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<p>Accurate simulation of land surface processes is pivotal for advancing climate model fidelity and projecting hydrological and ecological responses to climate change. In this study, we incorporate a dynamic root water uptake scheme (DROOT) into the Beijing Climate Center Climate System Model (BCC-CSM), enabling dynamic root distribution and plant water stress responses. This approach provides a more physiologically realistic representation of root-mediated water uptake than conventional static root parameterizations. Model performance was assessed through simulations spanning 1990–2014, focusing on key variables: soil moisture (SM), latent heat flux (LE), gross primary productivity (GPP), precipitation (PR), 2-m air temperature (T2M), and downward shortwave radiation (SW). Our results demonstrate that DROOT substantially enhances SM simulations, particularly in regions where the original model exhibited significant biases, such as the Amazon and mid-latitude zones. Tropical regions also show marked improvements in LE and GPP simulations. Although DROOT’s influence on PR and SW remains marginal, it effectively mitigates warm biases south of 50°N. Furthermore, the scheme refines vegetation’s role in the land–atmosphere water cycle by intensifying SM-LE coupling in semi-arid regions while attenuating the direct PR-SM relationship. This study highlights the critical role of accurately representing land surface ecohydrological processes in climate modeling.</p>

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Implementation and evaluation of a dynamic root water uptake scheme in the Beijing climate center climate system model

  • 期刊论文

  • 发表日期：

    2025年10月6日

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  • Junming Chen,
  • Jianduo Li,
  • Tongwen Wu,
  • Xiaoge Xin,
  • Rongwei Liao

摘要

Accurate simulation of land surface processes is pivotal for advancing climate model fidelity and projecting hydrological and ecological responses to climate change. In this study, we incorporate a dynamic root water uptake scheme (DROOT) into the Beijing Climate Center Climate System Model (BCC-CSM), enabling dynamic root distribution and plant water stress responses. This approach provides a more physiologically realistic representation of root-mediated water uptake than conventional static root parameterizations. Model performance was assessed through simulations spanning 1990–2014, focusing on key variables: soil moisture (SM), latent heat flux (LE), gross primary productivity (GPP), precipitation (PR), 2-m air temperature (T2M), and downward shortwave radiation (SW). Our results demonstrate that DROOT substantially enhances SM simulations, particularly in regions where the original model exhibited significant biases, such as the Amazon and mid-latitude zones. Tropical regions also show marked improvements in LE and GPP simulations. Although DROOT’s influence on PR and SW remains marginal, it effectively mitigates warm biases south of 50°N. Furthermore, the scheme refines vegetation’s role in the land–atmosphere water cycle by intensifying SM-LE coupling in semi-arid regions while attenuating the direct PR-SM relationship. This study highlights the critical role of accurately representing land surface ecohydrological processes in climate modeling.