In this study, we reconstructed the North Atlantic Ocean temperature field by combining an interpretable deep learning framework with multi-source satellite data, including sea surface temperature (SST), sea surface height (SSH), sea level anomaly (SLA), sea surface wind field (SSW), and SST gradient (GRAD). The optimal model configuration achieved a root mean square error (RMSE) of 0.49 °C. This study extends the SHapley Additive exPlanations (SHAP) method to spatial, temporal, and vertical dimensions to systematically analyze the model’s error sources and feature contributions. The results show that the reconstruction error is concentrated in regions with large physical gradients, such as the thermocline and Gulf Stream, exhibiting a significant seasonal bias pattern. SHAP analysis reveals a clear vertical transition in feature importance that SST dominates at all depths with a relative contribution of 34.60%. The contributions of SSW and GRAD were mainly concentrated at the sea surface, whereas the contributions of SSH and SLA began to increase in the lower mixed layer and peaked in the thermocline, becoming crucial in connecting the surface and ocean interior. This study highlights the depth and spatial dependence of feature contributions, providing a physical basis for the future optimization of remote sensing-based ocean temperature reconstruction models.

No apparent impact of moderate temperature increase on growth and fecundity in the sea star Asterias rubens.

Physiological effects of zinc availability in the coral endosymbiont Cladocopium goreaui in a continuous culture system.

This study investigates the sensitivity of satellite-based brightness temperature measurements at 3.74, 10.85, and 12.00 μ m with respect to the identification of water, ice, and mixed-phase clouds (MPC). Radiative transfer simulations computed by SCIATRAN reveal that the directional brightness temperature difference at 3.74 μ m ( Δ BT 3 . 74 ), which is dependent on scattering, enables water clouds and MPC separation from ice clouds. For water clouds and MPC, Δ BT 3 . 74 typically exceeds 2 K, whereas for ice clouds it remains below 2 K. To separate MPC from water clouds, we introduce the Liquid Cloud Probability Index (LCPI) based on cloud top temperature and absorption differences between water and ice at 10.85 and 12.00 μ m. LCPI values generally exceed 0.4 for water clouds but fall below 0.4 for many MPC cases. The Δ BT 3 . 74 and LCPI approach is validated using the Sea and Land Surface Temperature Radiometer (SLSTR) dual-view data collocated with the 2B-CLDCLASS-LIDAR cloud phase product, showing over 90% accuracy in water and ice phase classification, and approximately 60% for MPC. This dual-view, multi-channel method enhances the detection of cloud phases, offering improved results for brightness temperature measurements. • Directional brightness temperature difference at 3 . 74 μ m can be used to separate water and ice clouds. When used with brightness temperature differences at 10 . 85 μ m and 12 . 00 μ m , mixed-phase clouds can be identified. • Mixed-phase clouds occurring at lower cloud top heights are challenging to separate from water clouds.

North Atlantic SSTA triggers persistent extreme precipitation over South China by modulating the 25–50-day intraseasonal oscillation

Association of microplastic pollution with coral resilience in the presence of sea surface temperature anomalies.

Dual-iodine-cell Brillouin LiDAR for ocean temperature profile estimation based on flight data

Bias correction of sea temperature in Shandong coastal waters using LSTM-FVCOM and GRU-DF-FVCOM hybrid models

Long-term deep ocean temperature monitoring is crucial for understanding the ocean's role in climate variability and storage of heat in the deep ocean. Observation of the ocean surface is relatively accessible via both in-situ and remote sensing; however, continuous, high-temporal resolution, decade-long temperature records from abyssal depths face the technical challenges of sustained deep ocean deployments. The addition of calibrated, internally-recording temperature sensors to deep-ocean moorings not far from the sea floor provides a means of making high temporal resolution temperature observations. Quality controlling and merging records from successive mooring deployments results in a decade-long time series. Our work has been to optimize approaches for ensuring data quality and continuity in multi-year deep ocean temperature datasets. Here we show a comprehensive processing framework that yields 13 years (2012 to 2025) of continuous temperature measurements at approximately 4200 to 4500 meters depth from the Stratus Ocean Reference Station near 22 °S, 85 °W, 1500 km off the coast of Chile in the Southeast Pacific. Our framework incorporates timing checks, automated spike detection, systematic multi-sensor validation, statistical validation, human-in-the-loop quality control, and merging protocols. This framework establishes reproducible standards for processing long term oceanographic observations from multiple deployments. For the Stratus data set, the result is a unique, decade-long abyssal temperature record with quantified uncertainties that constitutes a benchmark time series for evaluating the realism of deep ocean temperature in models.

Alopecic syndrome in Guadalupe fur seals, Arctocephalus philippii townsendii (GFSs), was first observed a decade ago, coinciding with an anomalous warm sea surface temperature event and shifts in foraging behaviors of otariid pinnipeds from Mexican North Pacific colonies. With no evidence of dermatophytes or ectoparasites commonly associated with alopecia, it has been proposed that nutritional or metabolic changes, secondary to altered foraging, may increase the risk of alopecia. We employed 16S rRNA gene deep sequencing to investigate changes in the fecal bacteriome of GFS with and without alopecia. We found no significant differences in species richness nor Simpson's diversity index, and alopecia accounted for less than 6% of the variation in bacteriome structure. However, five bacterial phyla (Bacteroidota, Firmicutes, Fusobacteriota, Proteobacteria, and Spirochaetota) were overrepresented, and two (Actinobacteriota and Campylobacterota) were underrepresented, in GFSs with alopecia. At the genus level, animals with alopecia had a higher abundance of various bacteria, including Parabacteroides, Bacteroides, Lachnospiraceae, Roseburia, and genera within Erysipelotrichaceae, which have been linked to alopecia in humans. The GFS fecal bacteriome revealed 322 distinct bacterial functional pathways, of which 163 varied significantly between cases and controls. The most prominent differences found in GFSs with alopecia were overrepresentation of critical precursors for bacterial cell wall components, aromatic amino acid biosynthesis and pantothenate and CoA biosynthesis, and underrepresentation of glucosyltransferases and bacterial surface antigens, nitrogen and sulfur metabolism, and bacterial secretion systems. Our study provides preliminary evidence that changes in enteric microbiota may contribute to the pathogenesis of alopecia in GFSs via three main mechanisms: dysregulation of immune modulation and sustained inflammation, altered metabolism, and reduced redox balance and detoxification in the gut. While future studies need to explore these possibilities, our findings offer insight into the role of the microbiome in emerging pathologies of wildlife.

