Understanding the contribution of the vegetation-runoff system for simulating the African climate using the RegCM4 model

  • Samy A. AnwarEmail author
Original Paper


Experiments are conducted with a regional climate model (RegCM4) to understand the role of the vegetation-runoff system in simulating African climate. In some tests, the original leaf area index (LAI) formula is replaced with a new one derived from the BIOME-BGC model and then three simulations were conducted: SP-TOP (SP, satellite phenology with TOP as the default runoff scheme in the community land model, CLM), CN-TOP (CN, carbon-nitrogen module), and finally CN-VIC, the CN module with the variable infiltration capacity (VIC) runoff scheme turned on. Results show that the different vegetation-runoff configurations have a significant effect on the energy balance and regional climate. For example, the CN-VIC configuration leads to decreased evapotranspiration and increased sensible heat flux. Consequent changes to the surface energy balance also affect the regional climate. The CN-TOP configuration shows a cold bias over evergreen forest, while the CN-VIC configuration replaces this with a large warm bias. Regarding total precipitation, both CN-TOP and CN-VIC configurations do not affect the overall magnitude relative to the SP-TOP configuration; however, they simulate the timing of onset and offset in comparison with the observational dataset. Despite the substantial biases in the CN-VIC configuration, it can be recommended for future climate studies over Africa, as long as the four VIC parameters are calibrated over the African domain to obtain good results for the surface climate.


Regional climate Energy balance Carbon-nitrogen cycle Runoff scheme and energy balance 



OFID-ICTP is acknowledged for supporting the fund for the step program in ICTP institute. The climate group in (ICTP)—Earth System Physics (ESP) team is acknowledged for providing the RegCM code, computational facilities, and input data to run the model. Climate Research Unit (CRU) of University of East Anglia is acknowledged for providing the observed mean temperature data set. The MSWEP dataset was provided by NCEP/DOE 2 Reanalysis data provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their Web site at The contribution of Dr. Enda O’Brien (Climate Scientist, CECCR, King Abdul-Aziz University Jeddah, and Saudi Arabia) is valuable for improving the quality of the manuscript. The comments of unknown reviewers are very objective and useful to improve quality of this work.


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Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Egyptian Meteorological AuthorityQobry EL-KobbaCairoEgypt

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