1 Purpose

An important indicator for volcanic activity is the emission of trace gases, such as sulfur dioxide (SO2) (Schmincke 2004). SO2 is the third most abundant gas found in volcanic plumes after H2O and CO2. Additionally, volcanic eruptions and passive degassing are the most important natural source of SO2 and its atmospheric background level including anthropogenic emissions is usually relatively low. The lifetime of atmospheric SO2 varies from approximately 1-2 days in the troposphere to several weeks in the stratosphere.

Space-based atmospheric sensors operating in the ultra violet (UV) spectral range like TOMS, GOME and SCIAMACHY have played an important role in monitoring and quantifying volcanic SO2 emissions (Krueger 1983, Thomas et al. 2005, Loyola et al. 2007). The newest satellite-based sensors GOME-2 on MetOp-A and OMI on EOS-Aura enable to monitor volcanic activity and eruptions on a global scale and daily basis. Both sensors have also proven their ability to detect passive degassing of volcanoes (Carn et al. 2008, Rix et al. 2009). The GOME-2 SO2 retrieval is carried out in near real-time (NRT), i.e. within 2-3 hours after the actual GOME-2 measurement, which makes it a valuable tool for early warning systems (Rix et al. 2009), such as the Exupéry VFRS. In order to support the characterization of the volcanic activity daily MODIS true colour satellite imagery from the Aqua and Terra satellites with a spatial resolution of 500 m x 500 m enables the visual detection of volcanic ash.

A combination of satellite observations and backward trajectory ensembles are applied to derive more information on the volcanic eruption and plume characteristics out of the two-dimensional snapshots of the near-real-time GOME-2 observations. In order to quantify volcanic emission strengths and to reveal and investigate the long-range transport of volcanic emissions like SO2 and ash, case studies with the Lagrangian Particle Dispersion Model (LPDM) FLEXPART (Stohl et al. 2005) were carried out (Maerker et al. 2008).

The data are provided to the Exupéry database together with corresponding metadata and additional SO2 alert levels in the form of XML and GEOTIFF files. They can be visualized in the Exupéry Web GIS for the volcanic regions “Azores” and “Italy”.

Normalized intensity difference (ln(I/I0)inside_plume-ln(I/I0)outside_plume) for the Kasatochi eruption on 8 August 2008, as measured by GOME-2 (solid line) illustrating the strong SO2 absorption features used by the DOAS retrieval method. The dashed line denotes the SO2 absorption cross-sections in the UV wavelength region.
Coherent backward trajectory ensembles starting at the location of an enhanced GOME-2 SO2 observation (11 May 2008). The example demonstrates the height dependency of particle transport resulting in different transportation velocities.

1.1 Theoretical background

GOME-2 SO2 retrieval

SO2 columns are retrieved using data from the Second Global Ozone Monitoring Experiment (GOME-2) on MetOp-A. GOME-2 is a nadir-scanning UV-VIS spectrometer with a spectral coverage of 240 – 790 nm and a spectral (FWHM) resolution between 0.26 nm and 0.51 nm. It measures the back-scattered radiation from the earth-atmosphere system. In addition, a direct sun spectrum is recorded as reference once a day. The pixel size is 80 km x 40 km. With the normal operation mode near global coverage is achieved at the equator in one day.

SO2 slant columns are retrieved from the UV backscatter measurements of sunlight using the Differential Optical Absorption Spectroscopy (DOAS) method (Platt 1994) in the wavelength region between 315 – 326 nm. Input parameters for the DOAS fit include the absorption cross-section of SO2, for which the temperature is adjusted depending on the assumed height of the volcanic SO2 plume, and the absorption cross-sections of interfering gases, ozone and NO2. A further correction is made in the DOAS fit to account for the ring effect (rotational Raman scattering).

In the 315 – 326 nm wavelength range used for the retrieval, there is a strong interference of the SO2 and ozone absorption signals, especially at high solar zenith angles. Therefore, an interference correction is applied to the SO2 slant column values. The corrected slant column densities of SO2 are converted to geometry-independent vertical column (VC) amounts through division by an appropriate air mass factor (AMF) as VC = SC/AMF (Valks and Loyola 2008).

