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The Gulf of Mexico (GOM) is a regionally important marine ecosystem with valuable fisheries that may be detrimentally impacted by anthropogenic climate change. In recent years, our scientific understanding of climate change impacts on the GOM water quality has advanced considerably. Such advancements include increased understanding of climate change impacts on the GOM's hypoxia and sediment, and subsequent impacts on the region's marine ecosystem. This paper reviews these developments and highlights gaps in our understanding of climate change impacts on marine water quality and its implications in the GOM region. There is broad scientific agreement that physical changes induced by anthropogenic climate change are determining factors of water quality and biodiversity in the GOM. However, the scientific community should work toward a greater understanding of species and ecosystem specific changes through modeling studies exclusive to the GOM region and this should inform the development of broader multi-disciplinary mitigation strategies. [ABSTRACT FROM AUTHOR]

The cornerstone assumption of all Flood Geology models is that rocks can form quickly (i.e., within the timeframe of months to years). However, to date, only isolated examples from the field have been used to support the hypothesis without any quantitative justification. This paper therefore presents the theoretical basis (originally set out by Terzaghi, 1922) for determining the timescales for the first phase of lithification, the mechanical compaction of the sediment under its self-weight (otherwise known as consolidation). The paper demonstrates that when basic soil mechanics theory is applied to the consolidation of thick clay layers of the order of 1,000 m such as those found in the North Sea, Gulf of Mexico, and the Caspian Sea, the timescales predicted for compaction are orders of magnitude greater than is currently assumed. Additionally, it is shown that there is a physical limit to the rate at which sediment can accumulate without creating excessive pore pressure and inducing geotechnical failures. For clay, this limit is approximately 0.1 m/yr, and, for silt, approximately 10 m/yr. [ABSTRACT FROM AUTHOR]

This paper shows the observation and estimation of convective wind gusts by different satellite sensors at the C-band (Sentinel-1 SAR) and L-band (ALOS-1 SAR and SMAP radiometer) over Lake Victoria, the Gulf of Guinea, and the Gulf of Mexico. These areas are significantly impacted by deep convection associated with strong surface winds and heavy rainfall. In particular, the collocation of Sentinel-1 and SMAP images enables the observation of the movement of surface wind gusts corresponding to that of deep convective clouds. The convective wind intensity estimated from Sentinel-1 and SMAP data varies from 10 to 25 m/s. Additionally, we present an agreement in the observation of deep convective clouds, dynamics, and strong surface winds by different satellite sensors, including Meteosat geostationary (GEO), Aeolus Lidar, and Sentinel-1 SAR, respectively. We also evaluate the estimated convective wind gusts by comparison with the in situ measurements of the weather stations installed in the Gulf of Mexico, where deep convection occurs regularly. The result shows an agreement between the two wind sources estimated and measured. Likewise, the peaks of the measured wind gusts correspond to the occurrence of deep convective clouds observed by the GOES-16 GEO satellite. [ABSTRACT FROM AUTHOR]

The storage potential of hydrocarbon reservoirs in the central Gulf of Mexico (GOM) makes future development of CO2 storage projects in those areas promising for secure, large-scale, and long-term storage purposes. Focusing on the producing and depleted hydrocarbon fields in the continental slope of the central GOM, this paper analyzed, assessed, and screened the producing sands and evaluated their CO2 storage potential. A live interactive CO2 storage site screening system was built in the SAS® Viya system with a broad range of screening criteria combined from published studies. This offers the users a real-time assessment of the storage sites and enables them to adjust the filters and visualize the results to determine the most suitable filter range. The CO2 storage resources of the sands were estimated using a volumetric equation and the correlation developed by the National Energy Technology Laboratory (NETL). The results of this study indicate that 1.05 gigatons of CO2 storage resources are available in the developed reservoirs at the upper slope area of the central GOM. The Mississippi Canyon and Green Canyon protraction areas contain the fields with the largest storage resources. [ABSTRACT FROM AUTHOR]

