A four-dimensional ensemble-variational (4DEnVar) data assimilation (DA) system was developed for global numerical weather predictions (NWPs). Instead of using the adjoint technique, this system utilizes a dimension-reduced projection (DRP) technique to minimize the cost function of the standard four-dimensional variational (4DVar) DA. It dynamically predicts ensemble background error covariance (BEC) initialized from its previous inflated analyses and realizes the flow-dependence of BEC in the variational configuration during the assimilation cycle. These inflated analyses, linear combinations of the ensemble analyses increment and balanced random perturbations, aim to prevent the predicted BEC from underestimation as well as to implicitly achieve the hybrid of the flow-dependent and static BEC matrices. A limited number of leading eigenvectors of the localization correlation function are selected to filter out the spurious correlations in the BEC matrix (B-matrix). In order to evaluate the new system, single-point observation experiments (SOEs) and observing system simulation experiments (OSSEs) were conducted with sounding and cloud-derived wind data. The flow-dependent characteristic was verified in the SOEs that utilized the localized ensemble covariance and compared with that of 4DVar. In the OSSEs, 4DEnVar reduced the analysis errors compared with 4DVar. The deterministic forecast initialized from the 4DEnVar ensemble mean analysis has better (worse) performance in the medium-range (long-range) forecasts in the Northern Extratropics and opposite performance in the Southern Extratropics, and exhibits slightly worse effects in the Tropics. Moreover, the ensemble mean forecast initialized from the 4DEnVar ensemble analyses has higher forecast skills than 4DVar.

This study proposes new insights for the interpretation of GEOVIDE particle measurements. Potentiel resuspension sites due to internal tides (ITs) have been identified along the western Iberian shelf slope using a tidal regional model. Iberian shelf is mainly a source of lithogenic material whereas Galicia Bank is a source of biogenic matter. The potential pathways for particles from the resuspension sites toward the GEOVIDE stations are identified using IBIRYS reanalysis to infer their transport by the ocean circulation. It appears that each station is influenced by a specific pathway and mixed particles from several resuspension sites. This methodology reveals that the criticality of the bathymetry slope, commonly used to track resuspension sites from internal waves, is not sufficient to investigate ITs. An explicit resolution of ITs using a numerical tidal model is required for an exhaustive identification of the resuspension sites.

Previous studies have demonstrated that tides are subject to considerable changes on secular time scales. However, these studies rely on sea level observations from tide gauges that are predominantly located in coastal and shelf regions and therefore, the large-scale patterns remain uncertain. Now, for the first time, satellite radar altimetry (TOPEX/Poseidon & Jason series) has been used to study worldwide linear trends in tidal harmonic constants of four major tides (M2, S2, O1, and K1). This study demonstrates both the potential and challenges of using satellite data for the quantification of such long-term changes. Two alternative methods were implemented. In the first method, tidal harmonic constants were estimated for consecutive four-year periods, from which the linear change was then estimated. In the second method, the estimation of linear trends in the tidal constants of the four tides was integrated in the harmonic analysis. First, both methods were assessed by application to tide gauge data that were sub-sampled to the sampling scheme of the satellites. Thereafter the methods were applied to the real satellite data. Results show both statistically significant decreases and increases in amplitude up to 1 mm/year and significant phase changes up to ~0.1 deg/year. The level of agreement between altimeter-derived trends and estimates from tide gauge data differs per region and per tide.

