Reconstructing the Emission Height of Volcanic SO2 from Back Trajectories: Comparison of Explosive and Effusive Eruptions Modeling trace gas transport.

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Reconstructing the Emission Height of Volcanic SO2 from Back Trajectories: Comparison of Explosive and Effusive Eruptions Modeling trace gas transport can yield important information about both the injection height and time of gases into the atmosphere. When applied to volcanic emissions, transport modeling can yield valuable information about the time evolution of the eruption and how the emission height varies during the eruption period. Knowing the evolution of a volcanic cloud’s emission height can yield insights to volcanic eruption dynamics, and is also crucial for volcanic cloud forecasting. In this presentation, SO2 measurements from the Ozone Monitoring Instrument (OMI) are used to infer an injection height timeseries from two very different eruptions: the 2008 eruption of Kasatochi (an explosive eruption lasting over several hours) and the 2006 eruption of Nyamuragira (an effusive eruption lasting over several days). Statistical analyses based on the distance of closest approach to the volcano of back trajectories initialized at the measurements are used to derive the emission height timeseries for both eruptions. These transport-derived SO2 heights are then compared to the results obtained from the Iterative Spectral Fitting (ISF) algorithm, a radiative method to resolve the height of SO2 plumes. While volcanic SO2 transport modeling is the main focus of this work, we also explore the possibility and challenges involved in volcanic ash transport modeling. Nyamuragira (2006) Eruption Type: Effusive Duration: 11/ /04 Kasatochi (2008) Eruption Type: Explosive Duration: 08/ /09 Transport Modeling Trajectory Initialization:  At locations of OMI SO 2 observations  6 vertically stacked parcels at different vertical locations for each SO2 measurement.  Driven Backwards in time. Trajectories that were initialized at the correct height should arrive at the volcano. The Trajectory Transport Test: A trajectory has successfully described the transport of an SO2 measurement if it arrives within some minimum distance of the volcano. r*( ,t*) - The Distance of Closest Approach  - the theta height of that trajectory t* - is the time of closest approach P(  | t*) P(t*) [ Dec 2 nd ] We want the joint Probability P( ,t*) Using Bayes’ theorem, the joint probability P( ,t*) can be found: P( ,t*) = P(  |t*)P(t*) P( ,t*) - the probability that SO2 was emitted at time t* and height . From the daily trajectory ensemble, derive two PDFs: P(t*) – Probability of SO 2 emission from the volcano at time t* for any height . P(  |t*) – Probability of SO 2 emission from the volcano at height , for a given time t*. [ Distance of Closest Approach ] [ Overview ] [ PDFs of Volcanic Activity ] OMI SO2: Column Measurements of SO2 Comparison with the EISF height Retrievals A Record of Volcanic Activity from Trajectory PDFs Volcanic Eruptions Kasatochi Nyamuragira EISF Height Retrieval Period of Volcanic Activity (approx.) Comparison with the EISF (cont’d) A trajectory must arrive within a minimum distance, R, from the volcano: r*( ,t*) < R Condition for successful arrival at the volcano. [ The Trajectory Ensemble ] Building the Trajectory Ensemble: -> Read in OMI Data for a single day -> Select a subset of high SO2 Measurements -> Initialize Trajectories -> Retrieve the subset of trajectories where: r*( ,t*) < R Is could be argued that the fact that a back trajectory gets close to the volcano at some point is not by itself evidence of a correct path? - a parcel might take a path that is clearly not along the path emissions are observed to take. Track OMI observations made on a series of successive days. The PDFs for the full ensemble are derived as a linear combination of the PDFs for each individual day, weighted by the total number of trajectories in that PDF: N t - the total number of trajectories used to construct the PDFs on day T. * Here the sum is run from day 334 (Nov. 30th) to day 341 (Dec. 6th) Kasatochi Nyamuragira P( ,t*) - The SO2 injection height profiles for Kasatochi (upper) and Nyamuragira (lower). Kasatochi: Eruptions lasts ~ 2 days 219 (Dec. 7th) -> 221 (Dec 9th) Most SO2 injection to the 200mb surface with some at 300mb Nyamuragira: Eruptions lasts ~ 6 days 331 (Nov. 27th) -> 336 (Dec 3th) Most SO2 injection to the theta surface followed by a decay down to the 330 surface. Trajectory Derived EISF Derived The Trajectory (left) based Height PDF, derived by collapsing the time dimension in P( ,t). The EISF (right) based PDF, derived by summing the height retrievals for August 8th, 9th, and 10th. Trajectory PDF: Two peaks at heights 12km and 9.5 km EISF PDF: Most SO2 between 11.5km and 9km with two smaller peaks at 10.5 km and 9.5 km EISF Height Retrieval (Dec. 2nd) Forward Trajectory Reconstruction (Dec. 2nd) A Forward Trajectory Reconstruction (left) of the eruption was simulated for Dec. 2nd, based on the derived SO2 emission profile. This is compared to the EISF height retrieval (right) for the same day. - Both the Trajectory Reconstruction and EISF retrieval show similar a similar height structure. The cloud altitude increases with decreasing latitude, followed by a sharp decrease in cloud altitude. - However, the estimated altitudes between the two methods are significantly different. The trajectory based heights are about 6km higher than those computed from the EISF retrieval. The Extended Iterative Spectral Fitting (EISF) Algorithm - SO2 plumes perturbs the top-of-atmosphere solar backscattered ultraviolet radiance. - Perturbations vary depending the SO2 amount and height - Adjust the SO2 height and amount (as well as other parameters) until the difference between the forward model calculations and measured radiance are minimized Conclusions Visual representation of the PDFs derived from OMI measurements from Dec. 2nd 2006 (Nyamuragira) Combining the trajectory PDFs from different days has the effect of re-sampling the same air parcel along its path so that those trajectories which actually follow the SO2 plume back to the volcano reinforce each other in the total ensemble and so contribute most to the statistical ensemble. The trajectory arrival times (in arrival day) at the volcano for OMI measurements on Dec. 4th In this case, the measurements observed on Dec. 4th will have been observed on previous days. The measurements from Dec. 4th resample SO2 observed on previous days and provide overlapping trajectory information. E. J. Hughes 2 ; L. C. Sparling 1 ; S. A. Carn 3 ; A. J. Krueger 2 ; K. Yang 4 ; S. G. Trahan 1 1. Physics, University of Maryland, Baltimore County, Baltimore, MD, USA. 2. Joint Center for Earth Systems Technology, University of Maryland, Baltimore County, Baltimore, MD, USA. 3. Geological and Mining Engineering and Sciences, Michigan Technological University, Houghton, MI, USA. 4. Goddard Earth Sciences and Technology Center, University of Maryland, Baltimore County, Baltimore, MD, USA. r* 360 K 350 K Nov. 28 Nov. 29 Nov. 30 Dec. 1 Dec. 2 Dec. 3 Dec. 4 Dec. 5 Dec. 6 Aug. 13 Aug. 12 Aug. 11 Aug. 10 pm Aug. 09 Aug. 08 Aug. 10 am