Biogeochemical cycles in the Arctic Ocean are sensitive to the transport of materials from continental shelves into central basins by sea ice. However, it is difficult to assess the net effect of this supply mechanism due to the spatial heterogeneity of sea ice content. Manganese (Mn) is a micronutrient and tracer which integrates source fluctuations in space and time. The Arctic Ocean surface Mn maximum is attributed to freshwater, but studies struggle to distinguish sea ice and river contributions. Informed by observations from 2009 IPY and 2015 Canadian GEOTRACES cruises, we developed a three-dimensional dissolved Mn model within a 1/12 degree coupled ocean-ice model centered on the Canada Basin and the Canadian Arctic Archipelago (CAA). Simulations from 2002-2019 indicate that annually, 87-93% of Mn contributed to the Canada Basin upper ocean is released by sea ice, while rivers, although locally significant, contribute only 2.2-8.5%. Downstream, sea ice provides 34% of Mn transported from Parry Channel into Baffin Bay. While rivers are often considered the main source of Mn, our findings suggest that in the Canada Basin they are less important than sea ice. However, within the shelf-dominated CAA, both rivers and sediment resuspension are important. Climate induced disruption of the transpolar drift may reduce the Canada Basin Mn maximum and supply downstream. Other micronutrients found in sediments, such as Fe, may be similarly affected. These results highlight the vulnerability of the biogeochemical supply mechanisms in the Arctic Ocean and the subpolar seas to climatic changes.

Most marine plastic pollution originates on land. However, once plastic is at sea, it is difficult to determine its origin. Here we present a Bayesian inference framework to compute the probability that a piece of plastic found at sea came from a particular source. This framework combines information about plastic emitted by rivers with a Lagrangian simulation, and yields maps indicating the probability that a particle sampled somewhere in the ocean originates from a particular source. We applied the framework to the South Atlantic Ocean, focusing on floating river-sourced plastic. We computed the probability as a function of the particle age, at three locations, showing how probabilities vary according to the location and age. We computed the source probability of beached particles, showing that plastic found at a given latitude is most likely to come from the closest source. This framework lays the basis for source attribution of marine plastic.

The Alfred Wegener Institute Climate Model (AWI-CM) participates for the first time in the Coupled Model Intercomparison Project (CMIP), CMIP6. The sea ice-ocean component, FESOM, runs on an unstructured mesh with horizontal resolutions ranging from 8 to 80 km. FESOM is coupled to the Max-Planck-Institute atmospheric model ECHAM 6.3 at a horizontal resolution of about 100 km. Using objective performance indices, it is shown that AWI-CM performs better than the average of CMIP5 models. AWI-CM shows an equilibrium climate sensitivity of 3.2°C, which is similar to the CMIP5 average, and a transient climate response of 2.1°C which is slightly higher than the CMIP5 average. The negative trend of Arctic sea ice extent in September over the past 30 years is 20-30% weaker in our simulations compared to observations. With the strongest emission scenario, the AMOC decreases by 25% until the end of the century which is less than the CMIP5 average of 40%. Patterns and even magnitude of simulated temperature and precipitation changes at the end of this century compared to present-day climate under the strong emission scenario SSP585 are similar to the multi-model CMIP5 mean. The simulations show a 11°C warming north of the Barents Sea and around 2 to 3°C over most parts of the ocean as well as a wetting of the Arctic, subpolar, tropical and Southern Ocean. Furthermore, in the northern mid-latitudes in boreal summer and autumn as well as in the southern mid-latitudes a more zonal atmospheric flow is projected throughout the year.

Reliable estimates of occurrence probabilities of sea level extremes are required in coastal planning (e.g. design floods) and to mitigate risks related to flooding. Probabilities of specific extreme events have been traditionally estimated from the observed extremes independently at each tide gauge location. However, this approach has shortcomings. Firstly, sea level observations often cover a relatively short historical time period and thus contain only a small number of extreme cases (e.g. annual maxima). This causes substantial uncertainties when estimating the distribution parameters. Secondly, exact information on sea level extremes between the tide gauge locations and incorporation of depen- dencies of adjacent stations is often lacking in the analysis. A partial remedy to these issues is to exploit spatial dependencies exhibited by the sea level extremes. These dependencies emerge from the fact that sea level variations are often driven by the same physical and dynamical factors at the neighboring stations. Bayesian hierarchical modeling offers a way to model these dependencies. The model structure allows to share information on sea level extremes between the neighboring stations and also provides a natural way to represent modeling uncertainties. In this study, we use Bayesian hierarchical modeling to estimate return levels of annual sea level maximum in the Finnish coastal region, located along the north-east part of the Baltic Sea. As annual maxima are studied, we use the generalized extreme value (GEV) distribution as the basis of our model. To tailor the model specifically for the target region, spatial dependencies are modeled using physical covariates which reflect the distinct geometry of the Baltic Sea. We illustrate the added value of the hierarchical model in comparison to the traditional one using the available long-term tide gauge time series in Finland. Careful analysis of the sources of uncertainties is necessary when extrapolating the return level estimates into the future. This work is a part of project PREDICT (Predicting extreme weather and sea level for nuclear power plant safety) that supports nuclear power plant safety in Finland.

