Crustal motion observations from Global Positioning System (GPS) networks have not yet been fully exploited in previous studies on glacial isostatic adjustment (GIA) and mantle rheology structure. In this study, we have isolated GIA signals from vertical velocity observations at rigorously selected (over 2,000) GPS stations from the Nevada Geodetic Laboratory (NGL) by removing the effects of atmospheric and oceanic loading, as well as changes in the contemporary glaciers. We have also attempted to include hydrological and sea-level loading corrections based on the most updated model products, but found them still not accurate enough for GIA-related studies. Therefore, we recommend the GPS-derived global GIA uplift rate dataset MIDAS-AO without hydrological and sea-level loading corrections applied. Under the constraints of MIDAS-AO uplift rates, we refined the VM5a viscosity model and obtained two revised viscosity profiles, VM5aR_AO1 and VM5aR_AO2, that differ by an extra layer in the transition zone of the latter profile. With respect to VM5a, VM5aR_AO1 indicates a slight increase of viscosity within the upper mantle, while VM5aR_AO2 favors a softer upper part of the upper mantle and a stiffer transition zone. Maps of the variations of model-dataset misfits show that our new viscosity profiles commonly recover a better fit for sites located at the Scandinavian Peninsula and south of the Hudson Bay.

Previous studies suggest that boreal summer intraseasonal variations along the subtropical westerly jet (SJ), featuring quasi-biweekly periodicity, frequently modulate downstream subseasonal variations over East Asia (EA). Based on subseasonal hindcasts from six dynamical models, this study discovered that the leading two-three-week prediction skills for surface air temperature (SAT) are improved significantly in summer when the SJ has strengthened intraseasonal signals, which are best demonstrated over the eastern Tibetan Plateau, Southwest Basin, and North China. The reasons are that the enhanced quasi-biweekly wave and the associated energy dispersion along the SJ cause more regular quasi-biweekly periodic variations of downstream SAT, which potentially increase regional predictability. This study suggests not only that intraseasonal variations along the SJ could provide a window of opportunity for achieving better subseasonal prediction over EA, but also that intraseasonal waves along the SJ are crucial for improving EA subseasonal prediction.

The seismic waves emitted during granular flows are generated by different sources: high frequencies by inter-particle collisions and low frequencies by global motion and large scale deformation. To unravel these different mechanisms, an experimental study has been performed on the seismic waves emitted by dry, dense, quasi-steady granular flows. The emitted seismic waves were recorded using shock accelerometers and the flow dynamics were captured with a fast camera. The mechanical characteristics of the particle collisions were analyzed, along with the intervals between collisions and the correlations in particles’ motion. The high-frequency seismic waves (1-50 kHz) were found to originate from particle collisions and waves trapped in the flowing layer. The low-frequency waves (20-60 Hz) were generated by particles’ oscillations along their trajectories, i.e. from cycles of dilation/compression during coherent shear. The profiles of granular temperature (i.e. the mean squared value of particle velocity fluctuations) and average velocity were measured and related to each other, then used in a simple steady granular flow model, in which the seismic signal consists of the variously attenuated contributions of shear-induced Hertzian collisions throughout the flow, to predict the rate at which seismic energy was emitted. Agreement with the measured seismic power was reasonable, and scaling laws relating the seismic power, the shear strain rate and the inertial number were derived. In particular, the emitted seismic power was observed to be approximately proportional to the root mean square velocity fluctuation to the power $3.1 \pm 0.9$, with the latter related to the mean flow velocity.

