Using wavelet coherence to aid the retrieval of volcanic SO₂ from UV spectra
Changes in the emission rate of volcanic sulphur dioxide (SO₂) are crucial parameters for identifying volcanic unrest and forecasting the eruptive activity. Ground-based ultraviolet (UV) remote sensing provides a near continuous record of the SO (Formula presented.) emission rate, with Differential...
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| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/173148 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Changes in the emission rate of volcanic sulphur dioxide (SO₂) are crucial parameters for identifying volcanic unrest and forecasting the eruptive activity. Ground-based ultraviolet (UV) remote sensing provides a near continuous record of the SO (Formula presented.) emission rate, with Differential Optical Absorption Spectroscopy (DOAS) being the preferred method for quantifying SO (Formula presented.) absorption from recorded spectra. However, retrieving accurate column amounts of SO (Formula presented.) using DOAS requires a complex fitting procedure that relies on user expertise for selecting suitable fit parameters and visually inspecting the fit results. We explore an alternative approach that exploits the well-defined spatial frequencies present in sky-scattered UV spectra. We use wavelet coherence to compare UV spectra recorded with calibration cells of known SO (Formula presented.) concentration in the wavelength–spatial frequency plane. Our findings reveal that the Magnitude-Squared Wavelet Coherence (MSWC) is inversely proportional to the SO (Formula presented.) concentration, suggesting that this relationship could be used to quantify volcanic SO (Formula presented.) in natural spectra. To validate this approach, we analyze UV spectra recorded by scanning-DOAS instruments from the Network of Volcanic and Atmospheric Change (NOVAC) at Masaya volcano, Nicaragua, and Soufrière Hills volcano, Montserrat. We observe a favourable comparison between the MSWC values we calculate and the slant column densities (SCDs) of SO (Formula presented.) obtained using the DOAS and iFit algorithms, respectively. We demonstrate the MSWC to be a robust indicator of SO (Formula presented.) which may potentially serve as a proxy for differential SCDs of volcanic SO (Formula presented.). The straightforward computation of the wavelet coherence between spectra offers an efficient means to identify spectra which contain the signature of the volcanic plume and an objective approach to validate results obtained using traditional fitting routines. |
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