IMILAST: A Community Effort to Intercompare Extratropical Cyclone Detection and Tracking Algorithms
IMILAST: A Community Effort to Intercompare Extratropical Cyclone Detection and Tracking Algorithms
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DOI：
10.1175/bams-d-11-00154.1
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发表时间：
2013-04
影响因子：
8
通讯作者：
U. Neu;M. G. Akperov;Nina Bellenbaum;R. Benestad;R. Blender;R. Caballero;A. Cocozza;H. Dacre;Yang Feng;K. Fraedrich;J. Grieger;S. Gulev;J. Hanley;T. Hewson;M. Inatsu;K. Keay;S. Kew;I. Kindem;G. Leckebusch;M. Liberato;P. Lionello;I. Mokhov;J. Pinto;C. Raible;M. Reale;I. Rudeva;M. Schuster;I. Simmonds;M. Sinclair;M. Sprenger;N. Tilinina;I. Trigo;S. Ulbrich;U. Ulbrich;Xiaolan L. Wang;H. Wernli
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文献类型：
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作者：
U. Neu;M. G. Akperov;Nina Bellenbaum;R. Benestad;R. Blender;R. Caballero;A. Cocozza;H. Dacre;Yang Feng;K. Fraedrich;J. Grieger;S. Gulev;J. Hanley;T. Hewson;M. Inatsu;K. Keay;S. Kew;I. Kindem;G. Leckebusch;M. Liberato;P. Lionello;I. Mokhov;J. Pinto;C. Raible;M. Reale;I. Rudeva;M. Schuster;I. Simmonds;M. Sinclair;M. Sprenger;N. Tilinina;I. Trigo;S. Ulbrich;U. Ulbrich;Xiaolan L. Wang;H. Wernli
对温带气旋的不同自动检测和跟踪方法的结果的可变性进行评估，以确定与方法选择相关的不确定性。 15 个国际团队将他们自己的算法应用于同一数据集，即 1989 年至 2009 年欧洲中期天气预报中心 (ECMWF) 重新分析 (ERAInterim) 临时数据。该实验是社区项目中纬度风暴诊断比较（IMILAST；参见 www.proclim.ch/imilast/index.html）的一部分。展示了气旋频率、强度、生命周期和轨迹位置的结果分布，以说明使用不同方法的影响。在全球范围内，这些方法对于大洋区域的地理分布、气旋数量的年际变化、强趋势的地理模式以及许多生命周期特征的分布形状非常吻合。相比之下，气旋总数、弱气旋的检测以及一些人口稠密地区的分布存在最大差异。强旋风分离器的方法之间的一致性比浅旋风分离器更好。两个相对较大、强烈的气旋的案例研究表明，对这些事件生命周期中最强烈部分的识别在不同方法之间是可靠的，但在发展和溶解阶段存在相当大的差异。
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.