Atmospheric Waves Research Articles

Source mechanism of the 2023 Ms 5.5 earthquake in Subei, Gansu Province revealed by relocated aftershocks and InSAR: complement to the ‘shallow slip deficit’ of the eastern boundary of the Altyn Tagh fault

The Ms 5.5 earthquake struck on 24 October 2023, in Subei County, Gansu Province, China, occurring along the eastern segment of the Altyn Tagh fault. It raises the question of whether this earthquake is linked to the ongoing shortening slip rate along this segment or triggered by other seismic events. Analyzing the fault geometry of the Subei earthquake and understanding the significance of the weakening activity rate for seismic hazards in neighboring regions is crucial. The surface deformation from small- and medium-sized earthquakes (magnitudes less than Mw5.5) is often subtle, and the coseismic deformation detected by interferometric synthetic aperture radar (InSAR) is vulnerable to atmospheric disturbances, leading to significant measurement errors. Moreover, inaccuracies in the regional crustal velocity structure can cause errors in earthquake localization based on seismic data. These challenges complicate the establishment of a rupture model for seismogenic faults and hinder the inversion of fault slip models. To overcome these limitations, we employed the time-series InSAR stacking method and aftershock relocation to determine the fault geometry of the Subei earthquake. A two-step inversion method was utilized to ascertain both the fault geometry and slip distribution. Our modeling indicates that the 2023 Subei earthquake had a thrust mechanism with a component of strike-slip. The rupture did not reach the surface, with the maximum fault slip measuring 0.45 m at a depth of 2.5–3.5 km. The fault dips westward, and the moment magnitude is calculated at 5.4. This earthquake is associated with the ongoing weakening of the left-lateral strike-slip rupture along the Altyn Tagh fault in the Subei region. Furthermore, retrograde thrust tectonics significantly contribute to the absorption of accumulated stress during this process.Our findings highlight the potential of utilizing time-series InSAR images to enhance earthquake catalogs with geodetic observations, offering valuable data for further studies of the earthquake cycle and active tectonics. This approach is also applicable in other tectonically active regions, enhancing understanding of seismic hazards and risk assessment.

High‐Fidelity Information Transmission Through the Turbulent Atmosphere Utilizing Partially Coherent Cylindrical Vector Beams

As the demand for high‐capacity and high‐fidelity communication systems continues to increase, addressing the challenges posed by noise and atmospheric turbulence disturbances is imperative. This study introduces and experimentally implements a novel free‐space optical communication protocol. This protocol combines the advantages of reducing the spatial coherence of light at the source with the capabilities of convolutional neural networks at the receiver to encode and transmit optical images through a noisy link. Light beams that are robust against noise are generated and atmospheric turbulence is modeled in a laboratory setting by decreasing the degree of spatial coherence of the source. Eight orbital angular momentum states, four polarizations, and eight coherence states of a light source that generates partially coherent cylindrical vector beams are utilized. These elements are employed to achieve a 256‐ary encoding/decoding data transmission within our protocol. This study is expected to catalyze further research into the utilization of partially coherent light and neural networks in the realm of free‐space optical communications.

Spatiotemporal Pattern Detection of Ground Deformations Induced by Extreme Rainfall using InSAR EGMS: The case of Cortina d’Ampezzo after Vaia Storm

Abstract. During October 2018 Vaia Storm occurred in the north of Italy, resulting in a huge amount of rainfall that was recorded. The focus here is given to Cortina d’Ampezzo area in the Veneto Region, due to the high importance of the area from touristic and sport perspectives and the presence of landslides. This study is devoted to investigating the impact of the severe sudden rainfall caused by this extreme atmospheric disturbance on the trends of ground deformations over this area, adopting a risk assessment perspective. The ground deformation Time Series (TS) have been derived from the European Ground Motion Service (EGMS) Ortho products derived from Sentinel-1 InSAR data. Then, according to the daily precipitation records and considering the time of this event as a turning temporal point, the TSs of all data points have been divided into pre-event and post-event phases. After obtaining the displacement rates in each phase, the quantified magnitude of changes in the pre-post rates has been calculated through a proposed simple formulation. The spatial distribution of the deformation parameters (i.e., pre-event displacement velocity and change in the pre-post displacement velocities) is found to be a practical tool for gaining comprehensive knowledge regarding the ground deformation and the effect of the extreme weather conditions on the displacement trends over the area. Furthermore, the positioning of the occurrence of deformation parameters has been compared to the landslide inventory of the area. The results showed that the extreme rainfall caused severe acceleration of displacements, more significant in horizontal East-West direction rather than vertical Up-Down direction. Some slight deceleration has been also detected. No initiation (or reactivation) of the stable zones was witnessed, and the portions with high magnitude of pre-event velocities are the ones whose displacement rates have been remarkably modified due to the severe event.

