Seawater inundation was reported in the Limpopo River near the mouth at Xai-Xai, Mozambique. Local authorities identified a decrease in river flow as the cause of seawater inundation. We examined the potential of land subsidence in the relative risk of seawater inundation. Land subsidence has been identified as a risk to urban centers; however, we focused on the risk to the surrounding agricultural region. We used Sentinel-1 interferometric synthetic aperture radar (InSAR) with small baseline subset (SBAS) method to determine the rate of land subsidence throughout the agricultural-rich river valley surrounding Xai-Xai, Mozambique. InSAR presents a useful tool to assess land deformation; however, the signal decorrelated in the wet season, which limited our analysis to the dry season. Land subsidence may be due to groundwater abstraction, erosion without sediment transport and replenishment or other alteration of the surface, or tectonic movement. We estimated that the coastal region, which is largely agricultural, has subsided at an average rate of 13 mm/a from 2017 to 2022 and as much as 30 mm/a. This suggests that land subsidence contributes to the relative risk of seawater inundation on the same scale as the decrease in river discharge. Seawater inundation presents a threat to economic growth and food security in the region.

Large river systems provide many services, including water resources, barge transport, and sand and gravel (S&G) for mining. However, unlike damming, the impacts of channel dredging and S&G mining are poorly monitored. We quantify these impacts on the Lower Arkansas River, U.S.A., where anthropogenic processes are well documented. The construction of dams caused a 98% reduction in suspended sediment discharge (Qss). Since dam construction, fluvially-transported Qss and suspended sand discharge (Qsand) varied on the decadal scale, but the average of Qss (4.4 ± 0.5 Mtyr-1) and Qsand (1.1 ± 0.1 Mtyr-1) at Van Buren are of the same order as sediment removal rates by dredging (1.2 ± 0.1 Mtyr-1) and S&G mining (1.7 ± 0.1 Mtyr-1). During 1975-2019, the cumulative sediment deficit caused by dredging and S&G mining (1.7 Mtyr-1) outpaced the cumulative post-dam fluvial sediment deficit (0.7 Mtyr-1), indicating sediment extractions are now essential parts of rivers’ sediment balance.

Multiscale heterogeneity and insufficient characterization data for the specific subsurface formation of interest render predictions of multi-phase fluid flow in geologic formations highly uncertain. Quantification of the propagation uncertainty from the geomodel to the fluid-flow response is typically done within a probabilistic framework. This task is computationally demanding due to, e.g., the slow convergence of Monte Carlo simulations (MCS), especially when computing the tails of a distribution that will be used for risk assessment and decision-making under uncertainty. The frozen streamlines method (FROST) accelerates probabilistic predictions of immiscible two-phase fluid flow problems; however, FROST still relies on MCS to compute the travel-time distribution, which is then used to perform the transport (phase saturation) computations. To alleviate this computational bottleneck, we replace MCS with a deterministic equation for the cumulative distribution function (CDF) of the travel time. The resulting CDF-FROST approach yields the CDF of the saturation field without resorting to sampling-based strategies. Our numerical experiments demonstrate the high accuracy of CDF-FROST in computing the CDFs of both saturation and travel time. For the same accuracy, it is about 5 and 10 times faster than FROST and MCS, respectively.

Sentinel-3 A&B radar altimeters yield sea surface height measurements in both a high-precision Synthetic Aperture Radar Mode (SARM), and a Pseudo-Low Resolution Mode (PLRM). We stacked repeat cycles from both missions and in both modes to compare their resolution of small seamounts. Stacking entailed removing non-geoidal heights and height errors, testing for consecutive measurements over ocean, aligning to common locations at 1 km intervals along a synthetic track, and forming a median height profile. These profiles are available from the National Centers for Environmental Information (NCEI) data repository. Global maps show that, over the oceans, the median height is usually derived from more than 49 cycles, and the typical error in an individual PLRM measurement is approximately 1.9 times greater than an individual SARM measurement. We applied a seamount detection bandpass filter to the median profiles and compared their spectral resolution to that of the Satellite for ARgos and AltiKa (SARAL) AltiKa mission. Small seamounts are similarly resolved by Sentinel-3 A&B SARM data and by the SARAL/AltiKa data.

