The isotopic composition of dissolved oxygen offers a family of potentially unique tracers of respiration and transport in the subsurface ocean. Uncertainties in transport parameters and isotopic fractionation factors, however, have limited the strength of the constraints offered by 18O/16O and 17O/16O ratios in dissolved oxygen. In particular, puzzlingly low 17O/16O ratios observed for some low-oxygen samples have been difficult to explain. To improve our understanding of oxygen cycling in the ocean’s interior, we investigated the systematics of oxygen isotopologues in the subsurface Pacific using new data and a 2-D isotopologue-enabled isopycnal reaction-transport model. We measured 18O/16O and 17O/16O ratios, as well as the “clumped” 18O18O isotopologue in the northeast Pacific, and compared the results to previously published data. We find that transport and respiration rates constrained by O2 concentrations in the oligotrophic Pacific yield good measurement-model agreement across all O2 isotopologues only when using a recently reported set of respiratory isotopologue fractionation factors that differ from those most often used for oxygen cycling in the ocean. These fractionation factors imply that an elevated proportion of 17O compared to 18O in dissolved oxygen―i.e., its triple-oxygen isotope composition―does not uniquely reflect gross primary productivity and mixing. For all oxygen isotopologues, transport, respiration, and photosynthesis comprise important parts of their respective budgets. Mechanisms of oxygen removal in the subsurface ocean are discussed.

The COVID-19 global pandemic and associated government lockdowns dramatically altered human activity, providing a window into how changes in individual behavior, enacted en masse, impact atmospheric composition. The resulting reductions in anthropogenic activity represent an unprecedented event that yields a glimpse into a future where emissions to the atmosphere are reduced. While air pollutants and greenhouse gases share many common anthropogenic sources, there is a sharp difference in the response of their atmospheric concentrations to COVID-19 emissions changes due in large part to their different lifetimes. Here, we discuss two key takeaways from modeling and observational studies. First, despite dramatic declines in mobility and associated vehicular emissions, the atmospheric growth rates of greenhouse gases were not slowed. Second, it demonstrated empirically that the response of atmospheric composition to emissions changes is heavily modulated by factors including carbon cycle feedbacks to CH4 and CO2, background pollutant levels, the timing and location of emissions changes, and climate feedbacks on air quality.

Harsh subsurface environment limits robust workability of on-site instrumentation to be leveraged to track solid Earth’s dynamics. Distributed fiber-optic sensing technology (DFOS) allows long-period in-situ real-time detection of crustal geoenergy exploration-induced underground motions. Here, we first deployed 300-m-long fiber-optic cables behind casing of an actual injection well via single-ended, hybrid Brillouin-Rayleigh backscatterings interrogator to distributed monitor water injection test between two adjacent wells in onshore Mobara, Japan. Detailed DFOS recordings over the entire borehole visualized clear-cut spatiotemporal strain responses from one water injection. Potential injected water-transport footprint and impacted zone reasonably coincided with those of analogy-based strain fronts. Our study thus further uncovered that injection volume and injection pressure significantly dominated water injection-driven strain magnitude and coverage.

The shoreline development index – the ratio of a lake’s shore length to the circumference of a circle with the lake’s area – is a core metric of lake morphometry used in Earth and planetary sciences. In this paper, we demonstrate that the shoreline development index is scale-dependent and cannot be used to compare lakes with different areas. We show that large lakes will have higher shoreline development index measurements than smaller lakes of the same characteristic shape, even when mapped at the same scale. Specifically, the shoreline development index increases by about 14% for each doubling of lake area. These results call into question previously reported patterns of lake shape. We provide several suggestions to improve the application of this index, including a bias-corrected formulation for comparing lakes with different surface areas.

