Surveys in Geophysics

This paper reviews the recent progress in our estimation of ocean dynamic topography and the derived surface geostrophic currents, mainly based on multiple nadir radar altimeter missions. These altimetric observations provide the cornerstone of our ocean circulation observing system from space. The largest signal in sea surface topography is from the mean surface dominated by the marine geoid, and we will discuss recent progress in observing the mean ocean circulation from altimetry, once the geoid and other corrections have been estimated and removed. We then address the recent advances in our observations of the large-scale and mesoscale ocean circulation from space, and the particular challenges and opportunities for new observations in the polar regions. The active research in the ocean barotropic tides and internal tidal circulation is also presented. The paper also addresses how our networks of global multi-satellite and in situ observations are being combined and assimilated to characterize the four-dimensional ocean circulation, for climate research and ocean forecasting systems. For the future of ocean circulation from space, the need for continuity of our current observing system is crucial, and we discuss the exciting enhancement to come with global wide-swath altimetry, the extension into the coastal and high-latitude regions, and proposals for direct total surface current satellites in the 2030 period.

Edge detection techniques for potential field data are effective methods for identifying local and regional geological boundaries. Numerous edge detectors (e.g., derivative-, ratio- and statistic-based methods) have been successively proposed and applied to different scenarios. However, these edge detectors show diverse results, which can confuse interpreters in their filter selection and interpretation schemes. To better understand the capabilities of various edge detection methods and avoid over-interpretation of artifacts, it requires a unified evaluation of different edge detectors with the same test models. In this view, we first present a brief review of the previous edge detection methods. Then, using gravity data as an example, we build 2.5D and 3D models to examine the boundary recognition capabilities of 28 edge detectors. Based on the model test results, we classify the existing edge detectors and discuss the similarities and discrepancies of different detectors. These comparisons help us to infer the optimal edge interpretation by integrating multiple results and screening for false appearances. Finally, we apply edge detection techniques to the earthquake-prone Molucca Sea region and present a refined tectonic boundary division, assisted by the focal-mechanism solutions. Besides, we identified four deep boundaries that may be associated with plate subduction. These boundaries correspond well to the source location of earthquakes at different depths; hence, five depth-dependent earthquake zones are partitioned. In addition to subduction, we suggest that the fault system also contributes to the present-day tectonic configuration around the Molucca Sea. The relationship between the earthquake activity near the subduction zones or faults and the boundaries derived from edge detection provides new insights to study multi-plate convergence using multiple observations.

The spherical shell and spherical zonal band are two elemental geometries that are often used as benchmarks for gravity field modeling. When applying the spherical shell and spherical zonal band discretized into tesseroids, the errors may be reduced or cancelled for the superposition of the tesseroids due to the spherical symmetry of the spherical shell and spherical zonal band. In previous studies, this superposition error elimination effect (SEEE) of the spherical shell and spherical zonal band has not been taken seriously, and it needs to be investigated carefully. In this contribution, the analytical formulas of the signal of derivatives of the gravitational potential up to third order (e.g., V , $$V_{z}$$ V z , $$V_{zz}$$ V zz , $$V_{xx}$$ V xx , $$V_{yy}$$ V yy , $$V_{zzz}$$ V zzz , $$V_{xxz}$$ V xxz , and $$V_{yyz}$$ V yyz ) of a tesseroid are derived when the computation point is situated on the polar axis. In comparison with prior research, simpler analytical expressions of the gravitational effects of a spherical zonal band are derived from these novel expressions of a tesseroid. In the numerical experiments, the relative errors of the gravitational effects of the individual tesseroid are compared to those of the spherical zonal band and spherical shell not only with different 3D Gauss–Legendre quadrature orders ranging from (1,1,1) to (7,7,7) but also with different grid sizes (i.e., $$5^{\circ }\times 5^{\circ }$$ 5 ∘ × 5 ∘ , $$2^{\circ }\times 2^{\circ }$$ 2 ∘ × 2 ∘ , $$1^{\circ }\times 1^{\circ }$$ 1 ∘ × 1 ∘ , $$30^{\prime }\times 30^{\prime }$$ 30 ′ × 30 ′ , and $$15^{\prime }\times 15^{\prime }$$ 15 ′ × 15 ′ ) at a satellite altitude of 260 km. Numerical results reveal that the SEEE does not occur for the gravitational components V , $$V_{z}$$ V z , $$V_{zz}$$ V zz , and $$V_{zzz}$$ V zzz of a spherical zonal band discretized into tesseroids. The SEEE can be found for the $$V_{xx}$$ V xx and $$V_{yy}$$ V yy , whereas the superposition error effect exists for the $$V_{xxz}$$ V xxz and $$V_{yyz}$$ V yyz of a spherical zonal band discretized into tesseroids on the overall average. In most instances, the SEEE occurs for a spherical shell discretized into tesseroids. In summary, numerical experiments demonstrate the existence of the SEEE of a spherical zonal band and a spherical shell, and the analytical solutions for a tesseroid can benefit the investigation of the SEEE. The single tesseroid benchmark can be proposed in comparison to the spherical shell and spherical zonal band benchmarks in gravity field modeling based on these new analytical formulas of a tesseroid.

This review paper reports on the state-of-the-art concerning observations of surface winds, waves, and currents from space and their use for scientific research and subsequent applications. The development of observations of sea state parameters from space dates back to the 1970s, with a significant increase in the number and diversity of space missions since the 1990s. Sensors used to monitor the sea-state parameters from space are mainly based on microwave techniques. They are either specifically designed to monitor surface parameters or are used for their abilities to provide opportunistic measurements complementary to their primary purpose. The principles on which is based on the estimation of the sea surface parameters are first described, including the performance and limitations of each method. Numerous examples and references on the use of these observations for scientific and operational applications are then given. The richness and diversity of these applications are linked to the importance of knowledge of the sea state in many fields. Firstly, surface wind, waves, and currents are significant factors influencing exchanges at the air/sea interface, impacting oceanic and atmospheric boundary layers, contributing to sea level rise at the coasts, and interacting with the sea-ice formation or destruction in the polar zones. Secondly, ocean surface currents combined with wind- and wave- induced drift contribute to the transport of heat, salt, and pollutants. Waves and surface currents also impact sediment transport and erosion in coastal areas. For operational applications, observations of surface parameters are necessary on the one hand to constrain the numerical solutions of predictive models (numerical wave, oceanic, or atmospheric models), and on the other hand to validate their results. In turn, these predictive models are used to guarantee safe, efficient, and successful offshore operations, including the commercial shipping and energy sector, as well as tourism and coastal activities. Long-time series of global sea-state observations are also becoming increasingly important to analyze the impact of climate change on our environment. All these aspects are recalled in the article, relating to both historical and contemporary activities in these fields.

The formation factor, which reflects the electrical conductivity of porous sediments and rocks, is widely used in a range of research fields. Consequently, given the discovery of numerous porous reservoir rocks and sediments exhibiting complex conductivity characteristics, methods to quantitatively predict the formation factor have been actively pursued by many scholars. Nevertheless, the agreement between the theoretically calculated and measured formation factors remains unsatisfactory, partially because the distribution characteristics of the entire pore space affect the final formation factor. In this study, a new method for characterizing the formation factor is proposed that considers the impacts of different complex pore structures on the conductivity of pores at different positions in the pore space. With this method, the electrical transmission through a rock can be accurately and quantitatively estimated based on the conductivity and shape of pores, the tortuous conductivity, and the classification of the pore space into conductive, weakly conductive, and nonconductive pores. By evaluating 24 datasets encompassing 7 types of rocks and sediments, including marine hydrate-bearing sediments and shale, the proposed model achieves remarkable agreement with the experimental data. These excellent confirmation results are attributed to the ubiquitous presence of weakly conductive and nonconductive pores in almost all rocks and sediments. Through further research based on this paper, an increasing number of adaptation models and a comprehensive set of evaluation methods can be developed.

