bluuebunny/crossref_metadata_2025 huggingface dataset:
Temporal and plant-structural constraints for eco-evolutionary optimality models
Authors: Rebel Karin , Odé Astrid , Lankhorst Jan , de Boer Hugo
Published: March 2024

Quantifying leaf transpiration and photosynthesis is crucial for modeling global vegetation in a changing climate, but deriving general relationships and responses to environmental drivers across time scales remains challenging. A promising new approach to predict general leaf trait responses is the P-model (Prentice et al., 2014), which is based on eco-evolutionary optimality (EEO) theory. Leaf-level optimality is defined as the optimal ratio of leaf internal CO2 partial pressure to ambient CO2 partial pressure, resulting in maximum assimilation while minimizing respiration and transpiration costs. This process is coordinated via changes in both stomatal conductance and photosynthetic biochemistry, and results in a fundamental model with a strong dependency on climatic variables including temperature, relative humidity, CO2 levels, and light quantity. The P-model currently predicts instantaneous changes in leaf-level traits of photosynthesis and gas exchange without explicitly considering timescales of adaptation and acclimation, and the associated ranges of phenotypic plasticity of individual plants. It is also limited/confined to leaf-level traits, without considering whole-plant processes, like resource allocation. Thus, it is uncertain how leaf-level optimality and their related costs translate to organ level carbon and nitrogen allocation.Our work focuses on further developing and evaluating the P-model by incorporating time scales of acclimation and adaptation, as well as upscaling leaf-level traits to whole-plant traits. To achieve these aims, we first developed a theoretical framework which allows the distinction of different timescales. Using a literature review, we identified and highlighted the tight relationship between leaf traits across timescales, and we also identified constraints on key leaf-level EEO optimality traits, and the timescales at which these constraints occur. We then propose a new framework to separate these responses at physiological, developmental, and evolutionary timescales. Second, we performed experimental work in order to evaluate the link between leaf-level optimality and whole-plant acclimation. Our experiments showed a strong response in whole-plant resource allocation to nutrient availability while leaf-level optimality was unresponsive to the nutrient treatments. This indicates that while leaf-level optimality is regulated mainly by climatic variables, whole-plant performance is strongly influenced by below-ground resource availability. This research is a way forward in bridging plant ecophysiology and vegetation modeling, while acknowledging timescales and plasticity ranging from meteorology to deep time climate research. This work can be used to further develop EEO-modeling, and specifically the P-model.
Sulfuric acid speleogenetic by-products and secondary minerals in caves of the Mulapampa travertines (Western Cordillera, Andes, Peru)
Authors: Tyc Andrzej , Ciesielczuk Justyna , Gaidzik Krzysztof , Powolny Tomasz
Published: March 2024

Sulfuric acid speleogenesis (SAS) is a general cave formation process in carbonate rocks in the presence of sulfuric acid. Such caves are mainly formed at and above the water table by abiotic or/and biotic oxidation of hydrogen sulfide (H2S). One possible source of H2S may be volcanic activity. The oxidation of H2S produces sulfuric acid that immediately reacts with carbonate host rock, producing replacement gypsum and CO2.The Western Cordillera in the Peruvian Andes, characterized by volcanic and tectonic activity, features substantial travertine deposits. Among the most interesting and, at the same time, less known are the Mulapampa travertines located in the vicinity of the active Ampato-Sabancaya Volcanic Complex (ASVC). There are numerous collapse sinkholes in the travertine cover, and within three of them, caves have been found. discovered in three of them. Particularly interesting is the Gruta con lago cave, the bottom of which is located at the level of the current water table (ca. 40 m below ground level). It does not have the characteristic morphology of active SAS caves, but several speleogenetic by-products – mainly thick gypsum deposits – are typical of such features.Mineralogical studies of sediment samples from the lake at the bottom of Gruta con lago corroborated the sulfuric acid genesis of the cave. Native sulfur was detected in those samples, among others. Microscopic examination of native sulfur crystals reveals traces of substantial corrosion attributable to the activity of sulfur bacteria. In the same cave lake's bottom sediments, framboidal pyrites formed inside the biofilms (presumably of sulfate-reducing bacteria) were found. Common secondary minerals in SAS caves, such as barite or celestine, are present on the cave bottom and walls.This research was funded by the National Science Centre (Poland), grant No 2020/39/B/ST10/00042, and the Institute of Earth Sciences, University of Silesia, Poland.
Hydrogen in orthopyroxene records oxidation during hydration of the cold mantle wedge
Authors: Ramón-Fernández María , Padrón-Navarta José Alberto , Boudier Françoise , Garrido Carlos J.
Published: March 2024

