The evolution of coastal hazards in the context of climate change has been addressed at the regional scale by studying the height and frequency of extreme sea levels (ESL). However, sea level is not the only factor determining the hazard changes that can be used at this scale. Therefore, this article proposes an assessment method of coastal hazard changes integrating other determinants: geographical configurations (continental or island), tidal regimes and meteo-oceanic event types. This method, applied to the coasts of France (mainland and overseas), reveals significant differences in the evolution of coastal hazards: coasts subjected to high tidal ranges and storms (e.g., Atlantic, English Channel and North Sea) will experience a relatively moderate evolution of the hazard, thanks to «training» for the future conditions that present-day high variations constitute. Conversely, the microtidal shorelines of temperate latitudes (e.g., those of the Mediterranean) benefit from only a small variability generated mainly by storm surges, and are therefore poorly prepared for sea level rise. The situation of the small tropical islands is of particular concern: with the passage of cyclones these territories are subjected to very energetic sea states, but by their form, the surges remain moderate, which constitutes, as well as the low tidal ranges, a limiting factor for preparing for sea level rise. In addition to this approach at the regional level, geological, sedimentary and biological evolutions, as well as local hydraulic phenomena, should be considered to assess at a finer spatio-temporal scale the hazard changes.

In well-buffered modern soils, higher annual rainfall is associated with enhanced soil ferrimagnetic mineral content, especially of ultrafine particles that result in distinctive observable rock magnetic properties. Hence, paleosol magnetism has been widely used as a paleoprecipitation proxy. Identifying the dominant mechanism(s) of magnetic enhancement in a given sample is critical for reliable inference of paleoprecipitation. Here we use high-resolution magnetic field and electron microscopy to identify the grain-scale setting and formation pathway of magnetic enhancement in two modern soils developed in higher (~580 mm/y) and lower (~190 mm/y) precipitation settings from the Qilianshan Range, China. We find both soils contain 1-30 µm aeolian Fe-oxide grains with indistinguishable rock magnetic properties while the higher-precipitation soil contains an additional population of ultrafine (<150 nm), magnetically distinct magnetite grains. We show that the in situ precipitation of these ultrafine particles, likely during wet-dry cycling, is the only significant magnetic enhancement mechanism in this soil. These results demonstrate the potential for quantum diamond microscope (QDM) magnetic microscopy to extract magnetic information from distinct, even intimately mixed, grain populations. This information can be used to evaluate the contribution of distinct enhancement mechanisms to the total magnetization.

Bodies of rock that are detached (recovered) from subducting oceanic plates, and exhumed to Earth’s surface, become invaluable records of the mechanical and chemical processing of rock along subduction interfaces. Exposures of interface rocks with high-pressure (HP) mineral assemblages provide insights into the nature of rock recovery, yet various interpretations concerning thermal gradients, recovery rates, and recovery depths arise when directly comparing the rock record with numerical simulations of subduction. Constraining recovery rates and depths from the rock record presents a major challenge because small sample sizes of HP rocks makes statistical inference weak. As an alternative approach, this study implements numerical simulations of oceanic-continental convergence and applies a classification algorithm to identify rock recovery. Over one million markers are classified from 64 simulations representing a large range of subduction zones. We find recovery P’s (depths) correlate strongly with convergence velocity and moderately with oceanic plate age, while PT gradients correlate strongly with oceanic plate age and upper-plate thickness. Recovery rates strongly correlate with upper-plate thickness, yet show no correlation with other boundary conditions. Likewise, PT distributions of recovered markers vary among numerical experiments and generally show poor overlap with the rock record. A significant gap in predicted marker recovery is found near 2 GPa and 550 ˚C, coinciding with the highest density of exhumed HP rocks. Implications for such a gap in marker recovery include numerical modeling uncertainties, petrologic uncertainties, selective sampling of exhumed HP rocks, or natural geodynamic factors not accounted for in numerical experiments.

