Ensemble dispersion forecasting - Part 1. Concept, approach and indicators

S. Galmarini; R. Bianconi; W. Klug; T. Mikkelsen; R. Addis; S. Andronopoulos; P. Astrup; A. Baklanov; J. Bartniki; J.C. Bartzis; R. Bellasio; F. Bompay; R. Buckley; M. Bouzom; H. Champion; R. D'Amours; E. Davakis; H. Eleveld; G.T. Geertsema; H. Glaab; M. Kollax; M. Ilvonen; A. Manning; U. Pechinger; C. Persson; E. Polreich; S. Potemski; M. Prodanova; J. Saltbones; H. Slaper; M.A. Sofiev; D. Syrakov; J.H. Sørensen; L. Van der Auwera; I. Valkama; R. Zelazny

doi:10.1016/j.atmosenv.2004.05.030

Ensemble dispersion forecasting - Part 1. Concept, approach and indicators

S. Galmarini, R. Bianconi, W. Klug, T. Mikkelsen, R. Addis, S. Andronopoulos, P. Astrup, A. Baklanov, J. Bartniki, J.C. Bartzis, R. Bellasio, F. Bompay, R. Buckley, M. Bouzom, H. Champion, R. D'Amours, E. Davakis, H. Eleveld, G.T. Geertsema, H. GlaabM. Kollax, M. Ilvonen, A. Manning, U. Pechinger, C. Persson, E. Polreich, S. Potemski, M. Prodanova, J. Saltbones, H. Slaper, M.A. Sofiev, D. Syrakov, J.H. Sørensen, L. Van der Auwera, I. Valkama, R. Zelazny

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Abstract

The paper presents an approach to the treatment and analysis of long-range transport and dispersion model forecasts. Long-range is intended here as the space scale of the order of few thousands of kilometers known also as continental scale. The method is called multi-model ensemble dispersion and is based on the simultaneous analysis of several model simulations by means of ad-hoc statistical treatments and parameters. The models considered in this study are operational long-range transport and dispersion models used to support decision making in various countries in case of accidental releases of harmful volatile substances, in particular radionuclides to the atmosphere. The ensemble dispersion approach and indicators provide a way to reduce several model results to few concise representations that include an estimate of the models' agreement in predicting a specific scenario. The parameters proposed are particularly suited for long-range transport and dispersion models although they can also be applied to short-range dispersion and weather fields. (C) 2004 Elsevier Ltd. All rights reserved.

Original language	English
Journal	Atmospheric Environment
Volume	38
Issue number	28
Pages (from-to)	4607-4617
ISSN	1352-2310
DOIs	https://doi.org/10.1016/j.atmosenv.2004.05.030
Publication status	Published - 2004

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Galmarini, S., Bianconi, R., Klug, W., Mikkelsen, T., Addis, R., Andronopoulos, S., Astrup, P., Baklanov, A., Bartniki, J., Bartzis, J. C., Bellasio, R., Bompay, F., Buckley, R., Bouzom, M., Champion, H., D'Amours, R., Davakis, E., Eleveld, H., Geertsema, G. T., ... Zelazny, R. (2004). Ensemble dispersion forecasting - Part 1. Concept, approach and indicators. Atmospheric Environment, 38(28), 4607-4617. https://doi.org/10.1016/j.atmosenv.2004.05.030

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abstract = "The paper presents an approach to the treatment and analysis of long-range transport and dispersion model forecasts. Long-range is intended here as the space scale of the order of few thousands of kilometers known also as continental scale. The method is called multi-model ensemble dispersion and is based on the simultaneous analysis of several model simulations by means of ad-hoc statistical treatments and parameters. The models considered in this study are operational long-range transport and dispersion models used to support decision making in various countries in case of accidental releases of harmful volatile substances, in particular radionuclides to the atmosphere. The ensemble dispersion approach and indicators provide a way to reduce several model results to few concise representations that include an estimate of the models' agreement in predicting a specific scenario. The parameters proposed are particularly suited for long-range transport and dispersion models although they can also be applied to short-range dispersion and weather fields. (C) 2004 Elsevier Ltd. All rights reserved. ",

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author = "S. Galmarini and R. Bianconi and W. Klug and T. Mikkelsen and R. Addis and S. Andronopoulos and P. Astrup and A. Baklanov and J. Bartniki and J.C. Bartzis and R. Bellasio and F. Bompay and R. Buckley and M. Bouzom and H. Champion and R. D'Amours and E. Davakis and H. Eleveld and G.T. Geertsema and H. Glaab and M. Kollax and M. Ilvonen and A. Manning and U. Pechinger and C. Persson and E. Polreich and S. Potemski and M. Prodanova and J. Saltbones and H. Slaper and M.A. Sofiev and D. Syrakov and J.H. S{\o}rensen and Auwera, {L. Van der} and I. Valkama and R. Zelazny",

