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

Research output: Contribution to journalArticlepeer-review

280 Citations (Scopus)


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 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 languageEnglish
Pages (from-to)529-547
Number of pages19
JournalBulletin of the American Meteorological Society
Issue number4
Publication statusPublished - 1 Apr 2013

Bibliographical note

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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