Ocean Processes Research Articles

Assimilation of Surface Geostrophic Currents in the East Sea Using the Ensemble Kalman Filter

AbstractThe conventional ocean data assimilation process typically involves assimilating hydrographic data, such as temperature and salinity measurements, obtained from both satellites and in-situ observations. This study introduces a novel approach to enhance ocean circulation modeling by assimilating surface geostrophic currents derived from satellite altimetry data using the ensemble Kalman filter. To match the time scales for the variability in the observed surface geostrophic currents and the model currents, the current velocities from the model were low-pass filtered. The optimal cut-off period for the low-pass filter was determined to be 31 days in the East Sea. Eight sensitivity experiments were then conducted to examine the effects of observation error and low-pass filtering during the assimilation of surface geostrophic current data. Assimilation experiments with surface geostrophic current data improved surface currents but had minor negative impacts on the temperature and salinity when compared with assimilation experiments without surface geostrophic current data. Notably, the experiment with an observation error of 10 cm/s for the geostrophic current outperformed the other experiments. Surface geostrophic current assimilation improved the sea surface temperature during winter and effectively modified surface current patterns during autumn in the East Sea. Assimilating satellite-derived surface geostrophic currents in the ocean circulation model thus enhanced the accuracy of surface circulation simulation. This improvement in ocean analysis data offers significant benefits for understanding ocean climate change and for developing marine management strategies.

Constructing a 22-year internal wave dataset for the northern South China Sea: spatiotemporal analysis using MODIS imagery and deep learning

Abstract. Internal waves (IWs) are an important ocean phenomenon facilitating energy transfer between multiscale ocean processes. Understanding such processes necessitates the collection and analysis of extensive observational data. IWs predominantly occur in marginal seas, with the South China Sea (SCS) being one of the most active regions, characterized by frequent and large-amplitude IW activities. In this study, we present a comprehensive IW dataset for the northern SCS (https://doi.org/10.12157/IOCAS.20240409.001, Zhang and Li, 2024), covering the area from 112.40 to 121.32° E and from 18.32 to 23.19° N, spanning the period from 2000 to 2022 with a 250 m spatial resolution. During the 22 years, a total of 15 830 MODIS images were downloaded for further processing. Out of these, 3085 high-resolution MODIS true-color images were identified to contain IW information and were included in the dataset with precise IW positions extracted using advanced deep learning techniques. IWs in the northern SCS are categorized into four regions based on extracted IW spatial distributions. This classification enables detailed analyses of IW characteristics, including their spatial and temporal distributions across the entire northern SCS and its specific sub-regions. Interestingly, our temporal analysis reveals characteristic “double-peak” patterns aligned with the lunar day, highlighting the strong connection between IWs and tidal cycles. Furthermore, our spatial analysis identifies two IW quiescent zones within the IW clusters influenced by underwater topography, highlighting regional variations in IW characteristics and suggesting underlying mechanisms which merit further investigation. There are also three gap regions between distinct IW clusters, which may indicate different IW sources. The constructed dataset holds significant potential for studying IW–environment interactions, developing monitoring and prediction models, validating numerical simulations, and serving as an educational resource to promote awareness and interest in IW research.

Characteristics of R2019 Processing of MODIS Sea Surface Temperature at High Latitudes

