Evaluation of global ocean analysis and forecast system in the Tropical Indian Ocean

In this study, the global ocean analysis and forecast system is evaluated against the observations in the Indian Ocean for the 2017–2018 period. A comparison of temperature and salinity analysis with seven moored buoy observations showed an excellent mutual agreement with systematically underestimating the upper ocean variability. A similar comparison of ocean analysis with the ARGO dataset average over the different oceanic regions also shows an underestimation of temperature and salinity up to 300 m depth. Further, the temperature RMSE gradually increases from surface to thermocline depth for all regions. The sea surface temperature (SST) forecast is reasonably good at all buoy locations with RMSE less than 0.5°C and a correlation of more than 0.7 up to the day-7 forecasts for the 2017–2018 period. Similarly, the sea surface salinity (SSS) forecast is also good except northern Bay of Bengal (BoB) region where the high variability leads to poor correlation and large RMSE in this shallow and freshwater region. This study helps to understand how observations fit into the model through data assimilation and also quantifies the model forecast error. Further, the study is also vital for the development/research activity related to the model and data assimilation in the Tropical Indian Ocean (TIO) region.