# Ensemble simulation for Ubinas (2019) ## Fix column height ### General configuration - Start time: 19 July 2019, 07:00 UTC - End time: 21 July 2019, 00:00 UTC - Meteo data: ERA-5 (model levels) - Domain size: 600x400x60 - Species: Tephra ### Source: - Column height: 4 km avl (fixed) - Type: TOP-HAT - Start time: 19 July 2019, 07:00 UTC - End time: 19 July 2019, 18:00 UTC - Start time: 19 July 2019, 07:00 UTC - MFR: ESTIMATE-DEGRUYTER - Thickness: 1 km - Maximum particle size: 12 $\mu m$ - Granulometry file: ``` 0.011049 2300.0 0.900 0.296800505E-01 1 1 tephra fine_ash-06 T 0.007812 2300.0 0.900 0.163989677E-01 1 1 tephra fine_ash-07 T 0.005524 2300.0 0.900 0.806730489E-02 1 1 tephra fine_ash-08 T 0.003906 2300.0 0.900 0.353518749E-02 1 1 tephra fine_ash-09 T 0.002762 2300.0 0.900 0.137613813E-02 1 1 tephra fine_ash-10 T 0.001953 2300.0 0.900 0.679610383E-03 1 1 tephra fine_ash-11 T ``` ### Ensemble: - Column height perturbation: - Perturbation type: Relative (35%) - PDF: Uniform - Wind perturbation: - Perturbation type: Relative (20%) - PDF: Uniform ### Results: Probability *Snapshot:* ![](https://i.imgur.com/lNVpojV.png) *Video:* <iframe src="https://drive.google.com/file/d/1InvdAw0dTiRrbbkyQCHUXk4EfAECehKp/preview" width="640" height="480"></iframe> ### Results: Statistical estimators for column mass Possible estimators: 1. Ensemble median ($x_1$) 1. Ensemble mean ($x_2$) 1. Minimal distance ($x_3$) Typically, we have a very positively skewed distribution. In the next figure, very high values of the skewness are found in most of cases, except when the ensemble mean-to-spread ratio is greater than 1. In consequence, $x_1 \ll x_2$ for most of grid elements. ![](https://i.imgur.com/6c686FP.png) For the minimal distance estimator ($x_3$), we use the solution corresponding to the ensemble member which minimizes the distance: $$ \min_i \sqrt{(x_i - \overline x)^2 + (y_i - \overline y)^2} $$ where $x_i,y_i$ are the coordinates of the center of mass for the ensemble member $i$, and $\overline x,\overline y$ are the averaged coordinates of the center of mass. Conclusions: - Ensemble median: significantly underestimates column mass - Ensemble mean: too diffusive - Minimal distance: It has the advantage of being a physical solution. Members with large MFR/Column height do not have a greater weight (as $x_1$ and $x_2$). *Snapshot:* The paths of the center of mass are represented by red lines. ![](https://i.imgur.com/6efZnqQ.png) *Video:* <iframe src="https://drive.google.com/file/d/1gp2aWpbYKYYz-OJAnjaJzI3ZSvSyhMn8/preview" width="640" height="480"></iframe> ## Variable column height Column height timeseries: ![](https://i.imgur.com/rMz7Hq3.png) ### Ensemble: - Column height perturbation: - Perturbation type: Relative (35%) - PDF: Uniform - Wind perturbation: - Perturbation type: Relative (20%) - PDF: Uniform ### Results: Probability *Snapshot:* ![](https://i.imgur.com/KZYAwfi.png) *Video:* <iframe src="https://drive.google.com/file/d/11OsA6h8-GnoHPxTVRflm7g7uvJqkCJ-c/preview" width="640" height="480"></iframe> ### Results: Statistical estimators for column mass *Snapshot:* ![](https://i.imgur.com/ggHEwJD.png) *Video:* <iframe src="https://drive.google.com/file/d/1RBwPETYkkIvZCa0a9OeyNLvfjezlcBSa/preview" width="640" height="480"></iframe>