The mechanisms influencing the oxidation state of arc magmas and their correlation with high volatile content remain highly debated. It has been suggested that the incorporation of hydrogen into Nominally Anhydrous Minerals (NAMs), particularly pyroxenes, in the mantle wedge may play a significant role in the oxidation of arc magmas in subduction zones [1]. To assess this potential link, samples from two contrasting settings were analyzed using infrared spectroscopy (FTIR): [i] ultramafic xenoliths from the Colorado Plateau (CP, USA), representing a unique direct sampling of the cold part of the mantle wedge (< 800ºC), and [ii] reference samples from the Kilbourne Hole (New Mexico), and San Quintín volcanic field (Mexico) which were not directly affected by the fluids responsible for the hydration of xenoliths from CP. CP samples exhibit significant lithological variability, ranging from Opx-poor harzburgites to lherzolites and pyroxenites, with hydration levels varying from nominally dry and devoid of hydrated minerals to chlorite-rich samples  (occasionally antigorite), and to a lesser extent, bearing amphibole and Ti-clinohumite. The extent of hydration nicely correlates with the transition from spinel to magnetite. Hydrogen content hosted in NAMs ishigher and more variable in samples from the CP  cold hydrated mantle wedge (Ol: 4-32 and Opx: 146-685 ppm wt% H2O) compared to other localities  (Ol: 0-4 and Opx: 24-209 ppm wt% H2O). Notably, absorption bands exhibit distinct signatures for the two sample groups. Olivines from other localities  display bands related to Ti-defect complexes, while CP olivines also present bands related to Si- and Mg-vacancies. Interestingly, CP orthopyroxene shows distinctive bands (3544, 3520, 3325, and 3060 cm-1) previously observed at relatively high oxygen fugacities [1] consistent with the presence of magnetite in these samples. These bands are absent in samples outside CP. These observations suggest that NAMs can serve as sensors of redox processes occurring during the hydration of the cold mantle wedge and that fluids derived from the slabs have sufficiently oxidizing capacity to significantly alter its redox budget [2].[1] Tollan & Hermann, Nat. Geosci. 12, 667–671 (2019). [2] Evans. Geology 34, 489–492 (2006).Research funded by RUSTED project PID2022-136471N-B-C21 & C22 funded by MICIN/AEI/10.13039/501100011033 
Application of numerical integration and CUDA parallel in the calculation of ocean gravity gradient
Authors: Ye Zhourun , Bu Jingyu , Sneeuw Nico
Published: March 2024

Through Stokes kernel function and gravity anomaly, it is possible to calculate the gravity gradient disturbance on the geoid and its external space. For this Stokes’ integral expression, we apply Laguerre wavelet numerical integration to improve the accuracy of its computational results. Meanwhile, compute unified device architecture (CUDA) is used to implement parallel computing on the Graphic Processing Unit (GPU) for speeding up. The full tensors of gravity gradient in the experimental ocean area with 3°×2°are computed. Compared to serial computing, its computing acceleration ratio can be more than 10 times faster. The results of the vertical gravity gradient are compared and validated from the public model from the University of California San Diego.
A Cold Frontal Life Cycle Climatology and Front-Cyclone Relationships over the North Atlantic and Europe during Winter
Authors: Lichtenegger Tobias , Schaffer Armin , Maraun Douglas , Osso Castillon Albert , Truhetz Heimo
Published: March 2024

Atmospheric fronts and cyclones play an important role in day-to-day weather variability, especially in the mid-latitudes and during the winter season. Severe rainfall and windstorm events are often associated with the passage of a front or a cyclone. While there are many studies of individual fronts and climatologies based on objectively detected fronts, there is no comprehensive study considering the whole frontal life cycle over time. Therefore, a front and cyclone tracking algorithm, based on overlapping features at consecutive time steps, is used together with an improved front detection method to detect and track cold fronts and cyclones over the North Atlantic and Europe in the extended winter season (October - March) in the ERA5 reanalysis dataset. Several life cycle characteristics, e.g. the duration, velocity, frontogenesis and -lysis regions as well as dynamic and thermodynamic frontal parameters are defined to investigate the frontal life cycle and the conditions and processes in the frontal region. Fronts are linked to their parent cyclone to study relationships between frontal and cyclonic properties. The study confirms that fronts are mostly formed over the western and central North Atlantic and travelling along the main storm track into the European continent. During positive phases of the North Atlantic Oscillation, fronts are travelling faster and further and are associated with stronger precipitation and surface wind speeds over their whole life cycle. Stronger cyclones are related to stronger dynamics in the frontal region.
Global 1D river bathymetry estimation from remotely sensed observations
Authors: Rezende de Oliveira Silva Isadora , Malaterre Pierre-Olivier , Fatras Christophe , Oubanas Hind , Gejadze Igor , Peña-Luque Santiago
Published: March 2024

