Posts Tagged 'regionalmodeling'

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Wind control of the interannual ocean‐biogeochemical variability in the South Atlantic Bight

Published 23 February 2026 Science Closed
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Abstract

In the South Atlantic Bight (SAB), changes in the Gulf Stream (GS), particularly its strength and proximity to the coast, are thought to be primary factors determining the shelf-break upwelling rate. However, it is still not entirely clear if and to what extent those factors influence cross-shelf nutrient fluxes and shape the ocean biogeochemistry at interannual and longer timescales. Here, we use a high-resolution regional ocean-biogeochemical model and an ocean reanalysis product (1993–2022), along with a satellite-derived chlorophyll data set (1997–2022), to investigate the interannual ocean-biogeochemical variability in the SAB. Regional model outputs suggest that year-to-year changes in phytoplankton production are indeed largely driven by upwelling of cold and nutrient-rich water to the shelf-break. The upwelling variability, reflected in bottom temperature and vertically integrated production patterns, is strongly linked to surface velocity changes in the GS near the shelf break, but weakly related to the depth-integrated GS transport. The GS’s velocity changes, and the temperature and production anomalies, are well correlated to the alongshore wind stress, suggesting that local wind is the leading driver of the shelf-break upwelling variability at interannual timescales. Those relationships are also supported by circulation patterns from ocean reanalysis and satellite chlorophyll anomalies. Finally, examining the simulated shelf-slope interchanges in the carbonate system, we find that shelf-break upwelling significantly increases bottom acidification, a pattern linked to the low carbonate concentration in the slope waters. This study thus provides new insight for understanding and predicting GS and winds impacts on biogeochemical patterns from the SAB.

Plain Language Summary

The ocean current known as the Gulf Stream (GS) can induce upwelling of subsurface cold and nutrient-rich waters into the coastal margin of the South Atlantic Bight, influencing coastal temperature and phytoplankton growth. Previous studies suggested that the GS strength and its proximity to the coast are key factors determining the intensity of upwelling events. However, the degree to which these factors impact the year-to-year changes in phytoplankton production and other ocean properties remains unclear. Here we use numerical models of ocean currents and seawater biogeochemistry, as well as chlorophyll records derived from satellite measurements, to investigate that impact. The patterns showed that interannual changes in coastal temperature, phytoplankton production, water acidity, and dissolved oxygen are strongly modulated by upwelling changes in the outer edge of the continental margin (about 70 m depth in this region). This interannual upwelling variability is tightly coupled to variations in the surface alongshore GS velocity close to that outer edge, which is modulated by alongshore wind variability. Our study characterizes GS patterns associated with high and low productivity years, and highlights the role of surface wind as ultimate driver of the interannual upwelling variability in the South Atlantic Bight.

Key Points

  • A regional ocean model is used to investigate interannual variability of ocean-biogeochemistry in the South Atlantic Bight
  • Year-to-year changes in primary production, chlorophyll, and carbonate system patterns respond to shelf-break upwelling anomalies
  • Shelf-break upwelling is closely linked to the Gulf Stream velocity near the shelf break, modulated by alongshore wind variability
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Ocean acidification in Canada: the current state of knowledge and pathways for action

Published 23 February 2026 Science Closed
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Ocean acidification (OA) generally receives far less consideration than other climate stressors and related hazards, such as global warming and extreme weather events. Canada is uniquely vulnerable to OA given its extensive coastal oceans, the oceanographic processes in its three basins, accelerated warming and sea-ice melt, and extensive coastal communities and maritime economic sectors. Canada’s coastline is also home to extensive and diverse First Nations peoples with distinct histories, rights, title, laws, governance and whose traditions and cultures are extrinsically linked to the sea. However, there are currently very limited pathways to support OA action, mitigation, and/or adaptation in Canada, particularly at the policy level. Here, we present a first synthesis of the current state of OA knowledge across Canada’s Pacific, Arctic, and Atlantic regions, including monitoring, modelling, biological responses, socioeconomic and policy perspectives, and examples of existing OA actions and efforts at local and provincial levels. We also suggest a step-wise pathway for actions to enhance the coordinated filling of OA knowledge gaps and integration of OA knowledge into decision-making frameworks. The goals of these recommendations are to improve our ability to respond to OA in Canada, and minimize risks to coastal marine environments and ecosystems, vulnerable sectors, and communities.

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Nonlinear interactions of timing and amplitude biases in modeled Southern Ocean pCO2: the roles of dissolved inorganic carbon, total alkalinity, and sea surface temperature

Published 21 January 2026 Science Closed
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The Southern Ocean is a major sink for atmospheric carbon dioxide and critical to the current and future carbon cycle. This net annual CO2 flux reflects the balance between strong seasonal variability characterized by opposing periods of winter outgassing and summer uptake. Using a simple framework, we evaluate how model biases in both the amplitude and timing of dissolved inorganic carbon (DIC) and total alkalinity (TA) and in the amplitude of sea surface temperature (SST) impact simulated pCO2. We examine seasonal CO2 fluxes and pCO2 south of the Subantarctic Front in 42 Earth System Model and three state estimate simulations. Only 11 of the 45 simulations have a seasonal pCO2 cycle with a correlation of ≥0.7 to observed pCO2, while 26 have a correlation of <0. Four of the well-correlated models accurately represent the seasonality of SST, DIC, and TA, while TA biases compensate for DIC or SST biases in the other seven. DIC and SST amplitude biases are related to mixed layer (MLD) biases, with shallow MLDs, especially in the summer, correlated with larger amplitude DIC and SST cycles than observed. The amplitude of seasonal Net Primary Production is correlated to DIC and TA timing. We provide input on the main adjustments needed to correct the simulated pCO2 seasonality in each of the evaluated models. These findings highlight the difficulty and importance of capturing the seasonal processes influencing the carbonate system to correctly model and predict the Southern Ocean carbon sink and its response to a changing climate.