Spectroscopy using a visible photonic lantern at the Subaru Telescope: Laboratory characterization and the first on-sky demonstration on Ikiiki (α Leo) and ‘Aua (α Ori)

Context. Photonic lanterns (PLs) are waveguide devices enabling high-throughput single-mode spectroscopy and high angular resolution. Aims. We aim to present the first on-sky demonstration of a PL operating in visible light, to measure its throughput and assess its potential for high-resolution spectroscopy of compact objects. Methods. We used the SCExAO instrument (a double-stage extreme adaptive optics system installed at the Subaru Telescope) and FIRST mid-resolution spectrograph (R 3000) to test the visible capabilities of the PL on internal source and on-sky observations. Results. The best averaged coupling efficiency over the PL field of view was measured at 51% ± 10%, with a peak at 80%. We also investigated the relationship between coupling efficiency and the Strehl ratio for a PL, comparing them with those of a single-mode fiber (SMF). Findings show that in the adaptive optics regime a PL offers a better coupling efficiency performance than an SMF, especially in the presence of low-spatial-frequency aberrations. We observed Ikiiki (α Leo – mR = 1.37) and ‘Aua (α Ori – mR = −1.17) at a frame rate of 200 Hz. Under median seeing conditions (about 1 arcsec measured in the H band) and large tip or tilt residuals (over 20 mas), we estimated an average light coupling efficiency of 14.5% ± 7.4%, with a maximum of 42.8% at 680 nm. We were able to reconstruct both star’s spectra, containing various absorption lines. Conclusions. The successful demonstration of this device opens new possibilities in terms of high-throughput single-mode fiber-fed spectroscopy in the visible. The demonstrated on-sky coupling efficiency performance would not have been achievable with a single SMF injection setup under similar conditions, partly because the residual tip or tilt alone exceeded the field of view of a visible SMF (18 mas at 700 nm). This emphasizes the enhanced resilience of PL technology to such atmospheric disturbances. The additional capabilities in high angular resolution are also promising but still have to be demonstrated in a forthcoming investigation.

Resonant Excitation of Kelvin Waves by Interactions of Subtropical Rossby Waves and the Zonal Mean Flow

Abstract Equatorial Kelvin waves can be affected by subtropical Rossby wave dynamics. Previous research has demonstrated the Kelvin wave growth in response to subtropical forcing and the resonant growth due to eddy momentum flux convergence. However, the relative importance of the wave–mean flow and wave–wave interactions for the Kelvin wave growth compared to the direct wave excitation by the external forcing has not been made clear. This study demonstrates the resonant Kelvin wave excitation by interactions of subtropical Rossby waves and the mean flow using a spherical shallow-water model. The use of Hough harmonics as basis functions makes Rossby and Kelvin waves prognostic variables of the model and allows the quantification of terms contributing to their tendencies in physical and wave spaces. The simulations show that Kelvin waves are resonantly excited by interactions of Rossby waves and the balanced zonal mean flow in the subtropics, provided the Rossby and Kelvin wave frequencies, which are modified by the mean flow, match. The resonance mechanism is substantiated by analytical expressions. The Kelvin wave tendencies are caused by velocity and depth tendencies: The velocity tendencies due to the meridional advection of the zonal mean velocity can be outweighed by the zonal advection of the Rossby wave velocity or by the depth tendencies due to Rossby wave divergence. Identifying the resonant excitation mechanism in data should contribute to the quantification of Kelvin wave variability originating in the subtropics. Significance Statement This study seeks to understand how Kelvin waves, which are eastward-propagating disturbances in the tropical atmosphere, are connected to Rossby wave dynamics in the subtropics. Using idealized simulations, the Kelvin wave excitation is explained as a resonance effect due to interactions of Rossby waves and the zonal mean flow. The mechanism contributes to the understanding of atmospheric wave interactions and extratropical effects on the tropics. Further work searching for evidence of the new mechanism in atmospheric data may shed a new light on subseasonal variability in the tropics, such as the Madden–Julian oscillation.