Coastal watersheds are vulnerable to compound flooding associated with intense rainfall, storm surge, and high tide. Coastal compound flooding (CCF) simulation, in particular for low-gradient coastal watersheds, requires a tight-coupling procedure to represent nonlinear and complex flood processes and interconnectivity among multidimensional hydraulics and hydrologic models. This calls for the development of a fully-coupled CCF modeling framework. Here, the modeling framework is centered around the development of interconnected meshes of the node-link-basin using the Interconnected Channel and Pond Routing (ICPR) model. The modeling framework has been built for a complex drainage network, consisting of tidal creeks, tidal channels, underground sewer networks, and detention ponds in Charleston Peninsula, SC. The floodplain dynamics of the urbanized peninsula are modeled by a high-resolution LiDAR-derived Digital Elevation Model (DEM) and Digital Surface Model (DSM), and overland flow is simulated by energy balance, momentum balance, or diffusive wave methods. The performance of the CCF model is tested for the 2015 SC major flood and 2021 tidal flood events. The momentum balance-based CCF model shows 98.35% efficiency in capturing street-level flooding location and the CCF model depicts that using the DSM potentially improves the simulation accuracy of the flood by 15-33% compared to LiDAR DEM. Moreover, it is found the momentum balance between surge arrival from a tidally influenced river and rainfall runoff plays an important role in flood dynamics in urbanized catchments. This study contributes to the existing knowledge of fine-scale floodplain dynamics in urban areas by enhancing the fully-coupled numerical representation of CCF processes.

Predicting secondary organic aerosol (SOA) formation relies either on extremely detailed, numerically expensive models accounting for the condensation of individual species or on extremely simplified, numerically affordable models parameterizing SOA formation for large-scale simulations. In this work, we explore the possibility of creating a random forest to reproduce the behavior of a detailed atmospheric organic chemistry model at a fraction of the numerical cost. A comprehensive dataset was created based on thousands of individual detailed simulations, randomly initialized to account for the variety of atmospheric chemical environments. Recurrent random forests were trained to predict organic matter formation from dodecane and toluene precursors, and the partitioning between gas and particle phases. Validation tests show that the random forests perform well without any divergence over 10 days of simulations. The distribution of errors shows that the sampling of initial conditions for the training simulations needs to focus on chemical regimes where SOA production is the most sensitive. Sensitivity tests show that specializing multiple random forests for a specific chemical regime is not more efficient than training a single general random forest for the entire dataset. The most important predictors are those providing information about the chemical regime, oxidants levels and existing organic mass. The choice of predictors is crucial as using too many unimportant predictors reduces the performances of the random forests.

Changes in atmospheric iron (Fe) deposition to the open ocean affect net primary productivity, nitrogen fixation, and carbon uptake rates. We investigate the changes in soluble Fe (SFe) deposition from the pre-industrial period to the late 21st century using the EC-Earth3-Iron Earth System model, which stands out for its comprehensive representation of the atmospheric oxalate, sulfate, and Fe cycles. We show how anthropogenic activity has modified the magnitude and spatial distribution of SFe deposition by increasing combustion Fe emissions along with atmospheric acidity and oxalate levels. We find that SFe deposition has doubled since the early Industrial Era using the Coupled Model Intercomparison Project Phase 6 (CMIP6) emission inventory, with acidity being the main solubilization pathway for dust Fe, and ligand-promoted (oxalate) processing dominating the solubilization of combustion Fe. We project a global SFe deposition increase of 40% by the late 21st century relative to present day under Shared Socioeconomic Pathway (SSP) 3-7.0, which assumes weak climate change mitigation policies. In contrast, sustainable and business-as-usual SSPs (1-2.6 and 2-4.5) result in 35% and 10% global decreases, respectively. Despite these differences, SFe deposition consistently increases and decreases across SSPs over the (high nutrient low chlorophyl) equatorial Pacific and Southern Ocean (SO), respectively. Future changes in dust and wildfires with climate remains a key challenge for constraining SFe projections. We show that the equatorial Pacific and the SO would be sensitive not only to changes in Australian or South American dust emissions, but also to those in North Africa.

