Surface wind is significant for ocean state climate, ocean mixing, and viability of wind energy techniques. However, surface wind simulated from the regional climate model generally features substantial bias from observation. For the first time, this study compares the performance of five bias correction techniques, (1) linear scaling, (2) variance scaling, (3) quantile mapping based on empirical distribution, (4) quantile mapping based on Weibull distribution, and (5) cumulative distribution functions transformation, in reducing the statistical bias of a regional climate model wind output, which was downscaled from a global climate model CNRM‐CM5 during 1991–2000. The surface wind of JRA55 reanalysis data is used as reference. Results show that all bias correction methods are consistent in reducing the climatological mean bias in spatial patterns and intensities. The linear scaling method always performs the worst among all methods in correcting higher‐order statistical biases such as skewness, kurtosis, and wind power density. The other four bias correction methods are generally similar in reducing the statistical biases of different measures based on spatial distribution maps. However, when it comes to spatial averaged mean of statistical measures over CORDEX‐East Asia in January and July, the quantile mapping based on Weibull distribution generally shows the best skills among all methods in bias reduction.

The present study mainly investigates the storm surge variations at different temporal scales using hourly tide gauge data in the Bohai Sea. The seasonal variation, inter-decadal variation, long-term trend and the tide-surge interaction were analyzed separately. The results show that the storm surges in the southwest Bohai Sea are larger than those in the north. The storm surges were more serious in winter (Oct. to Mar.) than in summer half of the year. Significant inter-decadal variations exist in the Bohai Sea, and the extreme storm surge events have been intensifying since 2010. Storm surge intensities at three of the tide gauges (Qinhuangdao, Huludao and Tanggu) exhibited a decreasing trend from 1980 to 2016, with trends significant at the 95% level at Qinhuangdao and Tanggu. Significant tide-surge interactions were observed at all four tide gauges. The tide-surge interaction that results in peak surges mostly occurs during the flood and ebb tides. There is a statistically significant negative correlation between storm surge intensity and the Arctic Oscillation (AO) at Longkou and Tanggu, while there is a significantly positive correlation between storm surge intensity and the Siberian High (SH) at Huludao, Qinhuangdao and Tanggu. A linear regression analysis revealed that the variations of the AO and SH explained 19–48% of the variations in the storm surge intensity in the Bohai Sea.

Countries in East Asia have set ambitious goals for the development of wind energy to meet the increasing energy demand and to mitigate anthropogenic climate change. However, few studies have investigated changes in wind energy over East Asia under future climatic conditions. In this study, we investigate future changes of 100‐m wind speed and wind energy potential over the CORDEX‐East Asia region under the Representative Concentration Pathway (RCP) 8.5 scenario, by using ensemble simulations from the regional climate model Consortium for small‐scale modeling in CLimate Mode (CCLM). A multivariate bias adjustment method based on the N‐dimensional probability density function transform is used to correct raw simulated horizontal wind components. The comparison between future climate (2021–2050 and 2070–2099) and the present climate (1971–2000) shows decreases in wind speed, wind power density, and wind energy output over most of the CORDEX‐East Asia region, especially in the tropics. Projected increases are pronounced over the Himalayan regions, the Indo‐China Peninsula, the South China Sea, and the western Pacific Ocean in summer and over northeastern China, parts of Western China and the Indo‐China Peninsula in winter. Interannual and intra‐annual variability of wind power density are projected to intensify significantly for most of the CORDEX‐East Asia region. The occurrence of weak wind speeds (11 m/s) are projected to decrease over most of the ocean.

The variability and energetics of M₂ internal tides during their generation and propagation through the Kuroshio flows northeast of Taiwan are investigated using a high‐resolution numerical model. The corrugated continental slopes, particularly the I‐Lan Ridge and Mien‐Hua Canyon, are first identified as the energetic sources of M₂ internal tides. The domain‐integrated M₂ barotropic‐to‐baroclinic conversion rate under the Kuroshio influence is ~2.35 GW, ~0.9 GW of which is generated at the I‐Lan Ridge, ~0.93 GW at the Mien‐Hua Canyon, and ~0.52 GW at the north shelf. The M₂ internal tide generation is influenced by the horizontally varying, zonally tilting stratification associated with the Kuroshio. In this situation, the conversion rate decreases by ~30% at the I‐Lan Ridge but increases to within ~10% at the Mien‐Hua Canyon and north shelf, in comparison to the simulation initiated with horizontal homogeneous stratification. Internal tides from multiple sources interfere to form a three‐dimensional baroclinic field. The interference by the internal tides from the Mien‐Hua Canyon and north shelf is refracted by the Kuroshio and exhibits a mesoscale gyre pattern, which can explain the frequent occurrence of internal solitary waves. An energetic along‐slope tidal beam (TBKC) from the I‐Lan Ridge radiates southward against the northward Kuroshio flows, causing strong vertical displacement, which favorably compares with recently reported field measurements. The M₂ internal tide energy dissipates primarily near the source sites, and the remaining energy radiates outward over limited distances. Complex topographic features and background currents enhance the internal tide dissipation, which induces strong, inhomogeneous diapycnal mixing.