The ocean is an important sink for anthropogenic carbon, its size providing a vital constraint on the global carbon budget. Climate projections also depend on accurate modeling of the ocean carbon sink. However, estimates of the sink from data products based on surface ocean observations differ significantly from the results of global biogeochemical models (GOBMs), with the former suggesting more decadal variability over the observational period and a steeper uptake trend since around the year 2002. We present an alternative method for diagnosing the ocean carbon sink and characterizing transport and mixing of carbon in the ocean interior, using observational data. Our method combines a machine learning reconstruction of ocean interior carbon with an optimal transformation method (OTM) that uses a water mass framework to simultaneously close budgets of heat, freshwater and carbon. Focusing on two decades, we find a global sink of 2.03±0.22PgCyr-1 for 1993-2002 and 2.86±0.25PgCyr-1 for 2003-2012. The trend of 0.83±0.5PgCyr-1 is 75% larger compared to the data products (although within uncertainties), and nearly quadruples that suggested by the GOBMs, and is driven mainly by the North Pacific (>10N) and Southern Ocean (>35S) basins. The transport and mixing diagnosed by the OTM suggests an intensification of carbon uptake during Southern Ocean mode and intermediate water formation and a reduction in uptake during North Atlantic Deep Water formation have contributed to a southwards redistribution of carbon in the Atlantic. Over the same period, ocean transport and mixing acted to redistribute carbon from south to north in the Indo-Pacific.

Internal tides are generated in the stratified ocean interior by the interaction of barotropic tidal currents with rough bathymetry. Low-vertical-mode internal tides can transport energy thousands of kilometres from their generation site, and how and where they eventually lose this energy to turbulent dissipation and mixing is of importance to the oceanic energy budget. A potential mechanism for the transfer of energy from the low-mode internal tide to smaller scales is superharmonic generation, whereby internal tides in equatorial regions and non-uniform stratification excite waves with shorter wavelengths and higher frequencies. Here, we use a realistic global ocean model to investigate an enhanced superharmonic tidal signal in the equatorial Pacific Ocean. Using existing theory, we demonstrate that the superharmonic amplitude is consistent with nonlinear self-interaction of the original 'parent' baroclinic tide, providing strong evidence for an energy pathway from the mode-1 M2 internal tide to smaller horizontal scales and higher frequencies.

Finite fault models using satellite radar interferometry data indicate that the Mw 6.4 Puerto Rico earthquake occurred on a N-dipping fault. Focal mechanism solutions of aftershocks show three trends of strike-slip faults including two parallel WNW-ESE left-lateral faults. The parallel strike-slip faults bound a left-stepping pull-apart basin which localizes the most concentrated area of the swarm.

A document by Kostas Leptokaropoulos. Click on the document to view its contents.

Shifts in the phytoplankton assemblage induced by environmental changes have significant implications for carbon cycling and marine food webs, but remain poorly constrained across spatiotemporal scales. Here, we investigate the effects of rising sea surface temperatures and increased stratification on the phytoplankton composition and size in Northwestern Mediterranean Sea (2010-2019) using two sediment trap series: one in the oligotrophic Ligurian Sea and the other in the deep convection zone of the Gulf of Lion. We apply deep-learning image analysis to quantify phytoplankton particle fluxes, size distributions, and relative assemblages, focusing on coccolithophores, diatoms, and silicoflagellates. Our results show a general decline of phytoplankton fluxes to the seafloor, mirroring the decrease in vertical mixing in the water column. Both sites show a shift towards phytoplankton species adapted to stratified and nutrient-depleted conditions, although with contrasting patterns. In the Ligurian Sea, deep-dwelling coccolithophore species become dominant, while in the Gulf of Lion, summer-associated siliceous species, including large diatoms and silicoflagellates, show an increase. These contrasted trends, which likely result from differences in nutrient inputs and pH changes in the surface between the two sites, have implications for the efficiency of carbon export pathways at depth. Specifically, the increasing dominance of smaller phytoplankton in the Ligurian Sea leads to a reduction in carbon burial efficiency, while in the Gulf of Lion, the enhanced contribution of larger diatoms may sustain relatively higher export and burial rates in the future.

