Filling the Gaps: The Synergistic Application of Satellite Data for the Volcanic Ash Threat to Aviation

Although significant progress has been made in recent years, estimating volcanic ash concentration for the full extent of the airspace affected by volcanic ash remains a challenge. No single satellite, airborne or ground observing system currently exists which can sufficiently inform dispersion models to provide the degree of accuracy required to use them with a high degree of confidence for routing aircraft in and near volcanic ash. Toward this end, the detection and characterization of volcanic ash in the atmosphere may be substantially improved by integrating a wider array of observing systems and advancements in trajectory and dispersion modeling to help solve this problem. The qualitative aspect of this effort has advanced significantly in the past decade due to the increase of highly complementary observational and model data currently available. Satellite observations, especially when coupled with trajectory and dispersion models can provide a very accurate picture of the 3-dimensional location of ash clouds. The accurate estimate of the mass loading at various locations throughout the entire plume, however improving, remains elusive. This paper examines the capabilities of various satellite observation systems and postulates that model-based volcanic ash concentration maps and forecasts might be significantly improved if the various extant satellite capabilities are used together with independent, accurate mass loading data from other observing systems available to calibrate (tune) ash concentration retrievals from the satellite systems

Multilayer Cloud Detection with the MODIS Near-Infrared Water Vapor Absorption Band

Data Collection 5 processing for the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the NASA Earth Observing System EOS Terra and Aqua spacecraft includes an algorithm for detecting multilayered clouds in daytime. The main objective of this algorithm is to detect multilayered cloud scenes, specifically optically thin ice cloud overlying a lower-level water cloud, that presents difficulties for retrieving cloud effective radius using single layer plane-parallel cloud models. The algorithm uses the MODIS 0.94 micron water vapor band along with CO2 bands to obtain two above-cloud precipitable water retrievals, the difference of which, in conjunction with additional tests, provides a map of where multilayered clouds might potentially exist. The presence of a multilayered cloud results in a large difference in retrievals of above-cloud properties between the CO2 and the 0.94 micron methods. In this paper the MODIS multilayered cloud algorithm is described, results of using the algorithm over example scenes are shown, and global statistics for multilayered clouds as observed by MODIS are discussed. A theoretical study of the algorithm behavior for simulated multilayered clouds is also given. Results are compared to two other comparable passive imager methods. A set of standard cloudy atmospheric profiles developed during the course of this investigation is also presented. The results lead to the conclusion that the MODIS multilayer cloud detection algorithm has some skill in identifying multilayered clouds with different thermodynamic phase

Globally Detected Volcanic Lightning and Umbrella Dynamics During the 2014 Eruption of Kelud, Indonesia

Volcanic lightning shows considerable promise as a monitoring and research tool to characterize explosive eruptions. Its key strengths are rapid and remote detection, because the radio signals produced by lightning can propagate thousands of km at the speed of light. Despite these tantalizing properties, the scientific work on volcanic lightning has only recently started gaining momentum. Much more is needed to understand what lightning reveals about the evolution of an eruption in near-real time. Here we examine the timing and energy release of lightning generated by the eruption of Kelud volcano in Indonesia on 13 February 2014, as detected by the World Wide Lightning Location Network (WWLLN). The eruption column reached at least 26 km above sea level, representing the highest plume since the advent of global lightning networks in the last decade. Therefore, it provides valuable constraints on the electrification of end-member, sustained Plinian columns. We investigate the lightning in context with satellite images, photographs, and other published studies. Results show that the earliest satellite-detected activity was a thermal anomaly at ~15:46 UTC, corresponding to a directed blast at the onset of eruption (and only a few lightning strokes). Following a brief pause, the eruption produced a sustained column and umbrella cloud that spread outward into the tropical stratosphere. Rates of umbrella expansion provide an average mass eruption rate (MER) in the range of 8 × 107–1 × 108 kg s−1. A more nuanced picture emerges from the time-varying MERs (determined between each satellite pass), which show rapid intensification during the first hour of eruption, followed by constant MER for about an hour, and waning toward the end (after ~17:50 UTC). At this stage, decreasing flux into the umbrella cloud coincides with column instability and formation of pyroclastic density currents, as recorded by photos from the ground ~17:45 UTC. We infer that some of the erupted mass partitioned into ground-hugging currents, leading to a lower apparent MER. Interestingly, there is not a 1:1 correlation between lightning intensity and MER over the course of eruption. Stroke rates increase sharply within the first 30–40 min (during rapid intensification of the plume), and then drop below 2 strokes per min once the MER remains constant. This suggests that electrification was controlled by the rate of increase in MER—in other words, the acceleration of particles out of the vent. We also show that lightning stroke-rates and energies are greatest within 50 km of the vent, even when the ash cloud extends \u3e200 km downwind, indicating that lightning was focused in the regions of highest particle concentration and turbulence. Overall, we conclude that abrupt changes in lightning rates are clearly linked to changes in eruption behavior, and that rapid detection could aid monitoring efforts to characterize eruption rates or styles

