Details

Autor(en) / Beteiligte

• Lv, Yan
• Zhang, Li
• Li, Pan
• He, Honglin
• Ren, Xiaoli
• Xie, Zongqiang
• Wang, Yang
• Wang, Anzhi
• Shi, FuSun
• Chang, Ruiying
• Xiao, Jingfeng
• Wang, Xufeng

Titel

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

Ist Teil von

• Journal of advances in modeling earth systems, 2023-10, Vol.15 (10), p.n/a

Ort / Verlag

Washington: John Wiley & Sons, Inc

Erscheinungsjahr

2023

Link zum Volltext

Quelle

Wiley Online Library - AutoHoldings Journals

Beschreibungen/Notizen

• 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. Plain Language Summary As an important factor indicating climate and environmental changes, phenology plays an important role in regulating the variation of carbon, water, and energy exchange. Due to limited understanding of phenology mechanisms, the simulation of phenology remains large uncertainties. In this study, we evaluated and modified the leaf unfolding and leaf falling models using the long‐term phenological observations with the Community Land Model (CLM4.5), validated the modified leaf‐unfolding and leaf‐falling models by observed phenology and remote‐sensing phenology data, examined the ability of CLM4.5 with modified deciduous phenology submodels in simulating gross primary productivity, and used the modified phenology models to predict the changes in phenological dates in the future. Our results suggest that the deciduous phenology models, especially the leaf‐falling process, used in the CLM is urgent to be improved to reduce the errors in predicting growing season length and carbon fluxes in deciduous forests in the context of climate change. Key Points The involvement of chill accumulation with heat requirement in leaf unfolding models can improve the model performance We propose a new leaf falling model by considering the relationship between summer temperature and aging state threshold, which improves the model performance The revise of deciduous phenological model in CLM4.5 improves the simulation of gross primary productivity by influencing carbon uptake duration and amplitude