Float Data Research Articles

A neural network algorithm for quantifying seawater pH using Biogeochemical-Argo floats in the open Gulf of Mexico

Within the Gulf of Mexico (GOM), measurements of ocean pH are limited across space and time. This has hindered our ability to robustly monitor and study regional carbon dynamics, inclusive of ocean acidification, over this biogeochemically variable sea. The 2021 launch of Biogeochemical-Argo (BGC-Argo) ocean profiling floats that carry five sensors represented the entry of this particular ocean observing technology into this region. The GOM BGC-Argo floats have vastly increased the number of oxygen, nitrate, pH, chlorophyll-a fluorescence, and particulate backscattering profile observations within the “open GOM” region (>1,000 m water column depth). To circumvent a set of uncertainties associated with the collected sensor pH data, regionally trained neural network algorithms were developed to skillfully predict GOM pH (total scale, in situ temperature and pressure), which served as a secondary QC and sensor performance assessment tool. The GOM neural network pH (GOM-NNpH) algorithms were trained using a selection of climate quality CTD and bottle data (temperature, salinity, oxygen, nitrate, pressure, and location) collected as a part of NOAA’s Gulf of Mexico Ecosystems and Carbon Cruises (GOMECC). Neural network pH estimates were generated using the newly developed GOMNNpH algorithm and two widely used, globally trained neural network algorithms (Empirical Seawater Property Estimation Routines (ESPER) and CArbonate system and Nutrients concentration from hYdrological properties and Oxygen using a Neural-network (CANYON-B)) to compare algorithm performance against validation data. The results demonstrate the advanced skill of the GOM-NNpH in capturing water column variability and robustly reconstructing GOM pH profiles. Using a combination of concurrent float-measured seawater values of pressure, temperature, salinity, and oxygen, a GOM-NNpH algorithm was applied to two years of BGC-Argo float data. Resulting data were used to diagnose the performance of float pH sensors and to generate a time series of neural network estimated pH based on the collected float profiles. These algorithms emphasize the value of regionally-trained neural networks and their utility by the BGC-Argo community. Further, the GOM-NNpH algorithms can also be applied by a variety of users to estimate pH values in the open GOM in the absence of direct pH observations.

Impact of the Fujiwhara effect from tropical cyclones Seroja and Odette on ocean dynamic in Southern Indonesia: Insights from argo data and model analysis

Tropical cyclone (TC) disturbances can cause changes in ocean dynamics before, during, and afterwards. We employed an Argo data and ocean model product of Copernicus Marine Environment Monitoring Service (CMEMS) to address the gap in observations of the ocean response from the severe TC Seroja and its interactions with the tropical low TC Odette, known as the rare Fujiwhara effect phenomenon. Our study in southern Indonesia seawater was conducted between March and April 2021, beginning with reconciling the deviation of the CMEMS ocean model product by assessing the model accuracy to the Argo float data to build confidence in using the model for further analysis. Comparison revealed that the temperature model datasets have a higher correlation coefficient (∼0.95) with the Argo observation than the salinity model datasets. Further, we investigated the temporal evolution of vertical profiles and upper ocean responses both inside and beyond the TCs route zone. We discovered that the upper ocean response results in a colder and saltier surface with a recovery time of more than 15 days. Furthermore, as a result of the strong surface cooling, mixed layers inside the Seroja track were rapidly thickening following the passage of TC. Our findings provide insights into how the TCs Seroja and Odette affect the ocean layers, especially the primary ocean features and behaviours (temperature and salinity), using the Argo and model datasets.

Long-term responses of phytoplankton biomass to the ocean surface variables in the central parts of the Arabian Sea and the Bay of Bengal