Ambiguity over the Eocene opening times of the Tasman Gateway and Drake Passage makes it difficult to determine the initiation time of the Antarctic Circumpolar Current (ACC). If the Tasman Gateway opened later than Drake Passage, then Australia may have prevented the proto-ACC from forming. Recent modelling results have shown that only a relatively weak circumpolar transport results under Eocene surface forcing. This leads to warm and buoyant coastal water around Antarctica, which may impede the formation of deep waters and convective processes. This suggests that a change in deep water formation might be required to increase the density contrast across the Southern Ocean and increase circumpolar transport. Here we use a simple reduced gravity model with two basins, to represent the Atlantic and the Pacific. This fixes the density difference between surface and deep water and allows us to isolate the impact of deep water formation on circumpolar transport. With no obstacle on the southern boundary the circumpolar current increases its transport from 82.3 to 270.0 Sv with deep water formation. Placing an Antipodean landmass on the southern boundary reduces this transport as the landmass increases in size. However, circumpolar flow north of this landmass remains a possibility even without deep water formation. Weak circumpolar transport continues until the basin is completely blocked by the Antipodes. When the Antipodes is instead allowed to split from the southern boundary, circumpolar transport recovers to its unobstructed value. Flow rapidly switches to south of the Antipodes when the gateway is narrow.

The Great Slave Lake shear zone (GSLsz) is a type example for deeply eroded continental transform boundaries located in the Northwest Territories, Canada. Formed during the oblique convergence of the Archean Rae and Slave cratons, the GSLsz has accommodated up to 700 km of dextral shear. Here we present the results of in situ U-Pb apatite and titanite geochronology from 11 samples that were collected across the strike of the shear zone. Both geochronometers record a near-continuous history of ductile shear during crustal cooling and exhumation that spans ca. 1920–1740 Ma. By integrating the geochronological data with structural and metamorphic observations across the structure, we propose a tectonic model for the shear zone that consists of three stages. The first stage (ca. 1920–1880 Ma) is characterized by strain accommodation along two coeval fault strands. During the second stage (ca. 1880–1800 Ma), ductile shear ceases along the northernmost fault strand and the locus of strain migrates southwards towards the hinterland of the Rae cratonic margin. In the third stage (ca. 1800–1740 Ma), ductile strain localizes back along the southern of the two original fault strands, after which the present-day surface level of the shear zone transitions to brittle shear. Our results highlight both the significance of the lateral migration of the zone of active deformation in major crustal shear zones as well as the localization of strain along existing crustal structures.

The Jovian moon Io features hundreds of paterae, broad depressions often filled with lava. The largest such example, Loki Patera, features a large, polygonal, and fractured island in its center. This island may reflect the fragmentation of the upper Ionian lithosphere by a shallow magma body, facilitated by a great number of shallow extensional structures. We propose a model for the Ionian lithosphere in which the upper portion is heavily deformed by joints, normal faults, and graben resulting from combined tidal, subsidence, and thermal stresses, and a lower portion rife with major thrust faults formed by horizontal compression of deeper crustal levels from the continued burial of surface units. Some of those thrusts may be reactivated normal faults. An extensionally fractured upper lithosphere accounts for the Loki Patera island, for observations of more than 175 paterae with straight edges, for the fact that almost 95% of Io’s surface is covered with volcanic flow and plains units, and for widespread instances of mass wasting within Io’s gigantic mountain blocks. Additional, high-resolution image and topographic data are required to test this hypothesized model for the moon’s lithosphere.

Comets are active geological worlds with primitive surfaces that have been shaped to varying degrees by sublimation-driven sediment transport processes. Rosetta’s rendezvous with comet 67P/Churyumov-Gerasimenko (67P) in 2014 provided data with the necessary spatial and temporal resolutions to observe how micro-gravity worlds evolve. Rosetta’s observations have thus far revealed that the majority of changes to the surface occurred within 67P’s smooth terrains, vast sedimentary deposits that blanket a significant fraction of the nucleus. Understanding the global context of these changes, and therefore the sediment transport pathways that govern the evolution of 67P’s surface requires a thorough description of their changing morphologies, and an evaluation of existing global-scale spatial and temporal trends. Accordingly, we present a time-resolved synthesis of erosion and deposition activity on comet 67P as it passed through its August 13, 2015 perihelion from September, 2014 to August, 2016. Our mapping results indicate that, around perihelion, sediment is globally redistributed inter-regionally from 67P’s more active south to the north. Equally important, however, are local, topographically-influenced sediment transport processes, with large volumes of sediment moving intra-regionally over sub-kilometer scales. We also show evidence for regions of near-zero net erosion/deposition between approximately 30–60° latitude, which may act as terminal sedimentary sinks, with remobilization of these materials hindered by multiple factors. This work provides a complete mapping of the sediment transport processes and pathways across 67P observed by the Rosetta misison, and represents a critical step toward understanding the global landscape evolution of cometary surfaces.

