Convective cloud development during the Indian monsoon helps moisten the atmospheric environment and drive the monsoon trough northwards each year, bringing a large amount of India’s annual rainfall. Therefore, an increased understanding of how monsoon convection develops from observations will help inform model development. In this study, 139 days of India Meteorological Department Doppler weather radar data is analysed for 7 sites across India during the 2016 monsoon season. Convective cell-top heights (CTH) are objectively identified through the season, and compared with near-surface (at 2 km height) reflectivity. These variables are analysed over three time scales of variability during the monsoon: monsoon progression on a month-by-month basis, active-break periods and the diurnal cycle. We find a modal maximum in CTH around 6–8 km for all sites. Cell-averaged reflectivity increases with CTH, at first sharply, then less sharply above the freezing level. Bhopal and Mumbai exhibit lower CTH for monsoon break periods compared to active periods. A clear diurnal cycle in CTH is seen at all sites except Mumbai. For south-eastern India, the phase of the diurnal cycle depends on whether the surface is land or ocean, with the frequency of oceanic cells typically exhibiting an earlier morning peak compared to land, consistent with the diurnal cycle of precipitation. Our findings confirm that Indian monsoon convective regimes are partly regulated by the large-scale synoptic environment within which they are embedded. This demonstrates the excellent potential for weather radars to improve understanding of convection in tropical regions

Mankind's productive use of the low Earth orbit (LEO), from 400-2,000km in altitude, is at risk from increasing counts of debris objects and derelict satellites, which pose collision risks to active spacecraft. Of particular concern to space agencies and industry is the Kessler Syndrome (KS), which is the term for a hypothetical collapse scenario in which collisions between debris and satellites cause more debris, causing a destructive cascade that leaves the orbital environment unusable. In order to better understand this KS tipping point, the KESSYM model has been developed as a stochastic simulation of all the objects in the LEO. This model provides a forecast for the evolution of the orbital environment into the future, including the expected year, if any, that the KS collapse occurs. KESSYM allows for certain risks, such as war or terrorism in space, solar flares, or unconstrained exploitation of the space resources to be analyzed alongside KS mitigation measures, such as the hardening of spacecraft against debris, avoidance of collisions, removal of debris, and effective regulation. The conclusions drawn from the KESSYM simulation are that the KS is almost an inevitability within 200-250 years of today's date, but can be delayed or avoided altogether if action is taken.

The shielding effectiveness is a key index to measure the performance of electromagnetic protective materials However, the traditional shielding effectiveness testing methods exist many losses, there by the experimental data varying under different test conditions. This paper aims to provide a novel NV-center based optical high-resolution shielding performance testing method, a method that may directly provide the distribution of the electromagnetic field on the surface of the electromagnetic shielding material. This method was used to test the shielding performance of two different electromagnetic shielding materials, and comparison with the surface scan method has proved the feasibility and reliability of the optical high-resolution test method, providing a new idea for testing the effectiveness of electromagnetic shielding materials more accurately and effectively.

Energy routers based on the electronic power transformer are suitable for the AC-DC hybrid grid with multiple voltage levels, but their structures are complex. This paper proposes a novel energy router based on the multi-winding line frequency transformer. By a combination of a multi-winding line frequency transformer and power electronic devices, the proposed energy router can take advantage of the high reliability of the multi-winding line frequency transformer and the high controllability of power electronic devices. The proposed energy router is suitable for the AC-DC hybrid grid with multiple voltage levels and has the characteristic of a simple structure. The simulations and experimental results demonstrate the effectiveness of the proposed energy router.

Chlorinated aromatics and alkanes have important use value because of their flame retardancy，but they need to be monitored when used in recycled pulp. This paper report the use of palladium acetate/ Activated carbon activated by nitric acid as an online catalyst in the determination of chlorinated aromatics and chlorinated alkanes in recycled paper products with Gas Chromatography-Tandem Mass Spectrometry method, by which significantly improve the sensitivity of the method and dramatically lower the detection limits.