There are now more interferograms being generated from global satellite radar datasets than can be assessed by hand. The reliable, automatic detection of true displacement from these data is therefore critical, both for monitoring deformation related to geohazards and understanding solid earth processes. We discuss improvements to an unsupervised, event agnostic method for automatically detecting deformation in unwrapped interferograms. We use an anomaly detection framework that recognises any deformation as “anomalies” by learning the ‘typical’ spatio-temporal pattern of atmospheric and other noise in sequences of interferograms. Here, we present developments to our prototype model, ALADDIn (Autoencoder-LSTM based Anomaly Detector of Deformation in InSAR) using (1) a self-attention training technique to exploit redundancy in interferogram networks to capture the temporal structure of signals and (2) the addition of synthetic data for training. We evaluate the impact of these developments using two geophysical scenarios: (1) the detection of the same M_w 5.7 earthquake used to test our original model (20.03.2019, south-west Turkey), (2) the persistent uplift of Domoyu volcano (17.05.2017 to 14.12.2018, Argentina). We make a quantitative evaluation of the performance of our method using synthetic test data and find that for peak displacements exceeding a few cm and of length-scale greater than a few hundred metres, overall detection accuracy is 80 to 90%.

For the first time in 2015, four dedicated hydrographic cruises – one in each season – took place around the Canary Islands to determinate the seasonality of the flows at the eastern boundary of the North Atlantic Subtropical Gyre. The Canary Current (CC) is the eastern boundary current of the North Atlantic Subtropical Gyre and links the Azores Current with the North Equatorial Current. The CC shows a seasonal behavior in its path and strength, flowing on its easternmost position in winter (3.4±0.3 Sv), through the Canary Islands in spring (2.1±0.7 Sv) and summer (2.0±0.6 Sv) and on its westernmost position in fall (3.2±0.4 Sv). At the Lanzarote Passage (LP), the dominant flow is southward except in fall, where a northward transport is observed at surface (1.1±0.3 Sv) and intermediate (1.3±0.2 Sv) layers. A historical composite observational seasonal cycle is built from all the available estimations on the area and fits the 2015 seasonal cycle. The LP seasonal cycle and seasonal amplitude match the seasonal cycle of the Atlantic Meridional Overturning Circulation (AMOC) measured by the RAPID-MOCHA data array.

Graphene or graphene-based nanomaterials have emerged as novel scaffolds for developing robust bio-catalytic systems and a fast-developing promising contender for bioremediation. The interaction of bacteria and graphene is such an elusive issue that its implication in environmental biotechnology is unclear. The complexity and recalcitrant nature of the dyes make the conventional techniques inadequate and remain a challenge for industrial effluent treatment. Many scientists have developed hybrid processes and hybrid materials to enhance the treatment processes to satisfy increasingly stringent laws and criteria related to effluent discharge. The current study explicitly focuses on immobilization and growth of dye-degrading marine bacterial isolates on graphene oxide and their application in methylene blue dye degradation. The synergistic effects of adsorption and biodegradation achieved a unique clean-up performance that the counterpart-free bacteria could not fulfill. Further, toxicity analysis of intermediates also confirmed the non-toxic nature of the intermediates formed after synergistic treatment. This work has the potential to lead to zero effluent treatment processes.

The causes of the variations in CO2 of the past million years remain poorly understood. Imbalances between the input of elements from rock weathering and their removal from the atmosphere-ocean-biosphere system to the lithosphere likely contributed to reconstructed changes. We employ the Bern3D Earth system model of intermediate complexity to investigate carbon-climate responses to step-changes in the weathering input of phosphorus, alkalinity, carbon, and carbon isotope ratio (δ13C) in simulations extending up to 600,000 years. CO2 and climate approach a new equilibrium within a few ten thousand years, whereas the equilibration lasts several hundred thousand years for δ13C. These timescales represent a challenge for the initialization of sediment-enabled models and unintended drifts may be larger than forced signals in simulations of the last glacial-interglacial cycle. Changes in dissolved CO2 change isotopic fractionation during marine photosynthesis and δ13C of organic matter. This mechanism and changes in the organic matter export cause distinct spatio-temporal perturbations in δ13C of dissolved inorganic carbon. A cost-efficient emulator is built with the Bern3D responses and applied in contrasting literature-based weathering histories for the past 800,000 years. Differences between scenarios for carbonate rock weathering reach around a third of the glacial-interglacial CO2 amplitude, 0.05 ‰ for δ13C, and exceed reconstructed variations in marine carbonate ion. Plausible input from the decomposition of organic matter on shelves causes variations of up to 10 ppm in CO2 , 4 mmol m−3 in CO2−3, and 0.09‰ in δ13C. Our results demonstrate that weathering-burial imbalances are important for past climate variations.