Ground roll could seriously mask the useful reflection signals and decrease the signal-to-noise ratio (S/N) of seismic data, thereby affecting the subsequent seismic data processing. It is challenging for traditional methods to effectively extract high-fidelity reflection signals when ground roll noise and low-frequency reflection signals overlap in the frequency domain. We propose a fully convolutional framework with dense connections to attenuate ground roll (GRDNet) in land seismic data. GRDNet mainly consists of four blocks, which are convolutional, dense, transition down, and transition up blocks. The dense block consists of several convolution blocks to extract the waveform features of the seismic data. The short-long connection in the dense block and the skip connection in the encoder-decoder not only reuses the features extracted by the previous layer but also adds constraints other than the loss function to each convolution block. The well-trained network is tested on one synthetic data and two real land seismic datasets containing strong ground roll with linear and hyperbolic moveouts, respectively. Three traditional and two state-of-the-art deep learning (DL) methods are used as benchmarks to compare denoising performance with GRDNet. The testing results show that the proposed method can effectively attenuate the ground roll in seismic data and preserve useful reflection signals.

Permafrost is a sub-ground phenomenon and therefore cannot be directly observed from space. It is an Essential Climate Variable and associated with climate tipping points. Multi-annual time series of permafrost ground temperatures can be, however, derived through modelling of the heat transfer between atmosphere and ground using landsurface temperature, snow- and landcover observations from space. Results show that the northern hemisphere permafrost ground temperatures have increased on average by about one degree Celsius since 2000. This is in line with trends of permafrost proxies observable from space: surface water extent has been decreasing across the Arctic; the landsurface is subsiding continuously in some regions indicating ground ice melt; hot summers triggered increased subsidence as well as thaw slumps; rock glaciers are accelerating in some mountain regions. The applicability of satellite data for permafrost proxy monitoring has been demonstrated mostly on a local to regional scale only. There is still a lack of consistency of acquisitions and of very high spatial resolution observations. Both are needed for implementation of circumpolar monitoring of lowland permafrost. In order to quantify the impacts of permafrost thaw on the carbon cycle, advancement in wetland and atmospheric greenhouse gas concentration monitoring from space is needed.

We study the anelastic properties (attenuation and velocity dispersion) of surface waves at an interface between a finite water layer and a porous medium described by Biot theory including the frequency-dependent effects due to mesoscopic flow. A closed-form dispersion equation is derived, based on potential functions and open and sealed boundary conditions (BC) at the interface. The analysis indicates the existence of high-order surface modes for both BCs and a slow true surface mode only for sealed BC. The formulation reduces to two particular cases in the absence of water and with infinite-thickness water layer, with the presence of pseudo-versions of Rayleigh and Stoneley waves. The mesoscopic flow affects the propagation of all the pseudo-surface waves, causing significant velocity dispersion and attenuation, whereas the effect of the BC is mainly evident at high frequencies, due to the presence of the slow Biot wave. The mesoscopic-flow peak moves to low frequencies as the thickness of the water layer increases. In all cases, the true surface wave resembles the slow P2 wave, and is hardly affected by the flow.

Least-squares migration (LSM) is a data-fitting imaging approach seeking the seismic reflectivity image of the most accurate amplitude and optimal resolution. However, the high computational cost of LSM has hindered its broad application. In this study, we combine a convolutional neural network (CNN) with LSM to significantly improve the computational efficiency while retaining the imaging quality. Taking CNN as a “projector,” we treat LSM as the “projection” from the ordinarily migrated images to the least-squares updated images. We conduct this CNN-assisted LSM in the shot gather domain using a Gaussian beam migration and the corresponding LSM. The training data for CNN consist of 10–15% of all shot gathers, with the Gaussian beam migrated shot gathers as the input and the LSM shot gathers as the target. After the training, the processing time for the remaining shot gathers took several minutes for 2D cases. The results from testing with the Sigsbee 2B synthetic dataset and a field marine dataset indicate the CNN-assisted LSM saved 80–90% of the computation time of the full LSM and achieved significantly higher image fidelity than that of the ordinary migration.

We integrate multicomponent seismic data with geoelectrical data to perform an in-depth characterization of the shallow sediments in a very heterogenous area. Specifically, we perform first-break tomography, multichannel analysis of surface-waves and seismic reflection imaging on an unusual dataset. The dataset is unusual as the P-,SH_ and SV- wavefields were acquired and processed seperately. The results were then quatitatively integrated with those of the electrical resistivity tomography in a petrophysical inversion to compute porosity, saturation, resistivity and clay content.

Based on a brief review of forward algorithms for the computation of topographic gravitational and magnetic effects, including spatial, spectral and hybrid-domain algorithms working in either Cartesian or spherical coordinate systems, we introduce a new algorithm, namely the CP-FFT algorithm, for fast computation of terrain-induced gravitational and magnetic effects on arbitrary undulating surfaces. The CP-FFT algorithm, working in the hybrid spatial-spectral domain, is based on a combination of CANDECOMP/PARAFAC (CP) tensor decomposition of gravitational integral kernels and 2D Fast Fourier Transform (FFT) evaluation of discrete convolutions. By replacing the binomial expansion in classical FFT-based terrain correction algorithms using CP decomposition, convergence of the outer-zone computation can be achieved with significantly reduced inner-zone radius. Additionally, a Gaussian quadrature mass line (GQML) model is introduced to accelerate the computation of the inner zone effect. We validate our algorithm by computing the gravitational potential (GP), the gravitational vector (GV), the gravity gradient tensor (GGT), and magnetic fields caused by denselysampled topographic and bathymetric digital elevation models (DEMs) of selected mountainous areas around the globe. Both constant and variable density/magnetization models, with computation surfaces on, above and below the topography are considered. Comparisons between our new method and space-domain rigorous solutions show that with modeling errors well below existing instrumentation error levels, the calculation speed is accelerated thousands of times in all numerical tests. We release a set of open-source code written in MATLAB language to meet the needs of geodesists and geophysicists in related fields to carry out more efficiently topographic modeling in Cartesian coordinates under planar approximation.

We study the reflection and transmission (R/T) characteristics of inhomo�geneous plane waves at the interface between two dissimilar fluid-saturated thermo�poroelastic media at arbitrary incidence angles. The R/T behaviors are formulated based on the classic Lord-Shulman (LS) and Green-Lindsay (GL) heat-transfer models as well as a generalized LS model, respectively. The latter results from different values of the Maxwell-Vernotte-Cattaneo relaxation times. These thermoporoelastic models can predict three inhomogeneous longitudinal (P1, P2, and T) waves and one shear (S) wave. We first compare the LS and GL models for the phase velocities and attenuation coefficients of plane waves, where the homogeneous wave has a higher velocity but weaker thermal attenuation than the inhomogeneous wave. Considering the oil-water contact, we investigate R/T coefficients associated with phase angles and energy ratios, which are formulated in terms of incidence and inhomogeneity angles, with the latter having a significant effect on the interference energy. The proposed thermoporoelastic R/T model predicts different energy partitions between the P and S modes especially at the critical angle and near grazing incidence. We observe the anomalous behav�ior for an incident P wave with the inhomogeneity angle near the grazing incidence. The energy partition at the critical angle is mainly controlled by relaxation times and boundary conditions. Beyond the critical angle, the energy flux predicted by the Biot poroelastic and LS models vanishes vertically, becoming the opposite for the GL and generalized LS models. The resulting energy flux shows a good agreement with the R/T coefficients, and they are well proven by the conservation of energy, where the results are valuable for the exploration of thermal reservoirs.