The Arctic Ocean main thermocline may be characterized by a series of fine-scale thermohaline staircase structures that are present in a wide range of regions, the formation mechanism of which remains unclear. Recent analysis has led to the proposal of a theoretical model which suggested that these staircase structures form spontaneously in the salinity and temperature-stratified ocean when the turbulent intensity determined by the buoyancy Reynolds number Reb is sufficiently weak (Ma and Peltier (2021)). In the current work, we have designed a series of Reb controlled direct numerical simulations of turbulence in the Arctic Ocean thermocline to test the effectiveness of this theory. In these simulations, the staircases form naturally when Reb falls in the range predicted by the instability criterion that is the basis of the proposed theory. In the DNS analyses described we show that the exponential growth-rate of the layering mode of instability matches well with the prediction of (Ma and Peltier (2021)). The staircases formed in our simulations are further compared with the classical diffusive interface model initially proposed by (Linden and Schirtcliff (1978)), which argued that stable staircase structures can only form when the density ratio Rρ is smaller than the critical value Rρ^{cr}=τ^(-1/2). . We show that the staircase structures can stably persist in the model regardless of whether or not Rρ is satisfied because of the involvement of stratified turbulence in the interfaces of the staircase.

Reach-scale morphological channel classifications are underpinned by the theory that each channel type is related to an assemblage of reach- and catchment-scale hydrologic, topographic, and sediment supply drivers. However, the relative importance of each driver on reach morphology is unclear, as is the possibility that different driver assemblages yield the same reach morphology. Reach-scale classifications have never needed to be predicated on hydrology, yet hydrology controls discharge and thus sediment transport capacity. The scientific question is: do two or more regions with quantifiable differences in hydrologic setting end up with different reach-scale channel types, or do channel types transcend hydrologic setting because hydrologic setting is not a dominant control at the reach scale? This study answered this question by isolating hydrologic metrics as potential dominant controls of channel type. Three steps were applied in a large test basin with diverse hydrologic settings (Sacramento River, California) to: (1) create a reach-scale channel classification based on local site surveys, (2) categorize sites by flood magnitude, dimensionless flood magnitude, and annual hydrologic regime type, and (3) statistically analyze two hydrogeomorphic linkages. Statistical tests assessed the spatial distribution of channel types and the dependence of channel type morphological attributes by hydrologic setting. Results yielded ten channel types. Nearly all types existed across all hydrologic settings, which is perhaps a surprising development for hydrogeomorphology. Downstream hydraulic geometry relationships were statistically significant. In addition, cobble-dominated uniform streams showed a consistent inverse relationship between slope and dimensionless flood magnitude, an indication of dynamic equilibrium between transport capacity and sediment supply. However, most morphological attributes showed no sorting by hydrologic setting. This study suggests that median hydraulic geometry relations persist across basins and within channel types, but hydrologic influence on geomorphic variability is likely due to local influences rather than catchment-scale drivers.

Fine-scale motions ($<$100 km) contribute significantly to the exchanges and dissipation of kinetic energy in the upper ocean. However, knowledge of ocean kinetic energy at fine-scales (in terms of density and transfers) is currently limited due to the lack of sufficient observational datasets at these scales. The sea-surface height measurements of the upcoming SWOT altimeter mission should provide information on kinetic energy exchanges in the upper ocean down to 10-15 km. Numerical ocean models, able to describe ocean dynamics down to $\sim$10 km, have been developed in anticipation of the SWOT mission. In this study, we use two state-of-the-art, realistic, North Atlantic simulations, with horizontal resolutions $ \sim $ 1.5 km, to investigate the distribution and exchanges of kinetic energy at fine-scales in the open ocean. Our results show that the distribution of kinetic energy at fine-scales approximately follows the predictions of quasi-geostrophic dynamics in summertime but is somewhat consistent with submesoscale fronts-dominated regimes in wintertime. The kinetic energy spectral fluxes are found to exhibit both inverse and forward cascade over the top 1000 m, with a maximum inverse cascade close to the average energy-containing scale. The forward cascade is confined to the ocean surface and shows a strong seasonality, both in magnitude and range of scales affected. Our analysis further indicates that high-frequency motions ($<$1day) play a key role in the forward cascade and that the estimates of the spectral fluxes based on geostrophic velocities fail to capture some quantitative aspects of kinetic energy exchanges across scales.

