Simulating upper layer of Bay of Bengal through three-dimensional ocean circulation models is a challenging task. In this study, the surface current from the Nucleus European Modelling of Ocean (NEMO) based global ocean assimilation system is assessed against the high frequency (HF) radar data along the Andhra Pradesh coast on a daily scale during southwest monsoon 2016. The temporal variation of NEMO simulated surface current with HF radar data shows that the NEMO model captures the zonal current better than the meridional current. Both NEMO and HF radar show that the mean surface current average over latitude (15.8$^{\circ}$–16.3$^{\circ}$N) is westward for zonal surface current and southward for meridional current with maximum at 40–60 km away from the coast. Further, the monthly mean HF radar derived surface current indicates the strong south-westward flow of surface current dominated during July 2016 with speed more than 50 cm/s which is also well simulated by NEMO analysis. It also captures the cold core eddy during 15–25 July 2016 with very small north-eastward shift with respect to HF radar. The scatter plot of collocated surface zonal and meridional current average over the box (81.5–82.5$^{\circ}$E; 15.5–16.5$^{\circ}$N) clearly shows that NEMO analysis has the correlation of more than 0.5 for both zonal and meridional current.

$\bf{Highlights}$

$\bullet$ The simulation of upper layer of Bay of Bengal (BoB) through three dimensional ocean circulation models is a challenging task. In this study, the surface current from the high resolution NEMO based global ocean assimilation system is compared against the observed High Frequency (HF) radar data along the Andhra Pradesh Coast during the southwest monsoon 2016.

$\bullet$ NEMO analysis captures the mean and variability of surface current very well with HF radar. However, it underestimates the mean surface current which may be due to coarser model resolution and complex non-linear processes in the coastal region.

$\bullet$ The strong cold core eddy during 15–25 July 2016 is observed along the coast which is well simulated in NEMO model with small north-eastward shift with respect to HF radar.

$\bullet$ The scatter plot of collocated surface current from NEMO analysis and HF radar data average over the Andhra Pradesh Coast (APCO; 81.5–82.5$^{\circ}$E; 15.5–16.5$^{\circ}$N) clearly shows that NEMO analysis has the correlation of more than 0.5 for surface current.

For Earth’s climate system, the study of the seasonal variability of sea-ice is important as the sea-ice has a significant impact on the net radiative flux, which can inCuence the mean seasonal behaviours of the atmosphere and ocean. In this study, the seasonal hindcast of 14 austral winter seasons is conducted toassess the skill of a coupled model in simulating the seasonal Antarctic sea-ice and its connection with the other ocean and atmospheric variables. The GloSea4 set-up of the HadGEM3 coupled model is used for the seasonal simulations at the NCMRWF. The model could reproduce the sea-ice extent over the Antarctic for the Austral winter seasons with an average correlation value of 0.98. However, there are moderate biases in the sea-ice concentration. The sea-ice thickness in the model generally shows negative bias, which is not seen to be related to the surface air temperature biases in the coupled system. The moderate positive (warm) biases in the sea surface temperature extending into the upper ocean (30 m), combined with the sea-ice drift bias pattern away from the sea-ice region are the main reasons for the underestimation of sea-ice thickness in the model. The sea surface current bias pattern shows a poleward component that brings the warm water from the warm biased locations of the exterior region into the seaiceregion and explains the presence of warmer waters in the sea-ice regions. The anti-clockwise bias in the surface wind is seen to impact the surface current, Antarctic circumpolar current (ACC), having a similar anti-clockwise current bias. Despite these moderate biases in the model, the inter-annual variability ofsea-ice extent is having a reasonably good skill. The model is suitable for extended/seasonal prediction of sea-ice during Austral winter for Antarctic.