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Explainable machine learning models for coastal pH forecasting at aquaculture-relevant thresholds in Eastern Canada

Published 19 January 2026 Science Closed
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Highlights

  • Benchmark of ML models for coastal pHSWS forecasting.
  • Models trained on rare high-frequency data from Eastern Canada.
  • XGBoost balances sensitivity and precision at pHSWS < 7.75
  • SHAP shows Julian day dominance as composite environmental driver.
  • Promising low-cost framework for aquaculture acidification early warning.

Abstract

Ocean acidification poses a growing threat to marine ecosystems and aquaculture productivity, particularly in under-monitored coastal regions such as Eastern Canada. Existing pH prediction frameworks typically rely on multi-year records combining extensive carbonate chemistry, physical, and biological parameters. While these models can achieve high accuracy, their data requirements make them costly, complex, and challenging to implement for local, site-specific acidification forecasting in aquaculture contexts. To address this limitation, this study benchmarks several machine learning models for coastal pHSWS prediction using only three routinely measured environmental variables (temperature, salinity, sea level), from which we derived moving-average descriptors, local gradients, and two temporal indicators, resulting in a compact set of 11 input features. Six different models and a multivariate linear regression baseline were trained on one of the most complete and extended high-frequency datasets available (BSSS2018) and evaluated across four independent datasets: one from the same site but six months earlier (BSSS2017), and three from nearby bays in northeastern New Brunswick collected between 2017 and 2019. Among all tested models, XGBoost emerged as the most reliable and interpretable, achieving the best trade-off between sensitivity and precision at the operational acidification threshold (pHSWS < 7.75). Its performance remained acceptable within-site but declined across bays due to environmental and seasonal discrepancies, underscoring the importance of training data representativeness. SHAP-based explainability confirmed that Julian day was the dominant predictor, integrating the composite effects of seasonal environmental variability. Overall, this study demonstrates that using only low-cost, routinely measured features provides a promising foundation for short-term coastal pH forecasting, particularly for aquaculture monitoring needs. Despite limited inter-bay generalization, the proposed framework shows that interpretable machine learning models can deliver actionable early-warning insights under realistic data constraints. It constitutes one of the first data-driven benchmarks explicitly tested at aquaculture-relevant thresholds, highlighting a scalable and transparent approach toward operational acidification forecasting.

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Ocean acidification in Massachusetts bay and Boston harbor: insights from a 1-D modeling approach

Published 8 January 2026 Science Closed
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Highlights

  • NeBEM, an ERSEM-based biogeochemical and ecosystem model, is established for the U.S. Northeast.
  • NeBEM provides process-based insights into carbonate system variability beyond the capability of empirical data-fitting methods.
  • Biological processes strongly influence TA and DIC variability in outer Massachusetts Bay.

Abstract

Massachusetts Bay (MB)/Boston Harbor (BH) in the northeastern United States has reduced buffering capability, making it highly vulnerable to ocean acidification (OA). We applied the U.S. Northeast Biogeochemistry and Ecosystem Model (NeBEM), integrating the unstructured grid, Finite Volume Community Ocean Model with a modified European Regional Seas Ecosystem Model (ERSEM), to investigate seasonal and interannual OA variability through one-dimensional (1-D) experiments. Objectives were to (a) evaluate model skill in reproducing observed seasonal cycles of OA-related variables, particularly pCO2 and pH, in shallow and deep regions, and (b) assess sensitivity to parameterizations and algorithms for calculating dissolved inorganic carbon (DIC), total alkalinity (TA), pCO2, and pH. The 1-D NeBEM reproduced variability of nutrients, dissolved oxygen, chlorophyll-a, pCO2, and pH at the deep outer bay site, where air-sea interactions dominate, but failed at the shallow inner bay site due to the absence of river discharge-driven advection. Of TA algorithms tested, the semi-diagnostic method best captured observed seasonal pCO2 variation, achieving the highest correlation and lowest root mean square error, although all methods performed similarly for pH. Comparisons with multi-linear regression methods showed that empirical models are highly sensitive to calibration set. Mechanistic analysis indicated that TA variability is mainly regulated by nitrification and net community production (NCP), while DIC variability is driven primarily by NCP. Atmospheric CO₂ loading was the first-order contributor to DIC change in magnitude. However, it has decreased in MB over the past two decades, in contrast to regional and global trends. Therefore, it is not a major driver of OA progression in this system.