Sea Surface Salinity (SSS) is an increasingly-used Essential Ocean and Climate Variable. The SMOS, Aquarius, and SMAP satellite missions all provide SSS measurements, with very different instrumental features leading to specific measurement characteristics. The Climate Change Initiative Salinity project (CCI+SSS) aims to produce a SSS Climate Data Record (CDR) that addresses well-established user needs based on those satellite measurements. To generate a homogeneous CDR, instrumental differences are carefully adjusted based on in-depth analysis of the measurements themselves, together with some limited use of independent reference data. An optimal interpolation in the time domain without temporal relaxation to reference data or spatial smoothing is applied. This allows preserving the original datasets variability. SSS CCI fields are well-suited for monitoring weekly to interannual signals, at spatial scales ranging from 50 km to the basin scale. They display large year-to-year seasonal variations over the 2010-2019 decade, sometimes by more than +/-0.4 over large regions. The robust standard deviation of the monthly CCI SSS minus in situ Argo salinities is 0.15 globally, while it is at least 0.20 with individual satellite SSS fields. r2 is 0.97, similar or better than with original datasets. The correlation with independent ship thermosalinographs SSS further highlights the CCI dataset excellent performance, especially near land areas. During the SMOS-Aquarius period, when the representativity uncertainties are the largest, r2 is 0.84 with CCI while it is 0.48 with the Aquarius original dataset. SSS CCI data are freely available and will be updated and extended as more satellite data become available.

Shallow nearshore coastal waters provide a wealth of societal, economic and ecosystem services, yet their topographic structure is poorly mapped due to a reliance upon expensive and time intensive methods. Space-borne bathymetric mapping has helped address these issues, but has remained dependent upon in situ measurements. Here we fuse ICESat-2 lidar data with Sentinel-2 optical imagery, within the Google Earth Engine geospatial cloud platform, to create wall-to-wall high-resolution bathymetric maps at regional-to-national scales in Florida, Crete and Bermuda. ICESat-2 bathymetric classified photons are used to train three Satellite Derived Bathymetry (SDB) methods, including Lyzenga, Stumpf and Support Vector Regression algorithms. For each study site the Lyzenga algorithm yielded the lowest RMSE (approx. 10-15%) when compared with in situ NOAA DEM data. We demonstrate a means of using ICESat-2 for both model calibration and validation, thus cementing a pathway for fully space-borne estimates of nearshore bathymetry in shallow, clear water environments.

With plate tectonics operating on Earth, the preservation potential for mantle reservoirs from the Hadean Eon (>4.0 Ga) has been regarded as very small. The quest for such early remnants has been spurred by the observation that many Archean rocks exhibit excesses of 182W, the decay product of short-lived 182Hf. However, it remains speculative, if Archean 182W anomalies and also 182W deficits found in many young ocean island basalts (OIBs) mirror primordial Hadean mantle differentiation or just variable contributions from older meteorite building blocks delivered to the growing Earth. Here, we present a high-precision 182W isotope dataset for 3.22-3.55 Ga old rocks from the Kaapvaal Craton, southern Africa. In expanding previous work, our study reveals widespread 182W deficits in different rock units from the Kaapvaal Craton and also the very first discovery of a negative co-variation between short-lived 182W and long-lived 176Hf-143Nd-138Ce patterns, a trend of global significance. Amongst different models, these distinct patterns can be best explained by the presence of recycled mafic restites from Hadean protocrust in the ancient mantle beneath the Kaapvaal Craton. Further, the data provide unambiguous evidence for the operation of silicate differentiation processes on Earth during the lifetime of 182Hf, i.e., the first 60 million years after solar system formation. The striking isotopic similarity between recycled protocrust and the low 182W endmember of modern OIBs might also constitute the missing link bridging 182W isotope systematics in Archean and young mantle-derived rocks.

Free alternate bars are large-scale, downstream-migrating bedforms characterized by an alternating sequence of three-dimensional depositional fronts and scour holes that frequently develop in rivers as the result of an intrinsic instability of the erodible bed. Theoretical models based on two-dimensional shallow water and Exner equations have been successfully employed to capture the bar instability phenomenon, and to estimate bar properties such as height, wavelength and migration rate. However, the mathematical complexity of the problem hampered the understanding of the key physical mechanisms that sustain bar formation. To fill this gap, we considered a simplified version of the equations, based on neglecting the deformation of the free surface, which allows us to: (i) provide the first complete explanation of the bar formation mechanism as the result of a simple bond between variations of the water weight and flow acceleration; (ii) derive a simplified, physically based formula for predicting bar formation in a river reach, depending on channel width-to-depth ratio, Shields number and relative submergence. Comparison with an unprecedented large set of laboratory experiments reveals that our simplified formula appropriately predicts alternate bar formation in a wide range of conditions. Noteworthy, the hypothesis of negligible free surface effect also implies that bar formation is fully independent of the Froude number. We show that this intriguing property is intimately related to the three-dimensional nature of river bars, which allows for a gentle lateral deviation of the flow without significant deformation of the water surface.

