On the added value of the regional climate model REMO in the assessment of climate change signal over Central Africa

• Published in: Climate dynamics 2017-12, Vol.49 (11-12), p.3813-3838
• Main Authors: Fotso-Nguemo, Thierry C., Vondou, Derbetini A., Pokam, Wilfried M., Djomou, Zéphirin Yepdo, Diallo, Ismaïla, Haensler, Andreas, Tchotchou, Lucie A. Djiotang, Kamsu-Tamo, Pierre H., Gaye, Amadou T., Tchawoua, Clément
• Format: Article
• Language: English
• Subjects: African monsoon; Annual rainfall; Annual variations; Boundary conditions; Climate; Climate change; Climate models; Climate variability; Climatic analysis; Climatology; Computer simulation; Daily precipitation; Distribution; Earth; Earth and Environmental Science; Earth Sciences; Environmental assessment; Geophysics/Geodesy; Global climate; Global climate models; Interannual variability; Meteorological research; Monsoons; Oceanography; Rain; Rainfall intensity; Rainfall-climatic change relationships; Rainy season; Recession; Regional analysis; Regional climates; Seasonal distribution; Seasonal variability; Seasonal variation; Seasonal variations; Seasons; Simulation; Spatial distribution; Statistical analysis; Statistical methods; Temperature; Wet season
• ISSN: 0930-7575; 1432-0894
• DOI: 10.1007/s00382-017-3547-7

In this paper, the regional climate model REMO is used to investigate the added value of downscaling low resolutions global climate models (GCMs) and the climate change projections over Central Africa. REMO was forced by two GCMs (EC-Earth and MPI-ESM), for the period from 1950 to 2100 under the Representative Concentration Pathway 8.5 scenario. The performance of the REMO simulations for current climate is compared first with REMO simulation driven by ERA-Interim reanalysis, then by the corresponding GCMs in order to determine whether REMO outputs are able to effectively lead to added value at local scale. We found that REMO is generally able to better represent some aspects of the rainfall inter-annual variability, the daily rainfall intensity distribution as well as the intra-seasonal variability of the Central African monsoon, though few biases are still evident. It is also found that the boundary conditions strongly influences the spatial distribution of seasonal 2-m temperature and rainfall. From the analysis of the climate change signal from the present period 1976–2005 to the future 2066–2095, we found that all models project a warming at the end of the twenty-first century although the details of the climate change differ between REMO and the driving GCMs, specifically in REMO where we observe a general decrease in rainfall. This rainfall decrease is associated with delayed onset and anticipated recession of the Central African monsoon and a shortening of the rainy season. Small-scales variability of the climate change signal for 2-m temperature are usually smaller than that of the large-scales climate change part. For rainfall however, small-scales induce change of about 70% compared to the present climate statistics.