Preprints
https://doi.org/10.5194/egusphere-2023-1706
https://doi.org/10.5194/egusphere-2023-1706
04 Aug 2023
 | 04 Aug 2023

Non-steady-state Stomatal Conductance Modeling and Its Implications: From Leaf to Ecosystem

Ke Liu, Yujie Wang, Troy Magney, and Christian Frankenberg

Abstract. Accurate and efficient modeling of stomatal conductance (gs) has been a key challenge in vegetation models across scales. Current practice of most land surface models (LSMs) assumes steady-state gs and predicts stomatal responses to environmental cues as immediate jumps between stationary regimes. However, the response of stomata can be orders of magnitude slower than that of photosynthesis, and often cannot reach a steady state before the next model time-step, even on half-hourly time scales. Here, we implemented a simple dynamic gs model in the vegetation module of an LSM developed within the Climate Modeling Alliance, and investigated the potential biases caused by the steady-state assumption from leaf to canopy scales. In comparison with steady-state models, the dynamic model better predicted the coupled temporal response of photosynthesis and stomatal conductance to changes in light intensity using leaf measurements. In ecosystem flux simulations, while the impact of gs hysteresis response may not be substantial in terms of daily or monthly integrated canopy fluxes, our results suggested the importance of considering this effect when quantifying fluxes in the mornings and evenings, and interpreting diurnal hysteresis patterns observed in ecosystem fluxes. Furthermore, prognostic modeling can bypass the A-Ci iterations required for steady-state simulations and can be robustly run with comparable computational costs. Overall, our study highlights the implications of dynamic gs modeling in improving the accuracy and efficiency of LSMs, and for advancing our understanding of plant-environment interactions.

Ke Liu, Yujie Wang, Troy Magney, and Christian Frankenberg

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-1706', Anonymous Referee #1, 11 Sep 2023
    • AC1: 'Reply on RC1', Ke Liu, 05 Oct 2023
  • RC2: 'Comment on egusphere-2023-1706', Anonymous Referee #2, 15 Sep 2023
    • AC2: 'Reply on RC2', Ke Liu, 05 Oct 2023

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-1706', Anonymous Referee #1, 11 Sep 2023
    • AC1: 'Reply on RC1', Ke Liu, 05 Oct 2023
  • RC2: 'Comment on egusphere-2023-1706', Anonymous Referee #2, 15 Sep 2023
    • AC2: 'Reply on RC2', Ke Liu, 05 Oct 2023
Ke Liu, Yujie Wang, Troy Magney, and Christian Frankenberg
Ke Liu, Yujie Wang, Troy Magney, and Christian Frankenberg

Viewed

Total article views: 424 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
270 128 26 424 9 12
  • HTML: 270
  • PDF: 128
  • XML: 26
  • Total: 424
  • BibTeX: 9
  • EndNote: 12
Views and downloads (calculated since 04 Aug 2023)
Cumulative views and downloads (calculated since 04 Aug 2023)

Viewed (geographical distribution)

Total article views: 418 (including HTML, PDF, and XML) Thereof 418 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 01 Mar 2024
Download
Short summary
Stomata are pores on leaves that regulate gas exchange between plants and the atmosphere. Existing land models unrealistically assume stomata can jump between steady states when the environment changes. We implemented dynamic modeling for predicting gradual stomatal responses at different scales. Results suggested considering this effect on plant behavior patterns in diurnal cycles was important. Our framework also simplified simulations and can contribute to further efficiency improvements.