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Climate extremes like droughts and heatwaves impact how water, energy, and
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carbon move through ecosystems. To capture the exchange between the land surface
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and the atmosphere, we aim to apply the “STEMMUS-SCOPE” model across ecosystems
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at a global scale. The model STEMMUS simulates soil water and heat, and the
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model SCOPE the vegetation photosynthesis and land surface energy balance.
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Like other land surface models, STEMMUS-SCOPE relies on a large number of
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numerical calculations using various meteorological data and surface parameters
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as inputs. To overcome challenges such as computational costs and optimization
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issues in calibration, we developed open-source tools for efficient computing
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and data handling following FAIR guidelines within the context of EcoExtreML
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project. In this project, we improved the representation of
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soil-water-plant-energy interaction in the model, developed a machine learning
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approach to emulate the model, and enhanced the re-usability of the model using
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the Basic Model Interface (BMI).
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The technologies developed in EcoExtreML will
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contribute to developing a digital twin of soil-plant systems.
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The python package `PyStemmusScope` allows for preparing data and running the
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STEMMUS-SCOPE model, where STEMMUS simulates soil water and heat, and the model
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SCOPE the vegetation photosynthesis and land surface energy balance. In
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addition, it supports the use of the Basic Model Interface (BMI) to couple the
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model with other models.
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![Towards a digital twin of soil-plant system](ecoextreml_dt.png)
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The python package `PyStemmusScope` is developed in [EcoExtreML
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project](https://research-software-directory.org/projects/ecoextreml).

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