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The spatiotemporal variability of oceanic fronts in the Indonesian seas was investigated using high-resolution satellite observations. The study aimed to understand the underlying mechanism driving these fronts and their impact on chlorophyll-a variability. A high value of frontal probability was found near the coasts of major islands, exhibiting a distinct seasonal cycle with peaks occurrences during austral winter. The distribution variability of chlorophyll-a was generally consistent with the presence of active frontal zones, although a significantly positive relationship between fronts and chlorophyll-a was limited to only some specific areas, e.g., south Java Island and the Celebes Sea. Wind-driven upwelling played a major role in front generation in the Java upwelling region and enhanced frontal activity can promote the growth of phytoplankton, leading to higher chlorophyll-a. Furthermore, the study demonstrated that wind patterns preceded variations in front probability and chlorophyll-a by approximately two months. This lag suggests that the spatiotemporal variability of fronts and chlorophyll-a in this region is primarily influenced by the monsoon system. In addition, the sea surface temperature (SST) simultaneously modulated the chlorophyll-a variability. Negative SST anomalies were typically associated with positive anomalies in front probability the chlorophyll-a in most areas. Notably, the interannual variability of fronts and chlorophyll-a are prominent in the Java upwelling region. During El Niño years, this region experienced an enhanced monsoon, resulting in a negative SST anomaly alongside positive anomalies in front probability and chlorophyll-a. A comprehensive description and underlying dynamics of frontal activity in the Indonesian seas are provided by this study. The findings are helpful to delineate the variability in chlorophyll-a, thereby facilitating the future understanding of local primary production and the carbon cycle. Significance Statement: As typical mesoscale processes, oceanic fronts have significant impacts on biological processes and fisheries in marginal seas. The complex spatiotemporal variability of fronts and their effects on biological processes in the Indonesian seas remain poorly understood. This study aimed to address this knowledge gap by investigating the seasonal and interannual variability of fronts and their influence on chlorophyll-a, a key indicator of phytoplankton biomass and primary productivity. The study identified a high frontal probability in south Java Island during austral winter and El Niño years. Wind-driven upwelling was found to be a major factor in front generation and promoting phytoplankton growth. The findings of this study will improve the theoretical knowledge of regional dynamics, local primary production, and the carbon cycle in the Indonesian seas, benefiting fisheries management and ecosystem conservation efforts. [ABSTRACT FROM AUTHOR]

The ocean behaves as a typical multiscale fractal structure, whose dynamic and thermal variabilities extend over a wide range of spatial scales, r, spanning from 10−3 to 107 m. Studying the statistical characteristics of multiscale fractal structures is crucial to understanding the interactions and energy cascade processes between different spatial scales. Remote sensing data are one of the best choices for revealing these statistical characteristics. This work analyzes the multiscale (1–1000 km) fractal structures of sea surface temperature (SST) from the Level-2+ (L2P) satellite orbit Visible Infrared Imaging Radiometer Suite (VIIRS) products over the Kuroshio Extension (KE) region (145°E–160°W, 20°N–50°N), using a conventional method (second-order structure function, D(r)) and a newly developed statistical method (spatial variance, V(r)). The results show that both the power-law distribution slopes of D(r) and V(r) are close to 2/3, which is equivalent to the −5/3 wavenumber spectrum. V(r) is found to be more robust when depicting the fractal structure and variance density, V'(r), compared with D(r). V'(r) is slightly larger at the mesoscale (50–150 km) than at the large scale (higher than 150 km) and is much smaller than that at the submesoscale (smaller than 50 km). Additionally, V'(r) has an indiscernible diurnal variation but remarkable seasonal and latitudinal variations. For the seasonal variability, the maximum V'(r) appears in winter at the large scale and mesoscale, and gradually shifts towards spring at the submesoscale, which implies that a forward energy cascade process may occur during this period. The maximum of the latitude-dependent V'(r) appears around 40°N for all the scales. It is consistent with the latitude of the strongest background SST gradient, indicating that the background SST front is the main source of the strong SST multiscale spatial variabilities over the KE region. This work benefits the application of other high-resolution remote sensing data in this research field, including the forthcoming Surface Water Ocean Topography (SWOT) satellite product. [ABSTRACT FROM AUTHOR]