Areas covered in compact sea ice are often assumed to prohibit upper ocean photosynthesis. Yet under-ice phytoplankton blooms (UIBs) have increasingly been observed in the Arctic, driven by anthropogenic changes to the optical properties of Arctic sea ice. Here we show the Southern Ocean can also support widespread UIBs. Using under ice-enabled BGC-Argo float data, we detail numerous high phytoplankton biomass events below compact sea ice preceding seasonal ice retreat, and classify 12 distinct UIB events. Using joint light, sea ice, and ocean conditions obtained from the ICESat-2 laser altimeter and 11 climate model contributions to CMIP6, we find that more than 4 million square kilometers of the compact-ice-covered Southern Ocean could support these events in late spring and early summer.

We highlight a mechanism for the co-production of research with local communities as a means of elevating the social relevance of the geosciences, increasing the potential for broader and more diverse participation. We outline the concept of an “equitable exchange” as an ethical framework guiding these interactions. This principled research model emphasizes that “currencies”- the rewards and value from participating in research - may differ between local communities and geoscientists. For those engaged in this work, an equitable exchange emboldens boundary spanning geoscientists to bring their whole selves to the work, providing a means for inclusive climates and rewarding cultural competency.

We investigate the Chukchi and the Beaufort seas, where salty and warm Pacific Water flows in from the Bering Strait and interacts with the sea ice, contributing to its summer melt. For the first time, thanks to in-situ measurements recorded by two saildrones deployed during summer 2019 and to refined sea ice filtering in satellite L-Band radiometric data, we demonstrate the ability of satellite Sea Surface Salinity (SSS) observed by SMOS and SMAP to capture SSS freshening induced by sea ice melt, referred to as meltwater lenses (MWL). The largest MWL observed by the saildrones during this period occupied a large part of the Chukchi shelf, with a SSS freshening reaching -5 pss. it persisted for up to one month, to this MWL, induced low SSS pattern which restricted the transfer of air-sea momentum to the upper, as illustrated by measured wind speed and vertical profiles of currents. Combined with satellite-based Sea Surface Temperature, satellite SSS provides a monitoring of the different water masses encountered in the region during summer 2019. Using sea ice concentration and estimated Ekman transport, we analyse the spatial variability of sea surface properties after the sea ice edge retreat over the Chukchi and the Beaufort seas. The two MWL captured by both, the saildrones and the satellite measurements, result from different dynamics. Over the Beaufort Sea, the MWL evolution follows the meridional sea ice retreat, whereas in the Chukchi Sea, a large persisting MWL is generated by advection of a sea ice filament.

This study isolates the influence of sea ice mean state on pre-industrial climate and transient 1850-2100 climate change within a fully coupled global model: The Community Earth System Model version 2 (CESM2). The CESM2 sea ice model physics is modified to increase surface albedo, reduce surface sea ice melt, and increase Arctic sea ice thickness and late summer cover. Importantly, increased Arctic sea ice in the modified model reduces a present-day late-summer ice cover bias. Of interest to coupled model development, this bias reduction is realized without degrading the global simulation including top-of-atmosphere energy imbalance, surface temperature, surface precipitation, and major modes of climate variability. The influence of these sea ice physics changes on transient 1850-2100 climate change is compared within a large initial condition ensemble framework. Despite similar global warming, the modified model with thicker Arctic sea ice than CESM2 has a delayed and more realistic transition to a seasonally ice free Arctic Ocean. Differences in transient climate change between the modified model and CESM2 are challenging to detect due to large internally generated climate variability. In particular, two common sea ice benchmarks - sea ice sensitivity and sea ice trends - are of limited value for comparing models with similar global warming. More broadly, these results show the importance of a reasonable Arctic sea ice mean state when simulating the transition to an ice-free Arctic Ocean in a warming world. Additionally, this work highlights the importance of large initial condition ensembles for credible model-to-model and observation-model comparisons.

