Preprints
https://doi.org/10.5194/egusphere-2024-4114
https://doi.org/10.5194/egusphere-2024-4114
30 Jan 2025
 | 30 Jan 2025
Status: this preprint is open for discussion and under review for Biogeosciences (BG).

Plant phenology evaluation of CRESCENDO land surface models. Part II: Trough, peak, and amplitude of growing season

Daniele Peano, Deborah Hemming, Christine Delire, Yuanchao Fan, Hanna Lee, Stefano Materia, Julia E. M .S. Nabel, Taejin Park, David Wårlind, Andy Wiltshire, and Sönke Zaehle

Abstract. Leaf area index is an important metric for characterising the structure of vegetation canopies and scaling up leaf and plant processes to assess their influence on regional and global climate. Earth observation estimates of leaf area index have increased in recent decades, providing a valuable resource for monitoring vegetation changes and evaluating their representation in land surface and earth system models. The study presented here uses satellite leaf area index products to quantify regional to global variations in the seasonal timing and value of the leaf area index trough, peak, and amplitude, and evaluate how well these variations are simulated by seven land surface models, which are the land components of state-of-the-art earth system models. Results show that the models simulate widespread delays, of up to three months, in the timing of leaf area index troughs and peaks compared to satellite products. These delays are most prominent across the Northern Hemisphere and support the findings of previous studies that have shown similar delays in the timing of spring leaf out simulated by some of these land surface models. The modelled seasonal amplitude differs by less than 1 m2/m2 compared to the satellite-derived amplitude across more than half of the vegetated land area. This study highlights the relevance of vegetation phenology as an indicator of climate, hydrology, soil, and plant interactions, and the need for further improvements in the modelling of phenology in land surface models in order to capture the correct seasonal cycles, and potentially also the long-term trends, of carbon, water and energy within global earth system models.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Share
Daniele Peano, Deborah Hemming, Christine Delire, Yuanchao Fan, Hanna Lee, Stefano Materia, Julia E. M .S. Nabel, Taejin Park, David Wårlind, Andy Wiltshire, and Sönke Zaehle

Status: open (until 14 Mar 2025)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Daniele Peano, Deborah Hemming, Christine Delire, Yuanchao Fan, Hanna Lee, Stefano Materia, Julia E. M .S. Nabel, Taejin Park, David Wårlind, Andy Wiltshire, and Sönke Zaehle
Daniele Peano, Deborah Hemming, Christine Delire, Yuanchao Fan, Hanna Lee, Stefano Materia, Julia E. M .S. Nabel, Taejin Park, David Wårlind, Andy Wiltshire, and Sönke Zaehle

Viewed

Total article views: 70 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
53 12 5 70 8 1 1
  • HTML: 53
  • PDF: 12
  • XML: 5
  • Total: 70
  • Supplement: 8
  • BibTeX: 1
  • EndNote: 1
Views and downloads (calculated since 30 Jan 2025)
Cumulative views and downloads (calculated since 30 Jan 2025)

Viewed (geographical distribution)

Total article views: 71 (including HTML, PDF, and XML) Thereof 71 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 06 Feb 2025
Download
Short summary
Earth System Models are the principal tools for scientists to study past, present, and future climate changes. This work investigates the ability of a set of them to represent the observed changes in vegetation, which are vital to estimating the impact of future climate mitigation and adaptation strategies. This study highlights the main limitations in correctly representing vegetation variability. These tools still need further development to improve our understanding of future changes.
Share