The launch of gravity-dedicated satellite missions at the beginning of the new millennium led to an accuracy improvement of global Earth gravity field models (GGMs). One of these missions was the Gravity field and steady-state Ocean Circulation Explorer (GOCE) launched in 2009. As the first European Space Agency’s Earth Explorer Mission, the satellite carried a novel instrument, a 3-D gradiometer, which allowed measurement of the second-order directional derivatives of the gravitational potential (gravitational gradients) with a uniform quality and a near-global coverage. The main mission goal was to determine the static Earth’s gravity field with the ambitious precision of 1-2 cm in terms of geoid heights and 1 mGal in terms of gravity anomalies for spatial resolution of 100 km (half wavelength at the equator). More than three years of the outstanding measurements resulted in three levels of data products (Level 0, Level 1b and Level 2), six releases of GGMs, and several global grids of gravitational gradients. The grids, which represent a step between gravitational gradients measured directly along the GOCE orbit and those represented by GGMs, found their usage mainly in geophysical applications. In this contribution, we validate the official Level 2 product GRD_SPW_2 using height anomalies over two test areas located in central and northern Europe (Czechia/Slovakia and Norway). A mathematical model based on the least-squares spectral weighting is employed with corresponding spectral weights estimated for validation of gravitational gradient grids. This model continues gravitational gradients from the mean orbital altitude of GOCE down to the irregular Earth’s surface (not to a sphere) and transforms them to height anomalies in one computational step. Analytical downward continuation errors of the model are estimated using a closed-loop test. Prior to the comparison of height anomalies estimated from gravitational gradients with their reference values derived from Global Navigation Satellite Systems (GNSS)/levelling over the two test areas, the gravitational gradients and reference data are corrected for all systematic effects such as the tide system conversion. Moreover, the high-frequency part of the gravitational signal is estimated and subtracted from reference data as it is attenuated in the gravitational gradients measured by GOCE. A relative improvement between the release 6 and release 2 gradient grids reaches 48%\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\%$$\end{document} in terms of height anomalies in Czechia/Slovakia. The relative improvement in Norway is even more significant and reaches 55%\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\%$$\end{document}. The release 6 of the official Level 2 product GRD_SPW_2 gained the absolute accuracy with the standard deviation of 8.7 cm over Czechia/Slovakia and 9.3 cm over Norway.

Shallow-seismic full-waveform inversion (FWI) provides an effective way for the accurate reconstruction of near-surface models. The common 2D shallow-seismic FWI inverts either individual Rayleigh or Love waves, and the joint FWI of Rayleigh and Love waves can further improve the reliability of the result. Conventionally, FWI is formulated as a single-objective inverse problem and is solved with deterministic optimization algorithms. It suffers from a relatively high level of ill-posedness and high computational cost, which are two of the main problems that FWI faces. Recently, a random-objective waveform inversion (ROWI) method is proposed to mitigate these problems. ROWI reformulates waveform inversion as a multi-objective inverse problem and solves it with a stochastic optimization algorithm. The multi-objective framework and the stochastic nature provide ROWI relatively high freedom in searching for the optimal model and therefore improve its robustness against the poor initial model. In this paper, we perform a comprehensive comparison between the performance of shallow-seismic FWI and ROWI for the reconstruction of near-surface models. We compare their performance in the scenario of individual inversion of Rayleigh wave, individual inversion of Love wave, and joint inversion of both wave types. Besides, we also compare their effectiveness when using good and poor initial models. Synthetic examples of a highly heterogeneous model show that ROWI is more efficient and more robust than FWI in both individual and joint inversions. The individual ROWI of Love wave can reconstruct the model more efficiently than Rayleigh wave if a good initial model is available, and the other way around if a poor initial model is provided. The joint inversion, in both FWI and ROWI, outperforms the individual inversion of a single wave type. In both individual and joint inversions, ROWI is more efficient in reducing model error and more robust against the poor initial model than FWI. We also compare the performance of ROWI and FWI by using field data sets acquired in Rheinstetten, Germany. The results show that when a good initial model is available, both FWI and ROWI can nicely reconstruct the main structure of the subsurface model. The validity of the reconstructed model is proved by comparing it to a migrated ground-penetrating radar profile. ROWI can consistently reconstruct the model to a good level even when using a poor initial model, while the individual and joint FWIs fail to work when the initial model is poor. It confirms the relatively higher efficiency and robustness of ROWI than FWI in the reconstruction of near-surface models.

Modelling the response of seismic wavefields to sharp lateral variations in crustal discontinuities is essential for seismic tomography application and path effects correction in earthquake source characterization. This is particularly relevant when wavefields cross back-arc oceanic basins, i.e. mixed continental-oceanic settings. High-frequency (>0.05 Hz) seismic waves resonate and get absorbed across these settings due to a shallow Moho, crustal heterogeneities, and energy leakage. Here, we provide the first high-frequency wave-equation model of full seismograms propagating through realistic 3D back-arc basins. Inversion by parameters trial based on correlation analyses identifies P-, S- and coda-wave as attributes able to estimate jointly 3D Moho variations, sediment thickness, and earthquake source characteristics using data from a single regional earthquake. We use as data waveforms produced by the Accumoli earthquake (Central Italy, 2016), propagating across the Southern Tyrrhenian basin and recorded across Southern Italy. The best model comprises a deep Moho (∼\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sim$$\end{document}18 km) in the middle of the basin and a crustal pinch with the continental crust in Sicily. The deep Moho corresponds to the Issel Bridge, a portion of continental crust trapped between the Vavilov and Marsili volcanic centres. The Accumoli earthquake is optimally described at a depth of 7.3 km using a boxcar with rise time of 6 s. Our results show that the early S-wave coda comprises trapped and reverberating phases sensitive to crustal interfaces. Forward modelling these waves is computationally expensive; however, adding these attributes to tomographic procedures allows modelling both source and structural parameters across oceanic basins.

Passive surface wave methods are non-invasive, low-cost, and robust approaches to image near-surface shear-wave velocity (Vs) structure using passive seismic sources. A clean and high-resolution dispersion image is critical for surface wave analysis. In practice, however, artifacts or aliasing are almost inevitable in passive surface wave dispersion measurements and seriously pollute the measured dispersion spectra. It is significant to clarify how they are generated, how they affect the dispersion measurement, and how they can be attenuated. We provide the first comprehensive review on artifacts that are frequently observed in high-frequency (>1 Hz) passive surface wave dispersion measurements and summarize them into two general groups: geometry-related artifacts and source-related artifacts. Mathematical derivations and numerical as well as field examples are presented to explain the underlying physics of various artifacts and explore potential solutions and guidelines to attenuate them before and after field observations. This work will help the reader understand the complexity of the measured dispersion spectra and lead to improvements on rapidly advancing passive surface wave methods.

In the past twenty years, satellite gravimetry missions have successfully provided data for the determination of the Earth static gravity field (GOCE) and its temporal variations (GRACE and GRACE-FO). In particular, the possibility to study the evolution in time of Earth masses allows us to monitor global parameters underlying climate changes, water resources, flooding, melting of ice masses and the corresponding global sea level rise, all of which are of paramount importance, providing basic data on, e.g. geodynamics, earthquakes, hydrology or ice sheets changes. Recently, a large interest has developed in novel technologies and quantum sensing, which promise higher sensitivity, drift-free measurements, and higher absolute accuracy for both terrestrial surveys and space missions, giving direct access to more precise long-term measurements. Looking at a time frame beyond the present decade, in the MOCAST+ study (MOnitoring mass variations by Cold Atom Sensors and Time measures) a satellite mission based on an “enhanced” quantum payload is proposed, with cold atom interferometers acting as gravity gradiometers, and atomic clocks for optical frequency measurements, providing observations of differences of the gravitational potential. The main outcomes are the definition of the accuracy level to be expected from this payload and the accuracy level needed to detect and monitor phenomena identified in the Scientific Challenges of the ESA Living Planet Program, in particular Cryosphere, Ocean and Solid Earth. In this paper, the proposed payload, mission profile and preliminary platform design are presented, with end-to-end simulation results and assessment of the impact on geophysical applications.

Obtaining accurate subsurface Q (quality factor) models using full-waveform inversion (FWI) methods remains a challenging task. The forward modeling problem of viscoelastic wave propagation can be solved by superimposing N rheological bodies of Maxwell or Zener type with generalized standard linear solid rheology. However, different approaches were proposed to calculate the attenuation sensitivity kernels in viscoelastic FWI. This study reviews and compares previous theories for constructing the viscoelastic sensitivity kernels. Furthermore, we derive the viscoelastic sensitivity kernels directly following the adjoint-state (or Lagrangian multiplier) method. Compared to previous approaches, we reveal that the Q sensitivity kernels can be calculated with adjoint memory strain variables. In the numerical experiments, different methods are used to calculate the viscoelastic sensitivity kernels for comparison. We have found that when simultaneously inverting for velocity and Q models, these methods can provide inversion results of comparable quality. However, in the event of inaccurate velocity structures, the Q sensitivity kernels calculated with memory strain variables can resolve the Q anomalies more clearly, while suffering from fewer parameter trade-offs.