Rationale: Proteomic studies typically involve use of different types of softwares for annotating experimental tandem mass spectrometric data (MS/MS) and thereby simplify the process of peptide and protein identification. For such annotations, these softwares calculate the m/z values of the peptide/protein precursor and fragment ions, for which a database of protein sequences must be provided as input file. The calculated m/z values are stored as another database, which the user usually cannot view. ‘Database Creator for Protein/Peptide Mass Analysis’ (DC-PPMA) is a novel standalone software that can create custom databases and the user can view the custom database containing the calculated m/z values of precursor and fragment ions. Methods: Python language was used for implementation and the graphical user interface was built with Page/Tcl, making this tool more user-friendly and easier to analyze. DC-PPMA is freely available at https://vit.ac.in/PPMA/. Results: DC-PPMA contains three modules. Protein/peptide sequences as per user’s choice can be entered as input to the first module for creating custom database. In the second module, m/z values must be queried-in, which are searched within the custom database to identify protein/peptide sequences. The third module is suited for peptide mass fingerprinting, for which data arising from both ESI and MALDI MS can be utilized. Conclusions: Mass spectral data acquired from any proteomic approach: bottom-up, middle-down and top-down can be interrogated with DC-PPMA. A major facet of DC-PPMA is that the user can ‘view’ the custom database containing the m/z values of the precursor ions (e.g., proteolytic peptides) and the respective fragment ions (e.g., b & y ions), prior to the database search. The feature of ‘viewing’ the custom database cannot only be helpful for better understanding the search engine processes; but also, for ‘designing multiple reaction monitoring (MRM) methods’. Post-translational modifications and protein isoforms too can be analyzed.

Mountain landscapes have dynamic climates that, together with tectonic processes, importantly influence their topographic evolution. While spatio-temporal changes in rainfall are ubiquitous in these settings, their influence on river incision has been little studied. Here, we investigate how changes in rainfall pattern should affect both the steady state form and transient evolution of river profiles at the catchment scale using the stream power model. We find that non-uniform rainfall patterns complicate steady state relationships among conventional catchment-wide metrics like mean rainfall, channel steepness, and fluvial relief, which can influence the apparent sensitivity of landscapes and erosion rates to rainfall variations. We also find that transient responses to changes in rainfall pattern have an inherently multi-stage nature that importantly differs from expected responses to uniform changes in rainfall. This has several important implications, specifically for detecting transient responses to changes in rainfall pattern (and more broadly climate) in natural settings, and for interpretations of landscape morphometrics above and below transient knickpoints. We find that disparate responses by rivers and river segments that experience different rainfall conditions, particularly trunk and tributary rivers, are an important factor in understanding catchment-wide responses, and accounting for such disparities may be important for detecting and quantifying landscape sensitivity to rainfall variations. Lastly, we show how explicitly accounting for rainfall patterns in channel steepness calculations, and thus variations in erosional efficiency, may be a necessary step toward overcoming challenges related to rainfall variations, and thus ultimately for advancing understanding of landscape sensitivity to climate in mountain settings.

Interferometric Synthetic Aperture Radar (InSAR) measurements are increasingly being used to measure small amplitude tectonic deformations over large spatial scales. Residual signals are often present at these scales, and are interpreted to be noise of indeterminate origin, limiting studies of long-wavelength deformation. Here, we demonstrate the impact of bulk motion by the Earth’s tectonic plates on InSAR-derived velocity fields. The range-dependent incidence angle of the InSAR observations, coupled with plate velocities of centimeters per year, can induce long-wavelength spatial gradients of millimeters per year over hundreds of kilometers in InSAR-derived velocity fields. We show that, after applying corrections, including for the ionosphere and troposphere, plate motion represents the dominant source of long-wavelength secular velocity gradients in multi-year time series for several study areas. This signal can be accounted for using plate motion models, allowing improved detection of regional tectonic strain at continental scales.

The Dotson Ice Shelf has resisted acceleration and ice-front retreat despite high basal-melt rates and rapid disaggregation of the neighboring Crosson Ice Shelf. Because of this lack of acceleration, previous studies have assumed that Dotson is stable. Here we show clear evidence of Dotson's destabilization as it decelerates, contrary to the common assumption that ice-flow deceleration is synonymous with stability. Ungrounding of a series of pinning points initiated acceleration in the Upper Dotson in the early 2000s, which subsequently slowed ice flow in the Lower Dotson. Discharge from the tributary Kohler Glacier into Crosson increased, but non-proportionally. Using ICESat and ICESat-2 altimetry data we show that ungrounding of the remaining pinning points is linked to a tripling in basal melt rates between 2006-2016 and 2016-2020. Basal melt rates on Crosson doubled over the same period. The higher basal melt at Lower Dotson is consistent with the cyclonic ocean circulation in the Dotson cavity, which tends to lift isopycnals and allow warmer deep water to interact with the ice. Given current surface-lowering rates, we estimate that several remaining pinning points in the Upper Dotson will unground within one to three decades. The grounding line of Kohler Glacier will retreat past a bathymetric saddle by the late 2030s and merge into the Smith West Glacier catchment, raising concern that reconfiguration of regional ice-flow dynamics and new pathways for the intrusion of warm modified Circumpolar Deep Water could further accelerate grounding-line retreat in the Dotson-Crosson Ice Shelf System.