We use numerical simulations to study the resonant interaction of relativistic electrons with rising-frequency EMIC wave packets in the H band. We find that precipitation fluxes are formed by quasi-linear interaction and several nonlinear interaction regimes having opposite effects. In particular, the influence of Lorentz force on the particle phase (force bunching) decreases precipitation for particles with low equatorial pitch angles (up to 15-25), and can even block it completely. Four other nonlinear regimes are possible: nonlinear shift of the resonance point (can cause pitch angle drift in both directions); phase bunching (slightly increases pitch angle for untrapped particles); directed scattering (strongly decreases pitch angle for untrapped particles) and particle trapping by the wave field (decreases pitch angle). Equatorial pitch angle distribution evolution during several passes of particles through the wave packet is studied. The precipitation fluxes are evaluated and compared with theoretical estimates. We show that strong diffusion limit is maintained for a certain range of energies by a wave packet with realistic amplitude and frequency drift. In this case, the quasi-linear theory strongly underestimates the precipitated flux. With increasing energy, the precipitated fluxes decrease and become close to the quasi-linear estimates.

Two-dimensional hybrid particle-in-cell (PIC) simulations are carried out on a constant L-shell (or drift shell) surface of the dipole magnetic field to investigate the generation process of near-equatorial fast magnetosonic waves (a.k.a equatorial noise; MSWs hereafter) in the inner magnetosphere. The simulation domain on a constant L-shell surface adopted here allows wave propagation and growth in the azimuthal direction (as well as along the field line) and is motivated by the observations that MSWs propagate preferentially in the azimuthal direction in the source region. Furthermore, the equatorial ring-like proton distribution used to drive MSWs in the present study is (realistically) weakly anisotropic. Consequently, the ring-like velocity distribution projected along the field line by Liouville’s theorem extends to rather high latitude, and linear instability analysis using the local plasma conditions predicts substantial MSW growth up to +- 27deg latitude. In the simulations, however, the MSW intensity maximizes near the equator and decreases quasi-exponentially with latitude. Further analysis reveals that the stronger equatorward refraction at higher latitude due to the larger gradient of the dipole magnetic field strength prevents off-equatorial MSWs from growing continuously, whereas MSWs of equatorial origin experience little refraction and can fully grow. Furthermore, the simulated MSWs exhibit a rather complex wave field structure varying with latitude, and the scattering of energetic ring-like protons in response to MSW excitation occurs faster than the bounce period of those protons so that they do not necessarily follow Liouville’s theorem during MSW excitation.

This study presents an improved approach to common-conversion point stacking of converted body waves that incorporates scattering kernels, accurate and efficient measurement of stack uncertainties, and an alternative method for estimating free surface seismic velocities. To better separate waveforms into the P and SV components to calculate receiver functions, we developed an alternative method to measure near surface compressional and shear wave velocities from particle motions. To more accurately reflect converted phase scattering kernels in the common-conversion point stack, we defined new weighting functions to project receiver function amplitudes only to locations where sensitivities to horizontal discontinuities are high. To better quantify stack uncertainties, we derived an expression for the standard deviation of the stack amplitude that is more efficient than bootstrapping and can be used for any problem requiring the standard deviation of a weighted average. We tested these improved methods on Sp phase data from the Anatolian region, using multiple bandpass filters to image velocity gradients of varying depth extents. Common conversion point stacks of 23,787 Sp receiver functions demonstrate that the new weighting functions produce clearer and more continuous mantle phases, compared to previous approaches. The stacks reveal a positive velocity gradient at 80-150 km depth that is consistent with the base of an asthenospheric low velocity layer. This feature is particularly strong in stacks of longer period data, indicating it represents a gradual velocity gradient. At shorter periods, a lithosphere-asthenosphere boundary phase is observed at 60-90 km depth, marking the top of the low velocity layer.

