Search

This study identifies seasonally-reversed trends in Kuroshio strength and sea surface temperatures (SSTs) within the western North Pacific (WNP) since the 1990s, specifically in the 22° N-28° N region. These trends are characterized by increases during summer and decreases during winter. The seasonally-reversed trends are a result of the asymmetric responses of the WNP to a shift towards the positive phase of the Atlantic multidecadal oscillation (AMO) around the same period. The positive AMO induces an anomalous descent over the North Pacific during summer, leading to the direct strengthening of the gyre. However, during winter, it triggers an anomalous descent over the tropical Pacific, which excites a poleward wavetrain impacting the WNP and causing gyre weakening. The associated responses of the East Asian monsoon and China Coastal Current contribute to the observed seasonally-reversed SST trends. It is noteworthy that the seasonally-reversed trends in gyre strength and SSTs are predominantly observed north of 20° N in the WNP. This limitation arises because the anomalous cyclone within the winter poleward wavetrain is located north of this latitude boundary. Specifically, the clearest trends in gyre strength are observed in the northern segment of the Kuroshio, while the manifestation of SST trends in the Taiwan Strait could potentially be attributed to the influence and enhancement of the East Asian monsoon and the China Coastal Current. Due to the limited length of observational data, statistical significance of some of the signals discussed is rather limited. A CESM1 pacemaker experiments is further conducted to confirm the asymmetric responses of the North Pacific to the AMO between the summer and winter seasons.

We present a highly unusual case in southern Taiwan where internal tides (ITs) completely reverse the barotropic currents. A 3D baroclinic model is first validated and confirms the unexpected tidal current in that area. A series of sensitivity simulations are then used to progressively reveal the exact cause. Contrary to popular belief, a large canyon in that area is not responsible for the flow reversal. Results from using a relaxation technique in the model together with an energy flux analysis indicate that the energy of the large ITs emanated from the Luzon Strait is converted to the barotropic energy near the steep slope, which generates a local circulation and reverses the tidal flow there. Plain Language Summary: Observed tidal current in southern Taiwan, especially near Kaohsiung area are opposite to the prediction from most tidal models that suggest the flood currents are directed northwestward in southern Taiwan. The observation, however, always shows the opposite flow direction, with southeastward tidal flow during flood and northwestward flow during ebb. In this study, we develop a 3D model and conduct sensitivity tests to reveal the exact cause of this unusual flow feature: the internal tides propagated from Luzon strait. Key Points: Unexpected tidal current near southern Taiwan is identifiedUsing different scenario model setups, internal tide is identified as the main reason to reverse the tidal current3D Baroclinic model setup is necessary to capture the unexpected flow feature [ABSTRACT FROM AUTHOR]

Global warming has enduring consequences in the ocean, leading to increased sea surface temperatures (SSTs) and subsequent environmental impacts, including coral bleaching and intensified tropical storms. It is imperative to monitor these trends to enable informed decision-making and adaptation. In this study, we comprehensively examine the methods for extracting long-term temperature trends, including STL, seasonal-trend decomposition procedure based on LOESS (locally estimated scatterplot smoothing), and the linear regression family, which comprises the ordinary least-squares regression (OLSR), orthogonal regression (OR), and geometric-mean regression (GMR). The applicability and limitations of these methods are assessed based on experimental and simulated data. STL may stand out as the most accurate method for extracting long-term trends. However, it is associated with notably sizable computational time. In contrast, linear regression methods are far more efficient. Among these methods, GMR is not suitable due to its inherent assumption of a random temporal component. OLSR and OR are preferable for general tasks but require correction to accurately account for seasonal signal-induced bias resulting from the phase–distance imbalance. We observe that this bias can be effectively addressed by trimming the SST data to ensure that the time series becomes an even function before applying linear regression, which is named "evenization". We compare our methods with two commonly used methods in the climate community. Our proposed method is unbiased and better than the conventional SST anomaly method. While our method may have a larger degree of uncertainty than combined linear and sinusoidal fitting, this uncertainty remains within an acceptable range. Furthermore, linear and sinusoidal fitting can be unstable when applied to natural data containing significant noise. [ABSTRACT FROM AUTHOR]