|Title||Evaluation of semi-analytical algorithms to retrieve particulate and dissolved absorption coefficients in Gulf of California optically complex waters|
|Publication Type||Journal Article|
|Year of Publication||2018|
|Authors||Betancur-Turizo S.P, Gonzalez-Silvera A., Santamaria-del-Angel E., Tan J., Frouin R.|
|Type of Article||Article|
|Keywords||climate; Inherent optical properties; inversion; light-absorption; model; ocean color; ocean-color; phytoplankton; Remote sensing; sea; seawifs; variability|
Two semi-analytical algorithms, Generalized Inherent Optical Property (GIOP) and Garver-Siegel-Maritorena (GSM), were evaluated in terms of how well they reproduced the absorption coefficient of phytoplankton (a(ph)(lambda)) and dissolved and detrital organic matter (a(dg)(lambda)) at three wavelengths (lambda of 412, 443, and 488 nm) in a zone with optically complex waters, the Upper Gulf of California (UGC) and the Northern Gulf of California (NGC). In the UGC, detritus determines most of the total light absorption, whereas, in the NGC, chromophoric dissolved organic material (CDOM) and phytoplankton dominate. Upon comparing the results of each model with a database assembled from four cruises done from spring to summer (March through September) between 2011 and 2013, it was found that GIOP is a better estimator for a(ph)(lambda) than GSM, independently of the region. However, both algorithms underestimate in situ values in the NGC, whereas they overestimate them in the UGC. Errors are associated with the following: (a) the constant a*(ph)(lambda) value used by GSM and GIOP (0.055 m(2) mgChla(-1)) is higher than the most frequent value observed in this study's data (0.03 m(2) mgChla(-1)), and (b) satellite-derived chlorophyll a concentration (Chla) is biased high compared with in situ Chla. GIOP gave also better results for the a(dg)(lambda) estimation than GSM, especially in the NGC. The spectral slope S-dg was identified as an important parameter for estimating a(dg)(lambda), and this study's results indicated that the use of a fixed input value in models was not adequate. The evaluation confirms the lack of generality of algorithms like GIOP and GSM, whose reflectance model is too simplified to capture expected variability. Finally, a greater monitoring effort is suggested in the study area regarding the collection of in situ reflectance data, which would allow explaining the effects that detritus and CDOM may have on the semi-analytical reflectance inversions, as well as isolating the possible influence of the atmosphere on the satellite-derived water reflectance and Chla.