ANN-Based Bias Correction Algorithm for Precipitation in the Yarra River Basin, Australia

Regional Climate Models (RCM) applied to simulate future climate parameters such as precipitation and temperature are reported to suffer from bias. Bias correction is necessary for using such data for climate change impact studies. In this study, a new ANN based bias correction algorithm is suggeste...

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Bibliographic Details
Published inTheoretical Computer Science and Discrete Mathematics Vol. 10398; pp. 362 - 370
Main Authors Saravanan, P., Sivapragasam, C., Nitin, M., Balamurali, S., Ragul, R. K., Prakash, S. Sundar, Ganesan, G. Selva, Murugan, V. Vel
Format Book Chapter
LanguageEnglish
Published Switzerland Springer International Publishing AG 2017
Springer International Publishing
SeriesLecture Notes in Computer Science
Subjects
Artificial Neural Network
Bias correction
Climate change projection
Precipitation
Simulation
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Summary:Regional Climate Models (RCM) applied to simulate future climate parameters such as precipitation and temperature are reported to suffer from bias. Bias correction is necessary for using such data for climate change impact studies. In this study, a new ANN based bias correction algorithm is suggested and is compared with other three conventional methods, namely linear scaling, local intensity and power transformation. The proposed method outperforms conventional methods with mean, standard deviation and the RMSE of bias corrected time series more closely matches with that of the observed precipitation.
ISBN:9783319644189
3319644181
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-64419-6_47