Preprints
https://doi.org/10.5194/bg-2021-355
https://doi.org/10.5194/bg-2021-355
 
20 Jan 2022
20 Jan 2022
Status: this preprint is currently under review for the journal BG.

Local scale evaluation of the simulated interactions between energy, water and vegetation in land surface models

Jan De Pue1, José Miguel Barrios1, Liyang Liu2, Philippe Ciais2, Alirio Arboleda1, Rafiq Hamdi1, Manuela Balzarolo3, Fabienne Maignan2, and Françoise Gellens-Meulenberghs1 Jan De Pue et al.
  • 1Department of Meteorological and Climatological Research, Royal Meteorological Institute, Belgium
  • 2Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
  • 3Department of Biology, University of Antwerp, Belgium

Abstract. The processes involved in the exchange of water, energy and carbon in terrestrial ecosystems are strongly intertwined. To accurately represent the terrestrial biosphere in land surface models (LSM), the intrinsic coupling between these processes is required. Soil moisture and leaf area index are two key variables at the nexus of water, energy and vegetation. Here, we evaluated three LSM (ISBA, ORCHIDEE and a diagnostic model, based on the LSA SAF algorithms) in their ability to simulate the latent heat flux (LE) and gross primary production (GPP) coherently, and their interactions through leaf area index (LAI) and soil moisture. The models were validated using in situ eddy covariance observations, soil moisture measurements and remote sensed LAI. It was found that the diagnostic model performed consistently well, regardless land cover, whereas important shortcomings of the prognostic models were revealed for in herbaceous/dry sites. Despite their different architecture and parametrization, ISBA and ORCHIDEE shared some key weaknesses. In both models, LE and GPP were found to be oversensitive to drought stress. Though the simulated soil water dynamics could be improved, this was not the main cause of errors in the surface fluxes. Instead, these errors were strongly correlated to errors in LAI. The simulated phenological cycle in ISBA and ORCHIDEE was delayed compared to observations, and failed to capture the observed seasonal variability. The feedback mechanism between GPP and LAI (i.e. the biomass allocation scheme) was identified as a key element to improve the intricate coupling between energy, water and vegetation in LSM.

Jan De Pue et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on bg-2021-355', Jean-Christophe Calvet, 28 Feb 2022
    • AC1: 'Reply on CC1', Jan De Pue, 19 May 2022
  • RC1: 'Comment on bg-2021-355', Anonymous Referee #1, 23 Mar 2022
    • AC2: 'Reply on RC1', Jan De Pue, 19 May 2022
  • RC2: 'Comment on bg-2021-355', Anonymous Referee #2, 13 Apr 2022
    • AC3: 'Reply on RC2', Jan De Pue, 19 May 2022

Jan De Pue et al.

Jan De Pue et al.

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Short summary
The functioning of ecosystems involves numerous biophysical processes which interact with eachother. Land surface models (LSM) are used to describe these processes, and form an essential component of climate models. In this paper, we evaluate the performance of three LSM and their interactions to soil moisture and vegetation. Although we found room for improvement in the simulation of soil moisture and drought stress, the main cause of errors was related to the simulated growth of vegetation.
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