Details

Autor(en) / Beteiligte

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

Titel

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

Ist Teil von

• Bulletin of the American Meteorological Society, 2013-04, Vol.94 (4), p.529-547

Ort / Verlag

Boston: American Meteorological Society

Erscheinungsjahr

2013

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• 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.