Vessel electronic monitoring (EM) systems used in fisheries around the world apply a variety of cameras to record catch as it is brought on deck and during fish processing activities. In EM work conducted by the Center for Fisheries Electronic Monitoring at Mote (CFEMM) in the Gulf of Mexico commercial reef fish fishery, there was a need to improve upon current technologies to enhance camera views for accurate species identification of large sharks, particularly those that were released while underwater at the vessel side or underneath the hull. This paper describes how this problem was addressed with the development of the first known EM system integrated underwater camera (UCAM) with a specialized vessel-specific deployment device on a bottom longline reef fish vessel. Data are presented based on blind video reviews from CFEMM trained reviewers of the resulting UCAM video footage compared with video from only the overhead EM cameras from 68 gear retrievals collected from eight fishing trips. Results revealed that the UCAM was a successful tool for capturing clear underwater video footage of released large (>2m) sharks to enable reviewers to improve individual species identification, determination, and fate by 34.4%. This was particularly important for obtaining data on incidental catches of large protected shark species. It also provided clear underwater imagery of the presence of potential predators such as marine mammals close to the vessel, more specifically bottlenose dolphin (Tursiops truncatus) during gear retrieval, which often damaged or removed catch. This information is intended to assist researchers in need of gathering critical data on bycatch in close proximity to a vessel in which conventional overhead EM cameras are limited. [ABSTRACT FROM AUTHOR]

Natural methane hydrate has often been observed in sand layers that contain no particulate organic carbon (POC), but are surrounded by organic-rich, fine-grained marine muds. In this paper, we develop a reactive transport model (RTM) of a microbially-mediated set of POC degradation reactions, including hydrolysis of POC driven by extracellular enzymes, fermentation of the resulting high-molecular weight dissolved organic carbon (HMW-DOC), and methanogenesis that consumes low-molecular weight dissolved organic carbon (LMW-DOC). These processes are mediated by two groups of microbes, fermenters and methanogens that are heterogeneously distributed in different lithologies, with the largest numbers of microbes in the large pores of coarse-grained layers. We find that the RTM can reproduce methane hydrate occurrences observed in two different geological environments, at Walker Ridge Site 313-H (Gulf of Mexico) and IODP Site U1325 (Cascadia Margin). We also find that microbes can degrade POC even if they are physically separated, as extracellular enzymes and DOC can diffuse away from where they are produced by microbes. Microbial activity is highest at relatively early times after burial at shallow depths and near lithological boundaries, where concentration gradients transport solutes to intervals that contain the most microbes. [ABSTRACT FROM AUTHOR]

The dryline, often associated with the development of severe storms in the Southern Great Plains of the United States of America, is a boundary layer phenomenon that occurs when a warm and moist air mass from the Gulf of Mexico meets a hot and dry air mass from the southwest desert area. An accurate knowledge of the water vapor spatio-temporal variability in the lower part of the atmosphere is crucial for a better understanding of the evolution of the dryline. The tropospheric refractivity, directly related to water vapor content, is a proxy for the water vapor content of the troposphere. It has already been demonstrated that the refractivity and the refractivity vertical gradient can be jointly estimated from radar phase measurements. In fact, it has been shown that using kriging interpolation techniques, accurate refractivity maps within the coverage area of the radar can be obtained with high temporal resolution. In this paper, a detailed analysis of the time series of radar-based refractivity maps obtained during a dryline that occurred on the afternoon of 22 May 2002 during the International H 2 O Project ( I H O P _ 2002 ) is presented. Comparisons between the time series of radar refractivity maps, obtained with the NCAR S-Pol radar, and the refractivity measurements derived from automatic ground-based weather stations and the AERI instrument, placed at different locations within the coverage area of the NCAR S-Pol radar, demonstrate the accuracy of radar refractivity estimates even for highly variable conditions, both in time and space, in the troposphere. Correlation coefficients higher than 0.95 are obtained in all weather station locations. Regarding the RMSE, errors less than 6 N-units are obtained for all cases, being even as low as 2.92 N-units at some locations. [ABSTRACT FROM AUTHOR]

