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Mesoscale eddies are phenomena that widely exist in the ocean and have a significant impact on the ocean's temperature and salt structure, as well as on acoustic propagation effects. Currently, utilizing the limited data on mesoscale eddy environments for refined acoustic field reconstruction in offshore conditions at mid-to-far-ocean distances is an urgent problem that needs to be addressed. In this paper, we propose a mesoscale eddy reconstruction method (EddyGAN) based on the generative adversarial network (GAN) model which is inspired by the concept of global localization. We adopt a hybrid algorithm for eddy identification using JCOPE2M high-resolution reanalysis data and Archiving, Validation, and Interpretation of Satellite Oceanographic (AVISO) satellite altimeter data to extract mesoscale eddy sound speed profile (SSP) sample data, and then apply the EddyGAN model to train this dataset and perform mesoscale eddy acoustic field reconstruction. We also propose an evaluation method for mesoscale eddy acoustic field reconstruction that uses RMSE, SSIM, and convergence zone (CZ) accuracy based on World Ocean Atlas (WOA) climate state data completion as indicators. The reconstruction result of this model achieves an RMSE of 1.7 m/s, an SSIM of 0.77, and an average CZ accuracy of over 70%. This method better characterizes the mesoscale eddy sound field than the native GAN and other reconstruction methods, improves the accuracy of mesoscale eddy acoustic field reconstruction, and provides superior performance, offering significant reference value for mesoscale eddy reconstruction technology and subsequent ocean acoustic research. [ABSTRACT FROM AUTHOR]

Medium-voltage DC (MVDC) technology has gained increasing attention in recent years. Power electronics devices dominate these grids. Accurate simulation of such a grid, with detailed models of switching semiconductors, can quickly became very time-consuming, according to the number of connected devices to be simulated. A simulation approach based on interactions on a continuous time model can be very interesting, especially for developing a system-level control model of such a modern MVDC distribution grid. The aim of this paper is to present all the steps required for obtaining a continuous time modelling of a +/−10 kV MVDC grid case study, including a solid-state transformer (SST)- and modular multilevel converter (MMC)-based active front end (AFE). An additional aim of this paper is to supply educational content about the use of the continuous time simulation approach, thanks to a detailed description of the various devices modelled into the presented MVDC grid. The results of a certain number of simulation scenarios are eventually presented. [ABSTRACT FROM AUTHOR]

This paper demonstrates the effectiveness and superiority of Empirical Mode Decomposition (EMD) in projecting non-stationary hydrological data. The study focuses on daily Sea Surface Temperature (SST) sequences in the Niño 3.4 region and uses EMD to forecast the probability of El Niño events. Applying the Mann–Kendall test at the 5% significance level reveals a significant increasing trend in SST changes in this region, particularly noticeable after 1980. This trend is associated with the occurrence of El Niño and La Niña events, which have a recurrence interval of approximately 8.4 years and persist for over a year. The modified Oceanic Niño Index (ONI) proposed in this study demonstrates high forecast accuracy, with 97.56% accuracy for El Niño and 89.80% for La Niña events. Additionally, the EMD of SST data results in 13 Intrinsic Mode Functions (IMFs) and a residual component. The oscillation period increases with each IMF level, with IMF7 exhibiting the largest amplitude, fluctuating between ±1 °C. The residual component shows a significant upward trend, with an average annual increase of 0.0107 °C. These findings reveal that the EMD-based data generation method overcomes the limitations of traditional hydrological models in managing non-stationary sequences, representing a notable advancement in data-driven hydrological time series modeling. Practically, the EMD-based 5-year moving process can generate daily sea temperature sequences for the coming year in this region, offering valuable insights for assessing El Niño probabilities and facilitating annual updates. [ABSTRACT FROM AUTHOR]

A global inventory of extractive species mariculture in wave-exposed temperate waters shows that the longline is the technology used in more than 99% of the sites (Part 1 of this review). In this second part, I compare the static (longline at rest), quasi-static (tidal sea surface elevation, steady currents and mainline lifting operation) and dynamic (wind seas and swells) loading and motion of surface, semi-submerged and fully submerged longlines used to grow bivalves and kelp. This review is based on a hundred papers published on the subject mostly after 2010 and on simple analytical models used to illustrate the many compromises that must be made to ensure the survivability of the structure and the survival (retention), growth and quality of the cultured biomass. Surface longlines are unsuitable for fully exposed environments. To mitigate storm energy it is necessary to minimize the volume of surface buoys and submerge the mainline to the maximum depth possible. There is however a limit to minimizing the volume of surface buoys due to the uplifting of the mainline by currents. In the case of kelp, its optimal growing depth is within a few meters from the sea surface. This limitation can be partly circumvented by having the kelp float above the mainline. In the case of bivalves, mainline depth can be tens of meters below the sea surface. This comes with some disadvantages including difficulties in maintaining the delicate buoyancy balance, particularly for fully submerged longlines without legs, and reduced access to the mainline, particularly for fully submerged longlines with legs. Devices that allow autonomous or remote-controlled changes of mainline depth on a daily, occasional (husbandry and harvest operations) or seasonal basis have been tested but are not yet used commercially on longlines. [ABSTRACT FROM AUTHOR]

The study of upper ocean mixing processes, including their dynamics and thermodynamics, has been a primary focus for oceanographers and meteorologists. Wave breaking in deep water is believed to play a significant role in these processes, affecting air–sea interactions and contributing to the energy dissipation of surface waves. This, in turn, enhances the transfer of gas, heat, and mass at the ocean surface. In this paper, we use the FVCOM-SWAVE coupled wave and current model, which is based on the MY-2.5 turbulent closure model, to examine the response of upper ocean turbulent kinetic energy (TKE) and temperature to various wave breaking parametric schemes. We propose a new parametric scheme for wave breaking energy at the sea surface, which is based on the correlation between breaking wave parameter R B and whitecap coverage. The impact of this new wave breaking parametric scheme on the upper ocean under typhoon conditions is analyzed by comparing it with the original parametric scheme that is primarily influenced by wave age. The wave field simulated by SWAVE was verified using Jason-3 satellite altimeter data, confirming the effectiveness of the simulation. The simulation results for upper ocean temperature were also validated using OISST data and Argo float observational data. Our findings indicate that, under the influence of Typhoon Nanmadol, both parametric schemes can transfer the energy of sea surface wave breaking into the seawater. The new wave breaking parameter R B scheme effectively enhances turbulent mixing at the ocean surface, leading to a decrease in sea surface temperature (SST) and an increase in mixed layer depth (MLD). This further improves upon the issue of uneven mixing of seawater at the air–sea interface in the MY-2.5 turbulent closure model. However, it is important to note that wave breaking under typhoon conditions is only one aspect of wave impact on ocean disturbances. Therefore, further research is needed to fully understand the impact of waves on upper ocean mixing, including the consideration of other wave mechanisms. [ABSTRACT FROM AUTHOR]

Land Surface Temperature (LST) is integral to our understanding of the radiative energy budget of the Earth's surface since it provides the best approximation to the thermodynamic temperature that drives the outgoing longwave flux from surface to atmosphere. Since 5 July 2017, an operational LST product has been available from the Sentinel-3A mission, with the corresponding product being available from Sentinel-3B since 17 November 2018. Here, we present the first paper describing formal products, including algorithms, for the Sea and Land Surface Temperature Radiometer (SLSTR) instruments onboard Sentinel-3A and 3B (SLSTR-A and SLSTR-B, respectively). We evaluate the quality of both the Land Surface Temperature Climate Change Initiative (LST_cci) product and the Copernicus operational LST product (SL_2_LST) for the years 2018 to 2021. The evaluation takes the form of a validation against ground-based observations of LST across eleven well-established in situ stations. For the validation, the mean absolute daytime and night-time difference against the in situ measurements for the LST_cci product is 0.77 K and 0.50 K, respectively, for SLSTR-A, and 0.91 K and 0.54 K, respectively, for SLSTR-B. These are an improvement on the corresponding statistics for the SL_2_LST product, which are 1.45 K (daytime) and 0.76 (night-time) for SLSTR-A, and 1.29 K (daytime) and 0.77 (night-time) for SLSTR-B. The key influencing factors in this improvement include an upgraded database of reference states for the generation of retrieval coefficients, higher stratification of the auxiliary data for the biome and fractional vegetation, and enhanced cloud masking. [ABSTRACT FROM AUTHOR]