NASA’s Van Allen Probes observed significant, long-lived fluxes of inner belt electrons up to ~1MeV after geomagnetic storms in March and June 2015. Reanalysis of MagEIS data with improved background correction showed a clearer picture of the relativistic electron population that persisted through 2016 and into 2017 above the Fennel et al. (2015) limit. The intensity and duration of these enhancements allow estimation of decay timescales for comparison with simulated decay rates and theoretical lifetimes. We compare decay timescales from these data and DREAM3D simulations based on them using geomagnetic activity-dependent pitch angle diffusion coefficients derived from plasmapause-indexed wave data (Malaspina et al., 2016, 2018) and phase space densities derived from MagEIS observations. Simulated decay rates match observed decay rates more closely than the theoretical lifetime due to significantly nonequilibrium pitch angle distributions in simulation and data. We conclude that nonequilibrium effects, rather than a missing diffusion or loss process, account for observed short decay rates.

Convective cold pools (CPs) are known to mediate the interaction between convective rain cells and thereby help organize thunderstorm clusters, in particular mesoscale convective systems and extreme rainfall events. Unfortunately, the observational detection of CPs on a large scale has so far been hampered by the lack of relevant large-scale nearsurface data. Unlike numerical studies, where high-resolution near-surface fields of relevant quantities such as virtual temperature and winds are available and frequently used to detect cold pools, observational studies mainly identify CPs based on surface time series. Since research vessels or weather stations measure these time series locally, the characterization of cold pools from observations is limited to regional or station-based studies. To eventually enable studies on a global scale, we here develop and evaluate a methodology for the detection of CPs that relies only on data that (i) is globally available and (ii) has high spatio-temporal resolution. We trained convolutional neural networks to segment CPs in cloud and rainfall fields from high-resolution cloud resolving simulation output. Such data is not only available from simulations, but also from geostationary satellites that fulfill both (i) and (ii). The networks make use of a U-Net architecture, a common choice for image segmentation due to its strength in learning spatial correlations at different scales. Based on cloud and rainfall fields only, the trained networks systematically identify CP pixels in the simulation output. Our methodology may thus open for reliable global CP detection from space-borne sensors. As it also provides information on the spatial extent and the relative positioning of CPs over time, our method may offer new insight into the role of CPs in convective organization.

Distributed Acoustic Sensing (DAS) enables data acquisition for underwater Earth Science with unprecedented spatial resolution. Submarine fibre optic cables traverse sea bottom features that can lead to suspended or decoupled cable portions, and are exposed to the ocean dynamics and to high rates of marine erosion or sediment deposition, which may induce temporal variations of the cable’s mechanical coupling to the ocean floor. Although these spatio-temporal fluctuations of the mechanical coupling affect the quality of the data recorded by DAS, and determine whether a cable section is useful or not for geophysical purposes, the detection of unsuitable cable portions has not been investigated in detail. Here, we report on DAS observations of two distinct vibration regimes of seafloor fibre optic cables: a high-frequency (> 2 Hz) regime we associate to cable segments pinned between seafloor features, and a low-frequency (< 1 Hz) regime we associate to suspended cable sections. While the low-frequency oscillations are driven by deep ocean currents, the high-frequency oscillations are triggered by the passage of earthquake seismic waves. Using Proper Orthogonal Decomposition, we demonstrate that high-frequency oscillations excite normal modes comparable to those of a finite 1D wave propagation structure. We further identify trapped waves propagating along cable portions featuring high-frequency oscillations. Their wave speed is consistent with that of longitudinal waves propagating across the steel armouring of the cable. The DAS data on cable sections featuring such cable waves are dominated by highly monochromatic noise. Our results suggest that the spatio-temporal evolution of the mechanical coupling between fibre optic cables exposed to the ocean dynamics and the seafloor can be monitored through the combined analysis of the two vibration regimes presented here, which provides a DAS-based method to identify underwater cable sections unsuitable for the analysis of seismic waves.

