Passive Earth Observations of Volcanic Clouds in the Atmosphere

Abstract

Current Earth Observation (EO) satellites provide excellent spatial, temporal and spectral coverage for passive measurements of atmospheric volcanic emissions. Of particular value for ash detection and quantification are the geostationary satellites that now carry multispectral imagers. These instruments have multiple spectral channels spanning the visible to infrared (IR) wavelengths and provide 1 × 1 km2 to 4 × 4 km2 resolution data every 5–15 min, continuously. For ash detection, two channels situated near 11 and 12 μ m are needed; for ash quantification a third or fourth channel also in the infrared is useful for constraining the height of the ash cloud. This work describes passive EO infrared measurements and techniques to determine volcanic cloud properties and includes examples using current methods with an emphasis on the main difficulties and ways to overcome them. A challenging aspect of using satellite data is to design algorithms that make use of the spectral, temporal (especially for geostationary sensors) and spatial information. The hyperspectral sensor AIRS is used to identify specific molecules from their spectral signatures (e.g., for SO2) and retrievals are demonstrated as global, regional and hemispheric maps of AIRS column SO2. This kind of information is not available on all sensors, but by combining temporal, spatial and broadband multi-spectral information from polar and geo sensors (e.g., MODIS and SEVIRI) useful insights can be made. For example, repeat coverage of a particular area using geostationary data can reveal temporal behaviour of broadband channels indicative of eruptive activity. In many instances, identifying the nature of a pixel (clear, cloud, ash etc.) is the major challenge. Sophisticated cloud detection schemes have been developed that utilise statistical measures, physical models and temporal variation to classify pixels. The state of the art on cloud detection is good, but improvements are always needed. An IR-based multispectral cloud identification scheme is described and some examples shown. The scheme is physically based but has deficiencies that can be improved during the daytime by including information from the visible channels. Physical retrieval schemes applied to ash detected pixels suffer from a lack of knowledge of some basic microphysical and optical parameters needed to run the retrieval models. In particular, there is a lack of accurate spectral refractive index information for ash particles. The size distribution of fine ash (1–63 μ m, diameter) is poorly constrained and more measurements are needed, particularly for ash that is airborne. Height measurements are also lacking and a satellite-based stereoscopic height retrieval is used to illustrate the value of this information for aviation. The importance of water in volcanic clouds is discussed here and the separation of ice-rich and ash-rich portions of volcanic clouds is analysed for the first time. More work is required in trying to identify ice-coated ash particles, and it is suggested that a class of ice-rich volcanic cloud be recognized and termed a ‘volcanic ice’ cloud. Such clouds are frequently observed in tropical eruptions of great vertical extent (e.g., 8 km or higher) and are often not identified correctly by traditional IR methods (e.g., reverse absorption). Finally, the global, hemispheric and regional sampling of EO satellites is demonstrated for a few eruptions where the ash and SO 2 dispersed over large distances (1000s km).

Far‐travelled ash in past and future eruptions: combining tephrochronology with volcanic studies

“…Attempts to reconcile mapped deposits with satellite‐based observations show reasonable spatial correlations between ash clouds and resulting deposits to hundreds of kilometres, but fail to account for extrapolated estimates of unmapped ash at greater distances. A partial explanation for this discrepancy may be that infrared‐based retrieval methods are limited to ash sizes of 1–32 µm diameter (Prata and Lynch, ), and therefore may be missing ash mass in both smaller and larger size fractions (Stevenson et al , ). Also difficult to reconcile are the small ash sizes inferred from satellite retrievals, and used as input for most ash dispersion and transport models, compared with the large size reported for far‐travelled ash particles (Lacasse, ; Stevenson et al , ; Cashman and Rust, ).…”

“…Satellite‐based measurements of ash clouds, in contrast, are now routine and permit volcanic clouds to be tracked over thousands of kilometres, and for days after the end of an eruption (e.g. Mackie et al , ; Prata and Lynch, ). Problems arise, however, in linking satellite‐based and ground‐based observations.…”

“…Thin deposits, however, are easily remobilized by wind, water and gravity in the weeks, months and years that follow, adding errors to measurements of older deposits. Ash clouds can be tracked far beyond mapped deposits, but are limited to ash concentrations >~0.1–0.2 g m −2 (Prata and Lynch, ). Cryptotephra data are measured by shard counts that may lie close to this mass‐loading limit (Stevenson et al , ), although cryptotephra preservation varies with depositional environment, adding uncertainties to estimates of spatial coverage of ash at the time of the eruption (Davies et al , ; Lowe, ; Watson et al , ).…”

Atmospheric Dispersion Modelling at the London VAAC: A Review of Developments since the 2010 Eyjafjallajökull Volcano Ash Cloud

“…Satellite retrievals now have high temporal and spatial resolutions, but their application still has some limitations. Ash clouds can be obscured if they are overlaid by meteorological cloud, and retrievals can be problematic if the ash clouds are too optically thick or if they have a high-water content [142]. Retrievals are in two dimensions, and they do not provide information on the vertical profile of the ash concentrations, although the vertical depth and distribution of the ash layer can be determined from satellite-based (e.g., CALIOP) or ground-based lidar, and research flights when they become available.…”

FALL3D-8.0: a computational model for atmospheric transport and deposition of particles, aerosols and radionuclides – Part 2: model applications

“…To determine T s directly from measurements it is generally recommended to find a clear-air pixel near the volcanic cloud of interest (e.g. Wen and Rose, 1994) and can sometimes be determined by finding the maximum value of T 11 B in the scene (Prata and Lynch, 2019). Obtaining an estimate for T c from measurements, however, can be more difficult as the minimum value of T 11 B may not correspond to the (semi-transparent) ash cloud of interest.…”