Imilast: A community effort to intercompare extratropical cyclone detection and tracking algorithms

U Neu; MG Akperov; N Bellenbaum; R Benestad; R Blender; R Caballero; A Cocozza; HF Dacre; Y Feng; K Fraedrich; J Grieger; S Gulev; J Hanley; T Hewson; M Inatsu; K Keay; SF Kew; I Kindem; GC Leckebusch; MLR Liberato; P Lionello; II Mokhov; JG Pinto; CC Raible; M Reale; I Rudeva; M Schuster; I Simmonds; M Sinclair; M Sprenger; ND Tilinina; IF Trigo; S Ulbrich; U Ulbrich; XL Wang; H Wernli

Journal article

Imilast: A community effort to intercompare extratropical cyclone detection and tracking algorithms

U Neu, MG Akperov, N Bellenbaum, R Benestad, R Blender, R Caballero, A Cocozza, HF Dacre, Y Feng, K Fraedrich, J Grieger, S Gulev, J Hanley, T Hewson, M Inatsu, K Keay, SF Kew, I Kindem, GC Leckebusch, MLR Liberato Show all

Bulletin of the American Meteorological Society | Published : 2013

DOI: 10.1175/BAMS-D-11-00154.1

Abstract

The IMILAST intercomparison experiment was initiated involving 15 commonly used detection and tracking algorithms for extratropical cyclones reveals those cyclone characteristics that were robust between different schemes and those that differed considerably. All participating groups computed cyclone tracks for the same period using the same input, such as the European Center for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) dataset on whose results the first activity of the experiment was based. Space-time resolution of the input data had a significant impact on cyclone statistics. The experiment also revealed that high resolution was essential to help capture the..

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University of Melbourne Researchers

Ian Simmonds Author

Grants

Awarded by Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Funding Acknowledgements

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.