MarsWRF, the general circulation model of Mars, is one of the most commonly used models to study the dust cycle in the Martian atmosphere. It has been widely used to study the mechanisms of dust storms and their effects on the Martian atmosphere. To better understand the ability of MarsWRF to simulate the dust cycle on Mars, this study assesses the current dust lifting schemes in the model, specifically the convective lifting and wind stress schemes. It is found that, by tuning lifting efficiency, the model with the convective lifting scheme can generally reproduce the seasonal variation of the mid-level atmospheric temperature (T15) but cannot reproduce the observed spatial distribution of dust devils, which exhibits non-homogeneous (uniform) distribution in the northern (southern) hemisphere. The model with the wind stress lifting scheme can generally capture the observed magnitude of T15 and column dust optical depth (CDOD) with properly tuned lifting efficiency and threshold drag velocity. There is a discrepancy in the assessment of modeling seasonal variations of dust with T15 and CDOD, which may be partly due to the observational uncertainties related to T15 and CDOD and the empirical modeling methods of Martian dust optical properties and radiative effect. For the spatial distribution of dust, there are significant simulation biases regardless of the tuning, which may be caused by the biases in the dust lifting process and large-scale atmospheric circulation. The analysis highlights that dust lifting schemes need further improvement to better represent the dust cycle and their impacts on Mars.

Nutrients associated with internal waves are known to perturb phytoplankton communities in oligotrophic oceans, but details of the relevant processes and mechanisms are unclear. Here we report insights about the impacts of internal waves on the phytoplankton community based on 154-hour time-series of observations in an oligotrophic basin of the South China Sea. We found that the temporal variations of phytoplankton communities in the upper, middle, and lower layers of the euphotic zone differ. We demonstrated that these changes probably resulted from the perturbation caused by internal waves. These results suggest that the structure of the phytoplankton community in oligotrophic oceans is best described by a three-layer system at steady state and that the perturbation caused by internal waves helps to reveal this structure. We believe that the paradigm of this three-layer structure will provide a new theoretical framework for the study of phytoplankton-based biogeochemical processes in oligotrophic oceans.

Sudden stratospheric warmings (SSWs) are large-scale phenomena characterized by dramatic dynamic disruptions in the stratospheric winter polar regions. Previous studies, especially those employing whole atmosphere models, indicate that SSWs have strong impacts on the circulation of the mesosphere lower thermosphere (MLT) and drive a reversal in the mean meridional circulation (MMC) near 90-125 km altitude. However, the robustness of these effects and the roles of SSW-induced changes in global-scale wave activity to drive the reversal have been difficult to observe simultaneously. This work employs horizontal lower thermospheric (~93-106 km altitude) winds near 10S-40N latitude from the Michelson Interferometer for Global High-resolution Thermospheric Imaging (MIGHTI) instrument onboard the Ionospheric Connection Explorer (ICON) to present observational evidence of a prominent MLT MMC reversal associated with the January 2021 major SSW event and to demonstrate connections to semidiurnal tidal activity and possible associations with a ~3-day ultra-fast Kevin wave (UFKW).

Seismological data can provide timely information for slope failure hazard assessments, among which rockfall waveform identification is challenging for its high waveform variations across different events and stations. A rockfall waveform does not have typical body waves as earthquakes do, so researchers have made enormous efforts to explore characteristic function parameters for automatic rockfall waveform detection. With recent advances in deep learning, algorithms can learn to automatically map the input data to target functions. We develop RockNet via multitask and transfer learning; the network consists of a single-station detection model and an association model. The former discriminates rockfall and earthquake waveforms. The latter determines the local occurrences of rockfall and earthquake events by assembling the single-station detection model representations with multiple station recordings. RockNet achieves macro F1 scores of 0.990 and 0.981 in terms of discriminating earthquakes and rockfalls from other events with the single-station detection and association models, respectively.

