Development and comparison of circulation type classifications using the COST 733 dataset and software

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378289%3A_____%2F16%3A00432101" target="_blank" >RIV/68378289:_____/16:00432101 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11310/16:10328679

Výsledek na webu

<a href="http://dx.doi.org/10.1002/joc.3920" target="_blank" >http://dx.doi.org/10.1002/joc.3920</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/joc.3920" target="_blank" >10.1002/joc.3920</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Development and comparison of circulation type classifications using the COST 733 dataset and software

Popis výsledku v původním jazyce

In order to examine correspondence between different methods for circulation type classification, a dataset of classification catalogs for 12 different European regions has been created using a specially developed software package. Twenty-seven basic automatic classification methods have been applied in several variants to different input datasets describing atmospheric circulation. Together with six manual classifications a total of 33 methods are available for inter-comparison. Pattern correlation, frequency time-series correlation and the adjusted Rand index have been used for comparison. Highly significant correspondence has been detected only for two clustering techniques while the remaining classification methods show surprisingly low similarity. A Monte-Carlo test with 1000 classifications of randomly defined types even shows that most of the methods are not more similar among each other than any arbitrarily chosen types. The predominant dissimilarity between the methods is interpreted to be a result of a lack of inherent structures of the input data. Only simulated annealing clustering and self-organizing maps get nearly identical results because they can optimally fit the partitioning to the outer shape of the data cloud in the phase space. Also methods based on pre-defined types come to very different results because small changes in the definition of thresholds may lead to large differences in the partitioning. It is concluded that because of the missing inner structure of the data there is no clear statistical reason to prefer any of the examined methods. For practice in synoptic climatology this means that finding a suited classification for a certain purpose may require a broad comparison of methods. The software package cost733class for development, comparison and evaluation of classifications which was developed and used in this study is available at to facilitate this task.

Název v anglickém jazyce

Development and comparison of circulation type classifications using the COST 733 dataset and software

Popis výsledku anglicky

In order to examine correspondence between different methods for circulation type classification, a dataset of classification catalogs for 12 different European regions has been created using a specially developed software package. Twenty-seven basic automatic classification methods have been applied in several variants to different input datasets describing atmospheric circulation. Together with six manual classifications a total of 33 methods are available for inter-comparison. Pattern correlation, frequency time-series correlation and the adjusted Rand index have been used for comparison. Highly significant correspondence has been detected only for two clustering techniques while the remaining classification methods show surprisingly low similarity. A Monte-Carlo test with 1000 classifications of randomly defined types even shows that most of the methods are not more similar among each other than any arbitrarily chosen types. The predominant dissimilarity between the methods is interpreted to be a result of a lack of inherent structures of the input data. Only simulated annealing clustering and self-organizing maps get nearly identical results because they can optimally fit the partitioning to the outer shape of the data cloud in the phase space. Also methods based on pre-defined types come to very different results because small changes in the definition of thresholds may lead to large differences in the partitioning. It is concluded that because of the missing inner structure of the data there is no clear statistical reason to prefer any of the examined methods. For practice in synoptic climatology this means that finding a suited classification for a certain purpose may require a broad comparison of methods. The software package cost733class for development, comparison and evaluation of classifications which was developed and used in this study is available at to facilitate this task.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

DG - Vědy o atmosféře, meteorologie

OECD FORD obor

—

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

International Journal of Climatology

ISSN

0899-8418

e-ISSN

—

Svazek periodika

36

Číslo periodika v rámci svazku

7

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

19

Strana od-do

2673-2691

Kód UT WoS článku

000377276300002

EID výsledku v databázi Scopus

2-s2.0-84895141784