Paleomagnetic data are usually retrieved by subjecting bulk samples, e.g. lavas, to laboratory measurement protocols. In many instances, these protocols yield uninterpretable results caused by the presence of particles with adverse magnetic properties that blur the signal of the reliable magnetic particles. With Micromagnetic Tomography (MMT) we focus on identifying the signal of particles with reliable properties. Their individual magnetic moments are computed by scanning the surface of a ~3 mm2 thin section with a quantum diamond microscope (QDM) and locating the magnetic recorders with computed tomography. Currently, almost 80% of all resolved magnetic moments is discarded due to numerical instability, making it difficult to obtain statistically relevant paleointensities and paleodirections based on the remaining magnetic moments. We improve the number of reliable magnetic moments from MMT experiments by making a QDM scan of both sides of the sample. Here, we conduct a combined numerical and empirical study to investigate the benefits and difficulties of adding this double-sided scanning (DSS) protocol to MMT. By investigating the theoretical gain of DSS for varying sample thicknesses, we show that DSS returns three times more numerically stable magnetic moments compared to single sided scanning for a sample thickness of 50 μm. However, careful sample preparation and handling is required: best results are obtained when both sample surfaces are measured as parallel as possible, while keeping the sample intact when flipping it to the other side for the bottom measurement. By overcoming these difficulties, DSS will provide a significant boost in stable magnetic moments.

Accurately predicting tropical cyclone (TC) activities is important for both hazard mitigation and adaptation. However, the number of TC genesis simulated by numerical models is sensitive to the model's horizontal resolution and how convection is being represented. A super-parameterized (SP) general circulation model (GCM), in which convection and sub-grid processes are explicitly simulated using a cloud-resolving microscale model embedded in each GCM grid column, but in a 2-D configuration, can achieve an explicit representation of convective processes while maintaining an acceptable computational cost. Here, we compared TC genesis using the traditionally convective parametrized Community Atmosphere Model v5.0 (using Zhang and McFarlane (1995) deep convective scheme and the University of Washington shallow convective scheme, hereafter referred to as CPCAM) with the SP CAM v5.0 (SPCAM); in particular, aquaplanet experiments with zonally symmetric sea surface temperature and perpetual summer insolation were conducted using the two models. It was found that SPCAM TC genesis was 3-4 times greater than that in CPCAM. Storm’s wind-pressure relationship was also improved, and they were stronger in SPCAM. Additionally, more “non-rotating convective clusters” and “TC seeds” were found in SPCAM compared to CPCAM. More frequent TC genesis in SPCAM was primarily related to weaker vertical wind shear (VWS) and secondarily to stronger 850-hPa absolute vorticity. Reduced VWS in the SPCAM was related to a weaker Hadley cell owing to less southern hemisphere subtropical low cloud and hence shortwave reflection. A wider and more northward ITCZ in SPCAM caused an increase in absolute vorticity, promoting TC genesis. There were also, stronger convective coupled equatorial wave activities in SPCAM than in CPCAM; better-simulated ER-waves appeared to induce a higher number of TC genesis events in the SPCAM environment. In the future, more sophisticated multiscale modelling frameworks can be employed to improve the simulation of extreme events in relation to the large-scale environment, while achieving better computational efficiency.

Arizona State University, Earth Genome, and USACE' Engineer Research and Development Center has been working together under a Network for Engineering With Nature project to develop a Web Application tool for regional screening of Managed Aquifer Recharge (MAR) Projects. The objective of the project is to provide relative, regional indices for appropriate siting of MAR, which would be an innovative approach to flood management and restore hydrological and ecological processes linked to aquifer recharge. Developing a rigorous decision-making framework includes physical characteristics such as surface water runoff, connection with groundwater aquifers; as well as social considerations, such as land use, engaging stakeholders in floodplain management, and distribution of risks and benefits. A suite of analyses, from CONUS-wide Machine Learning for groundwater attributes and statistical estimation of flood volumes to surveys about perceptions of MAR were implemented to inform development of a decision support tool and supplemental guidance in an effort to increase the accessibility of this innovative flood management approach to floodplain managers. This research is funded by the Engineering With Nature ® and Network for Engineering With Nature® programs. https://ewn.erdc.dren.mil/

