Deep-sea Research Part Ii-topical Studies in Oceanography最新文献

Bathymetric changes within estuarine and coastal waters can alter the hydrodynamic evolution of sea level and currents, which in turn can influence the ecosystem by altering material property distributions. Here we apply the Tampa Bay Coastal Ocean Model (TBCOM), with an unstructured, high-resolution grid to investigate the hydrodynamic response to bathymetric changes at the periphery of the Tampa Bay mouth over a relatively small area when compared to the whole model domain. Two separate numerical experiments are conducted with the same forcing, one using the original bathymetry and the other employing a revised synthetic bathymetry. The simulated sea level, amplitude and phase of the M2 tide, and associated currents are compared for the two experiments. Significant changes in water level (up to+/-10 cm) and current velocities (up to 20 cm/s) are found in the shallow peripheral area with the two different bathymetric data sets. These bathymetric influences are not limited to the locations where the bathymetric changes occur; they also extend to remote areas of the bay. Since Tampa Bay bathymetry varies with storm-induced sediment redistributions and human actives such as shipping channel dredging and beach nourishment, these findings emphasize the need for accurate and updated bathymetry for coastal ocean modeling and applications.

Quantifying the relative contributions of the export of particulate organic carbon (POC), dissolved organic carbon (DOC) and active fluxes by migrating organisms is essential to understand the functioning and vulnerability of the ocean's biological pump. However, these fluxes are rarely measured at the same time. Here we provide a first simultaneous comparison of these biological pump components in the region of South Georgia. We use a combination of in-situ data and an inverse model to calculate the DOC export and the suspended POC export and compare them to the sinking POC and active export. We find that, in this region, the DOC total export contributes about 6.6% (23.0–37.5 mg C m⁻² day⁻¹) to the total export flux, the active flux has no discernible contribution, and the sinking POC flux is dominant with a mean value of 409 mg C m⁻² day⁻¹. Diapycnal fluxes of DOC obtained from the cruise data constitute only a minor fraction (0.05–1.28 mg C m⁻² day⁻¹) of the total DOC export estimated by the inverse model and are exceeded on average by the diapycnal flux of suspended POC. Our results also indicate that the total export of DOC is driven by isopycnal transport. Future fieldwork in the region of South Georgia should focus on quantifying the isopycnal flux of DOC. Future measurement campaigns should also aim to simultaneously measure the particulate, dissolved and active components of the biological pump at contrasting locations and at different times to resolve the variability of their relative contribution.

Seasonal eddy kinetic energy (EKE) variability in the Banda Sea during 1993–2014 is studied from an energy budget perspective, based on the outputs of Ocean Forecasting Australian Model version 3. High EKE is confined within the upper 300 m of the western Banda Sea with the largest intensity exceeding 3 $\times$ 10³ J/m² in the northwest monsoon (NWM) season. In this strong EKE region during NWM, eddies derive almost two thirds of their kinetic energy from the direct wind power input (WP), with additional contributions from the barotropic (BT) and baroclinic instability (BC) of the background flow. Both WP and BT modulate the EKE seasonality and drive the peak energy during NWM, while BC strengthens in the southeast monsoon (SEM) season because of the intensified baroclinicity of the upper circulation. The westerly wind bursts associated with the Madden-Julian Oscillation (MJO), together with steep topography, facilitate more cyclonic eddy generation events in the western Banda Sea during NWM. During SEM, EKE becomes relatively moderate across the Banda Sea but with a regional peak to the southwest of the Buru Island, which can be attributed to island wake effect. Over the Banda Sea, WP, BT and BC contribute 74% (42%), 14% (19%) and 12% (39%) of total energy to EKE during NWM (SEM), respectively. The majority of EKE generated is diverged horizontally by pressure work and dissipated by turbulent viscosity, with dissipation depleting the most. This study highlights the importance of both monsoon and MJO wind forcing in generating EKE variability along the pathway of the Indonesian Throughflow.

