Projection of Climate Attributes Using CanESM2 RCM for the Lemo District of Central Ethiopia of Region

Alemgena Reta Nigussie; Dagnachew Daniel; Nebiyat Yilma

doi:doi:10.11648/j.scif.20260201.12

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Projection of Climate Attributes Using CanESM2 RCM for the Lemo District of Central Ethiopia of Region

Alemgena Reta Nigussie^*, Dagnachew Daniel, Nebiyat Yilma

Published in Science Futures (Volume 2, Issue 1)

Received: 19 June 2025 Accepted: 3 November 2025 Published: 24 December 2025

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Abstract

This article assessed the historical climate attributes and the future projections for the Lemo district of south central Ethiopia based on the observed and the projected climate variables of the Meher season. An observation of rainfall, temperature, and down welling short wave radiation for the period 1991–2020 and climate projection data from the CanESM2 RCM for the period of 2021–2100 under the RCP4.5 and RCP8.5 were used. Model Bias Correction Method of capturing historical rainfall and temperature data for that specific area of study then correcting the bias found between the RCM data and observed station data. In our case, we have applied a scientific software called CMhyd (Climate Model data for hydrologic modeling) to extract the net CDF (Network Common Data Form) model data obtained from RCMs. Statistical tests and variability measuring indexes applied for analysis. Results showed insignificantly increasing trends of rainfall and temperature over the Lemo district during 1990 to 2020. And also the projections by 2021 to 2050 (near term), 2050 to 2080 (mid-term) as well as 2081 to 2100(end-term) indicate an increase in temperature compared to the 1991-2005 of baseline periods. Whereas high variability of rainfall amount, onset and cessation changes are expected to be happened in the future. This finding shows increasing trend of variability in rainfall and temperature indicating the risks of climate change impact. Therefore identifying relevant agricultural, environmental and social adaptation strategies are desirable.

Published in	Science Futures (Volume 2, Issue 1)
DOI	10.11648/j.scif.20260201.12
Page(s)	17-32
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), 2025. Published by Science Publishing Group

Keywords

Climate Projection, Climate Change, Rain-fed Agriculture, RCM, Lemo District

References

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[3]	Workayehu, T. (2014). Legume-based cropping for sustainable production, economic benefit and reducing climate change impacts in southern Ethiopia. Journal of Agricultural and Crop Research, 2(1), 11-21.
[4]	Wakjira, M. T., Peleg, N., Anghileri, D., Molnar, D., Alamirew, T., Six, J., & Molnar, P. (2021). Rainfall seasonality and timing: implications for cereal crop production in Ethiopia. Agricultural and Forest Meteorology, 310, 108633.
[5]	Mateos, L., López-Cortijo, I., & Sagardoy, J. A. (2002). SIMIS: the FAO decision support system for irrigation scheme management. Agricultural Water Management, 56(3), 193-206.
[6]	Hamed, K. H., & Rao, A. R. (1998). A modified Mann-Kendall trend test for autocorrelated data. Journal of hydrology, 204(1-4), 182-196.
[7]	Zeleke, T., Giorgi, F., Mengistu Tsidu, G., & Diro, G. T. (2013). Spatial and temporal variability of summer rainfall over Ethiopia from observations and a regional climate model experiment. Theoretical and applied climatology, 111(3), 665-681.
[8]	Yehualaw, E., Haile, T., Mickus, K., Beardsmore, G., & Nigusse, W. (2024). Electrical resistivity and magnetic methods in mapping groundwater on the western margin of the Central Main Ethiopian Rift-A case study in the Belesa area, eastern Lemmo Woreda, Ethiopia. Acta Geodaetica et Geophysica, 59(4), 441-461.
[9]	Nouaceur, Z., Murarescu, O., & Muratoreanu, G. (2025). The Investigation of Trends and Wet and Dry Rainfall Cycles in North Africa (In Morocco, Algeria, and Tunisia)(1970–2023). Geosciences, 15(3), 80.
[10]	Teutschbein, C., & Seibert, J. (2012). Bias correction of regional climate model simulations for hydrological climate-change impact studies: Review and evaluation of different methods. Journal of hydrology, 456, 12-29.
[11]	Gebru, B., Kwena, K., Mworozi, E., & Sewankambo, N. (2023). Scaling-up pathways of last mile climate information services for community resilience in Uganda and Kenya (CHAI-III).
[12]	Ampadu, B. (2021). Overview of hydrological and climatic studies in Africa: The case of Ghana. Cogent Engineering, 8(1), 1914288.
[13]	Nicholson, S. E. (2017). Climate and climatic variability of rainfall over eastern Africa. Reviews of Geophysics, 55(3), 590-635.

