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This study introduces the ROTated Atmospheric river coordinaTE (ROTATE) system — a novel storm‐centric coordinate system designed specifically for analyzing atmospheric rivers (ARs). It effectively preserves key AR signals in the time mean that may be lost or obscured in simple averaging due to diverse AR orientations and shapes. By applying the ROTATE system, we compared climatological characteristics for northern hemisphere ARs. Composites of four key meteorological variables, integrated vapor transport, integrated water vapor, precipitation, and windspeed, indicate distinct and clearer patterns of ARs compared to the conventional non‐rotated AR centroid‐based compositing approach. Moreover, the ROTATE system improves precipitation rates, particularly around the AR center and its head and tail regions, providing more distinct delineations of the precipitation signals between landfalling and oceanic ARs. Overall, the ROTATE system has the potential to serve as a valuable tool for better comparing and understanding the characteristics, processes, and impacts of ARs across different regions. Plain Language Summary: This study introduces a new method called ROTATE, designed to study long, narrow filamentary regions of intense water vapor transport in the lower atmosphere or so‐called atmospheric rivers (ARs). ROTATE helps us retain essential details in weather systems when averaging over time that otherwise might get lost using the usual averaging method. We used ROTATE to look at crucial characteristics of ARs such as how wet the air is, how fast the wind blows, how much water vapor is being transported, and how much rain falls. We found more apparent AR patterns with ROTATE compared to the traditional way of averaging ARs. The new method also helps us see finer details in rain distributions over land versus over the oceans. The results indicate ROTATE is a valuable tool to help us better compare and understand mean characteristics of ARs in different places. Key Points: Introduces a new coordinate system for analyzing atmospheric rivers (ARs)Provides clearer AR composite patterns and their multi‐variate relationships when compared to the conventional non‐rotated AR centroidEnhances the distinction of precipitation signals between landfall and oceanic ARs, especially around the AR center and its head/tail [ABSTRACT FROM AUTHOR]

Cloud seeding is considered a practical but unproved method to enhance precipitation or suppress hail, due to insufficient knowledge of ice formation and evolution after seeding clouds with ice nucleating particles. This study investigates the size effects on the immersion freezing of aerosol produced from commercial silver iodide (AgI) containing flares at mixed‐phase cloud temperatures from 243 to 267 K. Flare‐generated aerosol exhibited comparable ice nucleation ability (INA) to pure AgI particles in the size range of 200 and 400 nm. Non‐AgI impurities reduced the INA of flare‐generated particles ≤90 nm, which is lower than pure AgI particles ≤40 nm. The critical mass ice‐active site density of the generated aerosols (critical‐nm) was derived, indicating the minimum mass of AgI particles required for efficient ice nucleation. The new parameterization to predict critical‐nm can serve as a reference to optimize the effectiveness of cloud‐seeding materials for practical use. Plain Language Summary: Ice‐forming aerosol is commonly added to clouds, expecting precipitation enhancement via promotion of ice production. In this work, silver iodide (AgI) containing aerosol was generated from commercial cloud‐seeding products under different wind speed conditions. Its ice‐forming ability was studied at mixed‐phase cloud temperatures. The lower size limit for effective ice‐forming ability of the cloud‐seeding particles (90 nm) is higher than that of pure AgI particles (40 nm). The non‐AgI components produced by cloud‐seeding products are hypothesized to decrease the ice‐forming ability of smaller particles, as the mass fraction of ice‐nucleating AgI decreases. To estimate the minimum mass of AgI in a particle required for efficient ice nucleation under cloud‐seeding relevant conditions, we derived the critical ice‐activated mass fraction of the generated aerosols. These findings provide valuable insights into the optimization of cloud‐seeding practices for enhanced precipitation. Key Points: Silver iodide (AgI) containing cloud‐seeding aerosols exhibit comparable ice‐forming abilities to pure AgI at sizes of 200 and 400 nmNon‐AgI impurities produced from flare burning decrease the ice nucleation ability of particles smaller than 90 nmA new parameterization is presented to estimate the minimum mass of AgI particles required to maximize glaciogenic seeding [ABSTRACT FROM AUTHOR]

This study addresses a critical gap in understanding anthropogenic influences on tropical climate dynamics by investigating the impact of aerosol‐cloud interactions on large‐scale circulation. Despite extensive research on greenhouse gas‐induced warming and its effects on tropical circulation, the impact of aerosols, particularly their interactions with clouds, on large‐scale circulation remains understudied. Utilizing large‐domain radiative convective equilibrium cloud‐resolving simulations, this research demonstrates that increasing aerosol concentration intensifies tropical overturning circulation, evaluated at the mid‐troposphere (I) $(\mathcal{I})$, strongly correlating with domain mean cloud and radiative properties. Employing a weak temperature gradient approximation, I attribute variations in I $\mathcal{I}$ to changes in clear‐sky radiative cooling rather than stability. These radiative cooling changes are linked to humidity changes driven by warm rain suppression by aerosols. This study's findings underscore the need to take into account microphysical changes, particularly aerosol concentrations, when studying anthropogenic effects on tropical circulation. Plain Language Summary: Clouds intricately couple with the large‐scale overturning circulation in the tropics. Aerosols, small particles suspended in the atmosphere, interact with clouds. Thus, changes in aerosols concentration (Na) have the potential to affect cloud properties and by that the large‐scale circulation, with important implications for tropical climate and climate change. Despite this crucial relationship, the subject has been insufficiently explored. In this paper, I use a simplified, yet realistic, representation of the tropical atmosphere—radiative convective equilibrium large‐domain cloud‐resolving simulations—to investigate the effect of aerosol‐cloud interaction on overturning tropical circulation. By varying Na under diverse sea surface temperatures, I demonstrate that the strength of the overturning circulation intensifies with increasing Na. Utilizing a semi‐analytical expression for subsidence strength in clear‐sky tropical regions, I show that the intensified overturning circulation with increased Na can be attributed to heightened humidity in the mid‐troposphere, leading to intense radiative cooling. This mid‐tropospheric humidification can be explained by warm rain suppression by aerosols, which fosters stronger humidity mixing between clouds and their surroundings. These findings underscore the need to consider aerosol concentration changes when examining anthropogenic impacts on tropical circulation. Key Points: The overturning tropical circulation intensifies with aerosol concentration in a radiative convective equilibrium modelChanges in circulation strength can be explained by changes in diabatic subsidence driven by radiative changesRadiative changes can be explained by increased humidity at the mid‐troposphere due to warm rain suppression [ABSTRACT FROM AUTHOR]

We conducted a statistical analysis of local phase space density (PSD) minima across a wide energy range (∼20 keVs to ∼10 MeV), using observations from the Van Allen Probes and the Geostationary Operational Environmental Satellite. We identified deepening minima in PSD profiles of multi‐MeV (∼5% occurrence) and of "seed" electrons (up to 15% occurrence, corresponding to ∼70–100 s keV) and compared their distribution with a 3D diffusion model using the Versatile Electron Radiation Belts (VERB) code. The comparison of the observed and modeled distributions suggests that the PSD minima of seed electrons are likely associated with hiss waves and the corresponding L‐shell dependent electron lifetimes. However, the observed distribution was not fully reproduced by the model, potentially indicating other fast loss mechanisms of seed electrons. Plain Language Summary: This study presents a comprehensive analysis of the behavior of electrons within the Earth's radiation belts, specifically focusing on changes in the phase space density (PSD) across various energy levels. By analyzing data from the Van Allen Probes and the GOES satellite over 4 years, we observed notable reductions in PSD, particularly at very high‐energy electrons and somewhat lower energy electrons, often referred to as "seed" electrons. These reductions or minima in PSD are important for understanding the dynamics within the radiation belts. The study found that these minima can be explained by interactions with certain types of waves in space, like electromagnetic ion cyclotron or hiss waves. Furthermore, the PSD minima of the seed electrons likely depend on variations in the rate at which hiss waves can scatter electrons at various distances. Key Points: The deepening Phase Space Density (PSD) minima are noticeably observed at μ < 300 MeV/G, with occurrence reaching 15%The simulation can produce deepening PSD minima at μ < 60 MeV/GThe modeled seed electron deepening PSD minima are influenced by L‐dependent electron lifetimes due to interaction with hiss waves [ABSTRACT FROM AUTHOR]

Observations of a regular pulse burst (RPB) at the end of a K‐event are analyzed utilizing a simple geometric model and particle swarm optimization (PSO) to estimate the currents and propagation speeds of successive pulses of the RPB. The results show that the current of successive pulses is strongly overlapped and, for typical speeds of continuously propagating K‐events, are unphysically large (88 kA), exceeding the currents of most strokes to ground. By default, the unphysical nature of the result, coupled with very high frequency interferometer observations of an RPB in Florida, shows that the propagation speed of the pulses is significantly faster than expected, namely ∼0.6–1.8 × 108 m/s. This reduces the inferred current from 88 kA down to 6–18 kA, typical of intracloud events. The fast propagation speed of the stepping is explained by successive pulses retracing much of the path of the preceding pulses due to the successive pulses being strongly overlapped. Plain Language Summary: Regular pulse bursts (RBP) are a spectacular phenomenon in lightning studies, in which rapidly propagating, conductive channels called K‐events transition from a smoothly and continually lengthening channel to an intermittent but regularly‐spaced stepping process, with each step producing a highly‐impulsive current and electric field change, or "sferic." Here we introduce a new approach for analyzing sferic observations that models the K‐event as a series of successive segments, with the parameters of the current and extent of each pulse being determined by searching the multi‐dimensional parameter space that best fits the corresponding pulse waveforms. This was done using a process called PSO, and indicated that the RBP pulses were caused by a succession of overlapping fast breakdown events, but having unphysically strong currents. For the distant measurements of the study, the sferic amplitudes can determine only the product of current and propagation speed of the pulses, causing their current and speed values to be ambiguous. However, for the currents to have reasonable values, we are able to conclude that the speeds needed to be faster than assumed maximum value of 1.5 × 107 m/s value in the analysis. This contention is supported by observations of similar RPBs being studied by the authors. Key Points: A new, innovative method is developed for estimating the currents and extents of fast electric field change pulsesThe method is applied to the study of a regular pulse burst, showing that it consisted of a succession of fast overlapping eventsThe speed of the pulses is inferred to be significantly higher than that of continuously‐developing K‐leader [ABSTRACT FROM AUTHOR]

Extracting balanced geostrophic motions (BM) from sea surface height (SSH) observations obtained by wide‐swath altimetry holds great significance in enhancing our understanding of oceanic dynamic processes at submesoscale wavelength. However, SSH observations derived from wide‐swath altimetry are characterized by high spatial resolution while relatively low temporal resolution, thereby posing challenges to extract the BM from a single SSH snapshot. To address this issue, this paper proposes a deep learning model called the BM‐UBM Network, which takes an instantaneous SSH snapshot as input and outputs the projection corresponding to the BM. Training experiments are conducted both in the Gulf Stream and South China Sea, and three metrics are considered to diagnose model's outputs. The favorable results highlight the potential capability of the BM‐UBM Network to process SSH measurements obtained by wide‐swath altimetry. Plain Language Summary: Oceanic dynamic processes can be classified into two categories: balanced geostrophic motions (BM), including large‐scale circulation, mesoscale and submesoscale eddy turbulence, and unbalanced wave motions (UBM), including barotropic tides, and inertia–gravity waves (IGWs). Both types of motions coexist and have respective contributions to the sea surface height (SSH). How to extract the BM from the total SSH observations obtained by satellite altimetry is the crucial problem to be solved in this paper. To tackle this issue, we propose a deep learning model named the BM‐UBM Network to establish the relationship between the total SSH and the BM component. The BM‐UBM Network can generate SSH estimations for the BM when provided with a well‐resolved SSH snapshot. Key Points: A Deep learning model is developed to extract balanced motions from sea surface height snapshot based on a realistic simulationDiagnostics of three metrics reveal the effectiveness of the model in extracting balanced motionsThe model exhibits remarkable advantages over the Gaussian filter (baseline) in capturing the gradient and Laplacian information [ABSTRACT FROM AUTHOR]