Flooding has major economic, social, and environmental implications. Its modeling provides insights into potential risks and contributes to the protection of lives, natural resources, and infrastructure. In ﬂood hazard assessment, the topography representation is a key factor as it dictates the water extent resulting from the simulations. In particular, for small and medium flood scenarios, it is imperative to have good knowledge of the modeled in-channel water height, especially for the river's bank full discharge. As these constitute the majority of flood events, the risk assessment is severely impacted by the quality of their estimates. However, the determination of the water profile can be a challenging task in data-sparse areas, as the bathymetry of the river channels is not well described in open-access digital elevation models (DEMs). Using the global coverage of remote sensing derived water levels and extents, this study builds towards a global estimation of river bathymetry. The methodology to achieve this can be divided into two parts, the correction of the river topography that can be directly observed by the sensors, above a minimum water level (the dry bathymetry), and the estimate of the part under the minimum observed water line (wet bathymetry). For the improvement of the dry bathymetry, the contours from water masks derived by optical sensors are projected in DEMs and a smooth profile is built from upstream to downstream. The wet bathymetry is calculated using hydraulic simulation and inverse problem methodologies. It requires as inputs the corrected dry bathymetry, observed water surface elevation and slope, and a prior discharge. The algorithm computes the flow using an integrated version of a modified Manning–Strickler’s equation and probability from beta distribution. It computes the roughness and the bottom depth of the section assuming a rectangular shape. Preliminary results are promising; a good agreement with in-situ discharge was achieved for the Po River (NSE > 0.8). It shows the potential and importance of accurate estimates of the river bathymetry for future flood monitoring and forecast.
Building useful datasets for Earth System Model output
Authors: Kölling Tobias , Kluft Lukas
Published: March 2024

Global kilometer-scale climate models generate vast quantities of simulation output, presenting significant challenges in using this wealth of data effectively. We approach this challenge from the output user perspective, craft useful dataset requirements and show how this also simplifies data handling and reduces the “time to plot”.At first, this strategy involves the creation of a consolidated and analysis-ready n-dimensional dataset, directly from the running model. A dataset forms a consistent set of data, which as a whole aims to inform a user about what and what not to expect from the output of a given model run. This is notably distinct from multiple independent datasets or messages, which can’t convey the overall structure and are often (slightly, but annoyingly) inconsistent. Thus, the amount of user surprise can be reduced by reducing the number of output datasets of a model run towards 1. This of course requires synthesizing relevant information from diverse model outputs, but in turn streamlines the accessibility and usability of climate simulation data.With the goal of the user-perspective of a single large dataset established, we need to ensure that access to this dataset is swift and ergonomic. At the kilometer-scale, horizontal grids of global models outgrow the size of computer screens and the capacity of the human eye, changing viable dataset usage patterns: we can either observe a coarser version of the data globally or high resolution data locally, but not both. We make use of two concepts to cope with this fact: output hierarches and multidimensional chunking.By accumulating data in both temporal and spatial dimensions, while keeping the dataset structure, users can seemlessly switch between resolutions, reducing the computational burden during post-processing at the large scale perspective. In addition, splitting high-resolution data in compact spatiotemporal chunks, regional subsets can be extracted quickly as well. While adding the hierarchy adds a small amount of extra data to already tight disk space quotas, a good chunk design and state-of-the-art compression techniques reduce storage requirements without adding access time overhead. On top, the approach generates an opportunity for hierarchical storage systems: only those regions and resoultions which are actively worked on have to reside in “hot” storage.In summary, our collaborative efforts bring together diverse existing strategies to revolutionize the output and post-processing landscape of global kilometer-scale climate models. By creating a single analysis-ready dataset, pre-computing hierarchies, employing spatial chunking, and utilizing advanced compression techniques, we aim to address challenges associated with managing and extracting meaningful insights from these vast simulations. This innovative approach enhances the efficiency of many real-life applications, which is a necessity for analysing multi-decadal kilometer-scale model output.
Crystallographic preferred orientation of clay minerals in sediments from the Hikurangi accretionary prism offshore New Zealand
Authors: Kühn Rebecca , Kilian Rüdiger , Stipp Michael
Published: March 2024

The shortening of sediments in accretionary prisms is accomplished by localized faulting as well as non-localized deformation. While faulting is often easily recognized from seismic sections, accessing the amount and extent of non-localized deformation is rather challenging. In order to address this challenge, we explore samples from the active accretionary prism offshore Gisbourne, NZ at the Hikurangi margin which contains accreted sediments of Pliocene to recent age. Drilling at Site U1318F of IODP Expedition 375 recovered non- to semi-lithified sediments from a major accretionary fault, the Papaku Fault, including its hanging wall and footwall. The crystallographic preferred orientation (CPO) of the clay minerals is a measure for their alignment and was determined in 66 sediment samples from the drill core (250-500 mbsf) using high energy X-rays. The results show that the CPO strength of the clay mineral basal planes (00l) is in general weak and no depth-related trend can be observed. In the hanging wall of the Papaku Fault, (00l) pole figures have non-rotationally symmetric, unimodal density distributions displaying incomplete girdles. In the footwall, most (00l) pole figures exhibit unimodal, rotationally symmetric to weak girdle density distributions, with most maxima pointing parallel or subparallel to the drill core axis. Fault zone samples also exhibit rotationally symmetric, unimodal (00l) distributions, with maxima perpendicular to the fault plane.We assume that pre-shortening and pre-faulting, sediments had a weak initial CPO related to sedimentation and compaction with a rotationally symmetric, unimodal (00l) distribution. The girdle shape of the distribution in the hangingwall and to a minor extent in the footwall is introduced by non-localized deformation which results in grain-scale folding. Accordingly, diffuse shortening was larger in the present-day hanging wall than in the present-day footwall. Furthermore, we interpret the CPO in the Papaku fault itself to be a result of sediment shearing, overprinting any pre-existing CPO. The position of the Papaku fault is compatible with fault initiation where diffuse shortening was unable to propagate sufficiently towards the foreland.While our results also confirm existing tectonic models from this part of the Hikurangi margin, more importantly they demonstrate implications for strain distribution in fault and thrust systems as well as the usefulness of clay mineral CPO for unravelling deformation and tectonic processes in accretionary prism sediments.
New perspectives on crustal imagery leveraging offshore submarine fiber optic cables
Authors: Rivet Diane , Guerin Gauthier , Vernet Clara , Trabattoni Alister , Baillet Marie
Published: March 2024