The northern Indian Ocean has been warming steadily for over a half-century, especially the north-western Indian Ocean. It is widely reported that the increasing sea surface temperature in the global oceans decreases phytoplankton biomass and productivity. The impacts of long-term variations in the sea surface properties on the phytoplankton biomass (chlorophyll a) are least studied in the northern Indian Ocean. In this study, we have retrieved satellite, model, and ARGO float data sets to investigate the long-term variations in the distributions and trends of major oceanic variables for a better understanding of the respective changes that occurred in chlorophyll a concentration in the central regions of the Arabian Sea (AS) and the Bay of Bengal (BB). We have selected variables such as sea surface temperature (SST), sea surface salinity (SSS), photosynthetically available radiation (PAR), euphotic depth (ZEU), mixed layer depth (MLD), wind speed, mean sea level anomaly (MSLA), surface currents, etc., to relate with chlorophyll a. We found significant increasing trends in SST and positive-MSLA in both basins, and the chlorophyll a was decreased in the AS but contrastingly increased in the BB. Further data analysis revealed the possible reasons, such as seasonal changes in mean sea level anomaly and meridional currents, for the increasing trend of chlorophyll a in the central Bay of Bengal. The northward flow of the meridional currents during the southwest monsoon (SWM), transports the nutrient-rich water from the coastal upwelling zone of the southwest coast of India to the southern and central BB, and enhances chlorophyll a. Contrastingly, the southward flow of low-saline and nutrient-depleted Bay of Bengal water reduces the chlorophyll a. In addition, the large area of cold-core eddies found during the NEM enhanced the chlorophyll a in the central BB. Though contrasting trends between both basins in chlorophyll a distribution were found, the mean concentration of chlorophyll a in the northern Indian Ocean decreases. The present study signifies the importance of monsoon currents and eddies in regulating the chlorophyll a biomass and primary productivity in the AS and BB.

Mixing and Water Mass Transformation Over Discovery Bank, in the Weddell‐Scotia Confluence of the Southern Ocean

AbstractThe South Scotia Ridge, in the Atlantic sector of the Southern Ocean, is a key region for water mass modification. It is the location of the Weddell‐Scotia Confluence, an area of reduced stratification which separates the Weddell Gyre to the south and the Antarctic Circumpolar Current to the north, and which receives input of shelf waters from the tip of the Antarctic Peninsula. To elucidate the transformations over the ridge, we focus on one of its largest seamounts, Discovery Bank, which has previously been observed as hosting a stratified Taylor column that retains water for months to years, during which time water masses are entrained from north and south of the Weddell Front and steadily mixed. Data from ship‐deployed sensors and autonomous platforms are analyzed to quantify and understand the diapycnal mixing, heat fluxes and water mass transformations over the bank. Ocean glider and free‐profiling drifting float data show that the mid‐depth temperature maximum of the Circumpolar Deep Water (CDW) is eroded between the northern and southern sides of the bank, while diapycnal diffusivity is enhanced by up to an order‐of‐magnitude over its steeply sloping portions. This is accompanied by heat fluxes from the CDW layer being increased by up to a factor of six, which may contribute to a reduction in mid‐depth stratification. Tidal model analysis shows that the southern side of the bank hosts strong barotropic to baroclinic energy conversion (>150 N m−2), emphasizing the role of internal tides in modulating water mass transformations in the Confluence.

The Seasonal Variations of the Thermocline in the Banda Sea and its Water Mass Characteristics

This research was conducted to examine the seasonal variations in the Banda Sea's thermocline layer and its water mass characteristics. The research was conducted by analyzing Argo Float data. The data consists of six observation stations in West Season and Transitional Season II, and four stations in Transition Season I and East Season The thermocline layer thickness was identified based on the depth where the temperature decreased ≥ 0.05oC/m. The thermocline layer's distribution of depth and thickness and the distribution of temperature and salinity seasonally in the thermocline layer were analyzed with Microsoft Excel 2010. The analysis results showed that East Season and Transition Season II have a shallower upper boundary depth of the thermocline layer, a deeper lower boundary of the thermocline layer, and the thermocline layer is thicker when compared to the West Season and Transition Season I. The average temperature distribution is higher and the average salinity is lower in the West Season and Transition Season I. The mean rate of change in salinity and temperature in the thermocline layer seasonally ranged from 0.002-0.004 PSU/m and 0.06-0.08oC/m. The thermocline layer's stratification is stronger in the West Season and Transition Season I.

