IMILAST: A Community Effort to Intercompare Extratropical Cyclone Detection and Tracking Algorithms

Urs Neu; Mirseid G. Akperov; Nina Bellenbaum; Rasmus Benestad; Richard Blender; Rodrigo Caballero; Angela Cocozza; Helen F. Dacre; Yang Feng; Klaus Fraedrich; Jens Grieger; Sergey Gulev; John Hanley; Tim Hewson; Masaru Inatsu; Kevin Keay; Sarah F. Kew; Ina Kindem; Gregor C. Leckebusch; Margarida L. R. Liberato; Piero Lionello; Igor I. Mokhov; Joaquim G. Pinto; Christoph C. Raible; Marco Reale; Irina Rudeva; Mareike Schuster; Ian Simmonds; Mark Sinclair; Michael Sprenger; Natalia D. Tilinina; Isabel F. Trigo; Sven Ulbrich; Uwe Ulbrich; Xiaolan L. Wang; Heini Wernli

doi:10.1175/BAMS-D-11-00154.1

IMILAST: A Community Effort to Intercompare Extratropical Cyclone Detection and Tracking Algorithms

Urs Neu^*, Mirseid G. Akperov, Nina Bellenbaum, Rasmus Benestad, Richard Blender, Rodrigo Caballero, Angela Cocozza, Helen F. Dacre, Yang Feng, Klaus Fraedrich, Jens Grieger, Sergey Gulev, John Hanley, Tim Hewson, Masaru Inatsu, Kevin Keay, Sarah F. Kew, Ina Kindem, Gregor C. Leckebusch, Margarida L. R. LiberatoPiero Lionello, Igor I. Mokhov, Joaquim G. Pinto, Christoph C. Raible, Marco Reale, Irina Rudeva, Mareike Schuster, Ian Simmonds, Mark Sinclair, Michael Sprenger, Natalia D. Tilinina, Isabel F. Trigo, Sven Ulbrich, Uwe Ulbrich, Xiaolan L. Wang, Heini Wernli

^*Corresponding author for this work

Earth and Environmental Sciences

Research output: Contribution to journal › Article › peer-review

280 Citations (Scopus)

Abstract

The variability of results from different automated methods of detection and tracking of extratropical cyclones is assessed in order to identify uncertainties related to the choice of method. Fifteen international teams applied their own algorithms to the same dataset—the period 1989–2009 of interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERAInterim) data. This experiment is part of the community project Intercomparison of Mid Latitude Storm Diagnostics (IMILAST; see www.proclim.ch/imilast/index.html). The spread of results for cyclone frequency, intensity, life cycle, and track location is presented to illustrate the impact of using different methods. Globally, methods agree well for geographical distribution in large oceanic regions, interannual variability of cyclone numbers, geographical patterns of strong trends, and distribution shape for many life cycle characteristics. In contrast, the largest disparities exist for the total numbers of cyclones, the detection of weak cyclones, and distribution in some densely populated regions. Consistency between methods is better for strong cyclones than for shallow ones. Two case studies of relatively large, intense cyclones reveal that the identification of the most intense part of the life cycle of these events is robust between methods, but considerable differences exist during the development and the dissolution phases.

Original language	English
Pages (from-to)	529-547
Number of pages	19
Journal	Bulletin of the American Meteorological Society
Volume	94
Issue number	4
DOIs	https://doi.org/10.1175/BAMS-D-11-00154.1
Publication status	Published - 1 Apr 2013

Bibliographical note

Acknowledgments:
We thank Swiss Re for sponsoring the project (coordination office and workshops) and ECWMF for providing the input data of ERA Interim. C. C. Raible is supported by NCCR Climate, funded by the Swiss National Science Foundation. M. L. R. Liberato was supported by the project STORMEx (FCOMP-01-0124- FEDER-019524), funded by FCT and cofunded by FEDER. N. Bellenbaum, J. G. Pinto, and S. Ulbrich thank AON Benfield Impact Forecasting for support over the EUWS project. J. Grieger and M. Schuster are supported by the DFG project SACAI (DFG-LE1865/1–3). M. G. Akperov and I. I. Mokhov are supported by the Russian Ministry of Education and Science (11.519.11.5004). We appreciate the lead authorship of C. C. Raible, S. Gulev, J. G. Pinto, G. C. Leckebusch, and X. L. Wang, respectively, for the different analysis sections of this paper.

