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William H. Asquith

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The dataset folder entitled “SabLa” holds data structures consisting of statistical predictions of daily salinity time series for the Sabine Lake (SabLa) group, generated from the makESTUSAL software repository described by Asquith and others (2023b). The statistical methods included multiple methods of machine learning, which produced the daily salinity prediction and attendant credible uncertainties included in the data release. The geographic scope of the SabLa group includes the predictions for two locations defined using agency code and salinity site abbreviations.
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The dataset folder entitled “FloCo” holds data structures consisting of statistical predictions of daily salinity time series for the North Florida Gulf Coast (FloCo) group, generated from the makESTUSAL software repository described by Asquith and others (2023b). The statistical methods included multiple methods of machine learning, which produced the daily salinity prediction and attendant credible uncertainties included in the data release. The geographic scope of the FloCo group includes the predictions for ten locations defined using agency code and salinity site abbreviations.
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The dataset folder entitled “MissS” holds data structures consisting of statistical predictions of daily salinity time series for the Mississippi Sound (MissS) group, generated from the makESTUSAL software repository described by Asquith and others (2023b). The statistical methods included multiple methods of machine learning, which produced the daily salinity prediction and attendant credible uncertainties included in the data release. The geographic scope of the MissS group includes the predictions for eighteen locations defined using agency code and salinity site abbreviations.
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The dataset folder entitled “GalBa” holds data structures consisting of statistical predictions of daily salinity time series for the Galveston Bay (GalBa) group, generated from the makESTUSAL software repository described by Asquith and others (2023b). The statistical methods included multiple methods of machine learning, which produced the daily salinity prediction and attendant credible uncertainties included in the data release. The geographic scope of the GalBa group includes the predictions for eight locations defined using agency code and salinity site abbreviations.
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The dataset folder entitled “RookB” holds data structures consisting of statistical predictions of daily salinity time series for the Rookery Bay (RookB) group, generated from the makESTUSAL software repository described by Asquith and others (2023b). The statistical methods included multiple methods of machine learning, which produced the daily salinity prediction and attendant credible uncertainties included in the data release. The geographic scope of the RookB group includes the predictions for three locations defined using agency code and salinity site abbreviations.
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