Applications of Cluster Analysis and Pattern Recognition for Typhoon Hourly Rainfall Forecast

Joint Authors

Lin, Fu-Ru
Wu, Nan-Jing
Tsay, Ting-Kuei

Source

Advances in Meteorology

Issue

Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-17, 17 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2017-03-21

Country of Publication

Egypt

No. of Pages

17

Main Subjects

Physics

Abstract EN

Based on the factors of meteorology and topography, it is assumed that there exist some certain patterns in spatial and temporal rainfall distribution of a watershed.

A typhoon rainfall forecasting model is developed under this assumption.

If rainfall patterns can be analyzed and recognized in terms of individual watershed topography, only the spatial rainfall distribution prior to a specific moment is needed to forecast the rainfall in the next coming hours.

It does not need any other condition in meteorology and climatology.

Besides, supplement techniques of missing rainfall gage data are also considered to build an all-purpose forecast model.

By integrating techniques of cluster analysis and pattern recognition, present proposed rainfall forecasting model is tested using historical data of Tamsui River Basin in Northern Taiwan.

Good performance is validated by checking on coefficient of correlation and coefficient of efficiency.

American Psychological Association (APA)

Lin, Fu-Ru& Wu, Nan-Jing& Tsay, Ting-Kuei. 2017. Applications of Cluster Analysis and Pattern Recognition for Typhoon Hourly Rainfall Forecast. Advances in Meteorology،Vol. 2017, no. 2017, pp.1-17.
https://search.emarefa.net/detail/BIM-1122717

Modern Language Association (MLA)

Lin, Fu-Ru…[et al.]. Applications of Cluster Analysis and Pattern Recognition for Typhoon Hourly Rainfall Forecast. Advances in Meteorology No. 2017 (2017), pp.1-17.
https://search.emarefa.net/detail/BIM-1122717

American Medical Association (AMA)

Lin, Fu-Ru& Wu, Nan-Jing& Tsay, Ting-Kuei. Applications of Cluster Analysis and Pattern Recognition for Typhoon Hourly Rainfall Forecast. Advances in Meteorology. 2017. Vol. 2017, no. 2017, pp.1-17.
https://search.emarefa.net/detail/BIM-1122717

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1122717