Prediction Performance of Ocean Temperature and Salinity in Global Seasonal Forecast System Version 5 (GloSea5) on ARGO Float Data

Prediction Performance of Ocean Temperature and Salinity in Global Seasonal Forecast System Version 5 (GloSea5) on ARGO Float Data

Argo data anomaly detection algorithm based on selective ensemble of fuzzy clustering

Abstract Argo profiling float data is a crucial data source for fundamental research and predictive forecasting operations in oceanography and environmental science. However, compiling and organizing such datasets demands considerable time and human resources. Therefore, the quest for effective methods of detecting anomalies in Argo data is of paramount importance. In this regard, we propose three improvement strategies within the stacking ensemble framework: preserving the original training set, weighting base model outputs, and combining the two former methods. The aim is to explore implicit relationships within the data, enhance model prediction diversity, and improve Accuracy. Additionally, in the selection of base models, to address the challenge of conventional clustering-based ensemble algorithms in achieving high levels of both diversity and accuracy among base learners, we introduce a selective ensemble method based on C-means clustering. This method selects base learners for the ensemble based on weighted scores derived from membership and performance evaluation metrics. Both of these enhancement approaches demonstrate effective application and improved detection performance when applied to Argo data.

Evaluation of Vertical Patterns in Chlorophyll‐A Derived From a Data Assimilating Model of Satellite‐Based Ocean Color

AbstractSatellite‐based sensors of ocean color have become the primary tool to infer changes in surface chlorophyll, while BGC‐Argo floats are now filling the information gap at depth. Here we use BGC‐Argo data to assess depth‐resolved information on chlorophyll‐a derived from an ocean biogeochemical model constrained by the assimilation of surface ocean color remote sensing. The data‐assimilating model replicates well the general seasonality and meridional gradients in surface and depth‐resolved chlorophyll‐a inferred from the float array in the Southern Ocean. On average, the model tends to overestimate float‐based chlorophyll, particularly at times and locations of high productivity such as the beginning of the spring bloom, subtropical deep chlorophyll maxima, and non‐iron limited regions of the Southern Ocean. The highest model RMSE in the upper 50 m with respect to the float array is of 0.6 mg Chl m−3, which should allow the detection of seasonal changes in float‐based biomass (varying between 0.01 and >1 mg Chl m−3) but might hinder the identification of subtle changes in chlorophyll at narrow local scales. Both model and float profiling data show good agreement with in situ data from station ALOHA, with model estimates showing a slight accuracy edge in inferring depth‐resolved observations. Uncertainties in float bio‐optical estimates impede their use as a reliable benchmark for validation, but the general qualitative agreement between model and float data provides confidence in the ability of model to replicate biogeochemical features below the surface, where data is not directly constrained by the assimilation of satellite ocean color.

Different mechanisms for enhanced ocean response and feedback during sequential super typhoons

Relative to a single typhoon, the ocean response and feedback mechanisms during sequential super typhoon process have yet to be fully understood. The upper ocean responses to super typhoons Trami and Kong-Rey that occurred sequentially in autumn 2018 over the northwestern Pacific (NWP) Ocean were investigated using multi satellite and Argo float data. As a slow-moving typhoon, the location of maximum sea surface temperature (SST) cooling induced by Trami was determined by the typhoon's translation speed and the preexisting cyclonic eddy (CE). The most significant SST cooling was observed near the abrupt turning point, where Trami nearly stalled over the ocean, rather than in the CE region, although the CE could enhance the SST cooling. For the subsequent, fast-moving typhoon Kong-Rey, the most significant SST cooling was observed in the CE region. Two different mechanisms (i.e., slow translation and cyclonic eddy) for the enhancement of SST cooling, salinity and chlorophyll-a were also compared. For salinity and chlorophyll-a concentration, slow translation speed plays a more important role than the preexisting cold eddy. Additionally, both typhoons experienced rapid weakening, suggesting that typhoon-induced negative feedback affects not only the intensification of the typhoon itself but also the subsequent typhoon. An analysis of data from Argo floats demonstrated that weak mixing and upwelling contributed to a three-layer structure in the upper ocean temperature on the left side of the typhoon track; strong upwelling played a more important role in the cooling of the whole upper ocean near the typhoon track center; and strong vertical mixing was the dominant factor for the two-layer temperature structure on the right side.

