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Comparison of Daily Precipitation Bias Correction Methods Based on Four Regional Climate Model Outputs in Ouémé Basin, Benin

Received: 26 November 2016    Accepted: 05 December 2016    Published: 07 January 2017
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Abstract

Precipitation projections from regional climate models in West Africa are attributed with significant biases with respect to the observed. This study aims at evaluating of six methods of precipitation bias correction on four RCM (CCLM, CRCM, RACMO and REMO) outputs in the Ouémé basin. The bias correction methods used are classified into three namely: the Delta approach, the Linear Scaling method and the quantile approaches. Corrected and uncorrected RCM precipitation data were compared with the observed using Mean Absolute Error (MAE) and Root Mean Square error (RMSE). The findings showed that raw outputs of regional climate models (RCMs) are characterized with several biases. In general, the models overestimate precipitation. For daily precipitation correction, the quantile approaches assuming a gamma distribution for daily precipitation were not able to reduce the biases of precipitation. The empirical quantile mapping and the adjusted quantile mapping are the most effective in correcting the biases of daily precipitation. Thus the adjusted quantile mapping can be used to correct biases of precipitation projections for modeling the future availability of water resources.

DOI 10.11648/j.hyd.20160406.11
Published in Hydrology (Volume 4, Issue 6, November 2016)
Page(s) 58-71
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Delta, Linear Scaling, Precipitation, Bias Correction Method, Ouémé, Benin

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Author Information
  • National Polytechnic Institute, Yamoussoukro, C?te d'Ivoire; National Institute of Water, University of Abomey-Calavi, Abomey, Calavi, Benin

  • National Institute of Water, University of Abomey-Calavi, Abomey, Calavi, Benin

  • West African Science Service Centre on Climate Change and Adapted Land Use, University of Abomey-Calavi, Abomey, Calavi, Benin

  • National Polytechnic Institute, Yamoussoukro, C?te d'Ivoire

  • West African Science Service Centre on Climate Change and Adapted Land Use, University of Abomey-Calavi, Abomey, Calavi, Benin

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    Yèkambèssoun N’Tcha M’Po, Agnidé Emmanuel Lawin, Ganiyu Titilope Oyerinde, Benjamin Kouassi Yao, Abel Akambi Afouda. (2017). Comparison of Daily Precipitation Bias Correction Methods Based on Four Regional Climate Model Outputs in Ouémé Basin, Benin. Hydrology, 4(6), 58-71. https://doi.org/10.11648/j.hyd.20160406.11

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    ACS Style

    Yèkambèssoun N’Tcha M’Po; Agnidé Emmanuel Lawin; Ganiyu Titilope Oyerinde; Benjamin Kouassi Yao; Abel Akambi Afouda. Comparison of Daily Precipitation Bias Correction Methods Based on Four Regional Climate Model Outputs in Ouémé Basin, Benin. Hydrology. 2017, 4(6), 58-71. doi: 10.11648/j.hyd.20160406.11

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    AMA Style

    Yèkambèssoun N’Tcha M’Po, Agnidé Emmanuel Lawin, Ganiyu Titilope Oyerinde, Benjamin Kouassi Yao, Abel Akambi Afouda. Comparison of Daily Precipitation Bias Correction Methods Based on Four Regional Climate Model Outputs in Ouémé Basin, Benin. Hydrology. 2017;4(6):58-71. doi: 10.11648/j.hyd.20160406.11

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  • @article{10.11648/j.hyd.20160406.11,
      author = {Yèkambèssoun N’Tcha M’Po and Agnidé Emmanuel Lawin and Ganiyu Titilope Oyerinde and Benjamin Kouassi Yao and Abel Akambi Afouda},
      title = {Comparison of Daily Precipitation Bias Correction Methods Based on Four Regional Climate Model Outputs in Ouémé Basin, Benin},
      journal = {Hydrology},
      volume = {4},
      number = {6},
      pages = {58-71},
      doi = {10.11648/j.hyd.20160406.11},
      url = {https://doi.org/10.11648/j.hyd.20160406.11},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.hyd.20160406.11},
      abstract = {Precipitation projections from regional climate models in West Africa are attributed with significant biases with respect to the observed. This study aims at evaluating of six methods of precipitation bias correction on four RCM (CCLM, CRCM, RACMO and REMO) outputs in the Ouémé basin. The bias correction methods used are classified into three namely: the Delta approach, the Linear Scaling method and the quantile approaches. Corrected and uncorrected RCM precipitation data were compared with the observed using Mean Absolute Error (MAE) and Root Mean Square error (RMSE). The findings showed that raw outputs of regional climate models (RCMs) are characterized with several biases. In general, the models overestimate precipitation. For daily precipitation correction, the quantile approaches assuming a gamma distribution for daily precipitation were not able to reduce the biases of precipitation. The empirical quantile mapping and the adjusted quantile mapping are the most effective in correcting the biases of daily precipitation. Thus the adjusted quantile mapping can be used to correct biases of precipitation projections for modeling the future availability of water resources.},
     year = {2017}
    }
    

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  • TY  - JOUR
    T1  - Comparison of Daily Precipitation Bias Correction Methods Based on Four Regional Climate Model Outputs in Ouémé Basin, Benin
    AU  - Yèkambèssoun N’Tcha M’Po
    AU  - Agnidé Emmanuel Lawin
    AU  - Ganiyu Titilope Oyerinde
    AU  - Benjamin Kouassi Yao
    AU  - Abel Akambi Afouda
    Y1  - 2017/01/07
    PY  - 2017
    N1  - https://doi.org/10.11648/j.hyd.20160406.11
    DO  - 10.11648/j.hyd.20160406.11
    T2  - Hydrology
    JF  - Hydrology
    JO  - Hydrology
    SP  - 58
    EP  - 71
    PB  - Science Publishing Group
    SN  - 2330-7617
    UR  - https://doi.org/10.11648/j.hyd.20160406.11
    AB  - Precipitation projections from regional climate models in West Africa are attributed with significant biases with respect to the observed. This study aims at evaluating of six methods of precipitation bias correction on four RCM (CCLM, CRCM, RACMO and REMO) outputs in the Ouémé basin. The bias correction methods used are classified into three namely: the Delta approach, the Linear Scaling method and the quantile approaches. Corrected and uncorrected RCM precipitation data were compared with the observed using Mean Absolute Error (MAE) and Root Mean Square error (RMSE). The findings showed that raw outputs of regional climate models (RCMs) are characterized with several biases. In general, the models overestimate precipitation. For daily precipitation correction, the quantile approaches assuming a gamma distribution for daily precipitation were not able to reduce the biases of precipitation. The empirical quantile mapping and the adjusted quantile mapping are the most effective in correcting the biases of daily precipitation. Thus the adjusted quantile mapping can be used to correct biases of precipitation projections for modeling the future availability of water resources.
    VL  - 4
    IS  - 6
    ER  - 

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