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Dates

Publication Date
Start Date
1980-01-01
End Date
2021-12-31

Citation

Myers, R.D., Asquith, W.H., Banks, S.M., and Rodgers, K.D., 2024, Modeled daily salinity derived from multiple machine learning methodologies for 91 salinity monitoring sites in the northern Gulf of Mexico, 1980–2021: U.S. Geological Survey data release, https://doi.org/10.5066/P90GZAZU.

Summary

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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Attached Files

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SabLa_TWDB_SAB1_cols.txt 12.87 KB text/plain
SabLa_TWDB_SAB1_EVOD_POOLED.feather.zip 2.19 MB application/zip
SabLa_TWDB_SAB1_EVOD_POOLED.txt.zip 1.56 MB application/zip
SabLa_TWDB_SAB2_cols.txt 12.87 KB text/plain
SabLa_TWDB_SAB2_EVOD_POOLED.feather.zip 2.18 MB application/zip
SabLa_TWDB_SAB2_EVOD_POOLED.txt.zip 1.61 MB application/zip

Purpose

The purpose of this dataset is to provide to the terminal output from statistical prediction of daily salinity values for the Sabine Lake group for relay to other science endeavors.

Map

Spatial Services

ScienceBase WMS

Communities

  • USGS Lower Mississippi-Gulf Water Science Center

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