Articles | Volume 23, issue 19
https://doi.org/10.5194/acp-23-12477-2023
https://doi.org/10.5194/acp-23-12477-2023
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

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Cited articles

Arnal, L., Anspoks, L., Manson, S., Neumann, J., Norton, T., Stephens, E., Wolfenden, L., and Cloke, H. L.: “Are we talking just a bit of water out of bank? Or is it Armageddon?” Front line perspectives on transitioning to probabilistic fluvial flood forecasts in England, Geosci. Commun., 3, 203–232, https://doi.org/10.5194/gc-3-203-2020, 2020. a
Beckett, F. M., Witham, C. S., Leadbetter, S. J., Crocker, R., Webster, H. N., Hort, M. C., Jones, A. R., Devenish, B. J. and Thomson, D. J.: Atmospheric dispersion modelling at the London VAAC: A review of developments since the 2010 Eyjafjallajökull volcano ash cloud, Atmosphere, 11, 352, https://doi.org/10.3390/atmos11040352, 2020. a, b
Buehner, M.: Local ensemble transform Kalman filter with cross validation, Mon. Weather Rev., 148, 2265–2282, 2020. a
Buizza, R.: Optimal perturbation time evolution and sensitivity of ensemble prediction to perturbation amplitude, Q. J. Roy. Meteor. Soc., 121, 1705–1738, 1995. a
Buizza, R. and Palmer, T. N.: The singular vector structure of the atmospheric general circulation, J. Atmos. Sci. 52, 1434–1456, 1995. a, b
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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.
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