Distributed acoustic sensing transforms fiber-optic cables into giant and very dense seismic networks. Although less sensitive to ground motion than traditional networks, they offer new possibilities for passive imaging and temporal monitoring, especially in hardly accessible locations such as the seafloor. From two case studies - in South of France, on a 42km long cable off-shore Toulon and in Central Chile on the northern leg of the Concón landing site of the GTD telecom cable - we explore the capability to perform passive imagery using ambient seismic noise and coda waves.Despite a higher instrumental noise level and uneven ground coupling, underwater telecom cables can record the microseismic noise. This may be strong microseismic noise generated locally, or microseismic noise amplified by the resonance of the water column. The recorded microseismic noise at the seafloor allows a better understanding of its generation and provides high resolution images of shallow crustal structures.From the observation of ocean gravity waves and microseismic noise, we highlight the strong localization of seismic noise sources near the coast, which can be highly variable over short time scales.  Due to the localized nature of the noise sources, and because it is not always possible to average the noise recorded over long periods of time (months, years), conventional methods for ambient noise imagery show significant discrepancies in velocity estimates, up to 30%, especially at greater depths. We present here a method that minimizes the errors due to highly localized sources by carefully correcting the apparent velocities from the azimuth of the sources.In seismic areas, in addition to microseismic noise, it is possible to expand the frequency content toward higher frequencies using seismic coda. Coda waves are dominated by multi-diffracted surface waves on local heterogeneities. The spatial distribution of their energy is more isotropic. Using dispersion curves stacked over the coda of several earthquakes, we image the shallow crustal structure of the sediments. This innovative approach opens up new horizons for structural imaging and monitoring.In coastal environments, the distribution of noise sources must be systematically studied in order to obtain reliable results.
Seismic Investigation of the Ojos del Salado Volcano, Chile: The Highest Altitude Volcano in the World
Authors: Murray-Bergquist Louisa , Garcia Pina Ayon , Thorwart Martin , Ulloa Christopher , van Ginkel Janneke , van Huisstede Lisanne , Wessels Richard , Beniest Anouk
Published: March 2024

The Ojos del Salado Volcano in Chile is the highest altitude volcano in the world, but has not been visibly active since 1993, when steam was observed rising from near the summit. Since then the volcano has been considered dormant, however, it is unclear if it could become active again, and if so, what the ramifications would be. Little is known about the size and structure of the magma chamber, or its potential interaction with hydrothermal fluids and whether this is the heat source of the nearby hydrothermal lake, Laguna Verde.The region surrounding the volcano is very arid, but due to the cold climate at such high-altitude there are some remnant glaciers and permafrost from the last glacial maximum. Summer meltwater from these cryosphere features contributes to the water budget of the valley below, which adds to the importance of understanding the extent of remaining permafrost and the interactions between local volcanism and the cryosphere that could increase the rate of melting.In this study we combine InSAR data with local seismicity to investigate local crustal deformation and seismic activity at the Ojos del Salado Volcano. A small seismic array, deployed in 2022, measured seismicity in the vicinity of the volcano and acted as a pilot for the 2024 campaign and network design. A dense network of geophones was deployed on the volcano’s flanks in early 2024. We present the first results of the analysis of the data from this denser network, and the pilot study, which already showed seismicity in the vicinity of the volcano. From this analysis we gain insight into the level of activity of the Ojos del Salado Volcano, local deformation patterns and the style of faulting which is also an indication of potential fluid pathways that could link the volcano to the hydrothermal lake. With this information we can better understand the interaction between this unique volcano and the local cryosphere.
Exploring Pretrained Transformers for Ocean State Forecasting
Authors: Cremer Clemens , Anderson Henrik , Mariegaard Jesper
Published: March 2024

