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Uncertainty Estimation for Hyperspectral LwN(λ) Using a Generalized Sea Model Trio

This study explores the estimation of uncertainty in hyperspectral LwN(λ) values derived from a Generalized Sea Model (GSM) trio: Chlorophyll (Chl), Colored Dissolved Organic Matter (CDM), and Backscattering Coefficient (BBP). The analysis calculates the ensemble of LwN(λ) values and their uncertainty bounds by sampling data from the ACE bandset. The model follows established frameworks and employs tuning based on global datasets, investigating further steps to reassess uncertainty goals, widen GSM triplet sets, and enhance inversion modeling for improved accuracy.

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Uncertainty Estimation for Hyperspectral LwN(λ) Using a Generalized Sea Model Trio

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  1. LwN() Uncertainty Estimation Using Hyperspectral GSM • Assume a GSM trio (Chl, CDM & BBP) and associate uncertainty level • Drive hyperspectral GSM forward to calculate ensemble of LwN() values • Calculate LwN() & its uncertainty bounds • Sample using the ACE bandset Siegel/Maritorena (UCSB)

  2. LwN() = f(Chl,CDM,BBP;) acdm() = CDM exp(-S (-440)) - S tuned to global LwN data set aph() = A() ChlB() - following Bricaud model but tuned to global LwN data set bbb() = BBP (440/) -  tuned to … aw() => Follows Morel’s clearest waters bbw() => Buiteveld 94 (S=36; T=12C) Fo() => Thuillier IOPs => Rrs() following Gordon et al 88 1 nm resolution

  3. aph() = A() ChlB() A() B() Wavelength (nm)

  4. Global Mean GSM Trio # realizations =100 - assumes 25% uncertainty in GSM trio

  5. NABE Bloom GSM Trio # realizations =100 - assumes 25% uncertainty in GSM trio

  6. Plumes & Blooms GSM Trio # realizations =100 - assumes 25% uncertaint7 in GSM trio

  7. Sampling of the ACE Bandset

  8. Next Steps? • Reassess uncertainty goals - we stated 25% for each GSM output (?) • Widen set of GSM triplets using field observations (probably NOMAD2) • Propagate to TOA to determine bounds on Lsat() • Build into full inversion model to test approach end to end

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