Stefan Lachowycz
Postdoctoral Fulbright Scholar

Stefan Lachowycz

Research Interests

Physical volcanology; statistical analysis of volcanological data; external influences on volcanism; tephrochronology; volcano-ice interactions

Academics

M.S., Earth Sciences, University of Oxford, 2010
Ph.D., Earth Sciences, University of Oxford, 2016

Contact & Links

  • (202) 478-8841 | fax: (202) 478-8821
  • slachowycz at carnegiescience.edu
  • Department of Terrestrial Magnetism
    Carnegie Institution of Washington
    5241 Broad Branch Road, NW
    Washington, DC 20015-1305
  • curriculum vitae
  • Publications
  • Personal Website

Overview

Stefan Lachowycz
Area inundated by pyroclastic flows from the partial collapse of a lava dome (center of background) at Soufrière Hills Volcano, Montserrat (West Indies). Eruptive events such as the onset of extrusion and the destruction of lava domes sometimes occur without clear precursor signals in monitored parameters (seismicity, deformation, gas flux, etc.).

Stefan Lachowycz studies the temporal variability of different styles of volcanism over timescales from hours to hundreds of thousands of years, by analysing diverse records of volcanic activity. Understanding the nature of temporal variations in volcanism is essential to better understand volcanic processes and assess volcanic hazards. His PhD work at the University of Oxford entailed statistical analysis of time-series of earthquakes recorded during lava dome-forming eruptions at Volcán de Colima (Mexico) and Soufrière Hills Volcano (Montserrat), reviewing records of and analysing volcanic ash layers to constrain the history of explosive eruptions in the southernmost Andes, and studying time-varying volcano-ice interactions and magma chemistry at Volcán Sollipulli (Chile).

At the DTM, Stefan is investigating the prevalence and causes of (sub-)annual-scale changes in volcanic activity by statistical analysis of a variety of time-series from monitoring of diverse active volcanoes. Statistical analysis can reveal aspects of the underlying structure of the time-series that are not apparent from conventional analysis, so may be informative in forecasting changes in volcanic activity, which sometimes occur without clear precursory signals. Comparison of statistic time-series with each other and the monitoring data may also constrain the causes of changes in activity. He is particularly interested in the influence of external factors (such as weather and large earthquakes) on volcanic activity, as the conditions under and mechanisms by which volcanism is influenced by these factors are poorly understood.