The year 2019 marks the 60th anniversary of the concept of radial diffusion in magnetospheric research. This makes it one of the oldest research topics in radiation belt science. While first introduced to account for the existence of the Earth’s outer belt, radial diffusion is now applied to the radiation belts of all strongly magnetized planets. But for all its study and application, radial diffusion remains an elusive process. As the theoretical picture evolved over time, so, too, did the definitions of various related concepts, such as the notion of radial transport. Whether data is scarce or not, doubts in the efficacy of the process remain due to the use of various unchecked assumptions. As a result, quantifying radial diffusion still represents a major challenge to tackle in order to advance our understanding of and ability to model radiation belt dynamics. The core objective of this review is to address the confusion that emerges from the coexistence of various definitions of radial diffusion, and to highlight the complexity and subtleties of the problem. To contextualize, we provide a historical perspective on radial diffusion research: why and how the concept of radial diffusion was introduced at Earth, how it evolved, and how it was transposed to the radiation belts of the giant planets. Then, we discuss the necessary theoretical tools to unify the evolving image of radial diffusion, describe radiation belt drift dynamics, and carry out contemporary radial diffusion research.

Submarine canyons enhance cross-shelf mass exchanges, which are a key component of on-shelf nutrient budgets and biogeochemical cycles. Previous studies assume that canyon-induced tracer flux onto the shelf only depends on canyon-induced water upwelling. This paper investigates the validity of this dependence for nutrients, carbon and dissolved gasses. To estimate the canyon-induced tracer upwelling flux and its spatial distribution on the shelf, we performed numerical experiments simulating an upwelling event near an idealized canyon, adding 10 passive tracers with initial profiles representing nutrients, carbon and dissolved gasses. This paper presents a scaling estimate for canyon-induced tracer upwelling and for the on-shelf distribution of a given tracer. We find that tracer upwelling depends on the mean initial vertical tracer gradient within the canyon, the depth of upwelling and the upwelling flux. We identify a pool of low oxygen and high nutrient concentration, methane, dissolved inorganic carbon and total alkalinity on the shelf bottom, downstream of the canyon. The horizontal extension of the pool depends on the canyon-induced advective fluxes feeding the pool and the initial background distribution of tracers on the shelf. This canyon-induced distribution of tracers has the potential to impact demersal and benthic ecosystems by lowering dissolved oxygen levels and spreading corrosive waters along the shelf.

During the late Miocene, global cooling occurred alongside the establishment of near-modern terrestrial and marine ecosystems. Significant (3 to 5 °C) sea surface cooling from 7.5 to 5.5 Ma is recorded by proxies at mid to high latitudes, yet the magnitude of tropical cooling and the role of atmospheric carbon dioxide (pCO2) in driving this trend are debated. Here, we present a new orbital-resolution sea surface temperature (SST) record spanning the late Miocene to earliest Pliocene (9 to 5 Ma) from the eastern equatorial Indian Ocean (International Ocean Discovery Program Site U1443) based on Mg/Ca ratios measured in tests of the planktic foraminifer Trilobatus trilobus. Our SST record reveals a 3.2 °C decrease from 7.4 to 5.8 Ma, significantly increasing previous estimates of late Miocene tropical cooling. Analysis of orbital-scale variability shows that before the onset of cooling, SST variations were dominated by precession-band (19-23 kyr) variability, whereas tropical temperature became highly sensitive to obliquity (41 kyr) after 7.5 Ma, suggesting an increase in high latitude forcing. We compare a revised global SST database with new paleoclimate model simulations and show that a pCO2 decrease from 560 ppm to 300 ppm, in the range suggested by pCO2 proxy records, could explain most of the late Miocene sea surface cooling observed at Site U1443. Estimation of meridional sea surface temperature gradients using our new Site U1443 record as representative of tropical SST evolution reveals a much more modest increase over the late Miocene than previously suggested, in agreement with modelled gradients.

