%0 Journal Article %1 Neu2012IMILAST %A Neu, Urs %A Akperov, Mirseid G. %A Bellenbaum, Nina %A Benestad, Rasmus %A Blender, Richard %A Caballero, Rodrigo %A Cocozza, Angela %A Dacre, Helen F. %A Feng, Yang %A Fraedrich, Klaus %A Grieger, Jens %A Gulev, Sergey %A Hanley, John %A Hewson, Tim %A Inatsu, Masaru %A Keay, Kevin %A Kew, Sarah F. %A Kindem, Ina %A Leckebusch, Gregor C. %A Liberato, Margarida L. R. %A Lionello, Piero %A Mokhov, Igor I. %A Pinto, Joaquim G. %A Raible, Christoph C. %A Reale, Marco %A Rudeva, Irina %A Schuster, Mareike %A Simmonds, Ian %A Sinclair, Mark %A Sprenger, Michael %A Tilinina, Natalia D. %A Trigo, Isabel F. %A Ulbrich, Sven %A Ulbrich, Uwe %A Wang, Xiaolan L. %A Wernli, Heini %D 2012 %I American Meteorological Society %J Bull. Amer. Meteor. Soc. %K stormtracks storms review model stormidentification %N 4 %P 529--547 %R 10.1175/bams-d-11-00154.1 %T IMILAST: A Community Effort to Intercompare Extratropical Cyclone Detection and Tracking Algorithms %U http://dx.doi.org/10.1175/bams-d-11-00154.1 %V 94 %X 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.

@article{Neu2012IMILAST, 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.}, added-at = {2018-06-18T21:23:34.000+0200}, author = {Neu, Urs and Akperov, Mirseid G. and Bellenbaum, Nina and Benestad, Rasmus and Blender, Richard and Caballero, Rodrigo and Cocozza, Angela and Dacre, Helen F. and Feng, Yang and Fraedrich, Klaus and Grieger, Jens and Gulev, Sergey and Hanley, John and Hewson, Tim and Inatsu, Masaru and Keay, Kevin and Kew, Sarah F. and Kindem, Ina and Leckebusch, Gregor C. and Liberato, Margarida L. R. and Lionello, Piero and Mokhov, Igor I. and Pinto, Joaquim G. and Raible, Christoph C. and Reale, Marco and Rudeva, Irina and Schuster, Mareike and Simmonds, Ian and Sinclair, Mark and Sprenger, Michael and Tilinina, Natalia D. and Trigo, Isabel F. and Ulbrich, Sven and Ulbrich, Uwe and Wang, Xiaolan L. and Wernli, Heini}, biburl = {https://www.bibsonomy.org/bibtex/2d42f14b611c10d002f4239b511e61719/pbett}, citeulike-article-id = {13760817}, citeulike-linkout-0 = {http://journals.ametsoc.org/doi/abs/10.1175/BAMS-D-11-00154.1}, citeulike-linkout-1 = {http://dx.doi.org/10.1175/bams-d-11-00154.1}, day = 19, doi = {10.1175/bams-d-11-00154.1}, interhash = {727bc83b48972b25ad0d61e3c49e1162}, intrahash = {d42f14b611c10d002f4239b511e61719}, journal = {Bull. Amer. Meteor. Soc.}, keywords = {stormtracks storms review model stormidentification}, month = sep, number = 4, pages = {529--547}, posted-at = {2015-09-10 07:41:11}, priority = {2}, publisher = {American Meteorological Society}, timestamp = {2018-06-22T18:35:16.000+0200}, title = {IMILAST: A Community Effort to Intercompare Extratropical Cyclone Detection and Tracking Algorithms}, url = {http://dx.doi.org/10.1175/bams-d-11-00154.1}, volume = 94, year = 2012 }