Recent observations suggest that El Niño–Southern Oscillation (ENSO) impacts basal melting of West Antarctic ice shelves, yet sparse ocean observations limit our understanding of the associated processes. Here we investigate how ENSO events modulate subsurface West Antarctic shelf temperatures using high‐resolution global ocean‐sea ice model simulations. During El Niño, the subsurface shelf warming between 150 m and the shelf bottom can be up to 0.5°C in front of ice shelves. This warming arises from a weaker Amundsen Sea Low (ASL) and weaker coastal easterlies that reduce on‐shelf Ekman transport of cold surface waters, enabling enhanced transport of warm Circumpolar Deep Water (CDW) onto the shelf. A largely opposite response occurs during La Niña, with a stronger ASL and stronger Ekman transport that results in less cross‐shelf CDW transport and cooling in the subsurface. These findings have implications for interpreting basal melting on interannual to decadal time‐scales in West Antarctica. Plain Language Summary: El Niño‐Southern Oscillation (ENSO) is the Earth's dominant year‐to‐year climate variation. The impacts of its two phases, El Niño and La Niña, extend from the tropics to Antarctica through atmospheric waves. Past studies have suggested that West Antarctic ice shelves melt more during El Niño because of warmer ocean waters at the ice shelf bases. However, oceanic changes during El Niño lead to warming on the shelf near the ice which is difficult to isolate. That is because ENSO is only one of many drivers that impact shelf water temperatures. In this work, we simulate isolated ENSO events using an ocean circulation model. We show that during El Niño, the on‐shelf flow of cold surface waters in West Antarctica, driven by coastal easterly winds, is reduced because the winds weaken. To balance out this mass deficit at the surface, more warm CDW flows onto the continental shelf below. During La Niña, we see a largely opposite response. Stronger coastal easterlies increase the on‐shelf flow of cold surface waters and less CDW is flowing onto the shelf. Our results show the link between ENSO and mass loss of the West Antarctic ice shelves and ice sheet. Key Points: Ocean‐sea ice model simulations of El Niño and La Niña events illustrate how they modulate West Antarctic shelf temperaturesEl Niño weakens coastal easterlies, reduces on‐shelf Ekman flow of cold waters, increasing cross‐shelf flow of warm Circumpolar Deep Water (CDW)The La Niña shelf circulation response is largely opposite and reduces cross‐shelf transport of warm CDW [ABSTRACT FROM AUTHOR]

The 2023 Antarctic sea ice extent (SIE) maximum on 7 September was the lowest annual maximum in the satellite era (16.98 × 106 km2), with the largest contributions to the anomaly coming from the Ross (37.7%, −0.57 × 106 km2) and Weddell (32.9%, −0.49 × 106 km2) Seas. The SIE was low due to anomalously warm (>0.3°C) upper‐ocean temperatures combined with anomalously strong northerly winds impeding the ice advance during the fall and winter. Northerly winds of >12 ms−1 in the Weddell Sea occurred because of negative pressure anomalies over the Antarctic Peninsula, while those in the Ross Sea were associated with extreme blocking episodes off the Ross Ice Shelf. The Ross Sea experienced an unprecedented SIE decrease of −1.08 × 103 km2 d−1 from 1 June till the annual maximum. The passage of quasi‐stationary and explosive polar cyclones contributed to periods of southward ice‐edge shift in both sectors. Plain Language Summary: Sea ice provides a vital habitat for life in the Southern Ocean, and plays an important role in the ocean circulation, the dynamics of the Earth's climate, the biogeochemical cycle, and the regional ecosystem. Climatologically, Antarctic sea ice expands northwards from the continent each autumn and winter. However, in 2023 an unprecedented slow ice expansion occurred in the Southern Ocean ahead of the annual maximum on 7 September of 16.98 × 106 km2, which was 1.46 × 106 km2 below the long‐term average. In fact, the area covered by ice remained at a record low level every day from 21 April 2023 until 11 November 2023. Our findings suggest that an impact of upper‐ocean warming and changes in winds, combined with heat and moisture fluxes, extreme winds and high ocean waves associated with polar cyclones (storms), contributed to these record low ice conditions. In particular, cyclones caused episodes of exceptional slow ice expansion or even retreat, leading to negative ice anomalies. For instance, the ice‐edge in the Weddell Sea was moved southwards quickly in a few days (up to 256 km southward) with an ice area loss of ∼2.3 × 105 km2, equivalent to the size of United Kingdom. Key Points: The 2023 Antarctic sea ice extent maximum on 7 September (16.98 × 106 km2) was the lowest annual maximum in the satellite eraAnomalous upper‐ocean warming and strong northerly winds contributed to impeding the ice expansion in the Ross and Weddell SeasQuasi‐stationary and explosive polar cyclones contributed to periods of southward ice‐edge shift in both sectors [ABSTRACT FROM AUTHOR]

In the California Current System (CCS), changes in the phenology (i.e., seasonal timing) of coastal upwelling alter the functioning of this productive marine ecosystem. Recently developed coastal upwelling indices that account for upwelling strength and nutrient flux to the surface provide a more complete understanding of bottom‐up forcing in the region. Using these indices, we describe CCS upwelling phenological variability in vertical transport and nutrient flux. Physical and biogeochemical spring transitions generally co‐occur in winter or spring, followed by increased upwelling and nutrient flux. In the latter half of the year, upwelling continues but nutrient flux wanes as declining source nutrient concentrations limit the biological efficacy of coastal upwelling. Earlier spring transitions and higher season‐integrated upwelling intensity occur during strong La Niña events at all latitudes, driven largely by stronger alongshore wind stress. Understanding phenological changes in coastal upwelling is critical, as they could have significant ecosystem consequences. Plain Language Summary: In the California Current System (CCS), coastal upwelling carries nutrient‐rich waters to the surface, supporting primary production and driving the coastal ecosystem. This upwelling varies on a seasonal and interannual basis, as reflected in recently developed indices that account for the amount of water upwelled to the surface as well as the amount of nutrients carried in that water. Generally upwelling and nutrient transport are high in the first half of the year. Upwelling persists into the second half of the year, but nutrient transport decreases as the deep‐water sources of these nutrients are depleted. Upwelling in the CCS is also affected by the El Niño Southern Oscillation. During La Niña conditions, strong trade winds enhance upwelling and nutrient transport on the California coast. This paper presents regional, seasonal and interannual patterns of upwelling and nutrient delivery in the CCS, which are important drivers of change to this coastal ecosystem. Key Points: We define new upwelling phenology indices for the California Current System that include nutrient transportWe identify spatial, seasonal, and interannual patterns of upwelling and nutrient deliveryWe relate the physical mechanisms of coastal upwelling with its biological efficacy [ABSTRACT FROM AUTHOR]

The viscoelastic lower crust beneath Kyushu Island, influenced by the volcanic arc, interplays with active crustal faults in this region and helps to shape local tectonics. In this study, we employed a three‐dimensional viscoelastic finite element model to gain insights into the lithospheric rheology and crustal faulting kinematics, through modeling the postseismic deformation processes of the 2016 Mw 7.1 Kumamoto earthquake. Our model reveals a viscosity of 2 × 1020 Pa s for the lower crust and 2 × 1019 Pa s for the upper mantle. A reduced lower crust viscosity of 2 × 1019 Pa s in the volcanic arc area is required for better reproducing the Global Positioning System data. The stress‐driven afterslip decays rapidly over time and is up to 0.3 m within 5 years after the earthquake. We propose additional normal‐component afterslip to better explain the complex postseismic deformation in the near field, which may be due to the interaction between the fault and volcano Aso. Plain Language Summary: We have derived the first 5‐year postseismic deformation at more than 200 Global Positioning System (GPS) stations following the 2016 Kumamoto earthquake to constrain the rheological properties beneath the Kyushu Island, as well as the evolution of afterslip. Test models have determined the viscosity of the lower crust and upper mantle to be ∼2 × 1020 and ∼2 × 1019 Pa s, respectively, while the viscosity of the lower crust beneath the volcanic arc is ∼2 × 1019 Pa s, notably lower than that of the other area. The lower crust viscosity in the Beppu‐Shimabara Graben, except the volcano dominant area, is estimated to be no smaller than 1020 Pa s. The complex near‐field postseismic deformation cannot be fully explained by one single deformation process. The viscoelastic relaxation and afterslip must both be at play to control the postseismic deformation. In addition to the rheological heterogeneity, the afterslip may also be heterogeneous. We propose additional afterslip possibly induced by the Aso volcano to better fit the near‐field GPS observations. Our models provide insights into the lithospheric structure of Kyushu Island and the intricate behavior of fault slips. Key Points: We present a 3‐D finite element model to explore the postseismic viscoelastic relaxation and afterslip of the 2016 Kumamoto earthquakeThe steady‐state lower crust viscosity in Kyushu is ∼2 × 1020 Pa s, one order of magnitude higher than that beneath the volcanic arc regionThe complex near‐field postseismic deformation can be explained by the normal‐component afterslip induced by the Aso volcano [ABSTRACT FROM AUTHOR]

The diurnal variation and distribution of lunar surficial hydration (OH/H2O) is of great significance for understanding the solar wind implantation and water cycle on the Moon. Lunar south pole is an ideal place to study the diurnal variation of surficial hydration due to the large number of repeat observations of the same region, which is very limited in mid‐ or low‐latitudes. Here we showed clear 0.5‐hr interval diurnal variation of surficial hydration at lunar south pole. The variation of hydration band depth with local time is exactly the opposite to the variation of temperature, indicating that lunar surficial hydration changes sufficiently with temperature. This relationship indicates that both the diurnal variation and hydration content are latitude dependent. Our observations support the hypothesis that the diurnal variation of hydration on the Moon is due to the formation of metastable hydroxyl. Plain Language Summary: Hydration (OH/H2O) has been found on the surface of the Moon due to the implantation of solar wind. Hydration contents in the morning and evening were observed to be higher than that at local noon. Lunar south pole is a very good place to study the diurnal variation of surficial hydration compared with other places of the Moon as there are a lot of repeat observations of the same area at different local times. We conducted a detailed investigation of surficial hydration at the lunar south pole based on repeat Moon Mineralogy Mapper near‐infrared data. We found surficial hydration at lunar south pole gradually decreases toward local noon, and then recovers to the morning level at evening. The variation trend is exactly the opposite to the temperature, indicating lunar surficial hydration changes sufficiently with instantaneous temperature. These observations provide clues for studies on the formation and evolution of volatiles on the Moon and other airless bodies. Key Points: 0.5‐hr interval diurnal variation of lunar surficial hydration was revealed at lunar south pole for the first timeLunar surficial hydration changes sufficiently with instantaneous temperatureLunar surficial hydration did not change when the Moon enters the Earth's magnetotail [ABSTRACT FROM AUTHOR]

Within oxygen minimum zones, anaerobic processes transform bioavailable nitrogen (N) into the gases dinitrogen (N2) and nitrous oxide (N2O), a potent greenhouse gas. Mesoscale eddies in these regions create heterogeneity in dissolved N tracers and O2 concentrations, influencing nonlinear N cycle reactions that depend on them. Here, we use an eddy‐resolving model of the Eastern Tropical South Pacific to show that eddies enhance N2 production by between 43% and 64% at the expense of reducing N2O production by between 94% and 104% due to both the steep increase of progressive denitrification steps at vanishing oxygen, and the more effective inhibition of N2O consumption relative to production. Our findings reveal the critical role of eddies in shaping the N cycle of oxygen minimum zones, which is not currently represented by coarse models used for climate studies. Plain Language Summary: Nitrogen limits photosynthesis over large swaths of the ocean. Oxygen minimum zones are important oceanic environments where the presence of low O2 concentrations allow anaerobic microbial communities to transform bioavailable forms of nitrogen into the gases dinitrogen (N2) and nitrous oxide (N2O, a powerful greenhouse gas), which together lead to nitrogen loss from the oceans. The large scale ocean circulation acts to maintain these oxygen minimum zones, and the gradients in nitrogen and oxygen concentrations surrounding them. Turbulence also generates eddies and filaments which stir these gradients, promoting chemical heterogeneity. However, it is uncertain how eddies impact the nitrogen transformation rates dependent on nitrogen and oxygen tracer concentrations. Using a high resolution ocean model of the Eastern Tropical South Pacific oxygen minimum zone, we explore the contributions from eddies to total N2 and N2O production. We highlight that roughly half of total N2 production is caused by the presence of eddies, while N2O production is drastically reduced or even consumed. These findings expand our understanding of the ways in which eddies alter nitrogen loss from the oceans, and challenge the ability of non‐eddy resolving models to accurately represent N2 and N2O production in a changing ocean. Key Points: A high resolution model is used to estimate the effect of mesoscale eddies on the N cycle in a major oxygen minimum zoneEddies simultaneously enhance fixed N loss and suppress nitrous oxide productionThese eddy effects result from the progressive inhibition of the denitrification steps by oxygen concentrations [ABSTRACT FROM AUTHOR]