Deep Argo Observations of Antarctic Bottom Water in the Deep Fracture Zones of the Southwest Indian Ridge

AbstractThe Madagascar Basin is the primary pathway for Antarctic Bottom Water to ventilate the entire western Indian Ocean as part of the Global Overturning Circulation. The only way for this water mass to reach this basin is by crossing the Southwest Indian Ridge through its deep fracture zones. However, due to the scarcity of observations, the Antarctic Bottom Water presence has only been well‐established in the Atlantis II fracture zone. In May 2023, the Deep Madagascar Basin Experiment deployed three Deep SOLO Argo floats in the exit of the fracture zones that were more likely to transport Antarctic Bottom Water: Atlantis II, Novara, and Melville. These floats have been collecting temperature and salinity profiles every 3–5 days with high vertical resolution in the deep ocean. In the present paper, we use the first 7 months of float data to characterize the Antarctic Bottom Water in the deep fracture zone area, revisiting a half‐century puzzle about the Melville contribution. We also collected shipboard‐based profiles to calibrate float salinity and show it is within the Deep Argo program target accuracy. We find Antarctic Bottom Water in both Melville and Novara fracture zones, not only in Atlantis II. This is the first time the Novara contribution has been revealed. The floats also uncover their distinct properties, which may result from the different mixing histories.

Evaluation of Programming in C using WSM Method

Programming in C. The machine-oriented programming language C is mostly used to create many applications and operating systems, like Windows, as well as other complicated programmers, such the Oracle database, Kit, the Python interpreter, and games. Computer programmers and low-level programming applications are often written in the procedural or structured programming language C. Concatenation, data hiding, data compression, inheritance, and polymorphism are some extra aspects of C++ despite the fact that it is an object-oriented programming language. Multiple entities of the same type can be grouped together into a larger group using the C concept of an array. These entities or components may be user-defined data types or structures, such as integer, float, double, or float data types. C-written programmers compile and execute far more quickly than those written in other languages. This is because there are no additional processing overheads like garbage collection. As a result, when compared to other programming languages, the language is quick. An algorithm is a series of actions carried out in a preset order to address a challenge or finish a task. A function is a section of code that is called and carried out by other software elements. An operating system is made using it. The "C" programming language is used to create operating systems like Apple's OS X, Microsoft's Windows, and Symbian. It is utilized to create platforms for desktop and mobile devices. It is used to create compilers. One C feature that contains symbols for doing mathematical, relational, bitwise, conditional, or logical manipulations is the C operator. There are many built-in operators in the C programming language that can be used to carry out different tasks as needed by the application. C has an advantage over other dynamic languages since it is a statically typed programming language. Also, C is a compiler-based programming language, in contrast to Python and Java, which are interpreter-based. It expedites the compilation and execution of code. Weighted Sum works by multiplying the designated field values Indian Technical Institution or appraising the alternatives Analysis in Simply types, Enum types, Struct types, Nullable types. Evaluation parameters in Class types, Interface types, Array types, and Delegate types. Simply types, Enum types, Struct types, Nullable types. Class types, Interface types, Array types, and Delegate types. Nullable types got the first rank whereas Simply types have the lowest rank.

Exploring the relationship between sea ice and phytoplankton growth in the Weddell Gyre using satellite and Argo float data

Abstract. Some of the highest rates of primary production across the Southern Ocean occur in the seasonal ice zone (SIZ), making this a prominent area of importance for both local ecosystems and the global carbon cycle. There, the annual advance and retreat of ice impacts light and nutrient availability, as well as the circulation and stratification, thereby imposing a dominant control on phytoplankton growth. In this study, the drivers of variability in phytoplankton growth between 2002–2020 in the Weddell Gyre SIZ were assessed using satellite net primary production (NPP) products alongside chlorophyll-a and particulate organic carbon (POC) data from autonomous biogeochemical floats. Although the highest daily rates of NPP are consistently observed in the continental shelf region (water depths shallower than 2000 m), the open-ocean region's larger size and longer ice-free season mean that it dominates biological carbon uptake within the Weddell Gyre, accounting for 93 %–96 % of the basin's total annual NPP. Variability in the summer maximum ice-free area is the strongest predictor of inter-annual variability in total NPP across the Weddell Gyre, with greater ice-free area resulting in greater annual NPP, explaining nearly half of the variance (R2=42 %). In the shelf region, the return of sea ice cover controls the end of the productive season. In the open ocean, however, both satellite NPP and float data show that a decline in NPP occurs before the end of the ice-free season (∼ 80 to 130 d after sea ice retreat). Evidence of concurrent increases in float-observed chlorophyll-a and POC suggest that later in the summer season additional factors such as micro-nutrient availability or top-down controls (e.g. grazing) could be limiting NPP. These results indicate that in a warmer and more ice-free Weddell Gyre, notwithstanding compensating changes in nutrient supply, NPP is likely to be enhanced only up to a certain limit of ice-free days.