An advanced data-assimilative ocean circulation model is used to investigate Gulf Stream (GS) variability during 2017–2018. The modeling system applies a strong-constraint, 4D variational data assimilation algorithm. It assimilates satellite-based sea surface height and sea surface temperature measurements and in situ temperature and salinity profiles. Model skill assessment metrics along with comparisons of GS position and GS's three-dimensional mean kinetic energy with historical observations are applied to validate the data-assimilative model. The resulting time- and space-continuous ocean state estimates are used to diagnose eddy kinetic energy conversion and cross-stream eddy heat and salt fluxes over the two-year study period. The processes leading to kinetic energy conversion are primarily due to GS meanders. Significant inverse energy cascading (EKE→MKE and EKE→EPE) can occur during GS-eddy interactions, particularly during onshore intrusions or offshore meanderings of the GS. Throughout the two-year study period, the cross-stream eddy heat and salt fluxes off Cape Hatteras were predominantly positive (onshore). Both GS offshore meandering (occurring 44% of the time and associated with shelf/slope water export) and GS intrusion (occurring 56% of the time) contribute to onshore heat and salt transport. Improved understanding of these processes and dynamics requires strong integration of an advanced observational infrastructure that combines remote sensing; fixed, mobile, and shore-based observing components; and high-resolution data assimilative models.

Sardinella lemuru is known as a highly opportunistic and flexible forager. Their high abundance in the coastal upwelling of Bali Strait was initially attributed to their feeding habit on phytoplankton and hence attaining higher catch. It was challenged by subsequent reports which suggested zooplankton as their main diet. This difference is due to the lack of information on the one-year cycle of its seasonal feeding. Here we used a combination of the plankton in seawater and the stomach contents of S. lemuru and monsoonal oceanographic changes at Bali Strait to determine the diet composition and food selectivity in four fishing seasons of 2012–2013. The result shows that S. lemuru is an omnivorous fish, and its diet composition depends on plankton availability in the environment, size classes, and the monsoonal oceanographic change influenced by upwelling. This condition strongly supported high nutrients for phytoplankton availability in the seawater with medium diversity and moderate community stability, except in inter-monsoon-2 (Trans-2). Phytoplankton was found as the main diet item of S. lemuru during the higher abundance of phytoplankton (82.26% Rhizosolenia stolterfothii) in Trans-2. In contrast, its main diet was substituted by zooplankton (51.96% Nauplius of Paraeuchaeta norvegica) during lower phytoplankton abundance in the northwest monsoon (NW). In addition, S. lemuru has adaptive strategies in feeding habits: It not only has flexibility but also selectivity in the feeding habit, supported by the ability to perform vertical migration for plankton grazing in different depths, move to another feeding ground, or plankton might be carried by the Indonesian Throughflow (ITF) into the Bali Strait. This study provides valuable information on the feeding ecology of S. lemuru, possibly providing a scientific basis for the proper management of the S. lemuru fishery in Bali Strait.

We developed a Lagrangian larval dispersal model to estimate trajectories for eleven fish taxa inhabiting the Gulf of Mexico (GOM). Dispersal models are at family level resolution for Scaridae, Lutjanidae, Scombridae, Labridae, Ophichthidae, and Ophidiidae, at genus level resolution for Hemanthias, and at species level resolution for Trachurus lathami, Decapterus punctatus, Katsuwonus pelamis, and Euthynnus alleteratus. Hydrodynamics are provided by the West Florida Coastal Ocean Model (WFCOM). Larval samples are from the spring and fall SEAMAP ichthyoplankton surveys from 2007 to 2011. The Lagrangian model was run backwards/forwards in time from the sampling event to estimate spawning/settlement locations. Results were used to update larval dispersal dynamics in the GOM Atlantis ‘end-to-end’ ecosystem model for twelve functional groups. We compare dispersal and non-dispersal scenarios in the Gulf of Mexico Atlantis model and find differences in stock abundance and distribution of fish. This highlights that the abundance and distribution of fishery resources are sensitive to changing circulation patterns. This work takes an interdisciplinary approach to understanding larval dynamics and their impacts on ecosystems at the intersection of predictive statistical modeling, hydrodynamic modeling, and ecosystem modeling.

