Satellite observations are often incomplete due to cloud cover, resulting in missing ocean data. To address this, we developed T-DINEOF (Data Interpolating Empirical Orthogonal Function), a reconstruction method that simultaneously estimates sea surface temperature, chlorophyll concentration, and wind conditions by learning relationships among variables. Results show that T-DINEOF improves reconstruction accuracy, especially in regions with sparse data or weak correlations, providing more reliable ocean information for environmental monitoring.

Strong motions caused by surface waves can set the material at the bottom in motion. How strong the wave motions need to be depends on the bottom type, for example mud or sand. We estimated how often waves can lift particles from the bottom by comparing wave model results to sea floor samples in the laboratory. We included the effect of seasonal biological activity, which was found to be significant. 

This study reveals the structure and alteration of a narrow freshwater-driven ocean low-density filament and its evolution through tidal modulationa an dlocale filament kinematics. Using multi-platform in situ observations, it is shown that these submesoscale features can rapidly being altered and reshape in near-surface waters, influencing how energy and heat alter just below the ocean-atmosphere interface.

We introduce TS (Temperature-Salinity)-Cast, a novel deep neural network that reconstructs subsurface thermohaline structures from satellite observations. Validated against independent time-series data, TS-Cast achieves root mean squared errors of < 1 °C and < 0.1 psu in the upper 500 m of the Kuroshio Extension, comparable or surpassing data-assimilated numerical models. Critically, we demonstrate that the physical limitations of the input satellite data fundamentally constrain the model's predictive skill.

Ocean bottom pressure (p_b) is a key variable for monitoring the ocean circulation, yet global space gravimetry observations offer limited coverage in space and time. Our work examines how to improve estimates of p_b by optimally combining information in available data with an ocean circulation model. Results indicate that gravimetry data contain information complementary to that available in other ocean datasets and are thus important for determining variations in p_b and related circulations.

This work examines how large-scale climate modes affect waves and storm surges on the northeast coast of England. We combine weather types with a multivariate analysis of sea states. We find that the North Atlantic Oscillation and Scandinavian pattern influence local waves and surges by altering the occurrence probabilities of synoptic conditions associated with specific winds, storm locations, and pressure systems. Our results improve the understanding of climate impacts on coastal conditions.

The study use Conductivity, Temperature and Depth (CTD) measurement (including seals-borne CTD) to describe the seasonality of the stratification and mixing of one of the southernmost Fjords of Patagonia: The Almirantazgo Fjord. The region, typically tidal was indicated as the most important forcing for mixing the inner-sea of Tierra del Fuego, here the study shows that the persistent an episodic strong along-fjord winds could perturb the pynoclyne and rivals to the estuarine circulation.

The deep Ionian Sea strongly influences how the Mediterranean water masses circulate. By studying how internal waves interact with the seafloor, we found that rougher terrain changes how wave energy is spread out. Energy shifts from large to small scales, affecting deep water mixing. These findings help improve models of Mediterranean circulation by showing how seafloor shape impacts mixing in the deep sea.

The Arctic Ocean is changing fast, and river runoff plays a key role. Between 2015 and 2017, unusually large flows from Siberia’s Yenisey and Ob Rivers made the eastern Arctic much fresher. This stabilized the ocean, slowed currents, and reduced heat from below, allowing thicker sea ice to persist through summer. The study shows how bursts of river discharge can reshape the Arctic and help sea ice survive.

Marine heatwaves, periods of unusually warm sea temperatures, are increasing worldwide. Using observed sea surface temperature data and statistical clustering, this study shows that the North Sea contains two regions with different seasonal responses to climate patterns. Winter heatwaves in the south are driven by regional circulation, while summer events in the north reflect Atlantic and Pacific influences. These insights can help improve regional forecasting.

We investigate the impact of Greenland meltwaters on the ocean circulation and the North Atlantic region. To this end, we impose a quasi-realistic distribution of freshwater fluxes in a global climate model with 8-km horizontal resolution, much finer than the standard 100-km scale. The study reveals that the meltwaters disperse unevenly across the North Atlantic, guided by boundary currents and modulated by gradual changes in the large-scale circulation, which undergoes a progressive weakening.

Warm Atlantic Water flowing eastward north of Svalbard loses heat faster than can be explained by cooling to the atmosphere and mixing alone. Using year-long mooring observations and an ocean model, we found that mesoscale variability and energy transfer into eddies are largest in autumn and winter, when the boundary current is also at its strongest and warmest. This mesoscale activity enhances lateral heat exchange and likely contributes to the observed cooling of Atlantic Water along its path.

This study evaluates deep generative diffusion models for downscaling sea surface salinity in the Gulf Stream. Using a reanalysis dataset as a controlled framework, it assesses the added value of high-resolution sea surface temperature and sea surface height as auxiliary constraints. The results show that diffusion-based reconstructions preserve plausible fine-scale variability, highlighting the method’s potential for future applications to satellite products.

Mesoscale ocean eddies (10–100 km) are crucial for transporting heat and salt in global circulation. While traditionally parameterized in ocean models, advances in computational power allow them to be partly resolved, questioning whether parameterizations should be used in this regime. We examine implications for Atlantic water circulation and heat transport to the Arctic, highlighting challenges in using – or omitting – mesoscale eddy parameterizations.

The Atlantic inflow across the Iceland-Faroe Ridge carries almost half of the warm water towards the Arctic. This study explores the modifications of the Atlantic water on its way to and across this underwater ridge. While crossing the ridge, the water is strongly cooled and freshened, which can reduce the ability for deep-water formation. Understanding these processes is important for improving ocean and climate models so more realistic forecasts can be made in a warming climate.

The Amazon River plume interaction with the North Brazil Current creates sharp temperature-salinity differences called fronts that are important for modulating air-sea interactions and biogeochemical cycles. This study uses data from robotic sailboats and a numerical model to provide a comprehensive picture of these fronts associated with the local dynamics. We characterize three distinct frontal regimes and the temperature-salinity relations linked to the Amazon discharge and current strength.