Uncertainty Assessment and Applicability of an Inversion Method for Volcanic Ash Forecasting

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Uncertainty Assessment and Applicability of an Inversion Method for Volcanic Ash Forecasting Atmos. Chem. Phys., 17, 9205–9222, 2017 https://doi.org/10.5194/acp-17-9205-2017 © Author(s) 2017. This work is distributed under the Creative Commons Attribution 3.0 License. Uncertainty assessment and applicability of an inversion method for volcanic ash forecasting Birthe Marie Steensen1, Arve Kylling2, Nina Iren Kristiansen2, and Michael Schulz1 1Research department, Norwegian Meteorological Institute, Oslo, 0131, Norway 2Atmosphere and Climate Department, Norwegian Institute for Air Research (NILU), Kjeller, 2007, Norway Correspondence to: Birthe Marie Steensen ([email protected]) Received: 30 November 2016 – Discussion started: 27 January 2017 Revised: 2 June 2017 – Accepted: 9 June 2017 – Published: 31 July 2017 Abstract. Significant improvements in the way we can ob- estimate is found in this case to have an order-of-magnitude- serve and model volcanic ash clouds have been obtained greater impact on the a posteriori solution than the mass load since the 2010 Eyjafjallajökull eruption. One major devel- uncertainties in the satellite. Part of this is explained by a opment has been the application of data assimilation tech- too-high a priori estimate used in this study that is reduced niques, which combine models and satellite observations by around half in the a posteriori reference estimate. Setting such that an optimal understanding of ash clouds can be large uncertainties connected to both a priori and satellite gained. Still, questions remain regarding the degree to which mass load shows that they compensate each other, but the the forecasting capabilities are improved by inclusion of such a priori uncertainty is found to be most sensitive. Because of techniques and how these improvements depend on the data this, an inversion-based emission estimate in a forecasting input. This study explores how different satellite data and dif- setting needs well-tested and well-considered assumptions ferent uncertainty assumptions of the satellite and a priori on uncertainties for the a priori emission and satellite data. emissions affect the calculated volcanic ash emission esti- The quality of using the inversion in a forecasting environ- mate, which is computed by an inversion method that couples ment is tested by adding gradually, with time, more observa- the satellite retrievals and a priori emissions with dispersion tions to improve the estimated height versus time evolution model data. Two major ash episodes over 4 days in April of Eyjafjallajökull ash emissions. We show that the initially and May of the 2010 Eyjafjallajökull eruption are studied. too-high a priori emissions are reduced effectively when us- Specifically, inversion calculations are done for four differ- ing just 12 h of satellite observations. More satellite observa- ent satellite data sets with different size distribution assump- tions (> 12 h), in the Eyjafjallajökull case, place the volcanic tions in the retrieval. A reference satellite data set is chosen, injection at higher altitudes. Adding additional satellite ob- and the range between the minimum and maximum 4-day servations (> 36 h) changes the a posteriori emissions to only average load of hourly retrieved ash is 121 % in April and a small extent for May and minimal for the April period, be- 148 % in May, compared to the reference. The corresponding cause the ash is dispersed and transported effectively out of a posteriori maximum and minimum emission sum found for the domain after 1–2 days. A best-guess emission estimate these four satellite retrievals is 26 and 47 % of the a posteri- for the forecasting period was constructed by averaging the ori reference estimate for the same two periods, respectively. last 12 h of the a posteriori emission. Using this emission for Varying the assumptions made in the satellite retrieval is seen a forecast simulation leads to better performance, especially to affect the a posteriori emissions and modelled ash column compared to model simulations with no further emissions loads, and modelled column loads therefore have uncertain- over the forecast period in the case of a continued volcanic ties connected to them depending on the uncertainty in the eruption activity. Because of undetected ash in the satellite satellite retrieval. By further exploring our uncertainty esti- retrieval and diffusion in the model, the forecast simulations mates connected to a priori emissions and the mass load un- generally contain more ash than the observed fields, and the certainties in the satellite data, the uncertainty in the a priori model ash is more spread out. Overall, using the a posteri- Published by Copernicus Publications on behalf of the European Geosciences Union. 