A RCM investigation of the influence of vegetation status and runoff scheme on the summer gross primary production of Tropical Africa

Three 16-year simulations were conducted to investigate the potential influence of the vegetation cover changes (static versus interactive) alone and vegetation-runoff systems (CN-TOP versus CN-VIC) on the gross primary production (GPP) over tropical Africa using a regional climate model RegCM4-CLM45. CLM45 is the land surface model coupled to the RegCM4, CN is the carbon–nitrogen module, SIMTOP (TOP) is the default runoff scheme and Variable Infiltration Capacity (VIC) is the optional runoff scheme of the CLM45. The results showed that when the vegetation cover changes were considered alone, the RegCM4 model shows a low bias of GPP—relative to the static vegetation case—in comparison with the observation-based dataset (Machine Tree Ensemble (MTE)). On the other hand, when the effects of the soil moisture (as represented by the runoff scheme) and vegetation cover changes were combined together, the difference between the two vegetation-runoff systems was larger than when the vegetation cover changes were considered alone. This was evident as the CN-VIC severely underestimated the GPP with respect to the MTE; meanwhile the CN-TOP reversed this effect particularly over the Congo basin. Overall, GPP is more sensitive to vegetation-runoff systems than when the vegetation cover changes are only considered. In addition, the regional coupled RegCM4-CLM45-CN-VIC model can simulate the GPP with a reasonable bias as long as the four parameters of the VIC surface dataset are calibrated against in-situ observations of tropical Africa.