The Response of the Upper Ocean to Tropical Cyclones in the South Pacific

AbstractConsecutive Argo float profiles are used to observe upper ocean changes resulting from the passage of tropical cyclones (TCs) in the South Pacific between 2001 and 2023. Cross‐sectional composites of the ocean response are produced by normalizing the distance between the profile and cyclone track by the 34‐knot wind radius (R34) of each TC to better resolve the average changes in water properties. Surface cooling in the initial mixed layer (ML) extends from the center to about twice R34 and is stronger to the left of the TC track. Subsurface warming at the base of the ML is observed between 0.4 and 2 R34 on both sides of the track. Strong cooling is observed in a distinct core directly under the TC path, reaching temperature changes of over −1.6°C between 70 and 450 m depth. Significant upwelling of over 40 m displacement is observed within ±0.05 R34, extending to 1,000 m depth. Surface cooling (and subsurface warming at the base of the ML) are positively correlated with wind stress on the ocean from the TC, quantified by the Local Wind Power Dissipation (PDL), and negatively correlated with the energy required to destratify the upper ocean, defined by a Cooling Inhibition index (CI). Subsurface warming is common with low CI but is not observed with high CI. We demonstrate an improved method to analyze Argo float data for measuring TC‐upper ocean interaction in remote oceans and the usefulness of PDL and CI in calibrating the TC‐ocean interaction.

A Generalized Slab Model

Abstract We construct a generalized slab model to calculate the ocean’s linear response to an arbitrary, depth-variable forcing stress profile. To introduce a first-order improvement to the linear stress profile of the traditional slab model, a nonlinear stress profile, which allows momentum to penetrate into the transition layer (TL), is used [denoted mixed layer/transition layer (MLTL) stress profile]. The MLTL stress profile induces a twofold reduction in power input to inertial motions relative to the traditional slab approximation. The primary reduction arises as the TL allows momentum to be deposited over a greater depth range, reducing surface currents. The secondary reduction results from the production of turbulent kinetic energy (TKE) beneath the mixed layer (ML) related to interactions between shear stress and velocity shear. Direct comparison between observations in the Iceland Basin, the traditional slab model, the generalized slab model with the MLTL stress profile, and the Price–Weller–Pinkel (PWP) model suggest that the generalized slab model offers improved performance over a traditional slab model. In the Iceland Basin, modeled TKE production in the TL is consistent with observations of turbulent dissipation. Extension to global results via analysis of Argo profiling float data suggests that on the global, annual mean, ∼30% of the total power input to near-inertial motions is allocated to TKE production. We apply this result to the latest global, annual-mean estimates for near-inertial power input (0.27 TW) to estimate that 0.08 ± 0.01 TW of the total near-inertial power input are diverted to TKE production.

Heat content and temperature trends in the Mediterranean Sea as derived from Argo float data