\justify Several methods have been developed to quantify the oceanic accumulation of anthropogenic carbon dioxide (CO$_2$) in response to rising atmospheric CO$_2$. Yet, we still lack a corresponding estimate of the changes in the total oceanic dissolved inorganic carbon (DIC). In addition to the increase in anthropogenic CO$_2$, changes in DIC also include alterations of natural CO$_2$. Once integrated globally, changes in DIC reflect the net oceanic sink for atmospheric CO$_2$, complementary to estimates of the air-sea CO$_2$ exchange based on surface measurements. Here, we extend the MOBO-DIC machine learning approach by \citeA{keppler_mapped_2020} to estimate global monthly fields of DIC at 1$^{\circ}$ resolution over the top 1500 m from 2004 through 2019. We find that over these 16 years and extrapolated to cover the whole global ocean down to 4000 m, the oceanic DIC pool increased close to linearly at an average rate of 3.2$\pm$0.7 Pg C yr$^{-1}$. This trend is statistically indistinguishable from current estimates of the oceanic uptake of anthropogenic CO$_2$ over the same period. Thus, our study implies no detectable net loss or gain of natural CO$_2$ by the ocean, albeit the large uncertainties could be masking it. Our reconstructions suggest substantial internal redistributions of natural oceanic CO$_2$, with a shift from the mid-latitudes to the tropics and from the surface to below $\sim$200 m. Such redistributions correspond with the Pacific Decadal Oscillation and the Atlantic Multidecadal Oscillation. The interannual variability of DIC is strongest in the tropical Western Pacific, consistent with the El Ni$\tilde{n}$o Southern Oscillation.

Global climate models often simulate atmospheric conditions incorrectly due to their coarse grid resolution, flaws in their dynamics, and biases resulting from parameterization schemes. Here we document the magnitude and extent of minimum temperature biases in the CMIP6 model ensemble, relative to ERA5. Bias in the southern Cascadia region (i.e. Pacific Northwestern United States and southwestern British Columbia, Canada, spanning from the coast to the Rocky Mountains) stands out relative to the rest of North America, with some models showing a bias in excess of -10°C in the 1st percentile of daily winter minimum temperature. During the coldest minimum temperature days, the CMIP6 models show an anomalous high in mean sea level pressure in the Northeast Pacific – an atmospheric blocking pattern that is also present in ERA5. While this atmospheric blocking pattern is typically concurrent with cold temperatures across much of North America, terrain barriers such as the Rockies and Cascades prevent the cold air from reaching the Pacific Northwest in observation and reanalysis. Our results suggest that the bias in CMIP6 minimum temperatures is a result of unresolved topography in the Rockies and Cascade mountain ranges, such that the terrain does not adequately block cold air advection from the interior of the continent.

Extending across seven countries, the Alps represent an important element for climate and atmospheric circulation in Central Europe. Its complex topography affects processes on different scales within the atmospheric system. This is of major relevance for the decadal trends in Surface Solar Radiation (SSR), also known as Global Dimming and Brightening (GDB). In this study we analysed data from 14 stations in and around the Swiss and Austrian Alps, over a period ranging from the 1960s up to the 2010s, with the aim of characterizing the spatio-temporal variations of the GDB and understanding the causes for such trends in this region. Our results showed a different behavior in the SSR decadal trends in the western part of the Alps in comparison to the eastern part. We also identified a remarkable difference between the causes of such trends in the stations at low altitudes in comparison to the station at higher altitudes. The SSR trends under cloudy conditions revealed strong evidence for a control of the decadal trends by cloud optical depth at high elevation sites, in contrast with a strong clear-sky forcing at low elevations. Results from previous literature and available data suggest that such phenomena could be associated with the indirect and direct aerosol effect, respectively, due to differing pollution levels.