Satellite remote sensing is the best way to derive sea surface skin temperature (SSTskin) in the Arctic. However, as surface temperature retrieval algorithms in the infrared (IR) part of the electromagnetic spectrum are designed to compensate for atmospheric effects mainly due to water vapor, MODIS SSTskin retrievals have larger uncertainties at high latitudes where the atmosphere is very dry and cold, which is an extreme in the distribution of global conditions. MODIS R2019 SSTskin fields are currently derived using latitudinally and monthly dependent algorithm coefficients, including an additional band above 60°N to better represent the effects of Arctic atmospheres. However, the R2019 processing of MODIS SSTskin still has some unrevealed error characteristics. This study uses 21 years (2002–2022) of collocated, simultaneous satellite brightness temperature (BT) data from Aqua MODIS and in situ buoy-measured subsurface temperature data from iQuam for validation. Unlike elsewhere over the oceans, the 11 μm and 12 μm BT differences are poorly related to the column water vapor at high latitudes, resulting in poor atmospheric water vapor correction. Anomalous BT difference signals are identified, caused by the temperature and humidity inversions in the lower troposphere, which are especially significant during the summer. Although the existence of negative BT differences is physically reasonable, this makes the retrieval algorithm lose its effectiveness. Moreover, the statistics of the MODIS SSTskin data when compared with the iQuam buoy temperature data show large differences (in terms of mean and standard deviation) for the matchups at the Northern Atlantic and Pacific sides of the Arctic due to the disparity of in situ measurements and distinct surface and vertical atmospheric conditions. Therefore, it is necessary to further improve the retrieval algorithms to obtain more accurate MODIS SSTskin data to study surface ocean processes and climate change in the Arctic.

Combined effects of ocean-land processes on spring precipitation variability in Mongolian Plateau

The Mongolian Plateau hosts one of the world's most fragile ecosystems, characterized by high volatility and frequent natural disasters due to rapid climate change and human activities in recent decades. Frequent dust storms notably mark spring in this region. Through observational analysis and numerical modeling, this study investigates the impacts of comprehensive ocean and land processes—including sea surface temperature (SST) in the North Atlantic and Pacific Oceans, as well as Eurasian land conditions—on the interannual fluctuations of spring precipitation in the Mongolian Plateau (SPMP) from 1979 to 2020. The ocean-land processes involve: a tripole pattern of North Atlantic SST anomalies triggers an eastward-propagating continental-scale wave train; Increased snow cover in Central Asia induces significant anomalous low pressure through the albedo effect; El Niño-Southern Oscillation initiate a teleconnection pattern over the upstream region of the Indian-western Pacific Ocean. These anomalous ocean and land conditions interact with large-scale atmospheric circulations, altering dynamical and hydrological conditions around the Mongolian Plateau, thereby contributing to SPMP variation. Further corroboration from numerical model experiments supports the observational analysis results. The combined effects of multiple ocean-land factors effectively explain precipitation variability across extensive areas of the Mongolian Plateau. A regression model constructed using these land-ocean factors captures the time evolution of the SPMP well.

Reconstruction of Nearshore Surface Gravity Wave Heights From Distributed Acoustic Sensing Data

AbstractDistributed Acoustic Sensing (DAS) is a photonics technology converting seafloor telecommunications and optical fiber cables into dense arrays of strain sensors, allowing to monitor various oceanic physical processes. Yet, several applications are hindered by the limited knowledge of the transfer function between geophysical variables and DAS measurements. This study investigates the quantitative relationship between surface gravity DAS‐recorded wave‐generated strain signals along the seafloor and the pressure at a colocated sensor. A remarkable linear correlation is found over various sea conditions allowing us to reliably determine significant wave heights from DAS data. Utilizing linear wave potential theory, we derive an analytical transfer function linking cable deformation and wave kinematic parameters. This transfer function provides a first quantification of the effects related to surface gravity waves and fiber responses. Our results validate DAS's potential for real‐time reconstruction of the surface gravity wave spectrum over extended coastal areas. It also enables the estimation of waves hydraulic parameters at depth without the need from offshore deployments.

