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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Published in | Theoretical Computer Science and Discrete Mathematics Vol. 10398; pp. 362 - 370 |
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Main Authors | , , , , , , , |
Format | Book Chapter |
Language | English |
Published |
Switzerland
Springer International Publishing AG
2017
Springer International Publishing |
Series | Lecture Notes in Computer Science |
Subjects | |
Online Access | Get full text |
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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. |
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ISBN: | 9783319644189 3319644181 |
ISSN: | 0302-9743 1611-3349 |
DOI: | 10.1007/978-3-319-64419-6_47 |