Reviews of Geophysics最新文献

Age of stratospheric air is a well established metric for the stratospheric transport circulation. Rooted in a robust theoretical framework, this approach offers the benefit of being deducible from observations of trace gases. Given potential climate-induced changes, observational constraints on stratospheric circulation are crucial. In the past two decades, scientific progress has been made in three main areas: (a) Enhanced process understanding and the development of process diagnostics led to better quantification of individual transport processes from observations and to a better understanding of model deficits. (b) The global age of air climatology is now well constrained by observations thanks to improved quality and quantity of data, including global satellite data, and through improved and consistent age calculation methods. (c) It is well established and understood that global models predict a decrease in age, that is, an accelerating stratospheric circulation, in response to forcing by greenhouse gases and ozone depleting substances. Observational records now confirm long-term forced trends in mean age in the lower stratosphere. However, in the mid-stratosphere, uncertainties in observational records are too large to confirm or disprove the model predictions. Continuous monitoring of stratospheric trace gases and further improved methods to derive age from those tracers will be crucial to better constrain variability and long-term trends from observations. Future work on mean age as a metric for stratospheric transport will be important due to its potential to enhance the understanding of stratospheric composition changes, address climate model biases, and assess the impacts of proposed climate geoengineering methods.

Geothermal energy is a green source of power that could play an important role in climate-conscious energy portfolios; enhanced geothermal systems (EGS) have the potential to scale up exploitation of thermal resources. During hydraulic fracturing, fluids injected under high-pressure cause the rock mass to fail, stimulating fractures that improve fluid connectivity. However, this increase of pore fluid pressure can also reactivate pre-existing fault systems, potentially inducing earthquakes of significant size. Induced earthquakes are a significant concern for EGS operations. In some cases, ground shaking nuisance, building damages, or injuries have spurred the early termination of projects (e.g., Basel, Pohang). On the other hand, EGS operations at Soultz-sous-Forêts (France), Helsinki (Finland), Blue Mountain (Nevada, USA), and Utah FORGE (USA) have adequately managed induced earthquake risks. The success of an EGS operation depends on economical reservoir enhancements, while maintaining acceptable seismic risk levels. This requires state-of-the-art seismic risk management. This article reviews domains of seismology, earthquake engineering, risk management, and communication. We then synthesize “good practice” recommendations for evaluating, mitigating, and communicating the risk of induced seismicity. We advocate for a modular approach. Recommendations are provided for key technical aspects including (a) a seismic risk management framework, (b) seismic risk pre-screening, (c) comprehensive seismic hazard and risk evaluation, (d) traffic light protocol designs, (e) seismic monitoring implementation, and (f) step-by-step communication plans. Our recommendations adhere to regulatory best practices, to ensure their general applicability. Our guidelines provide a template for effective earthquake risk management and future research directions.

Soil salinization refers to the accumulation of water-soluble salts in the upper part of the soil profile. Excessive levels of soil salinity affects crop production, soil health, and ecosystem functioning. This phenomenon threatens agriculture, food security, soil stability, and fertility leading to land degradation and loss of essential soil ecosystem services that are fundamental to sustaining life. In this review, we synthesize recent advances in soil salinization at various spatial and temporal scales, ranging from global to core, pore, and molecular scales, offering new insights and presenting our perspective on potential future research directions to address key challenges and open questions related to soil salinization. Globally, we identify significant challenges in understanding soil salinity, which are (a) the considerable uncertainty in estimating the total area of salt-affected soils, (b) geographical bias in ground-based measurements of soil salinity, and (c) lack of information and data detailing secondary salinization processes, both in dry- and wetlands, particularly concerning responses to climate change. At the core scale, the impact of salt precipitation with evolving porous structure on the evaporative fluxes from porous media is not fully understood. This knowledge is crucial for accurately predicting soil water loss due to evaporation. Additionally, the effects of transport properties of porous media, such as mixed wettability conditions, on the saline water evaporation and the resulting salt precipitation patterns remain unclear. Furthermore, effective continuum equations must be developed to accurately represent experimental data and pore-scale numerical simulations.

Synthetic Aperture Radar (SAR) has emerged as a pivotal technology in geosciences, offering unparalleled insights into Earth's surface. Indeed, its ability to provide high-resolution, all-weather, and day-night imaging has revolutionized our understanding of various geophysical processes. Recent advancements in SAR technology, that is, developing new satellite missions, enhancing signal processing techniques, and integrating machine learning algorithms, have significantly broadened the scope and depth of geosciences. Therefore, it is essential to summarize SAR's comprehensive applications for geosciences, especially emphasizing recent advancements in SAR technologies and applications. Moreover, current SAR-related review papers have primarily focused on SAR technology or SAR imaging and data processing techniques. Hence, a review that integrates SAR technology with geophysical features is needed to highlight the significance of SAR in addressing challenges in geosciences, as well as to explore SAR's potential in solving complex geoscience problems. Spurred by these requirements, this review comprehensively and in-depth reviews SAR applications for geosciences, broadly including various aspects in air-sea dynamics, oceanography, geography, disaster and hazard monitoring, climate change, and geosciences data fusion. For each applied field, the scientific advancements produced because of SAR are demonstrated by combining the SAR techniques with characteristics of geophysical phenomena and processes. Further outlooks are also explored, such as integrating SAR data with other geophysical data and conducting interdisciplinary research to offer comprehensive insights into geosciences. With the support of deep learning, this synergy will enhance the capability to model, simulate, and forecast geophysical phenomena with greater accuracy and reliability.

