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

We report the first detection of unrest at Socompa, Northern Chile, a stratovolcano which has recorded no eruptions since ~7,200 years ago. We measure deformation at and around Socompa using Interferometric Synthetic Aperture Radar (InSAR) observations between Jan 2018 and Oct 2021. We find that, whilst initially inactive, Socompa shows a steady uplift (17.5 mm/yr) from Dec 2019, independently recorded by near-field continuous Global Positioning System (GPS) data. The data can be fit with pressure increase in an ellipsoidal source region stretching from 1.9 to 9.5 km, with a volume change rate of ~5.8×106 m3/yr. Our observations of the onset of uplift preclude the possibility that a nearby Mw 6.8 deep intraslab earthquake on 3rd June 2020 triggered the unrest. The deformation signal we detect indicates the initiation of unrest at Socompa, after at least two decades without measurable deformation, and many thousands of years without volcanic activity.

In the absence of consistent meteorological data on Mars, the morphology of dunes can be employed to study its atmosphere. Specifically, barchan dunes, which form under approximately unimodal winds, are reliable proxies for the dominant wind direction. Here, we characterize near-surface winds on Mars from the morphology of >106 barchans mapped globally on the planet by a convolutional neural network. Barchan migration is predominantly aligned with the global circulation: northerly at mid-latitudes and cyclonic near the north pole, with the addition of an anti-cyclonic north-polar component that likely originates from winds emerging from the ice cap. Locally, migration directions deviate from regional trends in areas with high topographic roughness. Notably, obstacles <100 km such as impact craters are efficient at deflecting surface winds. Our database, which provides insights into planetary-scale aeolian processes on modern-day Mars, can be used to constrain global circulation models to assist with predictions for future missions.

Gravitational wave high-energy Electromagnetic Counterpart All-sky Monitor (GECAM) is a space-borne instrument dedicated to monitoring high-energy transients, thereinto Terrestrial Gamma-ray Flashes (TGFs) and Terrestrial Electron Beams (TEBs). We propose a TGF/TEB search algorithm, with which 147 bright TGFs and 4 TEBs are identified during an effective observation time of $\sim$ 9 months. We show that, with gamma-ray and charged particle detectors, GECAM can effectively identify and distinguish TGFs and TEBs, and measure their temporal and spectral properties in detail. Moreover, we find an interesting TEB consisting of two pulses with a separation of $\sim$ 150 ms, which is expected to originate from a lightning process near the geomagnetic footprint. We also find that the GECAM TGF’s lightning-association ratio is $\sim$ 80\% in the east Asia region using the GLD360 lightning network, which is significantly higher than previous observations.

Volcanic seismicity provides essential insights into the behavior of an active volcano across multiple time scales. However, to understand how magma moves as an eruption evolves, better knowledge of the geometry and physical properties of the magma plumbing system is required. In this study, using full-wave ambient noise tomography, we image the 3-D crustal shear-wave velocity structure below GreatSitkin Volcano in the central Aleutian Arc. The new velocity model reveals two low-velocity anomalies, which correlate with the migration of volcanic seismicity. With a partial melt of up to about 30%, these low-velocity anomalies are characterized as mushy magma reservoirs. We propose a six-stage eruption cycle to explain the migration of seismicity and the alternating eruption of two reservoirs with different recharging histories. The findings in this study have broad implications for the dynamics of magma plumbing systems and the structural control of eruption behaviors.Published on GRL on 6/8/2023: https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2022GL102438

Ice cliff distribution plays a major role in determining the melt of debris-covered glaciers but its controls are largely unknown. We assembled a dataset of 37537 ice cliffs and determined their characteristics across 86 debris-covered glaciers within High Mountain Asia (HMA). We complemented this dataset with the analysis of 202 cliff formation events from multi-temporal UAV observations for a subset of glaciers. We find that 38.9% of the cliffs are stream-influenced, 19.5% pond-influenced and 19.7% are crevasses. Surface velocity is the main predictor of cliff distribution at both local and glacier scale, indicating its dependence on the dynamic state and hence evolution stage of debris-covered glacier tongues. Supraglacial ponds contribute to maintaining cliffs in areas of thicker debris, but this is only possible if water accumulates at the surface. Overall, total cliff density decreases exponentially with debris thickness as soon as debris gets thicker than 10 cm.

