Abstract
Abstract. SO2 cameras are becoming an established tool for measuring sulfur dioxide (SO2) fluxes in volcanic plumes with good precision and high temporal resolution. The primary result of SO2 camera measurements are time series of two-dimensional SO2 column density distributions (i.e. SO2 column density images). However, it is frequently overlooked that, in order to determine the correct SO2 fluxes, not only the SO2 column density, but also the distance between the camera and the volcanic plume, has to be precisely known. This is because cameras only measure angular extents of objects while flux measurements require knowledge of the spatial plume extent. The distance to the plume may vary within the image array (i.e. the field of view of the SO2 camera) since the plume propagation direction (i.e. the wind direction) might not be parallel to the image plane of the SO2 camera. If the wind direction and thus the camera–plume distance are not well known, this error propagates into the determined SO2 fluxes and can cause errors exceeding 50 %. This is a source of error which is independent of the frequently quoted (approximate) compensation of apparently higher SO2 column densities and apparently lower plume propagation velocities at non-perpendicular plume observation angles.Here, we propose a new method to estimate the propagation direction of the volcanic plume directly from SO2 camera image time series by analysing apparent flux gradients along the image plane. From the plume propagation direction and the known location of the SO2 source (i.e. volcanic vent) and camera position, the camera–plume distance can be determined. Besides being able to determine the plume propagation direction and thus the wind direction in the plume region directly from SO2 camera images, we additionally found that it is possible to detect changes of the propagation direction at a time resolution of the order of minutes. In addition to theoretical studies we applied our method to SO2 flux measurements at Mt Etna and demonstrate that we obtain considerably more precise (up to a factor of 2 error reduction) SO2 fluxes. We conclude that studies on SO2 flux variability become more reliable by excluding the possible influences of propagation direction variations.
Highlights
Prediction and monitoring of volcanic events is highly desirable
Remote sensing started with the correlation spectrometer (COSPEC, Moffat and Millan, 1971 and Stoiber et al, 1983) but more recently the differential optical absorption spectroscopy (DOAS) technique (Platt and Stutz, 2008) is applied to volcanoes
For field of view (FOV) angles of the SO2 camera larger than 2◦, the apparent plume extent in x direction and column densities are affected in a way that is different from the previous approach, when the plume is tilted with respect to the image plane
Summary
Prediction and monitoring of volcanic events is highly desirable. Besides conventional methods, like seismicity or deformation measurements, continuous monitoring of volcanic gas emissions is a still relatively new method for predicting volcanic eruptions. The propagation velocity of the plume and the distance between the plume and the camera are two important variables used to determine the SO2 flux from volcanoes using imaging data. An important prerequisite for the determination of absolute trace gas flux values is the precise knowledge of the distance between the plume and observing instrument (usually the SO2 camera). This distance is usually more difficult to (precisely) determine than it is generally assumed: while the geographic locations of the volcanic gas source (i.e. usually the crater) and the position of the instrument are almost always precisely known, the plume propagation direction (like the plume velocity) is not. This paper is about the possibility of determining the plume propagation direction itself from a time series of SO2 camera images of a volcanic plume
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