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Water property variability into a semi-enclosed sea dominated by dynamics, modulated by properties

Published 15 December 2025 Science Closed
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The biogeochemistry of the Salish Sea is strongly connected to its Pacific Ocean inflow through Juan de Fuca Strait (JdF), which varies seasonally and interannually in both volume and property flux. Long-term trends in warming, acidification, and deoxygenation are a concern in the region, and inflow variability influences the flux of tracers potentially contributing to these threats in the Salish Sea. Using ten years (2014–2023, inclusive) of Lagrangian particle tracking from JdF, we quantified the contributions of distinct Pacific source waters to interannual variability in JdF inflow and its biogeochemical properties. We decompose variability in salinity, temperature, dissolved oxygen, nitrate, and carbonate system tracers into components arising from changes in water source transport (dynamical variability) and changes in source properties (property variability). Observations in the region provide insight into source water processes not resolvable in the Lagrangian simulations, including denitrification and trace metal supply. Deep source waters dominate total inflow volume and drive variability in nitrate flux through changes in transport. Shallow source waters, particularly south shelf water, exhibit greater interannual variability and disproportionately affect temperature, oxygen, and [TA–DIC], driving change through both dynamical and property variability. This study highlights the combined roles of circulation and source water properties in shaping biogeochemical variability in a semi-enclosed sea, and how these roles differ between biogeochemical tracers. It provides a framework for attributing flux changes to specific source waters and physical and biogeochemical drivers, with implications for forecasting coastal ocean change under future climate scenarios.

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Compound marine heatwaves and acidity extremes in the Southern Ocean

Published 21 November 2025 Science Closed
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Abstract

Compound extremes of temperature and acidity that extend over substantial fractions of the water column can be particularly damaging to marine organisms, as they experience not only additional stress by the potentially synergistic effects of these two stressors, but also a reduction in habitable vertical space. Here, we detect and analyze such column-compound extremes (CCX) in the Southern Ocean between 1980 and 2019, and characterize their duration, intensity, and spatial extent. To this end, we use daily output from a hindcast simulation of the Regional Ocean Modeling System (ROMS), coupled with the Biological Elemental Cycling (BEC) model. We first detect extremes in temperature and acidity ([]) within the top 300 m using a relative threshold of 95% and then identify CCX where conditions are extreme for both stressors for at least 50 m of the water column. When analyzed on a fixed baseline, positive trends in ocean warming and acidification caused CCX to last longer, intensify, and expand throughout the Southern Ocean. In the Antarctic zone, CCX expanded between 1980 and 2019 more than ten times in volume, lasted up to 120 days longer, and doubled in anomaly. Some of the largest and longest events occurred in Antarctic Marine Protected Areas (MPAs), covering more than 200,000 km2 and persisting for over 500 days. CCX in the Subantarctic and Northern zones quadrupled in volume and increased by more than 30% in anomaly. Across the Southern Ocean, the increasing occurrence of CCX exacerbates the risks to marine ecosystems from warming and acidification.

Plain Language Summary

Extreme heat events in the ocean, known as Marine HeatWaves (MHW), are becoming more common due to climate change. These events can be even more harmful when they occur at the same time as Ocean Acidity eXtreme (OAX) events, synergistically causing stress for marine life. In this study, we looked at how often these combined events in the upper ocean, called Column-Compound eXtremes (CCX), occurred in the Southern Ocean between 1980 and 2019. We used a numerical model simulation to investigate changes in CCX during the study period. Compared to conditions in 1980, we find that CCX in the Antarctic zone have expanded more than 10 times in volume and lasted up to 120 days longer. In addition, expansive and intense CCX are found in Antarctic Marine Protected Areas (MPAs), posing a threat to vulnerable ecosystems. These events covered more than 200,000 km2 and lasted more than 500 days. The increasing occurrence of CCX across the Southern Ocean exacerbates the risks to marine ecosystems arising from ocean warming and acidification.

Key Points

  • In the Antarctic zone, Column-Compound eXtremes (CCX) occupied in 2019 relative to 1980 ten times more volume and doubled in anomaly
  • Marine Protected Areas in the Ross Sea and Antarctic Peninsula are disproportionately affected by the largest, longest, most intense CCX
  • More than 70% of surface marine heatwaves contain CCX in 2019, although up to 60% of CCX occur without any surface expression
Continue reading ‘Compound marine heatwaves and acidity extremes in the Southern Ocean’

A century of change in the California Current: upwelling system amplifies acidification

Published 19 November 2025 Science Closed
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Predicting the pace of acidification in the California Current System (CCS), a productive upwelling system that borders the west coast of North America, is complex because the anthropogenic contribution is intertwined with other natural sources. A central question is whether acidification in the CCS will follow the pace of increasing atmospheric CO2, or if climate effects and other biogeochemical processes will either amplify or attenuate acidification. Here, we apply the boron isotope pH proxy to cold-water orange cup corals to establish a historic level of acidification in the CCS and the Salish Sea, an associated marginal sea. Through a combination of complementary modeling and geochemical approaches, we show that the CCS and Salish Sea have experienced amplified acidification over the industrial era, driven by the interaction between anthropogenic CO2 and a thermodynamic buffering effect. From this foundation, we project future acidification in the CCS under elevated CO2 emissions. The projected change in pCO2 over the 21st century will continue to outpace atmospheric CO2, posing challenges to marine ecosystems of biological, cultural, and economic importance.