Camera-based rainfall observation is a useful technology that contributes to the densification of rainfall observation networks because it can measure rainfall with high spatio-temporal resolution and low cost. To develop of practical camera-based rainfall observation technology, using the extinction coefficient as a clue, this study proposed relational Equations representing the relationship between image information, rainfall intensity, and scene depth by linking the theoretically derived rainfall intensity with a technique proposed in the computer vision field for removing static weather effects. Then, the proposed Equations were applied to outdoor images taken by commercial interval cameras at the observation site in a mountainous watershed in Japan. As a result, it was confirmed that transmission calculated from the image information decreases exponentially according to the increase in rainfall intensity and scene depth, as assumed in the proposed Equations. Therefore, the proposed Equations are generally valid even for outdoor images, and extremely important findings that will improve camera-based rainfall observation techniques were obtained. On the other hand, the calculated extinction coefficient tended to be overestimated in patches with a small scene depth, and overestimation of the extinction coefficient due to aerosol effects was also observed in the images taken during no rainfall. Although there are issues at present that need to be resolved for the technology proposed in this study, this technology has the potential to help the development of a camera-based rainfall observation technology that is accurate, robust, versatile, and accessible.

The imprint of marine atmospheric boundary layer (MABL) dynamical structures on sea surface roughness, as seen from Sentinel-1 Synthetic Aperture Radar (SAR) acquisitions, is investigated. We focus on February 13th, 2020, a case study of the EUREC4A (Elucidating the role of clouds-circulation coupling in climate) field campaign. For suppressed conditions, convective rolls imprint on sea surface roughness is confirmed through the intercomparison with MABL turbulent organization deduced from airborne measurements. A discretization of the SAR wide swath into 25 x 25 km$^2$ tiles then allows us to capture the spatial variability of the turbulence organization varying from rolls to cells. Secondly, we objectively detect cold pools within the SAR image and combine them with geostationary brightness temperature. The geometrical or physically-based metrics of cold pools are correlated to cloud properties. This provides a promising methodology to analyze the dynamics of convective systems as seen from below and above.

Accelerating aseismic slip events have been commonly observed during the rupture nucleation processes of the earthquake. While that accelerating aseismic slip is usually considered strong evidence for precursory activity, it remains unclear whether all accelerating aseismic slip events are precursory to an incoming earthquake. Two contrasting nucleation models have been introduced to explain the observations associated with the nucleation of unstable slip: the pre-slip and cascade nucleation models. Each of these two-end members, however, has its own limitations. In this study, we employ Discrete Element Method (DEM) simulations of a 2-D strike-slip fault to simulate various rupture nucleation and triggering processes. Our simulation results manifest that the final seismic event is a product contributed by multiple pre-slip nucleation sites, which may interact, causing clock advance or cascade nucleation rupture processes. We also introduce a strengthening perturbation zone to investigate the role of a single nucleation site in an imminent seismic event. The simulation results reveal a new type of non-precursory aseismic slip, representing the region favoring the generation of the precursory slip process but not correlating to the incoming main event, which differs from the previous interpretation of precursory slip. Furthermore, we include weakening perturbation zones in some simulations to demonstrate how small earthquakes may or may not trigger a nucleation site depending on spatial and temporal conditions. Our simulation results imply that such non-precursory but accelerating aseismic slip events may suggest a fault segment that appears weakly coupled but possesses the potential to be triggered seismically.