Comprehending the temperature distribution within Earth's lithospheric mantle is of paramount importance for understanding the dynamics of Earth's interior. Traditional mineral‐based thermobarometers effectively constrain temperature and pressure for particular compositions, but their application is limited at the global scale. Here, we trained machine‐learning (ML) algorithms on 985 published high‐temperature and high‐pressure experiments for use as thermometers and barometers to overcome the limitations of classic methods. We compared our ML models to classic thermobarometers to assess the accuracies of predicted pressures and temperatures. The comparison shows that the ML models outperform classic methods and better fit various mineral pairs. Global application of the ML models unveils mantle conditions beneath cratons. Furthermore, depths to the lithosphere‐asthenosphere boundary (LAB) calibrated based on the ML thermobarometry results are generally deeper by ∼40 km than those derived geophysically, implying the existence of melt‐bearing or hydrated mineral zones at the LAB. Plain Language Summary: The temperature of the lithospheric mantle is pivotal to processes such as the production of magmas and the structural stability of cratons. Researchers have traditionally employed mineral‐based thermobarometers to lithospheric mantle temperatures, but those conventional techniques have limited applications and are susceptible to inaccuracies. Here, we explored a new approach using machine learning, a powerful tool for identifying complex patterns in high‐dimensional data space. We trained machine‐learning models using data from high‐pressure and high‐temperature experiments, then compared our machine‐learning models to traditional methods. Our results show that the machine‐learning models better predict pressure and temperature for specific mineral combinations. We also used our optimized model to predict mantle temperatures and pressures based on a global data set of xenolith analyses, revealing insights about the temperature of the lithospheric mantle and the depth to the lithosphere‐asthenosphere boundary beneath continents. This research shows that machine learning can greatly improve our understanding of Earth's deep processes, providing more accurate insights into its dynamics and evolution. Key Points: Thermometers and barometers calibrated and validated for xenolithic mantle minerals by machine learningGlobal lithospheric mantle temperatures predicted based on xenolithic mineral compositions calculated by machine‐learning thermobarometryThermal continental lithosphere‐asthenosphere boundarys refined by machine‐learning thermobarometry are consistently ∼40 km deeper than those determined geophysically [ABSTRACT FROM AUTHOR]

Chemical weathering associated with dissolution/precipitation at interfaces between minerals and flowing fluids is key for the evolution of geologic systems, including groundwater contamination and storage capacity. Relying on Atomic Force Microscopy (AFM) yields reaction rates at nanoscale resolutions. Challenges limiting our ability to quantify heterogeneity associated with these processes include establishing reliable platforms allowing AFM imaging of real‐time and in situ absolute material fluxes across mineral surfaces under continuous flow conditions to complement typically acquired surface topography images. We provide an experimental workflow and heterogeneous absolute rates at the nanoscale across the surface of a calcite crystal under dissolution. These high‐quality experimental observations are then interpreted through a stochastic approach. The latter is geared to embed diverse kinetic modes driving the degree of spatial heterogeneity of the reaction and corresponding to different mechanistic processes documented across the crystal surface. Plain Language Summary: Quantification of basic processes underpinning precipitation/dissolution at mineral/fluid interfaces is key for realistic assessment of chemical weathering rates driving rock morphology, subsurface storage capacity and contamination. We provide direct observation of the complex mechanistic processes acting at nanoscales through an original experimental platform relying on Atomic Force Microscopy imaging to evaluate absolute material fluxes associated with dissolution of a mineral subject to reaction under continuous flow conditions. Dissolution is characterized at very high spatial resolutions (∼10 nm). This enables observing in real‐time and in situ mechanistic processes driving system evolution. The ensuing rich data set of absolute reaction rates displays a marked degree of spatial heterogeneity. The latter is then interpreted within a stochastic framework to yield a detailed mechanistic appraisal of mineral dissolution. Key Points: A platform to evaluate absolute nanoscale topographic measurements of a crystal sample subject to dissolution/precipitation is designedThe associated spatially heterogeneous fields of absolute material fluxes across the surface are evaluatedReaction rates are described through a stochastic framework encapsulating behaviors of surface features driving dissolution processes [ABSTRACT FROM AUTHOR]

How and when sedimentary rocks record Earth's magnetic field is complex. Most studies assume a time‐progressive lock‐in mechanism during sediment deposition called depositional remanent magnetization (DRM). However, magnetic minerals can also form in situ, recording a chemical remanent magnetization (CRM) that is discontinuous in time. Disentangling the two mechanisms represents a major hurdle, and differences in their recording efficiencies remain unexplored. Here, our theoretical solutions demonstrate that CRM intensities exceed DRM by a factor of six when acquired in the same magnetic field. Novel experiments growing greigite (Fe3S4) in sediments and subsequent redeposition under identical magnetic field conditions confirm the predicted difference in recording efficiency. Thus, if left unrecognized, CRM leads to overestimated paleointensity and deserves more attention when interpreting Earth's magnetic history from sedimentary records. Recognition of fundamental differences between CRM and DRM characteristics provide a way forward to distinguish the recording mechanisms through routine laboratory protocols. Plain Language Summary: Remanent magnetizations preserved in sedimentary rocks serve as a continuous record of Earth's magnetic field history and play a fundamental role in understanding the Earth system. It is commonly assumed that magnetic minerals align with the magnetic field as a particle settles through the water column, known as a depositional remanent magnetization (DRM). However, diagenesis can lead to chemical growth of magnetic minerals, known as a chemical remanent magnetization (CRM). CRM lacks stratigraphic continuity and can obscure or completely overprint the original magnetization any time after sediment deposition, leading to a magnetic record that is uncorrelated with the age of the rock. Yet, CRMs go largely unrecognized. Theory and experiments in our paper document that CRMs record the magnetic field six times more efficiently than DRMs. Our work provides a way to distinguish the two through routine laboratory protocols. Key Points: Recording efficiency of chemical remanent magnetization (CRM) is six times higher than depositional remanent magnetization (DRM)Undetected chemical remanences lead to overestimated relative paleointensity estimatesComparison of natural and laboratory magnetization and demagnetization behavior help identify chemical remanent magnetizations in sediments [ABSTRACT FROM AUTHOR]

The porous structure of snow becomes denser with time under gravity, primarily due to the creep of its ice matrix with viscoplasticity. Despite investigation of this behavior at the macroscopic scale, the driving microscopic mechanisms are still not well understood. Thanks to high‐performance computing and dedicated solvers, we modeled snow elasto‐viscoplasticity with 3D images of its microstructure and different mechanical models of ice. The comparison of our numerical experiments to oedometric compression tests measured by tomography showed that ice in snow rather behaves as a heterogeneous set of ice crystals than as homogeneous polycrystalline ice. Similarly to dense ice, the basal slip system contributed at most, in the simulations, to the total snow deformation. However, in the model, the deformation accommodation between crystals was permitted by the pore space and did not require any prismatic and pyramidal slips, whereas the latter are pre‐requisite for the simulation of dense ice. Plain Language Summary: Knowledge of snow settlement is essential for many applications, such as paleoclimatology and avalanche forecasting. Snow densification is mainly driven by time dependent and irreversible deformations. Simulating this highly nonlinear behavior for intricate microstructures is time‐consuming, leading to a scarcity of studies and a limited understanding of the underlying microscale mechanisms. In this study, we took advantage of an advanced numerical solver to calculate the behavior of 3D imaged snow samples and compared it with in situ experiments. Our analysis has shown that the crystalline structure must be taken into account, but the discrepancy between experiments and simulations suggests the existence of other mechanisms, particularly between snow grains. Interestingly, deformation mechanisms other than those required to simulate dense ice have been observed. Key Points: Ice in snow cannot be considered as homogeneous, individual crystals are shown to impact snow creepThe models shows that basal glide of a few ice zones supports most of the snow deformationIn the simulations, the contribution of the hard slip systems is negligible, and deformation accommodation is enabled by the pore space [ABSTRACT FROM AUTHOR]

The October effect is known as a rapid and strong decrease in the signal amplitude of radio waves with very low frequency (VLF), reflected at the lowest edge of the ionosphere. This strong decrease can be observed only during the daytime. Although the October effect is long known, it is hardly investigated and its mechanism is still unknown. To get closer to a mechanism, we answer why the October effect does not occur during nighttime. Therefore, average characteristics of the October effect are obtained from different VLF transmitter‐receiver combinations. The occurrence of the October effect is then compared with characteristics of the neutral atmosphere temperature at VLF reflection heights as it seems to act as a proxy for the unknown mechanism. The temperature shows an asymmetric seasonal behavior at daytime VLF reflection heights poleward of 50°N but not during the nighttime, resulting in the October effect. Plain Language Summary: The October effect is known as a rapid and strong decrease in the signal amplitude of radio waves with very low frequency, reflected at the lowest edge of the ionosphere (60–90 km). This strong decrease can be observed only during the daytime. Although the October effect has been long known, it is hardly investigated and its mechanism is still unknown. To get one step closer to a mechanism, we want to answer the question of why the October effect does not occur during nighttime. There are two main reasons why the October effect does not occur during nighttime. First, the radio wave reflection height is at around 70 km during daytime and at 85 km during nighttime. The second is the different behavior of the temperature at these two altitudes. While the temperature follows the seasonal cycle of the sun at 85 km, it shows an asymmetric behavior between spring and autumn at 70 km. This unexpected behavior of the temperature at 70 km leads to the October effect during the daytime only. Key Points: Strong and rapid decrease in VLF amplitude in OctoberSpring‐fall asymmetry in VLF amplitude and lower mesospheric temperatureAsymmetry only at daytime VLF reflection height [ABSTRACT FROM AUTHOR]

Ice shelves are assumed to flow steadily from their grounding lines to the ice front. We report the detection of ice‐propagating extensional Lamb (plate) waves accompanied by pulses of permanent ice shelf displacement observed by co‐located Global Navigation Satellite System receivers and seismographs on the Ross Ice Shelf. The extensional waves and associated ice shelf displacement are produced by tidally triggered basal slip events of the Whillans Ice Stream, which flows into the ice shelf. The propagation velocity of 2,800 m/s is intermediate between shear and compressional ice velocities, with velocity and particle motions consistent with predictions for extensional Lamb waves. During the passage of the Lamb waves the entire ice shelf is displaced about 60 mm with a velocity more than an order of magnitude above its long‐term flow rate. Observed displacements indicate a peak dynamic strain of 10−7, comparable to that of earthquake surface waves that trigger ice quakes. Plain Language Summary: Ice shelves normally flow steadily toward their boundaries with the open ocean at the ice front. However, seismographs and Global Navigation Satellite System receivers deployed on the Ross Ice Shelf record guided elastic plate waves traveling in the ice as well as permanent displacement of the ice shelf. The elastic waves and ice shelf displacement originate from basal slip events of the Whillans Ice Stream, which flows into the Ross Ice Shelf. The velocity of the elastic waves is about 2,800 m/s, as expected for guided plate waves propagating in an ice shelf. During the passage of the elastic waves, the entire ice shelf with an area of 500,000 square kilometers is displaced about 60 mm in a direction away from the Whillans Ice Stream. These observations show that the strain imparted to the ice shelf by the once or twice daily Whillans Ice Stream basal slip events is sufficient to trigger ice quakes and perhaps enhance the deformation of the ice shelf. Key Points: Extensional Lamb waves propagate across the Ross Ice Shelf, radiated from slip events at the base of the Whillans Ice StreamDuring the passage of the Lamb waves, the entire ice shelf is displaced about 60 mm, with a velocity an order of magnitude above its long‐term flow rateThe displacement pulses produce a peak dynamic strain of 10−7, suggesting that they could trigger icequakes in the ice shelf [ABSTRACT FROM AUTHOR]

