Tavora, J; Fernandes, EH; Bitencourt, LP; Orozco, PMS (2020). El-Nino Southern Oscillation (ENSO) effects on the variability of Patos Lagoon Suspended Particulate Matter. REGIONAL STUDIES IN MARINE SCIENCE, 40, 101495.

South America is particularly subject to El-Nino Southern Oscillation (ENSO)-triggered phenomena, with above-average precipitation during ENSO warm events (El Nino) and below-average precipitation during cold events (La Nina). Seventeen years (2003-2019) of reflectance data from the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua sensor were used to quantify the Suspended Particulate Matter (SPM) distribution and variability in Patos Lagoon, southern Brazil, based on three semi-analytical algorithms. An atmospheric correction suitable for extremely turbid coastal waters was applied. Occasional negative retrievals of remote sensing reflectance (Rrs) products were filtered and removed. SPM concentrations were modeled from filtered Rrs values by applying the chosen semi analytical algorithms: a single band algorithm, a weighted algorithm, and a multi-band algorithm (referred here as NECHAD10, HAN16, and NOVOA17, respectively). After those steps, the daily modeled SPM data were averaged into eight-day, monthly, and yearly composites. SPM time series were then compared to the ENSO index and environmental parameters. As a result of substantial interannual variability, the highest SPM concentrations were found to match El-Nino events (in 2009 and 2012) while the lowest corresponded to a strong La Nina (2010) and a neutral year (2014). The modeled SPM was compared to in-situ SPM data to ensure the applicability to/in Patos Lagoon. Our main results suggest that while the three tested algorithms allow the analysis of temporal and spatial SPM variability, HAN16 and NOVOA17 seem to provide the best results for the Patos Lagoon region. On the other hand, NECHAD10 yields more satisfactory results considering the yearly and eight-day composites. Therefore, we call attention to the methods of handling data as each approach might lead to a different interpretation of the same phenomena. (C) 2020 Elsevier B.V. All rights reserved.