The artificial impoundment of water behind dams causes global mean sea level (GMSL) to fall as reservoirs fill, but also generates a local rise in sea level due to the increased mass in the reservoir and the crustal deformation this mass induces. To estimate spatiotemporal fluctuations in sea level due to water impoundment, we use a historical data set that includes 6,329 reservoirs completed between 1900 and 2011, as well as projections of 3,565 reservoirs that are expected to be completed by 2040. The GMSL change associated with the historical data (–0.2 mm yr-1 from 1900 – 2011) is consistent with previous studies, but the temporal and spatial resolution allows for local studies that were not previously possible, revealing that some locations experience a sea level rise of as much as 40 mm over less than a decade. Future construction of reservoirs through ~2040 is projected to cause a GMSL fall whose rate is comparable to that of the last century (–0.3 mm yr-1), but with a geographic distribution that will be distinct from the last century, including a rise in sea level in more coastal areas. The analysis of expected construction shows that significant impoundment near coastal communities in the coming decades could enhance the flooding risk already heightened by global sea level rise.

Much of the water that once flowed on the surface of Mars was lost to space long ago, and the total amount lost remains unknown. Clues to the amount lost can be found by studying hydrogen (H) and its isotope deuterium (D), both of which are produced when atmospheric water molecules H$_2$O and HDO dissociate. The freed H and D atoms then escape to space at different rates due to their different masses, leaving an enhanced D/H ratio. The rate of change of D/H is referred to as the fractionation factor $f$. Both the D/H ratio and $f$ are necessary to estimate water loss; thus, if we can constrain the range of $f$, we will be able to estimate water loss more accurately. In this study, we use a 1D photochemical model of the Martian atmosphere to determine how $f$ depends on assumed temperature and water vapor profiles. We find that for most Martian atmospheric conditions, $f$ varies between $10^{-1}$ and $10^{-5}$; for the standard Martian atmosphere, $f=0.002$ for thermal escape processes, and $f\approxeq0.06$ when both thermal and non-thermal escape are considered. Using these results, we estimate that Mars has lost at minimum 66-123 m GEL of water. Our results demonstrate that the value of $f$ is almost completely controlled by the amount of non-thermal escape of D, and that photochemical modeling studies that include fractionation must thus model both neutral and ion processes throughout the atmosphere.

Size segregation, which is a robust feature of sheared granular mixtures and geophysical mass flow deposits, is found to diminish in the presence of a viscous fluid. We study this inhibitive effect through coupled fluid-particle simulations of fully saturated granular flows. Granular-fluid mixture flows are modelled according to three distinct flow regimes -- free-fall, fluid-inertial, and viscous -- at different angles of inclination. Each flow regime corresponds to distinct flow dynamics and segregation behaviors. We find that segregation is indeed weaker and slower in the presence of an ambient fluid which is more so as the flow becomes more viscous. The ambient fluid affects segregation in two major ways. Firstly, buoyancy reduces the contact pressure gradients which are needed to drive large particles up, which at the same time reduces the particles' apparent weight. On the other hand, the streamwise drag force substantially changes the flow rheology, specifically the shear rate profile, thereby modifying the segregation behavior in the normal direction. Surprisingly, the fluid drag in the normal direction is negligible regardless of the fluid viscosity and does not affect segregation in a direct manner.