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Nigussie, A. R., Daniel, D., Yilma, N. (2025). Projection of Climate Attributes Using CanESM2 RCM for the Lemo District of Central Ethiopia of Region. Science Futures, 2(1), 17-32. https://doi.org/10.11648/j.scif.20260201.12

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ACS Style

Nigussie, A. R.; Daniel, D.; Yilma, N. Projection of Climate Attributes Using CanESM2 RCM for the Lemo District of Central Ethiopia of Region. Sci. Futures 2025, 2(1), 17-32. doi: 10.11648/j.scif.20260201.12

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AMA Style

Nigussie AR, Daniel D, Yilma N. Projection of Climate Attributes Using CanESM2 RCM for the Lemo District of Central Ethiopia of Region. Sci Futures. 2025;2(1):17-32. doi: 10.11648/j.scif.20260201.12

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@article{10.11648/j.scif.20260201.12,
  author = {Alemgena Reta Nigussie and Dagnachew Daniel and Nebiyat Yilma},
  title = {Projection of Climate Attributes Using CanESM2 RCM for the Lemo District of Central Ethiopia of Region},
  journal = {Science Futures},
  volume = {2},
  number = {1},
  pages = {17-32},
  doi = {10.11648/j.scif.20260201.12},
  url = {https://doi.org/10.11648/j.scif.20260201.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.scif.20260201.12},
  abstract = {This article assessed the historical climate attributes and the future projections for the Lemo district of south central Ethiopia based on the observed and the projected climate variables of the Meher season. An observation of rainfall, temperature, and down welling short wave radiation for the period 1991–2020 and climate projection data from the CanESM2 RCM for the period of 2021–2100 under the RCP4.5 and RCP8.5 were used. Model Bias Correction Method of capturing historical rainfall and temperature data for that specific area of study then correcting the bias found between the RCM data and observed station data. In our case, we have applied a scientific software called CMhyd (Climate Model data for hydrologic modeling) to extract the net CDF (Network Common Data Form) model data obtained from RCMs. Statistical tests and variability measuring indexes applied for analysis. Results showed insignificantly increasing trends of rainfall and temperature over the Lemo district during 1990 to 2020. And also the projections by 2021 to 2050 (near term), 2050 to 2080 (mid-term) as well as 2081 to 2100(end-term) indicate an increase in temperature compared to the 1991-2005 of baseline periods. Whereas high variability of rainfall amount, onset and cessation changes are expected to be happened in the future. This finding shows increasing trend of variability in rainfall and temperature indicating the risks of climate change impact. Therefore identifying relevant agricultural, environmental and social adaptation strategies are desirable.},
 year = {2025}
}

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TY  - JOUR
T1  - Projection of Climate Attributes Using CanESM2 RCM for the Lemo District of Central Ethiopia of Region
AU  - Alemgena Reta Nigussie
AU  - Dagnachew Daniel
AU  - Nebiyat Yilma
Y1  - 2025/12/24
PY  - 2025
N1  - https://doi.org/10.11648/j.scif.20260201.12
DO  - 10.11648/j.scif.20260201.12
T2  - Science Futures
JF  - Science Futures
JO  - Science Futures
SP  - 17
EP  - 32
PB  - Science Publishing Group
UR  - https://doi.org/10.11648/j.scif.20260201.12
AB  - This article assessed the historical climate attributes and the future projections for the Lemo district of south central Ethiopia based on the observed and the projected climate variables of the Meher season. An observation of rainfall, temperature, and down welling short wave radiation for the period 1991–2020 and climate projection data from the CanESM2 RCM for the period of 2021–2100 under the RCP4.5 and RCP8.5 were used. Model Bias Correction Method of capturing historical rainfall and temperature data for that specific area of study then correcting the bias found between the RCM data and observed station data. In our case, we have applied a scientific software called CMhyd (Climate Model data for hydrologic modeling) to extract the net CDF (Network Common Data Form) model data obtained from RCMs. Statistical tests and variability measuring indexes applied for analysis. Results showed insignificantly increasing trends of rainfall and temperature over the Lemo district during 1990 to 2020. And also the projections by 2021 to 2050 (near term), 2050 to 2080 (mid-term) as well as 2081 to 2100(end-term) indicate an increase in temperature compared to the 1991-2005 of baseline periods. Whereas high variability of rainfall amount, onset and cessation changes are expected to be happened in the future. This finding shows increasing trend of variability in rainfall and temperature indicating the risks of climate change impact. Therefore identifying relevant agricultural, environmental and social adaptation strategies are desirable.
VL  - 2
IS  - 1
ER  -

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Author Information

Alemgena Reta Nigussie

Weather/Climate Forecasting and Early Warning Department, Ethiopian Meteorology Institute, Hawassa, Ethiopia

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Dagnachew Daniel

Weather/Climate Forecasting and Early Warning Department, Ethiopian Meteorology Institute, Hawassa, Ethiopia

