Performance evaluation of Africa CORDEX regional climate models: case of Kpong irrigation scheme, Ghana
This study examined four Regional Climate Models (RCMs) from Coordinated Regional Climate Downscaling Experiment-Africa which are widely used in Africa researches, to select the best performing model against gridded observational dataset over the Kpong Irrigation Scheme area with data from 1964 to 2...
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| Published in | Spatial information research (Online) Vol. 28; no. 6; pp. 735 - 753 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Singapore
Springer Singapore
01.12.2020
대한공간정보학회 |
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| Online Access | Get full text |
| ISSN | 2366-3286 2366-3294 |
| DOI | 10.1007/s41324-020-00331-z |
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| Abstract | This study examined four Regional Climate Models (RCMs) from Coordinated Regional Climate Downscaling Experiment-Africa which are widely used in Africa researches, to select the best performing model against gridded observational dataset over the Kpong Irrigation Scheme area with data from 1964 to 2005. Statistical tools such as correlation coefficient (r), RMSE, and standardized deviations (σ), and Mann–Kendall trend analysis were used to determine model performance. The capability of the models to reproduce measured yearly cycles and inter-annual variability for both precipitation and temperature were also assessed. The average precipitation and temperature biases for all the models are located in the ± 0.8 mm range with temporal correlations below 0.3. The Mann–Kendall trend analysis revealed the existence of predominant decreasing trends. On the other hand, all the models were able to reproduce the inter-annual variability, but were unable to capture the long and short rainfall range and deviations accurately. In general, the RCA4-CanESM2 of the four RCMs reproduces the precipitation and temperature climatology with reasonable skill and suggested as the most efficient for climate impact assessment researches over the study area. Overall, our results provide a systematic diagnosis of the strengths and weaknesses of the four models over a wide range of temporal scale. |
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| AbstractList | This study examined four Regional Climate Models (RCMs) from Coordinated Regional Climate Downscaling Experiment-Africa which are widely used in Africa researches, to select the best performing model against gridded observational dataset over the Kpong Irrigation Scheme area with data from 1964 to 2005. Statistical tools such as correlation coefficient (r), RMSE, and standardized deviations (r), and Mann–Kendall trend analysis were used to determine model performance. The capability of the models to reproduce measured yearly cycles and inter-annual variability for both precipitation and temperature were also assessed. The average precipitation and temperature biases for all the models are located in the ± 0.8 mm range with temporal correlations below 0.3. The Mann–Kendall trend analysis revealed the existence of predominant decreasing trends. On the other hand, all the models were able to reproduce the inter-annual variability, but were unable to capture the long and short rainfall range and deviations accurately. In general, the RCA4-CanESM2 of the four RCMs reproduces the precipitation and temperature climatology with reasonable skill and suggested as the most efficient for climate impact assessment researches over the study area. Overall, our results provide a systematic diagnosis of the strengths and weaknesses of the four models over a wide range of temporal scale. KCI Citation Count: 0 This study examined four Regional Climate Models (RCMs) from Coordinated Regional Climate Downscaling Experiment-Africa which are widely used in Africa researches, to select the best performing model against gridded observational dataset over the Kpong Irrigation Scheme area with data from 1964 to 2005. Statistical tools such as correlation coefficient (r), RMSE, and standardized deviations (σ), and Mann–Kendall trend analysis were used to determine model performance. The capability of the models to reproduce measured yearly cycles and inter-annual variability for both precipitation and temperature were also assessed. The average precipitation and temperature biases for all the models are located in the ± 0.8 mm range with temporal correlations below 0.3. The Mann–Kendall trend analysis revealed the existence of predominant decreasing trends. On the other hand, all the models were able to reproduce the inter-annual variability, but were unable to capture the long and short rainfall range and deviations accurately. In general, the RCA4-CanESM2 of the four RCMs reproduces the precipitation and temperature climatology with reasonable skill and suggested as the most efficient for climate impact assessment researches over the study area. Overall, our results provide a systematic diagnosis of the strengths and weaknesses of the four models over a wide range of temporal scale. |
| Author | Anornu, Geophrey K. Awotwi, Alfred Gyamfi, Charles Anim-Gyampo, Maxwell Ashaley, James |
| Author_xml | – sequence: 1 givenname: James surname: Ashaley fullname: Ashaley, James email: jamash978@gmail.com organization: Regional Water and Environmental Sanitation Centre Kumasi (RWESCK), Department of Civil Engineering, Kwame Nkrumah University of Science and Technology (KNUST) – sequence: 2 givenname: Geophrey K. surname: Anornu fullname: Anornu, Geophrey K. organization: Regional Water and Environmental Sanitation Centre Kumasi (RWESCK), Department of Civil Engineering, Kwame Nkrumah University of Science and Technology (KNUST) – sequence: 3 givenname: Alfred surname: Awotwi fullname: Awotwi, Alfred organization: Department of Environmental Science, University for Development Studies (UDS) – sequence: 4 givenname: Charles surname: Gyamfi fullname: Gyamfi, Charles organization: Regional Water and Environmental Sanitation Centre Kumasi (RWESCK), Department of Civil Engineering, Kwame Nkrumah University of Science and Technology (KNUST) – sequence: 5 givenname: Maxwell surname: Anim-Gyampo fullname: Anim-Gyampo, Maxwell organization: Department of Earth Science, University for Development Studies (UDS) |
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| Cites_doi | 10.1002/met.1712 10.1175/JCLI-D-15-0439.1 10.1002/2015JD023905 10.1007/s00703-016-0462-0 10.1088/1748-9326/8/2/024018 10.1016/j.ecolind.2014.07.031 10.1007/s00382-001-0201-0 10.1002/joc.4374 10.1126/science.1239402 10.1029/2011JD015934 10.1002/2015JD024398 10.1002/joc.4895 10.1002/asl.897 10.4172/2157-7617.1000249 10.1016/j.jhydrol.2017.03.017 10.1007/s41324-017-0109-3 10.1002/hyp.10439 10.1007/s00382-018-4540-5 10.1002/2016GL069282 10.1890/08-08231 10.1007/s00382-018-4239-7 10.1007/s41324-017-0159-6 10.1007/s00382-008-0387-5 10.1038/ncomms14966 10.1175/1520-0442(1999)012<2451:EOCSMP>2.0.CO;2 10.1007/s41324-018-0182-2 10.1002/joc.1181 10.1002/joc.4856 10.1002/2016JD026025 10.1073/pnas.1314787111 10.1002/asl2.538 10.1007/s00704-018-2746-4 10.1007/s00382-017-3662-5 10.1016/j.agwat.2019.05.018 10.6084/M9.FIGSHARE.3381460 10.1007/s00704-017-2087-8 10.1007/978-981-13-7067-0_47 |
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| Keywords | Kpong irrigation scheme Climate change Inter-annual variability RCM Taylor diagram Trend analysis |
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| Snippet | This study examined four Regional Climate Models (RCMs) from Coordinated Regional Climate Downscaling Experiment-Africa which are widely used in Africa... |
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| Title | Performance evaluation of Africa CORDEX regional climate models: case of Kpong irrigation scheme, Ghana |
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