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Climate refugia could disappear from Australia’s marine protected areas by 2040

Published 3 November 2025 Science Closed
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Abstract

Climate change manifests in the ocean as chronic stressors, including warming, acidification and deoxygenation, and as acute stressors such as marine heatwaves. While marine protected areas (MPAs) are often designed to mitigate local stressors such as fishing and mining, their design seldom considers climate change. Using the Australian marine estate as a case study, we use projections from 11 CMIP6 Earth System Models to assess the climate exposure of Australian waters, and implications for the MPA network. We find that, under scenarios that exceed 1.8°C of global surface warming this century, ocean climate is projected to surpass recent variability (1995–2014) from mid-century. This results in the disappearance of climate analogs—where future ocean conditions remain within recent variability—and of climate refugia—regions with slowest rates of environmental change, most likely to retain biodiversity—by 2040. Australian MPAs and unprotected areas exhibit similar patterns of exposure to warming, acidification, deoxygenation, and marine heatwaves, suggesting that MPA placement with respect to future climate is no better than random. Despite potential re-emergence of climate refugia after 2060 under lower-emissions scenarios, continued emissions under current Nationally Determined Contributions (SSP2–4.5) risk ecosystem collapse from chronic and acute thermal stress across protected and unprotected waters. While cutting emissions can partially cap or delay climate impacts, even under lower-emissions scenarios, effective conservation requires adaptive strategies that protect biodiversity in place and on the move.

Plain Language Summary

Marine protected areas (MPAs) are designed to safeguard ocean biodiversity from threats like fishing, but their design rarely considers climate change impacts. We assessed the future exposure of Australia’s MPAs to climate change using projections of ocean climate. Our findings reveal that if global surface warming exceeds 1.8°C this century, Australian marine ecosystems will face entirely novel ocean conditions beyond recent historical variability (1995–2014) by mid-century. This results in the Australia-wide disappearance of regions with slowest rates of climate change—climate refugia—representing a substantial threat to marine biodiversity. Our results suggest that MPAs are no better off than unprotected areas, facing the same risks from warming, acidification, deoxygenation, and marine heatwaves as unprotected waters. We found that reducing emissions could facilitate the reappearance of some climate refugia after 2060, but continuing along current emissions trends risks ecosystem collapse from warming throughout Australia’s protected and unprotected waters. Effective marine conservation requires both emissions reductions and adaptive strategies to protect biodiversity as species respond to a changing ocean climate.

Key Points

  • Ocean climate in Australia will reach a climate horizon by mid-century, representing novel conditions beyond recent variability (1995–2014)
  • Under global warming scenarios exceeding 1.8°C this century, climate refugia are projected to disappear from Australian waters by 2040
  • Existing MPAs and unprotected areas exhibit equivalent patterns of exposure to multiple ocean climate metrics, suggesting a lack of climate-smart design
Continue reading ‘Climate refugia could disappear from Australia’s marine protected areas by 2040′

Unprecedented carbon accumulation in the Indian Ocean during 2016–2017

Published 29 October 2025 Science Closed
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Abstract

During 2016–2017, the Indian Ocean experienced a pronounced increase in dissolved inorganic carbon (∼0.39 PgC/yr), approximately four times greater than the annual mean air–sea CO2 flux. Using a reconstructed data product and a state-of-the-art ocean biogeochemical model, we attribute this anomaly to an enhanced Southern Ocean inflow and a weakened Indonesian Throughflow associated with an El Niño event accompanied by a positive Indian Ocean Dipole (IOD), and followed by a negative IOD during the El Niño-to-La Niña transition. The resulting carbon accumulation leads to a decline in aragonite saturation and a shoaling of the aragonite saturation horizon in the southeastern Indian Ocean. This subsurface acidification may pose risks to deep-water calcifying organisms. Our findings demonstrate that ocean carbon storage and acidification are strongly modulated by circulation-driven transport processes, highlighting the need for improved subsurface observations and model capabilities to better capture the interior carbon response to climate variability.

Plain Language Summary

Between 2016 and 2017, the Indian Ocean stored a much larger amount of carbon than usual—about four times more than the typical annual exchange of carbon between the ocean and atmosphere. Using reconstructed observations and an advanced ocean model, we show that this unusual carbon buildup was caused by stronger inflow from the Southern Ocean and a weaker Indonesian Throughflow, driven by El Niño and negative Indian Ocean Dipole events. This extra carbon made the water more acidic and caused the depth at which aragonite (a mineral important for shell-building organisms) remains stable to rise by nearly 20 m in the southeastern Indian Ocean. These chemical changes could threaten deep-water organisms that rely on stable chemical conditions. Our results highlight how ocean currents can strongly affect carbon storage and acidification, and point to the need for better subsurface measurements and models to understand how climate variability impacts the ocean interior.