This paper analyzes the ability of three conceptual stochastic models (one-box, two-box, and diffusion models) to reproduce essential features of sea surface temperature variability on intra-annual time scales. The variability of sea surface temperature, which is particularly influenced by feedback mechanisms in ocean surface–atmosphere coupling processes, is characterized by power spectral density, commonly used to analyze the response of dynamical systems to random forcing. The models are aimed at studying local effects of ocean–atmosphere interactions. Comparing observed and theoretical power spectra shows that in dynamically inactive ocean regions (e.g., north-eastern part of the Pacific Ocean), sea surface temperature variability can be described by linear stochastic models such as one-box and two-box models. In regions of the world ocean (e.g., north-western Pacific Ocean, subtropics of the North Atlantic, the Southern Ocean), in which the observed sea surface temperature spectra on the intra-annual time scales do not obey the ν − 2 law (where ν is a regular frequency), the formation mechanisms of sea surface anomalies are mainly determined by ocean circulation rather than by local ocean–atmosphere interactions. The diffusion model can be used for simulating sea surface temperature anomalies in such areas of the global ocean. The models examined are not able to reproduce the variability of sea surface temperature over the entire frequency range for two primary reasons; first, because the object of study, the ocean surface mixed layer, changes during the year, and second, due to the difference in the physics of processes involved at different time scales. [ABSTRACT FROM AUTHOR]

Despite common background La Niña conditions, Australia was very dry in November 2020 and wet in November 2021. This paper aims to provide an explanation for this difference. Large-scale drivers of Australian rainfall, including El Niño–Southern Oscillation, Indian Ocean dipole, Southern Annular Mode, and Madden–Julian oscillation, were examined but did not provide obvious clues for the differences. We found that the absence (in 2020) or presence (in 2021) of an enhanced thermal wind and subtropical jet over the Australian continent contributed to the rainfall anomalies. In general, La Niña sets up warm sea surface temperatures around northern Australia, which enhances the meridional temperature gradient over the continent and hence thermal wind and subtropical jet. In November 2021, these warm sea surface temperatures, coupled with a persistent midlatitude trough, which advected cold air over the Australian continent, led to an enhanced meridional temperature gradient and subtropical jet over Australia. The enhanced jet provided favorable conditions for the development of rain-bearing weather systems across Australia. In 2020, the continent was warm, displacing the latitude of maximum meridional temperature gradient south of the continent, resulting in fewer instances of the subtropical jet over Australia, and little development of weather systems over the continent. We highlight that although La Niña tilts the odds to wetter conditions for Australia, in any given month, variability in temperatures over the continent can contribute to subtropical jet variability and resulting rainfall in ways which confound the normal expectation from La Niña. Significance Statement: Forecasts of El Niño–Southern Oscillation are eagerly awaited, as the state of this climate driver has profound impacts on the likelihood of rainfall in regions around the world. While El Niño and La Niña do change rainfall likelihoods, the actual outcomes of these events are sometimes counter to expectation. This work explores one of the confounding factors to those expectations in the Australian context—the role of the meridional temperature gradient over the continent in modifying the storm track over Australia, which can disrupt the expected El Niño and La Niña teleconnections. We present case studies for two La Niña springs, highlighting that the Australian continent can help shape its own weather toward wetter or drier outcomes. [ABSTRACT FROM AUTHOR]

Europe and the Mediterranean are considered climate change hot spots. This is the reason why this paper focuses on the analysis of the trends of essential climate variables in a Mediterranean country, Greece. The analyzed period is 1991–2020, and the dataset used is ERA5-Land (produced by the European Center for Medium-Range Weather Forecasts), which has global coverage and an improved resolution of ~9 × 9 km compared to other datasets. Significant climatic changes across Greece have been put in evidence during the analyzed period. More specifically, the country averaged a 30-year trend of temperature of +1.5 °C, locally exceeding +2 °C, and this increasing trend is positively correlated with the distance of the areas from the coasts. Accordingly, the number of frost days has decreased throughout the country. In terms of rainfall, a major part of Greece has experienced increasing annual rainfall amounts, while 86% of the Greek area has experienced a positive trend of days with heavy rainfall (>20 mm). Finally, a multiple signal of the trend of consecutive dry days was found (statistically non-significant in the major part of Greece). [ABSTRACT FROM AUTHOR]

Estimating the ocean's subsurface thermohaline information from satellite measurements is essential for understanding ocean dynamics and the El Niño phenomenon. This paper proposes an improved double-output residual neural network (DO-ResNet) model to concurrently estimate the subsurface temperature (ST) and subsurface salinity (SS) in the tropical Western Pacific using multi-source remote sensing data, including sea surface temperature (SST), sea surface salinity (SSS), sea surface height anomaly (SSHA), sea surface wind (SSW), and geographical information (including longitude and latitude). In the model experiment, Argo data were used to train and validate the model, and the root mean square error (RMSE), normalized root mean square error (NRMSE), and coefficient of determination (R2) were employed to evaluate the model's performance. The results showed that the sea surface parameters selected in this study have a positive effect on the estimation process, and the average RMSE and R2 values for estimating ST (SS) by the proposed model are 0.34 °C (0.05 psu) and 0.91 (0.95), respectively. Under the data conditions considered in this study, DO-ResNet demonstrates superior performance relative to the extreme gradient boosting model, random forest model, and artificial neural network model. Additionally, this study evaluates the model's accuracy by comparing its estimations of ST and SS across different depths with Argo data, demonstrating the model's ability to effectively capture the most spatial features, and by comparing NRMSE across different depths and seasons, the model demonstrates strong adaptability to seasonal variations. In conclusion, this research introduces a novel artificial intelligence technique for estimating ST and SS in the tropical Western Pacific Ocean. [ABSTRACT FROM AUTHOR]

This paper assessed the phytoplankton structure and its relationship with the physical environment in the coastal region off Mazatlán, Mexico, in two seasons of 2022, a year in which a strong La Niña event took place: (1) the warmer (August) and (2) the transitional period to the cold phase (November), based on hydrographic data and samples collected in two systematic scientific expeditions. The results showed clear differences between both seasons. Regarding total abundance, August reached 125,200 cells L−1, while November amounted to 219,900 cells L−1. Regarding species composition, the diatoms Cylindrotheca closterium and Planktoniella sol were dominant in August, while Thalassionema nitzschioides and Tetramphora decussata dominated the assemblages in November. The dinoflagellate Protoperidinium punctulatum was dominant in both seasons. However, very marked differences in its abundance are reported. The differences observed in the species richness and abundance could be attributed to the physical configuration of the water column, particularly the surface temperature, which showed clear changes between both seasons. The results presented here confirmed the high phytoplankton richness (some of them with the potential to generate harmful algal blooms), abundance, and diversity values of the region, suggesting a strong relationship with the physical environment. [ABSTRACT FROM AUTHOR]

The North Atlantic Oscillation (NAO) and North Atlantic tripole sea surface temperature (SST_tri) are important modes in the atmosphere and ocean over the North Atlantic, respectively. The link between the two is well‐known. However, this link weakened during 1980–2001, which is particularly pronounced in late winter and was not detected in early winter. This phenomenon has not been well revealed. The role of NAO in the above correlation changes was discussed. In late winter, a significant eastward shift (up to 20° longitude) of NAO south center during 1980–2001 was observed in both observation and CMIP6, accompanied by the eastward expansion of NAO north center. Spatial shift of the NAO forced the region of strong air‐sea interactions to shift and resulting in the collapse of NAO‐related SST_tri. These findings deepen our understanding of the NAO on the subseasonal scale. Plain Language Summary: A significant correlation between the North Atlantic Oscillation (NAO) and the North Atlantic tripole sea surface temperature (SST_tri) is widely recognized. However, this study found that the correlation between the two was significantly weakened in late winter during 1980–2001 while no such change was detected in early winter. Therefore, this paper will focus on the late winter and discuss the role of NAO spatial structure in the above correlation changes. When the NAO south center is located over the North Atlantic, both observations and the climate models indicate that the corresponding North Atlantic SST shows a significant tripole pattern. However, during 1980–2001, the NAO south center shift significantly eastward from the North Atlantic toward Western Europe (up to 20° longitude). At the same time, the NAO north center expanded eastward significantly. The eastward shift of the NAO results in the significant eastward shift of the turbulent heat flux and wind stress anomalies. Shift in the region of strong air‐sea interaction led to the collapse of NAO‐related SST_tri. These findings deepen our understanding of the NAO on the subseasonal scale and also provide implications for subseasonal‐seasonal predictions of Eurasian climate extremes. Key Points: The link between NAO and North Atlantic tripole SST weakened obviously during 1980–2001 late winter, which was not detected in early winterThe eastward shift of ∼20° longitude in NAO south center forced the strong air‐sea interactions region to shift in observations and CMIP6NAO's spatial shift in late winter caused the changes in the link between NAO and North Atlantic tripole SST [ABSTRACT FROM AUTHOR]