An unprecedented warm sea surface temperature (SST) anomaly event, namely, the Blob, occurred in the northeast Pacific during the winter (October–January) of 2013/2014, causing substantial economic and ecological impacts. Here, we explore the driving forces of the Blob from both atmospheric and oceanic perspectives and show that the Blob primarily resulted from weak wintertime cooling due to the reduced air-sea heat flux transfer from the ocean to the atmosphere and the reduced horizontal advection of cold water in the upper ocean. Both mechanisms were attributed to an anomalous high-pressure system over the study region. Specifically, the anomalous air-sea heat flux, which was dominated by turbulent heat flux anomalies, was mainly induced by the increased air temperature (i.e., with a contribution of approximately 70%) and the weakened wind speed associated with the high-pressure system. The reduced horizontal heat advection was mainly due to the weakened winds acting on the ocean temperature meridional gradient. Using a regional ocean numerical model with different experimental runs, we evaluated the contributions of air temperature and wind drivers to the Blob at both the surface and subsurface of the ocean. The Blob was absent when the model was forced by climatology-air-temperature. Both the SST and integrated ocean heat content (OHC, 0–150 m) decreased, and the mixed layer depth (MLD) was deeper than that in the control run forced by real atmospheric conditions. In the climatology-winds experiment, obvious warm anomalies still existed, which were similar to but weaker than the control run. The SST (OHC) and MLD values in the climatology-winds run were between those of the climatology-air-temperature run and the control run. Compared to former studies that attribute the formation of the Blob to an anomalous air-sea heat flux and horizontal advection mainly induced by reduced winds, our study demonstrates that anomalous warm air temperatures played a more important role in its formation. [ABSTRACT FROM AUTHOR]

It has been suggested that the intraseasonal sea surface temperature (SST) variability in the tropical oceans can be amplified by the diurnal cycle of SST (dSST). Here, by analyzing the global tropical moored buoy array for the first time, we find that the intraseasonal SST variability is indeed amplified by the dSST in most of the tropical oceans, especially in the Indo‐Pacific warm pool, but weakened in the equatorial cold tongues of the Pacific and Atlantic Oceans. Such a divergent response is associated with the difference in atmosphere‐ocean interaction processes over these two regions. In the warm pool region, SST responds to the intraseasonal atmospheric variability, resulting in in‐phase intraseasonal fluctuations between SST and dSST that amplify the intraseasonal SST variability. However, in the cold tongue region, SST drives the atmospheric changes, which leads to out‐of‐phase intraseasonal fluctuations between SST and dSST and thus the inhibition of the intraseasonal SST variability. Plain Language Summary: The diurnal cycle is a fundamental timescale in the climate system, which has important nonlinear impacts on the variability on longer timescales. Previous studies have suggested that the diurnal cycle of sea surface temperature (SST) amplifies the SST variability on intraseasonal timescales of 20–90 days in the tropical region. By analyzing ocean temperature measurements from moored buoys located in the global tropical oceans, we find that the aforementioned amplification effect does exist in most of the tropical oceans, however, the diurnal cycle of SST weakens the intraseasonal SST variability in the equatorial eastern Pacific and Atlantic Oceans. Such contrasting results are associated with the different interaction processes between the atmosphere and the ocean over these regions. This is the first report of the inhibition effect, adding a new insight into the impact of the diurnal cycle of SST on intraseasonal SST variability. Key Points: The rectification of the intraseasonal sea surface temperature (SST) variability by the SST diurnal cycle is revealed by the global tropical moored buoy arrayThe intraseasonal SST variability is enhanced by the diurnal cycle in the Indo‐Pacific warm pool but weakened in the equatorial cold tonguesThese divergent responses are associated with the difference in atmosphere‐ocean interaction processes over these two regions [ABSTRACT FROM AUTHOR]