Key Points

  • Indian Ocean carbon storage varied unprecedentedly in 2016–2017, driven by circulation anomalies linked to climate variability
  • Anomalous dissolved inorganic carbon inventory was mainly due to increased Southern Ocean inflow and weakened Indonesian Throughflow
  • Anomalous carbon redistribution caused subsurface acidification, shoaling aragonite saturation depth by ∼20 m in the southeast Indian Ocean
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Remote sensing observation of sea surface temperature (SST) and pCO2 over the Bay of Bengal and Arabian Sea and its relation with chlorophyll variability

Published 13 October 2025 Science Closed
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The study is carried out to estimate the satellite-derived partial pressure of carbon dioxide (pCO2) in the Bay of Bengal (BoB) and Arabian Sea (AS) using sea surface temperature (SST)-based algorithm. The relationship of satellite-derived pCO2 with SST and chlorophyll has been understood in different seasonal months and years. The SST images are generated for the Bay of Bengal and Arabian Sea during two distinct seasonal months, December 2013 and 2014 and April 2014 and 2015. The daily and 8 days, monthly composite SST images are generated using INSAT-3D, MODIS-Aqua, and GHRSST datasets. The corresponding overpass time of MODIS-Aqua and INSAT-3D 13:30Hrs SST data has been archived. The SST is observed in the range of 24–32 °C. The SST-based pCO2 algorithm is applied over the northern Indian ocean and the pCO2 variability in two different seasons monitored. The pCO2 ranged around 350–750 μatm. The INSAT-3D derived 30-min time interval images processed on intra-day basis having 48 passes per day. The pCO2 images observed directly proportional relationship with the SST images during summer and inverse trend during winter. With the increase in SST by 1–2 °C, there has been increase in pCO2 by 2–5% during summer. The comparison of pCO2 on weekly and monthly time scales using the INSAT-3D, MODIS and GHRSST data has been observed to be interesting and showed matching trend. This exemplifies the preliminary study to understand the hourly, daily, weekly, monthly, and seasonal trend of SST and pCO2 variability in the northern Indian Ocean basins using satellite datasets. The MODIS-Aqua monthly composite chlorophyll images indicate that the high chlorophyll (0.8–1.4 mg m−3) patches are matching well with the high pCO2 concentration (400–450 μatm) patches during winter month and similar trend is not observed during summer month. Main findings of the paper are to have the pCO2 estimation using SST data in Indian scenario using multiple satellite datasets from MODIS-Aqua, INSAT, and GHRSST datasets and the comparison with ocean productivity using satellite-derived chlorophyll data. This study has a strong relevance in terms of ocean acidification monitoring using satellite data- and model-based time-series map generation. The study is important from the point of view of air-sea interaction, ocean acidification, and ocean biogeochemistry. The in situ pCO2 measurements, data validation, and fine-tuning would rely on the scope for regional algorithm development as future study and trend analysis from climate change perspective.

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Insights from a changing ocean: evolving biogeochemistry and its impacts on marine ecosystems and climate

Published 13 October 2025 Science Closed
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Marine biogeochemistry integrates chemical, biological, geological, and physical processes that are fundamental to Earth’s climate and ecosystems. As elements cycle through the ocean, atmosphere, and biosphere, they leave behind biogeochemical fingerprints that serve as proxies to track environmental change. Over the industrial era, anthropogenic CO2 emissions and other human activities have caused the oceans to change rapidly, perturbing this biogeochemical landscape. Characterizing biogeochemical shifts is critical to advance our understanding of climate-driven impacts, assess marine ecosystem health, and evaluate climate solutions. Recent advancements in biogeochemical tools and technologies have deepened our insights into oceanic change. The development of high-precision paleoproxies has extended records of ocean conditions into the pre-industrial era, while the Argo float array has enabled four-dimensional monitoring of biogeochemistry globally. High-resolution numerical modeling has also improved our ability to capture complex interactions at fine spatial and temporal scales, offering a holistic framework to understand anthropogenic impacts from past to future. Together, these technologies provide a comprehensive toolkit to characterize shifts in ocean biogeochemistry in unprecedented detail and advance our understanding of global environmental change. This thesis weaves together applications of novel biogeochemical tools to examine the drivers, impacts, and mitigation strategies of a rapidly changing ocean. Each chapter leverages diverse datasets and multiple tools to provide new insights on ocean change based on marine biogeochemistry. In Chapter 2, I combine boron-isotope measurements from cold-water corals with a biogeochemical model to reconstruct and investigate subsurface acidification trends over the industrial era in the California Current System. In Chapter 3, I combine Argo-based biogeochemical data products, archival tagging records, and machine learning methods to develop a four-dimensional species distribution model for an economically important fishery species, revealing biogeochemical constraints on its migration. In Chapter 4, I employ a high-resolution biogeochemical model of the Salish Sea to evaluate the detectability of ocean alkalinity enhancement, a marine carbon dioxide removal strategy for climate mitigation. These studies provide new frameworks and tools to investigate, monitor, and respond to a changing ocean.

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Estimating pCO2 using random forest regression in the Seto Inland Sea, Japan

Published 10 October 2025 Science Closed
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While research on pCO2 (partial pressure of carbon dioxide in seawater) in surface seawater in coastal areas has advanced, it remains less extensive than studies in the open ocean. One reason is the difficulty of measuring pCO2 directly. In this study, we develop models to estimate pCO2 from commonly measured parameters using the random forest. For estimating pCO2 from seawater temperature, salinity, pH, and dissolved oxygen, random forest is considered to be valid compared to multiple linear regression. In terms of pCO2 characteristics, building estimation models separately for Osaka Bay and Bisan Seto and other areas improved the accuracy compared to the single model, which estimation errors were 32.0, 34.9, 20.9 µatm, respectively. Inputting the Seto Inland Sea Comprehensive Water Quality Survey data to the three models, we estimated pCO2 and the spatial distribution. Compared to measured spatial variation, estimated pCO2 showed a similar trend and the maximum relative error was about 17%. From estimating spatial distribution, we obtained similar characteristics to the in situ measurements, such as the lowest in the inner part of Osaka Bay, and the highest in the Bisan Seto.