Future directions for deep ocean climate science and evidence-based decision making

IntroductionA defining aspect of the Intergovernmental Panel on Climate Change (IPCC) assessment reports (AR) is a formal uncertainty language framework that emphasizes higher certainty issues across the reports, especially in the executive summaries and short summaries for policymakers. As a result, potentially significant risks involving understudied components of the climate system are shielded from view.MethodsHere we seek to address this in the latest, sixth assessment report (AR6) for one such component—the deep ocean—by summarizing major uncertainties (based on discussions of low confidence issues or gaps) regarding its role in our changing climate system. The goal is to identify key research priorities to improve IPCC confidence levels in deep ocean systems and facilitate the dissemination of IPCC results regarding potentially high impact deep ocean processes to decision-makers. This will accelerate improvement of global climate projections and aid in informing efforts to mitigate climate change impacts. An analysis of 3,000 pages across the six selected AR6 reports revealed 219 major science gaps related to the deep ocean. These were categorized by climate stressor and nature of impacts.ResultsHalf of these are biological science gaps, primarily surrounding our understanding of changes in ocean ecosystems, fisheries, and primary productivity. The remaining science gaps are related to uncertainties in the physical (32%) and biogeochemical (15%) ocean states and processes. Model deficiencies are the leading cited cause of low certainty in the physical ocean and ice states, whereas causes of biological uncertainties are most often attributed to limited studies and observations or conflicting results.DiscussionKey areas for coordinated effort within the deep ocean observing and modeling community have emerged, which will improve confidence in the deep ocean state and its ongoing changes for the next assessment report. This list of key “known unknowns” includes meridional overturning circulation, ocean deoxygenation and acidification, primary production, food supply and the ocean carbon cycle, climate change impacts on ocean ecosystems and fisheries, and ocean-based climate interventions. From these findings, we offer recommendations for AR7 to avoid omitting low confidence-high risk changes in the climate system.

HALOBATES: An autonomous surface vehicle for high-resolution mapping of the sea-surface microlayer and near-surface layer on essential climate variables

Abstract Essential climate variables (ECVs) are physical, chemical, or biological parameters supporting the characterization of the climate system. The oceanic ECVs temperature and salinity have been defined for the sea surface (upper 1 mm) and bulk water (upper 2 meters). Direct observation and sampling of the sea surface from ships and buoys is limited due to the potential loss of integrity of the sea surface and contamination by the research platform. The design, development, and operation of a research vehicle with autonomous capabilities based on commercially available components are described in this study. The autonomous operation and fully automated sampling enable high-resolution mapping of the sea surface microlayer (SML), i.e., the upper < 1mm layer, and near-surface layer (< 1.2 m). Sampling the SML is based on a rotating glass disk sampler. The autonomous surface vehicle HALOBATES has been equipped with multiple conductivity, temperature, and depth sensors (CTDs) in a flow-through system to measure both sea surface and bulk temperature and salinity. The performance of the autopilot under various scenarios is demonstrated. Typical anomalies of ECVs within the SML and near-surface layer are evident and forced by both atmospheric and oceanic processes. Data analyses reveal HALOBATES' ability to resolve thermohaline structure on different spatial and temporal scales, for example, small-scale freshwater lenses and thermohaline changes across oceanic fronts. The integration of an Acoustic Doppler Current Profiler supports the interpretation of thermohaline structures. HALOBATES is a platform with cutting-edge technology for understanding climate-related processes between the ocean and atmosphere and providing high-resolution sea surface data for validating satellite products of ECVs.

A drop in Antarctic sea ice extent at the end of the 1970s

After a period of relative stability, the Antarctic sea ice extent has abruptly decreased in 2016 and has remained low since then. Both atmospheric and oceanic processes likely contributed to this drop but many questions remain regarding the underlying dynamics and it is unknown if this drop is unprecedented. Here we produce a new multi-variate spatial reconstruction covering 1958–2023 and show that a similar drop in sea ice extent occurred at the end of the 1970s, albeit with a smaller magnitude. Both drops show similar spatial patterns, with a higher sea ice loss in the East Antarctic sector than in the West Antarctic sector where the variability is strongly modulated by wind-driven changes. The ocean integrates the atmospheric forcing and provides memory that amplifies the magnitude of both drops.