Precise orbits of altimetry satellites are a prerequisite for the investigation of global, regional, and coastal sea levels together with their changes, since accurate satellite positions in the radial direction are required for the reliable determination of the water surface height (distance between the altimeter position in space and the water surface). Significant progress in the improvement of altimetry satellite orbit quality has been achieved in the last 30 years increasing the orbit accuracy in the radial direction from decimeter to centimeter and even sub-centimeter level. That was possible due to the improvements in the modeling of Earth’s time variable gravity field, ocean tides, terrestrial and celestial reference frames, but also due to the accomplishments reached in the observation methods used for altimetry satellites, namely Satellite Laser Ranging (SLR), Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS), and Global Positioning System (GPS—used for some satellites). In this paper, we review the main improvements in the models used for the determination of orbits of altimetry satellites, namely, in so called Geophysical Data Records (GDR) orbit standards from GDR-C to Precise Orbit Ephemeris-F (POE-F), illustrate the impact of the improvements in precise orbit determination of these satellites on the orbit accuracy in the radial direction. Additionally we investigate orbit differences in the radial direction, single-satellite crossover differences, radial, and geographically correlated orbit errors of contemporary orbits of various altimetry satellites namely Cryosat-2, Envisat, ERS-1, ERS-2, Jason-1, Jason-2, Jason-3, SARAL, Sentinel-3A, Sentinel-3B, and TOPEX/Poseidon derived by different institutions.

The amplitude-variation-with-angle (AVA) inversion for seismic data has been widely used for hydrocarbon detection in exploration seismology. Traditional AVA inversion quantitatively estimates high-resolution elastic parameters, i.e., P-wave velocity, S-wave velocity and density, from migrated seismic gathers by solving either a linear or nonlinear inverse problem. It is commonly an ill-posed problem and the inversion accuracy depends on initial models. Recently, deep learning has been introduced into the AVA inversion by building a complicated nonlinear relation between seismic data and elastic parameters based on the training on a large amount of labeled data. The performance of the deep-learning-based inversion is determined by the diversity of training datasets. Because of sparse well locations, the application of deep-learning-based AVA inversion is limited by well-log label sets in production. To mitigate this problem, we present an intelligent AVA inversion method using a convolutional neural network trained by realistic pseudo-well logs. By considering spatial and inter-parameter correlation of elastic parameters, we first generate a large number of realistic pseudo-well logs based on Monte Carlo simulation. Then, angle-domain common-image gathers are computed by convolving a source wavelet with angle-dependent reflectivity series, which are used to train a convolutional neural network (CNN) to predict elastic parameters. In this study, we introduce two CNN frameworks to investigate the feasibility of the proposed pseudo-well-based CNN AVA inversion method using both synthetic and field data. We also compare the proposed CNN-based AVA inversion method with traditional linear and nonlinear inversion methods constrained by prior knowledge in terms of efficiency and accuracy. The results of synthetic data show that the pseudo-well-based CNN AVA inversion method can accurately and efficiently estimate P-wave velocity, S-wave velocity and density, and has a potential to reduce inter-parameter crosstalk artifacts. In the tests of field data, because of inaccurate background velocity models and noisy angle-domain gathers, the accuracy of CNN prediction results is not as high as in synthetic example. However, the pseudo-well-based CNN AVA inversion method still has better performance to reduce inter-parameter crosstalk artifacts and requires less computing time than traditional AVA inversion method.

Africa is particularly vulnerable to climate change impacts, which threatens food security, ecosystem protection and restoration initiatives, and fresh water resources availability and quality. Groundwater largely contributes to the mitigation of climate change effects by offering short- to long-term transient water storage. However, groundwater storage remains extremely difficult to monitor. In this paper, we review the strengths and weaknesses of satellite remote sensing techniques for addressing groundwater quantity issues with a focus on GRACE space gravimetry, as well as concepts to combine satellite observations with numerical models and ground observations. One particular focus is the quantification of changes in groundwater resources in the different climatic regions of Africa and the discussion of possible climatic and anthropogenic drivers. We include a thorough literature review on studies that use satellite observations for groundwater research in Africa. Finally, we identify gaps in research and possible future directions for employing satellite remote sensing to groundwater monitoring and management on the African continent. Article Highlights Overview on the distribution and characteristics of African groundwater resources including future projections Combination of satellite and in situ observations with numerical models allows us to obtain a synoptic view of groundwater-related processes Summary of current concepts and achievements of satellite remote sensing-based groundwater monitoring and decision making over Africa

Coastal regions (including estuaries and deltas) are very complex environments with diverse hydrodynamic and bio-geomorphological contexts and with important socio-economic and ecological problems. These systems are among the most affected by human impact through urbanization and port activities, industrial and tourism activities. They are directly affected by the impact of climate change on sea level, storm surges frequency and strength, as well as recurrence of coastal river floods. A sustainable future for coastal zones depends on our capacity to implement systematic monitoring with focus on: (1) forcings affecting coastal zones at different spatio-temporal scales (sea level rise, winds and waves, offshore and coastal currents, tides, storm surges, river runoff in estuaries and deltas, sediment supply and transport, vertical land motions and land use); (2) morphological response (e.g., shoreline migration, topographical changes). Over the last decades, remote sensing observations have contributed to major advances in our understanding of coastal dynamics. This paper provides an overview of these major advances to measure the main physical parameters for monitoring the coastal, estuarine and delta environments and their evolution, such as the water level and hydrodynamics near the shoreline, water/sediment contact (i.e., shoreline), shoreline position, topography, bathymetry, vertical land motion, bio-physical characteristics of sediments, water content, suspended sediment, vegetation, and land use and land cover.

Seismic anisotropy tomography is the updated geophysical imaging technology that can reveal 3-D variations of both structural heterogeneity and seismic anisotropy, providing unique constraints on geodynamic processes in the Earth’s crust and mantle. Here we introduce recent advances in the theory and application of seismic anisotropy tomography, thanks to abundant and high-quality data sets recorded by dense seismic networks deployed in many regions in the past decades. Applications of the novel techniques led to new discoveries in the 3-D structure and dynamics of subduction zones and continental regions. The most significant findings are constraints on seismic anisotropy in the subducting slabs. Fast-velocity directions (FVDs) of azimuthal anisotropy in the slabs are generally trench-parallel, reflecting fossil lattice-preferred orientation of aligned anisotropic minerals and/or shape-preferred orientation due to transform faults produced at the mid-ocean ridge and intraslab hydrated faults formed at the outer-rise area near the oceanic trench. The slab deformation may play an important role in both mantle flow and intraslab fabric. Trench-parallel anisotropy in the forearc has been widely observed by shear-wave splitting measurements, which may result, at least partly, from the intraslab deformation due to outer-rise yielding of the incoming oceanic plate. In the mantle wedge beneath the volcanic front and back-arc areas, FVDs are trench-normal, reflecting subduction-driven corner flows. Trench-normal FVDs are also revealed in the subslab mantle, which may reflect asthenospheric shear deformation caused by the overlying slab subduction. Toroidal mantle flow is observed in and around a slab edge or slab window. Significant azimuthal and radial anisotropies occur in the big mantle wedge beneath East Asia, reflecting hot and wet upwelling flows as well as horizontal flows associated with deep subduction of the western Pacific plate and its stagnation in the mantle transition zone. The geodynamic processes in the big mantle wedge have caused craton destruction, backarc spreading, and intraplate seismic and volcanic activities. Ductile flow in the middle-lower crust is clearly revealed as prominent seismic anisotropy beneath the Tibetan Plateau, which affects the generation of large crustal earthquakes and mountain buildings.

