The leaf area index (LAI) is a key variable for representing vegetation state, and it is closely related to simulating carbon and water exchanges between land and the overlying atmosphere in land surface and terrestrial ecosystem models. Model simulations are still limited in their representation of vegetation phenological processes and capturing the resulting LAI seasonality. Therefore, this study demonstrated how LAI assimilation into the model improved carbon and water fluxes in different ecosystems over East Asia. We assimilated LAI derived from Moderate Resolution Imaging Spectroradiometer data for seven years (2004–2010) over East Asia into the Community Land Model version 4.5 with a biogeochemistry module (CLM4.5-BGC) by employing the ensemble adjustment Kalman filter method. Results showed that LAI assimilation remarkably improved estimated gross primary production (GPP). In particular, the root mean square error decreased from 97.12 to 48.63 gC/m²/month across the region for June–August. Additionally, while evapotranspiration (ET) was less sensitive to LAI than GPP, the ET components of ground evaporation, canopy evaporation, and canopy transpiration significantly changed after assimilation. The analysis of plant-available soil water showed that LAI assimilation has unique effects on soil moisture depending on the soil layer, climate, and ecosystems. In general, the improvement in ecological prediction skill by LAI assimilation was particularly evident in temperate needleleaf forests where LAI was overestimated most distinctly. This study improves our understanding of the role of LAI assimilation in eco-hydrological processes in different ecosystems with CLM4.5-BGC, which allows for the improvement of model forecasting and more accurate simulation of the effects of LAI state evolution.

叶面积指数（LAI）是代表植被状态的关键变量，它与模拟土地表面和陆地生态系统模型中的土地与上覆大气之间的碳和水交换密切相关。模型模拟在代表植物物候过程和捕获由此产生的LAI季节变化方面仍然受到限制。因此，这项研究证明了将LAI同化到模型中如何改善东亚不同生态系统中的碳和水通量。通过采用集合调整卡尔曼滤波方法，我们使用生物地球化学模块（CLM4.5-BGC）将东亚中分辨率成像光谱仪7年（2004-2010年）中的LAI与生物地球化学模块（CLM4.5-BGC）合并为社区土地模型4.5版。结果表明，LAI的同化显着提高了估计的初级生产总值（GPP）。特别是，均方根误差从97.12 gC / m降低至48.63 gC / m²整个6月至8月的/月。此外，尽管蒸散发（ET）对LAI的敏感性不如GPP，但同化后，地面蒸发，冠层蒸发和冠层蒸腾的ET成分发生了显着变化。对植物可用土壤水的分析表明，LAI同化对土壤水分的影响取决于土壤层，气候和生态系统。通常，在最明显地高估了LAI的温带针叶林中，LAI的同化提高了生态预测能力。这项研究提高了我们对CLM4.5-BGC在不同生态系统中LAI同化在生态水文过程中的作用的理解，从而可以改进模型预测并更准确地模拟LAI状态演化的影响。