• Decision-making processes of GCS projects in saline aquifers require a multitude of forward reservoir simulations. • DL surrogate models ease the computational cost of GCS management and operation optimization. • A DL-based workflow incorporating dimension reduction methods was proposed. • A novel strategy was proposed for effective dimension reduction and reconstruction of 3D CO2 saturation data. • The results suggest the proposed workflow provides sufficient predictive fidelity across temporal and spatial scales. Deep learning (DL) models are extensively used as surrogate models for high-fidelity simulations of multiphase fluid flow in porous media at large scales, enabling fast forecasts of the spatial–temporal evolution of three-dimensional (3D) state variables in geological carbon storage (GCS). However, training these models in high-dimensional space remains computationally demanding and prone to overfitting because of limited training data. This paper presents a novel workflow to address these challenges by integrating dimension reduction (DR) methods. The proposed workflow employed pre-trained DR models to extract the latent variables of geological models and state variables and utilized the multi-layer perceptron (MLP) for constructing mapping functions between the input and output variables in latent spaces. Subsequently, the pre-trained reconstruction models converted the MLP-predicted latent state variables to their original high-dimensional form. Furthermore, we proposed a novel strategy for the DR and reconstruction of 3D saturation fields to account for the unique data characteristics of sparsity, nonuniformity, and discontinuity. The proposed strategy applied PCA and inverse PCA for 2D average saturation fields and developed a DL-based 3D reconstruction model, leveraging three 2D average saturation fields as input to produce a 3D saturation field as output. The pre-training of DR and reconstruction models and training of MLP models were conducted on 84 Gulf of Mexico (GoM) simulations and evaluated on 12 testing simulations. Each simulation contained 720 monthly time steps, with the first 360 months as the injection period and the rest as the post-injection period. The proposed workflow, incorporating DR and DL models, accurately predicts the normalized 3D pressure fields, achieving mean square error (MSE) of 2.92 × 10−7 compared to the ground truth obtained from a full-physics simulator. Furthermore, the proposed strategy outperformed PCA and convolutional autoencoder (CAE) models on 3D saturation fields, resulting in minor workflow prediction errors with an MSE of 2.93 × 10−5. The results suggest the proposed workflow provides sufficient predictive fidelity across temporal and spatial scales, and enables a speedup of 160 times compared to the full-physics simulator, facilitating improved decision-making and risk assessment for large-scale GCS management in real-time scenarios. [ABSTRACT FROM AUTHOR]

• The XGBoost method and its incremental learning method are introduced to successfully predict missing S-wave velocity data from a limited number of samples in actual logging data. • The SHAP visualization tool is employed to establish the connection between S-wave velocity and other well log parameters within the XGBoost model, uncovering valuable empirical information. • The predicted S-wave velocity data using XGBoost contributes to the identification and estimation of the morphology and saturation of gas hydrates in the well logs of the target reservoir. As an elastic parameter of formations, shear-wave (S-wave) velocity has important significance for assessing the morphology and saturation of gas hydrates but is often incompletely measured in actual drilling. To acquire missing S-wave velocity data for gas hydrate research in the Gulf of Mexico Gas Hydrate Joint Industry Project Leg II (GOM JIP Leg II), this paper introduces Extreme Gradient Boosting (XGBoost). Meanwhile, three additional machine learning models were trained for comparative analysis. The results show that XGBoost has better predictive performance than Gradient Boosting Decision Tree (GBDT) and Ordinary Least Squares (OLS) regression, and is more suitable for the small-sample well-log data in this study than Long Short-Term Memory (LSTM) networks. Based on this, Shapley Additive Explanations (SHAP) were used to explain the importance and specific contributions of well-logging parameters in XGBoost, and incremental learning was employed to overcome the issue of insufficient data for initial model training. Finally, the application of the prediction results provides hydrate morphology identification and saturation estimation based on S-wave velocity. This research opens a new intelligent path for recovering missing S-wave velocity in GOM JIP Leg II and enhances in-depth assessment of gas hydrate potential in the region. [ABSTRACT FROM AUTHOR]

