Representing dynamic grass density in the land surface model ORCHIDEE r9010

Abstract. In semi-arid regions, grasses and shrubs often form spatial heterogeneous patterns interspersed with bare soil, optimizing resource use and productivity. Accurately representing the matrix of vegetation and bare soil in global land surface models is essential for advancing the understanding of the carbon, water, and dust cycles. This study focuses on grasslands using the land surface model ORCHIDEE (ORganizing Carbon and Hydrology In Dynamic EcosystEms), which originally assumes a globally fixed maximum grass density. This assumption, referred to as the fixed maximum density approach, limits the model’s ability to capture grassland responses to environmental changes, resulting in unsustainable productivity and unrealistically frequent mortality events, particularly in resource-limited regions. To address these limitations, we introduced a dynamic density approach that simulates grassland density based on indicators of vegetation growth, such as reserve and labile carbon content in the grass. The emerging positive correlation between precipitation and simulated grass density supported the validity of the approach. Compared to the fixed maximum density approach, the new approach substantially reduced simulated mortality events, raised the aridity threshold for frequent mortality, and maintained realistic grassland productivity in regions where the presence of grassland is indicated by the observed leaf area index (LAI). This study not only demonstrates that simulating grass density as a function of carbon availability improves ORCHIDEE’s capacity to capture grassland dynamics under environmental variability, but also provides a promising foundation for investigating land–atmosphere feedbacks in (semi-)arid regions.