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Article Synergistic Use of Remote Sensing and Modeling to Assess an Anomalously High Chlorophyll-a Event during Summer 2015 in the South Central Red Sea.
- Source :
- Remote Sensing; Aug2017, Vol. 9 Issue 8, p778, 20p
- Publication Year :
- 2017
-
Abstract
- An anomalously high chlorophyll-a (Chl-a) event (>2 mg/m3) during June 2015 in the South Central Red Sea (17.5° to 22°N, 37° to 42°E) was observed using Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Terra and Aqua satellite platforms. This differs from the low Chl-a values (<0.5 mg/m3) usually encountered over the same region during summertime. To assess this anomaly and possible causes, we used a wide range of oceanographical and meteorological datasets, including Chl-a concentrations, sea surface temperature (SST), sea surface height (SSH), mixed layer depth (MLD), ocean current velocity and aerosol optical depth (AOD) obtained from different sensors and models. Findings confirmed this anomalous behavior in the spatial domain using Hovmöller data analysis techniques, while a time series analysis addressed monthly and daily variability. Our analysis suggests that a combination of factors controlling nutrient supply contributed to the anomalous phytoplankton growth. These factors include horizontal transfer of upwelling water through eddy circulation and possible mineral fertilization from atmospheric dust deposition. Coral reefs might have provided extra nutrient supply, yet this is out of the scope of our analysis. We thought that dust deposition from a coastal dust jet event in late June, coinciding with the phytoplankton blooms in the area under investigation, might have also contributed as shown by our AOD findings. However, a lag cross correlation showed a two-month lag between strong dust outbreak and the high Chl-a anomaly. The high Chl-a concentration at the edge of the eddy emphasizes the importance of horizontal advection in fertilizing oligotrophic (nutrient poor) Red Sea waters. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 9
- Issue :
- 8
- Database :
- Complementary Index
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 124868632
- Full Text :
- https://doi.org/10.3390/rs9080778