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10.1175/BAMS-D-11-00154.1

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Neu, U., Akperov, M. G., Bellenbaum, N., Benestad, R., Blender, R., Caballero, R., Cocozza, A., Dacre, H. F., Feng, Y., Fraedrich, K., Grieger, J., Gulev, S., Hanley, J., Hewson, T., Inatsu, M., Keay, K., Kew, S. F., Kindem, I., Leckebusch, G. C., ... Wernli, H. (2013). IMILAST: A Community Effort to Intercompare Extratropical Cyclone Detection and Tracking Algorithms. Bulletin of the American Meteorological Society, 94(4), 529-547. https://doi.org/10.1175/BAMS-D-11-00154.1

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title = "IMILAST: A Community Effort to Intercompare Extratropical Cyclone Detection and Tracking Algorithms",

abstract = "The variability of results from different automated methods of detection and tracking of extratropical cyclones is assessed in order to identify uncertainties related to the choice of method. Fifteen international teams applied their own algorithms to the same dataset—the period 1989–2009 of interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERAInterim) data. This experiment is part of the community project Intercomparison of Mid Latitude Storm Diagnostics (IMILAST; see www.proclim.ch/imilast/index.html). The spread of results for cyclone frequency, intensity, life cycle, and track location is presented to illustrate the impact of using different methods. Globally, methods agree well for geographical distribution in large oceanic regions, interannual variability of cyclone numbers, geographical patterns of strong trends, and distribution shape for many life cycle characteristics. In contrast, the largest disparities exist for the total numbers of cyclones, the detection of weak cyclones, and distribution in some densely populated regions. Consistency between methods is better for strong cyclones than for shallow ones. Two case studies of relatively large, intense cyclones reveal that the identification of the most intense part of the life cycle of these events is robust between methods, but considerable differences exist during the development and the dissolution phases.",

author = "Urs Neu and Akperov, {Mirseid G.} and Nina Bellenbaum and Rasmus Benestad and Richard Blender and Rodrigo Caballero and Angela Cocozza and Dacre, {Helen F.} and Yang Feng and Klaus Fraedrich and Jens Grieger and Sergey Gulev and John Hanley and Tim Hewson and Masaru Inatsu and Kevin Keay and Kew, {Sarah F.} and Ina Kindem and Leckebusch, {Gregor C.} and Liberato, {Margarida L. R.} and Piero Lionello and Mokhov, {Igor I.} and Pinto, {Joaquim G.} and Raible, {Christoph C.} and Marco Reale and Irina Rudeva and Mareike Schuster and Ian Simmonds and Mark Sinclair and Michael Sprenger and Tilinina, {Natalia D.} and Trigo, {Isabel F.} and Sven Ulbrich and Uwe Ulbrich and Wang, {Xiaolan L.} and Heini Wernli",

note = "Acknowledgments: We thank Swiss Re for sponsoring the project (coordination office and workshops) and ECWMF for providing the input data of ERA Interim. C. C. Raible is supported by NCCR Climate, funded by the Swiss National Science Foundation. M. L. R. Liberato was supported by the project STORMEx (FCOMP-01-0124- FEDER-019524), funded by FCT and cofunded by FEDER. N. Bellenbaum, J. G. Pinto, and S. Ulbrich thank AON Benfield Impact Forecasting for support over the EUWS project. J. Grieger and M. Schuster are supported by the DFG project SACAI (DFG-LE1865/1–3). M. G. Akperov and I. I. Mokhov are supported by the Russian Ministry of Education and Science (11.519.11.5004). We appreciate the lead authorship of C. C. Raible, S. Gulev, J. G. Pinto, G. C. Leckebusch, and X. L. Wang, respectively, for the different analysis sections of this paper.",

year = "2013",

month = apr,

day = "1",

doi = "10.1175/BAMS-D-11-00154.1",

language = "English",

volume = "94",

pages = "529--547",

journal = "Bulletin of the American Meteorological Society",

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Neu, U, Akperov, MG, Bellenbaum, N, Benestad, R, Blender, R, Caballero, R, Cocozza, A, Dacre, HF, Feng, Y, Fraedrich, K, Grieger, J, Gulev, S, Hanley, J, Hewson, T, Inatsu, M, Keay, K, Kew, SF, Kindem, I, Leckebusch, GC, Liberato, MLR, Lionello, P, Mokhov, II, Pinto, JG, Raible, CC, Reale, M, Rudeva, I, Schuster, M, Simmonds, I, Sinclair, M, Sprenger, M, Tilinina, ND, Trigo, IF, Ulbrich, S, Ulbrich, U, Wang, XL & Wernli, H 2013, 'IMILAST: A Community Effort to Intercompare Extratropical Cyclone Detection and Tracking Algorithms', Bulletin of the American Meteorological Society, vol. 94, no. 4, pp. 529-547. https://doi.org/10.1175/BAMS-D-11-00154.1

TY - JOUR

T1 - IMILAST

T2 - A Community Effort to Intercompare Extratropical Cyclone Detection and Tracking Algorithms

AU - Neu, Urs

AU - Akperov, Mirseid G.

