the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 20 Sep 2024
Assimilation of volcanic sulfur dioxide products from IASI and TROPOMI into the chemical transport model MOCAGE: case study of the 2021 La Soufrière Saint-Vincent eruption
Abstract. Sulfur dioxide emitted during volcanic eruptions can be hazardous for aviation safety. As part of their activities, the Volcanic Ash Advisory Centres (VAACs) are therefore interested in the real-time atmospheric monitoring of this gas. A recent development aims at improving the forecasts of volcanic sulfur dioxide quantities made by the MOCAGE chemistry transport model. For this purpose, observations from both TROPOMI and IASI (B and C) instruments located on separate polar orbiting satellites are assimilated in the model. These sulfur dioxide measurements are based on the eruption event of the La Soufrière Saint-Vincent volcano in April 2021. Observations from the OMI instrument are considered as validation data. The resulting assimilation experiments show that the combined assimilation of IASI and TROPOMI observations always leads to a better forecast compared to the independent assimilation of data from each instrument. Sulfur dioxide atmospheric field forecasts are better when the available observations are numerous and cover a long time window.
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RC1: 'Comment on egusphere-2024-2941', Anonymous Referee #1, 16 Jan 2025
Review of 'Assimilation of volcanic sulfur dioxide products from IASI and TROPOMI into the chemical transport model MOCAGE: case study of the 2021 La Soufrière Saint-Vincent eruption' by M. Bacles et al.
General comments
This new study focuses on the assimilation of volcanic sulphur dioxide (SO₂) data from the TROPOMI and IASI satellite instruments into the MOCAGE chemical transport model, using the 2021 La Soufrière Saint-Vincent eruption as a case study. The research highlights the importance of integrating data from different satellite sensors, exploiting their complementary capabilities, to improve real-time atmospheric monitoring and forecasting of volcanic SO₂ plumes. The assimilation of combined observations significantly improves the accuracy of SO₂ plume predictions compared to using individual data sets, and also captures secondary transformations such as the conversion of SO₂ to sulphate aerosols. The study highlights the potential benefits of similar multi-sensor approaches for volcanic hazard monitoring and operational aviation safety.
The study is scientifically sound. The draft paper is well written and mostly clear and concise. I would like to recommend the paper for publication in AMT, subject to the following specific comments and technical corrections given below.
Specific comments
l204: "The background error covariance is spread on many vertical levels and on many meshgrids thanks to the correlation matrix." Please revisit the sentence and try to be a bit more specific, e.g. what are the actual correlation lengths imposed in the correlation matrix?
l359: I was wondering why the authors used the Probability of Detection (POD) but not the False Alarm Rate (FAR) and the Critical Success Index (CSI) to evaluate the model results? The POD is a useful metric, but it has limitations, for example if the model is too dispersive and largely overestimates the SO₂ plume concentrations, it will produce many hits and a high POD, but overall may not have good predictive quality. Could you please comment on this? Or even better, try to add FAR and CSI estimates?
l486: It would be good if the text was a bit more specific about how the background error covariances are defined.
l491: I'd like to suggest adding a few references regarding the limitations of the chemical modelling and the uncertainties of the meteorological data for the volcanic SO₂ chemistry-transport simulations, as these issues have been addressed in several previous studies.
l495: Using the information on where the satellites did not actually detect SO₂ sounds very helpful, especially to reduce false alarms. In this context it would be good to know if the FAR of the MOCAGE simulations is significant.
Technical corrections
l195: please combine multiple citations in a single set of parentheses
l201: "searched as a sum" -> "found as a sum"
l215: "15km of high" -> "15 km of altitude
l226: please use "AVK" or "Avk" consistently
l310 (and other places): please use abbreviations, "figure 4" -> "Fig. 4" (see AMT manuscript composition guidelines)
l372: please correct "The model did not ??? SO₂ total columns..."
l461: "TROPOMI and IASI instruments" -> "TROPOMI and IASI data"
l463: "more important amount of SO2" -> do you mean "more realistic"?
l475: "The more the forecast range term is small, the more the plume size is important". -> Revise/improve sentence?
Citation: https://doi.org/10.5194/egusphere-2024-2941-RC1 - RC2: 'Comment on egusphere-2024-2941', Anonymous Referee #2, 20 Jan 2025
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