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doi = "10.1016/j.atmosenv.2004.05.030",

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Galmarini, S, Bianconi, R, Klug, W, Mikkelsen, T, Addis, R, Andronopoulos, S, Astrup, P, Baklanov, A, Bartniki, J, Bartzis, JC, Bellasio, R, Bompay, F, Buckley, R, Bouzom, M, Champion, H, D'Amours, R, Davakis, E, Eleveld, H, Geertsema, GT, Glaab, H, Kollax, M, Ilvonen, M, Manning, A, Pechinger, U, Persson, C, Polreich, E, Potemski, S, Prodanova, M, Saltbones, J, Slaper, H, Sofiev, MA, Syrakov, D, Sørensen, JH, Auwera, LVD, Valkama, I & Zelazny, R 2004, 'Ensemble dispersion forecasting - Part 1. Concept, approach and indicators', Atmospheric Environment, vol. 38, no. 28, pp. 4607-4617. https://doi.org/10.1016/j.atmosenv.2004.05.030

TY - JOUR

T1 - Ensemble dispersion forecasting - Part 1. Concept, approach and indicators

AU - Galmarini, S.

AU - Bianconi, R.

AU - Klug, W.

AU - Mikkelsen, T.

AU - Addis, R.

AU - Andronopoulos, S.

AU - Astrup, P.

AU - Baklanov, A.

AU - Bartniki, J.

AU - Bartzis, J.C.

AU - Bellasio, R.

AU - Bompay, F.

AU - Buckley, R.

AU - Bouzom, M.

AU - Champion, H.

AU - D'Amours, R.

AU - Davakis, E.

AU - Eleveld, H.

AU - Geertsema, G.T.

AU - Glaab, H.

AU - Kollax, M.

AU - Ilvonen, M.

AU - Manning, A.

AU - Pechinger, U.

AU - Persson, C.

AU - Polreich, E.

AU - Potemski, S.

AU - Prodanova, M.

AU - Saltbones, J.

AU - Slaper, H.

AU - Sofiev, M.A.

AU - Syrakov, D.

AU - Sørensen, J.H.

AU - Auwera, L. Van der

AU - Valkama, I.

AU - Zelazny, R.

PY - 2004

Y1 - 2004

N2 - The paper presents an approach to the treatment and analysis of long-range transport and dispersion model forecasts. Long-range is intended here as the space scale of the order of few thousands of kilometers known also as continental scale. The method is called multi-model ensemble dispersion and is based on the simultaneous analysis of several model simulations by means of ad-hoc statistical treatments and parameters. The models considered in this study are operational long-range transport and dispersion models used to support decision making in various countries in case of accidental releases of harmful volatile substances, in particular radionuclides to the atmosphere. The ensemble dispersion approach and indicators provide a way to reduce several model results to few concise representations that include an estimate of the models' agreement in predicting a specific scenario. The parameters proposed are particularly suited for long-range transport and dispersion models although they can also be applied to short-range dispersion and weather fields. (C) 2004 Elsevier Ltd. All rights reserved.

AB - The paper presents an approach to the treatment and analysis of long-range transport and dispersion model forecasts. Long-range is intended here as the space scale of the order of few thousands of kilometers known also as continental scale. The method is called multi-model ensemble dispersion and is based on the simultaneous analysis of several model simulations by means of ad-hoc statistical treatments and parameters. The models considered in this study are operational long-range transport and dispersion models used to support decision making in various countries in case of accidental releases of harmful volatile substances, in particular radionuclides to the atmosphere. The ensemble dispersion approach and indicators provide a way to reduce several model results to few concise representations that include an estimate of the models' agreement in predicting a specific scenario. The parameters proposed are particularly suited for long-range transport and dispersion models although they can also be applied to short-range dispersion and weather fields. (C) 2004 Elsevier Ltd. All rights reserved.

KW - 1-E vind

U2 - 10.1016/j.atmosenv.2004.05.030

DO - 10.1016/j.atmosenv.2004.05.030

M3 - Journal article

SN - 1352-2310

VL - 38

SP - 4607

EP - 4617

JO - Atmospheric Environment

JF - Atmospheric Environment

IS - 28

ER -

Ensemble dispersion forecasting - Part 1. Concept, approach and indicators

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