Marine heatwaves (MHWs) are increasing in high-latitude oceans, yet behavioural responses of anadromous fishes to these potential stressors during short marine feeding seasons remain poorly understood. We combined acoustic telemetry (internal temperature and depth) with satellite-derived sea surface temperature data to quantify Arctic char (Salvelinus alpinus) responses to MHWs in the coastal Labrador Sea across two contrasting summers: 2023, with frequent early-season MHWs, and 2024, dominated by a late-season event. Using non-MHW detections, we fit seasonal baselines for each fish and calculated temperature and depth anomalies. Char tended to occur in inner habitats (estuaries/fjords), though 2024 showed greater among-individual variability in outer (coastal/headland) habitat use. Internal temperatures increased relative to baseline during MHW onset (median +0.64°C) with modest persistence post-onset (+0.23°C), whereas depth anomalies showed no consistent departures. Temperature anomalies increased from pre to during MHWs across body sizes and were strongest for larger fish during onset. In contrast, MHW conditions increased the probability of inner-habitat detection primarily for smaller fish after controlling for seasonality. Migration timing differed between years in a size-dependent way, with larger fish leaving the marine environment and entering rivers earlier in 2023. Overall, Arctic char responses did not provide evidence that they sought out thermal refuges during MHWs. However, size-dependent shifts in habitat use and migration timing indicate that MHWs can still alter marine habitat trade-offs, likely through indirect ecological factors (e.g., prey availability). Arctic char responses may intensify, however, when future heatwaves exceed physiological or growth-performance thresholds.

Prey size differentiation as a mechanism of trophic segregation in sympatric otariids in the Peruvian Humboldt Current System.

ABSTRACT Climate-driven variability is altering Taiwan’s marine ecosystems, with implications for Portunid crabs (Charybdis feriatus, Portunus pelagicus and Portunus sanguinolentus). This study assessed species-specific exposure to climate-driven changes using an exposure index (Ex) derived from five key environmental variables: chlorophyll-a (Chl-a), sea bottom temperature (SBT), sea surface salinity (SSS), sea surface height (SSH) and sea surface temperature (SST). Fishery-dependent data (2013–2022) were standardized using the Vector Autoregressive Spatio-Temporal (VAST) model, while individual exposure scores for each environmental variable were weighted by variable importance in projection (VIP) through partial least squares regression (PLSR). Results showed that exposure was strongly seasonal and species-specific; high exposure index (Ex ≥ 0.6) occurred mainly in spring – summer, overlapping with spawning periods and peak fishing effort, compounding risks to recruitment and population stability. Exposure differed among species, with SSH carrying the greatest weight for C. feriatus and P. sanguinolentus, and SSS most prominent in winter, while SST, SSS and SSH carried the greatest weight for P. pelagicus. Among climate indices, Niño 3.4 aligned positively with winter – spring exposure (most evident for C. feriatus). The NPO provided short leads (1–4 months) to higher Ex, while the PDO co-varied with exposure in spring and summer, especially for C. feriatus and P. sanguinolentus. Overall, understanding how climate variability raises exposure is essential for adaptive management; real-time monitoring to trigger short closures during vulnerable periods can protect recruitment and support SDG-14.

Contrasting pollution sensitivity for temperate reef assemblages revealed by microhabitat-resolved eDNA, algal sampling and visual surveys.

Seasonal forecast of sea surface temperatures via Neural ODEs

On the collapse of an endemic reef-building coral species.

Polychaete community responses to two decades of oceanographic change in Isfjorden, Svalbard.

Bioaccumulation of trace elements by Leach's storm-petrels (Hydrobates leucorhous) in the North and South Atlantic Ocean during the non-breeding period.

Temperature shapes the response of marine nitrogen-fixing cyanobacteria to nanoplastics.

Marine heatwaves (MHWs) are periods of unusually high sea surface temperature that can persist for weeks to months and extend across thousands of kilometers. Their increasing frequency and intensity under climate change threaten marine ecosystems and fisheries, yet the physical processes that govern their occurrence and evolution remain poorly understood. Here we analyze satellite and reanalysis data to show that atmospheric rivers (ARs)-long, narrow corridors of concentrated atmospheric moisture, often described as "rivers in the sky"-play a previously overlooked role in the development of MHWs in the North Pacific and North Atlantic. Under an AR, increased cloud cover cools the ocean through reduced solar radiation, while anomalously warm, humid air warms the ocean through the reduction of turbulent heat fluxes from the ocean. These two opposing mechanisms, dominant among others, vary with background climate state, causing seasonally and regionally varying ARs' impacts on MHWs. These findings stress the importance of understanding ocean-atmosphere compound extremes and their changes under a warming climate.