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Comparing two satellite-based ash detection algorithms, RST_ASH and the London VAAC method, revealed their complementary nature. Combining these methods can improve volcanic ash cloud identification, crucial for air traffic safety.

Keywords:
AIRSEyjafjallajökullLondon VAAC methodRSTASHSEVIRIash clouds

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Area of Science:

  • Geophysics
  • Atmospheric Science
  • Remote Sensing

Background:

  • The 2010 Eyjafjallajökull eruption highlighted critical limitations in current volcanic ash monitoring and forecasting systems.
  • Operational procedures for Volcanic Ash Advisory Centers (VAACs) require enhancement to better manage air traffic disruptions.

Purpose of the Study:

  • To compare the performance of two satellite-based ash detection algorithms: RST_ASH and the operational London VAAC method.
  • To analyze the similarities and differences in ash cloud identification during the Eyjafjallajökull eruption.
  • To assess the potential benefits of combining these algorithms for improved ash detection.

Main Methods:

  • Utilized Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor data for ash detection.
  • Applied and compared the RST_ASH algorithm and the London VAAC operational method.
  • Quantitatively compared a merged SEVIRI ash product with independent Atmospheric Infrared Sounder (AIRS) Dust Detection Algorithm (DDA) observations.

Main Results:

  • Identified complementary behaviors between the RST_ASH and London VAAC methods in detecting ash clouds.
  • Demonstrated that combining the outputs of both algorithms can enhance ash-affected area identification under specific conditions.
  • Validated the merged SEVIRI ash product against independent AIRS DDA observations.

Conclusions:

  • The combination of RST_ASH and London VAAC methods offers a potentially more robust approach to volcanic ash detection.
  • Improved ash identification through combined algorithms can significantly aid VAACs in supporting air traffic management.
  • Further research into integrating multiple satellite-based algorithms is recommended for operational volcanic ash monitoring.