The intensifying relationship between heatwaves in the mid–lower reaches of the Yangtze River valley and the upstream atmospheric wave train after the 2000s

The intensifying relationship between heatwaves in the mid–lower reaches of the Yangtze River valley and the upstream atmospheric wave train after the 2000s

Removing cloudiness on optical space images by a generative adversarial network model using SAR images

The object of this study is the process of removing cloudiness on optical space images. Solving the cloudiness removal task is an important stage in processing data from the Earth remote probing (ERP) aimed at reconstructing the information hidden by these atmospheric disturbances. The analyzed shortcomings in the fusion of purely optical data led to the conclusion that the best solution to the cloudiness removal problem is a combination of optical and radar data. Compared to conventional methods of image processing, neural networks could provide more efficient and better performance indicators due to the ability to adapt to different conditions and types of images. As a result, a generative adversarial network (GAN) model with cyclic-sequential 7-ResNeXt block architecture was constructed for cloud removal in optical space imagery using synthetic aperture radar (SAR) imagery. The model built generates fewer artifacts when transforming the image compared to other models that process multi-temporal images. The experimental results on the SEN12MS-CR data set demonstrate the ability of the constructed model to remove dense clouds from simultaneous Sentinel-2 space images. This is confirmed by the pixel reconstruction of all multispectral channels with an average RMSE value of 2.4 %. To increase the informativeness of the neural network during model training, a SAR image with a C-band signal is used, which has a longer wavelength and thereby provides medium-resolution data about the geometric structure of the Earth's surface. Applying this model could make it possible to improve the situational awareness at all levels of control over the Armed Forces (AF) of Ukraine through the use of current space observations of the Earth from various ERP systems

Detection of Extensive Equatorial Plasma Depletions After the 2022 Tongan Volcanic Eruption From Multiple Geodetic Satellite Ranging Systems

AbstractWe present a number of unique observations of ionospheric anomalies following the Hunga‐Tonga Hunga‐Ha'apai (HTHH) volcanic eruption on 15 January 2022. All are based on non‐dedicated geodetic satellite systems: Global Positioning System tracking of Low Earth Orbit (LEO) CubeSats, intersatellite tracking between two GRACE Follow‐On satellites, satellite radar altimeters to the ocean surface, and Doppler radio beacons from ground stations to LEO geodetic satellites. Their observations revealed the development of anomalously large trough‐like plasma depletions, along with plasma bubbles, in the equatorial regions of the Pacific and East Asian sectors. Trough‐like plasma depletions appeared to be confined within approximately ±20° magnetic latitude, accompanied by density enhancements just outside this latitude range. These plasma depletions and enhancements were aligned with the magnetic equator and occurred across broad longitudes. They were detected in regions where atmospheric waves from the HTHH eruption passed through around the time of the sunset terminator. We interpret these phenomena in terms of the E dynamo electric fields driven by atmospheric waves from the eruption. The uplift of the ionosphere beyond satellite altitudes, followed by subsequent plasma diffusion to higher latitudes along magnetic field lines, results in the formation of trough‐like plasma depletions around the magnetic equator and density enhancement at higher latitudes. The detection of plasma bubbles in the Asian sector during the non‐bubble season (January) is likely associated with the uplift of the ionosphere at the sunset terminator.

