the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Systematic underestimation of type-specific ecosystem process variability in the Community Land Model v5 over Europe
Abstract. Evapotranspiration (ET) and gross primary production (GPP) are critical fluxes contributing to the energy, water, and carbon exchanges between the atmosphere and the land surface. Land surface models such as the Community Land Model v5 (CLM5) quantify these fluxes, contribute to a better understanding of climate change's impact on ecosystems, and estimate the state of carbon budgets and water resources. Past studies have shown the ability of CLM5 to model ET and GPP magnitudes well but emphasized systematic underestimations and lower variability than in the observations.
Here, we evaluate the simulated ET and GPP from CLM5 at the grid scale (CLM5grid) and the plant functional type (PFT) scale (CLM5PFT) with observations from eddy covariance stations from the Integrated Carbon Observation System (ICOS) over Europe. For most PFTs, CLM5grid and CLM5PFT compared better to ICOS than publicly available reanalysis data and estimates obtained from remote sensing. CLM5PFT exhibited a low systematic error in simulating the ET of the ICOS measurements (average bias of -5.05 %), implying that the PFT-specific ET matches the magnitude of the observations closely. However, CLM5PFT severely underestimates GPP, especially in deciduous forests (bias of -43.76 %). Furthermore, the simulated ET and GPP distribution moments across PFTs in CLM5grid and CLM5PFT, reanalyses, and remote sensing data indicate an underestimated spatiotemporal variability compared to the observations across Europe. These results are essential insights for further evaluations in CLM5 by pointing to the limitations of CLM5 in simulating the spatiotemporal variability of ET and GPP across PFTs.
- Preprint
(6046 KB) - Metadata XML
-
Supplement
(5934 KB) - BibTeX
- EndNote
Status: open (until 13 Jul 2024)
-
RC1: 'Comment on egusphere-2024-978', Anonymous Referee #1, 13 Jun 2024
reply
Review of
Systematic underestimation of type-specific ecosystem process variability in the Community Land Model v5 over Europe
by Poppe-Teran et al.
General comments:
This is an interesting study that compares several gridded datasets of land energy, water and carbon fluxes with in situ observations over Europe. Simulations from the CLM5 land surface model are examined in more detail using two categories of simulations, one for each plant functional type and another aggregated to the grid cell level. It is found that CLM5 tends to underestimate the variability of water and carbon fluxes. A list of possible reasons is given in the Discussion section, but nothing is said about the representation of leaf area index (LAI) by CLM5 and how a misrepresentation of the LAI seasonal cycle and interannual variability could affect model performance. In the introduction, the authors give a very broad definition of phenology without ever mentioning LAI. In reality, LAI is certainly more directly related to phenology than any other variable considered in this work. Moreover, LAI strongly controls land surface fluxes and the evaporative fraction. How is LAI represented in CLM5? Because LAI responds to environmental conditions, it can exhibit large interannual variability. Failure to represent this variability would reduce the ability of the model to represent land surface fluxes.
Recommendation: major revisions.
Particular comments:
- L. 105-106 (warm winter 2020): Explain why it is called "warm winter".
- L. 143-144 (single soil column): This means that PFT-scale simulations are influenced by other PFTs. This weakens the rationale for PFT-scale simulations. It should be noticed than in other models, each PFT has its own soil column within a grid cell. This should be mentioned in the Discussion section.
- L. 151: How does soil moisture affect stomatal conductance? Given the scope of this work, this should be clearly and completely explained.
- L. 227 (warm winter 2020): For which time period are data available in the WARM-WINTER 2020 dataset? Only the 2019-2020 winter?
- L. 263 (1995-2018): Clarify the link to the WARM-WINTER 2020 data set.
- L. 300: Fig. 1c is not readable as many symbols overlap. This could be improved.
- L. 326 (Table 2): units are missing ; what is the meaning of the symbol of column 2, lines 6 and 11?
- L. 340 (Table 3): units are missing ; what is the meaning of the symbol of column 2, lines 6 and 11?
- L. 356 (Fig. 2): For a given PFT, is it a mean value across sites?
Citation: https://doi.org/10.5194/egusphere-2024-978-RC1
Viewed
HTML | XML | Total | Supplement | BibTeX | EndNote | |
---|---|---|---|---|---|---|
179 | 48 | 14 | 241 | 24 | 9 | 13 |
- HTML: 179
- PDF: 48
- XML: 14
- Total: 241
- Supplement: 24
- BibTeX: 9
- EndNote: 13
Viewed (geographical distribution)
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1