Improving Model Simulations of Volcanic Emission Clouds and Assessing Model Uncertainties

Volcanic emissions of ash and SO2 can be harmful to both human health, infrastructure, and aviation. In assessing these hazards, satellite remote sensing and transport modeling are useful tools. Satellite observations can track the volcanic clouds in the atmosphere, their main limitation being little vertical information. Transport models are used to forecast the three-dimensional atmospheric dispersion of the volcanic emissions, but large uncertainties are involved. The main sources of uncertainties are lacking knowledge of the emissions (source term), errors in the meteorological data driving the dispersion model, and the models description of physical processes such as loss mechanisms. One of the keys for achieving more reliable simulations is incorporating observation data into the models. In this chapter, we demonstrate three techniques useful for enhancing model simulations and for evaluating model uncertainties. First, the source term can be constrained by satellite observations via inverse modeling. Second, errors in the transport model and input data can be corrected for with data assimilation by updating the modeled fields with up-to-date observations. Third, uncertainties can be inferred from ensemble modeling. The Grimsvotn 2011 eruption is used to demonstrate how these three techniques together can improve the model simulations of volcanic clouds and determine model uncertainties.