Leverne et al. (2026) Advancing Satellite Solar‐Induced Chlorophyll Fluorescence Data Assimilation in Land Surface Models: An Assessment Over Boreal Evergreen Needleleaf Forests

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Journal of Advances in Modeling Earth Systems
• Year: 2026
• Date: 2026-11-01
• Authors: L. Leverne, Camille Abadie, Cédric Bacour, V. Tartaglione, Yuan Zhang, T. A. Black, V. Bastrikov, Nina Raoult, Philippe Peylin, A. Krieger‐Liszkay, Fabienne Maignan
• DOI: 10.1029/2026ms005862

Research Groups

Not explicitly stated in the provided abstract.

Short Summary

This study develops a data assimilation strategy combining satellite solar-induced fluorescence (SIF) and in situ gross primary production (GPP) to improve the simulation of boreal forest GPP in the ORCHIDEE land surface model. The co-assimilation significantly enhances the seasonal cycles of SIF and GPP, outperforming GPP-only assimilation and leading to a greater than 77% reduction in root mean square deviation (RMSD) against independent GPP products.

Objective

• To assess the complementarity of satellite SIF from TROPOMI and in situ GPP in constraining GPP dynamics simulated by the ORCHIDEE land surface model over boreal evergreen needleleaf forests, evaluating the framework using two non-photochemical quenching (NPQ) schemes.

Study Configuration

• Spatial Scale: Boreal evergreen needleleaf forests, regional scale.
• Temporal Scale: 2001–2020.

Methodology and Data

• Models used: ORCHIDEE land surface model (LSM), two non-photochemical quenching (NPQ) schemes (a process-based formulation separating sustained and reversible components, and a generic model representing total NPQ).
• Data sources: Satellite solar-induced fluorescence (SIF) from TROPOMI, in situ gross primary production (GPP), independent SIF grid cells, flux sites, FLUXSAT GPP product, FLUXCOM-X-BASE GPP product.

Main Results

• After assimilation, both SIF and GPP showed improved seasonal cycles when evaluated against independent SIF grid cells and flux sites.
• Regional-scale simulations better matched independent GPP products (FLUXSAT and FLUXCOM-X-BASE) over 2001–2020.
• A greater than 77% reduction in the root mean square deviation (RMSD) of the mean seasonal cycle was observed versus the prior, largely due to recalibration of model parameters after implementing a new radiative transfer scheme.
• SIF-GPP co-assimilation outperformed GPP-only assimilation for the GPP latitudinal profile and for the GPP mean seasonal cycle in three out of four cases.
• Despite affecting the simulated SIF seasonal cycle differently, the two NPQ models exhibited similar performances after assimilation.

Contributions

• Development of a novel data assimilation strategy that effectively combines satellite SIF and in situ GPP to constrain and improve GPP simulations in land surface models for boreal evergreen needleleaf forests.
• Demonstration of the significant complementarity of SIF-GPP co-assimilation, showing superior performance over GPP-only assimilation in improving GPP dynamics and latitudinal profiles.
• Quantitative evidence of substantial improvement in regional GPP simulations, with over 77% RMSD reduction against independent products.
• Evaluation of the impact of different NPQ schemes within a data assimilation framework, providing insights into their role in SIF-GPP relationships.

Funding

Not explicitly stated in the provided abstract.

Citation

@article{Leverne2026Advancing,
  author = {Leverne, L. and Abadie, Camille and Bacour, Cédric and Tartaglione, V. and Zhang, Yuan and Black, T. A. and Bastrikov, V. and Raoult, Nina and Peylin, Philippe and Krieger‐Liszkay, A. and Maignan, Fabienne},
  title = {Advancing Satellite Solar‐Induced Chlorophyll Fluorescence Data Assimilation in Land Surface Models: An Assessment Over Boreal Evergreen Needleleaf Forests},
  journal = {Journal of Advances in Modeling Earth Systems},
  year = {2026},
  doi = {10.1029/2026ms005862},
  url = {https://doi.org/10.1029/2026ms005862}
}