Meike Rix

Satellite Monitoring of Volcanic Sulfur Dioxide Emissions for Early Warning of Volcanic Hazards

Satellite-based remote sensing measurements of volcanic sulfur dioxide (SO2) provide critical information for reducing volcanic hazards. This paper describes the use of SO2 measurements from the thermal infrared sounder IASI and the UV-VIS instrument GOME-2 in services related to aviation hazard and early warning of volcanic unrest. The high sensitivity of both instruments to SO2 allows the detection and global tracking of volcanic eruption plumes and makes them a valuable tool for volcanic aviation hazard mitigation. The GOME-2 and IASI SO2 data are produced in near-real time and distributed to the Volcanic Ash Advisory Centers (VAACS) to assist them in issuing alerts to airlines and air traffic control organizations. Examples of recent eruptions affecting air traffic are presented including Jebel al Tair (Yemen, September 2007), Mount Okmok (Alaska, July 2008), and Mount Kasatochi (Alaska, August 2008). In addition, GOME-2 can detect changes in the SO2 emissions from passively degassing volcanoes and, therefore, provide critical information for hazard assessment. The monitoring of pre-eruptive degassing by GOME-2 is used in early warning of volcanic activity by a mobile volcano fast response system in combination with numerous other parameters, such as seismicity, deformation, and thermal anomalies.

Monitoring of volcanic SO 2 emissions using the GOME-2 satellite instrument

Atmospheric sulfur dioxide is an important indicator of volcanic activity. Space based atmospheric sensors like GOME-2 on MetOp and OMI on EOS-Aura make it possible to detect the emissions of volcanic SO2 and monitor volcanic activity and eruptions on a global scale. With GOME-2, it is possible to detect and track volcanic eruption plumes and SO2 from passive degassing in near-real time (NRT). This is particularly important for early warning services, as increases in SO2 fluxes are an indicator for new episodes of volcanic unrest. The SO2 daily measurements from space are used for several early warning services related volcanic risk (Exupery, GlobVolcano) and for aviation warning purposes (GSE-PROMOTE).

Trajectory matching and dispersion modeling of volcanic plumes utilising space-based observations

Within the projects SACS (Support to Aviation Control Service) and Exupery (the mobile volcano fast response system, VFRS) SO2 total columns are retrieved from different space-borne instruments such as GOME-2, SCIAMACHY and OMI. The backward trajectory matching technique is applied to relate exceptional SO2 values to particular sources and volcanic regions. Additionally, the moment of the eruption as well as the emission and the plume height can be estimated. Dispersion modeling is applied to forecast the motion of the plume and to estimate the SO2 emissions.

Investigating the GOME2/MetopA Total Sulphur Dioxide Load with the Aid of Chemical Transport Modelling over the Balkan Region

The current discerning capability of nadir viewing satellite instruments is mainly providing information on large volcanic events, such as the Kasatochi 2008 and the Eyjafjoll 2010 eruptions, and areas with high anthropogenic SO2 sources such as Peruvian smeltering regions. Consequently, there exists a constant need to improve the algorithms in order to provide satellite information on the megacities’ SO2 levels for air quality purposes. In the current study, we aim to assess the observational capability of the GOME2/MetopA instrument by analysing the total SO2 load estimated over the extended Balkan region with the use of the high spatial resolution Comprehensive Air Quality Model with extensions (CAMx) modelling results. Two years of satellite and modelling estimates have been analysed so as to pin-point locations of constantly high SO2 loading, locations with a marked seasonal variability as well as locations with high expected loading that might not be visible from the satellite orbit. Regions of specific interest will be chosen for further investigation and algorithm development based on updated modelling input parameters such as the SO2 loading profile.