Meteorological and geophysical hazards will concur and interact with coronavirus disease (COVID-19) impacts in many regions on Earth. These interactions will challenge the resilience of societies and systems. A comparison of plausible COVID-19 epidemic trajectories with multi-hazard time-series curves enables delineation of multi-hazard scenarios for selected countries (United States, China, Australia, Bangladesh) and regions (Texas). In multi-hazard crises, governments and other responding agents may be required to make complex, highly compromised, hierarchical decisions aimed to balance COVID-19 risks and protocols with disaster response and recovery operations. Contemporary socioeconomic changes (e.g. reducing risk mitigation measures, lowering restrictions on human activity to stimulate economic recovery) may alter COVID-19 epidemiological dynamics and increase future risks relating to natural hazards and COVID-19 interactions. For example, the aggregation of evacuees into communal environments and increased demand on medical, economic, and infrastructural capacity associated with natural hazard impacts may increase COVID-19 exposure risks and vulnerabilities. COVID-19 epidemiologic conditions at the time of a natural hazard event might also influence the characteristics of emergency and humanitarian responses (e.g. evacuation and sheltering procedures, resource availability, implementation modalities, and assistance types). A simple epidemic phenomenological model with a concurrent disaster event predicts a greater infection rate following events during the pre-infection rate peak period compared with post-peak events, highlighting the need for enacting COVID-19 counter measures in advance of seasonal increases in natural hazards. Inclusion of natural hazard inputs into COVID-19 epidemiological models could enhance the evidence base for informing contemporary policy across diverse multi-hazard scenarios, defining and addressing gaps in disaster preparedness strategies and resourcing, and implementing a future-planning systems approach into contemporary COVID-19 mitigation strategies. Our recommendations may assist governments and their advisors to develop risk reduction strategies for natural and cascading hazards during the COVID-19 pandemic.

We demonstrate that the relationship between the abundance of particulate surface area observed at sea-level and measurements of backscattered light by a ceilometer can be used to classify the mixing state of the atmospheric layer beneath the lowest observed cloud, where the relationship is defined by the Spearman Rank correlation. The accuracy of this correlation-based method was compared to two methods of detecting boundary layer decoupling based on radiosonde measurements. An optimized version of the new methodology correctly determined the mixing state of the below-cloud layer for 76 ± 4% of the radiosondes available for comparison. Further, it was more accurate than an alternative ground-based metric used to determine the below-cloud mixing state. For the majority of the time series in which the correlation analysis could be applied, the below-cloud boundary layer was well-mixed (54%), or else fog was present (27%), which indicated that aerosol particles observed at sea-level often have a direct pathway into low-cloud (81%). In the remaining analysis period, the near-surface atmospheric layer was stable and the atmospheric layer near the ocean surface was decoupled from the overlying cloud (19%). Forecasts from the Antarctic Mesoscale Prediction System also support our findings, showing that conditions that mix aerosol particles from the ocean surface to the lowest observed cloud occur 84% of the time over the open Southern Ocean. As a result, aerosol particles measured near sea-level are often tightly coupled to low-cloud formation over the Southern Ocean, highlighting the utility of shipborne aerosol observations in the region.

The steepness of the beach face is a fundamental parameter for coastal morphodynamic research. Despite its importance, it remains extremely difficult to obtain reliable estimates of the beach-face slope over large spatial scales (1000’s of km of coastline). In this letter, a novel approach to estimate this slope from time-series of satellite-derived shoreline positions is presented. This new technique uses a frequency-domain analysis to find the optimum slope that minimises high-frequency tidal fluctuations relative to lower-frequency erosion/accretion signals. A detailed assessment of this new approach at 8 locations spanning a range of tidal regimes, wave climates and sediment grain sizes shows strong agreement (R = 0.9) with field measurements. The automated technique is then applied across 1000’s of beaches in eastern Australia and California USA, revealing similar regional-scale distributions along these two contrasting coastlines and highlights the potential for new global-scale insight to beach-face slope spatial distribution, variability and trends.