As the world's glaciers recede in response to a warming atmosphere, a change in the magnitude and frequency of related hazards is expected. Among the most destructive hazards are glacier lake outburst floods (GLOFs), and their future evolution is concerning for local populations and sustainable development policy. Central to this is a better understanding of triggers. There is a long‐standing assumption that earthquakes are a major GLOF trigger, and seismic activity is consistently included as a key hazard assessment criterion. Here, we provide the first empirical evidence that this assumption is largely incorrect. Focusing on the Tropical Andes, we show that, of 59 earthquakes (1900–2021) the effects of which intersect with known glacier lakes, only one has triggered GLOFs. We argue that, to help develop climate resilient protocols, the focus for future assessments should be on understanding other key GLOF drivers, such as thawing permafrost and underlying structural geology. Plain Language Summary: Climate change is increasing glacier melt in high mountains and increasing the size and number of glacial lakes. Over time, these lakes may drain catastrophically to generate glacier lake outburst floods (GLOFs), which can devastate downstream communities and destroy valuable infrastructure such as roads, bridges, and hydroelectric power facilities. As a result, many risk assessments have been carried out to understand what the triggers of GLOFs might be, in order to better predict their occurrence. One of the main triggers has been assumed to be earthquakes, but this association has not been properly tested. In this paper, we use earthquake and GLOF data from the Peruvian and Bolivian Andes to test this and find that there is little association between earthquakes and GLOFs. We conclude by arguing that focus needs to be on other GLOF triggers, and earthquake activity should be used as a secondary – not primary – indicator in GLOF susceptibility studies. Key Points: Glacier lake outburst floods (GLOFs) are a major risk concern, with earthquakes being commonly considered effective triggers in hazard assessmentsOf 59 earthquakes (1900–2021), the effects of which intersect lakes in the Tropical Andes, only one triggered GLOFsWe suggest that earthquake activity should be used as a secondary – not primary – susceptibility indicator for GLOFs [ABSTRACT FROM AUTHOR]

The Arctic is notable as a region where the greatest rate of increase in precipitation associated with global warming is anticipated. The Arctic precipitation simulated by the Coupled Model Intercomparison Project Phase 6 models showed a strong increasing trend since the 1980s. We found that the forcing factor of the trend is a combination of the continued strengthening of greenhouse gas forcing and the leveling off of aerosol forcing dominated in earlier periods. From an energetic perspective, we found that the increased atmospheric radiative cooling and reduced sensible heat transport from lower latitudes contributed equally to the recent increase in Arctic precipitation. The combination of these two energetic factors suggests a doubling of the Arctic amplification factor for precipitation relative to that for temperature. Future Arctic precipitation will change in proportion to the temperature change, and the fractional contributions of the energetic factors will remain stable across various scenarios. Plain Language Summary: The Arctic region is inherently a low‐precipitation area. However, because of global warming, precipitation is expected to increase substantially in the Arctic region compared with the global average when viewed as a percentage change from the original precipitation. This severely affects climate change in the Arctic environment. The latest climate model simulations show that there has been a rapid increase in precipitation in the Arctic region in recent decades. The driving factors behind the rapid increase are the effects of the accelerating growth of greenhouse gas concentrations, which were previously suppressed by the increasing anthropogenic aerosol emissions before the 1980s. Based on the heat budget of the atmosphere, we identified important factors contributing to these precipitation changes. These include enhanced radiative cooling (responding locally to increased air temperature) and reduced heat transport from lower latitudes due to greater temperature increases at higher latitudes. Future precipitation will change in proportion to the temperature change while maintaining consistent fractional contributions across different scenarios. Key Points: Trends in Arctic precipitation in the recent and future decades are examined from multimodel simulationsThe recent rapid increase is driven by accelerating greenhouse gas concentrations and plateauing growth in anthropogenic aerosol emissionsIncreased radiative cooling and reduced poleward sensible heat transport equally contributed to the Arctic precipitation changes [ABSTRACT FROM AUTHOR]

While previous studies have largely focused on anthropogenic warming characterized by surface air temperature, little is known about the behaviors of human‐perceived temperature (HPT), which describe the "feels‐like" equivalent temperature by considering the joint effects of temperature, humidity and/or wind speed. Here we adopted an optimal fingerprinting method to compare seasonal mean HPTs in China with those from simulations conducted with multiple climate models participating in the Coupled Model Intercomparison Project Phase 6. We found clear anthropogenic signals in the observational records of changes in both summer and winter HPTs over the period 1971–2020. Moreover, the anthropogenic greenhouse gas influence was robustly detected, with clear separation from natural and anthropogenic aerosol forcings. The anthropogenic greenhouse gas forcing plays the dominant role (>90%) of human‐perceived warming. Urbanization effects contribute slightly and moderately to the estimated trends in summer and winter HPTs, respectively, in addition to the effects of external forcing. Plain Language Summary: Human influences have been identified in the observed warming quantified by surface air temperature (SAT), but SAT alone is inadequate as a metric for human thermal comfort. Here we focus on human‐perceived temperature (HPT), which describes the "feels‐like" equivalent temperature by considering the joint effects of temperature, humidity, and/or wind speed. We isolate anthropogenic impacts on the observed increase in summer and winter HPTs in China during 1971–2020 by comparing observations with state‐of‐the‐art climate models. Results show that the influence of anthropogenic greenhouse gas is detected, with clear separation from other external forcings such as solar and volcanic activities and anthropogenic aerosols. The human‐induced greenhouse gas increases are also found to explain most (>90%) of the observed human‐perceived warming. Along with the effects of large‐scale anthropogenic forcing, urbanization effects also have a slight to moderate influence on the estimated trends in summer and winter HPTs. Our work is an early attempt to provide quantitative evidence for the physiological impacts of anthropogenic global warming and local urbanization on human beings. Key Points: The warming is quantified by human‐perceived temperature that considers the joint effects of temperature, humidity and/or wind speedHuman influence could be robustly detected in both summer and winter human‐perceived warmingThe observed increase in human‐perceived temperature is mostly attributed to anthropogenic greenhouse gas increases [ABSTRACT FROM AUTHOR]

Following the Hunga Tonga–Hunga Ha'apai (HTHH) eruption in January 2022, stratospheric ozone depletion was observed at Southern Hemisphere mid‐latitudes and over Antarctica during the 2022 austral wintertime and springtime, respectively. The eruption injected sulfur dioxide and unprecedented amounts of water vapor into the stratosphere. This work examines the chemistry contribution of the volcanic materials to ozone depletion using chemistry‐climate model simulations with nudged meteorology. Simulated 2022 ozone and nitrogen oxide (NOx = NO + NO2) anomalies show good agreement with satellite observations. We find that chemistry yields up to 4% ozone destruction at mid‐latitudes near ∼70 hPa in August and up to 20% ozone destruction over Antarctica near ∼80 hPa in October. Most of the ozone depletion is attributed to internal variability and dynamical changes forced by the eruption. Both the modeling and observations show a significant NOx reduction associated with the HTHH aerosol plume, indicating enhanced dinitrogen pentoxide hydrolysis on sulfate aerosol. Plain Language Summary: The January 2022 eruption of the Hunga Tonga‐Hunga Ha'apai underwater volcano injected a large amount of water vapor (H2O) and moderate amounts of sulfur dioxide (SO2) into the stratosphere. Stratospheric ozone depletion was observed following the eruption at Southern Hemisphere (SH) mid‐latitudes and over Antarctica during the 2022 austral wintertime and springtime, respectively. The ozone layer in the stratosphere protects both people and the biosphere by absorbing harmful solar ultraviolet radiation. We use computer simulation to examine the impacts of chemical processes on the ozone layer from the volcanic materials. We find that chemistry results in 4% and 20% of the ozone loss at SH mid‐latitudes near 70 hPa in August and Antarctica around 80 hPa in October respectively. Most of the ozone changes are due to transport and dynamical processes from internal variability in the climate system and a forced response by the HTHH eruption. Key Points: Chemistry yields 4% and 20% ozone depletion in the lower stratosphere at mid‐latitudes and Antarctica in August and October, respectivelyThe majority of ozone depletion is ascribed to internal variability and dynamical changes induced by the eruptionHTHH aerosol plume is associated with notable NOx reduction, indicating enhanced dinitrogen pentoxide hydrolysis on sulfate aerosol [ABSTRACT FROM AUTHOR]

Humid heatwaves, characterized by high temperature and humidity combinations, challenge tropical societies. Extreme wet‐bulb temperatures (TW) over tropical land are coupled to the warmest sea surface temperatures by atmospheric convection and wave dynamics. Here, we harness this coupling for seasonal forecasts of the annual maximum of daily maximum TW (TWmax). We develop a multiple linear regression model that explains 80% of variance in tropical mean TWmax and significant regional TWmax variances. The model considers warming trends and El Niño and Southern Oscillation indices. Looking ahead, the strong‐to‐very‐strong El Niño at the end of 2023, with an Oceanic Niño Index of ∼2.0, suggests a 2024 tropical land mean TWmax of 26.2°C (25.9–26.4°C), and a 68% chance (24%–94%) of breaking existing records. This method also predicts regional TWmax in specific areas. Plain Language Summary: The heat and humidity in the tropics can be particularly challenging for people to stay comfortable and healthy. This combination of heat and moisture is described using a measure called the wet‐bulb temperature (TW). We found that these extremely humid and hot conditions on land can be predicted about 5 months in advance using a physics‐based statistical model. The forecast is possible because the peak of El Niño comes before the peak in the warmest sea surface temperatures, which affects the maximum TW on land. This prediction can help tropical societies to better prepare for extreme heat. Key Points: Tropical wet‐bulb temperatures (TW) peak around 5 months after El Niño wintersA multiple linear regression model considering the El Niño‐Southern Oscillation index and the long‐term warming trend effectively explains TWmax variabilityOur model quantifies the likelihood of strong El Niño and human‐induced warming pushing TWmax to record‐breaking levels [ABSTRACT FROM AUTHOR]

Concurrence of temperature inversion (TI) and humidity inversion (HI) is a particular configuration of the atmospheric boundary layer with important implications for early warning of fog formation. With a microwave radiometer device deployed in a 2‐month winter campaign at a coastal island in Qingdao, China, we here examine the relationship between TI and HI, and investigate the underneath mechanisms. Cases of temperature inversion are further divided into surface‐based temperature inversion (SBTI) and elevated temperature inversion (ETI), which show different relationship with HI. SBTI typically occurs at night with its strength significantly and positively correlated with HI. ETI also shows a high degree of temporal overlap with HI, but its strength has no obvious relationship with HI. The main explanation for this phenomenon is that ETI may block the vertical diffusion of water vapor, resulting in the formation of HI. Plain Language Summary: Temperature inversion (TI) and humidity inversion (HI) often occur simultaneously. Knowledge of their concurrence is, however, still quite limited, due to the lack of continuous observations. Using a 2‐month winter observation data set, obtained with a microwave radiometer device deployed in Qingdao, China, a coastal city of the Yellow Sea, we carefully examined the correlation between TI and HI. TI is furthermore regrouped into surface‐based temperature inversion (SBTI) and elevated temperature inversion (ETI). Although SBTI and ETI both occur frequently, accompanied with HI, the underneath physical mechanism seems different. For SBTI, the bottom of HI absorbs the radiation emitted from the ground, increases the temperature difference between the land and atmosphere, and finally enhances SBTI. However, ETI plays the role of blocking the water vapor turbulent diffusion and contributes to the development of HI. Key Points: Both surface‐based temperature inversion (SBTI) and elevated temperature inversion (ETI) show concurrence with humidity inversion (HI)Theories of water vapor condensation and turbulent diffusion blockage may not be sufficient for the concurrence of SBTI and HIETI blocks the upward turbulent diffusion of water vapor, contributing to the formation of HI [ABSTRACT FROM AUTHOR]

When the solar wind speed falls below the local Alfvén speed, the magnetotail transforms into an Alfvén wing configuration. A Grid Agnostic Magnetohydrodynamics for Extended Research Applications (GAMERA) simulation of Earth's magnetosphere using solar wind parameters from the 24 April 2023 sub‐Alfvénic interval is examined to reveal modifications of Dungey‐type magnetotail reconnection during sustained sub‐Alfvénic solar wind. The simulation shows new magnetospheric flux is generated via reconnection between polar cap field lines from the northern and southern hemisphere, similar to Dungey‐type magnetotail reconnection between lobe field lines mapping to opposite hemispheres. The key feature setting the Alfvén wing reconnection apart from the typical Dungey‐type is that the majority of new magnetospheric flux is added to the polar cap at local times 1–3 (21‐23) in the northern (southern) hemisphere. During most of the sub‐Alfvénic interval, reconnection mapping to midnight in the polar cap generates relatively little new magnetospheric flux. Plain Language Summary: Similar to how a shock wave forms around a supersonic plane, the supersonic plasma emanating from the sun forms a shock wave around Earth. However, the speed of sound through the plasma depends on different parameters that vary substantially based on the origin and evolution of solar material flowing into interplanetary space. In some coronal mass ejections, the characteristics of the plasma are such that the flow is sub‐sonic, leaving the magnetosphere in a unique state. Determining whether there are any space weather impacts associated with the sub‐sonic flow has been difficult due to lack of observations, but a recent event has ignited interest. This study examines the global structure and dynamics of the magnetosphere in a simulation representative of the sub‐sonic flow interval of the April 2023 geomagnetic storm. Key Points: On 24 April 2023, Earth's magnetosphere experienced an interval of sustained sub‐Alfvénic solar wind drivingSub‐Alfvénic driving suppresses typical Dungey‐type magnetotail reconnection but polar cap expansion is still limitedGlobal simulations have strong Earthward flows localized ∼10 RE tailward of theterminator, where most new magnetospheric flux is generated [ABSTRACT FROM AUTHOR]

