Improving Phenology Representation of Deciduous Forests in the Community Land Model: Evaluation and Modification Using Long‐Term Observations in China

Abstract

Abstract Phenology is an important factor indicating environmental changes and regulates the variations of carbon, water, and energy exchange. However, phenology models exhibit large uncertainties due to limited understanding of its mechanisms. In this study, we modified deciduous phenology scheme based on the evaluation of different phenological models using long‐term observations at Chinese Ecosystem Research Network with CLM4.5. The alternating leaf unfolding model and summer‐influenced autumn leaf falling model that we proposed, performed best in simulating leaf‐unfolding and leaf‐falling. Compared with the observed and remote‐sensed phenology, the modified model could better simulate the phenological dates at the site and regional scale. Moreover, the modified model improved the simulation of gross primary productivity (GPP) by decreasing the errors of modeled carbon uptake duration and amplitude. Furthermore, the advance in leaf‐unfolding slowed down from 0.20 days/year during 1981–2015 to 0.11 days/year during 2016–2100 under RCP4.5 because of the slowdown of climate warming, but the delay in leaf‐falling changed little. By the last decade of the twenty‐first century, the leaf‐unfolding would advance (8 days) and leaf‐falling would delay (16 days). The subtropical region had large interannual variation (IAV) in leaf‐unfolding because of the high sensitivity to temperature. The phenological dates IAV in the cold temperate region increased due to enhanced temperature IAV. We suggest that the deciduous phenology models, especially the leaf‐falling process, used in Community Land Model need to be improved to reduce the errors in predicting phenology and carbon flux in the future.

Keywords

• deciduous phenology
• gross primary productivity
• temporal trend
• interannual variation
• climate change
• CLM4.5