The development of volcanic ash cloud layers over hours to days due to atmospheric turbulence layering

Volcanic ash clouds often become multilayered and thin with distance from the vent. We explore one mechanism for the development of this layered structure. We review data on the characteristics of turbulence layering in the free atmosphere, as well as examples of observations of layered clouds both near-vent and distally. We then explore dispersion models that explicitly use the observed layered structure of atmospheric turbulence. The results suggest that the alternation of turbulent and quiescent atmospheric layers provides one mechanism for the development of multilayered ash clouds by modulating vertical particle motion. The largest particles, generally >100 μm, are little affected by turbulence. For particles in which both settling and turbulent diffusion are important to vertical motion, mostly in the range of 10–100 μm, the greater turbulence intensity and more rapid turbulent diffusion in some layers causes these particles to spend greater time in the more turbulent layers, leading to a layering of concentration. The results may have important implications for ash cloud forecasting and aviation safety.Published versio

Summary of data on well-documented eruptions for validation of volcanic ash transport and dispersal models

This is a collection of data, references, and links to data on well-documented eruptions whose observations can be used to validate ash-cloud transport models. Data include, among other things, plume height, duration, erupted volume, satellite observations, numerical wind fields, and grain-size distribution

Lightning Rings and Gravity Waves: Insights Into the Giant Eruption Plume From Tonga's Hunga Volcano on 15 January 2022

Abstract On 15 January 2022, Hunga Volcano in Tonga produced the most violent eruption in the modern satellite era, sending a water‐rich plume at least 58 km high. Using a combination of satellite‐ and ground‐based sensors, we investigate the astonishing rate of volcanic lightning (>2,600 flashes min−1) and what it reveals about the dynamics of the submarine eruption. In map view, lightning locations form radially expanding rings. We show that the initial lightning ring is co‐located with an internal gravity wave traveling >80 m s−1 in the stratospheric umbrella cloud. Buoyant oscillations of the plume's overshooting top generated the gravity waves, which enhanced turbulent particle interactions and triggered high‐current electrical discharges at unusually high altitudes. Our analysis attributes the intense lightning activity to an exceptional mass eruption rate (>5 × 109 kg s−1), rapidly expanding umbrella cloud, and entrainment of abundant seawater vaporized from magma‐water interaction at the submarine vent

Estimation and propagation of volcanic source parameter uncertainty in an ash transport and dispersal model: Application to the Eyjafjallajokull plume of 14-16 April 2010