On September 18, Category 4 Hurricane Ian made landfall near Fort Myers Beach and Sanibel Island, two barrier islands on the northern Gulf of Mexico. In this paper, we present a novel set of observations from a post-event High Water Mark field survey as well as wavelet analysis of in-situ wave data. We also present a qualitative overview of some erosive effects and infrastructure damage. Measured peak surge elevations exceed 5 m, and wave plus surge elevations exceed 6.0 m (NAVD88). High Water Mark observations are consistent within the expected range produced by numerical hindcast models. A wavelet analysis, from one of the few wave records available during the storm, demonstrates the presence of long-period basin mode waves at a 40-min period. The 40-min wave appeared on the wave record before the storm surge, and the peak of this motion also occurred before the peak of the surge. In addition, the wavelet analysis reveals the presence of infragravity wave energy (periods between 30 s and 20 min). Together, these intermediate and long-period waves add over 40 cm to the total water level at peak energy. The measured field data shows a rapidly decreasing surge elevation within the first 300 m from the pre-storm shoreline, and we observe no statistically meaningful attenuation difference between the highly developed shoreline of Fort Myers and the more vegetated shoreline of Sanibel Island. However, the structural survey team observed more infrastructure damage in Fort Myers than Sanibel Island. • On September 28, 2022 Hurricane Ian made landfall in Fort Myers Beach and Sanibel Island, Florida, USA. • Post-storm, our field survey team observed High Water Mark (HWM) and wave impacts in these areas. • Wavelet analysis reveals a peak in energy near a 40-min period that arrived before the main surge. • Long-period motions have the potential to add at least 40 cm to the quasi-steady surge. • Field observations reveal a rapid decrease in wave impact observations in the first 300 m from the shoreline in both study sites. • Sanibel, more vegetated, and Fort Myers, more developed, showed no statistically meaningful difference in surge attenuation. • However, Fort Myers experienced higher infrastructure damage than Sanibel Island. [ABSTRACT FROM AUTHOR]

Current ichnofacies models for shelf environments are largely based on analysis of ancient sedimentary deposits and have rarely been applied to studies of modern siliciclastic shelves. Siliciclastic shelf margins are key components of source rocks and unconventional shale plays that can be used as modern analogs to ancient systems. This paper examines the sedimentology and ichnology of shelf margin cores of the Mississippi River Delta containing strata formed during the 2004 (Ivan) and 2005 (Katrina and Rita) hurricane events in the Gulf of Mexico, together with those from the Kikori-Fly-Purari rivers in the Gulf of Papua, New Guinea and the Tūranganui-a-Kiwa/Poverty Bay shelf deposits of the Waipaoa River basin, offshore New Zealand. The cores provide examples of modern-day traces created by marine organisms on muddy shelves and are used to evaluate ichnological models that have been applied to determine sedimentation rates and depositional processes in ancient settings. In total, six facies were recognised based on lithology and ichnological characteristics: (1) laminated very fine sand, produced by waxing and waning currents, displaying scarce to moderate bioturbation; (2) laminated silty mud, formed by waxing and waning currents, exhibiting scarce, very low to moderate bioturbation; (3) normally graded sand and silt, created by suspension settling following a wave-enhanced sediment-gravity flow (WESGF), which reveals low to moderate bioturbation; (4) fluid mudflow/suspension settling deposits, characterised by structureless mud with low to high bioturbation; (5) biogenically mottled silty mud deposited by suspension settling which show high bioturbation intensity; and, (6) storm-generated facies of laminated sand formed by rapid sediment accumulation on the shelf. The different study areas show remarkably similar traces with variable intensity, diversity, abundance and distribution. The Mississippi River Delta cores are typified by Helminthopsis , Chondrites , Schaubcylindrichnus, Skolithos , Siphonichnus , navichnia, fugichnia and abundant bivalve shells. The deposits from the Gulf of Papua consist of Phycosiphon , Chondrites, Schaubcylindrichnus, Skolithos , Helminthopsis, Arenicolites, worm-like traces and abundant bivalve shell fragments. In addition to the traces and bivalves, Tūranganui-a-Kiwa/Poverty Bay shelf includes Asterosoma , Thalassinoides and gastropods. These traces are consistent with the newly defined Phycosiphon Ichnofacies (MacEachern and Bann, 2020), which characterise muddy prodelta settings. This research demonstrates that the neoichnology of modern shelf sediments match models developed from studies of ancient systems, and provides a robust tool for analysing and interpreting ancient shelf strata. • Four processes were interpreted to have formed the sediment facies in three continental shelves. • Facies from three different shelf margins display similar biogenic features with varying diversity and bioturbation. • Traces recognised to belong to recently proposed Phycosiphon Ichnofacies were recognised. • Link between sedimentation rate, bioturbation, facies and events processes is shown usingrectangular diagram. [ABSTRACT FROM AUTHOR]