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BACKGROUND AND OBJECTIVES: Understanding the correlation between tidal rhythms and marine organism behavior is crucial. This extends beyond fluctuations in chlorophyll a concentrations and includes various biological processes in the marine environment. Awareness is key for a comprehensive perspective on the role of tidal forces, affecting ocean's physical aspects and life form diversity. This study aims to explore the complex relationship between tidal movements and chlorophyll a concentrations in the northern Bay of Bengal, focusing on how tidal rhythms affect chlorophyll a concentrations. METHODS: The analyzed variables include tidal parameters, such as lunar semidiurnal tidal characteristics and Simpson-Hunter parameters, as well as sea level, tidal current, and current magnitude, obtained from the Tidal Model Driver. Additionally, hourly chlorophyll a data for January 2022 were acquired from the geostationary meteorological satellite Himawari-8, and the rate of change of chlorophyll a was determined through chlorophyll a calculations. This study employs wavelet analysis, applying continuous wavelet transform and wavelet transform coherence for chlorophyll a, rate of change of chlorophyll a, sea level, tidal current, and current magnitude, to explore oscillation patterns and temporal correlations within the marine ecosystem of the northern Bay of Bengal. FINDINGS: Lunar semidiurnal tidal amplitudes increase toward the north, peaking at the Sagar and Ramree Islands, and tidal phases rise from south to northeast. Most of the bay, categorized by <0.25 Formzahl values, experiences semidiurnal tides. Surface lunar semidiurnal elliptic currents, stronger in the north and east, flow clockwise and turn counterclockwise toward the south. The Simpson-Hunter parameter indicates heightened tidal mixing, particularly along the northern and eastern coasts. Region 2 showed the highest mean chlorophyll a concentration (12.58 milligram per cubic meter), whereas Region 1 showed the lowest mean chlorophyll a concentration (0.79 milligram per cubic meter). Similar trends were observed for tidal current and current magnitude. The continuous wavelet transform analysis provides data on chlorophyll a and the rate of change of chlorophyll a within 6, 12, and 24 hours, sea level changes within 8-16 hours, and consistent tidal effects on tidal current and current magnitude in the range of 5-7 hours. The wavelet transform coherence analysis highlights the relationships between chlorophyll a and sea level over 12 and 24 hours periods and between chlorophyll a and current magnitude. Furthermore, the wavelet transform coherence analysis examines the rate of change in chlorophyll a in relation to tidal currents over 6, 12, and 24 hours. CONCLUSION: Tides remarkably affect chlorophyll a concentrations. There are strong links between chlorophyll a concentrations and key tidal aspects, such as sea level and current magnitude. Higher tidal variables correlate with increased chlorophyll a concentrations and are related to the Simpson-Hunter parameter, indicating that regions with vigorous mixing show higher chlorophyll a concentrations. This finding highlights the major role of tidal forces and variations in the chlorophyll a concentrations in the Bay of Bengal. The wavelet transform coherence analysis of chlorophyll a, sea level, and current magnitude data in Regions 1, 2, and 3 show notable coherence in all areas.

BACKGROUND AND OBJECTIVES: This study aimed to investigate the long-term relationship between chlorophyll-a, sea surface temperature, and sea surface salinity monthly from January 2015 to December 2021. It was carried out in the Northern Bay of Bengal, which experiences extreme monsoons, in the southwest monsoon and northeast monsoon from June to September and November to February, respectively. Monsoon is the main cause of changes in chlorophyll-a, sea surface temperature and sea surface salinity. METHODS: The seasonal model was used to examine the relationship between these three parameters, which were obtained using the Copernicus Marine Environment Monitoring Service data. The seasonal model was used to observe periodic patterns and predict parameters based on their regularity. Meanwhile, Pearson's correlation analysis was conducted to determine the relationship between chlorophyll-a, sea surface temperature and sea surface salinity. FINDINGS: This study found that the three parameters, namely chlorophyll-a, sea surface temperature, and sea surface salinity, follow the monsoon pattern, as shown in the seasonal model. The minimum value of chlorophyll-a occurred in February, March and April, while the maximum value of approximately 2 milligram per cubic meter occured at stations 1, 2, 3, 4, 5 and 7, but at 9 and 10, it increased to 12 - 14 mg/m3. This indicates that station positions are very sensitive to changes in chlorohophyll-a values. When the southwest monsoon occurred, it reached the maximum. Furthermore, the minimum sea surface temperature values occurred in January and at almost every station in the year. It was shown to be associated with the northeast monsoon, which causes winter. On the sea surface temperature graph, several peaks were observed in positive local extremes yearly at almost all stations. The maximum sea surface temperature occurred in May, June, and July, according to the shape of the graph, which peaked in the middle of the year. The sea surface salinity graph formed a peak and valley which occurred yearly in May or April, as well as September and October, respectively. CONCLUSION: Chlorophyll-a had 1 trough and 1 peak, with the sea surface temperature graph possessing only 1 peak, while the sea surface salinity graph had 1 peak and 1 trough, respectively. These graph patterns implied that chlorophyll-a first achieved a minimum value before reaching the máximum. The sea surface temperature graph had a maximum value in the middle of the year, while the minimum occurred at the beginning or end. Moreover, the sea surface salinity graph first reached the maximum value and then declined to the minimum.