The Indian Ocean has warmed rapidly over the last half of the 20th century, with widespread effects on regional weather, and global climate. Determining the causes of the observed warming is challenging due to the lack of a long instrumental record of interior ocean temperature, leaving uncertainty around the active physical mechanisms and the role of decadal variability. Here we utilize unique temperature observations from three historical German oceanographic expeditions of the late 19th and early 20th centuries: SMS Gazelle (1874–1876), Valdivia (1898–1899), and SMS Planet (1906–1907). These observations reveal a mean 20th century ocean warming that extends over the upper 750 m, and a spatial pattern of subsurface warming and cooling consistent with a 1°–2° southward shift of the ocean gyres. These interior changes occurred largely over the last half of the 20th century, providing observational evidence for the acceleration of a multidecadal trend in subsurface Indian Ocean temperature.

Submesoscale currents, comprising fronts and mixed-layer eddies, exhibit a dual cascade of kinetic energy: a forward cascade to dissipation scales at fronts and an inverse cascade from mixed-layer eddies to mesoscale eddies. Within a coarse-graining framework using both spatial and temporal filters, we show that this dual cascade can be captured in simple mathematical form obtained by writing the cross-scale energy flux in the local principal strain coordinate system, wherein the flux reduces to the the sum of two terms, one proportional to the convergence and the other proportional to the strain. The strain term is found to cause the inverse energy flux to larger scales while an approximate equipartition of the convergent and strain terms capture the forward energy flux, demonstrated through model-based analysis and asymptotic theory. A consequence of this equipartition is that the frontal forward energy flux is simply proportional to the frontal convergence. In a recent study, it was shown that the Lagrangian rate of change of quantities like the divergence, vorticity and horizontal buoyancy gradient are proportional to convergence at fronts implying that horizontal convergence drives frontogenesis. We show that these two results imply that the primary mechanism for the forward energy flux at fronts is frontogenesis. We also analyze the energy flux through a Helmholtz decomposition and show that the rotational components are primarily responsible for the inverse cascade while a mix of the divergent and rotational components cause the forward cascade, consistent with our asymptotic analysis based on the principal strain framework.

Knowledge of the chemical speciation of particulate manganese (pMn) is important for understanding the biogeochemical cycling of Mn and other particle-reactive elements. Here, we present the synchrotron-based X-ray spectroscopy-derived average oxidation state (AOS) of pMn in the surface Arctic Ocean collected during the U.S. GEOTRACES Arctic cruise (GN01) in 2015. We show that the pMn AOS is less than 2.4 when sampled during the day and more than ~3.0 when sampled at night. We hypothesize that an active light-dependent redox cycle between dissolved Mn and particulate Mn(III/IV) exists during the day-night cycle in the surface Arctic Ocean, which occurs on the timescale of hours. The magnitude of observed pMn AOS is likely determined by the net effect of the length of the previous night and integrated light level before the end of pMn sampling.

Predicting Pacific Decadal Oscillation (PDO) transitions and understanding the associated mechanisms has proven a critical but challenging task in climate science. As a form of decadal variability, the PDO is associated with both large-scale climate shifts and regional climate predictability. We show that artificial neural networks (ANNs) predict PDO persistence and transitions from 12 months onward. Using layer-wise relevance propagation to investigate the ANN predictions, we demonstrate that the ANNs utilize oceanic patterns that have been previously linked to predictable PDO behavior. For PDO transitions, ANNs recognize a build-up of ocean heat content in the off-equatorial western Pacific 12-27 months before a transition occurs. The results support the continued use of ANNs in climate studies where explainability tools can assist in mechanistic understanding of the climate system.

Changes in the circulation of the Southern Ocean are known to have impacted global nutrient, heat, and carbon cycles during the glacial and interglacial periods of the late Pleistocene. Proxy-based records of these changes deserve continued scrutiny as the implications may be important for constraining future change. A record of authigenic uranium from the South Atlantic has been used to infer changes in deep-sea oxygenation and organic matter export over the past 0.5 million years. Since sedimentary uranium has the possible complication of remobilization, it is prudent to investigate the behavior of other redox-sensitive trace metals to confidently interpret temporal changes in oxygenation. Focusing here on the exceptionally long interglacial warm period, Marine Isotope Stage (MIS) 11, we found concurrent authigenic enrichments of uranium and rhenium throughout MIS 12 to 10, overall supporting prior interpretations of low-oxygen periods. However, there are differential responses of Re and U to oxygen changes and some evidence of small-scale Re remobilization, which may involve differences in molecular-level reduction mechanisms. Peaks in authigenic manganese intervening with peaks in Re and U indicate increases in porewater oxygenation which likely relate to increased Antarctic Bottom Water circulation at the onset of MIS11c and during the peak warmth of the interglacial around 400 ka.