Effusive volcanic eruptions have been common in Iceland throughout the Holocene with the largest ones happening prior to the industrial revolution. Such eruptions can affect climate through the formation of sulfate aerosols and subsequent impacts on clouds. As different atmospheric conditions modulate the cloud and climate responses to aerosol perturbations, a pre-industrial effusive eruption might have different climate impacts were it to happen today or in the future. Here we use an Earth system model to simulate the surface climate response to Icelandic effusive volcanic eruptions under pre-industrial, present day, and end of the 21st century climate conditions. For the last case, high anthropogenic greenhouse gas and aerosol emissions are assumed. We find that the climate state significantly modulates the climate response, especially in the Arctic where we model amplified surface warming during winter under pre-industrial conditions and stronger surface cooling during summer in warmer climates.

Tropical cloud fractions from combined CALIPSO and CloudSat observations are classified based on a K-means cluster analysis. These satellite instruments together retrieve detailed vertical structure of clouds, allowing for an objective decomposition of tropical clouds into distinct regimes. The identified cloud regimes are overall robust except that an increasing number of redundant high-cloud clusters are produced as the specified number of clusters is increased. This redundancy arises because geometrically thin clouds with slightly different altitudes can be mathematically distant from one another in the clustering procedure despite their morphological similarity, suggesting that an excessive number of clusters only generate unrealistic subclasses of high clouds. Objective evaluation metrics indicates that the most appropriate number of clusters is four, where the clusters may be labeled as near clear-sky, low cloud, high cloud, and deep convective regimes. A five-cluster classification is also deemed as reasonable, where a fifth regime of congestus clouds joins the other four regimes practically equivalent to the four-cluster solution. This study suggests that determining the optimal clustering solutions requires a careful interpretation from meteorological perspectives beyond a mere statistical assessment of clustering performance.

Nutrient runoff from different land management practices stimulates the growth of cyanobacteria and algae in surface water bodies. Excessive growth of algae in inland and coastal surface water bodies that release microcystins and other harmful algal contaminants are known as Harmful Algal Blooms (HABs). Monitoring HABs is important because they can cause negative health impacts to humans and create water quality issues such as depletion of dissolved oxygen in surface water bodies. Moreover, the increase in agricultural, industrial, and sewage effluents combined with frequent summer storms transports nutrients into water bodies and subsequently cause HABs. Therefore, implementing unmanned systems in monitoring HABs is useful because it reduces human contact with contaminated water and increases the spatial and temporal resolution of data collection. Recently unmanned aerial vehicles (UAVs) were used in monitoring surface water bodies for HABs because they are economical and collect data with high spatial resolution. However, in-situ monitoring combined with remote sensing enables in comparison of the two monitoring methods and evaluate the efficacy of remote sensing techniques to monitor HABs. Currently, monitoring is being conducted for HABs at the Grand Lake O' The Cherokees, OK, and Marion reservoir, KS using an unmanned surface vehicle (USV). Using the unmanned monitoring system, the chlorophyll and phycocyanin concentrations were estimated, and gridded estimates were plotted. Finally, the high spatial resolution data of chlorophyll, phycocyanin, and other water quality parameters by monitoring helps in calibrating statistical models to forecast HABs at Grand Lake and Marion reservoir. Methods and Results.

A document by Shannon McClish. Click on the document to view its contents.

Among the most vulnerable regions to climate change are small islands and low-lying coastal areas, due to the risks associated with sea level rise, changing weather patterns and their impact on saltwater intrusion, storminess and coastal erosion. Engaging local communities in the analysis of their vulnerability to climate impacts and the identification of climate-resilient development pathways is increasingly seen as an approach that takes into account the complexities and challenges of climate change. To this end, local and indigenous knowledge are important sources of information for capturing future drivers of change not included in typical top-down approaches that often elicit expert knowledge to inform adaptation options. However, a conventional literature search indicates that less attention has been paid to 1) measuring research impact on decision making; 2) post-assessment monitoring, review and implementation; and 3) how critiques and limitations of theory and methods are addressed. To contribute to this debate, a meta-analysis of participatory approaches (PA) in community-level assessments of climate vulnerability and adaptation options is undertaken-specifically focusing on communities in small islands and low-lying coastal regions-alongside a review of the available evidence of the extent to which studies were designed to contribute to decision making ('usability of science'). The primary rationale for this review is to inform the methodological and conceptual thinking of a larger project seeking to develop a climate change vulnerability and adaptation assessment framework suited to integration, participation and collaboration in the context of rural island communities in Scotland.