Data on source conditions for the 14 April 2010 paroxysmal phase of the Eyjafjallajökull eruption, Iceland, have been used as inputs to a trajectory-based eruption column model, bent. This model has in turn been adapted to generate output suitable as input to the volcanic ash transport and dispersal model, puff, which was used to propagate the paroxysmal ash cloud toward and over Europe over the following days. Some of the source parameters, specifically vent radius, vent source velocity, mean grain size of ejecta, and standard deviation of ejecta grain size have been assigned probability distributions based on our lack of knowledge of exact conditions at the source. These probability distributions for the input variables have been sampled in a Monte Carlo fashion using a technique that yields what we herein call the polynomial chaos quadrature weighted estimate (PCQWE) of output parameters from the ash transport and dispersal model. The advantage of PCQWE over Monte Carlo is that since it intelligently samples the input parameter space, fewer model runs are needed to yield estimates of moments and probabilities for the output variables. At each of these sample points for the input variables, a model run is performed. Output moments and probabilities are then computed by properly summing the weighted values of the output parameters of interest. Use of a computational eruption column model coupled with known weather conditions as given by radiosonde data gathered near the vent allows us to estimate that initial mass eruption rate on 14 April 2010 may have been as high as 108 kg/s and was almost certainly above 107 kg/s. This estimate is consistent with the probabilistic envelope computed by PCQWE for the downwind plume. The results furthermore show that statistical moments and probabilities can be computed in a reasonable time by using 94 = 6,561 PCQWE model runs as opposed to millions of model runs that might be required by standard Monte Carlo techniques. The output mean ash cloud height plus three standard deviations-encompassing c. 99. 7 % of the probability mass-compares well with four-dimensional ash cloud position as retrieved from Meteosat-9 SEVIRI data for 16 April 2010 as the ash cloud drifted over north-central Europe. Finally, the ability to compute statistical moments and probabilities may allow for the better separation of science and decision-making, by making it possible for scientists to better focus on error reduction and decision makers to focus on drawing the line for risk assessment. © 2012 Springer-Verlag Berlin Heidelberg

Ice fog in arctic during fram-ice fog project aviation and nowcasting applications

Increased understanding of ice fog microphysics can improve frost and ice fog prediction using forecast models and remote-sensing retrievals, thereby reducing potential hazards to aviationValiderad; 2014; 20140502 (andbra

A SmallSat Concept to Resolve Diurnal and Vertical Variations of Aerosols, Clouds, and Boundary Layer Height

International audienceA SmallSat mission concept is formulated here to carry out Time-varying Optical Measurements of Clouds and Aerosol Transport (TOMCAT) from space while embracing low-cost opportunities enabled by the revolution in Earth science observation technologies. TOMCAT's "around-the-clock" measurements will provide needed insights and strong synergy with existing Earth observation satellites to 1) statistically resolve diurnal and vertical variation of cirrus cloud properties (key to Earth's radiation budget), 2) determine the impacts of regional and seasonal planetary boundary layer (PBL) diurnal variation on surface air quality and low-level cloud distributions, and 3) characterize smoke and dust emission processes impacting their long-range transport on the subseasonal to seasonal time scales. Clouds, aerosol particles, and the PBL play critical roles in Earth's climate system at multiple spatiotemporal scales. Yet their vertical variations as a function of local time are poorly measured from space. Active sensors for profiling the atmosphere typically utilize sun-synchronous low-Earth orbits (LEO) with rather limited temporal and spatial coverage, inhibiting the characterization of spatiotemporal variability. Pairing compact active lidar and passive multiangle remote sensing technologies from an inclined LEO platform enables measurements of the diurnal and vertical variability of aerosols, clouds, and aerosol-mixing-layer (or PBL) height in tropical-to-midlatitude regions where most of the world's population resides. TOMCAT is conceived to bring potential societal benefits by delivering its data products in near-real time and offering on-demand hazard-monitoring capabilities to profile fire injection of smoke particles, the frontal lofting of dust particles, and the eruptive rise of volcanic plumes

Atmospheric controls on ground and space-based remote detection of volcanic ash Injection into the atmosphere, and link to early warning systems for aviation hazard mitigation

Violent volcanic eruptions, common especially in Southeast Asia, posean ongoing serious threat to aviation and local communities. However, the physicalconditions at the eruptive vent are difficult to estimate. In order to tackle thisproblem, satellite imagery and infrasound can rapidly provide information aboutstrong eruptions of volcanoes not closely monitored by on-site instruments. Forexample, the recent infrasonic array at Singapore, installed to support the coverageof the International Monitoring System, allows identification of nearby eruptingvolcanoes based on the characteristics of the recorded signal. But, due to its locationclose to the equator, seasonal changes in the wind velocity structure of the atmospherestrongly affect its potential to detect small volcanic eruptions at certainazimuths. To overcome this limit, infrasound could be augmented with satellite data. Yet, with the high average cloud cover in Southeast Asia, there are alsochallenges to identify weak volcanic plumes using satellite based monitoringtechniques. In this chapter, we aim to examine the relative strengths and weaknessesof the two technologies to better understand the possibility to improveoverall detection capability by combining infrasound with satellite imagery