The Model for Prediction Across Scales (MPAS) is used to simulate the East Asian winter monsoon (EAWM) over the 2011–2020 winter. The 45 day hindcasts are made with 30 km horizontal resolution and constructed to a time-lagged ensemble system. The climatology, the major modes of EAWM variability, and the blocking activities are examined. The evaluation results reveal that MPAS can simulate the climatologic characteristics of EAWM reasonably, with a surface cold bias of 4% and a positive rainfall bias of 9% over East Asia. MPAS can perform skillfully in the forecasts of surface temperature probability of East Asia and is more reliable in detecting below normal and above normal events. The features that influence the EAWM variability are also analyzed. MPAS simulates reasonably in the occurrence frequency of blocking high in both locations and duration time. The empirical orthogonal function analysis also shows that MPAS can capture the two major modes of the surface temperature of EAWM. On the other hand, it is also found that a biased sea surface temperature may modify the circulations over the Western Pacific and affect the simulated occurrence frequency of cold events near Taiwan during winter. [ABSTRACT FROM AUTHOR]

Sixteen years of satellite observational data in the Northwestern Pacific Ocean are used to describe the variability in the sea surface temperature (SST) gradient and its impact on chlorophyll-a concentrations (Chl-a). Spatially, a meridional dependence is identified in which the SST gradient increases to the north in association with elevated Chl-a. Temporally, the seasonal variability shows a large SST gradient and high Chl-a in winter and spring, while the SST gradient and Chl-a are much lower in summer. The seasonal variability in Chl-a leads the variability in the SST gradient by one month. A significant correlation between the SST gradient and Chl-a in the anomalous field is obtained only in the western section of the Kuroshio extension (KE) and the highest correlation is identified without any lags. An index for the section is defined as the proportion of the number of times that the SST gradient magnitude is anomalously large in each year, and the index is highly related to the stability of the KE and has a prominent influence on Chl-a in the region. An anomalously large positive (negative) SST gradient magnitude occurs when the KE is unstable (stable) and the corresponding Chl-a is high (low). [ABSTRACT FROM AUTHOR]

The ocean-atmosphere interaction over a summer upwelling system in the South China Sea (SCS) is investigated. A strong positive correlation between sea surface temperature (SST) and wind stress exists near the southeast coast of Vietnam, where strong SST fronts occur during summertime. This air-sea coupling relationship indicates that the ocean drives the atmosphere and receives feedback at the oceanic mesoscale, in contrast with the case for large scales. The coupling process off the southeast coast of Vietnam is initiated by coastal upwelling, which is driven by wind-induced offshore Ekman transport in early summer. Cold upwelled water reduces the wind stress aloft and results in a positive wind stress curl. The Ekman pumping induced by the wind stress curl is on average 18% stronger than that of the offshore Ekman transport and occupies a larger extent. As the upwelling season terminates by the end of summer, the air-sea coupling also diminishes. Our results reveal that the SST-induced wind stress curl anomalies have a positive feedback on SST change and that wind stress curl anomalies can further reduce the SST magnitude by as much as 0.5 °C. The factors influencing the strength and interannual variability in ocean-atmosphere interaction are also explored. The wind stress directional steadiness (WSDS) plays an important role in the air-sea coupling over the SCS SST frontal regions. The coupling between the wind stress and SST can fully develop under high WSDS. Furthermore, the interannual variabilities in air-sea coupling are largely impacted by the El Niño events by changing the regional wind. The influence of a strong El Niño event on the summer upwelling system is characterized by a warmer SST and declining winds, which are associated with weakened SST gradients and mesoscale air-sea coupling. The present study reveals that the interannual climate signals have a significant impact on the mesoscale ocean-atmosphere interaction in a typical upwelling system. It provides an example for investigation of seasonal and interannual variability of mesoscale air-sea coupling in other coastal regions. • Prominent ocean-atmosphere interaction is identified in an upwelling system. • Ocean drives the atmosphere and receives feedback at the oceanic mesoscale. • Air-sea coupling is characterized by seasonal and interannual variability. • Wind with steady direction sustains the ocean-atmosphere interaction. • Positive correlation exists between sea surface temperature and wind stress. [ABSTRACT FROM AUTHOR]