Plate tectonics characterize transform faults as conservative plate boundaries where the lithosphere is neither created nor destroyed. In the Atlantic, both transform faults and their inactive traces, fracture zones, are interpreted to be structurally heterogeneous, representing thin, intensely fractured, and hydrothermally altered basaltic crust overlying serpentinized mantle. This view, however, has recently been challenged. Instead, transform zone crust might be magmatically augmented at ridge-transform intersections before becoming a fracture zone. Here, we present constraints on the structure of oceanic crust from seismic refraction and wide-angle data obtained along and across the St. Paul fracture zone near 18°W in the equatorial Atlantic Ocean. Most notably, both crust along the fracture zone and away from it shows an almost uniform thickness of 5-6 km, closely resembling normal oceanic crust. Further, a well-defined upper mantle refraction branch supports a normal mantle velocity of 8 km/s along the fracture zone valley. Therefore, the St. Paul fracture zone reflects magmatically accreted crust instead of the anomalous hydrated lithosphere. Little variation in crustal thickness and velocity structure along a 200 km long section across the fracture zone suggests that distance to a transform fault had negligible impact on crustal accretion. Alternatively, it could also indicate that a second phase of magmatic accretion at the proximal ridge-transform intersection overprinted features of starved magma supply occurring along transform faults.

Evaluating historical simulations from global climate models (GCMs) remains an important exercise for better understanding future projections of climate change and variability in rapidly warming regions, such as the Arctic. As an alternative approach for comparing climate models and observations, we set up a machine learning classification task using a shallow artificial neural network (ANN). Specifically, we train an ANN on maps of annual mean near-surface temperature in the Arctic from a multi-model large ensemble archive in order to classify which GCM produced each temperature map. After training our ANN on data from the large ensembles, we input annual mean maps of Arctic temperature from observational reanalysis and sort the prediction output according to increasing values of the ANN’s confidence for each GCM class. To attempt to understand how the ANN is classifying each temperature map with a GCM, we leverage a feature attribution method from explainable artificial intelligence. By comparing composites from the attribution method for every GCM classification, we find that the ANN is learning regional temperature patterns in the Arctic that are unique to each GCM relative to the multi-model mean ensemble. In agreement with recent studies, we show that ANNs can be useful tools for extracting regional climate signals in GCMs and observations.

The ice stream geometry and large ice surface velocities at the onset region of the Northeast Greenland Ice Stream (NEGIS) are not yet well reproduced by ice sheet models. They are a significant source of uncertainty in present ice sheet projections towards their future contribution to sea-level rise. The quantification of basal sliding and a parametrisation of basal conditions remains a major gap. In this study, we assess the basal conditions of the onset region of the NEGIS in a systematic analysis of airborne ultra-wideband radar data. We evaluate basal roughness and basal return echoes in the context of the current ice stream geometry and ice surface velocity. We observe a change from a smooth to a rougher bed where the ice stream widens, and a distinct roughness anisotropy, indicating a preferred orientation of subglacial structures. In this region, we also find an apparent increase of the bed return power towards the centre of the ice stream, potentially indicating increased water content at the base. At the downstream part, we observe an increased bed return power throughout the entire width of the ice stream and outside its margins. Together with basal water routing pathways, this hints to two different zones in this part of NEGIS: the upstream region collecting water, reducing basal traction, and in the further downstream part the distribution of basal water underneath and beyond the shear margins. Our findings support the hypothesis that the NEGIS is strongly controlled by the subglacial water system in its onset region.