Traditional physics-based numerical models have served and are serving as reliable tools to gain insights into spatiotemporal behavior of ocean states such as water levels and currents. However, they have significant computational demand that often translates to slower forecasting capabilities. Additionally, these models can encounter difficulties in capturing certain physical processes and struggle to effectively bridge various spatial and temporal scales.Considering these challenges, machine learning-based surrogate models emerge as a promising alternative. Physical surrogate models that learn multiple physics (on different spatial and temporal scales) from large datasets during extensive pretraining (Multiple physics pretraining, MPP) can enable later applications to poorly observed data domains which are common in ocean sciences. Hence, transfer learning capabilities can help improve the oceanographic forecasting, especially in data-limited regimes.In this work, we explore the capabilities of pretrained transformer models for prediction on a test case for the North Sea. The results from two-dimensional simulations are used for training and fine-tuning. We utilize 2D datasets from publicly available PDEBench together with domain-specific datasets from DHI’s historical records of simulated 2D metocean data. We forecast water levels and currents with pretrained models and evaluate MPP forecast results against in-situ point observations and numerical model results.Initial findings suggest that pretraining poses potential for generalizing and transferring knowledge to novel regions and relevance in practical application. A challenge is posed by model interpretability, highlighting an area for further development.
The effect of anaerobic remineralization of the seagrass Halophila stipulacea on porewater biogeochemistry in the Gulf of Aqaba
Authors: Antler Gilad , Neta Soto , Winters Gidon
Published: March 2024

Seagrasses are marine flowering plants that play an important role in mitigating climate change by carbon sequestration. While only covering 0.2% of the ocean floor, seagrasses store over 15% of accumulated global carbon in the ocean’s sediments. The oxidizing microenvironments around their roots create strong and complex redox gradients which greatly affect microbial carbon mineralization rates in marine sediments. Despite seagrasses’ enormous ecological services as habitat and climate regulators, they are rapidly degrading around the world at alarming rates. Therefore, understanding the chemical changes and feedback that occur in sediments following the disappearance of seagrasses holds ecological importance.We incubated different compartments of the tropical seagrass Halophila stipulacea (old and young leaves, rhizomes, or roots) with two sediment types from the northern tip of the Gulf of Aqaba. We measured the chemical changes in major ions (DIC, Fe2+, H2S, SO42-) and sulfur isotope ratios in sulfate within the water. We used these measurements to calculate the remineralization rate of each seagrass compartment. Our results aid us in predicting the potential effects of H. stipulacea disappearance on key microbial processes in the marine environment.We show that the rhizomes had the fastest decomposition rates, followed by the young leaves, roots, and old leaves. This indicates the preservation potential of belowground biomass. Moreover, high hydrogen sulfide concentrations were only detected in the slurries containing rhizomes and young leaves. High sulfide concentrations can lead to enhanced seagrass mortality and a positive feedback loop where seagrass loss generates sulfide, leading to more seagrass loss. These results emphasize the importance of a deeper understanding of biogeochemical pathways following seagrass disappearance.
Conditioning Deep Learning Weather Prediction Models On Exogenous Fields
Authors: Hoffmann Sebastian , Thümmel Jannik , Goswami Bedartha
Published: March 2024

Deep learning weather prediction (DLWP) models have recently proven to be a viable alternative to classical numerical integration. Often, the skill of these models can be improved further by providing additional exogenous fields such as time of day, orography, or sea surface temperatures stemming from an independent ocean model. These merely serve as information sources and are not predicted by the model.In this study, we explore how such exogenous fields can be utilized by DLWP models most optimally and find that the de facto standard way of concatenating them to the input is suboptimal. Instead, we suggest leveraging existing conditioning techniques from the broader deep learning community that modulate the mean and variance of normalized feature vectors in latent space. These, so called, style-based techniques lead to consistently smaller forecast errors and, at the same time, can be integrated with relative ease into existing forecasting architectures. This makes them an attractive avenue to improve deep learning weather prediction in the future.
Spectra of stress: Variability in lithologies represented in geomechanical models
Authors: Ziegler Moritz , Reiter Karsten , Heidbach Oliver , Desroches Jean , Fjaer Erling , Giger Silvio
Published: March 2024

Knowledge of the current undisturbed stress state is a key issue of subsurface applications. Amongst others, the stability of caverns and boreholes depend on the stress magnitudes. For the prediction of the stress in a rock volume 3D geomechanical-numerical models are used. Technically the task is to estimate the equilibrium of forces between gravity and the elastic response due to lateral displacement boundary conditions that result in a best-fit with respect to pointwise stress magnitude data. For sensitivity studies of the effect of variable boundary conditions, the rock properties (Young’s modulus, Poisson ratio, density) are assigned to the corresponding lithologies that are implemented in the model volume. However, mainly the Young’s modulus has a high variability within each lithological unit.We demonstrate an approach where obtained information on the rock property distribution is included in a geomechanical model to provide several possible stress states. From these individual cases the range of stress states that are likely to be expected are estimated. This results in a bandwidth for the components of the stress tensor. For each component, a median stress magnitude is provided as well as a 1σ and 2σ range. This allows a more comprehensive estimate of the stress state which, in turn, allows to include uncertainties on stress magnitudes in the design of underground structures due to being more informed. Even though, a safety margin will always have to be included, well known and quantified uncertainties may lead to a reduction of said margin. In turn, this improves economic feasibility. The required safety margins can be adapted to the prevailing stress state for each individual unit if potentially unstable zones are identified well in advance.We demonstrate the applicability of the approach on the site of a planned deep geological repository. The Swiss National Cooperative for the Disposal of Radioactive Waste (NAGRA) provides an unprecedented amount and quality of both stress magnitude and rock property data records for this site. For each unit a cumulative density function of the rock properties is available which allows a robust assessment of the variability. Eventually, we are able to provide a bandwidth of the expected stress magnitudes throughout the model volume. A comparison with the measured bandwidths of stress magnitude data records along borehole trajectories shows a very good agreement between the modelled bandwidth and the range of obtained stress magnitudes.
Spatial variability in topology, connectivity and permeability within deformation band networks
Authors: Heggernes Hakan , Rotevatn Atle , Demurtas Matteo , Nixon Casey W. , Fossen Haakon
Published: March 2024

