Using naive Bayes classifier for classification of convective rainfall intensities based on spectral characteristics retrieved from SEVIRI

Journal of Earth system science

Mourad Lazri1¹  Soltane Ameur1¹  Slimane Hameg1¹ 

[1] Laboratoire Lampa, University Mouloud Mammeri, Tizi Ouzou, Algeria.$$

关键词: Convective cloud;    SEVIRI;    weather radar;    naive Bayes classifier;   

DOI  :  

学科分类：天文学(综合)

来源: Indian Academy of Sciences

【 摘 要 】

This paper presents a new algorithm to classify convective clouds and determine their intensity, based oncloud physical properties retrieved from the Spinning Enhanced Visible and Infrared Imager (SEVIRI).The convective rainfall events at 15 min, 4 × 5 km spatial resolution from 2006 to 2012 are analysed overnorthern Algeria. The convective rain classification methodology makes use of the relationship betweencloud spectral characteristics and cloud physical properties such as cloud water path (CWP), cloudphase (CP) and cloud top height (CTH). For this classification, a statistical method based on ‘naiveBayes classifier’ is applied. This is a simple probabilistic classifier based on applying ‘Bayes’ theoremwith strong (naive) independent assumptions. For a 9-month period, the ability of SEVIRI to classifythe rainfall intensity in the convective clouds is evaluated using weather radar over the northern Algeria.The results indicate an encouraging performance of the new algorithm for intensity differentiation ofconvective clouds using SEVIRI data.

【 授权许可】

Unknown