Paper
15 November 2018 Specifying algorithm uncertainties in satellite-derived PAR products
Robert Frouin, Didier Ramon, Dominique Jolivet, Mathieu Compiègne
Author Affiliations +
Proceedings Volume 10778, Remote Sensing of the Open and Coastal Ocean and Inland Waters; 107780W (2018) https://doi.org/10.1117/12.2501681
Event: SPIE Asia-Pacific Remote Sensing, 2018, Honolulu, Hawaii, United States
Abstract
Satellite ocean-color project offices routinely generate Level 2 and Level 3 daily Photo-synthetically Available Radiation (PAR) products. Accuracy is currently evaluated against in-situ measurements from buoys and fixed platforms at a few locations, but specifying algorithm (and other) uncertainties on a pixel-by-pixel basis is needed to assess product quality. Expressing uncertainties requires modeling the measurement, identifying all possible error sources (e.g., noise in the input variables, imperfect/incomplete mathematical model), and determining the combined uncertainty. In the present study, algorithm uncertainties associated with PAR products are considered, i.e., those due to model approximations and parameter errors (e.g., decoupling effects of clouds and clear atmosphere, neglecting diurnal variability of clouds, using aerosol climatology) assuming that the input variables (TOA reflectance at wavelengths in the PAR spectral range) are known perfectly. A procedure is provided to estimate and provide, for each pixel of a product, this uncertainty component of the total uncertainty budget, which is expected to dominate. The bias and standard deviation of the daily PAR estimates are calculated as a function of clear sky PAR and cloud factor (i.e., the effect of clouds on daily PAR). The uncertainty characterization is accomplished using an extended simulation dataset covering the 2003–2012 time period using hourly MERRA-2 input data. The large number of data points allows one to sample well atmospheric variability and in particular many variations of daytime cloudiness, for all latitudes. Selected maps of global daily and monthly PAR and associated uncertainties (bias, standard deviation), obtained from MERIS data, are analyzed. Comparisons with match-up data at the COVE calibration/evaluation site reveal that experimental uncertainties are similar to the theoretical uncertainties obtained from simulated data.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Robert Frouin, Didier Ramon, Dominique Jolivet, and Mathieu Compiègne "Specifying algorithm uncertainties in satellite-derived PAR products", Proc. SPIE 10778, Remote Sensing of the Open and Coastal Ocean and Inland Waters, 107780W (15 November 2018); https://doi.org/10.1117/12.2501681
Lens.org Logo
CITATIONS
Cited by 2 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Clouds

Satellites

Atmospheric modeling

In situ metrology

Mathematical modeling

Aerosols

Atmospheric particles

RELATED CONTENT

General outlines of the POLDER experiment
Proceedings of SPIE (December 15 1995)
PICASSO-CENA mission
Proceedings of SPIE (December 28 1999)
EOS Multiangle Imaging Spectroradiometer
Proceedings of SPIE (December 01 1990)

Back to Top