The Mediterranean Sea is very sensitive to climatic changes due to its semi-enclosed nature and is therefore defined as one of the hotspots in future climate change projections. In this study, we use Argo float data to assess climatologies and trends in temperature and Ocean Heat Content (OHC) throughout the Mediterranean Sea and for specific sub-basins (e.g. Western and Eastern Mediterranean, Gulf of Lion, South Adriatic). The amount of the OHC, spatially averaged in bins of 1°x1° over the period from 2001 to 2020, increases from west to east in the Mediterranean Sea. Time series of temperature and OHC from 2005 to 2020, estimated in the surface and intermediate layers (5-700 m) and deeper layer (700-2000 m), reveal significant warming trends and an increase of OHC. The upper 700 m of the Mediterranean Sea show a temperature trend of 0.041 ± 0.012°C·yr-1, corresponding to an annual increase in OHC of 3.59 ± 1.02 W·m-2. The Western Mediterranean Sea (5-700 m) is warming fastest with an increase in temperature at a rate of 0.070 ± 0.015°C·yr-1, corresponding to a yearly increase in OHC of 5.72 ± 1.28 W·m-2. Mixing and convection events within convection sites and along boundary currents transport and disperse the temperature and OHC changes. Significant warming trends are evident in the deeper layers (700-2000 m) of the two deep convection sites in the Mediterranean Sea (Gulf of Lion, South Adriatic), with an exceptionally strong warming trend in the South Adriatic from 2013 to 2020 of 0.058 ± 0.005°C·yr-1, corresponding to a yearly increase in OHC of 9.43 ± 0.85 W·m-2. The warming of the different water masses will show its feedback on ocean dynamics and air-sea fluxes in the next years, decades, and even centuries as these warming waters spread or re-emerge. This will provide more energy to the atmosphere, resulting in more extreme weather events and will also stress ecosystems and accelerate the extinction of several marine species. This study contributes to a better understanding of climate change in the Mediterranean region, and should act as another wake-up call for policy makers and society.

Effects of Tropical Cyclone (TC) Hellen on the north-westward movement of chlorophyll in the northern Mozambique Channel.

An intense tropical cyclone (TC), TC Hellen, occurred in the northern Mozambique Channel on March 27, 2014, and moved from the east coast of the African continent to the northern Madagascar island. TC Hellen dramatically altered the marine environment in the northern Mozambique Channel, resulting in a significant chlorophyll-a (Chl-a) bloom. A giant surface Chl-a northwest-ward movement from the northwest coast of Madagascar Island was first observed after the passage of TC Hellen in the northern Mozambique Channel. The dynamic mechanisms of these phenomenon were studied by satellite remote sensing, multisource reanalysis data, and Argo float data. The results show that transient northwestward-moving eddies, upwelling, and winds had important effects on the Chl-a bloom and its northwestward movement. Ekman transport driven by coastal southeasterly winds entrained waters with high Chl-a concentrations to the northwest, while TC Hellen enhanced cyclonic eddy upwelling and uplifted nutrient-rich deep water to the upper ocean. This vertical mixing and upwelling in turn triggered the Chl-a bloom in the offshore surface layer. This study provides insight into the reflection of phytoplankton dynamics by TCs in the northern Mozambique Channel.

Carbon Outgassing in the Antarctic Circumpolar Current Is Supported by Ekman Transport From the Sea Ice Zone in an Observation‐Based Seasonal Mixed‐Layer Budget

AbstractDespite its importance for the global cycling of carbon, there are still large gaps in our understanding of the processes driving annual and seasonal carbon fluxes in the high‐latitude Southern Ocean. This is due in part to a historical paucity of observations in this remote, turbulent, and seasonally ice‐covered region. Here, we use autonomous biogeochemical float data spanning 6 full seasonal cycles and with circumpolar coverage of the Southern Ocean, complemented by atmospheric reanalysis, to construct a monthly climatology of the mixed layer budget of dissolved inorganic carbon (DIC). We investigate the processes that determine the annual mean and seasonal cycle of DIC fluxes in two different zones of the Southern Ocean—the Sea Ice Zone (SIZ) and Antarctic Southern Zone (ASZ). We find that, annually, mixing with carbon‐rich waters at the base of the mixed layer supplies DIC which is, in the ASZ, either used for net biological production or outgassed to the atmosphere. In contrast, in the SIZ, where carbon outgassing and the biological pump are weaker, the surplus of DIC is instead advected northward to the ASZ. In other words, carbon outgassing in the southern Antarctic Circumpolar Current (ACC), which has been attributed to remineralized carbon from deep water upwelled in the ACC, is also due to the wind‐driven transport of DIC from the SIZ. These results stem from the first observation‐based carbon budget of the circumpolar Southern Ocean and thus provide a useful benchmark to evaluate climate models, which have significant biases in this region.