AU - Bellenbaum, Nina

AU - Benestad, Rasmus

AU - Blender, Richard

AU - Caballero, Rodrigo

AU - Cocozza, Angela

AU - Dacre, Helen F.

AU - Feng, Yang

AU - Fraedrich, Klaus

AU - Grieger, Jens

AU - Gulev, Sergey

AU - Hanley, John

AU - Hewson, Tim

AU - Inatsu, Masaru

AU - Keay, Kevin

AU - Kew, Sarah F.

AU - Kindem, Ina

AU - Leckebusch, Gregor C.

AU - Liberato, Margarida L. R.

AU - Lionello, Piero

AU - Mokhov, Igor I.

AU - Pinto, Joaquim G.

AU - Raible, Christoph C.

AU - Reale, Marco

AU - Rudeva, Irina

AU - Schuster, Mareike

AU - Simmonds, Ian

AU - Sinclair, Mark

AU - Sprenger, Michael

AU - Tilinina, Natalia D.

AU - Trigo, Isabel F.

AU - Ulbrich, Sven

AU - Ulbrich, Uwe

AU - Wang, Xiaolan L.

AU - Wernli, Heini

N1 - Acknowledgments: We thank Swiss Re for sponsoring the project (coordination office and workshops) and ECWMF for providing the input data of ERA Interim. C. C. Raible is supported by NCCR Climate, funded by the Swiss National Science Foundation. M. L. R. Liberato was supported by the project STORMEx (FCOMP-01-0124- FEDER-019524), funded by FCT and cofunded by FEDER. N. Bellenbaum, J. G. Pinto, and S. Ulbrich thank AON Benfield Impact Forecasting for support over the EUWS project. J. Grieger and M. Schuster are supported by the DFG project SACAI (DFG-LE1865/1–3). M. G. Akperov and I. I. Mokhov are supported by the Russian Ministry of Education and Science (11.519.11.5004). We appreciate the lead authorship of C. C. Raible, S. Gulev, J. G. Pinto, G. C. Leckebusch, and X. L. Wang, respectively, for the different analysis sections of this paper.

PY - 2013/4/1

Y1 - 2013/4/1

N2 - The variability of results from different automated methods of detection and tracking of extratropical cyclones is assessed in order to identify uncertainties related to the choice of method. Fifteen international teams applied their own algorithms to the same dataset—the period 1989–2009 of interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERAInterim) data. This experiment is part of the community project Intercomparison of Mid Latitude Storm Diagnostics (IMILAST; see www.proclim.ch/imilast/index.html). The spread of results for cyclone frequency, intensity, life cycle, and track location is presented to illustrate the impact of using different methods. Globally, methods agree well for geographical distribution in large oceanic regions, interannual variability of cyclone numbers, geographical patterns of strong trends, and distribution shape for many life cycle characteristics. In contrast, the largest disparities exist for the total numbers of cyclones, the detection of weak cyclones, and distribution in some densely populated regions. Consistency between methods is better for strong cyclones than for shallow ones. Two case studies of relatively large, intense cyclones reveal that the identification of the most intense part of the life cycle of these events is robust between methods, but considerable differences exist during the development and the dissolution phases.

AB - The variability of results from different automated methods of detection and tracking of extratropical cyclones is assessed in order to identify uncertainties related to the choice of method. Fifteen international teams applied their own algorithms to the same dataset—the period 1989–2009 of interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERAInterim) data. This experiment is part of the community project Intercomparison of Mid Latitude Storm Diagnostics (IMILAST; see www.proclim.ch/imilast/index.html). The spread of results for cyclone frequency, intensity, life cycle, and track location is presented to illustrate the impact of using different methods. Globally, methods agree well for geographical distribution in large oceanic regions, interannual variability of cyclone numbers, geographical patterns of strong trends, and distribution shape for many life cycle characteristics. In contrast, the largest disparities exist for the total numbers of cyclones, the detection of weak cyclones, and distribution in some densely populated regions. Consistency between methods is better for strong cyclones than for shallow ones. Two case studies of relatively large, intense cyclones reveal that the identification of the most intense part of the life cycle of these events is robust between methods, but considerable differences exist during the development and the dissolution phases.

U2 - 10.1175/BAMS-D-11-00154.1

DO - 10.1175/BAMS-D-11-00154.1

M3 - Article

SN - 0003-0007

VL - 94

SP - 529

EP - 547

JO - Bulletin of the American Meteorological Society

JF - Bulletin of the American Meteorological Society

IS - 4

ER -

IMILAST: A Community Effort to Intercompare Extratropical Cyclone Detection and Tracking Algorithms

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