For SO2, the AMF is strongly dependent on measurement geometry, surface albedo, clouds, aerosols, and most importantly, the shape of the vertical SO2 profile in the atmosphere. For the AMF calculations, an a priori volcanic SO2 profile is assumed with a predefined central plume height and a Gaussian SO2 distribution. As the correct plume height is rarely available at the time of measurement, the SO2 column is computed for three different assumed volcanic plume heights: 2.5 km, 6 km and 15 km above ground level. The lowest height represents passive degassing of low volcanoes, the second height effusive volcanic eruptions or passive degassing of high volcanoes and the third height explosive eruptions. The AMFs are calculated using the radiative transfer model LIDORT (Spurr et al. 2001).

MODIS true colour images

The MODIS (Moderate Resolution Imaging Spectroradiometer) instruments are onboard the two satellites AQUA and TERRA. MODIS scans a swath of 2330 km across track by 10 km along track and provides global coverage every 1 to 2 days. It acquires data in 36 spectral bands between 0.4 µm and 14.4 µm. Bands 1 and 2 are imaged at a spatial resolution of 250 m at nadir, bands 3-7 at 500 m and the remaining 29 bands at 1 km.

The MODIS Rapid Response System makes use of the combination of different MODIS spectral bands to create true- or false-colour images. These combinations of various wavelengths bring out different characteristics of the atmosphere, for land as well as ocean surface. For creating MODIS Rapid Response true colour imagery an algorithm developed by Jacques Descloitres at NASA/GSFC is applied to the Level 1B radiances in order to remove gross atmospheric effects (Gumley et al. 2010). MODIS true colour images are based on the three spectral bands at 670 nm, 565 nm and 479 nm. These wavelengths correspond to the red, green and blue region of the light spectrum and the resulting image is similar to what a human eye would see. Therefore it enables the visual detection of volcanic ash.

Trajectory matching technique

In order to identify the source-receptor relationship the GOME-2 SO2 observations are stochastically analyzed with the kinematic 3D trajectory model FLEXTRA (Stohl et al. 1999) by releasing ensembles of backward trajectories using the temporal and spatial characterization of the SO2 observation. The backward trajectories are started at different pressure levels from ground up to 20 km. The starting point is not confined to the centre coordinate of the GOME-2 pixel. It is rather defined as an air mass (e.g. a volume).

Due to the vertical wind shear as a result of the reduction of the friction force with the altitude or changes in pressure gradients, emitted particles and gases are transported in different directions and with various velocities depending on their emission height. If the volcanic source and the eruption time are known, the backward trajectories that pass the volcano’s coordinates can be filtered in dependency of their heights and time resulting in a distribution of the emission height for the moment of the eruption. If the emission source is unknown, the backward trajectories are summed up and normalised for every grid cell. The result of this is a trajectory density map indicating the most probable source of an SO2 or ash plume. The underlying assumption is that the source-receptor relationship can be definitively determined by taking advantage of coherent trajectories. Kolmogorov-Smirnoff tests show a predominantly correct solution of the source-receptor relationship and that the eruption parameters can be identified accurately enough. Limitations of the technique occur for adjoining volcanoes with a distance lower than 100km and for a small vertical wind shear (Seidenberger 2009).

FLEXTRA is driven by meteorological wind and temperature fields from the numerical weather prediction models of the European Center for Medium Range Weather Forecast (ECMWF) and the National Oceanic and Atmospheric Administration (NOAA) respectively. In order to reconfirm the estimated volcanic source and the appropriate emission height, ensembles of forward trajectories are released at the volcano coordinates for different levels between 0 km and 20 km above mean sea level. By matching these forward trajectories with the SO2 retrieval of GOME-2 the backward trajectory results can be verified.

As trajectory models deliver rather qualitative information and neglect processes like convection, diffusion and turbulence, the more advanced Lagrangian Particle Dispersion Model (LPDM) FLEXPART (Stohl et al. 2005) is used for validation tasks and further analysis of the satellite observations regarding the quantification of volcanic emission strengths and the investigation of long-range transport processes of volcanic SO2 and ash (Maerker et al. 2008). FLEXPART has been disposed in many studies of the long-range atmospheric transport also of volcanic ash (Prata et al. 2007). It was validated on the basis of continental-scale tracer experiment data (Stohl et al. 1998).

The LPDM is initialized using source term parameters such as emission source, height, time and duration determined by the stochastic trajectory analysis. The model results provide a three dimensional calculation of the transport of volcanic emissions and are therefore important to address the climate impact of eruptions. They are currently also applied to investigate the predominant loss processes of SO2 and ash in the atmosphere and to quantify the sensitivity of the GOME-2 SO2.