Our current understanding of global mean near-surface (land and sea) air temperature (GMSAT) during the Cenozoic era relies on paleo-proxy estimates of deep-sea temperature combined with assumed relationships between global mean deep-sea temperature (GMDST), global mean sea-surface temperature (GMSST), and GMSAT. The validity of these assumptions is essential in our understanding of past climate states such as the Early Eocene Climate Optimum hothouse climate (EECO, 56–48 Ma). The EECO remains relevant today, because EECO-like CO2 levels are possible in the 22nd century under continued high CO2 emissions. We analyze the relationship between the three global temperature indicators for the EECO using 25 different millennia-long model simulations with varying CO2 levels from the Deep-Time Model Intercomparison Project (DeepMIP). The model simulations show limited spatial variability in deep-sea temperature, indicating that local temperature estimates can be regarded representative of GMDST. Linear regression analysis indicates that compared to GMSST, both GMDST and GMSAT respond more strongly to changes in atmospheric CO2 by factors of 1.18 and 1.17, respectively. Consequently, this model-based analysis validates the assumption that changes in GMDST can be used to estimate changes in GMSAT during the EECO. Paleo-proxies of GMDST, GMSST, and GMSAT during EECO show the best fit with model simulations having an atmospheric CO2 level of 1,680 ppm, which matches paleo-proxies of atmospheric CO2 during EECO. Similar analyses of other past climate states are needed to examine whether these results are robust throughout the Cenozoic, providing insight into the long-term future warming under various shared socioeconomic pathways.

Several bills moving through Congress are likely to provide significant funding for expanding research and results in climate change solutions (CCS). This is also a priority of the Biden-Harris Administration. The National Science Foundation (NSF) will be expected to distribute and manage much of this funding through its grant processes. Effective solutions require both a continuation and expansion of research on climate change–to understand and thus plan for potential impacts locally to globally and to continually assess solutions against a changing climate–and rapid adoption and implementation of this science with society at all levels. NSF asked AGU to convene its community to help provide guidance and recommendations for enabling significant and impactful CCS outcomes by 1 June. AGU was asked in particular to address the following: 1. Identify the biggest, more important interdisciplinary/convergent challenges in climate change that can be addressed in the next 2 to 3 years 2. Create 2-year and 3-year roadmaps to address the identified challenges. Indicate partnerships required to deliver on the promise. 3. Provide ideas on the creation of an aggressive outreach/communications plan to inform the public and decision makers on the critical importance of geoscience. 4. Identify information, training, and other resources needed to embed a culture of innovation, entrepreneurialism, and translational research in the geosciences. Given the short time frame for this report, AGU reached out to key leaders, including Council members, members of several committees, journal editors, early career scientists, and also included additional stakeholders from sectors relevant to CCS, including community leaders, planners and architects, business leaders, NGO representatives, and others. Participants were provided a form to submit ideas, and also invited to two workshops. The first was aimed at ideation around broad efforts and activities needed for impactful CCS; the second was aimed at in depth development of several broad efforts at scale. Overall, about 125 people participated; 78 responded to the survey, 82 attended the first workshop, and 28 attended the more-focused second workshop (see contributor list). This report provides a high-level summary of these inputs and recommendations, focusing on guiding principles and several ideas that received broader support at the workshops and post-workshop review. These guiding principles and ideas cover a range of activities and were viewed as having high importance for realizing impactful CCS at the scale of funding anticipated. These cover the major areas of the charge, including research and solutions, education, communication, and training. The participants and full list of ideas and suggestions are provided as an appendix. Many contributed directly to this report; the listed authors are the steering committee.

