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Spatiotemporal variability of sea surface temperature and its relationship with salinity, chlorophyll-a concentration and bathymetry in Bangladesh
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The present research aimed to examine the long-term connections (i.e. from 2010 to 2021) between monthly chlorophyll-a, sea surface temperature, and sea surface salinity. The long-term variability of SST in the Bay of Bengal (BoB) was analyzed using open access data sets of monthly SST, Chlorophyll-a and Sea Surface Salinity to understand trends, relationships, and bathymetric influences on these oceanographic parameters. The SST records for the Bay of Bengal indicates a gradual increasing trend over the period studied. The Sea Surface Salinity (SSS) follows a seasonal trend and plays an essential effect in the distribution of SST in the BoB. The SST for the corresponding time range has been compared, and a strong correlation (R2=0.81) between SST and SSS has been found. The salinity value for the near-coastal zone is less than the away from the coast. The monsoon season lowers the value of SSS, which might be related to monsoonal rainfall and fresh water influx in the Bay of Bengal. Moreover, the Chlorophyll-a concentration, which is a direct indicator of the phytoplankton productivity, has been analyzed for this study. The chlorophyll-a concentration follows a locational and seasonal trend. The correlation between sea surface temperature (SST) and chlorophyll-a concentration was determined to be quite weak, primarily due to the minimal fluctuations in chlorophyll-a levels. For all of the data (i.e. SST, SSS, chlorophyll-a E S H concentration and bathymetry), seasonal and locational variability have been observed. A strong positive correlation was observed between the variability in sea surface temperature (SST) and sea surface salinity (SSS). The value of SST varies with increasing depth; with increasing depth the mean value for SST value decreases and the dispersion of values increases from the mean. This study would help ocean scientists and policy makers in understanding the interaction between physical parameters with the biological parameters and benefit them in further study as well as in maritime planning.
Ecological Society of Bangladesh
Title: Spatiotemporal variability of sea surface temperature and its relationship with salinity, chlorophyll-a concentration and bathymetry in Bangladesh
Description:
The present research aimed to examine the long-term connections (i.
e.
from 2010 to 2021) between monthly chlorophyll-a, sea surface temperature, and sea surface salinity.
The long-term variability of SST in the Bay of Bengal (BoB) was analyzed using open access data sets of monthly SST, Chlorophyll-a and Sea Surface Salinity to understand trends, relationships, and bathymetric influences on these oceanographic parameters.
The SST records for the Bay of Bengal indicates a gradual increasing trend over the period studied.
The Sea Surface Salinity (SSS) follows a seasonal trend and plays an essential effect in the distribution of SST in the BoB.
The SST for the corresponding time range has been compared, and a strong correlation (R2=0.
81) between SST and SSS has been found.
The salinity value for the near-coastal zone is less than the away from the coast.
The monsoon season lowers the value of SSS, which might be related to monsoonal rainfall and fresh water influx in the Bay of Bengal.
Moreover, the Chlorophyll-a concentration, which is a direct indicator of the phytoplankton productivity, has been analyzed for this study.
The chlorophyll-a concentration follows a locational and seasonal trend.
The correlation between sea surface temperature (SST) and chlorophyll-a concentration was determined to be quite weak, primarily due to the minimal fluctuations in chlorophyll-a levels.
For all of the data (i.
e.
SST, SSS, chlorophyll-a E S H concentration and bathymetry), seasonal and locational variability have been observed.
A strong positive correlation was observed between the variability in sea surface temperature (SST) and sea surface salinity (SSS).
The value of SST varies with increasing depth; with increasing depth the mean value for SST value decreases and the dispersion of values increases from the mean.
This study would help ocean scientists and policy makers in understanding the interaction between physical parameters with the biological parameters and benefit them in further study as well as in maritime planning.
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