Air‐entraining whitecaps provide an important source of bubbles over the global oceans, yet the rate at which the associated air is entrained is not well known. This lack of understanding limits the ability to accurately parameterize bubble‐mediated gas exchange and sea spray aerosol flux. In this paper I present a model to predict the total volume of air entrained by individual whitecaps and extend it to estimate the rate at which air is entrained per unit sea surface area. The model agrees well with existing models and measurements and can be forced by the rate at which energy is dissipated by the wavefield which can be routinely provided by spectral wave models. I then use the model to present the first distributions of the estimated total volume of air entrained by individual whitecaps, as well as their rate of air entrainment and air degassing. Plain Language Summary: The amount of air in the oceans in the form of bubbles at any given time is not well known because of the difficulty associated with making in‐situ measurements. This lack of knowledge inhibits how well ocean‐atmosphere exchange processes that are driven by air and bubbles can be represented in climate models. In this paper, I present a new model to estimate the volume of air entrained by individual breaking waves called whitecaps, as well as how quickly the air is entrained into the oceans and how quickly it leaves the oceans when bubbles rise to the surface and burst. Key Points: A model for the entrainment of air by oceanic whitecaps is presented which agrees well with existing models and measurementsDistributions of the estimated volume of air entrained by individual oceanic whitecaps are presented for the first timeKey uncertainties in the air fraction and entrainment velocities of individual whitecaps remain due to a lack of measurements [ABSTRACT FROM AUTHOR]

Existing models for estimating hyporheic solute mass flux often require numerous parameters related to flow, bed, and channel characteristics, which are frequently unavailable. We performed a meta‐analysis on existing data set, enhanced with high Reynolds number cases from a validated Computational Fluid Dynamics model, to identify key parameters influencing effective diffusivity at the sediment water interface. We applied multiple linear regression to generate empirical models for predicting eddy diffusivity. To simplify this, we developed two single‐parameter models using either a roughness or permeability‐based Reynolds number. These models were validated against existing models and literature data. The model using roughness Reynolds number is easy to use and can provide an estimate of the mass transfer coefficient for solutes like dissolved oxygen, particularly in scenarios where detailed bed characteristics such as permeability might not be readily available. Plain Language Summary: Current methods for estimating solute mass transfer across the sediment‐water interface of rivers often require a lot of information about flow and riverbed characteristics. Unfortunately, this information is often not readily available. We evaluated existing data from flume experiments and the field and added new data from a verified computational model, in order to identify which factors are most important in determining how much solute moves toward the bed at the sediment‐water interface. Using statistical tools, we developed two simple models that require minimal information about the stream and streambed. One model considers sediment size, the other looks at riverbed permeability. We validated these models by comparing them to existing methods and data from other studies, and they performed well. The model based on sediment size, which also reflects the roughness of the riverbed, performs best and is the most user‐friendly because it does not require information about permeability, which is harder to estimate. This model can be further applied for dissolved oxygen transfer and provide a reliable estimate of how oxygen moves at the sediment‐water interface, particularly when specific details about the riverbed are not available. Key Points: We used a validated numerical model to expand the available data set of hyporheic mass exchange under various bed and flow conditionsWe performed reanalysis of flume/field data combined with numerical results to develop models for the hyporheic mass exchange rateWe proposed unifying single‐parameter models for the estimation of hyporheic mass transfer coefficient in open‐channel flows [ABSTRACT FROM AUTHOR]

Headwater catchments play a vital role in regional water supply and ecohydrology, and a quantitative understanding of the hydrological partitioning in these catchments is critically needed, particularly under a changing climate. Recent studies have highlighted the importance of subsurface critical zone (CZ) structure in modulating the partitioning of precipitation in mountainous catchments; however, few existing studies have explicitly taken into account the 3D subsurface CZ structure. In this study, we designed realistic synthetic catchment models based on seismic velocity‐estimated 3D subsurface CZ structures. Integrated hydrologic modeling is then used to study the effects of the shape of the weathered bedrock and the associated storage capacity on various hydrologic fluxes and storages in mountainous headwater catchments. Numerical results show that the weathered bedrock affects not only the magnitude but also the peak time of both streamflow and subsurface dynamic storage. Plain Language Summary: In mountainous terrains, precipitation falling as snow and rain not only flows into streams but also infiltrates into the subsurface, replenishing the subsurface water storage. This stored water in the subsurface (including both soil moisture and rock moisture) supports various ecohydrological processes such as groundwater recharge and plant water use. In this study, we use computational simulation to study how the below‐ground heterogeneity affects the partitioning of precipitation into streamflow, subsurface water storage, plant water use, and deep groundwater recharge. Here, below‐ground heterogeneity refers to the depth extent of weathered rock at the hillslope‐ or catchment‐scale. Simulation results show that both the annual magnitude and weekly variations of the streamflow and subsurface storage change noticeably as the below‐ground weathering pattern varies, in particular under a snow‐dominated weather scenario. The outcome of this study will potentially help stakeholders develop more informed water management practices in the face of a warming climate and more extreme weather events. Key Points: Integrated hydrologic modeling of catchments with different subsurface critical zone structures was performedSimulation results show that the shape of the weathered bedrock and associated storage capacity affect various hydrologic processes in the catchmentThe effect of weathered bedrock on hydrological partitioning is more significant under weather conditions featuring large snow fractions [ABSTRACT FROM AUTHOR]

Mars features a crustal dichotomy, with its southern hemisphere covered by a thicker basaltic crust than its northern hemisphere. Additionally, the planet displays geologically recent volcanism only in its low latitude regions. Previous giant impact models coupled with simulations of mantle convection have shown that the crustal dichotomy can be explained by post‐impact melt crystallization that emplaced a thick crust in the southern hemisphere. In this study, we show that the depleted residue left behind by the original post‐impact crustal formation can spread laterally, potentially persisting beneath the northern hemisphere to the present‐day. Such a large‐scale mantle province would concurrently explain both the prevalence of long‐term magmatism on Mars and its strong preference for localized equatorial regions. Plain Language Summary: Mars has a thicker crust in the southern hemisphere than in the north hemisphere, this difference is named the Martian dichotomy. Various theories have been suggested in order to explain its origin. We focus in the present study on a southern giant impact hypothesis. By using numerical models, we study the fate of a magma pond that is created by a giant impact. As this pond cools, a crust is formed on the top, leaving behind a residue at depth. We show that this residue can spread below the crust to the opposite hemisphere of the planet, that is, the northern hemisphere. We show that this causes, additionally to the dichotomy, also a north‐south difference in both the thermal and compositional structure of the interior of Mars. The advantage of our model is that it can concurrently explain the Martian dichotomy and the location of large and small martian volcanoes near the equator. Key Points: Mantle convection modeling is performed to study the consequence of a giant impact until present dayA thick crust is formed on the impacted hemisphere, suggesting a southern giant impact origin for the Martian crustal dichotomyLong‐lived melting produced preferentially at low‐latitude region in our models can explain the observed Martian volcanism [ABSTRACT FROM AUTHOR]

Precipitation projections in transient climate change scenarios have been extensively studied over multiple climate model generations. Although these simulations have also been used to make projections at specific Global Warming Levels (GWLs), dedicated simulations are more appropriate to study changes in a stabilizing climate. Here, we analyze precipitation projections in six multi‐century experiments with fixed atmospheric concentrations of greenhouse gases, conducted with the UK Earth System Model and which span a range of GWLs between 1.5 and 5°C of warming. Regions are identified where the sign of precipitation trends in high‐emission transient projections is reversed in the stabilization experiments. For example, stabilization reverses a summertime precipitation decline across Europe. This precipitation recovery occurs concurrently with changes in the pattern of Atlantic sea surface temperature trends due to a slow recovery of the Atlantic Meridional Overturning Circulation in the stabilization experiments, along with changes in humidity and atmospheric circulation. Plain Language Summary: Climate model projections consistently predict that summer precipitation over Europe is expected to decline in the future as global temperatures rise under continued global warming. In our study, we use new climate model simulations that simulate a world where atmospheric concentrations of greenhouse gases are no longer increasing and the rise in global temperatures has slowed down. We show that the summer rainfall decline across Europe can, to some extent, be reversed if global temperatures were to stabilize. This has important implications for adaptation and planning decisions, particularly in so‐called climate change "hot‐spots" such as the Mediterranean. Key Points: Climate stabilization experiments show significant differences in projected precipitation compared to high‐emission transient scenariosNorthern European and Mediterranean projected summer drying is partially reversedEuropean summer precipitation changes are consistent with the atmospheric response to Atlantic SST changes [ABSTRACT FROM AUTHOR]

This study develops an unstructured mesh generation tool for land surface modeling using a multi‐scale hexagon discrete mesh. The tool can automatically determine the required mesh resolution for different regions based on multi‐objective criteria such as elevation, slope, land cover, and land use. The refined unstructured meshes demonstrate significant enhancement in the representation of spatial heterogeneity. The tool is coupled with the Common Land Model (CoLM) to enable land surface simulations using unstructured meshes. Evaluations focused on runoff, river discharge, and inundation indicate improved model performance compared to traditional structured mesh‐based CoLM simulations under the same computational cost constraints. This tool provides new capabilities for more efficiently capturing localized land surface processes and extreme events. Plain Language Summary: The traditional square mesh cells used in land surface models (LSMs) have limitations in capturing the hydrological processes in regions with spatial solid heterogeneity, for example, mountains and forest‐grass transition zones. This study develops a new tool to generate unstructured mesh with flexible cell shapes and sizes. The tool can automatically adjust the mesh resolution based on the various land surface features. Thus, it can represent better spatial differences in elevation, vegetation, soil, etc. For example, it can use finer meshes for mountains and coarser meshes for desert areas. The new unstructured meshes are coupled with an existing LSM called Common Land Model. Model testing shows improved runoff, river discharge, and flooding simulation compared to traditional square mesh models under the same computation cost. Overall, the new unstructured mesh modeling approach enables more efficient and accurate simulation of localized land processes and extreme events, for example, droughts and floods. It has significance for disaster prevention and environmental studies. Key Points: An unstructured mesh generation tool for land surface models can automatically refine resolution based on multi‐objective landscape criteriaCoupling refined unstructured meshes with the Common Land Model (CoLM) model improves local hydrological simulation compared to traditional mesh‐based CoLMThe tool enables more efficient and accurate modeling of localized land surface processes and extreme events such as droughts and floods [ABSTRACT FROM AUTHOR]