The tsunami-generated magnetic field is a magnetic field that show up with the moving of tsunami. In the previous studies, researchers claimed that the tsunami-generated magnetic field arrives earlier than the tsunami sea level change based on analytical solutions and numerical simulations. In this paper, we used the world's first simultaneous data of sea level change and magnetic field in the 2009 Samoa and 2010 Chile tsunamis to study the relation between these two physical quantities. We found that the vertical component of tsunami magnetic field arrives earlier than the sea level change. Moreover, the horizontal component of tsunami magnetic field arrives even earlier than the vertical component. The tsunami magnetic field was also revealed that it can be used to estimate the tsunami wave height very accurately. We investigated the observed tsunami magnetic field by our 3-D time-domain simulation. However, the currently existing tsunami source models were unable to reproduce the observation in our research area. We confirmed that a better source model can improve the simulation. It follows that our high precision tsunami wave height data converted from the magnetic field should be used to construct a better tsunami source model.

Long-period (T > 10 s) shear-wave reverberations between the surface and reflecting boundaries below seismic stations are useful for studying the mantle transition zone (MTZ) but finite-frequency effects may complicate the interpretation of waveform stacks. Using waveform data from the USArray and spectral-element method synthetics for 3-D seismic models, we illustrate that a common-reflection point (CRP) modeling of layering in the upper mantle must be based on 3-D reference structures and accurate calculations of reverberation traveltimes. Our CRP mapping of recorded waveforms places the 410-km and 660-km phase boundaries about 15 km deeper beneath the western US than beneath the central-eastern US if it is based on the 1-D PREM model. The apparent east-to-west deepening of the MTZ disappears in the CRP image if we account for shear-wave velocity variations in the mantle. We also find that ray theory overpredicts the traveltime delays of the reverberations if 3-D velocity variations in the mantle are prescribed by global models S40RTS, SEMUCB-WM1, and TX2015. Undulations of the 410-km and 660-km are underestimated in the analysis when their wavelengths are smaller than the Fresnel zones of the wave reverberations in the MTZ.

Joint probabilistic inversions of magnetotelluric (MT) and seismic data has great potential for imaging the thermochemical structure of the lithosphere as well as mapping fluid/melt pathways and regions of mantle metasomatism. In this contribution we present a novel probabilistic (Bayesian) joint inversion scheme for 3D MT and surface-wave dispersion data particularly designed for large-scale lithospheric studies. The approach makes use of a recently developed strategy for fast solutions of the 3D MT forward problem (Manassero et al., 2020) and combines it with adaptive Markov chain Monte Carlo (MCMC) algorithms and parallel-in-parallel strategies to achieve extremely efficient simulations. To demonstrate the feasibility, benefits and performance of our joint inversion method to image the conductivity, temperature and velocity structures of the lithosphere, we apply it to two numerical examples of increasing complexity. The inversion approach presented here is timely and will be useful in the joint analysis of MT and surface wave data that are being collected in many parts of the world. This approach also opens up new avenues for the study of translithospheric and transcrustal magmatic systems, the detection of metasomatised mantle and the incorporation of MT into multi-observable inversions for the physical state of the Earth’s interior.

Clinopyroxene and orthopyroxene are the two major repositories of rare earth elements (REE) in spinel peridotites. Most geochemical studies of REE in mantle samples focus on clinopyroxene. Recent advances in in situ trace element analysis has made it possible to measure REE abundance in orthopyroxene. The purpose of this study is to determine what additional information one can learn about mantle processes from REE abundances in orthopyroxene coexisting with clinopyroxene in residual spinel peridotites. To address this question, we select a group of spinel peridotite xenoliths (9 samples) and a group of abyssal peridotites (12 samples) that are considered residues of mantle melting and that have major element and REE compositions in the two pyroxenes reported in the literature. We use a disequilibrium double-porosity melting model and the Markov chain Monte Carlo method to invert melting parameters from REE abundance in the bulk sample. We then use a subsolidus reequilibration model to calculate REE redistribution between cpx and opx at the extent of melting inferred from the bulk REE data and at the closure temperature of REE in the two pyroxenes. We compare the calculated results with those observed in clinopyroxene and orthopyroxene in the selected peridotitic samples. Results from our two-step melting followed by subsolidus reequilibration modeling show that it is more reliable to deduce melting parameters from REE abundance in the bulk peridotite than in clinopyroxene. We do not recommend the use of REE in clinopyroxene alone to infer the degree of melting experienced by the mantle xenolith, as HREE in clinopyroxene in the xenolith are reset by subsolidus reequilibration. In general, LREE in orthopyroxene and HREE in clinopyroxene are more susceptible to subsolidus redistribution. The extent of redistribution depends on the modes of clinopyroxene and orthopyroxene in the sample and thermal history experienced by the peridotite. By modeling subsolidus redistribution of REE between orthopyroxene and clinopyroxene after melting, we show that it is possible to discriminate mineral mode of the starting mantle and cooling rate experienced by the peridotitic sample. We conclude that endmembers of the depleted MORB mantle and the primitive mantle are not homogeneous in mineral mode. A modally heterogeneous peridotitic starting mantle provides a simple explanation for the large variations of mineral mode observed in mantle xenoliths and abyssal peridotites. Finally, by using different starting mantle compositions in our simulations, we show that composition of the primitive mantle is more suitable for modeling REE depletion in cratonic mantle xenoliths than the composition of the depleted MORB mantle.