X‐Raying Neutral Density Disturbances in the Mesosphere and Lower Thermosphere Induced by the 2022 Hunga‐Tonga Volcano Eruption‐Explosion

AbstractWe present X‐ray observations of the upper atmospheric density disturbance caused by the explosive eruption of the Hunga Tonga‐Hunga Ha'apai (HTHH) volcano on 15 January 2022. From 14 January to 16 January, the Chinese X‐ray astronomy satellite, Insight‐HXMT, was observing the supernova remnant Cassiopeia A. The X‐ray data obtained during Earth's atmospheric occultations allowed us to measure neutral densities in the altitude range of 90–150 km. The density profiles above 110 km altitude obtained before the major eruption are in reasonable agreement with expectations by both GAIA and NRLMSIS 2.0 models. In contrast, after the HTHH eruption, a severe density depletion was found up to 1,000 km away from the epicenter, and a relatively weak depletion extending up to km for over 8 hr after the eruption. In addition, density profiles showed wavy structures with a typical length scale of either 20 km (vertical) or 1,000 km (horizontal). This may be caused by Lamb waves or gravity waves triggered by the volcanic eruption.

Synchronous decadal climate variability in the tropical Central Pacific and tropical South Atlantic

Pantropical climate interactions across ocean basins operate on a wide range of timescales and can improve the accuracy of climate predictions. Here, we show in observations that Central Pacific (CP) El Niño-like sea surface temperature (SST) anomalies have coevolved with tropical South Atlantic SST anomalies on a quasi-decadal (~10-year) timescale over the past seven decades. During the austral autumn–winter season, decadal warm SSTs in the tropical CP effectively induce tropical SST cooling in the South Atlantic, mainly by strengthening the South Atlantic subtropical anticyclone via an extratropical atmospheric wave teleconnection in the southern hemisphere. Partially coupled pacemaker simulations corroborate the observational findings, indicating that tropical CP decadal SSTs play a primary pacing role, while Atlantic feedback is of secondary importance throughout the study period. Our results suggest that the tropical CP could be an important source of decadal predictability for tropical South Atlantic SST and the surrounding climate.

Opportunities and barriers for skillful sub-seasonal prediction of East Asian summer precipitation

Abstract Accurate sub-seasonal (2-8 weeks) prediction of monsoon precipitation is crucial for mitigating flood and heatwave disasters caused by intra-seasonal variability (ISV). However, current state-of-the-art sub-seasonal-to-seasonal (S2S) models have limited prediction skills beyond one week when predicting weekly precipitation. Our findings suggest that predictability primarily arises from strong ISV events, and the prediction skills for ISV events depend on the propagation stability of preceding signals, regardless of models. This allows us to identify opportunities and barriers (OBs) within S2S models, clarifying what the models can and cannot achieve in ISV event prediction. Focusing on the complex East Asian summer monsoon (EASM), we discover that stable propagation of Eurasian and tropical atmospheric wave trains towards East Asia serves as an opportunity. This opportunity offers a one-week leading prediction skill of up to 0.85 and skillful prediction up to 13 days ahead for 43% of all ISV events. However, the Tibetan Plateau barrier highlights the limitation of EASM predictability. Identifying these OBs will help us gain confidence in making more accurate sub-seasonal prediction.

Combined Impacts of Autumn Snow Cover on the Tibetan Plateau and Northeast Asia on the Winter Eurasian Temperature