Permafrost is a widespread phenomenon in the cold regions of the globe and is under‐represented in global monitoring networks. This study presents a novel low‐cost, low‐power, and robust Autonomous Electrical Resistivity Tomography (A‐ERT) monitoring system and open‐source processing tools for permafrost monitoring. The processing workflow incorporates diagnostic and filtering tools and utilizes open‐source software, ResIPy, for data inversion. The workflow facilitates quick and efficient extraction of key information from large data sets. Field experiments conducted in Antarctica demonstrated the system's capability to operate in harsh and remote environments and provided high‐temporal‐resolution imaging of ground freezing and thawing dynamics. This data set and processing workflow allow for a detailed investigation of how meteorological conditions impact subsurface processes. The A‐ERT setup can complement existing monitoring networks on permafrost and is suitable for continuous monitoring in polar and mountainous regions, contributing to cryosphere research and gaining deeper insights into permafrost and active layer dynamics. Plain Language Summary: Permafrost, frozen ground in cold regions, has significant impacts on the global environment. Monitoring of permafrost is crucial because it influences the global carbon cycle, hydrology, contaminant movement, and ecosystem stability. However, current monitoring systems have limitations, particularly in remote regions like Antarctica. To tackle this challenge, a new monitoring system, Autonomous Electrical Resistivity Tomography (A‐ERT), was introduced. A‐ERT is a geophysical technique that employs electrical signals to study ground freezes and thaws with high precision over time. Alongside this, open‐source processing tools were developed to process obtained A‐ERT data and efficiently extract essential information from large data sets. The developed A‐ERT system is robust, low‐cost, low‐power, and designed to operate in harsh conditions. Tested in Antarctica, our findings show that A‐ERT data combined with processing pipelines offers a valuable tool for examining freezing and thawing processes in extreme environments. The proposed setup can contribute to a network of autonomous permafrost monitoring systems, important for cryosphere research and advancing our understanding of climate change's impact on permafrost dynamics. Key Points: We present a robust low‐cost Autonomous Electrical Resistivity Tomography system for permafrost monitoring in polar and mountainous regionsWe introduce an open‐source tool for processing and inverting large data sets, enabling quick and efficient extraction of key informationField experiments conducted in Antarctica show high‐temporal‐resolution imaging of ground freezing and thawing dynamics [ABSTRACT FROM AUTHOR]

The variability of Mars exosphere over monthly to solar‐cycle scales at 251 and 412 km altitude is quantified by analysis of 41‐Ls mean densities derived from precise orbit determination of the Mars Reconnaissance Orbiter (MRO) and Mars Odyssey (MO) satellites, respectively. The data encompass 2006–2020 (MRO) and 2002–2020 (MO). At both altitudes, most of the variance is captured by cos(Ls–ϕ), where ϕ ≈ 258°. This term represents the effects of solar heating changes due to the eccentricity of Mars orbit around the Sun, and climatological changes in heating due to lower‐atmosphere dust loading, which does not play a significant role. The remaining variability is connected with the "irregular" variability of solar flux over monthly time scales. For MO, the presence of Helium disrupts a clean correlation with these sources. Plain Language Summary: The force of continuous bombardment of atmospheric particles on a satellite slowly changes its orbit. By tracking the satellite, changes in its orbit can in turn be used to infer atmospheric particle densities. In this paper, we use tracking from NASA's Deep Space Network, an international array of giant antennas, to measure minute orbital changes of the Mars Reconnaissance Orbiter and Mars Odyssey satellite orbits (and thereby atmospheric densities) around Mars during the 2002–2020 time frame. These data are used to study how the outer regions of Mars atmosphere respond to changes in heating due to solar radation absorption by various chemical species, and by dust that is elevated into the atmosphere by strong winds near the surface. The major finding of this paper is that the variability of Mars outer atmosphere is mainly controlled by solar heating changes due to the eccentricity of Mars orbit around the Sun. Key Points: Densities from precise orbit determination of Mars Reconnaissance Orbiter and Mars Odyssey are used to quantify long‐term variability of Mars' exosphereThe annual term is the greatest contributor to total variance, followed by the irregular component of EUV/UV fluxDust‐induced inter‐annual variability is small, but the analysis method does suppress potentially important regional‐scale events [ABSTRACT FROM AUTHOR]

An array of atmospheric profile observations consists of three‐dimensional vectors representing pressure, temperature, and humidity, with each profile forming a continuous curve in this three‐dimensional space. In this paper, the Signature method, which can quantify a profile's curve, was adopted for the atmospheric profiles, and the accuracy of profile representations was investigated. The description of profiles by the signature was confirmed with adequate accuracy. The machine‐learning‐based model, developed using the signature, exhibited a high level of annual accuracy with minimal absolute mean differences in temperature and water vapor mixing ratio (<2.0 K or g kg−1). Notably, the model successfully captured the vertical structure and atmospheric instability, encompassing drastic variations in water vapor and temperature, even during intense rainfall. These results indicate the Signature method can comprehensively describe the vertical profile with information on how ordered values are correlated. This concept would potentially improve the representation of the atmospheric vertical structure. Plain Language Summary: The atmospheric profile can be visualized as a three‐dimensional curve representing pressure, temperature, and humidity. By utilizing the Signature method, we can measure and quantify the profile's curve, allowing for comprehensive modeling of the atmosphere. In this paper, we confirmed the accuracy of atmospheric profile representation using signatures and introduced the characteristics of signatures revealed through machine‐learning models. The description of profiles by the signature was confirmed with adequate accuracy. Moreover, the model demonstrated robust annual accuracy, with minimal temperature and water vapor discrepancies. It effectively captured the vertical structure and instability of the atmosphere, even during heavy rainfall, characterized by significant temperature and water vapor content fluctuations. Key Points: The utilization possibility of the Signature method for atmospheric profiles was confirmedBy utilizing the Signature method, we can measure and quantify the profile's curve, allowing for comprehensive modeling of the atmosphereThe machine‐learning model developed with the signature can predict the profiles with high annual accuracy [ABSTRACT FROM AUTHOR]

Relic coastal landforms (fossil corals, cemented intertidal deposits, or erosive features carved onto rock coasts) serve as sea‐level index points (SLIPs), that are widely used to reconstruct past sea‐level changes. Traditional SLIP‐based sea‐level reconstructions face challenges in capturing continuous sea‐level variability and dating erosional SLIPs, such as tidal notches. Here, we propose a novel approach to such challenges. We use a numerical model of cliff erosion embedded within a Monte Carlo simulation to investigate the most likely sea‐level scenarios responsible for shaping one of the best‐preserved tidal notches of Last Interglacial age in Sardinia, Italy. Results align with Glacial Isostatic Adjustment model predictions, indicating that synchronized or out‐of‐sync ice‐volume shifts in Antarctic and Greenland ice sheets can reproduce the notch morphology, with sea level confidently peaking at 6 m and only under a higher than present erosion regime. This new approach yields insight into sea‐level trends during the Last Interglacial. Plain Language Summary: Scientists typically investigate the position of sea level in geological time using the elevation, age, and characteristics of fossil marine organisms living in shallow water (e.g., coral reefs), beach deposits, or erosional features that were formed near the sea level. However, these indicators offer only fragmented, if not only point‐like information in time and not a continuous sea‐level record. To overcome this issue, we use a numerical model that reconstructs the shape of tidal notches (i.e., indentations created close to sea level in carbonate cliffs). We compare model‐generated notch shapes with the real shape of the tidal notch, and we produce a set of continuous sea‐level histories that are more likely to have produced one of the best‐preserved fossil tidal notches in the Orosei Gulf, Sardinia, Italy, carved during the Last Interglacial highstand, 125.000 years ago. Our findings suggest that whether the ice sheets in Antarctica and Greenland melted at the same time or separately, both scenarios could reproduce the actual shape of the tidal notch we observe at present. Our findings indicate that the erosion rate during that period was higher than present and the sea level is very likely to have reached up to 6 m. Key Points: Cliff erosion modeling and Monte Carlo analysis indicate tidal notch geometry can offer a continuous record of past sea level variabilityThe geometry of Orosei's tidal notch, Italy can be replicated through simultaneous or asynchronous Antarctic–Greenland ice melting scenariosThe morphology of the Last Interglacial notch is more efficiently replicated using higher‐than‐present erosion rates and a 6 m sea‐level peak [ABSTRACT FROM AUTHOR]

Submesoscale vertical velocities, w, are important for the oceanic transport of heat and biogeochemical properties, but observing w is challenging. New remote sensing technologies of horizontal surface velocity at O(1) km resolution can resolve surface submesoscale dynamics and offer promise for diagnosing w subsurface. Using machine learning models, we examine relationships between the three‐dimensional w field and remotely observable surface variables such as horizontal velocity, density, and their horizontal gradients. We evaluate the machine learning models' sensitivities to different inputs, spatial resolution of surface fields, the addition of noise, and information about the subsurface density. We find that surface data is sufficient for reconstructing w, and having high resolution horizontal velocities with minimal errors is crucial for accurate w predictions. This highlights the importance of finer scale surface velocity measurements and suggests that data‐driven methods may be effective tools for linking surface observations with vertical velocity and transport subsurface. Plain Language Summary: Vertical velocities, w, are associated with ocean currents that move toward or away from the ocean surface and are important for connecting the surface and deep ocean. It is extremely difficult to measure w directly, but measurements of other variables that are related to w, such as horizontal currents that move along the surface in the north‐south or east‐west directions, can be exploited to predict w. Here, we investigate the feasibility of inferring w from other more easily measurable data. We compare three machine learning methods to see which is best at finding relationships between more easily measurable variables (the input data) and w at different depths. We test how using different input variables, adding noise to the input data, or changing the spatial resolution of the input data, impact the w predictions. Our results show that machine learning models are successful at reconstructing the 3D w field using high‐resolution (∼1 km) surface data, and in particular, surface horizontal velocities are the most important to include. This study shows that data‐driven methods are promising for relating remotely sensed surface measurements of the ocean to vertical velocities below the surface, which can help provide us with a better understanding of the 3D ocean. Key Points: Machine learning models diagnose the oceanic 3D submesoscale vertical velocity field within and below the mixed layer from surface dataHigh resolution horizontal surface velocity data is crucial for obtaining accurate vertical velocities subsurfaceConvolutional Neural Networks are relatively robust to noisy data and coarser data resolution [ABSTRACT FROM AUTHOR]

The Maritime Continent (MC), a critical region for inter‐basin climate interaction, harbors the world's highest marine biodiversity. Ocean warming in the MC, although with notable impacts on regional climate and marine ecosystems, remains poorly constrained by observations. By applying a volume‐correction algorithm to existing gridded observational data sets, this study provides an estimate for the ocean heat content (OHC) change of the MC. The results suggest a substantial OHC increase of 2.65 ± 0.46 Zettajoules during 1990–2015 (1.08 ± 0.17 W m−2) and limited changes before and after. This increase primarily arose from the enhanced Pacific Walker circulation, which drove a convergence of upper‐layer warm water toward the MC. A potential heat storage "hotspot" with enhanced warming below 500 m emerges within the Sulu Sea, which is supported by analysis of profile data collected in boreal winter but not in other seasons. Plain Language Summary: The Maritime Continent (MC) between the Pacific and Indian Oceans is a tropical region of numerous islands separating small sea basins. This region possesses the highest marine biodiversity of the world, which has been affected by the warming climate. How much the MC has warmed awaits assessment. In this work, we applied a volume‐correction method to existing observational data sets to improve the estimate of ocean heat content (OHC) change. We found that the OHC of the MC increased abruptly by 2.65 ± 0.46 Zettajoules during 1990–2015, equivalent to 1.08 ± 0.17 W m−2, and showed limited changes before and after this period. This increase was mainly caused by stronger than normal Pacific trade winds. Notably, the Sulu Sea showed stronger warming below 500 m than other seas of the MC, which is particularly robust in boreal winter. Key Points: The volume‐corrected 0–2,000 m ocean heat content of the Maritime Continent (MC) showed a substantial increase of 2.65 ± 0.46 ZJ during 1990–2015The enhanced Pacific Walker circulation during 1990–2015 drove a convergence of upper‐layer warm water toward the MCThere is a potential heat storage "hotspot" in the Sulu Sea with enhanced warming below 500 m [ABSTRACT FROM AUTHOR]

The impact of mid‐latitude oceanic frontal zones with sharp meridional sea‐surface temperature (SST) gradients on the middle atmosphere circulation during austral winter is investigated by comparing two idealized experiments with a high‐top gravity wave (GW) permitting general circulation model. Control run is performed with realistic frontal SST gradients, which are artificially smoothed in no‐front run. The control run simulates active baroclinic waves and GW generation around the mid‐latitude SST front, with GWs propagating into the stratosphere and mesosphere. In the no‐front run, by contrast, baroclinic‐wave activity is significantly suppressed, and GWs with smaller amplitude are excited and then dissipated at higher altitudes in the mesosphere. Westward wave forcing in the winter hemisphere was more pronounced in the control run up to ∼0.03 hPa, resulting in a more realistic reproduction of the middle atmospheric polar vortex. The results demonstrate the importance of realistic mid‐latitude ocean conditions for simulating the middle atmosphere circulation. Plain Language Summary: The impact of the mid‐latitude oceanic fronts characterized by sharp sea‐surface temperature (SST) gradients is investigated using a global gravity‐wave permitting atmospheric model that represents the troposphere, stratosphere and mesosphere. Two idealized experiments were conducted with different SST profiles. Control run features a realistic SST profile characterized by frontal SST gradients in mid‐latitudes, while they are smoothed out artificially in the "no‐front" run. In winter the no‐front run simulates significantly suppressed generation of synoptic‐scale cyclones and anticyclones, which results in reduced upward propagation of higher‐frequency gravity waves into the stratosphere, exerting marked impact on the large‐scale circulation extending as high as the mesopause. Notably higher gravity wave activity in the control run leads to a weaker, and more realistic wintertime polar vortex in the stratosphere and mesosphere. This study emphasizes the potential influence of mid‐latitude oceanic conditions on the atmospheric circulation, not only in the troposphere but also throughout the stratosphere and mesosphere. Key Points: High‐top global model simulations are conducted to examine the impact of a mid‐latitude oceanic front on the atmospheric circulationThe oceanic front enhances tropospheric baroclinic‐wave activity and generation of gravity waves propagating into the middle atmosphereThe enhanced gravity waves act to reduce cold bias of the wintertime polar vortex in the Southern Hemisphere middle atmosphere [ABSTRACT FROM AUTHOR]

