Results of a data-assimilative ocean model (JCOPE2) from 1993 to 2012 were used to examine the correlation between the Pacific Decadal Oscillation (PDO) index and interannual variations of the Kuroshio transport in the East China Sea (ECS) and the influences of mesoscale eddies on this correlation. In a period from 1993 to 2002, the Kuroshio transport estimated from the JCOPE2 reanalysis has a positive correlation with the PDO index. This well-known correlation became weak or even disappeared when the analysis period was extended from 1993-2002 to 1993-2012. This occurs because the variation range of the PDO index became small during enhanced mesoscale eddy activity southeast of Taiwan in years after 2002. The eddies caused a larger variation in the Kuroshio transport in the years after 2002 than before 2002, and therefore, changed the correlation between the PDO index and Kuroshio transport in the ECS. The influence of mesoscale eddies on the Kuroshio transport has strong regional dependence: the Kuroshio transport from the area east of Taiwan to the midway along the shelf break in the East China Sea depends mainly on eddies arriving from southeast of Taiwan, while transport from the midway along the shelf break to the Tokara Strait depends mainly on the eddies arriving from northeast of Okinawa Island. The combination of PDO-related signals and eddy-related signals determines the interannual variations of the Kuroshio transport in the ECS and sufficient attention must be paid to the spatial dependence of the Kuroshio transport in the ECS on eddies.

During ice-free periods, the Northern Sea Route (NSR) could be an attractive shipping route. The decline in Arctic sea-ice extent, however, could be associated with an increase in the frequency of the causes of severe weather phenomena, and high wind-driven waves and the advection of sea ice could make ship navigation along the NSR difficult. Accurate forecasts of weather and sea ice are desirable for safe navigation, but large uncertainties exist in current forecasts, partly owing to the sparse observational network over the Arctic Ocean. Here, we show that the incorporation of additional Arctic observations improves the initial analysis and enhances the skill of weather and sea-ice forecasts, the application of which has socioeconomic benefits. Comparison of 63-member ensemble atmospheric forecasts, using different initial data sets, revealed that additional Arctic radiosonde observations were useful for predicting a persistent strong wind event. The sea-ice forecast, initialised by the wind fields that included the effects of the observations, skilfully predicted rapid wind-driven sea-ice advection along the NSR.

To investigate the impact of radiosonde data on the sea-ice forecast in the Northern Sea Route during an extremely developed cyclone on 6 August 2012, a series of numerical experiments were conducted using an ice-ocean coupled model with fine horizontal resolution (approximately 2.5 km). The atmospheric forcing data used for the model were forecast data with (CTL) and without (OSE) initialization by radiosonde data over the Fram Strait, obtained by the German R/V Polarstern, and the European Centre for Medium-Range Weather Forecasts Interim reanalysis data. All numerical experiments were run from 06:00 UTC on 3 August 2012 to 00:00 UTC on 8 August 2012 with an initial sea-ice concentration and thickness derived from the Advanced Microwave Scanning Radiometer 2 satellite data. The root-mean-square error and correlation coefficient for the sea-ice distribution showed that the CTL simulation predicted better the sea-ice distribution in the Northern Sea Route than the OSE simulation. This occurred in particular from 6 to 7 August when the cyclone became strong. The thermodynamic processes resulted in the difference in the sea-ice thickness due to changes in the vertical energy fluxes. However, the differences in the sea-ice concentration and velocity were caused mainly by the dynamics, particularly the difference in wind fields, rather than the thermodynamics. These results suggest that radiosonde data are effective in improving the forecast accuracy of the sea-ice distribution. Therefore, errors in the weather forecast data would have a substantial impact on the safety of ship navigation and the sea-ice distribution.

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