Two methods for the mapping of ocean surface currents from satellite measurements of sea level and future current vectors are presented and contrasted. Both methods rely on the linear and Gaussian analysis frameworkwith different levels of covariance definitions. The first method separately maps sea level and currents with single-scale covariance functions and leads to estimates of the geostrophic and ageostrophic circulations. The second maps both measurements simultaneously and projects the circulation onto 4 contributions: geostrophic, ageostrophic rotary, ageostrophic divergent and inertial. When compared to the first method, the second mapping moderately improves the resolution of geostrophic currents but significantly improves estimates of the ageostrophic circulation, in particular near-inertial oscillations. This method offers promising perspectives for reconstructions of the ocean surface circulation. Even the hourly dynamics can be reconstructed from measurements made locally every few days because nearby measurements are coherent enough to help fill the gaps. Based on numerical simulation of ocean surface currents, the proposed SKIM mission that combines a nadir altimeter and a Doppler scatterometer with a 300 km wide swath (with a mean revisit time of 3 days) would allow the reconstruction of 50% of the near-inertial variance around an 18 hour period of oscillation.

Particle methods can provide detailed descriptions of sea ice dynamics that explicitly model fracture and discontinuities in the ice, which are difficult to capture with traditional continuum approaches. We use the ParticLS software library to develop a discrete element method (DEM) model for sea ice dynamics at regional scales and smaller (<100 km). We model the sea ice as a collection of discrete rigid particles that are initially bonded together using a cohesive beam model that approximates the response of an Euler-Bernoulli beam located between particle centroids. Ice fracture and lead formation are determined based on the value of a non-local stress state around each particle and a Mohr-Coulomb fracture model. Therefore, large ice floes are modeled as continuous objects made up of many bonded particles that can interact with each other, deform, and fracture. We generate realistic particle configurations by discretizing the ice in MODIS satellite imagery into polygonal floes that fill the ice shape and extent that occurred in nature. The model is tested on ice advecting through an idealized channel and through Nares Strait. The results indicate that the bonded DEM model is capable of capturing the behavior of sea ice over a wide range of spatial scales, as well as the dynamic sea ice patterns through constrictions (arching, lead formation).

The Southern Ocean plays a major role in the global air-sea carbon fluxes, with some estimates suggesting it takes up 40% of the total anthropogenic carbon dioxide. Understanding the Southern Ocean overturning transport is particularly important because the overturning transport fluxes tracers between the depth and the surface. Recent work shows that this vertical transport preferentially occurs downstream of bottom topography, but there is further work to understand how this relates to the theory of overturning circulation. This study uses an idealized Southern Ocean-like MITgcm channel and particle tracking in the thickness-weighted circulation to develop a new understanding of the three dimensional-nature of the overturning. This study evaluates the overturning transport by splitting the flow into three main driving forces behind the transport. First, is a wind-driven Ekman transport which is spread out throughout the domain and only leading order in the upper overturning cell, although not entirely zonally-symmetric due to the meandering nature of the flow. The remaining two components are standing eddies and transient eddies both of which are localized near the topography. The existence of the ridge weakens the response of the overturning to changes in wind, especially in the lower cell. The localization of the vertical flow shows the necessity of careful modeling of these specific regions in the Southern Ocean to understand the transport and carbon export.

The seasonal variability of the Azores Current energy transfers is studied using the output from a regional ocean model of the Eastern Central North Atlantic, forced by climatological surface fluxes and open ocean boundary conditions. The results show a stable Azores Current with baroclinic energy transfers supporting the current's energetics. Inverse barotropic energy transfers that feed the mean flow are several orders of magnitude smaller but this mechanism is active all year due to the Reynolds Stress convergence. These results support the findings of a stable Azores Current all year round.

The Pacific Arctic region is characterized by seasonal sea-ice, the spatial extent and duration of which varies considerably. In this region, diatoms are the dominant phytoplankton group during spring and summer. To facilitate survival during periods that are less favorable for growth, many diatom species produce resting stages that settle to the seafloor and can serve as a potential inoculum for subsequent blooms. Since diatom assemblage composition is closely related to sea-ice dynamics, detailed studies of biophysical interactions are fundamental to understanding the lower trophic levels of ecosystems in the Pacific Arctic. One way to explore this relationship is by comparing the distribution and abundance of diatom resting stages with patterns of sea-ice coverage. In this study, we quantified viable diatom resting stages in sediments collected during summer and autumn 2018 and explored their relationship to sea-ice extent during the previous winter and spring. Diatom assemblages were clearly dependent on the variable timing of the sea-ice retreat and accompanying light conditions. In areas where sea-ice retreated earlier, open-water species such as Chaetoceros spp. and Thalassiosira spp. were abundant. In contrast, proportional abundances of Attheya spp. and pennate diatom species that are commonly observed in sea-ice were higher in areas where diatoms experienced higher light levels and longer day length in/under the sea-ice. This study demonstrates that sea-ice dynamics are an important determinant of diatom species composition and distribution in the Pacific Arctic region.