The impact of assimilating ground‐based radar reflectivity on the rainband structure and secondary eyewall formation (SEF) of Hurricane Matthew (2016) is investigated within the framework of the Hurricane Weather Research and Forecasting model and its hybrid three‐dimensional ensemble‐variational data assimilation (DA) system. Compared to the control experiment (no radar reflectivity DA), the radar reflectivity DA experiment shows a clear signal of concentric eyewall and eyewall replacement cycle. Results demonstrate that radar reflectivity DA improves the stratiform rainband analysis, resulting in the mid‐level cooling associated with mesoscale descending inflow (MDI). The MDI further contributes to the low‐level acceleration maximum with boundary layer dynamics and triggers new convective updrafts in the SEF region. Momentum budget analysis also suggests that the mean vertical advection of absolute angular momentum plays an important role in the local momentum tendency in the SEF region in Hurricane Matthew (2016). Plain Language Summary: The impact of assimilating radar reflectivity on the secondary eyewall formation (SEF) of Hurricane Matthew (2016) is investigated within the framework of the Hurricane Weather Research and Forecasting model and its hybrid three‐dimensional ensemble‐variational data assimilation (DA) system. Compared to the control experiment (no radar reflectivity DA), the radar reflectivity DA experiment shows a clear signal of secondary eyewall and eyewall replacement cycle. Results demonstrate that radar reflectivity DA improves the stratiform rainband analysis, resulting in mesoscale descending inflow (MDI). The MDI further contributes to the low‐level tangential wind increase in boundary layer and triggers new convective updrafts in the SEF region. Results also suggests that the mean vertical advection of absolute angular momentum plays an important role in the local momentum tendency in the SEF region in Hurricane Matthew (2016). Key Points: Utilizing radar reflectivity data assimilation enhances the analysis of stratiform rainbands associated with mesoscale descending inflow (MDI)Momentum budget analysis indicates that the MDI brings high angular momentum to the boundary layer through the mean vertical advection termThe high angular momentum by the MDI contributes to the low‐level acceleration maximum in the secondary eyewall formation region [ABSTRACT FROM AUTHOR]

We conducted two‐dimensional numerical simulations to investigate the mechanisms underlying the strong spatiotemporal correlation observed between submarine landslides and gas hydrate dissociation due to glacial sea‐level drops. Our results suggest that potential plastic deformation or slip could occur at localized and small scales in the shallow‐water portion of the gas hydrate stability zone (GHSZ). This shallow‐water portion of the GHSZ typically lies within the area enclosed by three points: the BGHSZ–seafloor intersection, the seafloor at ∼600 m below sea level (mbsl), and the base of the GHSZ (BGHSZ) at ∼1,050 mbsl in low‐latitude regions. The deep BGHSZ (>1,050 mbsl) could not slip; therefore, the entire BGHSZ was not a complete slip surface. Glacial hydrate dissociation alone is unlikely to cause large‐scale submarine landslides. Observed deep‐water (much greater than 600 mbsl) turbidites containing geochemical evidence of glacial hydrate dissociation potentially formed from erosion or detachment in the GHSZ pinch‐out zone. Plain Language Summary: Many submarine landslides spatiotemporally correlate with gas hydrate dissociation. However, direct mechanical evidence supporting whether the overpressure and deformation due to glacial sea‐level drop‐induced hydrate dissociation are adequate for triggering submarine landslides is lacking. Here, we present two‐dimensional thermal‐hydraulic‐chemical and geomechanical models of a gas‐hydrate system in response to glacial sea‐level drops and conduct sensitivity analyses of the model behavior under a wide range of key conditions from a global perspective. Our simulations suggest that glacial hydrate dissociation might induce plastic deformation or slip at localized and small scales only possibly within the shallow‐water portion of the hydrate stability zone. The deep part (>1,050 m below sea level) of the bottom boundary of the hydrate stability zone could not slip; therefore, the entire bottom boundary of the hydrate stability zone was not a complete slip surface. We demonstrate that glacial hydrate dissociation alone is unlikely to trigger large‐scale submarine landslides. Our work highlights the vicinity of the upper limit of the hydrate stability zone (where the base of the hydrate stability zone intersects the seafloor) as an important area for investigating overpressure and focused fluid flow, localized plastic deformation or slip, and downslope sediment transport related to glacial hydrate dissociation. Key Points: Glacial hydrate dissociation might cause potential plastic deformation or slip at localized and small scales in shallow parts of the GHSZThe large deformation surface at the BGHSZ boundary of the potential plastic deformation zone was not a complete slip surfaceGlacial sea‐level drop‐induced gas hydrate dissociation alone is unlikely to have caused large‐scale submarine landslides [ABSTRACT FROM AUTHOR]

Theoretical analysis has revealed a specific resonance that shares the same condition as Landau resonance, but instead involves wave electromagnetic fields rather than traditionally electrostatic fields. While this resonance, referred to as electromagnetic Landau resonance due to its properties, is considered significant for magnetospheric dynamics, rare reports or evaluations based on observations have been made thus far. Here, we present an event detected by the Magnetospheric Multiscale mission near the dayside magnetopause. During this event, ∼748‐eV protons are observed to be in resonance with a wave. Detailed data analysis demonstrates the resonant velocity closely matches the wave's parallel phase speed, which, combined with the significant work done by wave perpendicular electric field, confirms this interaction as electromagnetic Landau resonance. Further investigation indicates these protons are being secularly accelerated within this resonance. Consequently, our observations provide the first empirical evidence supporting the previously suggested theoretical importance of the electromagnetic Landau resonance. Plain Language Summary: The electromagnetic Landau resonance shares the same resonance condition as the normal Landau resonance, but differs in that it involves the electromagnetic components of wave fields instead of the electrostatic components found in the case of the latter. Although it has been examined in theories and confirmed to occur in space plasmas experimentally, this resonance, especially the accompanying evolution of particle velocity distributions, has yet to be evaluated quantitatively through spacecraft observations. In this paper, we report the first observation of this resonance obtained by the Magnetospheric Multiscale mission near the dayside magnetosphere. In the reported case, protons of ∼400–1,000 eV are found to be in resonance with a wave. A more detailed examination of the observed fields and protons shows the corresponding resonant velocity is nearly identical to the wave's parallel phase speed. This observation, combined with the significant work done by wave perpendicular electric field, conclusively confirms the observed interaction as the electromagnetic Landau resonance. Further investigation indicates the protons are secularly accelerated by the wave via this resonance. Hence, our observations provide empirical evidence supporting the previously suggested theoretical significance of the electromagnetic Landau resonance. Key Points: MMS observations of electromagnetic Landau resonance near the dayside magnetopause are presentedThis resonance follows the same condition as the Landau resonance, but modulates particles via the electromagnetic components of wave fieldsAnalysis of the observed fields and protons provide conclusive evidence for this resonance accelerating protons [ABSTRACT FROM AUTHOR]

Changes in the volume transport of Atlantic water into the Arctic Ocean can affect the heat and mass balance in the central Arctic Ocean. To understand the impacts of Arctic storms on the inflow through Fram Strait, we implemented the NEMO ocean model for the Arctic Ocean, to simulate the decadal variations of the water volume transport through Fram Strait. The simulations suggest that the water inflow tends to be weaker in the decades of the 1960 and 2010s but stronger in the 1980s. The decadal variation is associated with decadal variability of the storm density in the Greenland Sea. When there is an increased storm density near Fram Strait, the southerly wind anomalies dominate the Atlantic water pathway. As a response, there is an increased Atlantic inflow through Fram Strait. Plain Language Summary: On decadal scales, Arctic storms near Fram Strait are highly correlated with the water volume transport into the Arctic Ocean through Fram Strait. When there are more storms near Fram Strait, the transport tends to increase. In addition, the heat flux associated with the water volume transport reflects the impacts of both the linear trend in ocean temperature and the decadal variation of water volume transport. Key Points: On a decadal scale, the storms in the Greenland Sea can affect the volume transport of Atlantic water inflow through Fram StraitAssociated heat flux reflects the impacts of both the linear trend in ocean temperature and the decadal variation of water volume transport [ABSTRACT FROM AUTHOR]

A fundamental problem in plasma turbulence is understanding how energy cascades across multiple scales. In this paper, a new weak turbulence theory is developed to explain how energy can be transferred from Langmuir and Upper‐Hybrid waves to ion‐acoustic waves. A kinetic approach is used where the Boltzmann equation is Fourier‐Laplace transformed, and the nonlinear term is retained. A unique feature of this approach is the ability to calculate power spectra at low frequencies, for any wavelength or magnetic aspect angle. The results of this theory explain how the predominant type of 150‐km radar echoes are generated in the ionosphere. First, peaks in the suprathermal electron velocity distribution drive a bump‐on‐tail like instability that excites the Upper‐Hybrid mode. This excited wave then couples nonlinearly to the ion‐acoustic mode, generating the ∼10 dB enhancement observed by radars. This theory also explains why higher frequency radars like ALTAIR do not observe these echoes. Plain Language Summary: The onset and evolution of turbulent flows is one of the most important outstanding questions in classical physics. When a fluid, gas, or plasma goes turbulent the flow can no longer be described with simple parameters such as speed and temperature. The fundamental problem is that these types of parameters describe the whole system, but during turbulence the flow is irregular and involves both microscopic and macroscopic motions. The research presented here shows how a macroscopic instability can drive microscopic changes at vastly different length and time scales. The approach taken falls into the category of weak‐turbulence theory, which is where the turbulence is not overpowering, and therefore can be described using some of the standard tools from gas dynamics. This new turbulence theory is applied to the problem of 150‐km echoes. These echoes are a plasma instability observed by radars in the lower ionosphere between 130 and 170 km in altitude. The mechanism of the plasma instability driving 150‐km radar echoes has previously been worked out, but the weak‐turbulence theory developed here is needed to fully explain the observations. The results provide an unprecedented description of plasma turbulence across multiple time and length scales. Key Points: A kinetic theory is developed to explain how Langmuir and Upper‐Hybrid waves couple nonlinearly to ion‐acoustic wavesNonlinear mode coupling solves the problem of how 150‐km radar echoes are generated in the lower ionosphereMode coupling explains why only lower frequency (30–50 MHz) radars observe the enhanced ion‐acoustic waves in 150‐km echoes [ABSTRACT FROM AUTHOR]

The February 2023 Turkey‐Syria Earthquake doublet ruptured multiple segments of the East Anatolian Fault (EAF) Zone. Dominating seismicity focal mechanism shifted dramatically from strike‐slip to normal‐faulting after the doublet. To better understand this shift, here we derived a comprehensive 3D co‐seismic displacement field and performed the stress analysis. Abundant space geodetic data were used to generate high‐resolution 3D surface displacement, which provide tight constraints on fault geometry, slip distribution and stress field. Together with stress inversion from aftershock focal mechanisms, we show that the principal stress direction rotation in the region with the most normal‐faulting aftershocks is the staggering 29°. The induced heterogenous stress may explain the shift of the dominant focal mechanism toward normal faulting. We suggest that the extensional horsetail splay faults, likely formed through geologic time scale related to the releasing bend on the EAF, are the hosts of most of the normal faulting aftershocks. Plain Language Summary: Sudden dislocation of two sides of a fault, or the rupture of rocks, produces an earthquake. The dislocation direction relative to the fault traces reflects the direction of stress that are responsible for the earthquake. When dislocation direction is parallel to the fault strike, the earthquake is termed as strike‐slip type, and termed as normal‐faulting type when they are perpendicular. A remarkable feature for the 2023 Turkey‐Syria Mw7.8 & 7.7 earthquake doublet is that, background seismicity shifted dramatically from strike‐slip to normal type of faulting after the doublet. To unravel the physical process resulted in this feature, we use space geodetic measurements to derive the surface displacements and stress field associated with the doublet. The derived stress field shows a staggering 29° rotation occurred in a horsetail splay fault structure where many normal‐faulting earthquakes happened. The large stress rotation indicates the doublet released considerable stress and may result in a heterogeneous stress field due to the stress change. The combination of the identified horsetail structure and stress rotation can help better explain the occurrence of pervasive normal‐faulting earthquakes. Key Points: We map the 3D displacements, slip distribution, and stress fields related to the 2023 Turkey‐Syria Earthquake doubletDramatic stress rotation occurred after the Earthquake doublet, up to 29°Stress rotation and horsetail splay fault structure are potentially responsible for normal‐faulting aftershocks [ABSTRACT FROM AUTHOR]