1.2 References

Carn, S.A., Krueger, A., Arellano, S., Krotkov, N. and Yang, K. (2008): Daily monitoring of Ecuadorian volcanic degassing from space. Journal of Volcanology and Geothermal Research 176(1): 141-150.

Gumley, L., Descloitres, J. and Schmaltz, J. (2010): Creating Reprojected True Color MODIS Images: A Tutorial. URL: rapidfire.sci.gsfc.nasa.gov

Krueger, A.J. (1983): Sighting of El Chichon sulfur dioxide clouds with the Nimbus 7 total ozone mapping spectrometer, Science 220: 1377 – 1379

Loyola, D., J. van Geffen, P. Valks, T. Erbertseder, M. van Roozendael, W. Thomas, W. Zimmer and Wißkirchen K. (2007): Satellite-based detection of volcanic sulphur dioxide from recent eruptions in Central and South America. Advances in Geosciences 14:1-6

Maerker, C.; Seidenberger, K.; Erbertseder, T.; Rix, M.; Valks, P.; van Geffen, J. (2008): Trajectory matching and dispersion modeling of volcanic plumes utilising space-based observations. Use of Remote Sensing Techniques for Monitoring Volcanoes and Seismogenic Areas, 2008. USEReST 2008. Second Workshop, DOI 10.1109/USEREST.2008.4740343: 1-5

Platt, U. (1994): Differential optical absorption spectroscopy (DOAS), Air Monitoring by Spectroscopic Techniques. Chem. Anal. Ser. 127: 27-84, John Wiley, New York

Prata, A. J., Carn, S. A., Stohl, A. and Kerkmann, J. (2007): Long range transport and fate of a stratospheric volcanic cloud from Soufriere Hills volcano, Montserrat, Atmospheric Chemistry and Physics 7: 5093-5103

Rix, M., Valks, P., Hao, N., van Geffen, J., Clerbaux, C., Clarisse, L., Coheur, P.-F., Loyola, D., Erbertseder, T., Zimmer, W. and Emmad, S. (2009): Satellite Monitoring of Volcanic Sulfur Dioxide Emissions for Early Warning of Volcanic Hazards. JSTARS 2(3): 196–206.

Schmincke, H.-U. (2004): Volcanism. Springer-Verlag Berlin Heidelberg New York

Seidenberger, K (2009): Bestimmung der Charakteristik vulkanischer Emissionen mit satelliten-basierten Messungen, Trajektorienensembles und Chemie-Transport-Modellierung, Diploma Thesis, University of Augsburg and German Aerospace Center (DLR)

Spurr, R.J.D., Kurosu, T.P. and Chance, K.V. (2001): A linearized discrete ordinate radiative transfer model for atmospheric remote sensing retrieval, Journal of Quantitative Spectroscopy and Radiative Transfer 68: 689–735

Stohl, A., Hittenberger, M. and Wotawa, G. (1998): Validation of the Lagrangian particle dispersion model FLEXPART against large scale tracer experiment data, Atmospheric Environment 32: 4245-4264

Stohl, A., Haimberger, L., Scheele, M., and Wernli, H. (1999): An intercomparison of results from three trajectory models, Meteorological Applications 8:127–135

Stohl, A., Foster,C., Frank,A., Seibert,P., and Wotawa,G. (2005): Technical note: The Lagrangian particle dispersion model FLEXPART version 6.2, Atmospheric Chemistry and  Physics 5: 2461-2474

Thomas, W., Erbertseder, T., Ruppert, T., van Roozendael, M., Verdebout, J., Balis, D., Meleti, C. and Zerefos, C. (2005): On the Retrieval of Volcanic Sulfur Dioxide Emissions from GOME Backscatter Measurements, Journal of Atmospheric Chemistry 50:295-320

Valks, P. and Loyola, D. (2008): Algorithm Theoretical Basis Document for GOME-2 Total Column Products of Ozone, Minor Trace Gases and Cloud Properties (GDP 4.2 for O3M-SAF OTO and NTO), DLR/GOME-2/ATBD/01, Iss./Rev.: 1/D, 26 September 2008, URL: http://wdc.dlr.de/sensors/gome2/