Surveys in Geophysics最新文献

{"title":"The Intradecadal Periodic Signals in GPS Displacements and Their Possible Climate Change Influences","authors":"Hao Ding, WeiPing Jiang, Wei Luan, JianCheng Li, YuanJin Pan, Zhao Li","doi":"10.1007/s10712-024-09864-6","DOIUrl":"https://doi.org/10.1007/s10712-024-09864-6","url":null,"abstract":"<p>Intradecadal changes in GPS displacements have garnered significant attention within the research community; however, the existence of relatively stable intradecadal signals, as well as their characteristics and excitation sources, remains to be further confirmed. This study aims to comprehensively investigate this topic by reviewing relevant existing studies and analyzing over 50 diverse datasets. We first reanalyze two different GPS datasets, and based on those reanalyzed results, we unequivocally validate the existence of at least two intradecadal signals in GPS displacements, a significant ~ 5.9 yr periodic signal (with 4.2 ± 0.95 mm excitation amplitude and a <i>Y</i>_2,2 spatial pattern) as some previous studies suggested and a relatively weak ~ 4.8–5.4 yr signal, and we explain why some previous studies cannot detect the ~ 5.9 yr signal or find its actual spatial pattern. Reevaluating the data from the surface air pressure records (and related records), loading displacements, hydrological records, global mean sea level (GMSL), global mean surface temperature (GMST), and various climate indices demonstrate that there are indeed similar 5–7 yr oscillations as previously suggested, but they have clear differences with the ~ 5.9 yr GPS signal. Additionally, the presence of a ~ 4.7–5.3 yr signal in the in situ hydrological records, as well as a ~ 4.5–5.7 yr signal in surface air pressure, contributes to the ~ 4.8–5.4 yr signal observed in the GPS data, thereby influencing the identification of the 5.9 yr signal. The contrasting outcomes derived from hydrological models and in situ hydrological records indicate that the low-frequency components of the hydrological models lack reliability. As for the precise physical mechanism underlying the ~ 5.9 yr GPS signal, although we have eliminated climate changes as potential sources, it is still difficult to deduce a physical mechanism that could reasonably explain it.</p>","PeriodicalId":49458,"journal":{"name":"Surveys in Geophysics","volume":"76 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142360486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lost in Translation: The Need for Common Vocabularies and an Interoperable Thesaurus in Earth Observation Sciences","authors":"P. A. Strobl, E. R. Woolliams, K. Molch","doi":"10.1007/s10712-024-09854-8","DOIUrl":"https://doi.org/10.1007/s10712-024-09854-8","url":null,"abstract":"<p>The Earth Observation sciences are highly multidisciplinary with long value chains from the development, characterisation and deployment of sensors, through data processing and modelling, to the information services provided to decision makers in, for example, governments, companies and non-governmental organisations. A prerequisite to any multidisciplinary collaboration is effective communication and many communities involved in the value chains have developed vocabularies or terminologies to define terms from a particular viewpoint or legacy. However, these vocabularies are often inconsistent, with circular definitions, contradictions and using technical terms that are not defined. Here, three case studies from Earth Observation disciplines are considered involving challenges in the definition and use of the terms ‘observation’, ‘in-situ’ and ‘interoperable’. An approach is suggested for an initiative, starting in Earth Observation, to build a consistent thesaurus taking inspiration from the ISO 25964:2011 standard.</p>","PeriodicalId":49458,"journal":{"name":"Surveys in Geophysics","volume":"58 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142360503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Discovery of Physically Interpretable Wave Equations","authors":"Shijun Cheng, Tariq Alkhalifah","doi":"10.1007/s10712-024-09857-5","DOIUrl":"https://doi.org/10.1007/s10712-024-09857-5","url":null,"abstract":"<p>Using symbolic regression to discover physical laws from observed data is an emerging field. In previous work, we combined genetic algorithm (GA) and machine learning to present a data-driven method for discovering a wave equation. Although it managed to utilize the data to discover the two-dimensional (<i>x</i>, <i>z</i>) acoustic constant-density wave equation <span>(u_{tt}=v^2(u_{xx}+u_{zz}))</span> (subscripts of the wavefield, <i>u</i>, are second derivatives in time and space) in a homogeneous medium, it did not provide the complete equation form, where the velocity term is represented by a coefficient rather than directly given by <span>(v^2)</span>. In this work, we redesign the framework, encoding both velocity information and candidate functional terms simultaneously. Thus, we use GA to simultaneously evolve the candidate functional and coefficient terms in the library. Also, we consider here the physics rationality and interpretability in the randomly generated potential wave equations, by ensuring that both-hand sides of the equation maintain balance in their physical units. We demonstrate this redesigned framework using the acoustic wave equation as an example, showing its ability to produce physically reasonable expressions of wave equations from noisy and sparsely observed data in both homogeneous and inhomogeneous media. Also, we demonstrate that our method can effectively discover wave equations from a more realistic observation scenario.