Recent  

There is widespread interest in whether the Gulf Stream will decline under global warming. We analyse 19 coupled climate model projections of the AMOC over the 21^st century. The model consensus is that the AMOC will decline by about 40 % due to reductions in northward Gulf Stream transport and southward deep western boundary current transport. Whilst the wind-driven Gulf Stream decreases by 4 Sv, most of the decrease in the Gulf Stream is due to a reduction of 7 Sv in its thermohaline component.

Cold-water corals (CWCs) and tidal waves in the interior of the ocean have been connected in case studies. We demonstrate this connection globally using hydrodynamic simulations and a CWC database. Internal-tide generation shows a similar depth pattern with slope steepness and latitude as CWCs. Our results suggest that internal-tide generation can be a useful predictor of CWC habitat and that current CWC habitats might change following climate-change-related shoaling of internal-tide generation.

The Atlantic Meridional Overturning Circulation (AMOC) is an important component in the global climate system. Observations of the present-day AMOC indicate that it may weaken or collapse under global warming, with profound disruptive effects on future climate. However, AMOC weakening is not correctly represented because an important feedback is underestimated due to biases in the Atlantic's freshwater budget. Here we address these biases in several state-of-the-art climate model simulations.

We examine factors affecting variability in the volume of Labrador Sea Water (LSW), a water mass that is important for the uptake and storage of heat and carbon in the Atlantic Ocean. We find that LSW accumulated in the Labrador Sea exhibits a lagged response to remote conditions: surface wind stress, heat flux, and freshwater flux anomalies, especially along the pathways of the North Atlantic Current branches. We use our results to reconstruct and attribute historical changes in LSW volume.

Southwesterly winds impact cross-estuary flows by amplifying the eddy viscosity component during smaller tides. Moreover, they modify along-estuary gravitational circulation by diminishing both the barotropic and baroclinic components. Stratification results in contrasting sheared flows, distinguished by different dominant components compared to destratified conditions. Additionally, the eddy viscosity component is governed by various subcomponents in diverse stratified waters.

We use data from satellites and robotic floats to assess what drives year-to-year variability in primary production in the Weddell Gyre. We find that the maximum area of ice-free water in the summer is important in determining the total primary production in the region but that areas that are ice free for longer than 120 d become nutrient limited. This has potential implications for ecosystem health in a warming world, where a decline in sea ice cover will affect total primary production.

Analysis of a high-frequency time series of thermohaline data measured at the EMSO-E2M3A regional facility in the southern Adriatic Pit (SAP) reveals a significant change in the double-diffusive regime in 2017 associated with the intrusion of extremely salty waters into the area, suggesting salt fingering as the dominant regime. The strong heat loss at the surface during this winter allowed deep convection to transport this high-salinity water from the intermediate to deep layers of the pit.

This study explores extreme marine summers (EMSs) in the Mediterranean Sea using sea surface temperature (SST) data. EMSs arise mainly due to the warmest summer days being unusually warm. Air–sea heat fluxes drive EMSs in northern regions, where also enhanced marine heatwave conditions are found during EMSs. Long-term SST changes lead to warmer EMSs while not affecting the way daily SST values are organized during EMSs. Findings enhance comprehension of anomalously warm conditions in the basin.

This study employs machine learning to predict marine heatwaves (MHWs) in the Mediterranean Sea. MHWs have far-reaching impacts on society and ecosystems. Using data from ESA and ECMWF, the research develops accurate prediction models for sea surface temperature (SST) and MHWs across the region. Notably, machine learning methods outperform existing forecasting systems, showing promise in early MHW predictions. The study also highlights the importance of solar radiation as a predictor of SST.

This study examines the seasonal patterns of chlorophyll-a (chl-a) blooms in the Bransfield Strait using remote sensing data supported by novel and historical in situ observations. Through satellite data we show that we can identify two distinct phytoplankton niches along a thermal front known as the Peninsula Front: the Transitional Bellingshausen Water and Transitional Weddell Water pools. These findings enable the first climatological description of the chl-a blooms in the Bransfield Strait.

To analyse the influence of potential future mean sea level rise (SLR) and tidal flat elevation scenarios on the tidal dynamics in the Elbe estuary, we used a highly resolved hydrodynamic numerical model. The results show increasing tidal range in the Elbe estuary due to SLR alone. In combination with different tidal flat growth scenarios, they reveal strongly varying changes in tidal range. We discuss how changes in estuarine geometry can provide an explanation for the changes in tidal range.

Satellite salinity data are used for the first time to study variability in Arctic freshwater transport from the Lena River and are shown to be a valuable tool for studying this region. These data confirm east/westerly wind is the main control on fresh water and sea ice transport rather than the volume of river runoff. The strong role of the wind suggests understanding how wind patterns will change is key to predicting future Arctic circulation and sea ice concentration.

We apply two different forcing products to a high-resolution ocean model to investigate their impact on the simulated upper-current field in the tropical Atlantic. Where possible, we compare the simulated results to long-term observations. We find large discrepancies between the two simulations regarding the wind and current fields. We propose that long-term observations, once they have reached a critical length, need to be used to test the quality of wind-driven simulations.

While the deeper waters in the coastal ocean show signs of climate-change-induced warming and deoxygenation, some fjords can keep cool and oxygenated waters in the subsurface. We use a model to investigate how these subsurface waters created during winter can linger all summer in Bute Inlet, Canada. We found two main mechanisms that make this fjord retentive: the typical slow subsurface circulation in such a deep, long fjord and the further speed reduction when the cold waters are present.

Satellite retrievals of sea surface salinity (SSS) offer insights into freshwater changes in the Arctic Ocean. This study evaluates freshwater content in the Beaufort Gyre using SMOS and reanalysis data, revealing underestimation with reanalysis alone. Incorporating satellite SSS measurements improves freshwater content estimation, especially near ice-melting areas. Adding remotely sensed salinity aids in monitoring Arctic freshwater content and in understanding its impact on global climate.

Marine heatwaves are long periods of extremely warm ocean surface temperatures. Predicting such events a few months in advance would help decision-making to mitigate their impacts on marine ecosystems. This work investigates how well operational seasonal forecasts can predict marine heatwaves. Results show that such events can be predicted a few months in advance in the tropics but that extending the predictability skill to other regions will require additional work on the forecast models.

Satellite observations offer valuable information on phytoplankton abundance and community structure. Here, we employ satellite observations to infer seven phytoplankton groups at a global scale based on a new molecular method from Tara Oceans. The link has been established using machine learning approaches. The output of this work provides excellent tools to collect essential biodiversity variables and a foundation to monitor the evolution of marine biodiversity.

Understanding internal tide generation and propagation is crucial for predicting large-scale circulation and climate change. Internal tides are prone to interacting with background currents with similar spatial scales during propagation. This paper investigates the physical mechanism of the interaction between semidiurnal internal tides and an anticyclonic eddy in the northeastern South China Sea using a numerical model with high spatial and temporal resolution.

In this study we use a machine learning method called a Gaussian mixture model to divide part of the ocean (northwestern European seas and part of the Atlantic Ocean) into regions based on satellite observations of sea level. This helps us study each of these regions separately and learn more about what causes sea level changes there. We find that the ocean is first divided based on bathymetry and then based on other features such as water masses and typical atmospheric conditions.

From 2021 to 2022, a particular sub-estuary (East River estuary) suffered greatly from an enhanced salt intrusion. We conducted observation analysis, numerical simulations, and analytical solution to unravel the underlying mechanisms. This study is of help in the investigation of salt dynamics in sub-estuaries connected to main estuaries and of implications for mitigating salt intrusion problems in the regions.