Estimating sea surface salinity in coastal waters of the Gulf of Mexico using visible channels on SNPP-VIIRS

2014 ◽  
Author(s):  
Ryan A. Vandermeulen ◽  
Robert Arnone ◽  
Sherwin Ladner ◽  
Paul Martinolich
Keyword(s):  
Gulf Of Mexico ◽  
Coastal Waters ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity

scholarly journals An Improved Model for Chlorophyll-a Concentration Retrieval in Coastal Waters Based on UAV-Borne Hyperspectral Imagery: A Case Study in Qingdao, China

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2769
Author(s):  
Yingying Gai ◽  
Dingfeng Yu ◽  
Yan Zhou ◽  
Lei Yang ◽  
Chao Chen ◽  
...  
Keyword(s):  
Chlorophyll A ◽  
Coastal Waters ◽  
Wind Waves ◽  
Biological Indicator ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
New Model ◽  
Chl A ◽  
Improved Model

Chlorophyll-a (Chl-a) is an objective biological indicator, which reflects the nutritional status of coastal waters. However, the turbid coastal waters pose challenges to the application of existing Chl-a remote sensing models of case II waters. Based on the bio-optical models, we analyzed the suppression of coastal total suspended matter (TSM) on the Chl-a optical characteristics and developed an improved model using the imagery from a hyper-spectrometer mounted on an unmanned aerial vehicle (UAV). The new model was applied to estimate the spatiotemporal distribution of Chl-a concentration in coastal waters of Qingdao on 17 December 2018, 22 March 2019, and 20 July 2019. Compared with the previous models, the correlation coefficients (R2) of Chl-a concentrations retrieved by the new model and in situ measurements were greatly improved, proving that the new model shows a better performance in retrieving coastal Chl-a concentration. On this basis, the spatiotemporal variations of Chl-a in Qingdao coastal waters were analyzed, showing that the spatial variation is mainly related to the TSM concentration, wind waves, and aquaculture, and the temporal variation is mainly influenced by the sea surface temperature (SST), sea surface salinity (SSS), and human activities.

scholarly journals Sea Surface Salinity Estimation and Spatial-Temporal Heterogeneity Analysis in the Gulf of Mexico

2021 ◽  
Vol 13 (5) ◽  
pp. 881
Author(s):  
Zhiyi Fu ◽  
Fangfang Wu ◽  
Zhengliang Zhang ◽  
Linshu Hu ◽  
Feng Zhang ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
River Discharge ◽  
River Flow ◽  
High Accuracy ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Temporal Heterogeneity ◽  
Surface Salinity ◽  
Circular Distribution ◽  
Heterogeneity Analysis

As an important parameter to characterize physical and biogeochemical processes, sea surface salinity (SSS) has received extensive attention. Cubist is a data mining model, which can be well-suited to estimate and analyze SSS in the Gulf of Mexico (GOM) because it can reflect the SSS internal heterogeneity in the GOM—overall circular distribution, and the seasonality related to temperature and river discharge changes. Using remote sensing reflectance (Rrs) at 412, 443, 488 (490), 555, and 667 (670) nm and sea surface temperature (SST), a cubist model was developed to estimate SSS with high accuracy with the overall performance demonstrates a root mean square error (RMSE) of 0.27 psu and correlation coefficient of 0.97 of R2. The model divides the GOM area according to model rules into four sub-regions, which include estuary, nearshore, and open sea, reflecting the gradient distribution of SSS. The division of sub-regions and seasonal changes can be explained by the distribution of water bodies, river discharges, and local wind forces since it is obvious that the estuary region reaches the largest low-value area and spreads eastward with the monsoon in the spring when the river flow increases to the highest value. While the east to west wind in the non-summer monsoon period guides the plume westward, and the lowest river discharge in winter corresponds to the smallest low value area. After comparison with other statistical models, the cubist model showed satisfactory results in independent verification of cruise data, proving the estimation capability under different geographical conditions (such as estuaries and open seas) and seasons. Therefore, considering high accuracy and heterogeneity mining, the cubist-based model is an ideal method for coastal SSS estimation and spatial-temporal heterogeneity analysis, and can provide ideas for model construction for coastal areas with similar geographic environments.

scholarly journals Tracking sea surface salinity and dissolved oxygen on a river-influenced, seasonally stratified shelf, Mississippi Bight, northern Gulf of Mexico

2018 ◽  
Vol 169 ◽  
pp. 25-33 ◽  
Author(s):  
Brian Dzwonkowski ◽  
Severine Fournier ◽  
John T. Reager ◽  
Scott Milroy ◽  
Kyeong Park ◽  
...  
Keyword(s):  
Gulf Of Mexico ◽  
Dissolved Oxygen ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Northern Gulf Of Mexico

Hourly changes in sea surface salinity in coastal waters recorded by Geostationary Ocean Color Imager

2017 ◽  
Vol 196 ◽  
pp. 227-236 ◽  
Author(s):  
Rongjie Liu ◽  
Jie Zhang ◽  
Haiyan Yao ◽  
Tingwei Cui ◽  
Ning Wang ◽  
...  
Keyword(s):  
Coastal Waters ◽  
Ocean Color ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity

scholarly journals SPATIAL AND TEMPORAL ANALYSIS OF SEA SURFACE SALINITY USING SATELLITE IMAGERY IN GULF OF MEXICO

2017 ◽  
Vol XLII-4/W4 ◽  
pp. 219-223 ◽  
Author(s):  
S. Rajabi ◽  
M. Hasanlou ◽  
A. R. Safari
Keyword(s):  
Gulf Of Mexico ◽  
Temporal Analysis ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Loop Current ◽  
Surface Salinity ◽  
Spatiotemporal Resolution ◽  
Study Region ◽  
Distribution Maps ◽  
Saline Waters

The recent development of satellite sea surface salinity (SSS) observations has enabled us to analyse SSS variations with high spatiotemporal resolution. In this regards, The Level3-version4 data observed by Aquarius are used to examine the variability of SSS in Gulf of Mexico for the 2012-2014 time periods. The highest SSS value occurred in April 2013 with the value of 36.72 psu while the lowest value (35.91 psu) was observed in July 2014. Based on the monthly distribution maps which will be demonstrated in the literature, it was observed that east part of the region has lower salinity values than the west part for all months mainly because of the currents which originate from low saline waters of the Caribbean Sea and furthermore the eastward currents like loop current. Also the minimum amounts of salinity occur in coastal waters where the river runoffs make fresh the high saline waters. Our next goal here is to study the patterns of sea surface temperature (SST), chlorophyll-a (CHLa) and fresh water flux (FWF) and examine the contributions of them to SSS variations. So by computing correlation coefficients, the values obtained for SST, FWF and CHLa are 0.7, 0.22 and 0.01 respectively which indicated high correlation of SST on SSS variations. Also by considering the spatial distribution based on the annual means, it found that there is a relationship between the SSS, SST, CHLa and the latitude in the study region which can be interpreted by developing a mathematical model.

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