Description: Perturbations in stratospheric aerosol due to explosive volcanic eruptions are a primary contributor to natural climate variability. Observations of stratospheric aerosol are available for the past decades, and information from ice cores has been used to derive estimates of stratospheric sulfur injections and aerosol optical depth over the Holocene (approximately 10 000 BP to present) and into the last glacial period, extending back to 60 000 BP. Tephra records of past volcanism, compared to ice cores, are less complete but extend much further into the past. To support model studies of the potential impacts of explosive volcanism on climate variability across timescales, we present here an ensemble reconstruction of volcanic stratospheric sulfur injection (VSSI) over the last 140 000 years that is based primarily on terrestrial and marine tephra records. VSSI values are computed as a simple function of eruption magnitude based on VSSI estimates from ice cores and satellite observations for identified eruptions. To correct for the incompleteness of the tephra record, we include stochastically generated synthetic eruptions assuming a constant background eruption frequency from the ice core Holocene record. While the reconstruction often differs from ice core estimates for specific eruptions due to uncertainties in the data used and reconstruction method, it shows good agreement with an ice-core-based VSSI reconstruction in terms of millennial-scale cumulative VSSI variations over the Holocene. The PalVol reconstruction provides a new basis to test the contributions of forced vs. unforced natural variability to the spectrum of climate and the mechanisms leading to abrupt transitions in the palaeoclimate record with low- to high-complexity climate models. The PalVol volcanic forcing reconstruction is available at https://doi.org/10.26050/WDCC/PalVolv1 (Toohey and Schindlbeck-Belo, 2023).

Description: The study of offshore freshened groundwater (OFG) is gaining importance due to population growth and environmental pressure on coastal water resources. Marine controlled source electromagnetic (CSEM) methods can effectively map the spatial extent of OFG systems using electrical resistivity as a proxy. Integrating these resistivity models with sub-surface properties, such as host-rock porosity, allows for estimates of pore-water salinity. However, evaluating the uncertainty in pore-water salinity using resistivity models obtained from deterministic inversion approaches presents challenges, as they provide only one best-fit model, with no associated estimate of uncertainty. To address this limitation, we employ trans-dimensional Markov-Chain Monte-Carlo inversion on marine time-domain CSEM data, acquired in the Canterbury Bight, New Zealand. We integrate resistivity posterior probability distributions with borehole and seismic reflection data to estimate pore-water salinity with corresponding uncertainty estimates. The results highlight a low-salinity groundwater body in the center of the survey area, hosted by consecutive silty- and fine-sand layers approximately 20–60 km from the coast. The posterior probability distribution of resistivity models indicates freshening of the OFG body toward the shoreline within a permeable, coarse-sand layer 40–150 m beneath the seafloor, suggesting an active connection between the OFG body and the terrestrial groundwater system. The approach demonstrates how Bayesian inversion constrains the uncertainties in resistivity models and subsequently in pore-water salinity estimates. Our findings highlight the potential of Bayesian inversion to enhance our understanding of OFG systems and provide uncertainty constraints for hydrogeological modeling, thereby contributing to sustainable water resource development. Key Points A Bayesian workflow is employed to evaluate uncertainty in pore-water salinity estimates Offshore groundwater in Canterbury Bight stores freshened pore-water in fine-grained sediments, likely extending from the onshore aquifer Correlation between pore-water salinities and seismic-derived stratigraphy provides boundary conditions for hydrogeological modeling Plain Language Summary Geophysical methods that measure the electromagnetic properties of the Earth are effective in investigating freshwater sources beneath the seafloor. By combining the geophysical and geological information, we can better assess the quality of this groundwater. In this study, we develop a workflow that uses statistical methods to integrate electromagnetic observations with borehole and acoustic measurements along the eastern coast of the South Island of New Zealand. We aim to improve our understanding of the groundwater quality beneath the seafloor. Our research confirms the presence of freshened groundwater within the sandy seafloor up to 60 km from the coastline. Importantly, our observations indicate that the groundwater quality increases toward the coast. These findings are significant as they enhance the hydrogeological modeling of the groundwater system and suggest its potential as a source of freshwater.

Description: Highlights • The developed joint inversion quantifies both free gas and hydrate concentration. • The robust method uses sonic and conductivity logs as main input parameters. • For the test site it reveals two hydrate accumulations with very different characteristics. • The whole range of concentrations is shown that can explain the observed data. • The method is applicable to most continental margins when there is borehole control. Abstract Quantification of gas hydrates in marine sediments is crucial for understanding gas hydrate systems. By empirical relationships or effective medium modelling, gas hydrate concentrations can be derived from velocity and/or conductivity logs. However, these approaches do not take the co-occurrence of free gas and gas hydrate into account leading to large uncertainties in the calculated free gas and gas hydrate concentrations. To overcome this issue we adopt a joint elastic and electric self-consistent/differential effective medium model as the basis for a new joint inversion scheme that distinguishes between both phases. We apply this scheme to p-wave velocity and electric induction data measured by downhole-logging of boreholes at Formosa Ridge off Taiwan - a known hydrate province with an active gas conduit. Gaussian Mixture Modeling separates the background signal of the host medium from anomalies and allows to determine a background porosity as a probability density function of depth. We use this derived porosity to jointly invert electrical conductivity and velocity data for hydrate and free gas concentrations. At Formosa Ridge, we find two resistive anomalies, one in the shallow and another in the deep part of the borehole. Only the deep anomaly in conductivity coincides with a high-velocity anomaly. This is consistent with ∼30% hydrate with ∼1% free gas concentration. For the shallow anomaly, increased velocities due to hydrate concentrations of ∼15% are compensated by a decrease in velocity due to ∼1% of free gas. The method reconciles the different sensitivities of the two data types and yields hydrate and free gas concentrations that are largely consistent with geochemically derived values.