ABSTRACTThis study explores the combined effects of autumn snow cover anomalies on the Tibetan Plateau (TP) and Northeast Asia (NEA) on winter Eurasian temperature using observational data for the period 1972–2021 and a linear baroclinic model (LBM). Distinctive wintertime temperature patterns are found across the Eurasian continent corresponding to increased autumn snow cover in NEA when TP experiences normal, above‐normal, or below‐normal snow cover condition. In the scenario with an anomalous increase in autumn snow cover in NEA in combination with normal snow cover condition in TP, the overall winter temperature anomalies tend to be generally weak across the Eurasian continent. In years when autumn TP snow cover is above normal, the spatial distribution of winter temperature anomalies over the Eurasian continent associated with more NEA snow cover exhibits a ‘cold Arctic‐warm Eurasia’ (CAWE) pattern. The emergence of this CAWE pattern can be attributed to the low‐pressure system induced by the intensified NEA snow cover, which is further reinforced by the atmospheric wave train generated by negative North Atlantic sea surface temperature anomalies (SSTAs) in winter. This low‐pressure system amplifies the polar vortex and causes cooling in polar regions. Simultaneously, southeasterly winds along the southwestern flank of the North Pacific high‐pressure system contribute to warming in the mid‐latitude regions of Eurasia. While in years when autumn snow cover in TP is less than normal, more snow cover over NEA is accompanied by a ‘warm Arctic‐cold Eurasia’ (WACE) temperature anomaly pattern prevalent during the winter season. The decrease in autumn Barents‐Kara Sea ice is accompanied by a circulation pattern akin to the negative phase of the Arctic Oscillation during winter, favouring the southward intrusion of cold air, thus contributing to this WACE temperature anomaly pattern. Further analysis reveals that the impact of snow cover on the WACE temperature pattern is, for the most part, independent of the Arctic sea ice.

Internal gravity waves in the middle atmosphere and their impact on infrasound propagation across the International Monitoring System

Infrasound technology is used to monitor atmospheric events in order to guarantee compliance with the Comprehensive Nuclear-Test-Ban Treaty (CTBT). Over the 60 infrasound stations initially planned, 53 are operational to date as part of the International Monitoring System (IMS). As opposed to the waveform-related technologies that are used by the IMS to monitor the two other media of the geosphere (the underground and the oceans), infrasound waves are travelling in a continuously varying propagation medium. From minutes to hours and from a few hundreds of meters in the vertical to thousands of kilometers in the horizontal, atmospheric perturbations affect detection capabilities of the IMS at various scales. These perturbations need to be taken into account, for infrasound analysis to be able to provide accurate localization and characterization of sources of interest. In particular, internal gravity waves (atmospheric buoyancy waves) pose a serious challenge to atmospheric modelling because of the unresolved involved processes. They can dramatically affect transmission losses across the globe. Through numerical experiments and using high resolution modelling outputs of the atmosphere, backed up by atmospheric measurements, we demonstrate how gravity waves impact infrasound attenuation and drive signal amplification across the IMS.

Optical signal characteristics analysis of atmospheric disturbance density fields generated by high-speed aircraft

Aircraft disturbs the adjacent atmospheric environment in flight, forming spatial distribution features of atmospheric density that differ from the natural background, which may potentially be utilized as tracer characteristics to introduce new technologies for indirectly sensing the presence of aircraft. In this paper, the concept of a long-range aircraft detection based on the atmospheric disturbance density field is proposed, and the detection mode of tomographic imaging of the scattering light of an atmospheric disturbance flow field is designed. By modeling the spatial distribution of the disturbance density field, the scattered echo signal images of active light towards the disturbance field at long distance are simulated. On this basis, the characteristics of the disturbance optical signal at the optimal detection resolution are analyzed. The results show that the atmospheric disturbance flow field of the supersonic aircraft presents circular in the light-scattering echo images. The disturbance signal can be further highlighted by differential processing of the adjacent scattering images. As the distance behind the aircraft increases, the diffusion range of the disturbance signal increases, and the signal intensity and contrast with the background decrease. Under the ground-based observation conditions of the aircraft at a height of 10000 m, a Mach number of 1.6, and a detection distance of 100 km, the contrast between the disturbance signal and the background was 30 dB at a distance of one time from the rear of the fuselage, and the diffusion diameter of the disturbance signal was 50 m. At a distance eight times the length of the aircraft, the contrast decreased to 10 dB, and the diameter increased to 290 m. The contrast was reduced to 3 dB at a distance nine times the length of the aircraft, and the diameter was diffused to 310 m. These results indicate the possibility of long-range aircraft detection based on the characteristics of the atmospheric density field.