Time-series forecasting of particulate organic carbon on the Sunda Shelf: Comparative performance of the SARIMA and SARIMAX models

Conducting in-depth studies of carbon dynamics in the Southeast Asia’s Sunda Shelf waters is challenging. Particulate organic carbon (POC) is a key component that can be monitored in the region, but ocean assessment requires advanced research and POC monitoring, especially in relation to ocean dynamics and forecasts. Accurate forecasting of POC in marine environments is difficult due to the complexity of oceanic processes and the influence of various environmental factors. Statistical forecasting models such as Seasonal Autoregressive Integrated Moving Average (SARIMA) or SARIMA with Exogenous Factors (SARIMAX) are useful for this purpose. This study compares these two time-series forecasting models to assess the role of exogenous factors in predicting POC variability in Indonesian seas. The models were specified as SARIMA (3, 1, 3)x(2, 0, 0, 60) and SARIMAX (3, 1, 3)x(2, 0, 0, 60). We obtained Akaike Information Criterion (AIC) values of 1237.767 for the SARIMA model and 1207.341 for SARIMAX[exog=SST]. The SARIMA model's validation metrics were 6.94 % for MAPE, 10.80 for RMSE, and 0.65 for the correlation coefficient, outperforming the SARIMAX model. While SARIMAX incorporates additional environmental variables, SARIMA outperforms it based on MAPE, RMSE, and correlation coefficients. Our findings reveal that only sea surface temperature can significantly influence POC forecasts, thus providing a new perspective on oceanic carbon dynamics. From 2022–2030, POC levels are expected to range between 108.3 and 135.9 mg/m³, with a mean value of 120.9±5.4 mg/m³, lower than that observed from 2002 to 2022, which was 118.8±11.9 mg/m³. The highest peak in POC is predicted for the end of 2026 and 2027. The annual trend shows that the highest POC values correspond to the northwest monsoon season, with the lowest during the intermonsoon period.

A “natural sand plant” at the shelf edge in the low-energy Gulf of Lions, western Mediterranean Sea

Thick sand deposits at the edge of continental shelves, sometimes covered with large bedforms, are generally considered as relict features inherited from periods of low sea level, but alternative interpretations are possible, even in zones where modern oceanic processes are moderate. Detailed investigations in the western Gulf of Lions (western Mediterranean Sea) reveal the presence of remains of Marine Isotope Stage 4 (MIS 4) and MIS 2 shelf-edge deltas at the head of canyons. The sands were then “cannibalized” by strong rising sea-level currents, forming a 20-km-long, strike-oriented sand body covered by dunes. Presently, the migration of dunes is maintained by strong storm-driven currents. The seasonal reversal of circulation is at the origin of inversion of dune morphology, thus the sand body mimics a tidal sand bank with clockwise circulation of bedforms. In the long term, dunes migrate southward with a negative angle of climb, eroding into the underlying shelf-edge deltas. Acoustic Doppler current profiles and numerical simulations indicate that the sediment is sorted, once in suspension, and is flushed to the deep sea while sand bedload contributes to bedform migration. This relative enrichment of sand without external supply is referred to as a “natural sand plant,” by analogy with industrial sand plants where sand is washed and sieved. It forms a discontinuous sand belt, 5−20 m thick, more than 110 km along-strike, connecting multiple shelf-edge deltas. The geological importance of recognizing this recycling mechanism is indicated by the preservation of similarly large buried dunes formed during the deglaciation leading to interglacial MIS 7 at ca. 240 ka (Termination III).

