Figure 2
From: Sea level variability and modeling in the Gulf of Guinea using supervised machine learning
The spatial linear trend of mean sea level anomaly (MSLA) (A) and its forcing factors, including steric sea level anomaly (SSLA) (B), thermosteric sea level anomaly (TSLA) (C), halosteric sea level anomaly (HSLA) (D), precipitation (E), evaporation (F), runoff (G) ocean heat content (OHC) (H), Current (I), wind stress curl (WSC) (J), net heat flux (NHF) (K), and atmospheric pressure (L) for the period 2003 to 2012 in the Gulf of Guinea. The trends were obtained by subjecting the monthly mean of each dataset to a linear regression model, which calculates decadal slope at each grid point. The calculations, as well as the maps, were produced with a Python (3.10.9) script.