A lightning nitrogen oxides (LNOx) emissions model using satellite-observed lightning optical energy is introduced for utilization in Air Quality modeling systems. The effort supports assessments of air-quality/climate coupling as related to the influence of LNOx on atmospheric chemistry. The Geostationary Lightning Mapper (GLM), International Space Station Lightning Imaging Sensor (ISS-LIS), and the Tropical Rainfall Measuring Mission (TRMM) LIS data are used to examine the efficacy of the method, extend the previously derived LNOx record, and demonstrate a path for using ISS-LIS observations to cross-calibrate regional LNOx estimates from the future global constellation of geostationary lightning observations. A detailed evaluation of the GLM dataset is provided to establish the robustness of observations for LNOx estimates and to make preliminary assessments of the LNOx emissions model. Seasonal and geographical variation, land/ocean contrast, and annual fluctuation in the GLM observed lightning activity and flash optical energy are provided. GLM detection substantially degrades with the increase in the field of view, resulting in 44% more flashes and 40% less optical energy observation by GLM-16 (compared to GLM-17) to the east of the middle-longitude between the two mappers (106.2°W). Regular horizontal striations are found in the optical energy product. On average, GLM flashes matched to the cloud-to-ground flashes have ~30% longer duration, 50-70% more extension, and ≥ 100% higher optical energy compared to the unmatched flashes (assumed to be intra-cloud). The results from summer-long chemical transport simulations using LNOx generated from the emission model agrees with previous studies and shows consistency across the GLM/LIS datasets.

The recent deployment of nodal seismic instruments and DAS sensor networks has opened up a new chapter in observational seismology. Besides earthquake-generated signals, these new types of seismic array record a larger variety of low-frequency acoustic (infrasound) signals and noise than traditional instruments. Due to the near-surface deployments of these seismic sensing systems, the composition of the signals includes ground-motion sources that are associated with the atmosphere and manmade events. Meanwhile, with rapidly-growing data volumes recorded by nodal and DAS sensors, designing an automated system that detects time periods that are contaminated by these ground motions is essential. This presentation presents a comprehensive framework for the automated detection of ground-motion signals on seismic or infrasound instruments using computer vision, machine learning, and sensor fusion. Extensive experiments were conducted on Sage Brush Flats nodal array in Southern California, and our framework provides a benchmark performance for detecting aircraft events (one of the major ground-motion sources) and demonstrates the advantage of using an array of sensors. This framework is flexible and can also be extended to detecting other common types of ground motions, and to fusing other types of sensors. By combining models/systems that detect other types of ground motion, a complete characterization of the ground motions recorded by nodal and DAS sensor networks could be obtained. In addition, the data from other types of sensors such as All-Sky cameras and ADS-B or Mode S receivers could be integrated into this framework to further refine the detection performance.

Understanding the dynamic evolution of relativistic electrons in the Earth’s radiation belts during both storm and non-storm times is a challenging task. The U.S. National Science Foundation’s Geospace Environment Modeling (GEM) focus group “Quantitative Assessment of Radiation Belt Modeling” (QARBM) has selected two storm time and two non-storm time events that occurred during the second year of the Van Allen Probes mission for in-depth study. Here, we perform simulations for these GEM challenge events using the 3-Dimensional Versatile Electron Radiation Belt (VERB-3D) code. We set up the outer $L^*$ boundary using data from Geostationary Operational Environmental Satellites (GOES) and validate the simulation results against satellite observations from both the GOES and Van Allen Probe missions for 0.9 MeV electrons. Our results show that the position of the plasmapause plays a significant role in the dynamic evolution of relativistic electrons. The magnetopause shadowing effect is included by using last closed drift shell (LCDS), and it is shown to significantly contribute to the dropouts of relativistic electrons at high $L^*$.

Trace elements (TE) are tracers of multiple biotic and abiotic processes in the ocean and some of them are essential for marine life. Vertical export by particles is a major removal process of a large fraction of TE from the surface ocean. However, the seasonal export dynamics and its controlling factors, critical for the understanding of the internal TE cycling, remain poorly constrained. Here, we report and discuss the seasonal export of 15 TE in sinking particles collected by a sediment trap deployed in a highly productive region of the Southern Ocean. Basalt material was the main carrier phase for the export flux of 9 TE, and its dynamic was characterised by a strong decrease over time. TE export driven by biological carriers such as diatom spores and vegetative cells added pulsed seasonal dynamics to the lithogenic signal, while the contribution of fecal pellets was less variable over the season. For each TE, we were able to decipher the biological carrier phases that represent the most dominant export pathway. We discuss this partitioning with regards to the known metabolic functions of the different trace metals or TE of biological interest.

