Minimum sample size for synoptic weather type classification. Application to winter period data recorded on the catalan coast (North-East Spain)
✍ Scribed by X. Lana; G. Ández Fern Mills
- Publisher
- John Wiley and Sons
- Year
- 1994
- Tongue
- English
- Weight
- 579 KB
- Volume
- 14
- Category
- Article
- ISSN
- 0899-8418
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✦ Synopsis
Abstract
Characteristics of weather types obtained from a Davis and Kalkstein classification process can depend on a variety of factors. One of them is the number of components retained after principal component analysis (PCA) of the original data. The classification algorithm itself and the number of elements to be classified also play important roles in the final results. The main objective of the present paper is to describe a methodology leading to a deduction of the minimum sample size that must be considered in order to obtain a reliable synoptic weather type classification. Some rules related to the number of factors to be retained after a PCA and the optimal number of groups of our classification procedure are discussed. Finally, the main features of the winter weather types obtained from Barcelona Airport data are briefly presented.