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An assessment of the predictability of column minimum dissolved oxygen concentrations in Chesapeake Bay using a machine learning model

Abstract.

"Subseasonal to seasonal forecasts have the potential to be a useful tool for managing estuarine fisheries and water quality, and with increasing skill at forecasting conditions at these time scales in the atmosphere and open ocean, skillful forecasts of estuarine salinity, temperature, and biogeochemistry may be possible. In this study, we use a machine learning model to assess the predictability of column minimum dissolved oxygen in Chesapeake Bay at a monthly time scale. [...]"

Source: Estuarine, Coastal and Shelf Science
Authors: Andrew C. Ross, Charles A. Stock
DOI: 10.1016/j.ecss.2019.03.007

Read the full article here.