the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Plant phenology evaluation of CRESCENDO land surface models. Part II: Trough, peak, and amplitude of growing season
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.
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RC1: 'Comment on egusphere-2024-4114', Anonymous Referee #1, 02 Mar 2025
The manuscript Peano et al. compared results from seven land surface models (LSMs) to remote sensing estimated leaf area index (LAI) at global scale regarding the seasonal timing of LAI trough (lowest value) and peak (highest value) and amplitude (max. – min.). The results indicate that all studied LSMs tended to show delayed timing of LAI trough and peak, in particular for the Northern Hemisphere while the modeled amplitude is smaller than satellite estimates. While overall the work is pretty straightforward, I do have a few major comments.
- Model description of phenology scheme (L85-125) and related discussions do not provide enough details for readers who are not familiar with these models or with the different phenology schemes or both to understand what might be contributing to the current variations in model simulated LAI and its seasonal dynamics. While most models tend to show delayed timing of LAI trough and peak, there’s one model, LPG-GUESS did a better job capturing this (L170, L180). Why so? Similarly, when model differences, model-data discrepancy across different biomes/regions all present, it would be interesting to discuss the potential causes why we see all these differences. While the discussion tried to talk about the different sources of variability (L280) and potential observation biases (L295), it’s quite thin and not well organized to address the observed spatiotemporal data-model discrepancy. I think expanding discussion and organize it in a similar way as how the results are organized, and maybe also add a little more detail on different phenology schemes in each LSM can be very helpful. It would also be nice to see some suggestions for future model development or priority areas for data collections for better model parameterization or better observations for model benchmarking.
- How much of the data-model discrepancy in LAI seasonality can be contributed to model structure and parameterization respectively? I know this is not the main focus of this study, but I think it’s very important to know this before we conclude that we need better phenology models (specifically refer to model structure improvement). Related, it is not clear to me how simulated distribution of the different PFTs (evergreen vs deciduous: they vary in phenology in addition to many other features that can influence plant growth and mortality thus phenology) can influence the modeled LAI seasonality both spatially and temporally. Is it possible that the delayed timing of LAI trough and LAI peak is a mismatch between the observed and the simulated vegetation type that dominate a particular grid cell?
Specific comments
L20: add relevant citations.
L40: maybe can expand to add a little more detail here.
L140: how the different domain resolution might influence model results? Also how coarse is the model resolution?
L168: multi-model ensemble mean
Citation: https://doi.org/10.5194/egusphere-2024-4114-RC1 -
RC2: 'Comment on egusphere-2024-4114', Anonymous Referee #2, 05 Mar 2025
Review of
Plant phenology evaluation of CRESCENDO land surface models. Part II: Trough, peak, and amplitude of growing season.
by Peano et al.
General comments:
This is an interesting paper comparing global leaf area index (LAI) simulations with satellite-derived LAI observations. Seven land surface models are considered along with 3 satellite LAI data sets. All products and observations are first projected onto the same 0.5 degree x 0.5 degree grid and monthly averages are considered. Maps of simulated and observed LAI peak, trough, and annual amplitude are presented. Mean monthly LAI time series show that the models tend to simulate LAI peaks later than the observations. The paper is reasonably well written, but the discussion section could be improved.
Recommendation: major revisions.
Particular comment:
- Phenology simulations may be affected by errors in the atmospheric forcing. What is the quality of the CRUNCEP atmospheric forcing database? Has it been evaluated in previous studies?
- I am concerned with the definition of "LAI trough". Unlike the LAI peak, low LAI values (e.g. in winter or during a drought) can persist for several months. Commonly used phenology indicators, in addition to peak time, are leaf onset and leaf offset. Why not use these more common indicators? Is LAI trough equivalent to leaf offset?
- The observed model LAI peak lags at mid and high latitudes may indicate a problem in the representation of temperature. Temperature is a key driver of leaf emergence in these regions. The temperature relevant to phenology is likely to be close to the land surface temperature resulting from the energy budget calculations. This is particularly true for the ISBA model, where phenology is driven by photosynthesis and leaf temperature. Is daytime leaf temperature underestimated in this model? In a number of ISBA papers (e.g. https://doi.org/10.5194/hess-21-4861-2017) the LAI peak time is generally consistent with observations. What has changed in the ISBA settings? Is the surface temperature calculated in the same way as before?
- For all models, it should be stated how the temperature used in the phenology model is calculated and how reliable it is.
Citation: https://doi.org/10.5194/egusphere-2024-4114-RC2
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