Satellite observations from 2002 to 2017 were used to investigate the spatial distribution and temporal variability of chlorophyll-a (Chl-a) in the South China Sea (SCS). High levels of Chl-a were mostly found near the coasts of China and Vietnam, with a significantly long-term increasing trend. Large seasonal variability was found in the northern SCS and southeast of Vietnam. The Chl-a levels reached the maximum in winter and minimum in summer for majority of the SCS, while the seasonal variability to the southeast of Vietnam was out of phase. The monsoon winds and sea surface temperatures were the most important determinants impacting the distribution and variability of Chl-a along with other associated and influential environmental drivers, e.g., wind stress curl, frontal activity, and sea level anomalies. High correlation coefficients for the seasonal variability between Chl-a and other factors were found in a majority of the SCS, especially in the northern and central parts. The coefficients to the southeast of Vietnam were not valid at seasonal scales, but Chl-a and other factors were significantly correlated at the monthly anomalous fields. This observation occurred because the nutrient supply was mainly determined by local dynamics, e.g., wind-induced coastal upwelling and offshore transport. The interannual variability indicated low levels of Chl-a southeast of Vietnam during El Niño years because of the weakened southwest monsoon. The study offered the first comprehensive description of Chl-a in the SCS at seasonal, anomalous, and interannual variability scales and an analysis of the potential contributing dynamical processes. • Fifteen years of chlorophyll-a satellite data are examined in the South China Sea. • Multiple factors related to the variability of chlorophyll-a are investigated. • This is the first regional study of chlorophyll-a variability that is based on anomaly fields of dynamic factors. • Alongshore wind drives the offshore transport of Chlorophyll-a in the South China Sea. [ABSTRACT FROM AUTHOR]

The implicit equal-weights variational particle smoother (IEWVPS) is a combination of the particle filter (PF) and weak-constraint 4-dimensional variational (4D-Var) method, that inherits the merits of both. The IEWVPS avoids the filter degeneracy of particle filters through an implicit equal-weights scheme and reduces the root mean square deviations (RMSDs) by introducing the 4D-Var method. This method has been tested using the Lorenz 96 model in a previous study, and we now implement it in the Regional Ocean Model System (ROMS), which is a realistic and complex ocean model. Two key problems, the representation of the analysis error covariance and the choice of the parameter α , were solved during this implementation. With an eddy-permitting model, satellite-based sea surface height (SSH) and sea surface temperature (SST) observations were assimilated with a set of 40 particles IEWVPS scheme. Compared with the ensemble 4D-Var method, the IEWVPS can reduce the bias introduced by perturbed atmospheric forcing, effectively improving temperature simulations in the upper 50 m while maintaining the RMSD of SSH at the same level. Therefore, the cooling effect caused by typhoons in the upper ocean is better characterized under the IEWVPS scheme than with previously used method. The ratio of RMSD to the ensemble spread indicates that the ensemble quality of the IEWVPS is much better than that of the ensemble 4D-Var. In addition, the computational cost of the IEWVPS is only slightly larger than that of the ensemble 4D-Var. One additional tangent linear model integration, one additional nonlinear model integration, and perturbation fields inputs/outputs are still needed. • A non-linear hybrid data assimilation method of particle filter and 4D-Var is implemented in ROMS. • The new hybrid method can achieve more improvements of typhoon induced cooling effect than traditional 4D-Var method. • The simulation bias of SST can be relieved by using the new hybrid method. • The new hybrid method can improve the ensemble quality. [ABSTRACT FROM AUTHOR]