Big grains go far: understanding the discrepancy between tephrochronology and satellite infrared measurements of volcanic ash

Abstract

Abstract. There is a large discrepancy between the size of volcanic ash particles measured on the ground at least 500 km from their source volcano (known as cryptotephra) and those reported by satellite remote sensing (effective radius of 0.5–9 μm; 95% of particles < 17 μm diameter). Here we present new results from the fields of tephrochronology (a dating technique based on volcanic ash layers), dispersion modelling and satellite remote sensing in an attempt to understand why. A literature review and measurements of prehistoric and recent eruptions were used to characterise the size range of cryptotephra grains. Icelandic cryptotephra deposited in NW Europe has lognormal particle size distributions (PSDs) with median lengths of 20–70 μm (geometric standard deviation: 1.40–1.66; 95th percentile length: 42–126 μm). Grain-size range estimates from the literature are similar. We modelled the settling of volcanic ash using measured fall velocities of ash particles, a release height typical of moderate Icelandic eruptions (10 km), and a wind speed typical for NW Europe (10 m s−1), to show that an ash cloud can transport particles up to 80 μm diameter up to 850 km in 24 h. Thus, even moderately sized Icelandic eruptions can be expected to deposit cryptotephra on mainland Europe. Using simulated satellite infrared data for dispersion-model-derived ash clouds, we demonstrate a systematic bias towards small grain sizes in retrievals of volcanic ash clouds that contain large proportions of cryptotephra-sized grains. As the median radius of the simulated PSD increases, fewer ash-containing pixels are correctly identified. Where retrievals are made of simulated clouds with mass median radii larger than ~ 10 μm, the mean retrieved reff plateaus at around 9 μm. Assuming Mie scattering by dense spheres when interpreting satellite infrared brightness temperature difference (BTD) data puts an upper limit on retrieved particle sizes. If larger, irregularly shaped ash grains can also produce a BTD effect, this will result in further underestimation of grain size, e.g. in coarse ash clouds close to a volcano.

The importance of grain size and shape in controlling the dispersion of the Vedde cryptotephra

“…Importantly, particle shape affects size measurements (e.g. ); our results suggest that the discrepancy in methods of size measurement between the dispersion modelling and cryptotephra communities can explain much of the reported discrepancy between observed and modelled travel distances (Lacasse, ; Beckett et al ., ; Stevenson et al ., ; Watson et al ., ).…”

Modeling Eruption Source Parameters by Integrating Field, Ground‐Based, and Satellite‐Based Measurements: The Case of the 23 February 2013 Etna Paroxysm

“…These factors produce an uncertainty of ~40% and ~30% respectively associated with the total mass retrieval and effective radius (Corradini et al, ). Another source of uncertainty is related to the presence of relatively large particles (typically for r e > 6 μm), possibly within the fine ash clouds, which cannot be retrieved using the Mie theory as Q ext does not vary significantly for r e > λ /2 (Guéhenneux et al, ; Stevenson et al, ). Overall, the effects related to both misdetection issues (i.e., BTD) and the presence of coarse ash particles in the cloud lead to a mass underestimation of 50% (Stevenson et al, ).…”

Atmospheric processes affecting the separation of volcanic ash and SO<sub>2</sub> in volcanic eruptions: inferences from the May 2011 Grímsvötn eruption

“…Stevenson et al (2015) discuss potential errors in satellite retrievals by using cryptotephra data to speculate that larger particles exist in dispersing ash clouds (although no atmospheric observations are presented) and claim through modelling studies that current retrieval schemes (all of them) underestimate mass loadings because of the dense sphere as- sumption and lack of sensitivity to particles with diameters > 10 µm. Estimating precision in retrievals is difficult because of the uncertainties in the input parameters, such as the complex index of refraction, the size distribution, and the shapes of the particles, although shape is generally found to result in the smallest discrepancy of the input parameters, with theoretical simulations showing differences in the range of 10-40 % (Yang et al, 2007b;Kylling et al, 2014).…”