Quantitative Retrieval of Volcanic Sulphate Aerosols from IASI Observations - Sorbonne Université Access content directly
Journal Articles Remote Sensing Year : 2021

Quantitative Retrieval of Volcanic Sulphate Aerosols from IASI Observations

Elisa Carboni
  • Function : Author
  • PersonId : 1100540

Abstract

We developed a new retrieval algorithm based on the Infrared Atmospheric Sounding Interferometer (IASI) observations, called AEROIASI-H2SO4, to measure the extinction and mass concentration of sulphate aerosols (binary solution droplets of sulphuric acid and water), with moderate random uncertainties (typically ∼35% total uncertainty for column mass concentration estimations). The algorithm is based on a self-adapting Tikhonov–Phillips regularization method. It is here tested over a moderate-intensity eruption of Mount Etna volcano (18 March 2012), Italy, and is used to characterise this event in terms of the spatial distribution of the retrieved plume. Comparisons with simultaneous and independent aerosol optical depth observations from MODIS (Moderate Resolution Imaging Spectroradiometer), SO2 plume observations from IASI and simulations with the CHIMERE chemistry/transport model show that AEROIASI-H2SO4 correctly identifies the volcanic plume horizontal morphology, thus providing crucial new information towards the study of volcanic emissions, volcanic sulphur cycle in the atmosphere, plume evolution processes, and their impacts. Insights are given on the possible spectroscopic evidence of the presence in the plume of larger-sized particles than previously reported for secondary sulphate aerosols from volcanic eruptions.
Fichier principal
Vignette du fichier
remotesensing-13-01808.pdf (9.26 Mo) Télécharger le fichier
Origin : Publication funded by an institution

Dates and versions

hal-03244779 , version 1 (01-06-2021)

Identifiers

Cite

Henda Guermazi, Pasquale Sellitto, Juan Cuesta, Maxim Eremenko, Mathieu Lachatre, et al.. Quantitative Retrieval of Volcanic Sulphate Aerosols from IASI Observations. Remote Sensing, 2021, 13 (9), pp.1808. ⟨10.3390/rs13091808⟩. ⟨hal-03244779⟩
71 View
84 Download

Altmetric

Share

Gmail Facebook X LinkedIn More