We present the first evidence for a lower S-wave velocity (Vs ~3.3 to 3.5 km/s) at 8-17 km depth underlying a 4 km thick high-velocity zone with Vs >3.8 km/s beneath the west coast and the neighbouring parts of the Deccan Volcanic Province, India, coinciding with the last phase of volcanism. The velocity structure is derived from joint inversion of receiver function from 9 seismographs operated along ~106 km long W-E profile with the surface wave dispersion data. The low-velocity layer possibly represents the horizontally elongated frozen magma reservoir, the source for the magma eruption at ~65 million years produced due to the interaction of the Reunion hotspot with India. The shallow, high-velocity layer could be basaltic mafic intrusions responsible for the production of massive CO2 degassing. The Moho deepens beneath the west coast to ~45 km due to 10-15 km of underplating as a consequence of magma upwelling.

The non-linear reliance of channel steepness on erosion rates can be reconciled by the stochastic-threshold incision model that incorporates river incision threshold and discharge probability distribution into erosion efficiency. Here, we explored the usage of the model in river longitudinal profile inversion, by assuming time-dependent tectonic forcing and a linear exponent that relates channel incision to slope. We developed an analytical solution to the model equation and an inverse scheme to retrieve relative uplift rate history, whose validity was based on the theoretical demonstration on knickpoint preservation. Application of the inverse scheme to the main trunks of the Dadu River basin in the eastern Tibetan Plateau produced a history with two-phase increases in the uplift/incision rates, which is similar to the results from low-temperature thermochronology. Thus, our analytical procedures provide new insights into the link of tectonic uplift and river profile evolution, when channel steepness depends on erosion rates non-linearly. 

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

Stream networks are highly abundant across Earth’s surface, reflecting the tectonic and climatic history under which they have developed. Recent studies suggest that branching angles are strongly correlated with climatic aridity. However, the impact of tectonic forcing, especially in tectonically active regions, remains ambiguous. Here we analyze the branching angles of major stream networks on the eastern Tibetan Plateau, a region with complex tectonics, variable climate, and diverse landscapes. We find that spatial variations in tectonic uplift (as reflected in channel gradients) shape the branching geometry of stream networks on the steep eastern margin while in the flat interior of the eastern Tibetan Plateau, branching angles are mainly controlled by climatic aridity. This leads to the conclusion that, in the steep margin of the eastern Tibetan Plateau, climatic impacts on branching angles are overprinted by stronger tectonic controls.

Previous studies on South China’s convective precipitation forecast focused on the effects of multi-scale dynamics and microphysics parameterizations. However, how the uncertainty in aerosol data might cause errors in quantitative precipitation forecast (QPF) has yet to be investigated. In this case study, we estimate the impact of aerosol uncertainties on the QPF for South China’s severe convection using convection-permitting simulations. The variability range of aerosol concentrations is estimated with past observation for the pre-summer months. Simulation results suggest that the rainfall pattern and intensity change notably when aerosol concentrations are varied. The simulation with low aerosol concentrations produces the most intense precipitation, approximately 50\% stronger than the high-concentration simulation. Decreasing aerosol hygroscopicity also increases precipitation intensity, especially in pristine clouds. The aerosol uncertainty changes alter the number of cloud condensation and ice nuclei, which modifies the altitude and amount of latent heating and thereby modulates convection.

Products derived from remote sensing reflectances ($R_{rs}(\lambda)$), e.g. chlorophyll, phytoplankton carbon, euphotic depth, or particle size, are widely used in oceanography. Problematically, $R_{rs}(\lambda)$ may have fewer degrees of freedom (DoF) than measured wavebands or derived products. A global sea surface hyperspectral $R_{rs}(\lambda)$ dataset has DoF=4. MODIS-like multispectral equivalent data also have DoF=4, while their SeaWiFS equivalent has DoF=3. Both multispectral-equivalent datasets predict individual hyperspectral wavelengths’ $R_{rs}(\lambda)$ within nominal uncertainties. Remotely sensed climatological multispectral $R_{rs}(\lambda)$ have DoF=2, as information is lost by atmospheric correction, shifting to larger spatiotemporal scales, and/or more open-ocean measurements, but suites of $R_{rs}(\lambda)$-derived products have DoF=1. These results suggest that remote sensing products based on existing satellites’ $R_{rs}(\lambda)$ are not independent and should not be treated as such, that existing $R_{rs}(\lambda)$ measurements hold unutilized information, and that future multi- or especially hyper-spectral algorithms must rigorously consider correlations between $R_{rs}(\lambda)$ wavebands.