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Nebiyat Yilma

Meteorology and Hydrology Faculty, Water Technology Institute, Arba Minch, Ethiopia

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APA Style

Nigussie, A. R., Daniel, D., Yilma, N. (2025). Projection of Climate Attributes Using CanESM2 RCM for the Lemo District of Central Ethiopia of Region. Science Futures, 2(1), 17-32. https://doi.org/10.11648/j.scif.20260201.12

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ACS Style

Nigussie, A. R.; Daniel, D.; Yilma, N. Projection of Climate Attributes Using CanESM2 RCM for the Lemo District of Central Ethiopia of Region. Sci. Futures 2025, 2(1), 17-32. doi: 10.11648/j.scif.20260201.12

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AMA Style

Nigussie AR, Daniel D, Yilma N. Projection of Climate Attributes Using CanESM2 RCM for the Lemo District of Central Ethiopia of Region. Sci Futures. 2025;2(1):17-32. doi: 10.11648/j.scif.20260201.12

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@article{10.11648/j.scif.20260201.12,
  author = {Alemgena Reta Nigussie and Dagnachew Daniel and Nebiyat Yilma},
  title = {Projection of Climate Attributes Using CanESM2 RCM for the Lemo District of Central Ethiopia of Region},
  journal = {Science Futures},
  volume = {2},
  number = {1},
  pages = {17-32},
  doi = {10.11648/j.scif.20260201.12},
  url = {https://doi.org/10.11648/j.scif.20260201.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.scif.20260201.12},
  abstract = {This article assessed the historical climate attributes and the future projections for the Lemo district of south central Ethiopia based on the observed and the projected climate variables of the Meher season. An observation of rainfall, temperature, and down welling short wave radiation for the period 1991–2020 and climate projection data from the CanESM2 RCM for the period of 2021–2100 under the RCP4.5 and RCP8.5 were used. Model Bias Correction Method of capturing historical rainfall and temperature data for that specific area of study then correcting the bias found between the RCM data and observed station data. In our case, we have applied a scientific software called CMhyd (Climate Model data for hydrologic modeling) to extract the net CDF (Network Common Data Form) model data obtained from RCMs. Statistical tests and variability measuring indexes applied for analysis. Results showed insignificantly increasing trends of rainfall and temperature over the Lemo district during 1990 to 2020. And also the projections by 2021 to 2050 (near term), 2050 to 2080 (mid-term) as well as 2081 to 2100(end-term) indicate an increase in temperature compared to the 1991-2005 of baseline periods. Whereas high variability of rainfall amount, onset and cessation changes are expected to be happened in the future. This finding shows increasing trend of variability in rainfall and temperature indicating the risks of climate change impact. Therefore identifying relevant agricultural, environmental and social adaptation strategies are desirable.},
 year = {2025}
}

Copy | Download

TY  - JOUR
T1  - Projection of Climate Attributes Using CanESM2 RCM for the Lemo District of Central Ethiopia of Region
AU  - Alemgena Reta Nigussie
AU  - Dagnachew Daniel
AU  - Nebiyat Yilma
Y1  - 2025/12/24
PY  - 2025
N1  - https://doi.org/10.11648/j.scif.20260201.12
DO  - 10.11648/j.scif.20260201.12
T2  - Science Futures
JF  - Science Futures
JO  - Science Futures
SP  - 17
EP  - 32
PB  - Science Publishing Group
UR  - https://doi.org/10.11648/j.scif.20260201.12
AB  - This article assessed the historical climate attributes and the future projections for the Lemo district of south central Ethiopia based on the observed and the projected climate variables of the Meher season. An observation of rainfall, temperature, and down welling short wave radiation for the period 1991–2020 and climate projection data from the CanESM2 RCM for the period of 2021–2100 under the RCP4.5 and RCP8.5 were used. Model Bias Correction Method of capturing historical rainfall and temperature data for that specific area of study then correcting the bias found between the RCM data and observed station data. In our case, we have applied a scientific software called CMhyd (Climate Model data for hydrologic modeling) to extract the net CDF (Network Common Data Form) model data obtained from RCMs. Statistical tests and variability measuring indexes applied for analysis. Results showed insignificantly increasing trends of rainfall and temperature over the Lemo district during 1990 to 2020. And also the projections by 2021 to 2050 (near term), 2050 to 2080 (mid-term) as well as 2081 to 2100(end-term) indicate an increase in temperature compared to the 1991-2005 of baseline periods. Whereas high variability of rainfall amount, onset and cessation changes are expected to be happened in the future. This finding shows increasing trend of variability in rainfall and temperature indicating the risks of climate change impact. Therefore identifying relevant agricultural, environmental and social adaptation strategies are desirable.
VL  - 2
IS  - 1
ER  -

Copy | Download