A general physiologically driven representation of leaf turnover in grasslands in the QUINCY land surface model (revision: 974a6b7f)

Seitz, Josua; Yajima, Midori; Zhu, Yu; Joseph, Lumnesh Swaroop Kumar; Yang, Jinyan; Lacroix, Fabrice; Luo, Yunpeng; Schaumberger, Andreas; Bahn, Michael; Zaehle, Sönke; Caldararu, Silvia

doi:10.5194/gmd-19-8289-2026

Articles | Volume 19, issue 17

https://doi.org/10.5194/gmd-19-8289-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-19-8289-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 17

Development and technical paper

|

08 Sep 2026

Development and technical paper |

| 08 Sep 2026

A general physiologically driven representation of leaf turnover in grasslands in the QUINCY land surface model (revision: 974a6b7f)

Josua Seitz, Midori Yajima, Yu Zhu, Lumnesh Swaroop Kumar Joseph, Jinyan Yang, Fabrice Lacroix, Yunpeng Luo, Andreas Schaumberger, Michael Bahn, Sönke Zaehle, and Silvia Caldararu

Data sets

PLUMBER2: forcing and evaluation datasets for a model intercomparison project for land surface models Anna Ukkola https://doi.org/10.25914/5fdb0902607e1

Majadas de Tietar: Ecosystem level and understorey carbon, water, and energy fluxes in a Mediterranean tree-grass ecosystem Arnaund Carrara et al. https://doi.org/10.5281/zenodo.1314194

PhenoCam Dataset v3.0: Vegetation Phenology from Digital Camera Imagery, 2000-2023 O. Zimmerman et al. https://doi.org/10.3334/ORNLDAAC/2389

Model code and software

QUINCY model MPI-BGC https://doi.org/10.17871/quincy-model-2019

ICON-Land: Tile-based representation of lateral exchange processes P. de Vrese https://doi.org/10.5281/zenodo.17085112

Scripts for "A general physiologically driven representation of leaf turnover in grasslands in the QUINCY land surface model (revision: 974a6b7f)'' Josua I. Seitz et al. https://doi.org/10.5281/zenodo.18659433

Short summary

This study presents a new global leaf turnover model for grasslands in the QUINCY (QUantifying Interactions between terrestrial Nutrient CYcles and the climate system) land surface model. Land surface models often struggle to simulate grassland carbon dynamics and phenology accurately. By allowing environmental conditions to directly control leaf senescence we improve its timing as well as the accuracy of whole-season carbon dynamics across a wide range of climates and grassland ecosystems.