Dolomite (CaMg(CO3)2) forms in minor quantities in few modern environments yet comprises most of the Precambrian carbonate rock record. Precambrian dolomites are often fine-grained and fabric-retentive and are interpreted to have precipitated as primary cements or formed as early diagenetic replacements of CaCO3. Primary dolomite precipitation from seawater in depositional environments has not yet been described. Here, we use synchrotron radiation to produce a nanoscale-resolution crystal orientation map of one exquisitely preserved ooid deposited at the onset of the Shuram carbon isotope excursion at ~574 Ma. The crystal orientation map reveals small (~10 μm) acicular, radially-oriented crystals grouped into bundles of similarly-oriented crystals with varying optical properties. We interpret this dolomite formed via primary, spherulitic precipitation during ooid growth in shallow marine waters. This result provides additional evidence that the physicochemical properties of late Precambrian oceans promoted dolomite precipitation and supports a primary origin for the Shuram excursion.

Leveraging aerosol data from multiple airborne and surface-based field campaigns encompassing diverse environmental conditions, we identify a generally consistent oxalate-sulfate mass ratio, with a median of 0.0217 (95% confidence interval: 0.0154 – 0.0296; r = 0.76). Ground-based aerosol data show that the median oxalate-sulfate ratio is robust within both the mixed layer and the submicrometer particle size range, with higher values observed for supermicrometer particles. We demonstrate that dust and biomass burning emissions can separately bias this ratio towards higher values by at least one order of magnitude. Since sulfate is more readily measured, this ratio could be used to infer oxalate from sulfate in the absence of biomass burning and/or air masses rich with coarse aerosol types (especially dust). This ratio may also have implications for model estimates of secondary organic aerosol (SOA) formation, and particularly the aqueous processing route for oxalate production.

The propagation of the fast magnetosonic (FMS) wave in the curved magnetic field is studied. A hemicylindrical model of the magnetosphere is considered where the magnetic field lines are represented by concentric circles. An ordinary differential equation is derived describing the coupled Alfv\’en and FMS waves. Using the equation, it was demonstrated that in the curved field the propagation of the fast mode is drastically different from the propagation in the planar magnetic field. In particular, on the magnetic surface known as the reflection surface for the fast mode in the planar magnetic field, there is a wave singularity where some components of the wave’s magnetic field (the azimuthal and compressional components) as well as the plasma density have logarithmic singularity. The physical reason for this singularity is the decrease of the volume of the magnetic flux tube toward the axis of the cylinder.

The coupled Atmospheric and Hydrological Modelling System (AHMS) combines a hydrological model (HMS) with the Weather Research and Forecast model (WRF) through the Noah-MP land surface scheme. This system is applied in offline mode to the hydrological processes in the Yellow River Basin which has been dramatically affected by intensive human activities over the past decades. In the earlier studies, the river water use for irrigation is often not considered, which is however an essential component of the water balance in the arid and semi-arid areas of the Yellow River Basin. Here, the channel routing model of the AHMS is extended to account for irrigation water taken from river. The irrigation water requirements are estimated based on the WATNEEDS model. AHMS is applied for the period 1979-2013 and the model results are compared with observations. It is found that for the upstream stations, the model simulated and observed streamflow are in good quantitative agreement. Comparison with the observed streamflow at the Huayuankou station near the outlet of the upper and the middle reaches of the Yellow River Basin shows that the model performance improves significantly with the consideration of irrigation. For the entire Yellow River Basin, the AHMS is found to perform well with consideration of irrigation water consumption. The progress achieved in the present work demonstrates the capacity of the AHMS for long-term hydrological simulations in the Yellow River Basin and the AHMS simulation provide a comprehensive and quantitative overview of the water resources in this important river basin.