A severe hailstorm that occurred in Spain on 30 August 2022, caused material and human damage, including one fatality due to giant hailstones up to 12 cm in diameter. By applying a pseudo‐global warming approach, here we evaluate how a simultaneous marine heatwave (and anthropogenic climate change) affected a unique environment conductive to such giant hailstones. The main results show that the supercell development was influenced by an unprecedented amount of convective available energy, with significant contributions from thermodynamic factors. Numerical simulations where the marine heatwave is not present show a notable reduction in the hail‐favorable environments, related mainly to modifications in thermodynamic environment. Our simulations also indicate that the environment in a preindustrial‐like climate would be less favorable for convective hazards and thus the hailstorm event would likely not have been as severe as the observed one, being possible to perform a novel attribution of such kind. Plain Language Summary: In August 2022, northeastern Spain faced a damaging hailstorm with hailstones up to 12 cm, causing significant harm and one fatality. This study examined how hail‐favorable environments were modified by a marine heatwave and human‐induced climate change. Numerical simulations show that the storm's intensity was influenced by abundant atmospheric energy and moisture from the warm sea, partly influenced by human‐induced warming. When the warm sea factor was excluded from the simulations, hailstones were smaller. These findings emphasize the role of human‐induced climate change and warm sea surface temperature events in intensifying extreme and high‐impact weather events like hailstorms. Key Points: Unprecedented hailstones in Spain (up to 12 cm) caused widespread damage and one fatalityA record‐breaking marine heatwave enhanced the strong hail‐favorable environmentNovel demonstration of an extreme hailstorm event attribution to anthropogenic warming [ABSTRACT FROM AUTHOR]

The El Niño‐Southern Oscillation (ENSO) is considered an important driver of rainfall variability in Australia, amongst many other global locations. Despite knowledge of the expected modulation of seasonal rainfall by ENSO, there is no consistently used method to quantify the role that specific ENSO events play in driving the observed anomalous rainfall. In this manuscript we adapt the Fraction of Attributable Risk (FAR) method, commonly used to identify the anthropogenic impact on a particular event, to quantify the impact of ENSO on the occurrence of monthly rainfall anomalies. We also explicitly calculate the ENSO induced change in risk and the FAR for all observed spring rainfall rates for our eastern Australian regions. A prominent role for ENSO in driving the large spring 2022 rainfall anomalies is identified. Though we choose to focus on ENSOs impact on rainfall in various Eastern Australian regions, the results are applicable to other climate modes, regions and climatic variables. Plain Language Summary: The El Niño‐Southern Oscillation (ENSO) is considered an important driver of rainfall variability in Australia, amongst many other global locations. Despite understanding how ENSO is expected to alter rainfall, we do not currently quantify the role ENSO played in driving a observed rainfall anomaly in any given season. In this manuscript we adapt a method that is commonly used to identify the anthropogenic impact on a particular event; and instead, we quantify the impact of ENSO on the occurrence of monthly rainfall anomalies. We then calculate the ENSO‐induced change in risk for all observed spring rainfall rates for our selected eastern Australian regions. A prominent role for ENSO in driving large rainfall anomalies of spring 2022 is also identified. Though we choose to focus on ENSOs impact on rainfall in various eastern Australian regions in this study, the results are applicable to other climate modes, regions and climatic variables. Key Points: We adapt the commonly used Fraction of Attributable Risk method to attribute rainfall variability to the El Niño‐Southern OscillationWe present the ENSO induced change in risk and the FAR for all observed spring rainfall rates for three eastern Australian regionsThe increased spring 2022 East Australian rainfall was >5 times more likely, and largely attributed to the La Niña conditions present [ABSTRACT FROM AUTHOR]

Ocean mass increase contributes to global sea level rise, and plays an important role in understanding climate change. Here, we develop a data assimilation approach that enables the inference of ocean mass increase from global tide gauge network. This approach incorporates outputs from climate models and sea level fingerprints caused by water mass changes over land areas. The results suggest a trend of 2.15 ± 0.72 mm/yr for ocean mass increase over the period 1993–2022, which closes the global sea level budget with estimates of thermosteric sea level rise. Furthermore, the inferred ocean mass increase offers an insight into the causes of sea level rise since 1950. These findings emphasize the significance of climate models, in addition to simulating sea level changes, they contribute to understanding causes of sea level rise over the past decades. Plain Language Summary: Tide gauges record long‐term sea level changes, which encompass ocean thermal expansion and ocean mass increase due to water mass loss over global land areas. By carefully modeling these components, we can estimate the increase in global ocean mass using data from tide gauges. To this end, we construct a data assimilation approach that is driven by outputs from climate models. This approach reveals a 2.15 ± 0.72 mm/yr ocean mass trend for the satellite altimetry era, which could explain the observed global sea level rise with estimates of ocean thermal expansion. Further analysis indicates that the inferred ocean mass increase, combined along with the outputs of climate models, closely agrees with an independently reconstructed global mean sea level rise. Our findings emphasize the crucial role of climate models in comprehending the factors contributing to sea level rise over the past decades. Key Points: A data assimilation technique is driven by outputs from climate models to infer ocean mass increase from tide gaugesThe inferred ocean mass trend closes the global sea level budget over the satellite altimetry eraResults offer insights into the causes of global sea level rise since 1950 [ABSTRACT FROM AUTHOR]

A realistic representation of top‐of‐the‐atmosphere (TOA) radiation response to surface warming is key for trusting climate model projections. We show that coupled models with freely evolving ocean‐atmosphere interactions systematically underestimate the observed global TOA radiation trend during 2001–2022 in 552 simulations. Locally, even if a simulation spontaneously reproduces observed surface temperature trends, TOA radiation trends are more likely under‐ than overestimated. This response bias stems from the models' inability to reproduce the observed large‐scale surface warming pattern and from errors in the atmospheric physics affecting short‐ and longwave radiation. Models with a better representation of the TOA radiation response to local surface warming have a relatively low equilibrium climate sensitivity. Our bias metric is a novel process‐based approach which links a model's current response to climate change to its behavior in the future. Plain Language Summary: A realistic representation of the radiation balance at the top of the Earth's atmosphere (TOA) by coupled climate models is essential for trust in future climate projections. Despite that relevance, it is still not clear whether the models correctly simulate the coupling between surface warming and TOA radiation because of the short observational record. We show that climate models systematically underestimate the observed increase in global TOA radiation during 2001–2022 in 552 simulations. Locally, even if a simulation reproduces observed changes in surface temperature, changes in TOA radiation are more likely under‐ than overestimated. This response bias stems from the models' inability to reproduce the observed large‐scale patterns of surface warming and from errors in the atmospheric physics which suppress the communication of the surface information to the TOA. Models that better represent the TOA radiation response to local surface warming have a relatively low equilibrium climate sensitivity, that is, a weak global‐mean surface warming in response to a doubling of the atmospheric CO2 concentration above pre‐industrial levels. Our new bias metric links a model's current response to climate change to its behavior in the future. Key Points: Climate models underestimate the observed global TOA radiation trend during 2001–2022Surface warming patterns and atmospheric physics matter for the observation‐model discrepancyModels with a small bias in the coupling between surface warming and TOA radiation trends have a relatively low climate sensitivity [ABSTRACT FROM AUTHOR]

Jeffbenite (Mg3Al2Si3O12) is a tetragonal phase found in so far only in superdeep diamonds, and its thermoelastic parameters are a prerequisite for determining entrapment pressures as it is regarded as a potential indicator for superdeep diamonds. In this study, the thermoelastic properties of synthetic Fe3+‐jeffbenite were measured up to 33.7 GPa and 750 K. High‐temperature static compression data were fitted, giving (∂KT0/∂T)P = −0.0107 (4) GPa/K and αT = 3.50 (3) × 10−5 K−1. The thermoelastic properties and phase stability are applied to modeling isomekes, or P‐T paths intersecting possible conditions of entrapment in diamond. We calculate that under ideal exhumation, jeffbenite entrapped at mantle transition zone conditions will exhibit a high remnant pressure at 300 K (Pinc) of ∼5.0 GPa. Elastic geobarometry on future finds of jeffbenite inclusions can use the new equation of state to estimate entrapment pressures for this phase with still highly uncertain stability field in the mantle. Plain Language Summary: Ongoing superdeep diamonds research is providing new insights into the Earth's deep mantle. Natural superdeep diamonds and its inclusions can show compelling evidence for retrograde conversion from the lower mantle or transition zone precursors; along with carbonate melt‐peridotite reactions. Jeffbenite with a composition of Mg3Al2Si3O12, found in so far only in superdeep diamonds can be regarded as a potential indicator mineral for superdeep diamonds. Recent synthesis of Fe3+‐rich jeffbenite provides an opportunity for in‐situ measurements to study the thermodynamic properties of jeffbenite at deep‐mantle conditions. Thus, in this study, we explored the high pressure and temperature stability and thermoelastic properties of Fe‐bearing jeffbenite up to 33.7 GPa and 750 K. The thermoelastic data and phase stability were measured and the results are applied to modeling the isomekes, or P‐T paths intersecting possible conditions of entrapment and along which the pressure on the inclusion is equal to the external pressure on the diamond host. Our finding can be applied to determining entrapment pressures in such diamond inclusions in future finds and its primary or retrograde history is essential in understanding mantle dynamics and the hidden consequences of plate tectonics. Key Points: We measure the phase stability and thermoelastic properties on synthetic Fe‐bearing jeffbeniteThe thermoelastic data are applied to modeling isomekes and the remnant pressure (Pinc) is determinedThe smaller thermal expansivity of jeffbenite gives rise to a broader pressure and temperature stability field in the upper lower mantle [ABSTRACT FROM AUTHOR]

In the Baltic Sea, sea level variations are often very pronounced. During the winter season, storm surges caused by strong extratropical cyclones (ETCs) can have major societal impacts on coastal cities. In this study, using reanalysis‐based cyclone tracks and in‐situ tide gauge records, we show that serial cyclone clustering (SCC) leads to higher sea levels in the Baltic Sea than situations where only one ETC passes the tide gauge. Consequently, almost half of extreme sea level events in the Baltic Sea are associated with cyclone clustering periods. For example, in Helsinki, 45% of the extreme sea level events coincided with SCC periods of three or more ETCs, while only 6% of the events coincided with a single ETC. Our study represents a significant advance in the understanding of the factors influencing sea level variations in the Baltic Sea. Plain Language Summary: Sea levels in the Baltic Sea can vary a lot. In winter, powerful storms can lead to storm surges that seriously affect coastal towns. Our research studied storm paths and sea level observations. We found that multiple consecutive storms within a week raise sea levels in the Baltic Sea more than when only one storm passes the same location. As a result, most of the high sea level events in the Baltic Sea are linked to periods when several storms pass the region. In Helsinki, for instance, almost half of all analyzed high sea level events co‐occurred with periods when at least three storms occurred, while only 6% of high sea level events occurred due to a single storm. Our analysis is a significant progression in understanding the reasons that impact the Baltic Sea water levels. Hence, these results could aid in preparing for possible coastal floods. Key Points: Serial cyclone clustering (SCC) commonly causes elevated sea levels in the Baltic SeaPeak storm surges during SCC are on average 2–2.7 times (25–48 cm) higher than during single cyclonesThe intensity of the cyclones within the SCC modulates the storm surge levels, with deeper cyclones more likely to induce higher surges [ABSTRACT FROM AUTHOR]