On Jan. 15, 2022, the Hunga Tonga-Hunga Ha’apai (HT) eruption injected SO2 and water into the middle stratosphere. Shortly after the eruption, the water vapor anomaly moved northward toward and across the equator. This northward movement appears to be due to a Rossby wave forced by the excessive IR water vapor cooling. Following the early eruption stage, persistent mid-stratospheric water vapor and aerosol layers were mostly confined to Southern Hemisphere (SH) tropics (Eq. to 30°S). However, during the spring of 2022, the westerly phase of the tropical quasi-biennial oscillation (QBO) descended through the tropics. The HT water vapor and aerosol anomalies were observed to again split across the equator coincident with the descent of the QBO shear zone. This split occurred because of the enhanced meridional transport circulation associated with the QBO. Neither transport event can be reproduced using MERRA2 assimilated winds.

We investigate the effect of extremely rough bathymetry on energy dissipation and mixing in a coastal region characterized by small-scale seafloor features penetrating a strongly-stratified density interface of comparable vertical scale. Our data from the non-tidal Baltic Sea include shear microstructure measurements and observations from a broadband echosounder, here used to resolve the extreme variability and intermittency of stratified turbulence in the vicinity of obstacles. Scale analysis and acoustic imaging of small-scale turbulent motions suggest that the underlying mixing mechanisms are related to topographic wake eddies and, to a smaller extent, to breaking internal waves near the bathymetric features. Vertical diffusivities exceed those at a nearby reference station with smooth bathymetry by up to two orders of magnitude. Our study emphasizes the importance of rough small-scale (< 1 km) bathymetric features for energy dissipation and vertical turbulent transport in coastal areas shaped by e.g., glacial, tectonic, or volcanic processes.

A document by Linying Gao. Click on the document to view its contents.

Climate change has altered the frequency, intensity, and timing of mean and extreme precipitation events. Extreme precipitation has caused tremendous socio-economic losses and displays strong regional variability. Although many previous studies have addressed daily extreme precipitation, hourly extreme rainfall still needs to be thoroughly investigated. In this study, we investigated the trends, spatio-temporal variability, and long-term variations in mean and extreme precipitation over South Korea using daily and hourly observational data. During the past 50 years (1973–2022), there has been a notable escalation in maximum hourly precipitation, although the boreal summer mean precipitation has increased only marginally. Regionally, an increase in mean and extreme rainfall occurred in the northern part of the central region. Moreover, increased intensity and frequency of extreme precipitation have contributed more to the total summer precipitation in recent years. Our findings provide scientific insights into the progression of extreme summer precipitation events in South Korea.

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

Atmospheric aerosol radiative effects regulate surface air pollution (O3 and PM2.5) via both the aerosol–photolysis effect (APE) and the aerosol–radiation feedback (ARF) on meteorology. Here, we elucidate the roles of APE and ARF on surface O3 and PM2.5 in the heavily polluted megacity, Delhi, India by using a regional model (WRF-Chem) with constraints from available and limited observation. While APE reduces surface O3 (by 6%) and PM2.5 concentrations (by 2.4% via impeding the secondary aerosol formations), ARF contributes to a 17.5% and 2.5% increase in surface PM2.5 and O3, respectively. The synergistic APE and ARF impact contributed to ~1 % of the total concentrations of O3 and PM2.5. Hence, the reduction of PM2.5 may lead to O3 escalation due to weakened APE. Sensitivity experiments indicate the need and effectiveness of reducing VOC emission for the co-benefits of mitigating both O3 and PM2.5 concentrations in Delhi.