Sea surface temperatures for Tampa Bay, the West Florida Continental Shelf (WFS) and the adjacent deep Gulf of Mexico are examined for trends. Data sets are from stations maintained by the Hillsborough County Environmental Protection Commission, buoys maintained by the University of South Florida Coastal Ocean Monitoring and Prediction System and the National Oceanic and Atmosphere Administration (NOAA) National Data Buoy Center, the Optimum Interpolation Sea Surface Temperature analyses by the NOAA National Centers for Environmental Information, and the Hadley Centre Sea Surface Temperature. These various data sets, each with different record lengths, require the consideration of trends both on the basis of record length and start time. Tampa Bay shows a warming trend, but with considerable inter-annual variability and start time bias resulting in a lack of statistical significance in more recent years. The WFS is also generally warming, and its inter-annual variability is largely controlled by the upwelling of cooler, deeper Gulf of Mexico water across the shelf break. The deep GOM shows statistically significant warming in most of the data except for the “gappy” records from buoys, both along the continental shelf and in the deep water. Trends in the Gulf of Mexico are mostly between 0.1 and 0.5 ^°C/decade, somewhat larger than the secular rise found globally, although within the range of the observed decadal variability.

As a partially mixed estuary, Tampa Bay is influenced both by its connections to the adjacent Gulf of Mexico (GOM) and what occurs locally within the estuary. To assist in addressing the many scientific questions arising from various environmental factors, a very high resolution Tampa Bay Coastal Ocean Model (TBCOM) is modified to downscale from the deep GOM, across the continental shelf and into Tampa Bay to provide daily, automated nowcasts and forecasts. Veracity tests are provided for sea levels and currents forced by tides, synoptic weather variations and for extreme events. The model is also demonstrated to reproduce the net estuarine circulation through comparisons between in situ observations and model simulations. With demonstrated accuracy, TBCOM forecast sea levels are provided online as a reference for navigation support and for extreme events such as hurricane storm surge. Model simulations, even with a perfect model, are subject to errors by the forcing functions. For Tampa Bay, the NOAA NAM winds used to force the model are found to underestimate the actual winds, suggesting that additional wind observations for assimilation into operational weather forecast models may offer further improvements. This finding highlights the need for further coordination between coastal ocean observing systems and the ocean and atmosphere modeling communities. With coastal ocean and estuary material properties determined largely by the circulation, most ecological applications require accurate and timely circulation information, which the TBCOM Nowcast/Forecast System for Tampa Bay endeavors to provide.

Variations in the upper ocean thermal structure have significant implications for air-sea interaction and upper-ocean ecosystem processes. Vertical profiles of temperature measured by a moored buoy located at 10.5°N, 94°E in the Andaman Sea and simulation by an Indian Ocean model are used in this study to characterise the intraseasonal variations (ISV) in the Andaman Sea (AndS) thermal structure and identify their sources. The seasonal variations in the upper ocean thermal structure show a strong semi-annual cycle driven by monsoons. The sub-surface temperature shows significant intraseasonal oscillations within a band of 40–110 days, which are de-coupled from that in the mixed layer, which has dominant periodicity in the band of 90–120 days. Thermocline ISV are seasonally modulated with a primary peak during August–September and a secondary peak during February–March, with significant year-to-year variations. A cross-wavelet analysis shows that ISV in the 40–60 days period is in phase with that at the eastern boundary and they are locally forced by the passage of eddies. The 60–110 day band is out of phase with the eastern boundary and is forced by Rossby waves radiated from the equatorially generated intraseasonal coastal Kelvin waves.

Vinciguerria lucetia is a mesopelagic fish whose larvae show an almost permanent presence in the southern portion of the California Current System. Due to its sensitivity to environmental changes, the species has been considered an indicator of water masses and interannual variability. Fish larvae abundance registered from 1997 to 2015 by the program Investigaciones Mexicanas de la Corriente de California was used to predict the abundance distribution of V. lucetia larvae under two extreme thermal conditions (2000 La Niña and 2015 El Niño), utilizing the novel machine learning algorithm eXtreme Gradient Boosting (XGBOOST). The data were segmented into COLD and WARM groups based on the mean sea surface temperature recorded at each station and contrasted with an undivided TOTAL group. Models were generated using 12 environmental and biological predictor features. Root-mean-squared logarithm error (RMSLE) was used as a prediction performance metric for both internal and external validation. The COLD model showed the best performance for the internal validation with a lower RMSLE value, while the TOTAL model for both the coldest and warmest external validation presented the lowest RMSLE values. The external validation demonstrated models that accurately predicted the spatial distribution; however, none of the models were able to accurately predict the same abundance magnitude observed in both extreme thermal conditions. Nevertheless, XGBOOST shows promise for describing the future distribution traits of V. lucetia.