While deterministically predicting the time and location of earthquakes remains impossible, earthquake forecasting models can provide estimates of the probabilities of earthquakes occurring within some region over time. To enable informed decision-making of civil protection, governmental agencies, or the public, Operational Earthquake Forecasting (OEF) systems aim to provide authoritative earthquake forecasts based on current earthquake activity in near-real time. Establishing OEF systems involves several nontrivial choices. This review captures the current state of OEF worldwide and analyzes expert recommendations on the development, testing, and communication of earthquake forecasts. An introductory summary of OEF-related research is followed by a description of OEF systems in Italy, New Zealand, and the United States. Combined, these two parts provide an informative and transparent snapshot of today's OEF landscape. In Section 4, we analyze the results of an expert elicitation that was conducted to seek guidance for the establishment of OEF systems. The elicitation identifies consensus and dissent on OEF issues among a non-representative group of 20 international earthquake forecasting experts. While the experts agree that communication products should be developed in collaboration with the forecast user groups, they disagree on whether forecasting models and testing methods should be user-dependent. No recommendations of strict model requirements could be elicited, but benchmark comparisons, prospective testing, reproducibility, and transparency are encouraged. Section 5 gives an outlook on the future of OEF. Besides covering recent research on earthquake forecasting model development and testing, upcoming OEF initiatives are described in the context of the expert elicitation findings.

A holistic review is given of the Southern Ocean dynamic system, in the context of the crucial role it plays in the global climate and the profound changes it is experiencing. The review focuses on connections between different components of the Southern Ocean dynamic system, drawing together contemporary perspectives from different research communities, with the objective of closing loops in our understanding of the complex network of feedbacks in the overall system. The review is targeted at researchers in Southern Ocean physical science with the ambition of broadening their knowledge beyond their specific field, and aims at facilitating better-informed interdisciplinary collaborations. For the purposes of this review, the Southern Ocean dynamic system is divided into four main components: large-scale circulation; cryosphere; turbulence; and gravity waves. Overviews are given of the key dynamical phenomena for each component, before describing the linkages between the components. The reviews are complemented by an overview of observed Southern Ocean trends and future climate projections. Priority research areas are identified to close remaining loops in our understanding of the Southern Ocean system.

Soil moisture is an essential climate variable of the Earth system. Understanding its spatiotemporal dynamics is essential for predicting weather patterns and climate variability, monitoring and mitigating the effects and occurrence of droughts and floods, improving irrigation in agricultural areas, and sustainably managing water resources. Here we review in depth how soils can remember information on soil moisture anomalies over time, as embedded in the concept of soil moisture memory (SMM). We explain the mechanisms underlying SMM and explore its external and internal drivers; we also discuss the impacts of SMM on different land surface processes, focusing on soil-plant-atmosphere coupling. We explore the spatiotemporal variability, seasonality, locality, and depth-dependence of SMM and provide insights into both improving its characterization in land surface models and using satellite observations to quantify it. Finally, we offer guidance for further research on SMM.

Convective flow in the deep mantle controls Earth's dynamic evolution, influences plate tectonics, and has shaped Earth's current surface features. Present and past convection-induced deformation manifests itself in seismic anisotropy, which is particularly strong in the mantle's uppermost and lowermost portions. While the general patterns of seismic anisotropy have been mapped for the upper mantle, anisotropy in the lowermost mantle (called D′′) is at an earlier stage of exploration. Here we review recent progress in methods to measure and interpret D′′ anisotropy. Our understanding of the limitations of existing methods and the development of new measurement strategies have been aided enormously by the availability of high-performance computing resources. We give an overview of how measurements of seismic anisotropy can help constrain the mineralogy and fabric of the deep mantle. Specifically, new and creative strategies that combine multiple types of observations provide much tighter constraints on the geometry of anisotropy than have previously been possible. We also discuss how deep mantle seismic anisotropy provides insights into lowermost mantle dynamics. We summarize what we have learned so far from measurements of D′′ anisotropy, how inferences of lowermost mantle flow from measurements of seismic anisotropy relate to geodynamic models of mantle flow, and what challenges we face going forward. Finally, we discuss some of the important unsolved problems related to the dynamics of the lowermost mantle that can be elucidated in the future by combining observations of seismic anisotropy with geodynamic predictions of lowermost mantle flow.

On behalf of the authors and readers of Reviews of Geophysics (RoG), the American Geophysical Union, and the broader scientific community, the editors wish to wholeheartedly thank those who reviewed manuscripts for RoG in 2023.

Data assimilation plays a dual role in advancing the “scientific” understanding and serving as an “engineering tool” for the Earth system sciences. Land data assimilation (LDA) has evolved into a distinct discipline within geophysics, facilitating the harmonization of theory and data and allowing land models and observations to complement and constrain each other. Over recent decades, substantial progress has been made in the theory, methodology, and application of LDA, necessitating a holistic and in-depth exploration of its full spectrum. Here, we present a thorough review elucidating the theoretical and methodological developments in LDA and its distinctive features. This encompasses breakthroughs in addressing strong nonlinearities in land surface processes, exploring the potential of machine learning approaches in data assimilation, quantifying uncertainties arising from multiscale spatial correlation, and simultaneously estimating model states and parameters. LDA has proven successful in enhancing the understanding and prediction of various land surface processes (including soil moisture, snow, evapotranspiration, streamflow, groundwater, irrigation and land surface temperature), particularly within the realms of water and energy cycles. This review outlines the development of global, regional, and catchment-scale LDA systems and software platforms, proposing grand challenges of generating land reanalysis and advancing coupled land‒atmosphere DA. We lastly highlight the opportunities to expand the applications of LDA from pure geophysical systems to coupled natural and human systems by ingesting a deluge of Earth observation and social sensing data. The paper synthesizes current LDA knowledge and provides a steppingstone for its future development, particularly in promoting dual driven theory-data land processes studies.