Research interest in the Kinki region, southwestern Japan, has been aroused by the frequent occurrence of microearthquake activity that do not always coincide with documented active fault locations. Previous studies in the Kinki region focused mainly on deep, large-scale structures and could not efficiently resolve fine-scale (~10 km) shallow crustal structures. Hence, characterization of the upper crustal structure of this region at an improved spatial resolution is required. From the cross-correlation of the vertical components of the ambient seismic noise data recorded by a densely-distributed seismic array, we estimated Rayleigh wave phase velocities using a frequency domain method. Then, we applied a direct surface wave tomographic method for the measured phase velocity dispersion data to obtain the 3D S-wave velocity model of the Kinki region. The estimated velocity model reveals a NE-SW trending low-velocity structure coinciding with the Niigata-Kobe Tectonic Zone (NKTZ) and the active Biwako-seigan Fault Zone (BSFZ). Also, we identified fine-scale low-velocity structures coinciding with known active faults on the eastern side of the NKTZ, as well as sets of low-velocity structures across the Tanba region, that may be attributable to the weathering effects or activity of unidentified concealed fault zones. Furthermore, sedimentary basins manifest as low-velocity zones extending to depths ranging from ~1.5 to 2 km, correlating with those reported in previous studies. Our results therefore contribute towards fundamental understanding of earthquake faulting as well as tectonic boundary and will be useful for hazard assessment and disaster mitigation.

The continuous redistribution of water mass involved in the hydrologic cycle leads to deformation of The continuous redistribution of water involved in the hydrologic cycle leads to deformation of the solid Earth. On a global scale, this deformation is well explained by the loading imposed by hydrological mass variations and can be quantified to first order with space-based gravimetric and geodetic measurements. At the regional scale, however, aquifer systems also undergo poroelastic deformation in response to groundwater fluctuations. Disentangling these related but distinct 3D deformation fields from geodetic time series is essential to accurately invert for changes in continental water mass, to understand the mechanical response of aquifers to internal pressure changes as well as to correct time series for these known effects. Here, we demonstrate a methodology to accomplish this task by considering the example of the well-instrumented Ozark Plateaus Aquifer System (OPAS) in central United States. We begin by characterizing the most important sources of groundwater level variations in the spatially heterogeneous piezometer dataset using an Independent Component Analysis. Then, to estimate the associated poroelastic displacements, we project geodetic time series corrected for hydrological loading effects onto the dominant groundwater temporal functions. We interpret the extracted displacements in light of analytical solutions and a 2D model relating groundwater level variations to surface displacements. In particular, the relatively low estimates of elastic moduli inferred from the poroelastic displacements and groundwater fluctuations may be indicative of aquifer layers with a high fracture density. Our findings suggest that OPAS undergoes significant poroelastic deformation, including highly heterogeneous horizontal poroelastic displacements.

Despite decades-long debate over the mechanics of low-angle normal faults dipping less than 30°, many questions about their strength, stress, and slip remain unresolved. Recent geologic and geophysical observations have confirmed that gently-dipping detachment faults can slip at such shallow dips and host moderate-to-large earthquakes. Here, we analyze the first 3D dynamic rupture models to assess how different stress and strength conditions affect rupture characteristics of low-angle normal fault earthquakes. We model observationally constrained spontaneous rupture under different loading conditions on the active Mai’iu fault in Papua New Guinea, which dips 16-24° at the surface and accommodates ~8 mm/yr of horizontal extension. We analyze four distinct fault-local stress scenarios: 1) Andersonian extension, as inferred in the hanging wall; 2) back-rotated principal stresses inferred paleopiezometrically from the exhumed footwall; 3) favorably rotated principal stresses well-aligned for low-angle normal-sense slip; and 4) Andersonian extension derived from depth-variable static fault friction decreasing towards the surface. Our modeling suggests that subcritically stressed detachment faults can host moderate earthquakes within purely Andersonian stress fields. Near-surface rupture is impeded by free-surface stress interactions and dynamic effects of the gently-dipping geometry and frictionally stable gouges of the shallowest portion of the fault. Although favorably-inclined principal stresses have been proposed for some detachments, these conditions are not necessary for seismic slip on these faults. Our results demonstrate how integrated geophysical and geologic observations can constrain dynamic rupture model parameters to develop realistic rupture scenarios of active faults that may pose significant seismic and tsunami hazards to nearby communities.