</p>","PeriodicalId":49458,"journal":{"name":"Surveys in Geophysics","volume":"28 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142321266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Global Energy Balance as Represented in Atmospheric Reanalyses","authors":"Martin Wild, Michael G. Bosilovich","doi":"10.1007/s10712-024-09861-9","DOIUrl":"https://doi.org/10.1007/s10712-024-09861-9","url":null,"abstract":"<p>In this study, we investigate the representation of the global mean energy balance components in 10 atmospheric reanalyses, and compare their magnitudes with recent reference estimates as well as the ones simulated by the latest generation of climate models from the 6th phase of the coupled model intercomparison project (CMIP6). Despite the assimilation of comprehensive observational data in reanalyses, the spread amongst the magnitudes of their global energy balance components generally remains substantial, up to more than 20 Wm⁻² in some quantities, and their consistency is typically not higher than amongst the much less observationally constrained CMIP6 models. Relative spreads are particularly large in the reanalysis global mean latent heat fluxes (exceeding 20%) and associated intensity of the global water cycle, as well as in the energy imbalances at the top-of-atmosphere and surface. A comparison of reanalysis runs in full assimilation mode with corresponding runs constrained only by sea surface temperatures reveals marginal differences in their global mean energy balance components. This indicates that discrepancies in the global energy balance components caused by the different model formulations amongst the reanalyses are hardly alleviated by the imposed observational constraints from the assimilation process. Similar to climate models, reanalyses overestimate the global mean surface downward shortwave radiation and underestimate the surface downward longwave radiation by 3–7 Wm⁻²<i>.</i> While reanalyses are of tremendous value as references for many atmospheric parameters, they currently may not be suited to serve as references for the magnitudes of the global mean energy balance components.</p>","PeriodicalId":49458,"journal":{"name":"Surveys in Geophysics","volume":"18 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142276091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: Investigation of Fluid Types in Shale Oil Reservoirs","authors":"Xiaojiao Pang,&nbsp;Guiwen Wang,&nbsp;Lichun Kuang,&nbsp;Jin Lai,&nbsp;Nigel P. Mountney","doi":"10.1007/s10712-024-09851-x","DOIUrl":"10.1007/s10712-024-09851-x","url":null,"abstract":"","PeriodicalId":49458,"journal":{"name":"Surveys in Geophysics","volume":"45 5","pages":"1595 - 1600"},"PeriodicalIF":4.9,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142234213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Electromagnetic Subsurface Imaging in the Presence of Metallic Structures: A Review of Numerical Strategies","authors":"Octavio Castillo-Reyes,&nbsp;Pilar Queralt,&nbsp;Perla Piñas-Varas,&nbsp;Juanjo Ledo,&nbsp;Otilio Rojas","doi":"10.1007/s10712-024-09855-7","DOIUrl":"10.1007/s10712-024-09855-7","url":null,"abstract":"<div><p>Electromagnetic (EM) imaging aims to produce large-scale, high-resolution soil conductivity maps that provide essential information for Earth subsurface exploration. To rigorously generate EM subsurface models, one must address both the forward problem and the inverse problem. From these subsurface resistivity maps, also referred to as volumes of resistivity distribution, it is possible to extract useful information (lithology, temperature, porosity, permeability, among others) to improve our knowledge about geo-resources on which modern society depends (e.g., energy, groundwater, and raw materials, among others). However, this ability to detect electrical resistivity contrasts also makes EM imaging techniques sensitive to metallic structures whose EM footprint often exceeds their diminutive stature compared to surrounding materials. Depending on target applications, this behavior can be advantageous or disadvantageous. In this work, we review EM modeling and inverse solutions in the presence of metallic structures, emphasizing how these structures affect EM data acquisition and interpretation. By addressing the challenges posed by metallic structures, our aim is to enhance the accuracy and reliability of