Wind driven circulation in the North Sea is revisited with a specific focus on locally modified winds and their impacts. We show for the first time that local extrema of the wind stress curl (WSC), generated by orography and ocean-atmosphere interactions, help regulate circulation in the northern North Sea. While calculated transports are strongly coupled with wind stress, which itself is driven by large-scale forcing, transports through the Norwegian Trench are more strongly correlated with the WSC field due to local extrema. Such WSC extrema regulates the sub-mesoscale eddy activity around the Norwegian Trench. We conclude that local modification of the WSC is a result of both orography and ocean-atmosphere interaction along the frontal Norwegian coastline. Ocean-atmosphere interaction is considered a potential mechanism developing the WSC extrema. Our results show that local winds are more important than previously documented, with important implications for regional circulation likely to result from future changes to local surface gradients, such as may arise from changing meteorological or hydro-climatic forcing. These additional impacts on North Sea circulation that may not be accountable from changes in wind stress alone.

Biological productivity in the ocean directly influences the partitioning of carbon between the atmosphere and ocean interior. Through this carbon cycle feedback, changing ocean productivity has long been hypothesized as a key pathway for modulating past atmospheric carbon dioxide levels and hence global climate. Because phytoplankton preferentially assimilate the light isotopes of carbon and the major nutrients nitrate and silicic acid, stable isotopes of carbon (C), nitrogen (N), and silicon (Si) in seawater and marine sediments can inform on ocean carbon and nutrient cycling, and by extension the relationship with biological productivity and global climate. Here we compile water column C, N, and Si stable isotopes from GEOTRACES-era data in four key ocean regions to review geochemical proxies of oceanic carbon and nutrient cycling based on the C, N, and Si isotopic composition of marine sediments. External sources and sinks as well as internal cycling (including assimilation, particulate matter export, and regeneration) are discussed as likely drivers of observed C, N, and Si isotope distributions in the ocean. The potential for C, N, and Si isotope measurements in sedimentary archives to record aspects of past ocean C and nutrient cycling is evaluated, along with key uncertainties and limitations associated with each proxy. Constraints on ocean C and nutrient cycling during late Quaternary glacial-interglacial cycles and over the Cenozoic are examined. This review highlights opportunities for future research using multielement stable isotope proxy applications and emphasizes the importance of such applications to reconstructing past changes in the oceans and climate system.

The seasonal pattern of the eastward jet through the Tsugaru Strait between 2014 and 2019 was investigated using surface velocity data obtained from high-frequency radar located in the eastern part of the strait. The vorticity-front-model was used to estimate the volume transport of low-vorticity water and the intensity of the vorticity gap at the front using the climatological mean zonal velocity distribution. The flow mode at the outlet was then defined as either the summer/autumn “gyre mode” or winter/spring “coastal mode”. The distribution of the parameters was consistent with the theoretical understanding, showing that in addition to the volume transport, an increase in the vorticity gap can also contribute to the development of the gyre. The results also suggest an impact from the jet in the strait on the coastal flow along the coast of Japan.

In coral reef studies, mass spectrometry methods are widely applied to determine geochemical proxies in corals as a tool to evaluate seawater changes. As the coral grows, its skeleton forms annual bands similar to the growth rings found in trees. The density of the calcium carbonate skeletons changes as the water temperature, light, and nutrient conditions change. The elements stored within these bands can provide insight into the changing conditions of seawater over the entire lifetime of the coral, and serve as useful environmental records. Corals incorporate trace elements that can be precisely measured using high-resolution techniques, such as Laser Ablation-Inductively Coupled Plasma-Mass Spectrometry (LA-ICP-MS). This analytical tool offers high levels of precision to determine the distribution of trace elements along the annual bands of coral skeletons. This approach can serve to monitor fixed-point time-series for water quality research, as well as large-scale observations in ocean science. Ultimately, this procedure can be applied to reconstruct past climate oscillation episodes and/or to quantify the impacts of marine pollution on coral reefs. The benefits of techno-scientific aspects of new and established mass spectrometry applications in coral reef research hold great promise that may continue to be improved in future studies. Given the current climate crisis, this issue requires accurate measurements to increase our understanding on the impacts that have become more frequent and intense.