Forecasting the impact of marine heat waves on farmed bivalves Nodipecten nodosus and Magallana gigas

Marine heat waves are considered a threat to the cultivation of commercially important species because exposure to thermal stress may lead to mass mortalities of organisms. Investigating the upper thermal limits of marine species and their capacity for shifting these limits can contribute to securing the sustainability of aquaculture activities as exposure to heat extremes is increasing in frequency. The scallop Nodipecten nodosus and oyster Magallana [Crassostrea] gigas are two bivalve species commercially farmed in Brazil and production of spat is undertaken mainly at two hatcheries located in different regions subjected to distinct climate and seawater temperature conditions over the year. This study investigated the upper thermal tolerance of populations of N. nodosus and M. gigas sourced from temperate and tropical farming areas. Groups of N. nodosus and M. gigas farmed under warmer temperature regimes exhibited lower mortality rates when exposed to elevated temperatures compared to groups sourced from cooler waters and consequently displayed higher values of lethal temperature 50 (LT50). N. nodosus exhibited superior thermal tolerance than was previously known, however, commercial cultivation of this species is still at risk of mass mortalities depending on the duration and intensity of forecasted heat waves in both cultivation regions. M. gigas showed a high capacity to endure acute thermal stress at the resting stage of the reproductive cycle. To enhance the aquaculture sector's resilience to climate change, we recommend the development of cultivation methods that account for marine and atmospheric heat wave events, alongside continuous monitoring of abiotic factors at farming sites.

The analysis of the scatters of the filtered residuals of the GNSS stations from the crustal movement observation network of China

Through the analysis of the coordinate time series of the stations in the Crustal Movement Observation Network of China (CMONOC) from 2011 to 2019, it is found that the daily network scatters of the filtered residuals (called as SFR) of the station coordinate time series have obvious seasonal variation characteristics which reaches a maximum during summer and a minimum during winter. This phenomenon has not yet been further explained. Our analysis results demonstrate that the seasonal pattern of the daily SFR solutions is the temperature-dependent, such as small-scale atmospheric perturbation. The pattern of SFR series of the difference between the zenith wet delay (ZWD) calculated with GPS data and that calculated with meteorological data is similar to the SFR solutions computed using GPS data. The results mean that the estimated ZWD using GPS data does not fully capture the total real atmospheric variation. The atmospheric delay model in current GNSS analysis can effectively solve large-scale atmospheric delay estimation, but it may fail to deduct certain small-scale atmospheric disturbances. We think that a considerable portion of these small-scale disturbances are absorbed by the estimates of station positions.

An enhanced neighborhood differential method for potential landslide identification from stacking-InSAR results

Stacking-InSAR is widely used for identifying potential landslide. However, in Stacking-InSAR results, there are often challenges to clearly identify the potential landslide due to wide-scale system errors, especially the elevation-related atmospheric disturbances, leading to low precision of potential landslide identification. This paper introduces an enhanced neighborhood differential method that employs a concept of step size to identify potential landslide from Stacking-InSAR. Applied to the mountainous regions in the northwestern part of Sichuan Province, China, this method successfully identified 117 potential landslides, verified through field investigations. Compared to traditional Stacking-InSAR, this method additionally identified 34 potential landslides. Further analysis indicates that the optimal step size in the neighborhood differential method should ensure that one differential pixel is located inside the potential landslide area while the other is outside, thereby making the step size closely related to the spatial extent of the potential landslide. The results indicate that this method could effectively reduce wide-scale system error in Stacking-InSAR results, providing an important technical reference for the rapid and efficient identification of potential landslide over a wide mountainous area in the future.

