Improving the ISBA_CC land surface model simulation of water and carbon fluxes and stocks over the Amazon forest

Abstract. We evaluate the ISBA_CC (Interaction Soil Biosphere Atmosphere Carbon Cycle) land surface model (LSM) over the Amazon forest, and propose a revised parameterization of photosynthesis, including new soil water stress and autotrophic respiration (R_A) functions. The revised version allows the model to better capture the energy, water and carbon fluxes when compared to five Amazonian flux towers. The performance of ISBA_CC is slightly site dependent although similar to the widely evaluated LSM ORCHIDEE (Organizing Carbon and Hydrology In Dynamic Ecosystems – version 1187), which is based on different assumptions. Changes made to the autotrophic respiration functions, including a vertical profile of leaf respiration, lead to yearly simulated carbon use efficiency (CUE) and carbon stocks which is consistent with an ecophysiological meta-analysis conducted on three Amazonian sites. Despite these major improvements, ISBA_CC struggles to capture the apparent seasonality of the carbon fluxes derived from the flux tower estimations. However, there is still no consensus on the seasonality of carbon fluxes over the Amazon, stressing a need for more observations as well as a better understanding of the main drivers of autotrophic respiration.