The waters of the Bay of Bengal (BoB) are influenced by the northeast monsoon (November-February) and the southwest monsoon (June-September). This study aims to determine the relationship between sea surface temperature (SST), sea surface salinity (SSS), and chlorophyll-a (Chl-a) during January 2021 in the BoB. The method used in this study is the method of correlation analysis, hypothesis testing, and analysis of variance using monthly average data for January 2021. The data comes from the Copernicus Marine Environment Monitoring Service (CMEMS) portal. Our analysis showed that high Chl-a was inversely related to low SST and SSS conditions and vice versa. This finding confirms the results of other previous studies. Medium and negative correlations occurred for the Chl-a - SST and Chl-a - SSS pairs. Meanwhile, the SST- SSS pair shows a strong and positive correlation. The hypothesis test shows that the conclusions drawn from these correlation relationships are acceptable. Furthermore, from the analysis of variance obtained, it was found that Chl-a had a significant effect on variations in SST and SSS, while SST had a significant effect on variations in SSS.

This study analyzes the relationship between sea surface chlorophyll-a concentration (SSC), sea surface temperature (SST), and wind velocity in the Indian Ocean and a part of the South China Sea during February and August 2022. Satellite data include SSC (mg m −3 ) and SST (°C) from NASA Ocean Color, and wind velocity (m s −1 ) from Copernicus ERA5. Pearson correlation analysis was used to evaluate relationships among these variables. The results show that average SSC in February was 0.23 mg m −3 , decreasing to 0.15 mg m −3 in August. Average SST was 29.98°C in February, increasing to 30.25°C in August, while wind velocity averaged 4.19 m s −1 in February and 4.23 m s −1 in August. A weak positive correlation was found between SSC and SST, with coefficients of 0.31 in February and 0.15 in August, indicating that rising SST slightly influence SSC. SSC and wind velocity exhibited a weak negative correlation (−0.31 in February and −0.07 in August), suggesting stronger winds reduce SSC. SST and wind velocity showed a strong negative correlation (−0.76 in February and −0.85 in August), indicating that higher wind velocity lower SST. These findings reveal seasonal dynamics and interactions between atmospheric and oceanic factors affecting marine ecosystems. By understanding these relationships, this study contributes to sustainable management of tropical marine resources and offers insights for mitigating climate change impacts. The results are relevant for researchers and policymakers developing strategies to protect biodiversity and enhance resilience of tropical oceans.

This research is a preliminary study regarding the extraction of kinetic energy from sea tides in Aceh’s waters. Aceh’s waters have a reasonably long coastline (> 2000 km), which has not been studied and utilized much. The extraction of kinetic energy from ocean tides is based on the speed of currents and turbines. Hydrodynamic verification is based on sea-level data from TPXO7.2 and Geospatial Indonesia Agency (GIA). The tidal data is sufficiently consistent with the verification data from TPXO7.2 and GIA. Based on the results, the model succeeded in accurately describing the hydrodynamics currents in the research domain based on comparative verification data. The velocity of M2 tidal flow in the waters of West Aceh is relatively low, particularly in the waters of Ulee Lheue is 0.018 m/s while in Calang waters, it is 0.025 m/s. The maximum tidal energy in Ulee Lheue waters is 9, 142 × 10 −2 kW, with a daily power of 4.63 × 10 3 kW. In Calang waters, the maximum energy is 2, 449 × 10 −1 kW, while the daily power is 1, 0167 × 10 4 kW. These results indicate that Calang Waters (Aceh Jaya district) had more significant potential for tidal currents and energy than Ulee Lheue Waters (Aceh Besar district).

BACKGROUND AND OBJECTIVES: El Niño - Southern Oscillation is known to affect the marine and terrestrial environment in Southeast Asia, Australia, northern South America, and southern Africa. There has been much research showing that the effects of El Niño - Southern Oscillation are extensive. In this study, a simulation of an El Niño event is carried out, which is ideal in the vertical layer of the Pacific Ocean (0-250 meters). The fast Fourier transform is used to process the vertical modeling data so that the results can accurately represent El Niño. METHODS: A non-hydrostatic 3-dimensional numerical model is used in this research. To separate the signal produced and obtain the quantitative difference of each sea layer, the simulation results are analyzed using the fast Fourier transform. Winds blow from the west to the east of the area in perfect El Niño weather, with a reasonably high wind zone near the equator (forming a cosine). Open fields can be found on the north and south sides, while closed fields can be found on the west and east sides. Density is uniform up to a depth of 100 meters, then uniformly increases by 1 kilogram per cubic meter from 100 to 250 meters. FINDINGS: The results of the model simulation show that one month later (on the 37th day), the current from the west has approached the domain's east side, forming a complete coastal Kelvin wave. The shape of coastal Kelvin waves in the eastern area follows a trend that is similar to the OSCAR Sea Surface Velocity plot data obtained from ERDDAP in the Pacific Ocean in October 2015. In this period, the density at a depth of 0-100 meters is the same, while the density at the depth layer underneath is different. CONCLUSION: Strong winds could mix water masses up to a depth of 100 meters, implying that during an ideal El Niño, the stratification of the water column is influenced by strong winds. The eastern domain has the highest sea level amplitude, resulting in perfect mixing up to a depth of 100 m, while wind effect is negligible in the lower layers. The first layer (0-50 m) and the second layer (50-100 m) have the same density and occur along the equator, according to FFT. The density is different and much greater in the third layer (100-150 m).