We paired data collected on Cibicidoides spp. with data collected on O. umbonatus, L. wuellerstorfi, and N. umbonifera. We also paired data collected on O. umbonatus with data collected on Cibicidoides spp., L. wuellerstorfi, and N. umbonifera. (Fig. 3). Our results show: Lobatula wuellerstorfi and O. umbonatus element/Ca correlate well with those of Cibicidoides spp. for all elements analyzed. The correlation of Sr-Li-B/Ca bf between these species is the most statistically significant (P<0.05). Nuttallides umbonifera shows no statistically significant correlation with Cibicidoides spp. in any of the analyses. Additionally, the Mg-Li/Ca bf correlation between these two species presents the lowest R-squared of the regression (R 2 < 5%). This implies that the element incorporation in this species is substantially different in terms of its response to environmental variables. The correlation between O. umbonatus and Cibicidoides spp. is statistically significant for all the elements/Ca analyzed. The correlation between L. wuellerstorfi and O. umbonatus and between N. umbonifera and O. umbonatus are statistically significant only for B-Sr/Ca bf (P<0.05). The data collected allowed us to derive correction factors to normalize L. wuellerstorfi and O. umbonatus to Cibicidoides spp. and also to normalize data collected on Cibicidoides spp. to O. umbonatus. Here, we show data collected along our Miocene through Pleistocene paleodepth transect normalized to Cibicidoides spp. (Fig. 4). Our results show: Mg-Li-Sr/Ca bf record similar ratios before the Miocene Climate Optimum (MCO) at ~2400 m and ~3500 m. In contrast, B/Ca bf records a larger gradient across paleodepths, displaying the highest ratios at ~3500 m. Mg-Li-B-Sr/Ca bf ratios increase during the MCO. The element/Ca ratio gradient across ~2400 m and ~3500 m increases during and after the MCO, except for Li/Ca bf. Li/Ca bf ratios remain stable at ~2400 m and ~3500 m. After the MCO, Li/Ca bf at ~1200 m is ~17 µmol/mol higher than at ~3500 m at 11 Ma. B/Ca bf is lower at ~2400 m than at ~3500 m throughout the studied interval, except at 5.2 and 0.5 Ma. Mg-Li-B/Ca bf decrease starting from 5 Ma. In contrast to other elements, Sr/Ca bf increased slightly over the last 5 M.y. from 1.1 to 1.3 mmol/mol.

A document by Melanie J Frost. Click on the document to view its contents.

A document by Zach Ulibarri. Click on the document to view its contents.

A document by Sushel Unninayar. Click on the document to view its contents.

The transport and delivery of low-abundance, bioactive trace elements to the surface ocean by aerosol mineral dust is a major planetary control over marine primary production and hence the global carbon cycle. Variations in the concentration of atmospheric dust have established links to global climate over geologic timescales and to regional biogeographic shifts over seasonal timescales. Constraining atmospheric dust variability is thus of high value to understanding oceanographic systems, especially vast, constitutively low-nutrient subtropical gyre ecosystems and high-nutrient/low-chlorophyll ecosystems where availability of the trace element iron is a dominant ecological control. Here we leverage the MERRA-2 reanalysis product to examine over four decades of surface-level atmospheric mineral dust concentrations in a domain of the subtropical North Pacific centered at ocean Station ALOHA. This study region has been sampled regularly since the mid-1980s and was the site of the Hawaii Aerosol Time-Series (HATS) project in 2022-2023. Two unequal semi-annual periods of elevated dust are evident in the long-term data are described and constrained. We look for evidence of shifts in total and seasonal atmospheric dust abundances and in the timing of the onset of the dominant spring/summer dusty period, finding year-to-year variations but little evidence for long-term trends. We observe significant but complex relationships between the Pacific Decadal Oscillation (PDO) index and both dust and precipitation. The data show that 2022 was among the dustiest years for the study domain in the preceding two decades and, by contrast, that 2023 exhibited a significant early-spring lull in dust.