High-resolution three-dimensional (3D) variations in ocean temperature and salinity fields are of great significance for ocean environment monitoring. Currently, AI-based 3D temperature and salinity field predictions rely on expensive 3D data, and as the prediction period increases, the stacking of high-resolution 3D data greatly increases the difficulty of model training. This paper transforms the prediction of 3D temperature and salinity into the prediction of sea surface elements and the inversion of subsurface temperature and salinity using sea surface elements, by leveraging the relationship between sea surface factors and subsurface temperature and salinity. This method comprehensively utilizes multi-source ocean data to avoid the issue of data volume caused by stacking high-resolution historical data. Specifically, the model first utilizes 1/4° low-resolution satellite remote sensing data to construct prediction models for sea surface temperature (SST) and sea level anomaly (SLA), and then uses 1/12° high-resolution temperature and salinity data as labels to build an inversion model of subsurface temperature and salinity based on SST and SLA. The prediction model and inversion model are integrated to obtain the final high-resolution 3D temperature and salinity prediction model. Experimental results show that the 20-day prediction results in the two sea areas of the coastal waters of China and the Northwest Pacific show good performance, accurately predicting ocean temperature and salinity in the vast majority of layers, and demonstrate higher resource utilization efficiency. [ABSTRACT FROM AUTHOR]

Understanding past and present hydrosystem feedbacks to global ocean–atmospheric interactions represents one of the main challenges to preventing droughts, extreme events, and related human catastrophes in the face of global warming, especially in arid and semiarid environments. In eastern Africa, the El Niño–Southern Oscillation (ENSO) was identified as one of the primary drivers of precipitation variability affecting water availability. However, the northern East African Rift System (EARS) still suffers from the underrepresentation of predictive and ENSO teleconnection models because of the scarcity of local to regional historical or palaeo-data. In this paper, we provide a 50-year seasonal flood and drought chronicle of the Awash River catchment from the study of laminated sediment from Gemeri and Afambo lakes (central Afar region, Ethiopia) with the aim of reconstructing the magnitude of regional hydroclimatic events. Pluricentimetric micro-laminated lithogenic facies alternating with plurimillimetric carbonate-enriched facies are investigated in both lakes. We couple dating methods including radiocarbon, short-lived radionuclides, palaeomagnetic field variations, and varve counting on both lake deposits to build a high-resolution age model and to discuss the regional hydrosedimentary dynamics of the Awash River over the last ∼ 700 years with a focus on the last 50 years. Using a multiproxy approach, we observe that following a multicentennial enhanced hydrological period, the two lakes have experienced a gradual decrease in river load inflow since 1979 CE, attaining extreme drought and high evaporative conditions between 1991 and 1997 CE. In 2014, the construction of a dam and increased agricultural water management in the lower Awash River plain impacted the erodibility of local soils and the hydrosedimentary balance of the lake basins, as evidenced by a disproportionate sediment accumulation rate. Comparison of our quantitative reconstruction with (i) lake water surface evolution, (ii) the interannual Awash River flow rates, and (iii) the El Niño 3.4 model highlights the intermittent connections between ENSO sea surface temperature anomalies, regional droughts, and hydrological conditions in the northern EARS. [ABSTRACT FROM AUTHOR]

Hurricane Elsa was the first hurricane to impact the island of Barbados in more than 60 years. Global warming is expected to increase the number of intense hurricanes in the Atlantic Ocean, which present a greater risk of future devastating hurricane impacts on the island. This study investigates the meteorological conditions and rapid intensification of Elsa between June 27 and July 3, 2021, by using meteorological data sets and results from the Weather Research and Forecasting model. The study also uses damage assessment data to analyze wind damage caused to residential homes as Elsa passed over Barbados on July 2. Unusually warm sea surface temperatures for June/early July, and a strong North Atlantic Subtropical High that was positioned anomalously close to the Caribbean islands, contributed to Elsa's rapid intensification and its track across the Atlantic, respectively. It was also found that most reported damages on the island involved the complete or partial removal of roofs and were concentrated in and around the capital city Bridgetown, which is most likely due to the high concentration of poorly constructed houses in this area. Therefore, there is a need to improve the building codes of houses to ensure that they withstand strong hurricane winds. It was recommended that the implementation of a mandatory building code in addition to the provision of subsidies for low-income persons to improve their homes could aid with this issue. Furthermore, the paper highlights deficiencies in weather models in predicting the genesis and rapid intensification of Elsa, which highlights a need for improvements. Practical Applications: After more than 60 years without hurricanes in Barbados, Hurricane Elsa passed over Barbados on July 2, 2021, causing damage to the built environment on the island. Elsa was rated as a Category 1 hurricane. Unusually warm sea surface temperatures for June/early July and a strong high-pressure system that was positioned anomalously close to the Caribbean islands were responsible for Elsa's formation and trajectory over Barbados. Elsa exhibited rapid intensification—an increase in 1-min sustained wind speeds of more than 15 m s−1 in 24 h—but this intensification was not properly forecasted by weather prediction models. Most reported damages on the island involved the complete or partial removal of roofs. The highest concentration of damages was in and around Bridgetown. Barbados has a building code, but adherence to it is not mandatory. The enforcement of a mandatory building code would increase resilience of Barbados to hurricanes, but it would also require government subsidies for persons who cannot afford to build their houses up to code. It is imperative that the government and population take early action to prepare themselves before any devastating hurricane disasters in the future. [ABSTRACT FROM AUTHOR]

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This paper aims to analyze the North Brazil Current (NBC) rings during the initial 5 months of 2020 using surface currents derived from Automatic Identification System (AIS) data in comparison with altimetry-based Archiving, Validation and Interpretation of Satellite Oceanographic Data (AVISO) current fields. The region of NBC rings is characterized by relatively high marine traffic, facilitating an accurate current estimation. Our investigation primarily focused on a brief period coinciding with intensive in situ measurements (EUREC4A-OA experiment). The Angular Momentum Eddy Detection and tracking Algorithm (AMEDA) detection algorithm was then employed to detect and track eddies in both fields. Subsequently, a particular NBC ring present in the region in January and February 2020 was examined. The comparison demonstrated that AIS data exhibited the precision and resolution necessary to effectively identify the NBC rings and smaller surrounding eddies, aligning well with other datasets such as in situ measurements, sea surface temperature (SST), and sea surface salinity (SSS) data. Moreover, we established that AIS data yielded accurate regional velocity fields, as evidenced by an analysis of energy spectra. Furthermore, our analysis revealed that AIS data captured aspects of eddy–eddy interactions which were not adequately depicted in AVISO fields. [ABSTRACT FROM AUTHOR]

Ocean observational gridded products are vital for climate monitoring, ocean and climate research, model evaluation, and supporting climate mitigation and adaptation measures. This paper describes the 4th version of the Institute of Atmospheric Physics (IAPv4) ocean temperature and ocean heat content (OHC) objective analysis product. It accounts for recent developments in quality control (QC) procedures, climatology, bias correction, vertical and horizontal interpolation, and mapping and is available for the upper 6000 m (119 levels) since 1940 (more reliable after ∼ 1957) for monthly and 1°×1° temporal and spatial resolutions. IAPv4 is compared with the previous version, IAPv3, and with the other data products, sea surface temperatures (SSTs), and satellite observations. It has a slightly stronger long-term upper 2000 m OHC increase than IAPv3 for 1955–2023, mainly because of newly developed bias corrections. The IAPv4 0–2000 m OHC trend is also higher during 2005–2023 than IAPv3, mainly because of the QC process update. The uppermost level of IAPv4 is consistent with independent SST datasets. The month-to-month OHC variability for IAPv4 is desirably less than IAPv3 and the other OHC products investigated in this study, the trend of ocean warming rate (i.e., warming acceleration) is more consistent with the net energy imbalance at the top of the atmosphere than IAPv3, and the sea level budget can be closed within uncertainty. The gridded product is freely accessible at 10.12157/IOCAS.20240117.002 for temperature data (Cheng et al., 2024a) and at 10.12157/IOCAS.20240117.001 for ocean heat content data (Cheng et al., 2024b). [ABSTRACT FROM AUTHOR]

