Solar Radiation Triggers the Bimodal Leaf Phenology of Central African Evergreen Broadleaved Forests.

Central African evergreen broadleaved forests around the equator exhibit a double annual cycle for canopy phenology and carbon uptake seasonality. The underlying drivers of this behavior are poorly understood and the double seasonality is not captured by land surface models (LSM). In this study, we developed a new leaf phenology module into the ORCHIDEE LSM (hereafter ORCHIDEE‐AFP), which utilizes short‐wave incoming radiation (SWd) as the main driver of leaf shedding and partial rejuvenation of the canopy, to simulate the double seasonality of central African forests. The ORCHIDEE‐AFP model has been evaluated by using field data from two forest sites and satellite observations of the enhanced vegetation index (EVI), which is a proxy of young leaf area index (LAIYoung) with leafage less than 6 months, as well as six products of GPP or GPP proxies. Results demonstrate that ORCHIDEE‐AFP successfully reproduces observed leaf turnover (R = 0.45) and young leaf abundance (R = 0.74), and greatly improve the representation of the bimodal leaf phenology. The proportion of grid cells with a significant positive correlation between the seasonality of modeled LAIYoung and observed EVI increased from 0.2% in the standard model to 27% in the new model. For photosynthesis, the proportions of grid cells with significant positive correlations between modeled and observed seasonality range from 26% to 65% across the six GPP evaluation products. The improved performance of the ORCHIDEE‐AFP model in simulating leaf phenology and photosynthesis of central African forests will allow a more accurate assessment of the impacts of climate change in tropical forests. Plain Language Summary: Evergreen broadleaved forests in central Africa near the equator have a unique behavior where their leaf growth and ability to take in carbon peak twice a year. However, the reason underlying this behavior is not well understood, and the current process‐oriented terrestrial biosphere models can not represent this double peak. In this study, we integrated a new module, which uses sunlight as the main factor for when leaves fall and new ones grow in the forest, into a popular process‐oriented terrestrial biosphere model called ORCHIDEE, to simulate this unique behavior in central African forests (hereafter ORCHIDEE‐AFP). We tested our model using real‐world data from the forests acquired at the site level and satellite images. The results show that our new model can successfully simulate when leaves change and how much carbon the forests take in. The new model demonstrates better performance than the standard model. Our improved model will be useful for predicting the future of these forests more accurately under climate change. Key Points: Solar radiation is an adequate climate factor to drive the bimodal leaf phenology of central tropical African rainforestsWe developed a new phenology scheme with solar radiation‐triggered leaf shedding and flushing for the ORCHIDEE land surface model (LSM)The ORCHIDEE LSM with the new phenology scheme captures central tropical African rainforests' bimodal leaf phenology and photosynthesis [ABSTRACT FROM AUTHOR]