions
- inversion methods & linearization issues
- calculation of uncertainties
- SAA product validation & sensitivity analyses
- strategies to produce level-3 products
- http://oceancolor.gsfc.nasa.gov/forum/oceancolor/board_show.pl?bid=24

## pre-workshop achievements (Mar - Sep) - analyses

- in situ-to-in situ & satellite-to-in situ match-ups
- global (level-3) comparisons
- spatial coverage (level-2) comparisions
- sensitivities to parameterization & noisy input
- sensitivity to inversion method
- level-2 vs. level-3 inversion
- http://oceancolor.gsfc.nasa.gov/MEETINGS/OOXIX/IOP/analyses.html

## construction (& deconstruction) of an SAA ...

*a *() and *b**b *() are desired products

## construction (& deconstruction) of an SAA ...

*a *() and *b**b *() are desired products

## consensus to refine spectral optimization to initiate process ...

- * 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

- Spectral Optimization:
- * define shape functions for (e.g.) bbp(), adg(), aph()
- * optimization via L-M

## 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

## generalized IOP model (GIOP) in l2gen 

-  specify sensor wavelengths to fit
- e.g., 412,443,490,510,555
- e.g., 412,490,555
-  select aph form and set params
- tabulated:  , ap*()
- gaussian: , 
-  select adg form and set params
-  exponential: , S
-  select bbp 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 (), aph (), adg (), bb (), bbp ()
- = any sensor wavelength(s)
- C*a **(*given ap* at )
-  (dynamic model params)
- internal flags

## summary:

- consensus was reached on the way forward
- 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
- the group will continue our dialog, review results of data processing, & make recommendations for improvements
- NASA will reintroduce refinements & reprocess the data
- once we have agreement that products are as good as (currently) possible, full mission reprocessing(s) will be initiated
- all code will be available via SeaDAS
- NASA will implement code for optical water class mapping & evaluate how to implement this with class-based SAA parameterization

## http://oceancolor.gsfc.nasa.gov/MEETINGS/OOXIX/IOP

- http://oceancolor.gsfc.nasa.gov/forum/oceancolor/forum_show.pl