Sea surface temperature (SST) prediction plays an important role in scientific research, environmental protection, and other marine-related fields. However, most of the current prediction methods are not effective enough to utilize the spatial correlation of SSTs, which limits the improvement of SST prediction accuracy. Therefore, this paper first explores spatial correlation mining methods, including regular boundary division, convolutional sliding translation, and clustering neural networks. Then, spatial correlation mining through a graph convolutional neural network (GCN) is proposed, which solves the problem of the dependency on regular Euclidian space and the lack of spatial correlation around the boundary of groups for the above three methods. Based on that, this paper combines the spatial advantages of the GCN and the temporal advantages of the long short-term memory network (LSTM) and proposes a spatiotemporal fusion model (GCN-LSTM) for SST prediction. The proposed model can capture SST features in both the spatial and temporal dimensions more effectively and complete the SST prediction by spatiotemporal fusion. The experiments prove that the proposed model greatly improves the prediction accuracy and is an effective model for SST prediction. [ABSTRACT FROM AUTHOR]

Data on the reproductive biology of elasmobranchs are essential for understanding their life history. Published studies on batoid ray reproductive biology are comparatively scarce, leading to limited understanding and data gaps. The Oceania fantail ray, Taeniura lessoni, is a good example. This Data Deficient nearshore stingray is restricted to Melanesia, with lacking biological and ecological data, including reproduction. To expand upon the limited life-history data for this species, this short paper provides observational data on the reproductive condition in female T. lessoni, at Drawaqa Island, Fiji. Field work involved direct observations and ocean temperature measurements. Over 40 days spanning three months, 105 surveys were conducted across five sites, resulting in 71 sightings of the species. Based on spot patterns and body markings, four female individuals were identified. Between January and March 2024, these females exhibited convex dorsa indicating advanced gestation, transitioning to concave dorsa suggesting parturition. The presence of neonates from early March onwards coincided with the estimated parturition period inferred from the rays' condition. Furthermore, a female previously pregnant was photographed with a dermal abrasion around her pectoral fin, possibly indicating pre-copulatory biting, suggesting a continuous reproductive cycle. The average monthly water temperature at the surveyed sites remained relatively stable throughout the study. Collectively, our findings suggest that Drawaqa Island provides suitable habitat niches for reproductive activities in female T. lessoni. Repeated and long-term data is certainly needed to confirm either a continuous reproductive cycle or seasonal peaks. While preliminary, our observational data represents the first documentation on female reproductive condition in a stingray in Fiji. [ABSTRACT FROM AUTHOR]

Much research has raised concerns about how a warming planet will interact with natural cyclical climatic variations, and the implications for the resilience and vulnerability of coastal communities. As the anticipated effects of climate change will continue to intensify, it is necessary to understand the response and adaptive capacity of individuals and communities. Coastal communities in Ecuador have evolved in an environment of such cyclical climatic variations referred to as El Niño-Southern Oscillation (ENSO) and La Niña. These climatic events are frequently characterized by extreme variations in precipitation, violent storms, and coastal flooding during El Niño and lowered sea water temperatures and drought during La Niña. This paper draws on survey data and long-term ethnographic research in Ecuadorian coastal communities to explore how fishers understand the impacts of ENSO and implications for their livelihood decisions and resilience to climate variability. The results suggest that fishers along the coast of Ecuador understand and respond differentially to the impacts of ENSO depending on social, cultural, environmental, and geographical factors. These differential levels of response suggest that livelihood diversification may uphold social resilience, which has implications for how coastal communities may adapt to the increasingly harsh weather conditions predicted by many climate models. Our findings further suggest that the impacts of El Niño are more salient than the impacts of La Niña; these findings have significant implications for fisheries management and science communication. [ABSTRACT FROM AUTHOR]

In this paper, we explore different prognostic methods to account for skin sea surface temperature diurnal variations in a coupled ocean–atmosphere regional model of the Mediterranean Sea. Our aim is to characterise the sensitivity of the considered methods with respect to the underlying assumption of how the solar radiation shapes the warm layer of the ocean. All existing prognostic methods truncate solar transmission coefficient at a warm-layer reference depth that is constant in space and time; instead, we implement a new scheme where this latter is estimated from a chlorophyll dataset as the e -folding depth of solar transmission, which thus allows it to vary in space and time depending on seawater's transparency conditions. Comparison against satellite data shows that our new scheme, compared to the one already implemented within the ocean model, improves the spatially averaged diurnal signal, especially during winter, and the seasonally averaged one in spring and autumn, while showing a monthly basin-wide averaged bias smaller than 0.1 K year-round. In April, when most of the drifters' measurements are available, the new scheme mitigates the bias during nighttime, keeping it positive but smaller than 0.12 K during the rest of the monthly averaged day. The new scheme implemented within the ocean model improves the old one by about 0.1 K, particularly during June. All the methods considered here showed differences with respect to objectively analysed profiles confined between 0.5 K during winter and 1 K in summer for both the eastern and the western Mediterranean regions, especially over the uppermost 60 m. The new scheme reduces the RMSE on the top 15 m in the central Mediterranean for summertime months compared to the scheme already implemented within the ocean model. Overall, the surface net total heat flux shows that the use of a skin sea surface temperature (SST) parameterisation brings the budget about 1.5 Wm-2 closer to zero on an annual basis, despite all simulations showing an annual net heat loss from the ocean to the atmosphere. Our "chlorophyll-interactive" method proved to be an effective enhancement of existing methods, its strength relying on an improved physical consistency with the solar extinction implemented in the ocean component. [ABSTRACT FROM AUTHOR]

The number and coverage of weather observations over the oceans were considerably reduced during World War II (WW2) due to disruptions to normal trade routes. The observations that do exist for this period are often unavailable to science as they are still only available as paper records or scanned images. We have rescued the detailed hourly weather observations contained in more than 28,000 logbook images of the US Navy Pacific Fleet stationed at Hawai'i during 1941–1945 to produce a dataset of more than 630,000 records. Each record contains the date and time, positional information and several meteorological measurements, totalling more than 3 million individual observations. The data rescue process consisted of a citizen science project asking volunteers to transcribe the observations from the available images, followed by additional quality control processes. This dataset not only contains hourly weather observations of air temperature, sea surface temperature, atmospheric pressure, wind speed and wind direction, mainly in the Pacific Ocean but also includes some observations from the Atlantic and Indian Oceans. The new observations are found to be of good quality by inter‐comparing independent measurements taken on ships travelling in convoy and by comparing with the 20th‐Century Reanalysis. This dataset provides invaluable instrumental weather observations at times and places during WW2, which fill gaps in existing reconstructions. [ABSTRACT FROM AUTHOR]

Wave-induced radiation stress (RS), as a primary driver of ocean currents influenced by waves, plays an important role in the response of upper ocean temperatures under typhoons. Previous studies have mainly focused on wave-generated currents and coastal currents in nearshore areas. This paper incorporates the geostrophic effect into the wave-induced radiation stress of wave-current interaction, and the effect of waves on the changes in upper ocean temperature (including sea surface temperature (SST) and mixed layer temperature) under typhoon Nanmadol (2022) is studied. The FVCOM-SWAVE model is used to conduct a preliminary numerical study in the western Pacific Ocean. The RS with the geostrophic effect increased the horizontal and vertical components, leading to an enhancement in turbulent mixing and a decrease in SST by up to 1.0 °C to 1.4 °C, which is closer to the SST obtained by OISST remote sensing fusion observation data. In the strong divergence domain, the direction of the vortex flow exhibits a more pronounced turn to the right, accompanied by an increase in water velocity. The vertical temperature profile of the ocean shows that the water below is perturbed by the RS component of the geostrophic effect, and the depth of the mixed layer increases by about 2 m, which is closer to the depth of the mixed layer observed by the Argo floats, indirectly enhancing the vertical mass transport of the ocean. In general, this shows that RS, which takes into account geostrophic effects, enhances the effect of waves on the water below, indirectly leading to lower temperatures in the upper ocean, and the simulated results align more closely with the observed data, offering valuable insights for enhancing marine numerical forecasting accuracy. [ABSTRACT FROM AUTHOR]