subsurface EM characterization, ultimately leading to improved management of geo-resources and environmental monitoring. Here, we consider the latter through the lens of a triple helix approach: physics behind metallic structures in EM modeling and imaging, development of computational tools (conventional strategies and artificial intelligence schemes), and configurations and applications. The literature review shows that, despite recent scientific advancements, EM imaging techniques are still being developed, as are software-based data processing and interpretation tools. Such progress must address geological complexities and metallic casing measurements integrity in increasing detail setups. We hope this review will provide inspiration for researchers to study the fascinating EM problem, as well as establishing a robust technological ecosystem to those interested in studying EM fields affected by metallic artifacts.</p></div>","PeriodicalId":49458,"journal":{"name":"Surveys in Geophysics","volume":"45 5","pages":"1627 - 1661"},"PeriodicalIF":4.9,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10712-024-09855-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142090217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding the Adjoint Method in Seismology: Theory and Implementation in the Time Domain","authors":"Rafael Abreu","doi":"10.1007/s10712-024-09847-7","DOIUrl":"10.1007/s10712-024-09847-7","url":null,"abstract":"<div><p>The adjoint method is a popular method used for seismic (full-waveform) inversion today. The method is considered to give more realistic and detailed images of the interior of the Earth by the use of more realistic physics. It relies on the definition of an adjoint wavefield (hence its name) that is the time-reversed synthetics that satisfy the original equations of motion. The physical justification of the nature of the adjoint wavefield is, however, commonly done by brute force with ad hoc assumptions and/or relying on the existence of Green’s functions, the representation theorem and/or the Born approximation. Using variational principles only, and without these mentioned assumptions and/or additional mathematical tools, we show that the time-reversed adjoint wavefield should be defined as a premise that leads to the correct adjoint equations. This allows us to clarify mathematical inconsistencies found in previous seminal works when dealing with viscoelastic attenuation and/or odd-order derivative terms in the equation of motion. We then discuss some methodologies for the numerical implementation of the method in the time domain and to present a variational formulation for the construction of different misfit functions. We here define a new misfit travel-time function that allows us to find consensus for the longstanding debate on the zero sensitivity along the ray path that cross-correlation travel-time measurements show. In fact, we prove that the zero sensitivity along the ray path appears as a consequence of the assumption on the similarity between data and synthetics required to perform cross-correlation travel-time measurements. When no assumption between data and synthetics is preconceived, travel-time Fréchet kernels show an extremum along the ray path as one intuitively would expect.</p></div>","PeriodicalId":49458,"journal":{"name":"Surveys in Geophysics","volume":"45 5","pages":"1363 - 1434"},"PeriodicalIF":4.9,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142042403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Review on Intelligent Recognition with Logging Data: Tasks, Current Status and Challenges","authors":"Xinyi Zhu,&nbsp;Hongbing Zhang,&nbsp;Quan Ren,&nbsp;Lingyuan Zhang,&nbsp;Guojiao Huang,&nbsp;Zuoping Shang,&nbsp;Jiangbing Sun","doi":"10.1007/s10712-024-09853-9","DOIUrl":"10.1007/s10712-024-09853-9","url":null,"abstract":"<div><p>Geophysical logging series are valuable geological data that record the physical and chemical information of borehole walls and in-situ formations, and are widely used by geologists for interpreting geological problems due to their continuity, high resolution, and ease of access. Recently, machine learning methods are gradually bringing data science and geoscience closer together, and Intelligent Recognition using Logging Data (IRLD) is increasingly becoming an important interpretation task. However, due to the specificity of geological information, relatively low data quality makes the direct application of machine learning models to IRLD often not optimal. And to the best of our knowledge, IRLDs are not highly generalizable and technical surveys are still lacking. Therefore, this paper presents a comprehensive review of IRLD. Specifically, after systematically reviewing geophysical well logging and machine learning techniques, the main applications and general processes for the cross-discipline task of IRLD are summarized. More importantly, the key challenges of IRLD in the four stages of data acquisition, feature engineering, model building, and practical application are discussed in this review. The potential risks of these challenges are visualized by using real logging data from a study area in the South China Sea and the example of a lithology identification task. For these challenges, we give the current state-of-the-art methods and feasible strategies in conjunction with published research. This comprehensive review is expected to provide insights for practitioners to construct more robust models and achieve more effective application results in IRLD.