Land water storage plays a key role for the Earth’s climate, natural ecosystems, and human activities. Since the launch of the first Gravity Recovery and Climate Experiment (GRACE) mission in 2002, spaceborne observations of changes in terrestrial water storage (TWS) have provided a unique, global perspective on natural and human-induced changes in freshwater resources. Even though they have become much used within the broader Earth system science community, space-based TWS datasets still incorporate important and case-specific limitations which may not always be clear to users not familiar with the underlying processing algorithms. Here, we provide an accessible and illustrated overview of the measurement concept, of the main available data products, and of some frequently encountered technical terms and concepts. We summarize concrete recommendations on how to use TWS data in combination with other hydrological or climatological datasets, and guidance on how to avoid possible pitfalls. Finally, we provide an overview of some of the main applications of GRACE TWS data in the fields of hydrology and climate science. This review is written with the intention of supporting future research and facilitating the use of satellite-based terrestrial water storage datasets in interdisciplinary contexts.

This article reviews the state of the art in the use of space-borne observations for analyzing extreme rainfall and flood events in Africa. Floods occur across many space and timescales, from very localized flash flood events to slow propagation of discharge peaks in large rivers. We discuss here how satellite data can help us understand the genesis and impacts of these flood events, monitor their evolution, and better constrain prediction models, thereby improving early warning and population protection. To illustrate these topics, we reanalyze major flood events that occurred in Niger, Mozambique, Central African Republic and Ivory Coast, using satellite information.

The acoustic behavior in fluid attenuating media can be effectively simulated using a fractional Zener model (FZM). Because of the fractional time derivatives of both stress and strain in the constitutive relationship, this mechanism is very realistic and flexible in describing seismic attenuation. However, using conventional FZM wave equations to propagate seismic waves requires storing large amounts of previous wavefield information to calculate the fractional time derivatives, which is unacceptable in practice. In this paper, we derive a new time-domain viscoacoustic wave equation in the framework of the FZM. This new equation does not contain any fractional time derivatives; thus, it is more economical in computational costs. Furthermore, the amplitude attenuation and phase dispersion effects are separated in the newly proposed equation, which is very favorable to compensate for energy loss and correct phase dispersion in reverse-time migration. To improve the accuracy, we incorporate a wave number (k)-space operator into the decoupled FZM wave equation to compensate for temporal dispersion errors caused by the second-order finite-difference discretization. Therefore, a high-temporal-accuracy viscoacoustic wave equation is derived to simulate nearly constant-Q wavefields in attenuating media. In the implementation, a low-rank decomposition method is introduced to solve the mixed-domain operators. Numerical analysis and modeling results demonstrate the effectiveness and applicability of the proposed method for simulating the decoupled viscoacoustic wavefield with high accuracy.

Rank-reduction methods are effective for separating random noise from the useful seismic signal based on the truncated singular value decomposition (TSVD). However, the results that the TSVD operator provides are still a mixture of noise and signal subspaces. This problem can be solved using the damped rank-reduction method by damping the singular values of noise-contaminated signals. When the seismic data include highly curved events, the rank should be large enough to preserve the details of the useful signal. However, the damped rank-reduction operator becomes less powerful when using a large rank parameter. Hence, the denoised data contain significant remaining noise. More recently, the optimally damped rank-reduction method has been proposed to solve the extra noise problem as the rank value ncreases. The optimally damped rank-reduction operator works well for a moderately large rank but becomes ineffective for a very large rank. We introduce an adaptive damped rank-reduction algorithm to attenuate the residual noise for a very large rank parameter. To elaborate on the proposed algorithm, we first construct a gain matrix by only using the input rank parameter, which we introduce directly into the adaptive singular-value weighting formula to make it more stable as the rank parameter becomes too large. Then, we derive a damping operator based on the improved optimal weighting operator to attenuate the residual noise. The proposed method, which can be regarded as an improved version of the optimally damped rank-reduction method, is insensitive to the input parameter. Examples of synthetic and real three-dimensional seismic data show the denoising improvement using the proposed method.

Groundwater exploration is the most promising way to overcome water scarcity in hyper-arid regions around the world. Due to the scarcity of hydrogeological information in these regions, groundwater exploration is a challenging issue requiring the joint application of satellite and land-based information to delineate the groundwater aquifers in such harsh environments. In this research, an integrative approach was undertaken for groundwater exploration in the southwestern corner of Egypt as one of the most hyper-arid regions in North Africa. To fill the knowledge gap in this large area, two high-resolution satellite gravity datasets (EIGEN-6C4 and TOPEX-1min) were employed in combination with land-based geophysical surveys for a better understanding of groundwater potentialities in terms of structural controls. Further, the approaches of high-pass filter, tilt angle derivative, and enhanced horizontal gradient amplitude were used to analyze EIGEN-6C4 dataset. Additionally, 2D and 3D models along with a high-pass filtered gravity map were constructed to provide the subsurface barriers and preferential groundwater flow pathways. Several NNE windows have been recognized, particularly to the east of Gabel Kamel along Uweinat-Aswan uplifting allowing groundwater flow along northeastern structural trends. To verify this assumption, land-based magnetic and DC resistivity sounding surveys were executed at two selected sites based on the interpretation of satellite gravity and remote sensing data. The resistivity and 2D magnetic modeling reveal the presence of remarkable sub-basins with sufficient saturated sedimentary cover. Ultimately, the review of the different datasets, including satellite gravity and land-based geophysical investigations, facilitated the geological interpretation for detecting the structural controls on the groundwater flow paths and produced satisfactory results at shorter time frames and lower costs compared to typical groundwater exploration in arid or hyper-arid regions of the same characteristics elsewhere.

The Hunga Tonga-Hunga Ha'apai (HTHH) underwater volcano triggered giant atmospheric shock waves propagating around the world. These shock waves were the major factor for the changes in numerous geophysical parameters. A novel multi-instrumental array is located ~ 10,275 km northwest of the HTHH volcano. Most instruments of the array were installed within ~ 400 m 2 for monitoring vibrations and perturbations in the lithosphere, atmosphere , and ionosphere. The multiple instruments captured the eruption-associated disturbances with various scales ranging from minutes to hours over the certain location, simultaneously, which offer an excellent opportunity for investigating the geosphere coupling. The primary phenomena of the eruption-associated disturbances are the long-period changes (period of ~ 2 h) in the ionospheric total electron content (TEC) and the magnetic field in the upper atmosphere (above 100 km altitude), indicating the interactions of the ionospheric electrodynamics. The secondary phenomena included the wind disturbances at ~ 3000 m altitude, which contribute to short-period changes (periods of up to ten minutes) in air pressure, ground vibrations, and atmospheric electric field. The near-surface disturbances propagate upward with a near acoustic speed that causes short-period variations in the geomagnetic field and TEC. The primary changes in ionospheric electrodynamics, wind disturbance in the lower atmosphere, and its upward propagation , as well as the resonance, enrich our understanding of the geosphere coupling.

Near-surface geophysical techniques are useful for the characterization of archaeological areas because of their ability to rapidly cover wide extensions and obtain high-resolution data to identify the location for archaeological excavations. However, in hyperarid environments usual geophysical techniques may fail to obtain the expected results due to the dry near surface. This study proposes an integration of ground penetrating radar (GPR) and electromagnetic induction (EMI) techniques, to elucidate the origin of thousands of aligned circular features located at the Iluga archaeological area emplaced on one of the driest places on Earth (Pampa del Tamarugal, Atacama Desert). The GPR was useful to recognize alluvial deposits, sandy aeolian filling in pre-existing holes and roots right underneath circular features. Magnetic susceptibility data derived from the EMI in-phase component, usually considered a complementary result, were useful to identify fireplaces in the vicinity of the alignments. These geophysical findings were verified with an archaeological excavation. It has been found that circular features resulted from an extensive deforestation process in the Pampa del Tamarugal, consisting in the extraction of both trunk and roots of algarrobos (Prosopis chilensis) or tamarugos (Prosopis tamarugo), likely for recent charcoal production. The proposed methodology delivers promising results for archaeological and shallow geological studies in hyperarid and dry environments.

The ability to map floods from satellites has been known for over 40 years. Early images of floods were rather difficult to obtain, and flood mapping from satellites was thus rather opportunistic and limited to only a few case studies. However, over the last decade, with a proliferation of open-access EO data, there has been much progress in the development of Earth Observation products and services tailored to various end-user needs, as well as its integration with flood modeling and prediction efforts. This article provides an overview of the use of satellite remote sensing of floods and outlines recent advances in its application for flood mapping, monitoring and its integration with flood models. Strengths and limitations are discussed throughput, and the article concludes by looking at new developments.