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Interspecific vulnerabilities to elevated pCO2 in the northwestern Gulf of Mexico, a baseline of sensitivity and geochemical regimes

Published 9 October 2025 Science Closed
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Marine organisms rely on stable seawater conditions and vary in taxa-specific tolerances to environmental change. The capacity for acclimatization in marine taxa is dependent on local adaptation. Our ability to generate accurate global predictions starts in identifying regional responses, informing facets that fit globally in a mosaic of response to environmental extremes. The northwestern Gulf of Mexico (nwGoM) has not previously been isolated as a region with significant multi-taxon level comparisons under geochemical extremes. Therefore, we aim to procure a nwGoM regional baseline via a literature search in all known marine taxa’s response to elevated CO2 partial pressure (pCO2) coupled with real-time ecosystem modeling of this region. The baseline carbonate chemistry conditions indicate that pH, aragonite saturation state (Ωarag), and pCO2 exhibit greater temporal and spatial variability within the upper 20 m of the water column, with nearshore waters showing more pronounced seasonal spatial variation than offshore waters. Of the taxon reported, 68.5% reported a negative response to increased pCO2, whereas 31.4% showed a neutral or mixed neutral response (positive or negative). Only 11.4% of reported taxa showed a positive response to elevated pCO2. Shown here is a holistic negative response to increased pCO2 through collating external studies. Data was only found on 1.0% of the total species we recorded in the nwGoM region, highlighting a significant gap in our understanding of regional ecosystem wide sensitivity. Of the species shown here, 83% have habitat ranges within the top 20 m of the water column, and with seasonal variability they may be exposed to several extremes, modeled here but overlooked when compared to global predictions. Continuing experimental work on the reported species here will inform regional predictions to fit the global mosaic predicting the state of our oceans to future conditions.

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Remote sensing of coastal acidification: UAS and satellite-based estimation in the Mississippi Sound and landscape change impact assessment

Published 7 October 2025 Science Closed
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Ocean acidification results from atmospheric CO₂ absorption, while coastal acidification is more localized, influenced by nutrient runoff, freshwater input, and organic matter decomposition. Due to its complexity, specialized monitoring is essential. The present research estimated two key carbonate system parameters total alkalinity (TA) and partial pressure of carbon dioxide (pCO₂) using uncrewed aircraft systems (UAS) imagery and autonomous surface vessel (ASV) observations over an oyster reef in the Western Mississippi Sound (WMS). Field campaigns were conducted from 2018 to 2022 to collect high resolution aerial imagery over the largest oyster reef in WMS, utilizing a multispectral sensor mounted on a drone. An ASV was deployed during June, July, and September 2021 UAS missions over the same sites to collect in situ data, including pH, partial pressure of carbon dioxide (pCO2), sea surface temperature (SST), sea surface salinity (SSS), colored dissolved organic matter (CDOM), and chlorophyll-a (Chl-a). Random forest models developed and accurately estimated TA and pCO₂ (R² > 0.91). Time-series maps were generated using Chl-a images derived from UAS imagery and SSS images derived from CDOM maps, employing salinity-CDOM linear regression model developed in this study. Results demonstrate UAS effectiveness in small-scale coastal monitoring due to its high spatial resolution. However, UAS lacks spatial coverage needed for broader regions like Mississippi Sound. To address this, MODIS imagery and HYCOM model outputs were integrated with ASV data collected in June and August 2023 in this research. Random forest models using SST, SSS, and Chl-a performed well (R² = 0.81 for TA, 0.87 for pCO₂). By incorporating MODIS Level 3 SST and Chl-a (1 km) and HYCOM SSS (downscaled 4 km to 1 km), this research generated annual and monthly time-series maps of mean TA and pCO₂ over the entire Mississippi Sound for the period 2002–2020. These maps reveal spatial seasonal dynamics and long-term trends. This research also investigated how land use and land cover (LULC) changes influenced TA and pCO₂ across the entire Mississippi Sound from 2002 to 2020. Spatial correlation and trend maps revealed associations between eight LULC class type changes and TA and pCO₂ patterns. The findings suggest connections between environmental changes and carbonate system responses but do not confirm causation, instead providing a basis for hypothesis generation and further study of biogeochemical processes. Overall, this dissertation highlights how combining remote sensing, in situ measurements, machine learning technique, and LULC analysis improves coastal acidification assessment in the Mississippi Sound.