Heat related illnesses are one of the leading causes of weather-related mortality in the United States, and heat extremes continue to increase in frequency and duration. Public health interventions include population mobility, including travel to central cooling centers or wellness checks on vulnerable populations. Using anonymized cellphone data from Safegraph’s neighborhood patterns dataset and gridded temperature data from gridMET, we explored the mobility-temperature relationship in the San Francisco Bay Area at fine spatial and temporal scale. We leveraged spatial variability in median income and temporal variability in COVID-19 related policies across two summers (2020-2021) to analyze their influence on the mobility-temperature relationship. We completed quantile regressions for a dataset stratified by income and year. We found that mobility increased at a higher rate with higher temperatures in 2020 than 2021. However, in 2021, the relationship reversed for several wealthier income groups, where mobility decreased with higher temperatures. We then augmented the analysis and calculated a panel regression with fixed effects to characterize the mobility-temperature relationship while controlling for temporal and spatial variability. This analysis suggested that all areas exhibited lower mobility with higher summer temperatures. However, similar to the results of the quantile regression, the rate of decrease in mobility in response to high temperature was significantly greater among the wealthiest census block groups compared with the least wealthy. Given the fundamental difference in the mobility response to temperature across income groups, our results are relevant for heat mitigation efforts in highly populated regions in current and future climate conditions.

The vertical structure of the Kuroshio Extension (KE) is investigated using velocity measurements from a subsurface mooring array. Mode decomposition based on climatological Temperature/Salinity (T/S) data shows that the barotropic and first baroclinic normal modes dominate the vertical structure of the zonal flow in the KE. This structure is also well described by the leading mode of Empirical Orthogonal Functions (EOFs) that contains the first two vertical normal modes. Further analysis demonstrates that the projection coefficient of the mooring velocity onto the summed vertical mode could be well represented by the surface geostrophic velocity. Therefore, we propose a dynamic method that relates the surface geostrophic flow and the vertical structure of the zonal flow. The applicability of this method is verified with both reanalysis datasets and estimation from hydrographic data. The findings implicate that the KE transport can be well reproduced by surface geostrophic flow and climatological T/S data only.

Quaternary convergence at rates of ~10 mm/yr between the Arabian and Eurasian plates is largely accommodated by the Kura fold-thrust belt at the longitude of the Greater Caucasus Mountains in Azerbaijan and eastern Georgia. Here we present the results of the first paleoseismic study of the Kura fold-thrust belt in Azerbaijan. A single paleoseismic trench was excavated across a 2-m-high fault scarp near Agsu revealing evidence of two recent surface rupturing earthquakes. Radiocarbon dating of the faulted sediments places limits of earthquake timing of AD 1713-1895 and AD 1872-2003 for the two events. Allowing for uncertainties in radiocarbon dating, the two events likely correspond to historical destructive M~7 earthquakes near Shamakhi, Azerbaijan in AD 1668 and 1902. Holocene shortening and dip-slip rates for the Kura fold-thrust belt are 8 and 8.5 mm/yr, respectively, based on the depositional age of an abandoned uplifted strath terrace in a water gap to the west of Agsu. These rates should be treated as maxima, as they are ~100% of the previously determined structurally and geodetically measured shortening across the belt, and were measured from only one of two primary structures in this part of the belt. The lack of reported historical ruptures from the past 8 centuries to the west of Agsu, in contrast with the numerous recorded destructive earthquakes of the Shamakhi region, suggests that the central and western parts of the Kura fold-thrust belt produce less frequent, but more destructive earthquakes, and may have accumulated sufficient strain to produce a M>8 earthquake.

Reliable short-time prediction of thermospheric mass density along the satellite orbit is always essential but challenging for the operation of Low-Earth orbit (LEO) satellites. In this paper, three machine-learning prediction algorithms are investigated, including the Bidirectional Long Short-Term Memory (Bi-LSTM), the Transformer, and the Light Gradient Boosting Machine (LightGBM) ensemble model of the above models. We use satellite data from CHAMP, GOCE, and SWARM-C to evaluate the robustness and accuracy of different density variations. The comparison demonstrates that all models achieve compelling predictions and are much better than NRLMSISE-00. The LightGBM ensemble model (LE-model) consistently outperforms others in accuracy and stability. Furthermore, when the obtained density data from the newly launched satellites are limited, the trained LE-model can provide a valid prediction for the new satellite orbit by transfer learning. This study offers a promising insight into the short-time prediction of thermospheric mass density using ensemble-transfer learning and may be advantageous to future research on space whether.