AI Summary & Key Takeaways
AI InsightThe results show that the model is capable of simulating daily mean SSHA with an RMSE value of 1.2 cm.
📌 3 Key Takeaways
Abstract
The skill of a high-resolution Black Sea circulation model (ROMS) is assessed using the available satellite and field data for Sea Surface Height Anomaly (SSHA), Sea Surface Temperature, and CTD profiles. The model is configured to simulate the 9-year period between 2012 and 2021. The model’s skill is assessed using standard analytical methods for error calculation such as Root Mean Square Error (RMSE) and correlation. Additionally, the model results are assessed using several more recent methods such as the relative operating characteristic (ROC). The results show that the model is capable of simulating daily mean SSHA with an RMSE value of 1.2 cm. When the mean monthly SSHA values are considered, the RMSE drops down to 0.7 cm. The biggest source of the error for SSHA is found to be related to the freshwater balance, as the Black Sea is a freshwater-dominated marine environment. The results for SST show that the model is able to capture both the daily and seasonal variation with high correlation values. The correlation coefficient for basin averaged SST over the entire simulation period compared to the satellite-based OISST data is calculated as 0.98, and the RMSE value is 1.6 °C. In addition to the surface comparisons obtained from SSHA and SST, the model results are compared to 2300 Argo Float CTD profiles. The RMSE is 1.1 °C for the temperature profiles and 0.7 PSU for the salinity over the entire water column. The methods used to assess the skill of the model show that the model is quite capable of simulation of oceanic conditions within the Black Sea. As one of the aims of this model’s development is to simulate mesoscale-to-sub-mesoscale eddies, results on the model’s capabilities show that it can simulate eddies successfully from 5 – 50 km eddies in the Black Sea.