Bias‐Eliminating Techniques in the Computation of Power Spectra for Characterizing Gravity Waves: Interleaved Methods and Error Analyses

AbstractObservational data inherently contain noise which manifests as uncertainties in the measured parameters and creates positive biases or noise floors in second‐order products like variances, fluxes, and spectra. Historical methods estimate and subsequently subtract noise floors, but struggle with accuracy. Gardner and Chu (2020, doi.org/10.1364/AO.400375) proposed an interleaved data processing method, which inherently eliminates biases from variances and fluxes, and suggested that the method could also eliminate noise floors of power spectra. We investigate the interleaved method for spectral analysis of atmospheric waves through theoretical studies, forward modeling, and demonstration with lidar data. Our work shows that calculating the cross‐power spectral density (CPSD) from two interleaved subsamples does reduce the spectral noise floor significantly. However, only the Co‐PSD (the real part of CPSD) eliminates the noise floor completely, while taking the absolute magnitude of CPSD adds a reduced noise floor back to the spectrum when the sample number is finite. This reduced noise floor can be further minimized through averaging over more observations, completely different from traditional spectrum calculations whose noise floor cannot be reduced by incorporating more samples. We demonstrate the first application of the interleaved method to spectral data, successfully eliminating the noise floor using the Co‐PSD in a forward model and in lidar observations of the vertical wavenumber of gravity waves at McMurdo, Antarctica. This high accuracy is gained by sacrificing precision due to photon‐count splitting, requiring additional observations to counter this effect. We provide quantitative assessment of accuracy and precision as well as application recommendations.

Cloud-Edge Motion by a Ducted Gravity Wave

Abstract The reflection of a wave at a fluid interface is fundamental to the atmospheric wave duct. As latent heating distinguishes the buoyancy response between cloudy and clear air, cloud edges can serve as a ducting interface for gravity waves. However, advection of the thermodynamic conditions by the ducted wave itself can cause evaporation or condensation, where the motion of cloud edges results from shrinking or enlarging regions of saturated air. For an idealized ducted wave mode trapped by a cloud layer, a linear Boussinesq analysis shows that its vertical motions produce a sinusoidal corrugation of the cloud edge that travels with the wave. When thermodynamic conditions are continuously varying, the cloud edge propagates as a moving onset of phase change and not as a material interface. Using this Boussinesq solution to initialize the full-physics Cloud Model 1 (CM1), the simulation confirms the amplitude and speed of the cloud-edge wave. In a comparison of simulations for domains of decreasing height, convergence to the Boussinesq ducted wave can be quantitatively established. This demonstration suggests a theory-based convergence benchmark for the motion of a cloud edge by phase change. Significance Statement Waves in the atmosphere can cause evaporation or condensation that results in changes to the shape of an individual cloud. A standard theory for airflow is extended to include the motion of the edges of a cloud. An example wave cloud as approximated by this theory is shown to be reproduced, with high accuracy, in a computer weather forecast model. The quantitative verification of this basic theory for clouds represents a new opportunity for exploring how wave interactions may be involved in the complex processes that shape the clouds that are an important component in our weather and climate systems.

Dynamics of rain-triggered lahars and destructive power inferred from seismo-acoustic arrays and time-lapse camera correlation at Volcán de Fuego, Guatemala

AbstractLahars, or volcanic mudflows, are one of the most devastating natural, volcanic hazards. Deadly lahars, such as the one that occurred after the Nevado del Ruiz, Columbia eruption in 1985, in which at least 23,000 people tragically lost their lives, threaten the safety and well-being of humans, the economy, and the infrastructure of many of the communities living in the vicinity of volcanoes. Due to their complex flow behaviors, lahars remain a major challenge to those studying them. We present an analysis of several rain-triggered lahar events at Volcán Fuego in Guatemala using both seismic and infrasound monitoring to quantify both ground vibrations and low-frequency atmospheric sound waves associated with these mudflows. Geophysical data collected over this field campaign quantifies flow parameters such as velocities, stage and the frequency of these rain-triggered lahars. Time-lapse imagery of lahar flows is compared with filtered seismo-acoustic signal characteristics to ascertain stage predictions and relationship to stage fluxes. Using random forest regression models, we establish moderate correlations (correlation coefficient modes 0.48–0.53) with statistical significance (p value = 0.01–0.02) between signal energetics and respective stage. Compiling a catalog of rain-triggered lahar events in Volcán de Fuego’s drainages over a season permits a dataset amenable to statistical analysis. Our goal is the development of new-generation geophysical monitoring tools that will be capable of remote and real-time estimation of flow parameters.