Mesoscale ocean vortices are common phenomenon and fairly distributed over the global oceans. In this study, mesoscale vortex in the South China Sea is identified by processing of AIPOcean data. The characteristic parameters of the identified vortex are extracted by using Okubo-Weiss (OW) method. The empirical sound velocity formula and interpolation method are used to obtain the spatial characteristics of temperature and sound velocity of the mesoscale vortex. After this, a theoretical model based on the Gaussian method is established to fit and simulate the vortex parameters. Using this model, the influence of mesoscale vortex strength, cold and warm vortex, vortex center position and sound source frequency on sound propagation are analyzed in COMSOL software. Finally, the actual parameters of the identified vortex are compared with the ideal Gaussian vortex model. It is found that different types of mesoscale vortices have different effects on the underwater sound propagation characteristics. Cold vortices, for example, cause the sound energy convergence zone to move toward the sound source, reducing the convergence zone’s span, whereas warm vortices cause the sound energy convergence zone to move away from the sound source, increasing the convergence zone’s span. Furthermore, the stronger the mesoscale vortices, the greater the impact on the sound field. Our COMSOL-based results are consistent with previous research, indicating that this model could be useful for studying underwater acoustic propagation in vortices.
2016 and 2017 were marked by strong El Niño and weak La Niña events, respectively, in the tropical East Pacific Ocean. The strong El Niño and weak La Niña events in the Pacific significantly impacted the sea surface temperature (SST) in the tropical Indian Ocean (TIO) and were followed by extreme negative and weak positive Indian Ocean Dipole (IOD) phases in 2016 and 2017, which triggered floods in the Indian subcontinent and drought conditions in East Africa. The IOD is an irregular and periodic oscillation in the Indian Ocean, which has attracted much attention in the last two decades due to its impact on the climate in surrounding landmasses. Much work has been done in the past to investigate global climate change and its impact on the evolution of IOD. The dynamic behind it, however, is still not well understood. The present study, using various satellite datasets, examined and analyzed the dynamics behind these events and their impacts on SST variability in the TIO. For this study, the monthly mean SST data was provided by NOAA Optimum Interpolation Sea Surface Temperature (OISST). SST anomalies were measured on the basis of 30-year mean daily climatology (1981–2010). It was determined that the eastern and western poles of the TIO play quite different roles during the sequence of negative and positive IOD phases. The analysis of air-sea interactions and the relationship between wind and SST suggested that SST is primarily controlled by wind force in the West pole. On the other hand, the high SST that occurred during the negative IOD phase induced local convection and westerly wind anomalies via the Bjerknes feedback mechanism. The strong convection, which was confined to the (warm) eastern equatorial Indian Ocean was accompanied by east–west SST anomalies that drove a series of downwelling Kelvin waves that deepened the thermocline in the east. Another notable feature of this study was its observation of weak upwelling along the Omani–Arabian coast, which warmed the SST by 1 °C in the summer of 2017 (as compared to 2016). This warming led to increased precipitation in the Bay of Bengal (BoB) region during the summer of 2017. The results of the present work will be important for the study of monsoons and may be useful in predicting both droughts and floods in landmasses in the vicinity of the Indian Ocean, especially in the Indian subcontinent and East African regions.
Sea surface temperature (SST) and isothermal layer depth (ILD) are important oceanic parameters and could play a significant role in understanding the upper thermal structure as well as improve the predictive capability of monsoons in the tropical oceans. In a disparate departure from the past research, the present study investigates the seasonal variability of SST and ILD in association with the monsoon cycle in the Arabian Sea and Sea of Oman regions by examination of Argo datasets for 2016-17. In this study, the ILD climatology is determined from temperature profiles provided by the Argo floats based on a threshold technique
T
z
≥
SST
−
1
°
C
to investigate the region of stronger and weaker monsoon wind forcing. For SST, values of temperature are used nearest to the sea surface (depth
z
≤
5 m). The region is split into four distinct zones for an accurate description of the monsoon cycle: the south Arabian Sea, the central Arabian Sea, the north Arabian Sea, and the Sea of Oman. It is observed that summer monsoon is more pronounced in the south-central basin of the Arabian Sea, where ILD is deepening (>100 m in September 2016) mainly due to stronger wind forcing in this region. On the contrary, the Sea of Oman region is displayed with smaller ILD amplitude (<10 m in June 2016) with larger SST, meaning that this region is weakly influenced by the summer monsoon. The seasonal relationship established between ILD variability and monsoon cycle for 2016-17 shows that ILD could be a useful indicator for predicting summer monsoon in the Arabian Sea regions. Our analysis results indicate that the dynamics for SST variability are different in these regions and are influenced either by large-scale atmospheric forcing, such as the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), or by the effects of mesoscale variations occurring along the Oman-Arabian coast.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.