Despite the ability to image coronal mass ejections (CMEs) from the Sun through the inner heliosphere, the forecasting of their Time-of-Arrival (ToA) to Earth does not yet meet most Space weather users’ requirements. The main physical reason is our incomplete understanding of CME propagation in the inner heliosphere. Therefore, many ToA forecasting algorithms rely on simple empirical relations to represent the interplanetary propagation phase using, mostly, kinematic information from coronagraphic observations below 30 solar radii (Rs) and a couple rather implying assumptions of constant direction and speed for the transient. Here, we explore a different, yet still empirical approach. We replace the assumption of constant speed in the inner heliosphere with a two-phase behavior consisting of a decelerating (or accelerating) phase from 20 Rs to some distance, followed by a coasting phase to Earth. In a nod towards a forecasting scheme, we consider only Earth-directed CMEs use kinematic measurements only from the Heliospheric Imagers aboard both STEREO spacecraft, treat each spacecraft separately to increase the event statistics, analyze the measurements in a data-assimilative fashion and intercompare them against three popular localization schemes for single viewpoint observations (fixed-φ, harmonic mean and self-similar expansion. For the 21 cases, we obtain the best mean absolute error (MAE) of 6.4±1.9 hours, for the harmonic mean approximation. Remarkably, the difference between predicted and observed ToA is < 52 minutes for 42% of the cases. We find that CMEs continue to decelerate beyond even 0.7 AU, in some cases.

The Free Core Nutation (FCN) is a rotational mode related to non-alignment of the rotation axis of the core and of the mantle. There is a big gap between the observed FCN period (about 430 Sidereal days) and the theoretically calculated period (ranging from 450 Sd to 470 Sd). We propose a spectral element method to compute the period of FCN and obtain a good result, which is $437$ Sd. {\bf Keywords: } FCN, Spectral Element Method

Observations of fold growth in fold-thrust belt settings show that brittle deformation can be localized or distributed. Localized shear is associated with frictional slip on primary faults, while distributed brittle deformation is recognized in the folding of the bulk medium. The interplay of these processes is clearly seen in fault-bend folds, which are folds cored by a fault with an abrupt change in dip (e.g., a ramp-décollement system). While the kinematics of fault-bend folding were described decades ago, the dynamics of these structures remain poorly understood, especially the evolution of fault slip and off-fault deformation over different periods of the earthquake cycle. In order to investigate the dynamics of fault-bend folding, we develop a numerical modeling framework that combines a long-term elasto-plastic model of folding in a layered medium with a rate-state frictional model of fault strength evolution in order to simulate geologically and mechanically consistent earthquake sequences. In our simulations, slip on the ramp-décollement fault and inelastic fold deformation are mechanically coupled processes that build geologic structure. As a result, we observe that folding of the crust does not occur steadily in time but is modulated by earthquake cycle stresses. We suggest combining seismological and geodetic observations with geological fault models to uncover how elastic and inelastic crustal deformation generate fault-bend folds. We find that distinguishing between the elastic and inelastic response of the crust to fault slip is possible only in the postseismic period following large earthquakes, indicating that for most fault systems this information currently remains inaccessible.

Working with airborne electromagnetic (AEM) data acquired in the Kaweah Subbasin in the Central Valley of California, U.S.A., we developed a new approach for imaging the top of the bedrock and the confining Corcoran Clay layer. Our approach included multiple L2-norm and Lp-norm inversions as well as an interpolation process. The major improvement in imaging the two targets was made in the Lp-norm inversion step by incorporating prior knowledge. For the Corcoran Clay, pairs of resistivity and driller’s logs at two wells guided the selection of the best resistivity model and were used to increase the accuracy of the estimated Clay thickness. The bedrock surface was poorly constrained by well data in the existing groundwater model, appearing as a flat surface. We had good AEM data coverage in the area so had higher confidence in the obtained map of the bedrock surface at depths ranging from 15 m to 160 m. There was relatively good agreement between the location of the Corcoran Clay in the AEM data (depth ranging from 50 to 130 m and thickness ranging from 3 to 25 m) and the existing groundwater model, with both depth and thickness showing ~15% relative difference. The AEM data provided information about the continuity of the Corcoran Clay that is challenging to capture in the well data. The locations of the bedrock and Corcoran Clay were used in a structurally-constrained inversion to improve the imaging of the smaller-scale resistivity structure.

