Articles | Volume 12, issue 9
https://doi.org/10.5194/amt-12-5137-2019
https://doi.org/10.5194/amt-12-5137-2019
Research article
 | 
25 Sep 2019
Research article |  | 25 Sep 2019

A new discrete wavelength backscattered ultraviolet algorithm for consistent volcanic SO2 retrievals from multiple satellite missions

Bradford L. Fisher, Nickolay A. Krotkov, Pawan K. Bhartia, Can Li, Simon A. Carn, Eric Hughes, and Peter J. T. Leonard

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Cited articles

Ahmad, Z. and Bhartia, P. K.: Effect of Molecular anisotropy on the backscattered UV radiance, Appl. Optics, 34, 8309–8314, https://doi.org/10.1364/AO.34.008309, 1995. 
Ahmad, Z., Bhartia P. K., and Krotkov, N. A.: Spectral properties of backscattered UV radiation in cloudy atmospheres, J. Geophys. Res.-Atmos., 109, D01201, https://doi.org/10.1029/2003JD003395, 2004. 
Bhartia, P. K. (Ed.): OMI Algorithm Theoretical Basis Document, Vol. II, Ozone Products, available at: https://disc.gsfc.nasa.gov/datasets/OMTO3_V003/summary?keywords=OMTO3 (last access: 11 September 2019), 2002. 
Bobrowski, N., Honninger, G., Galle, B., and Platt, U.: Detection of bromine monoxide in a volcanic plume, Nature, 423, 273–276, http://https://doi.org/10.1038/nature01625, 2003. 
Bogumil, K., Orphal, J., Homann, T., Voigt, S., Spietz, P., Fleischmann, O. C., Vogel, A., Hartmann, M. Kromminga, H., Bovensmann, H., Frerick, J., Burrows J. P.: Measurements of molecular absorption spectra with the SCIAMACHY pre-flight model: instrument characterization and reference data for atmospheric remote-sensing in the 230–2380 nm region, J. Photoch. Photobio. A, 157, 167–184, https://doi.org/10.1016/S1010-6030(03)00062-5, 2003. 
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Short summary
This article describes a new discrete wavelength algorithm, MS_SO2, which has been used operationally to retrieve global daily volcanic SO2 vertical column densities and the UV volcanic ash index from the Total Ozone Mapping Spectrometer (TOMS) data collected by NASA’s Nimbus-7 satellite from 1978 to 1991. We examine the sensitivity of the algorithm to the detection of SO2, evaluate potential sources of error and compare results from MS_SO2 with the Principal Component Analysis (PCA) algorithm.
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