EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Impact of LAI assimilation by LDAS-Monde on modelled photosynthesis and respiration in the ISBA land surface model

Bertrand Bonan, Bertrand Decharme, Christine Delire, and Jean-Christophe Calvet
Bertrand Bonan et al.
  • CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France (

Land Data Assimilation Systems (LDASs) aim to monitor the evolution of land surface variables (LSVs). They were initially designed with a focus on soil moisture and temperature. Since then, the focus has increasingly expanded towards vegetation monitoring with the assimilation of Leaf Area Index (LAI) or other vegetation-related data. LDAS-Monde, the offline land data assimilation system (LDAS) developed by Météo-France’s research centre (CNRM), has been a pioneer in that domain, as it can assimilate LAI while updating directly soil moisture especially in the root-zone area. This approach has also demonstrated several times its ability to improve the simulation of Gross Primary Production (GPP) by the ISBA (Interactions Soil-Biosphere-Atmosphere) land surface model, included in LDAS-Monde.

In this work, the impact of assimilating LAI on GPP and net ecosystem exchange (NEE) is assessed with two versions of the ISBA land surface model: the classical ISBA A-gs involved currently in LDAS-Monde and the more sophisticated ISBA-Carbon Cycle (ISBA-CC) version. ISBA A-gs simulates the assimilation of carbon by photosynthesis following the work of Goudriaan et al. (1985) and Jacobs et al. (1996) while the ecosystem respiration is emulated with a simple Q10 formulation (Rivalland et al., 2005). ISBA-CC uses the same approach for photosynthesis but by modelling all biomass reservoirs (such as roots or wood) can calculate more accurately autotrophic respiration. ISBA-CC also involves a heterotrophic respiration calculated by a soil carbon module. The comparison and the impact assessments are carried out at site levels using the PLUMBER2 datasets and at larger spatial scales using a new version of FLUXCOM GPP and NEE products.

How to cite: Bonan, B., Decharme, B., Delire, C., and Calvet, J.-C.: Impact of LAI assimilation by LDAS-Monde on modelled photosynthesis and respiration in the ISBA land surface model, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-1032,, 2023.