This paper evaluates Indo-Pacific warm pool (IPWP) sea surface temperature (SST) warming biases of Coupled Model Intercomparison Project Phase 5 (CMIP5) and CMIP6. The IPWP warming trend in the CMIP5 multi-model ensemble (MME) is closer to observation than in CMIP6 MME, but the IPWP expanding trend is the opposite. There is no qualitative improvement in the simulation of IPWP warming from CMIP5 to CMIP6. In addition, four metrics were used to investigate the performance of Indo-Pacific region warming trends in all models. CMIP6 models perform better than CMIP5 with smaller root mean square error and bias in MME and higher skill scores in MME and top models, which is tightly linked to their better performance in simulating associated physical processes in CMIP6 models. IPWP warming biases are mainly attributed to the combined effects of positive atmospheric process biases and negative ocean dynamics term biases. The positive atmospheric process biases are primarily related to the shortwave radiation and latent heat flux from atmospheric forcing, the latter of which can be attributed to the biases in surface wind fields. Compared with CMIP5 models, the IPWP warming simulated by CMIP6 models is weaker, related to the less robust atmospheric processes and the shallower thermocline anomalies simulated by CMIP6. [ABSTRACT FROM AUTHOR]

Atmospheric rivers (ARs), responsible for extreme weather conditions, are mid-latitude systems that can cause significant damage to coastal areas. While forecasting ARs beyond two weeks remains a challenge, past research suggests potential benefits may come from properly accounting for the changes in sea surface temperature (SST) through air–sea interactions. In this paper, we investigate the impact of ARs on SST over the North Pacific by analyzing 25 years of ocean reanalysis data using an SST budget equation. We show that in the region of strong ocean modification, ocean dynamics can offset over 100% of the anomalous SST warming that would otherwise arise from atmospheric forcing. Among all ocean processes, ageostrophic advection and vertical mixing (diffusion and entrainment) are the most important factors in modifying the SST tendency response. The SST tendency response to ARs varies spatially. For example, in coastal California, the driver of enhanced SST warming is the reduction in ageostrophic advection due to anomalous southerly winds. Moreover, there is a large region where the SST shows a warming response to ARs due to the overall reduction in the total clouds and subsequent increase in total incoming shortwave radiation. Strong air-sea interactions during atmospheric rivers often lead to modest upper ocean heat changes. The authors show that interior ocean dynamics are compensating for these air-sea exchanges. These findings can help improve subseasonal forecasts. [ABSTRACT FROM AUTHOR]

The yellowfin tuna represents a significant fishery resource in the Pacific Ocean. Its resource endowment status and spatial variation mechanisms are intricately influenced by marine environments, particularly under varying climate events. Consequently, investigating the spatial variation patterns of dominant environmental factors under diverse climate conditions, and understanding the response of yellowfin tuna catch volume based on the spatial heterogeneity among these environmental factors, presents a formidable challenge. This paper utilizes comprehensive 5°×5° yellowfin tuna longline fishing data and environmental data, including seawater temperature and salinity, published by the Western and Central Pacific Fisheries Commission (WCPFC) and the Inter-American Tropical Tuna Commission (IATTC) for the period 2000–2021 in the Pacific Ocean. In conjunction with the Niño index, a multiscale geographically weighted regression model based on geographically weighted principal component analysis (GWPCA-MGWR) and spatial association between zones (SABZ) is employed for this study. The results indicate the following: (1) The spatial distribution of dominant environmental factors affecting the catch of Pacific yellowfin tuna is primarily divided into two types: seawater temperature dominates in the western Pacific Ocean, while salinity dominates in the eastern Pacific Ocean. When El Niño occurs, the area with seawater temperature as the dominant environmental factor in the western Pacific Ocean further extends eastward, and the water layers where the dominant environmental factors are located develop to deeper depths; when La Niña occurs, there is a clear westward expansion in the area with seawater salinity as the dominant factor in the eastern Pacific Ocean. This change in the spatial distribution pattern of dominant factors is closely related to the movement of the position of the warm pool and cold tongue under ENSO events. (2) The areas with a higher catch of Pacific yellowfin tuna are spatially associated with the dominant environmental factor of mid-deep seawater temperature (105–155 m temperature) to a greater extent than other factors, the highest correlation exceeds 70%, and remain relatively stable under different ENSO events. The formation of this spatial association pattern is related to the vertical movement of yellowfin tuna as affected by subsurface seawater temperature. (3) The GWPCA-MGWR model can fully capture the differences in environmental variability among subregions in the Pacific Ocean under different climatic backgrounds, intuitively reflect the changing areas and influencing boundaries from a macro perspective, and has a relatively accurate prediction on the trend of yellowfin tuna catch in the Pacific Ocean. [ABSTRACT FROM AUTHOR]

The analysis of tephra layers in maar lake sediments of the Eifel shows 14 well-visible tephra during the last glacial cycle from the Holocene to the Eemian (0–130,000 yr b2k). These tephra were analyzed for their petrographic composition, which allows us to connect several tephra to eruption sites. All tephra were dated by application of the ELSA-20 chronology, developed using the late Pleistocene infilled maar lake of Auel and the Holocene lake Holzmaar (0–60,000 yr b2k). We extend the ELSA-20 chronology with this paper for the millennia of 60,000–130,000 yr b2k (ELSA-23 chronology), which is based on the infilled maar lake records from Dehner, Hoher List, and Jungferweiher. The evaluation of the tephra from the entire last glacial cycle shows that all 14 tephra were close to interstadial warming of the North Atlantic sea surface temperatures. In particular, phreatomagmatic maar eruptions were systematically associated with Heinrich events or C-events. These events represent times of warming of the Southern Hemisphere, global sea level rise, and CO2 increase, which predate the abrupt interstadial warming events of the Northern Hemisphere. This synchroneity indicates a physical relationship between endogenic and exogenic processes. Changes in the lithospheric stress field in response to changes in continental ice loads have already been suggested as a potential candidate to explain the exogenic forcing of endogenic processes. The chronology of volcanic activity in the Eifel demonstrates that intraplate mantle plumes are also affected by the exogenic forcing of endogenic processes. [ABSTRACT FROM AUTHOR]

Argo floats are widely used to characterize vertical structures of ocean eddies, yet their capability to invert sea surface features of eddies, especially those overlooked by available altimeters, has not been explored. In this paper, we propose an "interior-to-surface" inversion algorithm to effectively expand the capacity of eddy detection by estimating altimeter-missed eddies' surface attributes from their Argo-derived potential density anomaly profiles, given that the interior property and surface signature of eddies are highly correlated. An altimeter-calibrated machine learning ensemble is employed for the inversion training based on the joint altimeter–Argo eddy data and shows promising performance with mean absolute errors of 5.4 km, 0.5 cm, and 14.3 cm2 s−2 for eddy radius, amplitude, and kinetic energy, respectively. Then, the trained ensemble model is applied to independently invert the properties of eddies captured by an Argo-alone detection scheme, which yields high spatiotemporal consistency with their altimeter-captured counterparts. In particular, a portion of Argo-alone eddies is ∼25% smaller than altimeter-derived ones, indicating Argo's unique capability of profiling weaker submesoscale eddies. Sea surface temperature and chlorophyll data are further applied to validate the reliability of eddies identified and characterized by the Argo-only algorithm. This new methodology effectively complements that of altimetry in eddy detection and can be expanded to estimate other physical/biochemical eddy variables from a variety of in situ observations. Significance Statement: Despite thousands of eddies being routinely identified on a daily basis, it has been recognized that a substantial portion of eddies may still be missed due to inadequate sampling of altimeter constellations. Taking advantage of eddy's correlation between surface and interior, a considerable number of eddies are discovered for the first time through an Argo-based eddy identification scheme. Here, we propose a new methodology to independently infer these recaptured eddies' surface properties from their vertical signals through an "interior-to-surface" inversion process. The inferred eddy properties are verified by the spatiotemporal consistency with those derived from altimetry. Since Argo is capable of profiling smaller and weaker eddies, the proposed methodology significantly complements and expands that of altimetry in eddy observation. [ABSTRACT FROM AUTHOR]

The Northeastern China cold vortex (NCCV) is one type of strong cyclonic vortex that occurs near Northeastern China (NEC), and NCCV activities are typically accompanied by a series of hazardous weather. This paper employed an automatic algorithm to identify the NCCVs from 1979 to 2018 and analyzed their circulation patterns and climatic impacts by using the defined NCCV intensity index (NCCVI). The analysis revealed that the NCCV activities in summer exhibited a strong inter-annual variability, with an obvious periodicity of 3-4 years and 6-7 years, but without significant trends. In years when the NCCVI was high, NEC experienced negative geopotential height anomalies, cyclonic circulation, and cooler temperature anomalies, which were conducive to the maintenance and development of NCCV activities. Furthermore, large amounts of water vapor converged in NEC through two transportation routes as the NCCVs intensified, leading to a significant positive (negative) correlation with the summer precipitation (surface temperature) in NEC. The Atlantic sea surface temperature (SST) anomalies were closely related to summer NCCV activities. As the Atlantic SST rose, large amounts of surface sensible and latent heat flux were transported into the lower troposphere, inducing a positive geopotential height anomaly that occurred on the east side of the heat source. As a result, an eastward diverging flow was formed in the upper troposphere and propagated downstream, i.e., the eastward propagating Rossby wave train, which eventually led to a coupled circulation in the Ural Mountains and NEC, as well as more intensive NCCV activities in summer. [ABSTRACT FROM AUTHOR]