In a reference frame rotating with Mercury’s mantle and crust, the inner core and fluid core precess in a retrograde sense with a period of 58.646 days. The precession of a triaxial inner core with a different density than the fluid core induces a periodic gravity variation of degree 2, order 1. Elastic deformations from the pressure that the precessing fluid core exerts on the core mantle boundary also contribute to this gravity signal. We show that the periodic change in Stokes coefficients ΔC21 and ΔS21 for this signal of internal origin is of the order of 10^{-10}, similar in magnitude to the signal from solar tides. The relative contribution from the inner core increases with inner core radius and with the amplitude of its tilt angle with respect to the mantle. The latter depends on the strength of electromagnetic coupling at the inner core boundary which in turn depends on the radial magnetic field B_r; a larger B_r generates a larger tilt. The inner core signal features a contrast between ΔC21 and ΔS21 due to its triaxial shape, discernible for an inner core radius >500 km if B_r>0.1 mT, or for an inner core radius >1100 km if B_r<0.01 mT. A detection of this contrast would confirm the presence of an inner core and place constraints on its size and the strength of the internal magnetic field. These would provide key constraints for the thermal evolution of Mercury and for its dynamo mechanism.

Atmospheric rivers (ARs) are long and narrow filaments of vapor transport responsible for most poleward moisture transport outside of the tropics. Many AR detection algorithms have been developed to automatically identify ARs in climate data. The diversity of these algorithms has introduced appreciable uncertainties in quantitative measures of AR properties and thereby impedes the construction of a unified and internally consistent climatology of ARs. This paper compares eight global AR detection algorithms from the perspective of AR life cycles following the propagation of ARs from origin to termination in the MERRA2 reanalysis over the period 1980-2017. Uncertainties related to lifecycle characteristics, including number, lifetime, intensity, and frequency distribution are discussed. Notably, the number of AR events per year in the Northern Hemisphere can vary by a factor of 5 with different algorithms. Although all algorithms show that the maximum origin (termination) frequency locates over the northwestern (northeastern) Pacific, significant disagreements occur in regional distribution. Spreads are large in AR lifetime and intensity. The number of landfalling AR events produced by the algorithms can vary from 16 to 78 events per cool season, i.e. by almost a factor of five, although the agreement improves for stronger ARs. By examining the AR’s connection with the Madden-Julian Oscillation and El Niño Southern Oscillation, we find that the overall responses of ARs (such as changes in AR frequency, origin, and landfalling activity) to low-frequency climate variabilities are consistent among algorithms.

Remarkably, we know more about the radiation environment onboard the International Space Station than we do about radiation values at altitudes between 30-40 km in the middle stratosphere. Within this work, we provide data about the radiation dose measured during two consecutive balloon flights flown within a 4-month timeframe over New Mexico and Antarctica Data were measured with the M-42 radiation detector. On each flight, the M-42 was installed as part of a larger research payload: MARSBOx (New Mexico, 23 September 2019); and E-MIST (Antarctica, 15 December 2019-12 January 2020). The temporal proximity of the flights provided similar prevailing space weather conditions and solar activity (minimal during each mission). Against that common backdrop, the main differences between flights, including mission duration and geomagnetic shielding could be readily compared. Near identical space weather conditions provided a window of opportunity for studying the influence of altitude and geomagnetic shielding on dose and fluence rate of galactic cosmic radiation under maximum intensity conditions. Herein, we report relevant count- and dose rates for the missions, alongside Geant4 Monte Carlo calculations; this included crossings of the Regener maximum during the ascent and descent flights over New Mexico and the absence of a distinct maximum in dose rates at zero geomagnetic shielding for the polar flight. While dose rates in silicon at float altitudes (≈35 km-39 km) were a maximum of 2.5 +/- 0.4 microGy/h over New Mexico, we reached values of up to 8.4 +/- 0.3 microGy/h over Antarctica, thereby approaching dose rates similar to the surface of Mars.