We present a new approach that allows for the inversion of quantities derived from the observed data using non-diagonal data covariance matrices. For example, we can invert approximations of apparent resistivity and phase instead of magnetotelluric impedance using this methodology. Compared to the direct inversion of these derived quantities, the proposed methodology has two advantages: i) If an inversion algorithm allows for the specification of a full data covariance matrix, users can invert for arbitrary derived quantities by specifying the appropriate covariance matrix instead of having to rely on the inversion code to have implemented this feature. ii) It is fully compatible with the assumptions of least-squares optimization and thus avoids potential issues with bias when inverting quantities that are non-linear functions of the original data, We discuss the theory of this approach and show an example using magnetotelluric data. However, the same method can be applied to other types of geophysical data, for example gravity gradient measurements.

Water retention curves (WRCs) and hydraulic conductivity functions (HCFs) are critical soil-specific characteristics necessary for modeling the movement of water in soils using the Richardson-Richards equation (RRE). Well-established laboratory measurement methods of WRCs and HCFs are not usually unsuitable for simulating field-scale soil moisture dynamics because of the scale mismatch. Hence, the inverse solution of the RRE is used to estimate WRCs and HCFs from field measured data. Here, we propose a physics-informed neural networks (PINNs) framework for the inverse solution of the RRE and the estimation of WRCs and HCFs from only volumetric water content (VWC) measurements. Unlike conventional inverse methods, the proposed framework does not need initial and boundary conditions. The PINNs consists of three linked feedforward neural networks, two of which were constrained to be monotonic functions to reflect the monotonicity of WRCs and HCFs. Alternatively, we also tested PINNs without monotonicity constraints. We trained the PINNs using synthetic VWC data with artificial noise, derived by a numerical solution of the RRE for three soil textures. The PINNs were able to reconstruct the true VWC dynamics. The monotonicity constraints prevented the PINNs from overfitting the training data. We demonstrated that the PINNs could recover the underlying WRCs and HCFs in non-parametric form, without a need for initial guess. However, the reconstructed WRCs at near-saturation–which was not fully represented in the training data–was unsatisfactory. We additionally showed that the trained PINNs could estimate soil water flux density with a broader range of estimation than the currently available methods.

The Magnetospheric Multiscale (MMS) mission has presented a new opportunity to study the fine scale structures and phenomena of the Earth’s magnetosphere, including cross scale processes associated with the Kelvin-Helmholtz Instability (KHI), but such studies of the KHI and its secondary processes will require a database of MMS encounters with Kelvin-Helmholtz (KH) waves. Here we present an overview of 45 MMS observations of the KHI from September 2015 to March 2020. Growth rates and unstable solid angles for each of the 45 events were calculated using a new technique to automatically detect plasma regions on either side of the magnetopause boundary. There was no apparent correlation between solar wind conditions during the KHI and its growth rate and unstable solid angle, which is not surprising as KH waves were observed downstream of their source region. We note all KHI were observed for solar wind flow speeds between 295 km/s and 610 km/s, likely due to a filtering effect of the instability onset criteria and plasma compressibility. Two-dimensional Magnetohydrodynamic (2D MHD) simulations were compared with two of the observed MMS events. Comparison of the observations with the 2D MHD simulations indicates that the new region sorting method is reliable and robust. The ability to automatically detect separate plasma regions on either side of a moving boundary and determine the KHI growth rate may prove useful for future work identifying and studying secondary processes associated with the KHI.

The empirical constitutive modeling framework of Rate- and State-dependent Friction (RSF) is commonly used to describe the time-dependent frictional response of fault gouge to perturbations from steady sliding. In a previous study (Ferdowsi & Rubin, 2020), we found that a granular-physics-based model of a fault shear zone, with time-independent properties at the contact scale, reproduces the phenomenology of laboratory rock and gouge friction experiments in velocity-step and slide-hold protocols. A few slide-hold-slide simulations further suggested that the granular model might outperform current empirical RSF laws in describing laboratory data. Here, we explore the behavior of the same Discrete Element Method model in slide-hold and slide-hold-slide protocols over a wide range of sliding velocities, hold durations, and system stiffnesses, and provide additional support for this view. We find that, similar to laboratory data, the rate of stress decay during slide-hold simulations is in general agreement with the “Slip law” version of the RSF equations, using parameter values determined independently from velocity-step tests. During reslides following long hold times, the model, similar to lab data, produces a nearly constant rate of frictional healing with log hold time, with that rate being in the range of ~0.5-1 times the RSF “state evolution” parameter b. We also find that, as in laboratory experiments, the granular layer undergoes log-time compaction during holds. This is consistent with the traditional understanding of state evolution under the Aging law, even though the associated stress decay is similar to that predicted by the Slip and not the Aging law.