Networks of deformation bands in porous granular rocks represents potential low-permeable baffles to fluid flow in subsurface reservoirs. However, little work addresses the network properties of such networks, like spatial intensity, network connectivity and network geometry. Motivated by this, we here present an investigation of two-dimensional, horizontal exposures of deformation band networks within the Jurassic Entrada Sandstone in the San Rafael Desert (Utah). We analyse the geometry and topology (i.e. a network represented as nodes and branches) of the studied networks to: 1) characterise deformation band orientation, connectivity and areal intensity; 2) assess spatial topological variability; 3) elucidate large scale variation across the study area; 4) evaluate effective network permeabilities. Effective deformation band network permeability is calculated by incorporating a topological measure of network connectivity into the permeability calculations. Deformation band networks show distinct topological signatures, typically being dominated by Y-nodes, and IC- and CC-branches. Depending on the orientation of deformation bands and numbers of different sets of deformation bands within each studied network, both topology and areal intensity vary. Low proportion of isolated II-branches reflects the evolution of deformation bands through bifurcation and abutment, creating Y-nodes, to form interconnected networks. We document great spatial variability I network connectivity and topology within individual networks. Similarly, the effective permeability within well-connected (parts of) the studied deformation band networks (>1.5 connections per branch) significantly reduce effective permeabilities, whereas areas within the networks with low connectivity offer higher-permeable pathways for tortuous fluid flow.
Simultaneous dynamical reconstructions of Sea Surface Height and Temperature from multi-sensor satellite observations.
Authors: Le Guillou Florian , Rio Marie-Helene , Ciani Daniele , Storto Andrea , Buongiorno Nardelli Bruno
Published: March 2024

For many years, satellite observations of sea surface height (SSH) and sea surface temperature (SST) have provided invaluable information on the dynamics of the upper ocean at many scales. SSH and SST variables are dynamically linked, and are very often used together for many scientific studies (e.g. estimating heat transport in the upper layer by SSH-derived geostrophic currents). As observations are unevenly distributed in space and time (SSH is measured along one-dimensional trajectories and SST measurements are affected by clouds), many scientific and operational applications rely on gridded SSH and SST products. However, these products suffer from two main limitations. Firstly, conventional mapping techniques rely on static optimal interpolation schemes, which limits the estimation of nonlinear dynamics at scales poorly sampled by altimetry or, for SST, in regions densely affected by clouds (e.g. near western boundary currents). Secondly, SSH and SST reconstructions are performed separately, without relying on synergies between the two variables, which has an impact on the consistency of the two reconstructed fields.We introduce an original dynamical mapping algorithm to simultaneously reconstruct SSH and SST from multi-sensor satellite observations. This innovative method combines a weakly constrained, reduced-order, 4-dimensional variational scheme with simple physical models – quasi-geostrophic for SSH and advection-diffusion for SST. The weak constraint of the models on the inversion procedure ensures that the reconstructed SSH and SST fields closely match the observations while preserving the space-time continuity of the dynamical structures.The work focuses on the North Atlantic Ocean over the year 2023 and considers the available along-track altimetric SSH, microwave and infrared SST data. The performances of the method are evaluated through Observing System Experiments, utilizing independent altimetric (from conventional and SWOT satellites) and drifter data. Results show a significant improvement of the reconstruction of short energetic structures, both in terms of SSH and SST, compared to operational products. The benefit of using SST observations for reconstructing SSH fields increases as the number of altimeters is reduced. This opens new opportunity to use the method for sea-level related climate applications that rely on a stable two altimeters constellation.
Geologic CH4 storage with CO2 cushion gas: using dynamic binary diffusion coefficients instead of a global constant in numerical simulations is more precise and results in lower mixing losses
Authors: Kempka Thomas , Kühn Michael
Published: March 2024