The amount of radiative energy received at the Earth's surface depends on two factors: Earth–Sun distance and sunlight angle. Because of the former, high-eccentricity cycles can induce the appearance of seasons in the tropical ocean. In this paper, we use the Earth system model IPSL-CM5A2 to investigate the response of the low-latitude ocean to variations in Earth's orbit eccentricity. Sea surface temperature (SST) and primary production (PP) were simulated under six precession configurations at high eccentricity and two configurations at low eccentricity, representing extreme configurations observed over the past 1 million years. Results show that high eccentricity leads to increased seasonality in low-latitude mean SST, with an annual thermal amplitude of approximately 2.2 °C (vs. 0.5 °C at low eccentricity). Low-latitude mean PP, which already exhibits inherent seasonality under low-eccentricity conditions, sees its seasonality largely increased under high eccentricity. As a consequence, we show that on long timescales the intensity of SST seasonality exhibits only the eccentricity frequency, whereas that of PP additionally follows precession dynamics. Furthermore, the seasonal variations in both SST and PP at high eccentricities are influenced by the annual placement of the perihelion with its direct impact of radiative energy received in tropical regions. This leads to a gradual and consistent transition of seasons within the calendar. We introduce the concept of "eccentriseasons", referring to distinct annual thermal differences observed in tropical oceans under high-eccentricity conditions, which shift gradually throughout the calendar year. These findings have implications for understanding low-latitude climate phenomena such as the El Niño–Southern Oscillation (ENSO) and monsoons in the past. [ABSTRACT FROM AUTHOR]

Accurate prediction of ocean surface currents is important for marine safety, ship routing, tracking of pollutants and in coupled forecasting. Presently, velocity observations are not routinely assimilated in global ocean forecasting systems, largely due to the sparsity of the observation network. Several satellite missions are now being proposed with the capability to measure Total Surface Current Velocities (TSCV). If successful, these would substantially increase the coverage of ocean current observations and could improve accuracy of ocean current forecasts through data assimilation. In this paper, Observing System Simulation Experiments (OSSEs) are used to assess the impact of assimilating TSCV in the Met Office's global ocean forecasting system. Synthetic observations are generated from a high-resolution model run for all standard observation types (sea surface temperature, profiles of temperature and salinity, sea level anomaly and sea ice concentration) as well as TSCV observations from a Sea surface KInematics Multiscale monitoring (SKIM) like satellite. The assimilation of SKIM like TSCV observations is tested over an 11 month period. Preliminary experiments assimilating idealised single TSCV observations demonstrate that ageostrophic velocity corrections are not well retained in the model. We propose a method for improving ageostrophic currents through TSCV assimilation by initialising Near Inertial Oscillations with a rotated incremental analysis update (IAU) scheme. The OSSEs show that TSCV assimilation has the potential to significantly improve the prediction of velocities, particularly in the Western Boundary Currents, Antarctic Circumpolar Current and in the near surface equatorial currents. For global surface velocity the analysis root-mean-squareerrors (RMSEs) are reduced by 23% and there is a 4-day gain in forecast RMSE. There are some degradations to the subsurface in the tropics, generally in regions with complex vertical salinity structures. However, outside of the tropics, improvements are seen to velocities throughout the water column. Globally there are also improvements to temperature and sea surface height when TSCV are assimilated. The TSCV assimilation largely corrects the geostrophic ocean currents, but results using the rotated IAU method show that the energy at inertial frequencies can be improved with this method. Overall, the experiments demonstrate significant potential benefit of assimilating TSCV observations in a global ocean forecasting system. [ABSTRACT FROM AUTHOR]

Recent studies have highlighted the increasingly dominant role of external forcing in driving Atlantic and Pacific Ocean variability during the second half of the 20th century. This paper provides insights into the underlying mechanisms driving interactions between modes of variability over the two basins. We define a set of possible drivers of these interactions and apply causal discovery to reanalysis data, two ensembles of pacemaker simulations where sea surface temperatures in either the tropical Pacific or the North Atlantic are nudged to observations, and a pre-industrial control run. We also utilize large-ensemble means of historical simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to quantify the effect of external forcing and improve the understanding of its impact. A causal analysis of the historical time series between 1950 and 2014 identifies a regime switch in the interactions between major modes of Atlantic and Pacific climate variability in both reanalysis and pacemaker simulations. A sliding window causal analysis reveals a decaying El Niño–Southern Oscillation (ENSO) effect on the Atlantic as the North Atlantic fluctuates towards an anomalously warm state. The causal networks also demonstrate that external forcing contributed to strengthening the Atlantic's negative-sign effect on ENSO since the mid-1980s, where warming tropical Atlantic sea surface temperatures induce a La Niña-like cooling in the equatorial Pacific during the following season through an intensification of the Pacific Walker circulation. The strengthening of this effect is not detected when the historical external forcing signal is removed in the Pacific pacemaker ensemble. The analysis of the pre-industrial control run supports the notion that the Atlantic and Pacific modes of natural climate variability exert contrasting impacts on each other even in the absence of anthropogenic forcing. The interactions are shown to be modulated by the (multi)decadal states of temperature anomalies of both basins with stronger connections when these states are "out of phase". We show that causal discovery can detect previously documented connections and provides important potential for a deeper understanding of the mechanisms driving changes in regional and global climate variability. [ABSTRACT FROM AUTHOR]

Simple Summary: Ten years of Mediterranean monk seal stranding data along the Greek coastal areas were analyzed. The spatial distribution of stranding events along with the associated causes of death were modeled and mapped, while the relationship between the possibility of a stranding event and environmental and anthropogenic factors was thoroughly explored. The number of stranding events was found to be higher during the winter period. Moreover, the values of two major teleconnection oscillation indices during the first half of the year as well as the sea surface temperature in the Mediterranean from October to December were positively correlated with the number of stranding events of "unknown" cause. The size of fishing grounds and the number of sightings were associated with a higher probability of "human-related" stranding events. Finally, the central Aegean Sea was found to be a hotspot for "human-related" strandings, while, the eastern Ionian Sea, the southern coasts of the island of Cephalonia, and the gulf between the island of Lefkada and mainland Greece were found to present higher probabilities of monk seal subadult stranding events. This paper presents the results of an analysis of stranding events of the Mediterranean monk seal Monachus monachus over a decade. The analysis involved categorization according to the cause of stranding and seasonality, the identification of hotspot stranding areas and an assessment of possible correlations between stranding events and environmental/climatic patterns using time series analysis. Moreover, Generalized Additive Models (GAMs) were applied to explore the effects of the size of small-scale fishing grounds, the number of species sightings, and the occurrence of reproduction sites on "human-related" strandings. Finally, special focus was put on the central part of the eastern Ionian Sea for the assessment of stranding hotspot areas by means of the Multi-Criteria Decision Analysis (MCDA) approach, based on different kinds of spatial information such as anthropogenic pressures and the location of breeding sites and feeding grounds. Time series analysis results revealed that oscillation indices, during the first half of the year, and sea surface temperature (SST) in the Mediterranean from October to December were positively correlated with monk seal stranding events. GAMs underlined that areas combining extended small-scale fishery grounds and a higher number of sightings were more likely to cause more strandings. Regarding spatial analyses, the central Aegean Sea was highlighted as a hotspot for "human-related strandings", while the MCDA approach emphasized that the southern coasts of Cephalonia and the gulf between Lefkada and mainland Greece were susceptible to subadult strandings. [ABSTRACT FROM AUTHOR]