We study the effects of pore fluid pressure (Pf ) on the pre-earthquake, near-fault stress state and 3D earthquake rupture dynamics through 6 scenarios utilizing a structural model based on the 2004 Mw 9.1 Sumatra-Andaman earthquake. As pre-earthquake Pf magnitude increases, effective normal stress and fault shear strength decrease. As a result, magnitude, slip, peak slip rate, stress drop and rupture velocity of the scenario earthquakes decrease. Comparison of results with observations of the 2004 earthquake support that pre-earthquake Pf averages near 97 % of lithostatic pressure, leading to pre-earthquake average shear and effective normal tractions of 4-5 MPa and 22 MPa. The megathrust in these scenarios is weak, in terms of low mean shear traction at static failure and low dynamic friction coefficient during rupture. Apparent co-seismic principal stress rotations and absolute post-seismic stresses in these scenarios are consistent with the variety of observed aftershock focal mechanisms. In all scenarios, the mean apparent stress rotations are larger above than below the megathrust. Scenarios with larger Pf magnitudes exhibit lower mean apparent principal stress rotations. We further evaluate pre-earthquake Pf depth distribution. If Pf follows a sublithostatic gradient, pre-earthquake effective normal stress increases with depth. If Pf follows the lithostatic gradient exactly, then this normal stress is constant, shifting peak slip and peak slip rate up-dip. This renders constraints on near-trench strength and constitutive behavior crucial for mitigating hazard. These scenarios provide opportunity for future calibration with site-specific measurements to constrain dynamically plausible megathrust strength and Pf gradients.

The shape of ice-shelf cavities are a major source of uncertainty in understanding ice-ocean interactions. This limits assessments of the response of the Antarctic ice sheets to climate change. Here we use vibroseis seismic reflection surveys to map the bathymetry beneath the Ekström Ice Shelf, Dronning Maud Land. The new bathymetry reveals an inland-sloping trough, reaching depths of 1100 m below sea level, near the current grounding line, which we attribute to erosion by palaeo-ice streams. The trough does not cross-cut the outer parts of the continental shelf. Conductivity-temperature-depth profiles within the ice-shelf cavity reveal the presence of cold water at shallower depths and tidal mixing at the ice-shelf margins. It is unknown if warm water can access the trough. The new bathymetry is thought to be representative of many ice shelves in Dronning Maud Land, which together regulate the ice loss from a substantial area of East Antarctica.

A description and assessment of the first release of the Arctic Subpolar gyre sTate Estimate (ASTE_R1), a data-constrained ocean-sea ice model-data synthesis is presented. ASTE_R1 has a nominal resolution of 1/3o and spans the period 2002-2017. The fit of the model to an extensive (O(10^9)) set of satellite and in situ observations was achieved through adjoint-based nonlinear least-squares optimization. The improvement of the solution compared to an unconstrained simulation is reflected in misfit reductions of 77% for Argo, 50% for satellite sea surface height, 58% for the Fram Strait mooring, 65% for Ice Tethered Profilers, and 83% for sea ice extent. Exact dynamical and kinematic consistency is a key advantage of ASTE_R1, distinguishing the state estimate from existing ocean reanalyses. Through strict adherence to conservation laws, all sources and sinks within ASTE_R1 can be accounted for, permitting meaningful analysis of closed budgets at the grid-scale, such as contributions of horizontal and vertical convergence to the tendencies of heat and salt. ASTE_R1 thus serves as the biggest effort undertaken to date of producing a specialized Arctic ocean-ice estimate over the 21st century. Transports of volume, heat, and freshwater are consistent with published observation-based estimates across important Arctic Mediterranean gateways. Interannual variability and low frequency trends of freshwater and heat content are well represented in the Barents Sea, western Arctic halocline, and east subpolar North Atlantic. Systematic biases remain in ASTE_R1, including a warm bias in the Atlantic Water layer in the Arctic and deficient freshwater inputs from rivers and Greenland discharge.