Natural Hazards

, Volume 66, Issue 2, pp 389–412 | Cite as

Volcanic ash forecast during the June 2011 Cordón Caulle eruption

  • Estela Collini
  • María Soledad Osores
  • Arnau Folch
  • José G. Viramonte
  • Gustavo Villarosa
  • Graciela Salmuni
Original Paper

Abstract

We modelled the transport and deposition of ash from the June 2011 eruption from Cordón Caulle volcanic complex, Chile. The modelling strategy, currently under development at the Argentinean Naval Hydrographic Service and National Meteorological Service, couples the weather research and forecasting (WRF/ARW) meteorological model with the FALL3D ash dispersal model. The strategy uses volcanological inputs inferred from satellite imagery, eruption reports and preliminary grain-size data obtained during the first days of the eruption from an Argentinean ash sample collection network. In this sense, the results shown here can be regarded as a quasi-syn-eruptive forecast for the first 16 days of the eruption. Although this article describes the modelling process in the aftermath of the crisis, the strategy was implemented from the beginning of the eruption, and results were made available to the Buenos Aires Volcanic Ash Advisory Centers and other end users. The model predicts ash cloud trajectories, concentration of ash at relevant flight levels, expected deposit thickness and ash accumulation rates at relevant localities. Here, we validate the modelling strategy by comparing results with satellite retrievals and syn-eruptive ground deposit measurements. Results highlight the goodness of the combined WRF/ARW-FALL3D forecasting system and point out the usefulness of coupling both models for short-term forecast of volcanic ash clouds.

Keywords

Cordón Caulle volcanic complex Meteorological model Ash cloud forecast FALL3D model 

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Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  • Estela Collini
    • 1
  • María Soledad Osores
    • 1
  • Arnau Folch
    • 2
  • José G. Viramonte
    • 3
  • Gustavo Villarosa
    • 4
  • Graciela Salmuni
    • 5
  1. 1.Servicio de Hidrografía Naval (SHN) and Servicio Meteorológico Nacional (SMN)Buenos AiresArgentina
  2. 2.CASE DepartmentBarcelona Supercomputing Center-Centro Nacional de Supercomputación (BSC-CNS)BarcelonaSpain
  3. 3.INENCO-GEONORTE (UNSa-CONICET)SaltaArgentina
  4. 4.INIBIOMA, CRUB (CONICET-Universidad Nacional del Comahue)BarilocheArgentina
  5. 5.CONAEBuenos AiresArgentina

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