Preprints
https://doi.org/10.5194/acp-2021-638
https://doi.org/10.5194/acp-2021-638

  16 Aug 2021

16 Aug 2021

Review status: this preprint is currently under review for the journal ACP.

Can we assess the value meteorological ensembles add to dispersion modelling using hypothetical releases?

Susan Janet Leadbetter, Andrew R. Jones, and Matthew C. Hort Susan Janet Leadbetter et al.
  • Met Office, Exeter, EX1 3PB, UK

Abstract. Atmospheric dispersion model output is frequently used to provide advice to decision makers, for example, about the likely location of volcanic ash erupted from a volcano or the location of deposits of radioactive material released during a nuclear accident. Increasingly scientists and decision makers are requesting information on the uncertainty of these dispersion model predictions. One source of uncertainty is in the meteorology used to drive the dispersion model and in this study ensemble meteorology from the Met Office ensemble prediction system is used to provide meteorological uncertainty to dispersion model predictions. Two hypothetical scenarios, one volcanological and one radiological, are repeated every 12 hours over a period of 4 months. The scenarios are simulated using ensemble meteorology and deterministic forecast meteorology and compared to output from simulations using analysis meteorology using the Brier skill score. Adopting the practice commonly used in evaluating numerical weather prediction models (NWP) where observations are sparse or non-existent we consider output from simulations using analysis NWP data to be truth. The results show that on average the ensemble simulations perform better than the deterministic simulations although not all individual ensemble simulations outperform their deterministic counterpart. The results also show that greater skill scores are achieved by the ensemble simulation for later time steps rather than earlier time steps and at those later time steps for deposition than for air concentration. For the volcanic ash scenarios it is shown that the performance of the ensemble at one flight level can be different to that at a different flight level, e.g. a negative skill score might be obtained for FL350-550 and a positive skill score for FL200-350. This study does not take into account any source term uncertainty but it does take the first steps towards demonstrating the value of ensemble dispersion model predictions.

Susan Janet Leadbetter et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2021-638', Anonymous Referee #1, 10 Sep 2021
  • RC2: 'Comment on acp-2021-638', Anonymous Referee #2, 14 Sep 2021
  • RC3: 'Comment on acp-2021-638', Anonymous Referee #3, 14 Sep 2021

Susan Janet Leadbetter et al.

Susan Janet Leadbetter et al.

Viewed

Total article views: 295 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
216 73 6 295 3 2
  • HTML: 216
  • PDF: 73
  • XML: 6
  • Total: 295
  • BibTeX: 3
  • EndNote: 2
Views and downloads (calculated since 16 Aug 2021)
Cumulative views and downloads (calculated since 16 Aug 2021)

Viewed (geographical distribution)

Total article views: 281 (including HTML, PDF, and XML) Thereof 281 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 22 Oct 2021
Download
Short summary
In this study we look at the ability of meteorological ensembles (multiple realisations of the meteorological data) to provide information about the uncertainty in the dispersion model predictions. Statistical measures are used to evaluate the model predictions and these show that on average the ensemble predictions outperform the non-ensemble predictions.
Altmetrics