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Effects of climate change on marine ecosystems in the southeastern Pacific: multiple ocean stressors assessed through climate velocities

Published 3 October 2025 Science Closed
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Anthropogenic climate change (CC) has triggered a cascade of impacts on marine ecosystems, often referred to as the ‘deadly trio’: warming, acidification, and deoxygenation. While these stressors will globally lead to the compression of marine habitats, their regional effects vary significantly and remain understudied. This is particularly true for the southeastern Pacific (SEP), which supports rich pelagic and benthic ecosystems closely linked to a complex seafloor featuring archipelagos and extensive seamount chains. Using model simulations from Phase 6 of the Coupled Model Intercomparison Project, this study examines future regional-scale environmental changes in the SEP. Our analysis builds on the observation that the South Pacific Ocean Gyre is among the regions experiencing the least warming globally and that the epipelagic zone within the oxygen minimum zone (OMZ) may oxygenate in the future. These conditions may promote habitat expansion, which we assess using the climate velocities for temperature, oxygen, and pH. Estimates of climate velocities from the ensemble model mean under a pessimistic near future (2015-2050) yield values ranging from –730 to 449 km/year, exhibiting greater absolute climate velocities for oxygen than pH. Over the longer-term horizon (2015–2100), the area of zones where absolute climate velocity exceeded the 75th percentile increased by 65%, 72%, and 215% for temperature, oxygen, and pH, respectively. The strongest velocities (absolute value) occur in the equatorial sector and in the Humboldt system. While all regions mostly show a climate-driven habitat loss due to surface-to-200 m pH decline, two broad areas benefit from conservation below the surface: a region in the tropics extending from 10°S–100°W to the east of Rapa Nui and the coastal region of Peru and Chile, extending up to the Desventuradas and Juan Fernández archipelagos. While the former is due to the slow warming rates (<2.9 km yr−1), the latter results from both slow deoxygenation and oxygenation climate velocities (between −2.9 and 2.9 km yr−1) along the coast of those countries, a zone that overlaps with the lowest changes in pH in the SEP, giving them a unique conservation value. We demonstrate that epipelagic ecosystems within the OMZ may be less impacted by CC than those outside of it. These findings highlight key areas for conservation under future ocean warming, deoxygenation and pH changes.

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Riverine-coastal carbon dynamics, acidification, and CO2 outgassing in an intensive mariculture bay

Published 17 September 2025 Science Closed
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Highlights

  • Coupled DIC and δ13CDIC analysis enabled quantification of carbonate system alteration.
  • Organic matter degradation dominated the main channel, causing acidification.
  • Summer phytoplankton production buffered acidification in western bay waters.
  • Remineralized exogenous nitrogen and nitrification intensified oxygen consumption.
  • Net carbon dioxide outgassing occurred throughout Sansha Bay in winter and summer.

Abstract

Semi-enclosed bays offer hydrodynamic conditions favorable for mariculture, yet this activity can greatly alter coastal carbon dynamics and may transform coastal waters into bioreactors that modulate the carbonate system by stimulating organic matter (OM) inputs, respiration, primary production, and coupled oxygen consumption-acidification. We investigate seasonal variability in carbonate system dynamics and dissolved inorganic carbon stable isotopic composition (δ13CDIC) in Sansha Bay, the largest large yellow croaker culture site in China, which is flushed by rivers and varying coastal water masses. Adopting a semi-analytical framework that uses a two end-member mixing model, we found that along the main channel, DIC concentrations were elevated by ∼5.3–87.5 μmol kg−1, along with pH reduction of ∼0.05–0.07 units. Instead, western off-main channel with longer residence times exhibited opposing trends: winter DIC accumulation (up to 167 μmol kg−1) and summer net removal (up to −75 μmol kg−1), accompanying a pH decrease/increase of ∼0.12/∼0.19 units, respectively. Excess DIC was mainly attributable to OM remineralization and partially removed by phytoplankton production. The bay supplied a net CO2 source, supported by high pCO2 (mean: 811/562 μatm in winter/summer, respectively). Box model analysis showed that marine-derived OM remineralization combined with mariculture feed inputs caused DIC enrichment and declining oxygen consumption and pH evidenced by a −16.6 ‰ δ13Cox value and 0.43–0.70 carbon/oxygen stoichiometry. Results underscore the role of interacting water masses and mariculture in modulating the carbonate system and its coupling with oxygen and pH dynamics. They provide critical insights into biogeochemical processes driving hypoxia and acidification in intensively farmed coastal ecosystems.

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A regional physical–biogeochemical ocean model for marine resource applications in the Northeast Pacific (MOM6-COBALT-NEP10k v1.0)

