Using synthetic case studies to explore the spread and calibration of ensemble atmospheric dispersion forecasts

Jones, Andrew R.; Leadbetter, Susan J.; Hort, Matthew C.

doi:https://doi.org/10.5194/acp-23-12477-2023

Articles | Volume 23, issue 19

https://doi.org/10.5194/acp-23-12477-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-23-12477-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 23, issue 19

Research article

|

09 Oct 2023

Research article |

| 09 Oct 2023

Using synthetic case studies to explore the spread and calibration of ensemble atmospheric dispersion forecasts

Andrew R. Jones, Susan J. Leadbetter, and Matthew C. Hort

Supplement

https://doi.org/10.5194/acp-23-12477-2023-supplement

Data sets

Hypothetical ensemble dispersion model runs with statistical verification S. Leadbetter and A. Jones https://doi.org/10.5281/zenodo.4770066

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Short summary

The paper explores spread and calibration properties of ensemble atmospheric dispersion forecasts for hypothetical release events. Real-time forecasts from an ensemble weather prediction system were used to generate an ensemble of dispersion predictions and assessed against simulations produced using analysis meteorology. Results demonstrate good performance overall but highlight more skilful predictions for material released in the upper air compared with releases near the surface.