El-Niño Southern Oscillation (ENSO) effects on the variability of Patos Lagoon Suspended Particulate Matter
South America is particularly subject to El-Niño Southern Oscillation (ENSO)-triggered phenomena, with above-average precipitation during ENSO warm events (El Niño) and below-average precipitation during cold events (La Niña). Seventeen years (2003–2019) of reflectance data from the Moderate Resolut...
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Published in | Regional studies in marine science Vol. 40; p. 101495 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
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Elsevier B.V
01.11.2020
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ISSN | 2352-4855 2352-4855 |
DOI | 10.1016/j.rsma.2020.101495 |
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Abstract | South America is particularly subject to El-Niño Southern Oscillation (ENSO)-triggered phenomena, with above-average precipitation during ENSO warm events (El Niño) and below-average precipitation during cold events (La Niña). 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-Niño events (in 2009 and 2012) while the lowest corresponded to a strong La Niña (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.
•Long-term assessment of MODIS-aqua surface suspended particulate matter in Patos Lagoon, Brazil.•Interannual variability of SPM correlated with ENSO events.•Performance assessment of three well-known algorithms to retrieve SPM concentrations in Patos Lagoon. |
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AbstractList | South America is particularly subject to El-Niño Southern Oscillation (ENSO)-triggered phenomena, with above-average precipitation during ENSO warm events (El Niño) and below-average precipitation during cold events (La Niña). 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-Niño events (in 2009 and 2012) while the lowest corresponded to a strong La Niña (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.
•Long-term assessment of MODIS-aqua surface suspended particulate matter in Patos Lagoon, Brazil.•Interannual variability of SPM correlated with ENSO events.•Performance assessment of three well-known algorithms to retrieve SPM concentrations in Patos Lagoon. South America is particularly subject to El-Niño Southern Oscillation (ENSO)-triggered phenomena, with above-average precipitation during ENSO warm events (El Niño) and below-average precipitation during cold events (La Niña). 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-Niño events (in 2009 and 2012) while the lowest corresponded to a strong La Niña (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. |
ArticleNumber | 101495 |
Author | Orozco, Priscila Mulattieri Suarez Bitencourt, Liliane Paranhos Fernandes, Elisa Helena Távora, Juliana |
Author_xml | – sequence: 1 givenname: Juliana surname: Távora fullname: Távora, Juliana email: juliana.tavora@maine.edu, j.tavora@utwente.nl organization: School of Marine Sciences, University of Maine, 04469, Aubert Hall, room 360, Orono, USA – sequence: 2 givenname: Elisa Helena surname: Fernandes fullname: Fernandes, Elisa Helena email: fernandes.elisa@gmail.com organization: Instituto de Oceanografia, Universidade Federal do Rio Grande (FURG), Av. Itália, km 8, Campus Carreiros, CP 474, CEP 96201-900, Rio Grande, RS, Brazil – sequence: 3 givenname: Liliane Paranhos surname: Bitencourt fullname: Bitencourt, Liliane Paranhos email: liparanhosb@gmail.com organization: Instituto de Oceanografia, Universidade Federal do Rio Grande (FURG), Av. Itália, km 8, Campus Carreiros, CP 474, CEP 96201-900, Rio Grande, RS, Brazil – sequence: 4 givenname: Priscila Mulattieri Suarez surname: Orozco fullname: Orozco, Priscila Mulattieri Suarez email: priorozco@gmail.com organization: Instituto de Oceanografia, Universidade Federal do Rio Grande (FURG), Av. Itália, km 8, Campus Carreiros, CP 474, CEP 96201-900, Rio Grande, RS, Brazil |
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SubjectTerms | algorithms Brazil coastal water El Nino ENSO environmental factors La Nina moderate resolution imaging spectroradiometer MODIS particulates Patos Lagoon reflectance Remote sensing Suspended sediment time series analysis |
Title | El-Niño Southern Oscillation (ENSO) effects on the variability of Patos Lagoon Suspended Particulate Matter |
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