Natural gas storage is currently considered as one key pillar of the EU strategy to ensure security of energy supply. In view of CH4 storage, Oldenburg [1] demonstrated in a theoretical study that using CO2 as cushion gas instead of CH4 has the advantage of increasing natural gas storage capacities of geologic reservoirs by up to 30 %. This is due to CO2 undergoing a significant density change when its’ critical pressure is exceeded during CH4 injection. Kühn et al. [2] investigated a comparable scenario with CH4 gas storage in a closed cycle with CO2 in one reservoir to temporarily store and reuse wind and solar energy. However, the potential qualitative degradation of the stored CH4 due to mixing with the CO2 cushion gas has not yet been sufficiently addressed in terms of the impact of the modeller’s choice of diffusion coefficients. Hence, the present study focuses on a quantitative assessment of the mixing behaviour of CH4 and CO2 under consideration of dynamic binary diffusion coefficients in a reference numerical simulation benchmark [1,3]. The TRANSPORTSE numerical simulator [4,5] is used with dedicated measures to mitigate the initially high numerical dispersion, introduced by the benchmark’s relatively coarse grid discretisation. The simulation results show that the mixing region is substantially reduced if dynamic binary diffusion coefficients are applied instead of a global constant for both gas components. Consequently, it is demonstrated that previous numerical assessments of natural gas storage with a carbon dioxide cushion gas overestimate the simulated CH4-CO2-mixing area, and thus the calculated mixing losses. Hence, combined gas storage of CH4 and CO2 is more efficient than expected so far.[1] Oldenburg, C. M. (2003) Carbon Dioxide as Cushion Gas for Natural Gas Storage. Energy Fuels 17(1), 240−246. https://doi.org/10.1021/ef020162b[2] Kühn, M., Nakaten, N. C., Streibel, M., Kempka, T. (2014): CO2 Geological Storage and Utilization for a Carbon Neutral “Power-to-gas-to-power” Cycle to Even Out Fluctuations of Renewable Energy Provision. Energy Procedia, 63, 8044-8049. https://doi.org/10.1016/j.egypro.2014.11.841[3] Ma, J., Li, Q., Kempka, T., Kühn, M. (2019) Hydromechanical Response and Impact of Gas Mixing Behavior in Subsurface CH4 Storage with CO2-Based Cushion Gas Energy & Fuels 33 (7), 6527-6541. https://doi.org/10.1021/acs.energyfuels.9b00518[4] Kempka, T. (2020) Verification of a Python-based TRANsport Simulation Environment for density-driven fluid flow and coupled transport of heat and chemical species. Advances in Geosciences, 54, 67-77. https://doi.org/10.5194/adgeo-54-67-2020[5] Kempka, T., Steding, S., Kühn, M. (2022) Verification of TRANSPORT Simulation Environment coupling with PHREEQC for reactive transport modelling. Advances in Geosciences, 58, 19-29. https://doi.org/10.5194/adgeo-58-19-2022
Quaternary and Pliocene sea-level changes at Camarones, central Patagonia, Argentina
Authors: Rovere Alessio , Rubio Sandoval Karla , Ryan Deirdre D. , Richiano Sebastian , Giachetti Luciana M. , Hollyday Andrew , Bright Jordon , Gowan Evan J. , Pappalardo Marta , Austermann Jacqueline , Kaufman Darrell S.
Published: March 2024

Geological indicators of past relative sea level changes are fundamental to reconstruct the extent of former ice sheet during past interglacials, which are considered analogs for future climate conditions. Four interglacials, dating from Holocene to Pliocene, have left sea-level imprints in the proximity of the coastal town of Camarones in Central Patagonia, Argentina. Sea-level index points were preserved as beach ridges deposited by storm waves above modern sea level. We used highly accurate survey techniques to measure the elevation of these deposits. Satellite-derived wave measurements and wave runup models were then employed to calculate their indicative meaning (i.e., their elevation with respect to sea level at the time of deposition). The paleo relative sea levels (i.e., uncorrected for post-depositional vertical land motions) associated with the four interglacials (with 1σ uncertainties) are 6±1.5 m (Holocene); 8.7±2.1 m (MIS 5e); 14.5±1.5 m (MIS 9 or 11); and 36.2±2.7 m (Early Pliocene). Ages have been obtained using both published (U-series, Electron Spin Resonance, and Radiocarbon) and new (Amino Acid Racemization and Radiocarbon) dating constraints. We compare our results with published glacial isostatic adjustment and mantle dynamic topography predictions, and we highlight that refining these models before calculating the global mean sea level for the interglacials mentioned above is necessary. Our high-resolution data provide a significant benchmark for paleo relative sea-level studies in the Southwestern Atlantic.

