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Deep Sea Res
Le, C., Hu, C., English, D., Cannizzaro, J., & Kovach, C. (2013). Climate-driven chlorophyll-a changes in a turbid estuary: Observations from satellites and implications for management.
Remote Sensing of Environment
Significant advances have been made in ocean color remote sensing of turbidity and water clarity for estuarine waters, yet accurate estimations of chlorophyll-a concentrations (Chla in mg m− 3) has been problematic, posing a challenge to the research community and an obstacle to managers for long-term water quality assessment. Here, a novel empirical Chla algorithm based on a Red-Green-Chorophyll-Index (RGCI) was developed and validated for MODIS and SeaWiFS observations between 1998 and 2011. The algorithm showed robust performance with two independent datasets, with relative mean uncertainties of ~ 30% and ~ 50% and RMS uncertainties of ~ 40% and ~ 65%, respectively, for Chla ranging between 1.0 and > 30.0 mg m− 3. These uncertainties are comparable or even lower than those reported for the global open oceans when traditional blue-green band ratio algorithms are used. A long-term Chla time series generated from SeaWiFS and MODIS observations showed excellent agreement between sensors and with in situ measurements. Substantial variability in both space and time was observed in the four bay segments, with higher Chla in the upper bay segments and lower Chla in the lower bay segments, and higher Chla in the wet season and lower Chla in the dry season. On average, river discharge could explain ~ 60% of the seasonal changes and ~ 90% of the inter-annual changes, with the latter mainly driven by climate variability (e.g. El Niño and La Niña years) and anomaly events (e.g. tropical cyclones). Significant positive correlation was found between monthly mean Chla anomalies and monthly Multivariate ENSO Index (MEI) (Pearson correlation coefficient = 0.43, p < 0.01, N = 147), with high Chla associated with El Niño and lower Chla associated with La Niña. Further, a Water Quality Decision Matrix (WQDM) was established from satellite observations, providing complementary and more reliable information to the existing WQDM based on less synoptic and less frequent field measurements. The satellite-derived WQDM and long-term time-series data support the decision making efforts of the management agencies that regulate nutrient discharge to the bay. Similar approaches may be established for other estuaries where field data are much more limited than for Tampa Bay.
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Wilson, M., Meyers, S. D., & Luther, M. E. (2013). Synoptic volumetric variations and flushing of the Tampa Bay estuary.
Two types of analyses are used to investigate the synoptic wind-driven flushing of Tampa Bay in response to the El Niño-Southern Oscillation (ENSO) cycle from 1950 to 2007. Hourly sea level elevations from the St. Petersburg tide gauge, and wind speed and direction from three different sites around Tampa Bay are used for the study. The zonal (u) and meridional (v) wind components are rotated clockwise by 40° to obtain axial and co-axial components according to the layout of the bay. First, we use the subtidal observed water level as a proxy for mean tidal height to estimate the rate of volumetric bay outflow. Second, we use wavelet analysis to bandpass sea level and wind data in the time–frequency domain to isolate the synoptic sea level and surface wind variance. For both analyses the long-term monthly climatology is removed and we focus on the volumetric and wavelet variance anomalies. The overall correlation between the Oceanic Niño Index and volumetric analysis is small due to the seasonal dependence of the ENSO response. The mean monthly climatology between the synoptic wavelet variance of elevation and axial winds are in close agreement. During the winter, El Niño (La Niña) increases (decreases) the synoptic variability, but decreases (increases) it during the summer. The difference in winter El Niño/La Niña wavelet variances is about 20 % of the climatological value, meaning that ENSO can swing the synoptic flushing of the bay by 0.22 bay volumes per month. These changes in circulation associated with synoptic variability have the potential to impact mixing and transport within the bay.
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