Subduction zones are essential for mantle convection through the recycling of oceanic lithosphere, however, asthenospheric flow at convergent margins is not uniform. Deformation of the asthenosphere can be driven by subduction processes such as, viscous entrainment to plate motions, slab rollback-induced toroidal flow, and mantle wedge dynamics. These mechanisms are critical to understanding volcanism, margin evolution, and lithosphere-asthenosphere coupling. The easternmost Alaska subduction zone has been extensively studied showing evidence from seismic anisotropy for large-scale toroidal flow around the slab edge. Westward however, near the Shumagin Gap, few observations have been made. Along-strike changes in oceanic plate fabric, steepening slab dip, proximity to the slab edge, plate motion, and hydration of the mantle may all influence anisotropy and mantle flow in this region. Here, we evaluate models using independent offshore shear-wave splitting measurements acquired using data from the Alaska Amphibious Community Seismic Experiment (AACSE). We compare our splitting observations to forward models that consider the distribution of anisotropy and the backazimuthal dependence of observations. The models we test include viscously entrained flow due to oceanic plate motion (~310° CW North), anisotropic fabric variations, anisotropy related to bending faults and mantle serpentinization, and changes in frozen anisotropy in the oceanic lithosphere. Onshore shear-wave splitting observations show fast-axis directions ~55° CW North, inconsistent with 2D mantle wedge flow, assuming A-type olivine, but it is consistent with B-type fabric or trench-parallel flow as suggested by previous studies. Offshore splitting observations appear to vary along-strike. Here, two distinct oceanic plate fabrics exist, one developed from a northeast-spreading direction and the other from an east-spreading direction. Frozen anisotropy in the oceanic lithosphere may play a significant role in the splitting signal produced offshore and may be an important contributor to the distribution of seismic anisotropy. By synthesizing onshore and offshore observations here with our understanding of flow at the eastern slab edge, we can build a more complete model of mantle dynamics for the Alaskan subduction zone.

The export flux of organic carbon from the upper ocean is the starting point of the transfer and long term storage of photosynthetically-fixed carbon in the deep ocean. This “biological carbon pump” is a significant component of the global carbon cycle, reducing atmospheric CO2 levels by ~ 200 ppm. Carbon exported out of the upper ocean also fuels the productivity of the mesopelagic zone, including significant fisheries. Here we show that, despite its importance, export flux is poorly constrained in Earth System Models, with the modelled range in projected future global-mean changes due to climate change spanning +1.8 to -41%. Fundamental constraints to understanding export flux arise because a myriad of interconnected processes make the biological carbon pump challenging to both observe and model. Our synthesis prioritises the processes likely to be most important to include in modern-day estimates (particle fragmentation and zooplankton vertical migration) and future projections (phytoplankton and particle size spectra, and temperature-dependent remineralisation) of export. We also identify the observations required to achieve more robust characterisation, and hence improved model parameterization, of export flux, and thus decrease uncertainties in current and future estimates of this important planetary carbon flux.

Plankton play an important role in marine food webs, in biogeochemical cycling, and in Earth’s climate; yet observations are sparse, and predictions of how they might respond to climate change vary. Correlative species distribution models (SDM’s) have been applied to predicting biogeography based on relationships to observed environmental variables. To investigate sources of uncertainty, we use a correlative SDM to predict the plankton biogeography of a 21st Century marine ecosystem model (Darwin). Darwin output is sampled to mimic historical ocean observations, and the SDM is trained using generalised additive models. We find that predictive skill varies across test cases, and between functional groups, with errors that are more attributable to spatiotemporal sampling bias than sample size. End-of-century predictions are poor, limited by changes in target-predictor relationships over time. Our findings illustrate the fundamental challenges faced by empirical models in using limited observational data to predict complex, dynamic systems.