In this paper, we applied a variety of statistical methods to study gravity waves in the troposphere and lower stratosphere in the Brazilian sector, using an unprecedented large database from Instituto de Controle do Espaço Aéreo (ICEA) of radiosonde measurements carried out in 2014 on 32 locations in the Brazilian territory totaling 49,652 wind profiles. The average wind profiles were computed and classified by means of a hierarchical cluster analysis. The kinetic and potential energy densities of the gravity waves were determined using a detrending technique based on the least squares method and the Fast Fourier Transform. The time series of the energy densities were analyzed in detail and some persistent and seasonal behavior was found in some cases. A systematic search for quasi monochromatic waves was carried out and the main characteristics of such waves propagating in the troposphere and the lower stratosphere were found. The correlation analysis between the troposphere and the lower ionosphere based on parameters observed on both layers was used to investigate the wave coupling between the two layers. The results we found have implications in the so-called seeding problem of the equatorial ionospheric irregularities.

The open-source PlanetProfile framework was developed to investigate the interior structure of icy moons based on self-consistency and comparative planetology. The software, originally written in Matlab, relates observed and measured properties, assumptions such as the type of materials present, and laboratory equation-of-state data through geophysical and thermodynamic models to evaluate radial profiles of mechanical, thermodynamic, and electrical properties, as self-consistently as possible. We have created a Python version of PlanetProfile. In the process, we have made optimization improvements and added parallelization and parameter-space search features to utilize fast operation for investigating unresolved questions in planetary geophysics, in which many model inputs are poorly constrained. The Python version links to other scientific software packages, including for evaluating equation-of-state data, magnetic induction calculations, and seismic calculations. Physical models in PlanetProfile have been reconfigured to improve self-consistency and generate the most realistic relationships between properties. Here, we describe the software design and algorithms in detail, summarize models for major moons across the outer solar system, and discuss new inferences about the interior structure of several bodies. The high values and narrow uncertainty ranges reported for the axial moments of inertia for Callisto, Titan, and Io are difficult to reconcile with self-consistent models, requiring highly porous rock layers equivalent to incomplete differentiation for Callisto and Titan, and a high rock melt fraction for Io. This effect is even more pronounced with the more realistic models in the Python version. Radial profiles for each model and comparison to prior work are provided as Zenodo archives.

Tidal salt marshes are widespread along the World’s coasts, and are ecologically and economically important as they provide several valuable ecosystem services. In particular, their significant primary production, coupled with sustained vertical accretion rates, enables marshes to sequester and store large amounts of organic carbon and makes them one of the most carbon-rich ecosystems on Earth. Organic carbon accumulation results from the balance between inputs, i.e. organic matter produced by local plants or imported, and outputs through decomposition and erosion. Additionally, organic matter deposition actively contributes to marsh vertical accretion, thus critically affecting the resilience of marsh ecosystems to rising relative sea levels. A better understanding of organic-matter dynamics in salt marshes is key to address salt-marsh conservation issues and to elucidate marsh importance within the global carbon cycle. Toward this goal, we empirically derived rates of organic matter decomposition by burying 712 commercially available tea bags at different marshes in the microtidal Venice Lagoon (Italy), and by analyzing them following the Tea Bag Index protocol. We find values of the decomposition rate (k) and stabilization factor (S) equal to 0.012±0.003 day-1 and 0.15±0.063, respectively. Water temperature critically affects organic matter decomposition, enhancing decomposition rates by 8% per °C on average. We argue that, at least in the short term, the amount of undecomposed organic matter that actively contributes to carbon sequestration and marsh vertical accretion strongly depends on the initial organic matter quality, which is a function of marsh and vegetation characteristics.

Pressure transient and tracer testing are conventional methods employed to investigate physical properties associated with fluid flow and/or storage in subsurface reservoirs or aquifers. These methods have been adopted independently to investigate from different physical aspects. Here, to quantify the heterogeneity of pore distributions containing subsurface fluid, a novel concept, which combines the pressure and tracer concentration responses obtained during pressure transient and tracer tests, respectively, has been proposed and validated. Herein, the key parameter is the difference between the apertures of the equivalent planar fractures estimated from the pressure and tracer concentration responses. In particular, this difference is attributed to the fact that the pressure and tracer concentration responses obey different physical mechanisms, diffusion and advection–dispersion problems, respectively, that generate dissimilar responses to the heterogeneity of pore distribution. The concept was successfully validated using laboratory experiments and reservoir simulations conducted at multiple scales. As observed, the apparent pore volume estimated from the pressure responses tended to be larger than the actual value owing to the delay in pressure responses during propagation through the pore. By quantifying the existence of undiscovered permeable structures in a reservoir simulation model, the proposed concept provides an insightful guide for successful decision-making in explorational and developmental geothermal projects. Furthermore, the concept provides a scale for assessing the accuracy of a reservoir simulation model in expressing an actual heterogeneous permeable structure.