Published 5 September 2025 Science Closed
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Regional ocean models enable the generation of computationally affordable and regionally tailored ensembles of near-term forecasts and long-term projections of sufficient resolution to serve marine resource management. Climate change, however, has created marine resource challenges, such as shifting stock distributions, that cut across domestic and international management boundaries and have pushed regional modeling efforts toward “coastwide” approaches. Here, we present and evaluate a multidecadal hindcast with a Northeast Pacific regional implementation of the Modular Ocean Model, version 6, with sea ice and biogeochemistry that extends from the Chukchi Sea to the Baja California Peninsula at 10 km horizontal resolution (MOM6-COBALT-NEP10k, or NEP10k). This domain includes an Arctic-adjacent system with a broad, shallow shelf seasonally covered by sea ice (the eastern Bering Sea), a sub-Arctic system with upwelling in the Alaska Gyre and predominant downwelling winds and large freshwater forcing along the coast (the Gulf of Alaska), and a temperate, eastern boundary upwelling ecosystem (the California Current Ecosystem). The coastwide model was able to recreate seasonal and cross-ecosystem contrasts in numerous ecosystem-critical properties including temperature, salinity, inorganic nutrients, oxygen, carbonate saturation states, and chlorophyll. Spatial consistency between modeled quantities and observations generally extended to plankton ecosystems, though small to moderate biases were also apparent. Fidelity with observed zooplankton biomass, for example, was limited to first-order seasonal and cross-system contrasts. Temporally, simulated monthly surface and bottom temperature anomalies in coastal regions (<500 m deep) closely matched estimates from data-assimilative ocean reanalyses. Performance, however, was reduced in some nearshore regions coarsely resolved by the model’s 10 km resolution grid and for point measurements. The time series of satellite-based chlorophyll anomaly estimates proved more difficult to match than temperature. System-specific ecosystem indicators were also assessed. In the eastern Bering Sea, NEP10k robustly matched observed variations, including recent large declines, in the area of the summer bottom water “cold pool” (<2 °C), which exerts a profound influence on eastern Bering Sea fisheries. In the Gulf of Alaska, the simulation captured patterns of sea surface height variability and variations in thermal, oxygen, and acidification risk associated with local modes of interannual to decadal climate variability. In the California Current Ecosystem, the simulation robustly captured variations in upwelling indices and coastal water masses, though discrepancies in the latter were evident in the Southern California Bight. Enhanced model resolution may reduce such discrepancies, but any benefits must be carefully weighed against computational costs given the intended use of this system for ensemble predictions and projections. Meanwhile, the demonstrated NEP10k skill level herein, particularly in recreating cross-ecosystem contrasts and the time variation of ecosystem indicators over multiple decades, suggests considerable immediate utility for coastwide retrospective and predictive applications.

Continue reading ‘A regional physical–biogeochemical ocean model for marine resource applications in the Northeast Pacific (MOM6-COBALT-NEP10k v1.0)’

Statistical models for the estimation of pH and aragonite saturation state in the Northwestern Gulf of Mexico

Published 4 September 2025 Science Closed
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Historical water column carbonate measurements have been scarce in the Gulf of Mexico (GOM); thus, the progression of ocean acidification (OA) is still poorly understood, especially in the subsurface waters. In the literature, statistical models, such as multiple linear regression (MLR), have been created to fill OA data gaps in different ocean regions. Additionally, machine learning techniques such as random forest (RF) have been used in model creations for both the open ocean and marginal seas. However, there is no statistical model for subsurface carbonate chemistry parameters (i.e., pH and ΩArag) in the GOM. By creating models with various architectures built upon the relationships between commonly measured hydrographic properties (e.g., salinity, temperature, pressure, and dissolved oxygen or DO) and carbonate chemistry parameters (e.g., pH and aragonite saturation state, or ΩArag), data gaps can be potentially filled in areas with insufficient sampling coverage. In this study, two statistical models were created for pH and ΩArag in the northwestern GOM (nwGOM) within the range of 27.1–29.0˚N and 89–95.1˚W using both MLR and RF methods. The calibration data used in the models include salinity, temperature, pressure, and DO collected from seven cruises that took place between July 2007 and February 2023. The models predict ΩArag with R2 ≥ 0.94, mean square error (MSE) ≤ 0.04, and pH with R2 ≥ 0.93, MSE ≤ 0.0005. Both the MLR and RF models perform similarly. These models are valuable tools for reconstructing pH and ΩArag data where direct chemical observations are absent but hydrographic information is available in the nwGOM. Nevertheless, potential shifts in circulation, water mass changes, and accumulation of anthropogenic CO2 need to be accounted for to improve and revise these models in the future.

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Model based analysis of the methane seeping influence on the acidification in the East Siberian Arctic Shelf waters

Published 4 September 2025 Science Closed
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A giant Arctic subsea permafrost reservoir of methane (CH4) in different forms (hydrates, free gas) is leaking, likely at an increasing rate under climate warming. This is causing a massive CH4 release from sediments into the water column and atmosphere. A part of the released CH4 is oxidized in the water column to CO2. In this work we applied a model for analyzing of consequences for the water column carbonate system of excessive production of CO2 during the aerobic oxidation of CH4 in an area of its intensive seeping in the East Siberian Arctic Shelf (ESAS). The model system comprised a 2-Dimensional vertical Benthic Pelagic transport Model 2DBP, principal biogeochemistry and carbonate system modules from the biogeochemical model BROM (Bottom RedOx Model), and a gas bubble fate module that parameterizes bubbles rising and dissolution. The simulations showed that consumption of oxygen and production of carbon dioxide via aerobic oxidation of methane results in spatial anomalies of pH and dissolved oxygen concentration that are consistent with the field observations. We hypothesize that aerobic oxidation of methane in the regions of intensive seeping leads to production of CO2, with associated decrease of pH and lowering of aragonite saturation to less than 1, therefore contributing to the extreme acidification states that are observed on the East Siberian Arctic Shelf.

Continue reading ‘Model based analysis of the methane seeping influence on the acidification in the East Siberian Arctic Shelf waters’

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