Gendering Ocean Management for Sustainable Ocean Care in Ghana

UNESCO presently offers a universal regime and policy environment for the identification and management of natural and cultural heritages. However, heritage does not merely signify cultural diversity; it can also facilitate greater equity and equality. The research problem addressed in this article is that in Ghana, the national government perceives and treats the small-scale fishing (SSF) sector as a masculine space and endeavour, ignoring the gendered aspects of this environment, of SSF practice and ocean care. In the article, it is hypothesized that if the SSF sector is treated as a socially differentiated space, and if the concern of ocean care is prioritized as a key imperative in Ghanaian ocean management, it is likely that a more inclusive and sustainable ocean management process and SSF sector will emerge in Ghana. Mindful of the socially differentiated nature of the SSF sector in Ghana, the goal of the research presented in this article is to use mixed qualitative research methods (participant-observation and semi-structured interviews) to investigate gendered knowledge forms and gendered practices in ocean care in the central region of Ghana. A key finding of the research is that gendered ritual practices, including canoe building and use in Ghana, are critical to long-term, sustainable, and inclusive ocean management in the country. Recognition of the gendered dimensions of ocean management in Ghana may also result in more inclusive ocean governance policies and nature management policies in Ghana in general. The conclusion of the article is that ocean governance in Ghana should consider and mainstream a gendered perspective of the SSF sector, to advance transformative, sustainable, and inclusive ocean care. The article draws on theories of intersectionality, African indigenous feminist thought, and critical heritage studies to analyse the data gathered, to support the discussion, and to propose the way forward for the national government.

Delivering scientific evidence for global policy and management to ensure ocean sustainability

AbstractLife depends on the ocean, with societal health, cultural systems and national economies reliant on ocean processes and resources. As ocean resources are used, and humans continue to drive climate change, the benefits from the ocean to society are being diminished. Science must meet the needs of policy and deliver to decision makers the information and tools for identifying pathways that support continued delivery of the benefits society derives from the ocean, whilst minimising impacts. This is crucial if the world’s nations are to meet the goals and targets they have set under international agreements. Here, we outline how a global assessment that focuses specifically on the ocean, the World Ocean Assessment, is linking science to the governments of the world and their policies within an internationally mandated framework. In doing so, we identify key elements that are needed for facilitating engagement by decision makers and uptake of knowledge, and the pathways taken by the assessment in implementing them. We also provide insights into the evolution that the World Ocean Assessment has undertaken over its first three cycles to progress its goal of enhancing the scientific basis of policymaking. We identify the challenges in delivering science to policy at a global scale and the work that still needs to be done in filling gaps to achieve a coordinated, comprehensive mechanism for connecting science with policy and ensuring future sustainability of the ocean.

Chaos analysis and traveling wave solutions for fractional (3+1)-dimensional Wazwaz Kaur Boussinesq equation with beta derivative

Wazwaz Kaur Boussinesq (WKB) equation can effectively simulate the behavior of water waves in shallow water, including the nonlinear effect and dispersion phenomenon of waves, which is of great significance for understanding the dynamic process of ocean, river and other water bodies. To enrich the wave equation theory, the (3+1)-dimensional integer order derivative of WKB equation is changed to the fractional one with beta derivative. The current work deals with the fractional (3+1)-dimensional WKB equation for discussing its chaotic behavior and establishing some new analytic solutions. The chaotic properties of the equation are verified by the trend of evolution along with time, Lyapunov exponents and initial sensitivity analysis. And then complete discrimination system for polynomial method is applied to derive some trigonometric, hyperbolic, Jacobi elliptic and other solutions. The graphical demonstrations are provided for part of these solutions. From these visualized graphs, the solitary, periodic and quasi-periodic wave are shown and the effect of fractional derivatives on the equation can be seen intuitively.

Signature of the western boundary currents in local climate variability.

The western boundary currents are characterized by narrow, intense ocean jets and are among the most energetic phenomena in the world ocean. The importance of the western boundary currents to the mean climate is well established: they transport vast quantities of heat from the subtropics to the midlatitudes1, and they govern the structure of the climatological mean surface winds2-6, precipitation4-6 and extratropical storm tracks7-13. Their importance to climate variability is much less clear, as the tropospheric response to extratropical sea surface temperature (SST) variability is generally modest relative to the internal variability in the midlatitude atmosphere12-14. Here we exploit novel local analyses based on high-spatial-resolution data to demonstrate that SST variability in the western boundary currents has a more robust signature in climate variability than has been indicated in previous work. Our results indicate that warm SST anomalies in the major boundary currents of both hemispheres are associated with a distinct signature of locally enhanced precipitation and rising motion anomalies that extend throughout the depth of the troposphere. The tropospheric signature closely mirrors that of ocean dynamical processes in the boundary currents. Thus, the findings indicate a distinct and robust pathway through which extratropical ocean dynamical processes influence local climate variability. The observational relationships are also reproducible in Earth system model simulations but only when the simulations are run at high spatial resolution.