The suspended sediment in Aceh waters was analysed from remote Sensing Reflectance of Aqua MODIS resolution 4 km. Two equations from previous studies were used to determine the magnitude and distribution of suspended sediment concentrations in Aceh waters during 2018. The results show the suspended sediment concentrations from the two equations are relatively the same even though they differ spatially (offshore and near the coast of Aceh waters). Based on Zhan et al. equation, the suspended sediment in Aceh waters have a maximum value of 0.786 mg/L and a minimum value of 0.589 mg/L. Meanwhile, based on Zhang et al. equation, the maximum and minimum suspended sediment in Aceh Waters are 0.639 mg/L and 0.271 mg/L, respectively. Based on these two equations, Krueng Kluet estuary located in the western part of Aceh has the highest suspended sediment. In contrast, Krueng Peusangan estuary in the eastern part of Aceh has a low sediment concentration. The highest suspended sediment in Aceh waters occurs in November to December and the low period is in April to September. The heavy rainfall encourages freshwater runoff and high suspended sediment in the mouth of the Aceh waters, especially in the western part of Aceh.

The Makassar Strait (MS) is the main passage through the Pacific to Indonesian waters, which divides the islands of Kalimantan and Sulawesi. These waters are rich with natural resources. The research objective was to determine the energy produced by the M2 tides in the Makassar Strait. Ocean currents and energy are analyzed from the output of a two-dimensional numerical model. The results showed that the tidal flow velocity in the Makassar Strait was above 1 m/s, especially in Balikpapan (1.1975 m/s,) Mamuju (1.3379 m/s), and Pantoloan/Palu (1.2728 m/s). While the power or tidal current energy in Balikpapan is 3, 6238 × 10 4 kWatt, Mamuju is 2, 0215 × 10 5 kWatt, and Pantoloan/Palu is 7, 4006 × 10 5 kWatt. The tidal energy is intense in Pantoloan/Palu compared to other stations.

This paper discusses an algorithm to find a similar subgraph called findSimSubG algorithm. A similar subgraph is a subgraph with a maximum number of edges, contains no isolated vertex and is contained in every Hamiltonian cycle of a Hamiltonian Graph. The algorithm runs only on Hamiltonian graphs with at least two Hamiltonian cycles. The algorithm works by examining whether the initial subgraph of the first Hamiltonian cycle is a subgraph of comparison graphs. If the initial subgraph is not in comparison graphs, the algorithm will remove edges and vertices of the initial subgraph that are not in comparison graphs. There are two main processes in the algorithm, changing Hamiltonian cycle into a cycle graph and removing edges and vertices of the initial subgraph that are not in comparison graphs. The findSimSubG algorithm can find the similar subgraph without using backtracking method. The similar subgraph cannot be found on certain graphs, such as an n-antiprism graph, complete bipartite graph, complete graph, 2n-crossed prism graph, n-crown graph, n-möbius ladder, prism graph, and wheel graph. The complexity of this algorithm is O(m|V|), where m is the number of Hamiltonian cycles and |V| is the number of vertices of a Hamiltonian graph.

The instability of the density of seawater causes the formation of internal waves in the sea. This phenomenon is difficult to observe visually but can be studied with a hydrodynamic model approach. This study investigates the internal waves caused by underwater obstructions (seamounts) and the stratified density with a two-dimensional marine hydrodynamic model. Four scenarios are simulated in studying internal waves. Two scenarios used one barrier with uniform density and stratified density (based on the Brunt Vaisala stability frequency N 2 = 5 x 10 -4 s -2 ). Meanwhile, the other two scenarios use two barriers with uniform density and stratified density (based on the Brunt Vaisala stability frequency N 2 = 5 x 10 -4 s -2 ). Based on the simulation results, it is known that the density conditions have a significant effect on the dynamics of ocean currents. In hydrodynamic simulations of one and two barriers with varying or stratified densities, current resonances and density resonances are formed underwater topography. Meanwhile, in uniform density, the currents formed the rotor, cavity, turbulence, and resonance with the underwater topography. Thus the current dynamics are stronger in the case of uniform density than in the stratified density. It has implications for differences in the mixing of suspended matter in the sea. So this study can be useful in the study of sediment transport, upwelling, the thermocline layer, energy from internal waves, and the distribution of plankton or fish larvae.