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contributor authorNeu, Urs
contributor authorAkperov, Mirseid G.
contributor authorBellenbaum, Nina
contributor authorBenestad, Rasmus
contributor authorBlender, Richard
contributor authorCaballero, Rodrigo
contributor authorCocozza, Angela
contributor authorDacre, Helen F.
contributor authorFeng, Yang
contributor authorFraedrich, Klaus
contributor authorGrieger, Jens
contributor authorGulev, Sergey
contributor authorHanley, John
contributor authorHewson, Tim
contributor authorInatsu, Masaru
contributor authorKeay, Kevin
contributor authorKew, Sarah F.
contributor authorKindem, Ina
contributor authorLeckebusch, Gregor C.
contributor authorLiberato, Margarida L. R.
contributor authorLionello, Piero
contributor authorMokhov, Igor I.
contributor authorPinto, Joaquim G.
contributor authorRaible, Christoph C.
contributor authorReale, Marco
contributor authorRudeva, Irina
contributor authorSchuster, Mareike
contributor authorSimmonds, Ian
contributor authorSinclair, Mark
contributor authorSprenger, Michael
contributor authorTilinina, Natalia D.
contributor authorTrigo, Isabel F.
contributor authorUlbrich, Sven
contributor authorUlbrich, Uwe
contributor authorWang, Xiaolan L.
contributor authorWernli, Heini
date accessioned2017-06-09T16:44:03Z
date available2017-06-09T16:44:03Z
date copyright2013/04/01
date issued2012
identifier issn0003-0007
identifier otherams-73183.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4215269
description abstractbility 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.
publisherAmerican Meteorological Society
titleIMILAST: A Community Effort to Intercompare Extratropical Cyclone Detection and Tracking Algorithms
typeJournal Paper
journal volume94
journal issue4
journal titleBulletin of the American Meteorological Society
identifier doi10.1175/BAMS-D-11-00154.1
journal fristpage529
journal lastpage547
treeBulletin of the American Meteorological Society:;2012:;volume( 094 ):;issue: 004
contenttypeFulltext


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