Genomic and biogeographic characterisation of the novel prasinovirus Mantoniella tinhauana virus 1.

Mamiellophyceae are a ubiquitous class of unicellular green algae in the global ocean. Their ecological importance is highlighted in studies focused on the prominent genera Micromonas, Ostreococcus, and Bathycoccus. Mamiellophyceae are susceptible to prasinoviruses, double-stranded DNA viruses belonging to the nucleocytoplasmic large DNA virus group. Our study represents the first isolation of a prasinovirus in the South China Sea and the only one to infect the globally distributed genus Mantoniella. We conducted a comparative analysis with previously identified viral relatives, encompassing morphological characteristics, host specificity, marker-based phylogenetic placement, and whole-genome sequence comparisons. Although it shares morphological and genetic similarities with established prasinoviruses, this novel virus showed distinct genetic traits, confining its infection to the species Mantoniella tinhauana. We also explored the global biogeography of this prasinovirus and its host by mapping metagenomic data and analysing their relationship with various environmental parameters. Our results demonstrate a pronounced link between the virus and its host, both found predominantly in higher latitudes in the surface ocean. By gaining an increased understanding of the relationships between viruses, hosts, and environments, researchers can better make predictions and potentially implement measures to mitigate the consequences of climate change on oceanic processes.

The Characteristics of Different Apparent Optical Property Parameters in Non‐Destructively Estimating Absorptive Substances Within Sea Ice: A Case Study in Liaodong Bay

AbstractAbsorptive substances (AS) embedded in sea ice can alter irradiance transmission, exerting a significant influence on oceanic biogeochemical processes. Their quantification is thus essential, and a regression model based on the normalized difference index of transmittance (T(λ)) has been widely used for retrieving ice algal biomass. However, the potentials of albedo (α(λ)) and the diffuse attenuation coefficient (Kd(λ)) in AS estimation have not been explored. To fill this gap, sea ice optical properties observed in Liaodong Bay in 2009, 2010, 2013, and 2022 were used to investigate the characteristics of α(λ), T(λ), and Kd(λ) in non‐destructively estimating As through sensitivity analyses based on the Hydrolight radiative transfer model. The effects derived from AS vertical distribution, scattering coefficient and ice thickness were studied specifically. Ultimately, a significant relationship between α(λ) and the total absorption coefficient of AS was derived (R2 = 0.79) for Liaodong Bay sea ice. Sensitivity analyses revealed that it could only retrieve AS in the upper 15–20 cm, which was influenced by variations in ice thickness and scattering coefficient. In contrast, T(λ) could retrieve AS throughout the ice column and is less affected by scattering variation; but it is significantly affected by the vertical distribution of AS in the upper layer. Kd(λ) has the best potential in AS estimation, but for sea ice thinner than 30 cm, the effect of variation in ice thickness could not be neglected, similar to T(λ). Knowledge of this is helpful for the future development of AS estimation.

Re-thinking human interactions with the oceans.

Earth's marine ecosystems are changing rapidly, in large part owing to the damaging effects of human activities. Unless humans find better ways of interacting with the seas and oceans, the marine resources upon which we rely will diminish as more ecosystems collapse. The consequences for human health and wellbeing will be severe. The meta-discipline of Oceans and Human Health has catalogued how the oceans and their constituents benefit human lives. Examples include access to seafood, pharmaceuticals and physical and mental health benefits. This interdisciplinary research effort has also revealed how the integrated impact of anthropogenic activities has disrupted ocean processes resulting in extensive losses of marine biodiversity, increasing chemical and microbial pollution, proliferation of harmful algal blooms and increased coastal inundation, all of which threaten human populations. In response, non-governmental organizations and national governments have established various agreements and treaties to prevent further damage, restore what has been lost and grasp new economic opportunities. Nevertheless, ocean-related risks continue to escalate rapidly in the absence of political commitment. New thinking regarding the interconnectedness of all human/ocean interactions is required to remove the barriers and impediments that hamper tackling the wicked problem of fostering health and wellbeing while achieving ocean sustainability.