Connectivity of material constituents govern the transport, mechanical, chemical, thermal, and electromagnetic properties. Energy storage, recovery and conversion depends on connectivity of material constituents. High-resolution microscopy image of a material captures the microstructural aspects describing the distribution, topology and morphology of various material constituents. In this study, six metrics are developed and tested for quantifying the connectivity of material constituents as captured in the high-resolution microscopy images. The six metrics are as follows: geobody connectivity metric based on percolation theory, Euler number based on integral geometry, indicator variogram based on geostatistics, two-point cluster function, connectivity function, and travel-time histogram based on fast marching method. The performances of these metrics are tested on 3000 images representing six levels of connectivity. The metrics are also evaluated on the organic constituent captured in the scanning electron microscopy (SEM) images of organic-rich shale samples. The connectivity function and travel-time histogram based on fast-marching method are the most robust and reliable metrics. Material constituents exhibiting high connectivity result in large values of average travel time computed using fast-marching method and average connected distance computed using connectivity function. The proposed metrics will standardize and speed-up the analysis of connectivity to facilitate the characterization of properties and processes of energy-relevant materials.

A rapid northward drift of the Indian plate after 130 Ma has also recorded significant plate rotations due to the torques resulting from multiple vectorial forces. Magnetic anomaly, seismic tomography and palaeomagnetic database is used here to constrain drift velocities, tilt and lithospheric root delamination at different temporal snapshots. It results into estimates of 263.2 to 255.7 mmyr-1 latitudinal drift, 234 to 227.3 mmyr-1 longitudinal drift and 352.2 to 342.1 mmyr-1 diagonal drift, for the period from ~66 to 64 Ma during the Chrons C30n.y–C29n.y. Alternative models suggest active driving forces arising from i) slab pull, ii) ridge push from eastern-, western and southern plate margins, and iii) Reunion plume-push force; in addition to delamination of the lithospheric root during approximately 65+2 Ma. Delamination amplified the buoyancy of the Indian plate in contrast to sudden loading from Deccan basaltic pile that resulted into complex drift dynamics expressed by hyper plate velocities within global plate circuit.

Four-dimensional variational (4D-Var) data assimilation is an effective method for obtaining physically consistent time-varying states. In this study, a method using a neural network surrogate model obtained by machine learning is proposed to solve one of the most serious challenges in 4D-Var: to construct an adjoint model. The feasibility of the proposed method was demonstrated by a 4D-Var experiment using a surrogate model for the Lorenz 96 model. In the method, several effective procedures have been proposed to obtain an accurate surrogate model and the assimilated initial conditions, including two-stage learning (i.e., single- and multi-step learning) of neural networks, limiting the target states of the surrogate model to a small subspace of the state phase space, and updating the surrogate model during 4D-Var iterations.

Low-velocity accretionary wedges and sedimentary layers overlying continental plates widely exist in subduction zones. However, the two structures are commonly neglected in velocity models used in slip inversion, ground motion estimation, and dynamic rupture simulation, which may cause a biased estimation of coseismic slip and near-fault ground motions during subduction zone earthquakes. We use the 2011 Mw 9.0 Tohoku-Oki earthquake as an example and reproduce the observed seafloor deformation using 2-D dynamic rupture models with or without an accretionary wedge and a sedimentary layer. We find that the co-existence of the accretionary wedge and sedimentary layer significantly enhances the shallow coseismic slip and amplifies ground accelerations near the accretionary wedge. Hence, stress drop on the shallow fault estimated from the coseismic slip or surface deformation is overestimated when the two structures are neglected. We further simulate a suite of earthquakes where the up-dip rupture terminates at different depths. Results show that a sedimentary layer enhances coseismic slip in all cases, while an accretionary wedge can lead to a sharper decline in slip when negative dynamic stress drop exists on the shallow fault. However, a combination of the two structures tends to enhance fault slip, especially when rupture breaks through a trench. Thus, their combined effects are nonlinear and can be larger than the respective contribution of each structure. Our results emphasize that subduction zones featuring a co-existence of an accretionary wedge and a sedimentary layer may have inherently higher earthquake and tsunami hazards.