Potential field filters are widely used in exploration and interpretation of geologic structures, archaeological sites, hazards assessment, and in engineering and environmental studies. There are countless filters and attributes and their number keeps growing: directional, horizontal and vertical derivatives; analytic, monogenic and direct analytic signals; modules; local phase; tilt angle; azimuth; local (horizontal, vertical and total) wavenumbers; theta function; high order derivatives; enhancements; normalizations. Furthermore, almost all of these filters can be applied to other filters—often named with overwhelming acronym combinations making it almost impossible to keep up with the particular and general development of this field. In this work, we present a review of more than 200 publications and compile more than 50 proposed methods in a unified mathematical framework, and an easy-to-follow notation. We asses all the methods, their definitions, connections, variations, redundancies and limitations, including a vast list of references and some historical notes. We improve and amend some points—regarding not only its mathematical applications but also the attributions that correspond to each method. We also establish connections with other fields of research—seismics, mathematics, image analysis—in which the same or similar techniques are used, but have remained isolated and unknown to each other.

West African rainfall is an important part of the global climate system that influences the Atlantic thermohaline circulation, hurricane activities, and dust transport. The water cycle is linked to the monsoon and its interannual to decadal variations. Over the past decades, West Africa has seen major climate variability with extended droughts that had negative effects during the 1970s and 1980s. Indeed, when it is too scarce, rain causes shortages, reduces agricultural yields, and leads to migrations. On the other hand, when it is too abundant, it causes catastrophic floods and poses threats to populations, water resources as well as natural and farmlands. In this paper, drought is considered as part of climate-related hazards and one of the main hydrometeorological extreme events occurring in West Africa. The exposure to drought has made the region more vulnerable. Thus, two sites, namely the Niger river basin and the Bandama watershed (Côte d’Ivoire), are studied in this paper to review and analyze the weather and climate extreme events that affect vast areas of West Africa. Grounded in remote sensing, statistical, and socio-anthropological approaches, this work first reviews drought as observed from space; then assesses rainfall and evapotranspiration between 1970 and 2013 as indicators of risks of water resources scarcity in the hydro-system of the Bandama river in Côte d'Ivoire. The results reveal that the West African region is highly vulnerable to this hydrometeorological extreme event with heavy impacts on people and the economy due to a large dependency on rainfed agriculture. Thus, planning and management of drought require a change of paradigm. In addition, more comprehensive studies on hydrometeorological extreme events are necessary and policies must be better designed to significantly improve the tackling of droughts with better mitigation strategies.

The effect of stress on wave propagation in fluid-saturated porous thermoelastic media is poorly understood. To fill this gap, we propose the dynamical equations for stressed fluid-saturated porous thermoelastic media based on the poroacoustoelasticity model and porothermoelasticity model to describe the effect of stress on the wave dispersion and attenuation. A plane-wave analysis for dynamical equations formulates stress-dependent velocities of five wave propagation modes, including three longitudinal (P) waves, namely fast P wave, slow P wave and thermal (T) wave, and two shear (S) waves, namely fast S wave and slow S wave. Additional slow P wave and T wave arise due to the Biot and thermal loss mechanisms in porothermoelastic media. The stress-induced rock anisotropy accounts for the S wave splitting phenomenon. Modelling results show that energy dissipations of fast P wave and T wave are induced by the coupling between Biot and thermal loss mechanisms, while the fast and slow S waves, slow P wave are only affected by Biot loss mechanism. The rock permeability and fluid viscosity are mainly related to Biot mechanism, while the thermal conductivity and thermal expansion coefficient for solid phase are related to Biot and thermal mechanisms. In addition, the triaxial stress and confining stress have remarkable effects on the wave velocities as well as attenuation peaks. The predicted wave velocities in water-saturated sandstone and granite behave a reasonable agreement with the laboratory measurements. Our results help to provide better understanding of wave propagation in high-stress high-temperature fields. Article Highlights We propose the dynamical equations for fluid-saturated porous thermoelastic media with the effect of stress. Our model predicts five wave propagation modes, namely fast P wave, slow P wave, thermal wave, fast S wave and slow S wave. Biot and Thermal loss mechanisms are coupled to describe the stress-dependent dispersions and attenuations for these five wave modes.

Unexpected short patches of natural VLF emissions at f > 5 kHz have been observed at the ground station of Kannuslehto (KAN, L ~ 5.5) in Northern Finland. In contrast with usual VLF emissions (e.g., chorus, hiss, and quasiperiodic emissions) these high-frequency bursty-patches are observed at frequencies higher than half of the equatorial electron gyro-frequency of the L shell of KAN. Moreover, most of these waves reached frequencies above the local equatorial electron gyrofrequency at L = 5.5. Thus, they cannot be attributed to the classical theory of electron-cyclotron interaction. We present a review of VLF bursty-patches at KAN during winters 2011–2021. These emissions have rarely been observed as they are usually hidden by sferics originating from lightning discharges. Therefore, a special numeric filtering technique was used to reduce noise from sferics. VLF bursty-patches typically occur as sequences of short right-hand polarized bursts separated by a few minutes and lasting several hours. Here, we discuss the spectral structure of long-lasting bursty-patches (6 + hours) and the properties of individual patches. We established two categories: (1) “triggered-like” hiss-like bursts at f ~ 4–7 kHz with a very abrupt onset and detected under quiet geomagnetic conditions, and (2) “dash-like” emissions at f > 6 kHz that resemble narrowband hiss and observed under moderate activity. Even though VLF bursty-patches in winters 2011–2021 were observed under weak or slightly disturbed magnetic activity, their annual cyclical occurrence was similar to variations in solar activity. The nature of these VLF patches has not been established yet, but they appear to be generated at L shells lower than that of KAN. Their exact generation region and propagation behavior remain unknown, with further theoretical and experimental research being required.

Signal processing techniques play an important role in seismic data analysis. Variational mode decomposition (VMD), as a powerful signal processing method, has been extensively applied in seismic signal processing. A large number of papers on the application of VMD in seismic data analysis have appeared in various journals, conference proceedings, and technical communications. The paper aims to investigate and summarize the recent advancements of VMD and its application in seismic data analysis and give a comprehensive reference for scholars that may be interested in this topic so that researchers can select a more in-depth research direction. Firstly, the VMD principle is briefly introduced, and the advantage and limitations of this approach are illustrated in detail. Secondly, recent applications of the VMD in seismic data analysis are summarized in terms of specific scenarios, such as seismic time–frequency analysis (TFA), seismic denoising, and other applications. Finally, the key problems of VMD in seismic data analysis are discussed, and the potential research directions are listed. It is expected that the review would be constructive to the basic understanding of the VMD concept for beginners and insightful exploration of VMD’s applications in seismic data analysis for advanced researchers. Article Highlights Seismic data analysis plays an important role in extracting valuable information from seismic records This paper surveys the VMD and its applications in the field of seismic data analysis in a comprehensive way Promising research prospects of VMD in seismic data analysis are proposed

Geophysical well log data are widely used in the field of structural geology, sedimentary geology and petroleum geology. Gaps and misunderstandings are still existing in the scientific interpretation of geophysical well logs. Logging environments and log curves need correction and standardization before interpretation, additionally, there are some special geological phenomena that will mislead the well log interpretation. This review critically highlights the typical misunderstandings existing in the well log data interpretation, and proposes countermeasures as well as scientific interpretation of well logs when encounter these misunderstandings. The factors that affect the well log data acquisition are summarized in terms of types of drilling muds, borehole stability and logging instrument rotation. The vertical resolution of various log series spans a wide range from 5 mm to about 10 m. In the field of structural geology, well logs can be used for determination of stratum attitude, fault recognition, fracture and in situ stress characterization as well as unconformity identification. Lithology and depositional facies can be interpreted using well logs. Well logs aim at finding hydrocarbons, and are used for source rock characterization and logging reservoir evaluation in the petroleum geology field. Then the typical misunderstandings and countermeasures in solving geological issues using geophysical well logs are reviewed from published papers as well as from the authors’ personal experiences. This review will provide insights into the scientific interpretation of geophysical well log data, and help solving geological issues for the petrophysicist and geologist.