9206 B. M. Steensen et al.: Uncertainty assessment and applicability of an inversion method ori emissions in our model reduces the uncertainties in the Boichu et al. (2013) investigated the SO2 emissions of the ash plume forecast, because it corrects effectively for false- 2010 Eyjafjallajökull eruption in early May by a similar in- positive satellite retrievals, temporary gaps in observations, version method and found that SO2 source terms calculated and false a priori emissions in the window of observation. with only a single satellite image gave consistent results for young plumes but showed increased uncertainty as the plume evolved. A better source term for the entire episode studied may be found by assimilating several satellite observations 1 Introduction over the entire period studied. Wilkins et al. (2016a) used The fine-ash fraction (ash particles with diameter < 64 µm) of an insertion method for ash forecasting by initializing a dis- tephra from volcanic eruptions can be transported over large persion model with ash layers derived from retrievals of the distances and cause jet engine malfunction and damages Spinning Enhanced Visible and Infrared Imager (SEVIRI) to airplane windshields (Casadevall, 1994). Both the 2010 on board the Meteosat Second Generation (MSG-2) satellite. April and May Eyjafjallajökull eruption and the May 2011 The study found that the model field calculated by includ- Grimsvötn eruption caused flight delays and cancellations ing up to six satellite observations gave a broader and more leading to economical loss (European Commission, 2011). extensive ash cloud, which compared worse to the satellite Although satellite observations can show snapshots of the in- observation on 8 May at 09:00 UTC than a single satellite re- stantaneous horizontal extension of ash, volcanic ash trans- trieval inserted 6 h before the observation time. The ash cloud port and dispersion models (VATDMs) are needed to fore- found by several retrievals is considered a more conservative cast the dispersion of the volcanic clouds. These models need choice for giving commercial air traffic advice, however, as a robust estimate of source parameters such as ash release it includes ash that may not be captured by a single observa- height, amount of ash released, and ash particle sizes. The tion. combined choice of these source parameters is below named In the previous studies using the inversion method by Stohl the source term. During an eruption, information about the et al. (2011), the a posteriori source terms were calculated af- source term is often limited. Stohl et al. (2011) present an ter the eruption had ceased and using all satellite data avail- inversion method to calculate a source term constrained by able for the entire eruption period. However, in this study satellite observations, using a priori source terms and model more satellite observations will be added gradually to the in- simulations. This inversion technique has been successfully version algorithm to simulate a real forecast scenario. The applied to calculate ash emissions from the Eyjafjallajökull purpose of using the inversion method is to make the model- and Grimsvötn eruptions as well the 2014 Kelut eruption simulated ash with the inversion-derived a posteriori source (Stohl et al., 2011; Kristiansen et al., 2012, 2015; Moxnes term more similar to the observed ash column loads than et al., 2014). The method has also been applied to volcanic model simulations with source terms calculated by empiri- cal plume height relationships like the one given in Mastin eruptions with SO2 emissions (Kristiansen et al. 2010; Eck- hardt et al., 2008). et al. (2009) (used here as a priori source term). The inver- The satellite data, a priori, and model input data required sion algorithm only calculates a constrained source term up by the inversion algorithm all have assumed uncertainties until the start of the forecast, as it requires satellite observa- connected to them that weight their relative contributions to tions. For emissions to be used during the forecast period the inversion results. Both the assumed a priori and satellite there are several possibilities: for example, (1) assume no uncertainties used in the studies mentioned above vary from further emissions, (2) use the latest a priori emission from around 100 % of the input data values down to 0 %, or a min- Mastin et al. (2009), or (3) use the average of the last hours imum value based on the confidence of the a priori source of the a posteriori from the inversion. Assuming the eruption term and satellite data available for the three eruption cases. continues, the third option includes some information from For the Kelut eruption, however, where the eruption reached the satellite observations that may limit the uncertainty of the stratosphere, the a priori source term was highly unreli- using a priori default emission. The use of an average of the able, so the uncertainty was set to 1000 % of the assumed a emission during the last 12 h will be compared here against priori values to make the result be almost exclusively driven zero emissions in the forecast period. by the satellite data. Eckhardt et al. (2008) found small differ- Meteorological clouds that contain ice, supercooled ences between the a posteriori estimates when using a zero or droplets, or unfrozen cloud droplets decrease the ability to a non-zero constant value a priori estimate for the 2007 Jebel identify ash in satellite retrievals or retrieve higher concen- at Tair eruption.
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