Description: Although marine controlled source electromagnetic (CSEM) methods are effective for investigating offshore freshened groundwater (OFG) systems, interpreting the spatial extent and salinity of OFG remains challenging. Integrating CSEM resistivity models with information on sub-surface properties, such as host-rock porosity, allows for estimates of pore-water salinity. However, deterministic inversion approaches pose challenges in quantitatively analyzing these estimates as they provide only one best-fit model with no associated estimate of model parameter uncertainty. To address this limitation, we employ a trans-dimensional Markov-Chain Monte-Carlo inversion on marine CSEM data, under the assumption of horizontal stratification, collected from the Canterbury Bight, New Zealand. We integrate the resulting posterior distributions of electrical resistivity with borehole and seismic reflection data to quantify pore-water salinity with uncertainty estimates. The results reveal a low-salinity groundwater body in the center of the survey area at varying depths, hosted by consecutive silty- and fine-sand layers approximately 20 to 60 km from the coast. These observations support the previous study’s results obtained through deterministic 2-D inversion and suggest freshening of the OFG body closer to the shore within a permeable, coarse-sand layer 40 to 150 m beneath the seafloor. This implies a potential active connection between the OFG body and the terrestrial groundwater system. We demonstrate how the Bayesian approach constrains the uncertainties in resistivity models and subsequently in pore-water salinity estimates. Our findings highlight the potential of Bayesian inversions in enhancing our understanding of OFG systems, providing crucial boundary conditions for hydrogeological modeling and sustainable water resource development.

Description: Offshore groundwater systems have been suggested as alternative sources of potable water in islands and coastal regions. In this study, we integrate offshore controlled-source electromagnetic (CSEM) with borehole data to identify an offshore groundwater system in the Canterbury Bight, New Zealand. CSEM data were acquired with a seafloor-towed system along four profiles and 2-D inversion was carried out using MARE2DEM to derive resistivity models along each profile. Moreover, a trans-dimensional Bayesian inversion was conducted to assess the distribution of plausible resistivity-depth models. The study area was previously investigated during IODP Expedition 317 in which a pore-fluid salinity anomaly (24 psu at 40 mbsf) was recorded in borehole U1353. A comparison between the CSEM resistivity model and the resistivity-depth profile converted from pore-water salinity within the borehole shows a strong correlation between CSEM and borehole data at the closest waypoint to site U1353. We show through a Markov-Chain Monte Carlo approach that our estimates of seafloor resistivity agree with the measured borehole data. The computed resistivity distributions at the borehole provide significant evidence that the CSEM inversion models can be used to extrapolate groundwater inferences from the borehole onto a basin scale providing improved geophysical imaging capabilities for offshore freshened groundwater.

Description: The Tristan da Cunha islands are located 450 km east of the Mid-Atlantic Ridge and 60 km north of the Tristan da Cunha transform fault, and fracture zone system in the Atlantic Ocean. The islands are products of intraplate hotspot volcanism. However, several controversies are associated with theories for the origin of the Tristan da Cunha hotspot. Previous magnetotelluric data 3-D inversion results based on finite-difference algorithm couldn’t image plume-like vertical structure, unlike many geological and geochemical studies (Baba et al., 2017). In this study, we revisit the electrical structure of the region by inverting combined vertical magnetic transfer functions and the MT responses from seafloor stations around the islands and those newly obtained on the Tristan da Cunha and Nightingale islands. The topographic effect is one of the keys to obtaining a more reliable subsurface structure, and therefore, we use two finite-element-based inversion methods of Usui (2021) and Grayver (2015). For inversion analysis, we compared the topographic responses from these methods and a finite-difference-based forward modeling method (Baba & Seama, 2002; Baba & Chave, 2005) used in the previous study (Baba et al., 2017). The responses for sites with minimum topography effects are almost identical from all the three methods except for some sites where difference is observed in shorter periods. This could be due to the difference in the mesh resolution around the sites. The responses for sites with significant topography effects show a reasonable match for the finite-element methods in longer periods. In contrast a significant difference is observed in responses from all three methods for short periods. The comparison of modeled responses proves the applicability of Usui’s inversion scheme to MT data from this region. In the workshop, the inversion results from Usui’s inversion method will be presented.