This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 re- search and innovation programme (grant agreement no. 802414)
Crowd-sourced Turbidity Event Scale for Proactive Management of Drinking Water Quality in Distribution Systems
Authors: Gleeson Killian , Husband Stewart , Gaffney John , Boxall Joby
Published: March 2024

Drinking water distribution systems operate to transport high-quality treated water across large distances to entire populations, yet water quality and contamination events occur between treatment and tap. Deployment of water quality instrumentation within drinking water distribution systems enables such events to be better understood. Specifically, in-network turbidity sensors offer a unique opportunity to measure network discolouration events, which are difficult to predict and may pose health risks to end users. However, extracting actionable information from the increasing volume of water quality data represents a major challenge to realising the true benefits of digitalisation. Typically this involves manual interpretation of time series plots, which is time-consuming and impractical for larger sensor networks. There is therefore a need to develop automated algorithmic approaches to process and integrate the turbidity signals. However, the information that is of interest and such algorithms should detect is uncertain. This study employed crowd-sourcing exercises with groups of domain experts to identify significant features within turbidity time series data from real-world distribution systems. The labelled data derived from these exercises delivers valuable insights and a critical benchmark for evaluating algorithmic methods designed to replicate human interpretation. Reflecting on the outcomes of the labelling tasks led to the development of a turbidity event scale that differentiates between advisory (< 2 NTU), alert (2 < NTU < 4), and alarm (> 4 NTU) level events. This event scale provides network operators with tools required to manage discolouration events both reactively and, crucially, proactively. A time-based averaging method, centred on data from the same time each day, proved most effective in identifying the advisory events, when compared to popular time series forecasting approaches. The event scale is demonstrated on a real-world example not included in the labelling exercises, showcasing the practical benefits and scalability of this data-driven approach. The automation of event detection and categorisation developed here offers the potential to obtain actionable insights to protect the quality of drinking water as it passes through ageing network infrastructure.
Exploring dissolved organic matter (DOM) signatures across contrasting UK landscapes using a high-resolution mass spectrometry ‘fingerprinting’ approach.
Authors: Lloyd Charlotte , Pemberton Jonathan , Johnes Penny , Jones Davey , Yates Chris , Glanville Helen , Brailsford Fran , Evershed Richard
Published: March 2024

Dissolved organic matter (DOM) plays a vital role in river ecosystem function and therefore understanding its composition is key. DOM has important implications for nutrient cycling and riverine health and with this in mind, it is vital to gain a more comprehensive understanding of the composition of riverine DOM at a molecular level and how this varies across contrasting landscapes. There are many factors which will influence DOM signatures, from differences in climate, soil type/geology, land-use, as well as intensity and nature of anthropogenic activity. Through understanding the potential relationships between these factors and DOM composition, we can gain key information regarding both sources of riverine DOM within river catchments, aiding pollution mitigation strategies, and how signatures may vary under changing climate and/or land-use.The analysis of DOM poses a significant analytical challenge due to its complexity, however the advances in mass spectrometry now allows detailed characterisation at molecular scale. This study examines the DOM composition across 56 UK field sites spanning contrasting landscapes, including four different geologies/soil types. Additionally, 18 effluents from UK sewage treatment works (STW) were investigated. River water samples were collected and an untargeted analysis carried out using direct-infusion high-resolution mass spectrometry (DI-MS) and the resultant DOM signatures across the samples were compared.Principal component analysis (PCA) and hierarchical clustering analysis methodologies were applied and showed that the DOM molecular composition between sites could be distinguished according to landscape character. Specifically, the PCA analysis showed that contrasting geologies/soil types were separated by the derived Principle Component (PC) 2 while PC1 separated the riverine samples from the STW effluents in the analytical space. Explanatory variables including landcover, land-use and population density alongside bulk nutrient data were used to begin to elucidate the driving factors behind the PCs. In addition to differences in DOM signatures, further analysis of the molecular compositions identified anthropogenically derived organic compounds, for example, series of polypropylene glycol (PPG) and polyethylene glycol (PEG) oligomers, which were present in almost all landscapes across the UK, illustrating that they are now ubiquitous across riverine environments. Using these data, we can begin to provide generalisable information regarding the molecular composition of DOM across different UK landscapes.
Air mass history linked to the development of Arctic mixed-phase clouds
Authors: Murray-Watson Rebecca , Gryspeerdt Ed
Published: March 2024

The development of clouds during marine cold-air outbreaks (MCAOs) represent a complex phenomenon, transitioning from stratocumulus decks near ice edges to cumuliform fields downwind. This change cloud morphology changes the radiative properties of the cloud, and therefore is of importance to the surface energy budget. Therefore, it is crucial to understand the factors which may drive transition to a broken cloud field. Previous in situ and modelling studies suggest the formation of ice may enhance precipitation and therefore accelerate break-up. However, little is known about the development of mixed-phase clouds in MCAOs. 

This study uses pseudo-Lagrangian trajectories and satellite data to analyze this mixed-phase cloud development. We observe a rapid transition from liquid to ice phases in MCAO clouds, contrasting with similar cloud formations outside MCAO conditions. These mixed-phase clouds initially form at temperatures below -20°C near ice edges but can dominate even at -13°C further into outbreaks. This temperature shift suggests a significant role for biological ice nucleating particles (INPs), which increase in prevalence as air masses age over marine environments. The study also notes the influence of the air mass's history over snow- and ice-covered surfaces, which may be low in INPs, on cloud evolution. This link helps explain seasonal variations in Arctic cloud development, both during and outside of MCAOs. Our findings emphasize the importance of understanding local marine aerosol sources and the broader INP distribution in the Arctic for accurate cloud phase modeling in the region. 