Shiru, Mohammed Sanusi and Chung, Eun Sung and Shahid, Shamsuddin and Alias, Noraliani (2020) Gcm selection and temperature projection of Nigeria under different RCPs of the CMIP5 GCMS. Theoretical and Applied Climatology, 141 (3-4). pp. 1611-1627. ISSN 0177-798X
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Official URL: http://dx.doi.org/10.1007/s00704-020-03274-5
Abstract
The possible future changes in temperature over Nigeria were projected in this study. Using Climate Research Unit (CRU) temperature as the reference data, gain ratio (GR), entropy gain (EG), and symmetrical uncertainty (SU) feature selection methods and a multi-criteria decision-making (MCDM) approach were used in selecting the most suitable GCMs for Nigeria from 20 Coupled Model Intercomparison Project phase 5 (CMIP5) global climate models (GCMs). The biases in selected GCMs were corrected using power transformation (PT) method. Multi-model ensembles (MMEs) were generated for the selected GCMs for the different temperature classes’ maximum, average, and minimum for all RCPs. The MMEs were used for the projection of temperatures over the country during 2010–2039, 2040–2069, and 2070–2099. The GCMs HadGEM2-ES, CESM1-CAM5, CSIRO-Mk3.6.0, and MRI-CGCM3 were the best performing in replicating temperature characteristics of the observed temperature in Nigeria. The MME mean projections of bias-corrected (BC) GCMs using PT revealed that there will be an increase in temperature of 4.0 °C at the semi-arid and 5.0 °C at the arid regions during dry and wet seasons respectively under RCP 4.5. In the same regions, the maximum temperature is expected to increase up to 5.5 °C under RCP 8.5 during 2070–2099 in the dry season. In the wet season, temperatures are expected to be higher under RCP 8.5, with an increase of 0.0–4.0 °C in the southern region and 3.0–6.9 °C in the northern region.
Item Type: | Article |
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Uncontrolled Keywords: | ensemble forecasting, seasonal variation |
Subjects: | T Technology > TA Engineering (General). Civil engineering (General) |
Divisions: | Civil Engineering |
ID Code: | 90323 |
Deposited By: | Yanti Mohd Shah |
Deposited On: | 30 Apr 2021 14:48 |
Last Modified: | 30 Apr 2021 14:48 |
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