A multi-season convection-permitting regional climate simulation of the Maritime Continent (MC) using the Met Office Unified Model (MetUM) with 2.2 km grid spacing is presented and evaluated. The simulations pioneer the use of atmosphere–ocean coupling with the multi-column K profile parametrisation (KPP) mixed-layer ocean model in atmospheric convection-permitting climate simulations. Comparisons are made against a convection-parametrised simulation in which it is nested and which in turn derives boundary conditions from the ERA5 reanalysis. This paper describes the configuration, performance of the mean state and variability in the two simulations compared against observational datasets. The models have both minor sea surface temperature (SST) and wet precipitation biases. The diurnal cycle, representation of equatorial waves, and relationship between SST and precipitation are all improved in the convection-permitting model compared to the convection-parametrised model. The Madden–Julian oscillation (MJO) is present in both models with a faster-than-observed propagation speed. However, it is unclear whether fidelity of the MJO simulation is inherent to the model or whether it predominantly arises from the forcing at the boundaries. [ABSTRACT FROM AUTHOR]

Sea ice, as an important component of the Earth's ecosystem, has a profound impact on global climate and human activities due to its thickness. Therefore, the inversion of sea ice thickness has important research significance. Due to environmental and equipment-related limitations, the number of samples available for remote sensing inversion is currently insufficient. At high spatial resolutions, remote sensing data contain limited information and noise interference, which seriously affect the accuracy of sea ice thickness inversion. In response to the above issues, we conducted experiments using ice draft data from the Beaufort Sea and designed an improved GBDT method that integrates feature-enhancement and active-learning strategies (IFEAL-GBDT). In this method, the incident angle and time series are used to perform spatiotemporal correction of the data, reducing both temporal and spatial impacts. Meanwhile, based on the original polarization information, effective multi-attribute features are generated to expand the information content and improve the separability of sea ice with different thicknesses. Taking into account the growth cycle and age of sea ice, attributes were added for month and seawater temperature. In addition, we studied an active learning strategy based on the maximum standard deviation to select more informative and representative samples and improve the model's generalization ability. The improved GBDT model was used for training and prediction, offering advantages in dealing with nonlinear, high-dimensional data, and data noise problems, further expanding the effectiveness of feature-enhancement and active-learning strategies. Compared with other methods, the method proposed in this paper achieves the best inversion accuracy, with an average absolute error of 8 cm and a root mean square error of 13.7 cm for IFEAL-GBDT and a correlation coefficient of 0.912. This research proves the effectiveness of our method, which is suitable for the high-precision inversion of sea ice thickness determined using Sentinel-1 data. [ABSTRACT FROM AUTHOR]

In this paper, based on an Fe-based amorphous alloy, four kinds of RGO/Cu/Fe-based amorphous composite coatings with mass ratios of 5%, 10%, 15%, and 20% of RGO/Cu were prepared on the surface of 45# steel by using high-velocity oxy-fuel (HVOF) spraying. The coatings were immersed in simulated seawater at room temperature and at 90 °C for different lengths of time, and their corrosion resistance was tested using electrochemical impedance spectroscopy (EIS), scanning electron microscopy (SEM), and X-ray diffraction (XRD), and the surface morphology and phase distribution of the samples were observed. The results showed that with the increase in the introduction ratio of RGO/Cu, when the addition ratio reached 15%, the composite coating had the best corrosion resistance. After soaking in simulated seawater at 90 °C for 18 days, the surface of the coating showed slight peeling and crack propagation, but no obvious pitting phenomenon occurred. The corrosion mechanism of the RGO/Cu/Fe coating in high-temperature seawater is mainly that high temperature causes the cracking of the coating, which opens up a transport channel for corrosion media. However, due to the addition of RGO, the corrosion has a certain self-limitation effect, which is mainly due to the toughening effect of RGO on the coating and its effect on extending the corrosion channel. [ABSTRACT FROM AUTHOR]

Sea surface temperature (SST) is a key variable in the study of the global climate system and one of the important parameters in the process of air–sea interaction. Therefore, the demand for SST is developing towards high quality and high precision. In this paper, the ability of the multi-layer perceptron (MLP) optimized by the Aquila optimizer (AO) to solve nonlinear problems and the advantages of the deep belief network (DBN) to effectively process complex data are used to construct the IMLP-DBN inversion algorithm. The algorithm takes into account the influences of atmospheric conditions and satellite zenith angles. The data set is the infrared remote sensing data of the moderate resolution imaging spectroradiometer (MODIS) and the actual measurement data of buoys on sunny days and few clouds. Analysis of the inversion results shows that the root mean square error (RMSE) of the inversion value and the measured value is 0.14, and the sum of square errors (SSE) is 0.78. Compared with the MOD28 product data, the RMSE and SSE of the inversion are reduced by 66% and 24%, respectively. [ABSTRACT FROM AUTHOR]

Continental shelves are amongst the most dynamic and vulnerable regions in the oceans, and understanding their dynamics has implications for the transport of organisms and materials in both coastal and offshore zones. Determining the circulation patterns in systems experiencing high variability is crucial, but challenging as continuous and high‐resolution long‐term data sets are still scarce. In this paper, we use 9‐years (2010–2018) of High‐Frequency Radar surface current observations and satellite‐derived Sea Surface Temperature to investigate the spatiotemporal variability of surface currents on the offshore, shelf break and inner continental regions along the Wadjemup (Rottnest) Continental Shelf (WCS), South‐West Australia. We use the indigenous Noongar calendar that defines six‐seasons: Birak (DJ), Bunuru (FM), Djeran (AM), Makuru (JJ), Djilba (AS), and Kambarang (ON); to better represent the seasonal changes in local winds and surface circulation. The surface currents revealed the poleward‐flowing Leeuwin Current (LC), the equatorward‐flowing Capes Current (CC), their interactions, and eddy features (radii >10 km). The LC was the strongest (weakest) over Djeran/Makuru (Birak/Bunuru), whilst CC and offshore eddies were persistent from Kambarang‐Bunuru. Along WCS, CC and offshore eddies locally modulated LC strength and position, whereas the El Niño Southern Oscillation influenced its interannual variability. During El Niño (La Niña) years, LC was weakened (strengthened), whilst CC and offshore eddy activity were strengthened (weakened). Particularly during La Niña years, LC increased its cross‐shore migration and had an unseasonal peak in 2011. Our findings contribute to the understanding of the variability of boundary and coastal currents, and their local impacts on coastal circulation. Plain Language Summary: Variability in surface circulation influences the transport of suspended material and organisms. We investigated how patterns of surface currents change over intra‐seasonal, seasonal to interannual timescales across the Wadjemup (Rottnest) Continental Shelf using 9 years of High‐Frequency Radar maps of surface current and satellite Sea Surface Temperature (SST). The current patterns in the offshore, continental shelf break and the inner continental shelf were compared to local winds, sea level, and El Niño Southern Oscillation (ENSO) events to explain observed patterns. We adopted the 6 Noongar seasons to better represent winds and surface circulation variability. Results revealed distinct surface flow patterns along WCS: the poleward‐flowing Leeuwin Current (LC), the equatorward‐flowing Capes Current (CC) and associated eddy features. LC was the strongest (weakest) over Djeran (AM)/Makuru (JJ) (Birak (DJ)/Bunuru (FM)), whilst CC and offshore eddies were persistent during Kambarang (ON)‐Bunuru. The interannual variability of surface flows were modulated by ENSO. During El Niño (La Niña) years, LC was weakened (strengthened), whilst CC and offshore eddy activity were strengthened (weakened). Particularly during La Niña years, LC increased its cross‐shore migration and had an unseasonal peak in currents in 2011. Key Points: Long‐term HFR‐surface current observations revealed different flow regimes with strong spatiotemporal variability across the continental shelf and slopeSeasonal surface flow patterns reflected wind forcing related to local indigenous seasonsEl Niño Southern Oscillation events controlled the inter‐annual variability in the surface currents [ABSTRACT FROM AUTHOR]

Sea surface temperature (SST) significantly influences the dynamics of the global climate system, impacting climate change, marine ecosystems, and marine engineering. Traditional SST prediction methods, such as time series and machine learning models, often focus solely on temporal features and neglect spatial distribution patterns. In contrast, current deep learning techniques typically limit predictions to short-term periods. This paper introduces a novel SST prediction model that integrates both temporal and spatial dimensions, employing parallel prediction and a spatio-temporal attention mechanism to enhance accuracy. The model achieves long-term SST forecasting, significantly reduces the parameter count and computational effort, and maintains high prediction precision. Experiments in the El Niño 3.4 region and the East China Sea show that this method outperforms existing deep learning approaches, accurately predicting SST over periods ranging from 7 to 60 days with superior efficiency and accuracy. Overall, this work presents an effective new approach for SST prediction with crucial implications for climate change research, marine ecosystems, and marine engineering. [ABSTRACT FROM AUTHOR]

