Assessment of Various Rainfall Bias Correction Techniques in Peninsular Malaysia

DOI

10.2991/978-94-6463-014-5_12How to use a DOI?

Keywords

Bias Correction; Quantile Mapping; Delta Method; Quantile Delta Mapping; General Circulation Model

Abstract

Climate impact assessment models can have outputs that are sensitive to biases on the local scale. Hence, bias correction methods are used to amend the distribution of the climate impact assessment model in order to match the local observations. A great deal of errors can be removed from the model after bias correction is applied. This study focuses on identifying the best bias correction method after applying it on the observed rainfall data over Peninsular Malaysia. The bias correction methods used in this study includes the quantile mapping method, the delta method and the quantile delta mapping method. The rainfall data of 15 rainfall stations were obtained from the Malaysian Meteorological Department, whereas the General Circulation Model data used follows the CNRM-CM5 model. The quantile mapping method is well-known for seasonal forecasting which has grown extensively due to its broad use in correcting climatological biases in studies projecting future climate change. The delta method uses observations as a basis and is a stable and robust method that produces future time series with dynamics similar to current conditions, but it does not take into account the potential future changes in climate dynamics. The quantile delta mapping method is a break from other typical quantile mapping methods whereby it is not constrained by stationary assumptions. The results show that the quantile mapping method is the best bias correction method among the three methods used in this study.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yashotha Satianesan
AU  - Wei Lun Tan
AU  - Lloyd Ling
PY  - 2022
DA  - 2022/12/12
TI  - Assessment of Various Rainfall Bias Correction Techniques in Peninsular Malaysia
BT  - Proceedings of the International Conference on Mathematical Sciences and Statistics 2022 (ICMSS 2022)
PB  - Atlantis Press
SP  - 114
EP  - 129
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-014-5_12
DO  - 10.2991/978-94-6463-014-5_12
ID  - Satianesan2022
ER  -