Cold season Arctic strong cyclones enhance Atlantification of the Arctic Ocean

In recent years, as the Arctic Ocean’s warming trend has accelerated, there has been increasing attention on the process of Atlantification in the Arctic Ocean. This study focused on the Arctic Atlantic inflow zone (AAZ) as its research area. Multi-source reanalysis data and in-situ Argo float data were utilized to detect Arctic strong cyclones (ASCs) in the AAZ and analyze the resulting changes in the upper ocean. The findings reveal that during the cold season (October to March), influenced by ASCs’ intensity, frequency, tracks, and the concurrent weakening of ocean stratification, these cyclones can disrupt the cold halocline layer through mechanisms such as mixing and Ekman pumping. This process facilitates the transport of heat from the deep, warm and saline Atlantic Water within the ocean to the subsurface layers. Concurrently, ASCs during the cold season can enhance the process of Atlantification in the Arctic Ocean by intensifying the intrusion of the Barents Sea Branch. Additionally, the attenuation of oceanic stratification during ASCs is primarily driven by changes in salinity, particularly above the 100 m.

North Pacific Water Mass Contribution in the Northern Sea of Lembata Island, East Nusa Tenggara

As the Indonesian Throughflow (ITF) passes through the Flores Sea, we expect it will affect the water mass character in the northern sea of Lembata Island. Therefore, we examined the contribution of North Pacific (NP) water mass, i.e., the North Pacific Subtropical Water (NPSW) and the North Pacific Intermediate Water (NPIW) in the study area. We used 30 CTD casts from OTEC Geological Survey Center Expedition 2017 and ARGO float data, analyzed through the TS diagram and Optimum Multiparameter (OMP). The remnant of the NPSW (NPIW) core layer was found at 140-190 (220-330) m depth, deeper than it occurs in the NP source regime, and of previous pathway seas i.e. Makassar Strait. The OMP results show NPSW (NPIW) contribution is about 20-75 (50-70)%. Contrary to the ITF direction from the western pathway, the value of NP water mass contribution is larger in the eastern than in the western part of the northern sea of Lembata Island. We speculated the ITF flows away from the northern sea of Lembata Island, blocked by the headland in the eastern part of Flores Island. Then a small part of ITF is deflected back to the west, but unfortunately, no detailed current is available in the study area.

The abnormal track of super typhoon Hinnamnor (2022) and its interaction with the upper ocean

The upper ocean response and feedback to super typhoon Hinnamnor (2022) were systematically investigated considering multi-satellite, Array for Real-time Geostrophic Oceanography (Argo) float and reanalysis data. Hinnamnor experienced three main stages: a rapid intensification (RI) stage with a high moving speed along a westward track, a rapid weakening (RW) stage with a low moving speed along a northward sudden-turning track and a re-intensification (Re-I) stage with a moderate speed along a northward track. At the westward straight-line stage, despite the thin warm water layer (D26 < 40 m) and shallow mixed layer depth (MLD) (<20 m), its fast movement (∼8.1 m/s) tended to generate weaker sea surface temperature (SST) cooling (approximately 1 °C) and shorter cooling exposure. Consequently, the negative feedback decreased (negative feedback factor FSST:approximately−0.47to−0.20), causing Hinnamnor's rapid intensification (25 knots/6 h). Although the MLD was deeper (approximately 30 m) and the warm water layer was thicker (approximately 60 m) at the sudden-turning stage, the low translation speed (<2 m/s) tended to generate stronger SST cooling (approximately 5.6 °C) and longer cooling exposure, both of which intensified the negative feedback (FSST:approximately−0.8to−0.4), causing Hinnamnor's rapid weakening (−22 knots/6 h). At the northward stage, Hinnamnor re-intensified under a weak warm eddy with a moderate moving speed (3.6–5.4 m/s). An intriguing leftward bias in SST cooling occurred due to the preexisting cold eddy (CE) on the left side of the track. Analysis of the Argo floats in the RI and RW regions showed that the enhanced upwelling and vertical mixing yielded more significant SST cooling in the CE region at the RW stage due to the CE and low translation speed (<2 m/s). The differences between the RI and RW regions were remarkable when using the Hybrid Coordinate Ocean Model (HYCOM) global ocean model output.