The role of air–sea heat flux for marine heatwaves in the Mediterranean Sea

Abstract. Recent studies have significantly contributed to understanding physical mechanisms associated with the occurrence of marine heatwaves (MHWs). Building upon prior research, this study investigates the relative role of air–sea heat exchange and oceanic processes during the onset and decline phases of surface MHWs in the Mediterranean Sea based on a joint analysis of remote sensing data and reanalysis outputs over the period 1993–2022. Results show that air–sea heat flux is the major driver in 44 % of the onset and only 17 % of the declining MHW phases. Thus, these findings suggest that oceanic processes play a key role in driving sea surface temperature (SST) anomalies during MHWs, particularly during declines. The role of surface flux becomes more important during warmer months and onset periods. Spatially, the heat flux contribution is greater in the Adriatic and Aegean sub-basins, where it becomes the major driver of most onset phases. Latent heat emerges as the most significant heat flux component in forming the SST evolution across all seasons. Onset and decline phases lasting less than 5 d experience a weaker contribution of heat flux compared to longer phases (lasting 5–10 or more than 10 d). Moreover, an inverse relationship between MHW severity and the contribution of heat flux is observed. At the subsurface, mixed layer shoaling is found over the entire duration of most MHWs, particularly for those of shorter duration. Therefore, the surface cooling right after the peak day is likely not associated with vertical mixing in such cases. These findings suggest that other oceanic processes, potentially horizontal advection, have a key role in modulating SST at the beginning of most MHW declines. In turn, further dissipation of heat is commonly driven by vertical mixing, as indicated by a significant mixed layer deepening after the MHW end day in most cases. This study emphasizes the need to consider subsurface information for future studies of MHWs and highlights the importance of accounting for limitations associated with the definitions employed for MHW phases.

Quantification of ocean microplastic fragmentation processes in the Sea of Japan using a combination of field observations and numerical particle tracking model experiments

This study estimated the fragmentation rate of microplastics (MiPs) in the Sea of Japan by analyzing MiP size over time following their generation from macroplastics (MaPs). A 5-year particle-tracking model was used to simulate the MaP and MiP motions driven by ocean currents, Stokes drift, the windage of MaPs, beaching, re-drifting, the conversion process from MaPs to MiPs, and the removal of MiPs from the upper ocean. MiP sizes decreased downstream in the Tsushima Current flowing northeastward. The highest correlation between MiP size and elapsed time occurred in the simulation where MiP fragmentation also occurred in the ocean, at 20 % of the rate on beaches. The apparent fragmentation rate in nature was estimated to approximately 1.0 mm/100 days. This study demonstrated that incorporating spatiotemporal information from the simulation into observed size results could further our understanding of fragmentation of MiPs degraded in marine environments.

A climate change signal in the tropical Pacific emerges from decadal variability.

The eastern tropical Pacific has defied the global warming trend. There has been a debate about whether this observed trend is forced or natural (i.e., the Interdecadal Pacific Oscillation; IPO) and this study shows that there are two patterns, one that oscillates along with the IPO, and one that is emerging since the mid-1950s, herein called the Pacific Climate Change (PCC) pattern. Here we show these have distinctive and distinguishable atmosphere-ocean signatures. While the IPO features a meridionally broad wedge-shaped SST pattern, the PCC pattern is marked by a narrow equatorial cooling band. These different SST patterns are related to distinct wind-driven ocean dynamical processes. We further show that the recent trends during the satellite era are a combination of IPO and PCC. Our findings set a path to distinguish climate change signals from internal variability through the underlying dynamics of each.