For more than a century, river discharge has been measured indirectly through observations of water level and flow velocity, but recently the number of gauging stations worldwide has decreased and the situation is particularly serious in African countries that suffer more than others from discontinuous and incomplete monitoring. As one of the most vulnerable regions in the world to extreme weather events and global warming, African countries need adequate and reliable monitoring. Decades of available Earth Observations data represent a tool complementary to the hydro-monitoring network and, in recent decades, they have demonstrated their potential, especially for data-poor regions. In this paper, a review of methods for hydrological and hydraulic modeling and for estimating river discharge by the use of satellite data, specifically radar altimetry and optical sensors, is provided, with particular focus on their role in the climate changes monitoring. More emphasis is placed on their relevance on African basins highlighting limits and advantages.

Near-surface site characterization is of great significance in the fields of geotechnical engineering and resource exploration. In this paper, we propose a near-surface site characterization method based on the joint iterative analysis of first-arrival and surface-wave data (JIAFS). The proposed method combines the advantages of first-arrival traveltime tomography (FATT) and multichannel analysis of surface waves (MASW). First, the 1D S-wave velocity (vS\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$v_{{\text{S}}}$$\end{document}) models obtained by MASW are interpolated to construct the pseudo-2D vS\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$v_{{\text{S}}}$$\end{document} model. According to the available geological survey information and borehole data, the initial Poisson’s ratio (σ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sigma$$\end{document}) model is estimated. Based on the estimated σ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sigma$$\end{document} model, the pseudo-2D vS\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$v_{{\text{S}}}$$\end{document} model is converted to a referenced P-wave velocity (vP\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$v_{{\text{P}}}$$\end{document}) model which is utilized to constrain the progress of FATT. This helps FATT overcome the inherent defect that it cannot effectively identify velocity-inversion interfaces and low-velocity zones. On the other hand, the vP\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$v_{{\text{P}}}$$\end{document} model obtained by FATT can provide a favorable priori information to improve the reliability of the results of MASW. Then, the vP\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$v_{{\text{P}}}$$\end{document} and vS\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$v_{{\text{S}}}$$\end{document} models obtained by constrained FATT and MASW are used to update the σ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sigma$$\end{document} model. In addition, the vP\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$v_{{\text{P}}}$$\end{document} and vS\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$v_{{\text{S}}}$$\end{document} models are also used as initial models in the next iterative analysis. Finally, through the iteration of this process, the two inversion methods can make use of their own advantages to improve each other, so we can establish accurate near-surface vP\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$v_{{\text{P}}}$$\end{document}, vS\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$v_{{\text{S}}}$$\end{document} and σ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sigma$$\end{document} models under complex geological conditions. A velocity model including low-velocity zone is established for synthetic model test to analyze and verify the advantage of JIAFS. The vP\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$v_{{\text{P}}}$$\end{document}, vS\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$v_{{\text{S}}}$$\end{document} and σ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sigma$$\end{document} models obtained by JIAFS can accurately identify the low-velocity zone and match the true models well. In addition, the proposed method is applied to the field seismic data acquired for oil and gas exploration in Northwest China. Compared with the results of individual inversions and borehole data, JIAFS can establish more reliable 3D vP\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$v_{{\text{P}}}$$\end{document}, vS\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$v_{{\text{S}}}$$\end{document} and σ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sigma$$\end{document} models by interpolating the 2D inversion results, which reveals further details and enhances the geological interpretation significantly.

Since the rise of the gold price in 2000, artisanal and small-scale gold mining (ASGM) is a growing economic activity in developing countries. It represents a source of income for several millions of people in West Africa. Exploitation techniques have evolved from traditional gold panning to mechanization and use of chemical products that are harmful for the environment. Government strategies to control and regulate this activity are impeded by the difficulties to collect spatial information, due to the remote location and the mobile and informal natural of ASGM. Here we present and discuss the value of remote sensing techniques to complement the knowledge on artisanal mining impacts, including for detection of illegal sites, the evaluation of the degradation of soils and waters, the deforestation and the monitoring of expansion of ASGM with time. However, these techniques are blind regarding gender issues, labor relations, mobility, migration, and insecurity and need to be considered with knowledges from other disciplines. Remote sensing is also instilled with various powers accruing to those enabled to produce and interpret these data. Remote sensing should be therefore used in a reflexive manner that accounts for the social, ethical and political implications of ASGM governance informed by space observations.

Anisotropy is ubiquitous in the Earth's crust, which causes the elastic characteristics of seismic waves to change with direction. The study of seismic wave anisotropy is of great significance to seismic exploration, prediction and geodynamics. As one of the sources of seismic anisotropy, in situ stress belongs to secondary anisotropy as common as the intrinsic and fracture-induced anisotropy, but it is often ignored among the sources of seismic anisotropy. Therefore, we focus on the study of seismic anisotropy under the influence of in situ stress using the nonlinear acoustoelasticity theory. Based on a horizontal transversely isotropic (HTI) model and the linear slip theory, the characteristics of azimuthal seismic reflection response in anisotropic media under horizontal in situ stress are discussed in this paper. Firstly, by using the quasi-linear relationship between stress and Tsvankin’s anisotropic parameters and the transformation relationship between anisotropic and fracture parameters in HTI medium, the elastic stiffness matrix of an HTI medium with the effect of horizontal in situ stress is established. Secondly, the reflection coefficient of PP-wave seismic data for a planar weak-contrast interface separating two weak-anisotropy and small-stress HTI half-spaces is derived using both the seismic scattering theory and the stiffness matrix under horizontal in situ stress, building the quantitative relationship between azimuthal seismic reflection characteristics and the model parameters, such as the background elastic parameters, the fracture parameters and the horizontal-stress-induced anisotropic parameters. Finally, the variation rules of azimuthal seismic reflection response characteristics of four elastic interfaces under different in situ stress conditions are analyzed. The results demonstrate that the seismic inversion for fracture parameters and horizontal-stress-induced anisotropic parameters is more favorable under the condition of large incident angle. In addition, the effect of horizontal in situ stress on the reflection coefficient depends on the second- and third-order elastic properties of the rock itself. Also, the established seismic PP-wave reflection coefficient equation has provided an alternative approach to calculate the magnitude of horizontal in situ stress. Article Highlights A novel linearized PP-wave reflection coefficient is presented for HTI media with the effect of horizontal in situ stress The response law of azimuthal seismic reflection characteristics induced by horizontal in situ stress is demonstrated A simple inversion method is provided to calculate the magnitude of horizontal in situ stress

Quantitative and qualitative knowledge about the potential impacts of climate change on extreme hydrological events is crucial for water resource management and extreme risk management under climate change. This has theoretical and realistic implications to study and couple the climate system with hydrologic processes, to understand the system and solve related problems in water resources and extreme hydrology, such as decision making, plan management, environmental protection, and ecological balance. This paper reviews recent studies investigating climate change impact on hydrological extremes using a perspective of the integrated modeling framework comprising climate change scenarios, climate models, bias correction methods, hydrological modeling (model structure and parameterization), and reducible uncertainty arising from these sources characterized by a paucity of knowledge. The available research outcomes show the extreme high flows are likely to increase under climate change in the most parts of Europe, Asia, and the USA, but greatly vary and decrease in Africa and Latin America, which is highly variable and uncertain in space and time. Each component in integrated modeling has an important role in shifting and producing uncertainty in projected extreme flow. Among them, the climate model’s discrepancy and hydrological models’ structure are the more dominant source of uncertainty in projection of extreme high and low (or mean) flow in most of the regions, respectively. However, the quality of input data and hydrological model structures are the most dominant source of uncertainty in Africa, Latin America, and some parts of Asia. This indicated that these regions have strong hydrological cycle and higher physiographic heterogeneity. We believe that our existing knowledge and skills need to be improved and transformed into an accurate mathematical and physical representation, to minimize the uncertainty due to the effect of choices in the methodology chain. So, disentangling the aggregated uncertainty in the cascade modeling chain can be done by using variances, which can help understand the interaction effect and identify their contribution to the projected extreme flow. This comprehensive review can help modelers to identify and reduce uncertainty in projecting hydrological extremes and policy makers for full awareness of the various uncertainties to make a robust decision for water resources management under climate change.

