Amazonian evergreen forests show distinct canopy phenology and photosynthetic seasonality but the climatic triggers are not well understood. This imposes a challenge for modeling leaf phenology and photosynthesis seasonality in land surface models (LSMs) across Amazonian evergreen forest biome. On continental scale, we tested two climatic triggers suggested by site observations, vapor pressure deficit (VPD), and short-wave incoming radiation (SW) for defining leaf shedding and incorporated VPD- and SW-triggered new canopy phenology modules in the ORCHIDEE LSM (hereafter VPD-AP and SW-AP versions). Our results show that both VPD and SW are plausible precursors of large scale litterfall seasonality across the basin by comparing against in situ data from 14 sites. Specially, both VPD-AP and SW-AP correctly capture the increases in litterfall during the early dry season, followed by a flush of new leaves with increasing photosynthetic rates during the later dry season. The VPD-AP version performs better than the SW-AP version in capturing a dry-season increase of photosynthesis across the wet Amazonia areas where mean annual precipitation exceeds 2,000 mm yr$^{-1}$, consistent with previous satellite data analysis. Both VPD-AP and SW-AP model versions perform well in northern, central and southern Amazon regions where the SW seasonality is unimodal, but miss the seasonality of satellite GPP proxies in the eastern region off the coast of Guyana shield where SW seasonality is bimodal. Our findings imply that atmospheric dryness and sunlight availability likely explain the seasonality of leaf shedding and leaf flush processes, respectively, and consequently control canopy photosynthesis in Amazonian evergreen forests< Leer menos