Abstract
This study assessed the projections of temperature over West Africa using the simulated daily temperatures which were output of two (2) Coordinated Regional Climate Downscaling Experiment (CORDEX) models, include historical runs (1951-2005) and two (2) concentration pathways scenarios (RCP 4.5 from 2006-2100 and RCP 8.5 from 2006-2070) obtained from Earth System Grid Federation (ESGF) and Copernicus Climate Change Service (C3S-Climate Data Store) with spatial resolution of 0.22 0 . Results show that over West Africa under the Representation Concentration Pathways (RCP 4.5) scenario, there is a strong agreement between the distribution of model and observed PDF for the maximum temperature as the probability density functions ( PDF) increases between 0.1 to 0.2 within the range of maximum temperature of 32.5°C to 36.0°C, the observed and MPI-CCLM5 revealed an agreement while the CCCma-CanRCM4 overestimated the PDF with a spike of 0.45 in March, April and May from 1979-2018. The validation of the PDF yielded skill score for the maximum temperature revealed at 0.86 and 0.81 for CCCma-CanRCM4 and MPI-CCLM5 models respectively under RCP 4.5 scenario in March, April and May from 1979-2018 over West Africa. In June, July, August and September from 1979 to 2018 under the RCP 4.5 scenario, there is a fair agreement between the distribution of model and observed PDF for the maximum temperature as the PDF increases from 0.1 to 0.15 with the MPI-CCLM5 model in fair agreement with the observed while the CCCma-CanRCM4 model overestimated the observed with a spike PDF value of 0.47.The validation of the PDF yielded skill score for the maximum temperature revealed at 0.89 and 0.86 for CCCma-CanRCM4 and MPI-CCLM5 models respectively under RCP 4.5 scenario in June, July, August and September from 1979-2018 over West Africa. The findings revealed a warming trend in the possible future climate of West Africa and the temperature increase could pose a serious threat on socioeconomic activities, which necessitates a call to action for possible climate adaption and mitigation pathways for planners and policymakers. Keywords: Temperature, RCP, PDF DOI: 10.7176/JEES/11-10-01 Publication date: October 31 st 2021
Highlights
Alexander et al (2006) and New et al (2006) revealed a significant increase, at regional level, in the temperatures of both warmest and coldest days, and in the duration and frequency of warm spells especially in South and West Africa
3.1 Probability Density Function and Skill Score 3.1.1 March, April and May (a) Minimum Temperature Model and observed probability density functions (PDFs) fairly agree at the distribution as the PDF tend to increase from 0.1 to 0.5 and there is an evident agreement of the MPI-CCLM5 and the observed where the PDF value is less than 0.1
Under the RCP 8.5 scenario (Figure 3), the models and observed PDF disagreed at the distribution as the PDF tend to increase from 0.1 to 0.3 with gap from the observed as the models (CCCma-CanRCM4 and MPI-CCLM5) underestimated the observed minimum temperature ranging from 17°C to 30°C, both models are in consensus in their underestimation with a spike in CCCma-CanRCM4 for PDF value ranging from 0.1-0.35 in March, April and May from 1979-2018 over West Africa
Summary
Alexander et al (2006) and New et al (2006) revealed a significant increase, at regional level, in the temperatures of both warmest and coldest days, and in the duration and frequency of warm spells especially in South and West Africa. Donat et al (2013) reported a global analysis of climate extreme indices based on station data since the beginning of the twentieth century: the station density over Africa is very scarce, significant trends in the number of warm days and nights and duration of warm spells are reported for e.g. South Africa. Based on the same dataset and reanalysis data, a comprehensive analysis of climate extreme indices simulated by Global Circulation Models (GCMs) was presented by Sillmann et al (2013a). Many other studies have assessed GCM performance using monthly to annual time-scale data Studies by Alexander et al (2006) and Dessai et al (2005) revealed the importance of considering climate statistics other than means to evaluate model performance. This study focused on use of probability density functions (PDFs) according to Millard (2013) to assess model performance and skill score developed by Siegert (2017) for forecast verification routines for weather and climate
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