The study was carried out to find significant lipid constituents of Sporotrichum schenckii (S. schenckii), purified lipid extract was assessed, and the ecology of S. schenckii was also studied. Phospholipids, triglycerides, and cholesterol were the three major lipid constituents of S. schenckii (77.9%). Other lipids (22.1%) were too few to be quantitated. 16 different types of fungi were isolated out of 120 samples processed; the maximum isolations were of Aspergillus spp., the most typical contaminant fungus. There was no particular correlation between the fungus isolate and the type of sample or its collection site. The pattern of various fungal isolates was almost identical irrespective of the sample and place. None of the samples processed was positive for S. schenckii S. schenckii, though said to be a saprophyte, was not grown in the 120 samples studied. The endemicity of the disease, however, points towards the existence of the fungus in the area.

Significant multi-centennial climate variability with a clear peak at approximately 200 years is found in a pre-industrial control simulation conducted with the EC-Earth3 climate model. The oscillation mainly emerges from the North Atlantic and appears to be closely associated with the Atlantic Meridional Overturning Circulation (AMOC). By examining the salinity advection feedback, we find that the perturbation flow of mean subtropical-subpolar salinity gradients in the subpolar area governs as positive feedback to the AMOC anomaly. Meanwhile, the mean advection of salinity anomalies and the vertical mixing or convection acts as negative feedback to restrain the AMOC anomaly. In a warmer climate, although the AMOC becomes weaker, such low-frequency variability still exists, indicating the robustness of the salinity advection feedback mechanism.

An intense earthquake swarm is occurring in the crust of the northeastern Noto Peninsula, Japan. Fluid movement related to volcanic activity is often involved in earthquake swarms in the crust, but the last volcanic activity in this area occurred in the middle Miocene (15.6 Ma), and no volcanic activity has occurred since then. In this study, we investigated the cause of this earthquake swarm using spatiotemporal variation of earthquake hypocenters and seismic reflectors. Hypocenter relocation revealed that earthquakes moved from deep to shallow areas via many planes, similar to earthquake swarms in volcanic regions. The strongest M5.4 earthquake initiated near the migration front of the hypocenters. Moreover, it ruptured the seismic gap between the two different clusters. The initiation of this earthquake swarm occurred at a locally deep depth (z = ~17 km), and we found a distinctive S-wave reflector, suggesting a fluid source in the immediate vicinity. The local hypocenter distribution revealed a characteristic ring-like structure similar to the ring dike that forms just above the magma reservoir and is associated with caldera collapse and/or magma intrusion. These observations suggest that the current seismic activity was impacted by fluids related to ancient or present hidden magmatic activity, although no volcanic activity was reported. Significant crustal deformation was observed during this earthquake swarm, which may also be related to fluid movement and contribute to earthquake occurrences. A seismic gap zone in the center of the swarm region may represent an area with aseismic deformation.

A month-long data assimilation experiment is carried out to assess the impact of CrIS and IASI Transformed Retrievals (TRs) on the accuracy of analyses and forecasts from a 3-h Weather Research and Forecasting (WRF) cycling system implemented over the central North Pacific Ocean. Conventional observations and satellite MicroWave (MW) radiance data are assimilated along with TRs in comparative experiments. Both the NCEP Global Forecasting System (GFS) and the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses are used in the evaluation process. The results show that the assimilation of TRs, both alone, and in combination with MW radiance assimilation, have the greatest impact on the characterization of the moisture field in the middle atmospheric levels (800 to 300 hPa), and particularly in the lower portion (800 to 600 hPa). The latter improvement is likely due to a refinement in the vertical definition of the trade-wind inversion.