We review the current geoscientific knowledge of the volcanic unrest of 2004–2005 on Tenerife (Canary Islands) and revisit its gravimetric imprint. We revise the interpretation of the observed spatiotemporal (time-lapse) gravity changes accompanying the unrest by applying the Growth inversion approach based on model exploration and free geometry growing source bodies. We interpret the Growth solution, our new gravimetric model of the unrest, in the context of structural controls and the existing volcanological and geological knowledge of the central volcanic complex (CVC) of the island. Structural controls are inferred from the updated structural subsurface CVC density model obtained by our new Growth inversion of the available complete Bouguer anomalies (CBA data). Our gravimetric picture sees the unrest as a failed eruption, due to a stalled magma intrusion in the central position below the Teide–Pico Viejo stratocones, followed by upward and lateral migration of volcanic fluids reaching the aquifer and the SW end of the caldera wall. We thus classify the volcanic unrest of 2004–2005 as hybrid, in agreement with previous studies. The Growth inversion indicates that magma propagated along the boundary between the basaltic core of the island, the Boca Tauce volcanic body and the more permeable (less compacted) volcanic rocks with lower density. This gravimetric picture of the unrest provides new insights into the potential future reactivation of the volcanic system.

The Antarctic and Arctic regions are Earth's open windows to outer space. They provide unique opportunities for investigating the troposphere–thermosphere–ionosphere–plasmasphere system at high latitudes, which is not as well understood as the mid- and low-latitude regions mainly due to the paucity of experimental observations. In addition, different neutral and ionised atmospheric layers at high latitudes are much more variable compared to lower latitudes, and their variability is due to mechanisms not yet fully understood. Fortunately, in this new millennium the observing infrastructure in Antarctica and the Arctic has been growing, thus providing scientists with new opportunities to advance our knowledge on the polar atmosphere and geospace. This review shows that it is of paramount importance to perform integrated, multi-disciplinary research, making use of long-term multi-instrument observations combined with ad hoc measurement campaigns to improve our capability of investigating atmospheric dynamics in the polar regions from the troposphere up to the plasmasphere, as well as the coupling between atmospheric layers. Starting from the state of the art of understanding the polar atmosphere, our survey outlines the roadmap for enhancing scientific investigation of its physical mechanisms and dynamics through the full exploitation of the available infrastructures for radio-based environmental monitoring.

The defining of upper crustal structures is an essential process for understanding the tectonic evolution and geodynamics of a region. In this context, the paper aims to determine basement depth and upper crustal structures through the Bouguer gravity anomalies and seismic reflection sections in Denizli Graben located in the western part of Turkey. The gravity data have been analyzed using the power spectrum technique. The results from this technique show that the average Moho depth, basement depth of the middle layer, and the depth of sediment basin in the region have been calculated as 33.6, 12.8, and 3.9 km, respectively. Furthermore, the Moho depth of the region has been estimated using gravity anomalies and is computed to be about 33 km in Denizli Graben. As such, it is shown that the depth values obtained from power spectrum analysis and Moho depth calculations are consistent with each other. Bouguer gravity anomalies have been also modeled three-dimensionally (3D). In the model map, the basement depth of the Denizli Graben has been calculated as approximately 9–10 km. Besides these, by interpreting the seismic section, the depth of the interface in the Denizli Graben has been obtained as approximately 2634 m for one-way travel time. This depth is quite shallow compared to the one (i.e., around 10 km) obtained from the gravity model. Thus, the interface seen in the seismic section is not considered to be the deepest part of the Denizli Graben. From the geothermal and oil exploration perspectives, the obtained basement and interface depths are quite beneficial, especially for the drilling planning.

Passive surface-wave methods have been given increased attention from the near-surface geophysics community because of their advantages of being low-cost and environment-friendly, especially in urban environments. The traffic noise sources, however, are not randomly distributed in time and space in densely populated urban areas. Stacking of cross-correlations is unable to effectively attenuate the azimuthal effects due to noise source distribution, resulting in overestimated surface-wave phase velocities. To solve this problem, we proposed a beamforming-based segment (i.e., time window) selection scheme that applies a beamforming technique with a pseudo-linear array to capture the noise segments coming from the sources in the stationary-phase zone. The azimuthal range of in-line noise sources is determined by the Fresnel angle calculated from the measured shortest wavelength. The cross-correlation is applied to these selected stationary-phase segments. The causal parts of cross-correlations are stacked to obtain the final virtual shot gather, since the single directional in-line noise sources are known through beamforming analysis. We used a synthetic test and two real-world examples of traffic-induced noise data acquired in urban environments to verify the feasibility of the proposed scheme. Results demonstrated that the proposed selection scheme can obtain virtual shot gathers with higher signal-to-noise ratio, higher-resolution dispersion energy, and accurate phase velocities, which provides an alternative tool for the applications of using passive surface-wave methods in urban environments, especially for the case of changes in distribution of noise sources in a short time.

Africa stands to gain from Earth Observation (EO) science, products and applications. However, its use and application remain below potential on the continent. This article examines how EO can better serve the needs of African users. First, we argue that a successful uptake of EO services is conditional on understanding the African context and matching EO development and deployment to it. Using reference cases, we find that actors outside Africa drive most EO initiatives, whereas country-level expenditures on EO remain low. Recent developments, such as the African space policy and strategy, and initiatives in partnerships with Africa-based organisations to develop a community of practice on EO hold the potential to fill the identified gaps. The analysis indicates that most EO users are either government organisations or researchers, with very few cases involving other types of users. It is generally assumed that users at the local levels are educated and digitally literate, or that the transmission of EO-based knowledge is achieved by government officers and researchers. Although still very few, potentials are emerging for the private sector to deploy EO products and services such as crop or index-based insurance directly to farmers. These private initiatives have prospects for further developing indigenous EO capacity as envisioned in the African space policy and strategy. We then formulate recommendations for a transdisciplinary approach that integrates user contexts, attributes and needs to enhance the uptake of EO products and services in Africa. We conclude by proposing actions to close some of the identified gaps and seize emerging opportunities. Supplementary information: The online version contains supplementary material available at 10.1007/s10712-022-09724-1.

Seismic inversion in geophysics is an effective way to obtain underground rock properties from seismic survey data on the Earth’s surface. In particular, we can obtain much more information to characterize subsurface geological structure and lithology via pre-stack seismic inversion, with offset information added to the inversion, than by post-stack seismic inversion. However, pre-stack seismic inversion is usually a nonlinear and complicated process. In this article, we adopt a L1-2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_{1 - 2}$$\end{document}-norm as a constraint on pre-stack seismic inversion, promoting the generation of a sparse solution. We also propose a novel pre-stack seismic inversion method that reduces the complexity of the solving method by utilizing an objective function decomposition scheme. Comparison of calculation time, accuracy and sparsity of the inversion solutions indicates that the proposed algorithm has better accuracy and robustness. Moreover, considering the difficulty of regularization parameter selection, we develop an adaptive parameter selection strategy based on generalized Stein unbiased risk estimation (G-SURE) and incorporate it into the solving algorithm. The adaptive approach finds an appropriate regularization parameter in each iteration and obtains the optimal solution directly, which is beneficial for improving computational efficiency. A synthetic data test verifies that the adaptive method can converge to the optimal solution iteratively in the case of arbitrary initial regularization parameters. Finally, in application to real field data, we explain why the adaptive method is the better choice even though adaptive and non-adaptive methods can obtain solutions with similar accuracy. Article Highlights A novel pre-stack seismic inversion method is proposed based on a proximal difference- of-convex algorithm (pDCA) A new adaptive regularization parameter selection strategy is proposed based on Generalized Stein unbiased risk estimation (G-SURE) Verification that one of the regularization parameters has a limited effect in L1-2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_{1 - 2}$$\end{document}-norm