ALBERT

Description: Chemical weathering driven by physical erosion is a natural process that strongly affects chemical and solid matter budgets at the Earth's surface. However, the influence of extreme climatic erosion on chemical weathering dynamics is poorly understood. Badland landscapes formed in highly erodible substrates have the potential to respond to individual events on scales that are rapid enough for direct observation. Here, we assess the geochemical and grain-size composition of suspended sediment and riverine chemistry measurements collected from two catchments during the 2017 Nesat and Haitang typhoons in southwestern (SW) Taiwan. During the typhoons, the Na+ concentration covaried with suspended sediment concentration (SSC), which we attributed to sodium-induced deflocculation. Evaporite weathering at peak rainfall is succeeded by peak silicate weathering at maximum discharge. Overall, our observations suggest that initial weathering of near-surface evaporite enhances the physical erosion of silicate rock during extreme rainfall events.

Description: Chemical weathering driven by physical erosion is one of the manifestations of natural processes that strongly affect chemical and solid matter budgets at the Earth’s surface. However, the influence of extreme climatic erosion on chemical weathering dynamics is poorly understood. Badland landscapes formed in highly erodible, homogeneous substrates have the potential to respond to individual events on scales that are rapid enough for direct observation. Here, we assess the geochemical and grain-size composition of suspended sediment and riverine chemistry measurements collected from two catchments during the 2017 Nesat and Haitang typhoons in southwestern Taiwan. During the typhoons, the sodium adsorption ratio covaried with suspended sediment concentration, which we attributed to sodium-induced deflocculation. Evaporite weathering at peak rainfall is succeeded by peak silicate weather at maximum discharge, which dominates the weathering signal of the event. Overall, our observations suggest that initial weathering of near-surface evaporite enhances the physical erosion of silicate rock during extreme rainfall events.

Description: The Tonga volcano eruption in the middle of January 2022 triggered a variety of wave perturbations that propagated across the globe multiple times, disturbing the entire atmosphere and manifesting as concentric traveling ionospheric disturbances (CTIDs) of various periods and wave characteristics. This study reports a comprehensive view of such ionospheric variations triggered from a single source, illustrating the global evolution of the CTIDs with the propagation of the barometric Lamb wave by using total electron content (TEC) measurements derived from more than 7000 ground based global navigation satellite system (GNSS) receivers. The results, for the first time, show conjugate appearance of the ionospheric perturbations, resulting in rapid occurrence of CTIDs in the northern hemispheres, much ahead of the direct arrival of the surface Lamb waves. Both direct and conjugate CTIDs show similar horizontal phase velocities of 320-390 m/s, matching with the dispersion relation of Lamb mode. In addition to the CTIDs, the Tonga eruption also resulted in a huge region of ionospheric being almost void of any plasma density, revealed in both ground- and space-based observations, which lasted for several hours. This is apparently generated by the merging of a giant ionosphere hole formed in the vicinity of the eruption location, with the deep equatorial trough of an unusually strong pre-reversal enhancement (PRE) in the post-sunset period. The impulsive pressure, composition changes, water vapor injection and the impacts of successive eruptions apparently created the long-lasting giant ionosphere hole.

Description: Highlights • Code comparisons build confidence in simulators to model interdependent processes. • International hydrate reservoir simulators are compared over five complex problems. • Geomechanical processes significantly impact response of gas hydrate reservoirs. • Simulators yielded comparable results, however many differences are noted. • Equivalent constitutive models are required to achieve agreement across simulators. Geologic reservoirs containing gas hydrate occur beneath permafrost environments and within marine continental slope sediments, representing a potentially vast natural gas source. Numerical simulators provide scientists and engineers with tools for understanding how production efficiency depends on the numerous, interdependent (coupled) processes associated with potential production strategies for these gas hydrate reservoirs. Confidence in the modeling and forecasting abilities of these gas hydrate reservoir simulators (GHRSs) grows with successful comparisons against laboratory and field test results, but such results are rare, particularly in natural settings. The hydrate community recognized another approach to building confidence in the GHRS: comparing simulation results between independently developed and executed computer codes on structured problems specifically tailored to the interdependent processes relevant for gas hydrate-bearing systems. The United States Department of Energy, National Energy Technology Laboratory, (DOE/NETL), sponsored the first international gas hydrate code comparison study, IGHCCS1, in the early 2000s. IGHCCS1 focused on coupled thermal and hydrologic processes associated with producing gas hydrates from geologic reservoirs via depressurization and thermal stimulation. Subsequently, GHRSs have advanced to model more complex production technologies and incorporate geomechanical processes into the existing framework of coupled thermal and hydrologic modeling. This paper contributes to the validation of these recent GHRS developments by providing results from a second GHRS code comparison study, IGHCCS2, also sponsored by DOE/NETL. IGHCCS2 includes participants from an international collection of universities, research institutes, industry, national laboratories, and national geologic surveys. Study participants developed a series of five benchmark problems principally involving gas hydrate processes with geomechanical components. The five problems range from simple geometries with analytical solutions to a representation of the world's first offshore production test of methane hydrates, which was conducted with the depressurization method off the coast of Japan. To identify strengths and limitations in the various GHRSs, study participants submitted solutions for the benchmark problems and discussed differing results via teleconferences. The GHRSs evolved over the course of IGHCCS2 as researchers modified their simulators to reflect new insights, lessons learned, and suggested performance enhancements. The five benchmark problems, final sample solutions, and lessons learned that are presented here document the study outcomes and serve as a reference guide for developing and testing gas hydrate reservoir simulators.

Description: Earth system modelling (ESM) is essential for understanding past, present and future Earth processes. Deep learning (DL), with the data-driven strength of neural networks, has promise for improving ESM by exploiting information from Big Data. Yet existing hybrid ESMs largely have deep neural networks incorporated only during the initial stage of model development. In this Perspective, we examine progress in hybrid ESM, focusing on the Earth surface system, and propose a framework that integrates neural networks into ESM throughout the modelling lifecycle. In this framework, DL computing systems and ESM-related knowledge repositories are set up in a homogeneous computational environment. DL can infer unknown or missing information, feeding it back into the knowledge repositories, while the ESM-related knowledge can constrain inference results of the DL. By fostering collaboration between ESM-related knowledge and DL systems, adaptive guidance plans can be generated through question-answering mechanisms and recommendation functions. As users interact iteratively, the hybrid system deepens its understanding of their preferences, resulting in increasingly customized, scalable and accurate guidance plans for modelling Earth processes. The advancement of this framework necessitates interdisciplinary collaboration, focusing on explainable DL and maintaining observational data to ensure the reliability of simulations.