By using ERA5 reanalysis data, this paper combined existing research definitions of gale processes to analyze the variation characteristics of gale processes occurring in the South China Sea region, and to study the response of the gale process to East Pacific sea surface temperature. The results indicate that the gale process shows the significant annual variation and the most frequent in winter and least frequent in summer. While there is no significant trend in the frequency of gale processes in each season. There is a significant negative correlation between the frequency of gale process and the East Pacific sea surface temperature in spring, autumn, and winter. When the sea surface temperature in the eastern Pacific rises abnormally, the frequency of gale processes in the South China Sea decreases. When abnormally high, the frequency of gale process in the South China Sea increases. In summer, this relationship is the opposite. When sea surface temperature is abnormal, the anomalous anticyclone triggered in the western Pacific, and has a weakening effect on the prevailing winds in the South China Sea, leading to a reduction in high wind speed and gale events, thereby reducing the frequency of gale process. [ABSTRACT FROM AUTHOR]

Marine heatwave (MHW) events have significant consequences for marine ecosystems and human society. This paper investigates a MHW's spatial–temporal characteristics in the Changjiang River Estuary and its surrounding coastal regions (CRESs), as well as analyzes the drivers, using satellite and reanalysis data spanning from 1982–2021. The findings show that, during the last 40 years, all four of the MHW indicators have increased. The summer MHW is more severe than other seasons, showing a rising pattern from southeast to northwest. The rise of MHWs can be attributed to the increase in sea surface heat flux, weak wind speed, and powerful El Niño events. Additionally, two special MHW events were detected during the entire study period: Event A lasted for 191 days from 9 October 2006 to 17 April 2007; Event B had an average intensity of 4.93 °C from 5 July 1994 to 1 August 1994. For locations so close to each other, the characteristics of MHWs can also vary, and the mechanisms behind them are highly complex. [ABSTRACT FROM AUTHOR]

In this reply to the discussion of our paper (Kumar et al. in Nat Hazards 116:2437–2455, 2023), we attempt to rebut the claims made regarding the use of the maximum sustained wind speed of a cyclone event irrespective of its location, inappropriate implementation of fitting methods, and inconsistent use of future projected sea surface temperature to historical records. While the discussion highlights certain observations about our results, the application of such techniques for evaluating PMTC parameters (adhering to AERB criteria) requires further research. [ABSTRACT FROM AUTHOR]

This review will serve as an entry point for international researchers who would like to tap into the vast scientific potential of Chinese-language literature on oceanic fronts. We focused on observational physical oceanography studies of marine fronts. A thorough bibliographic search netted 95 papers published in 1982–2023, with a sharp increase in the total number of papers from 2006–2010 to 2011–2015, when this number almost tripled. This trend continued unabated through the early 2020s. The sharp increase in Chinese-language publications preceded by several years a rapid increase in English-language publications in the same field. Regionally, the overwhelming majority of papers is focused on the China Seas, particularly the East China Seas and northern South China Sea. Elsewhere, a number of papers were dedicated to the Southern Ocean and North Atlantic. Thematically, papers on remote sensing of ocean fronts dominate the literature, with special attention to the development of front-detection algorithms that can be applied to satellite data on sea surface temperature, salinity, chlorophyll, and sea level anomaly. Numerous papers on marine fronts in the China Seas present important results that have to be considered by international researchers. Overall, this review emphasizes the significant contributions made by Chinese oceanographers, particularly to studies of the frontal oceanography of the China Seas. [ABSTRACT FROM AUTHOR]

This study addresses a critical gap in understanding anthropogenic influences on tropical climate dynamics by investigating the impact of aerosol‐cloud interactions on large‐scale circulation. Despite extensive research on greenhouse gas‐induced warming and its effects on tropical circulation, the impact of aerosols, particularly their interactions with clouds, on large‐scale circulation remains understudied. Utilizing large‐domain radiative convective equilibrium cloud‐resolving simulations, this research demonstrates that increasing aerosol concentration intensifies tropical overturning circulation, evaluated at the mid‐troposphere (I) $(\mathcal{I})$, strongly correlating with domain mean cloud and radiative properties. Employing a weak temperature gradient approximation, I attribute variations in I $\mathcal{I}$ to changes in clear‐sky radiative cooling rather than stability. These radiative cooling changes are linked to humidity changes driven by warm rain suppression by aerosols. This study's findings underscore the need to take into account microphysical changes, particularly aerosol concentrations, when studying anthropogenic effects on tropical circulation. Plain Language Summary: Clouds intricately couple with the large‐scale overturning circulation in the tropics. Aerosols, small particles suspended in the atmosphere, interact with clouds. Thus, changes in aerosols concentration (Na) have the potential to affect cloud properties and by that the large‐scale circulation, with important implications for tropical climate and climate change. Despite this crucial relationship, the subject has been insufficiently explored. In this paper, I use a simplified, yet realistic, representation of the tropical atmosphere—radiative convective equilibrium large‐domain cloud‐resolving simulations—to investigate the effect of aerosol‐cloud interaction on overturning tropical circulation. By varying Na under diverse sea surface temperatures, I demonstrate that the strength of the overturning circulation intensifies with increasing Na. Utilizing a semi‐analytical expression for subsidence strength in clear‐sky tropical regions, I show that the intensified overturning circulation with increased Na can be attributed to heightened humidity in the mid‐troposphere, leading to intense radiative cooling. This mid‐tropospheric humidification can be explained by warm rain suppression by aerosols, which fosters stronger humidity mixing between clouds and their surroundings. These findings underscore the need to consider aerosol concentration changes when examining anthropogenic impacts on tropical circulation. Key Points: The overturning tropical circulation intensifies with aerosol concentration in a radiative convective equilibrium modelChanges in circulation strength can be explained by changes in diabatic subsidence driven by radiative changesRadiative changes can be explained by increased humidity at the mid‐troposphere due to warm rain suppression [ABSTRACT FROM AUTHOR]

Ulva prolifera (U. prolifera) green tide outbreaks have occurred in the Yellow Sea of China for many years, causing serious losses to marine ecology and the marine economy. The monitoring and tracking of U. prolifera green tide is a crucial aspect of marine ecological disaster prevention and control management. This paper aims to investigate the spatiotemporal distribution changes in U. prolifera green tide in the Yellow Sea throughout its life cycle. A survey of the Yellow Sea from 2008 to 2023 was conducted using multi-source remote sensing images. Long-term monitoring and analysis of U. prolifera revealed the evolution process of the green tide, including the early development, outbreak, decline, and extinction stages, considering time, space, and frequency of occurrence. Additionally, this study examined peak coverage change patterns over the past 16 years and analyzed the influence of environmental factors such as sea surface temperature and sea surface wind field on the development of U. prolifera. The research results serve as a valuable reference for the monitoring, early warning, and scientific prevention and control of U. prolifera green tide in the Yellow Sea, as well as other similar marine disaster areas. [ABSTRACT FROM AUTHOR]

Basalt fiber–reinforced polymer (BFRP), a composite material known for its cost-effectiveness and excellent resistance to chloride ion corrosion, combined with environmentally friendly geopolymer is expected to contribute to the development of sustainable marine engineering structures. However, concerns still remain regarding the durability of this structure in marine environments. This paper presents an experimental investigation of the durability of basalt fiber–reinforced polymer bars immersed in seawater under the combined effects of the seawater sea-sand geopolymer mortar (SSGM) covering and prestressing. The prestress level was maintained at 20% of the ultimate tensile strength of the BFRP at room temperature in the first 7 days; the alkaline content of the SSGM, represented by the mass ratio of Na2O in the alkaline activator to the precursor, was either 4% or 6%; and the seawater temperatures were room temperature, 40°C, or 60°C. The prestress losses of the BFRP bars were monitored over the entire period, and tensile tests were conducted at 30, 60, 120, and 240 days. The results show that the prestress losses of the BFRP were less than 40% after 240 days of immersion. Prestress accelerated the degradation of the BFRP performance due to fiber damage and microcracking. The alkalinity of the activator in the SSGM did not have a significant effect on the tensile strengths of the BFRP bars immersed in seawater. However, the higher the alkalinity, the higher was the compressive strength of the SSGM and the lower were the prestress losses of the BFRP, which was attributed to the increased compactness friction caused by shrinkage of the SSGM. Carbonates combined with hydrogen ions in the water to form carbonic acid, and hydroxyl groups combined with the cations in the sea sand and the SSGM to form a strongly alkaline solution; these solutions were harmful to the long-term performance of the BFRP bars. [ABSTRACT FROM AUTHOR]