</p></div>","PeriodicalId":49458,"journal":{"name":"Surveys in Geophysics","volume":"45 5","pages":"1493 - 1526"},"PeriodicalIF":4.9,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141986606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decadal Variations in Equatorial Ellipticity and Principal Axis of the Earth from Satellite Laser Ranging/GRACE","authors":"Minkang Cheng","doi":"10.1007/s10712-024-09852-w","DOIUrl":"10.1007/s10712-024-09852-w","url":null,"abstract":"<div><p>The Earth exhibits an equatorial flattening specified by the ellipticity and the east longitude (or orientation) of the equatorial major axis, which is uniquely determined by the degree 2 and order 2 gravitational coefficients, <i>C</i>₂₂ and <i>S</i>₂₂. The 31-year SLR (satellite laser ranging) and 22-year GRACE/GRACE-FO (gravity recovery and climate experiment) data are analyzed to study the climate-related secular and 5.7 years to decadal variations in <i>C</i>₂₂ and <i>S</i>₂₂, in turn, the drift and decadal variation in the Earth’s equatorial ellipticity and orientation of the principal axis of the least moment of inertia. The effects of the surface floating mass changes (including atmosphere, ocean and surface water redistribution and the melting of the mountain and polar glaciers) and the interior fluid convective (Earth’s core flows) were evaluated. Results reveal that the equatorial ellipticity of the Earth is linearly increasing along with a remarkable decadal variation and the Earth’s equator is flattening by ~ 0.16 mm/yr.</p></div>","PeriodicalId":49458,"journal":{"name":"Surveys in Geophysics","volume":"45 5","pages":"1601 - 1626"},"PeriodicalIF":4.9,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141880215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trends and Variability in Earth’s Energy Imbalance and Ocean Heat Uptake Since 2005","authors":"Maria Z. Hakuba, Sébastien Fourest, Tim Boyer, Benoit Meyssignac, James A. Carton, Gaël Forget, Lijing Cheng, Donata Giglio, Gregory C. Johnson, Seiji Kato, Rachel E. Killick, Nicolas Kolodziejczyk, Mikael Kuusela, Felix Landerer, William Llovel, Ricardo Locarnini, Norman Loeb, John M. Lyman, Alexey Mishonov, Peter Pilewskie, James Reagan, Andrea Storto, Thea Sukianto, Karina von Schuckmann","doi":"10.1007/s10712-024-09849-5","DOIUrl":"https://doi.org/10.1007/s10712-024-09849-5","url":null,"abstract":"<p>Earth’s energy imbalance (EEI) is a fundamental metric of global Earth system change, quantifying the cumulative impact of natural and anthropogenic radiative forcings and feedback. To date, the most precise measurements of EEI change are obtained through radiometric observations at the top of the atmosphere (TOA), while the quantification of EEI absolute magnitude is facilitated through heat inventory analysis, where ~ 90% of heat uptake manifests as an increase in ocean heat content (OHC). Various international groups provide OHC datasets derived from in situ and satellite observations, as well as from reanalyses ingesting many available observations. The WCRP formed the GEWEX-EEI Assessment Working Group to better understand discrepancies, uncertainties and reconcile current knowledge of EEI magnitude, variability and trends. Here, 21 OHC datasets and ocean heat uptake (OHU) rates are intercompared, providing OHU estimates ranging between 0.40 ± 0.12 and 0.96 ± 0.08 W m⁻² (2005–2019), a spread that is slightly reduced when unequal ocean sampling is accounted for, and that is largely attributable to differing source data, mapping methods and quality control procedures. The rate of increase in OHU varies substantially between − 0.03 ± 0.13 (reanalysis product) and 1.1 ± 0.6 W m⁻² dec⁻¹ (satellite product). Products that either more regularly observe (satellites) or fill in situ data-sparse regions based on additional physical knowledge (some reanalysis and hybrid products) tend to track radiometric EEI variability better than purely in situ-based OHC products. This paper also examines zonal trends in TOA radiative fluxes and the impact of data gaps on trend estimates. The GEWEX-EEI community aims to refine their assessment studies, to forge a path toward best practices, e.g., in uncertainty quantification, and to formulate recommendations for future activities.</p>","PeriodicalId":49458,"journal":{"name":"Surveys in Geophysics","volume":"10 1","pages":""},"PeriodicalIF":4.6,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141790957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}