the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 21 Jun 2024
Process-based Modeling of Solar-induced Chlorophyll Fluorescence with VISIT-SIF version 1.0
Abstract. Satellite retrievals of solar-induced chlorophyll fluorescence (SIF) can provide opportunities to improve our understanding of terrestrial ecosystem dynamics and the carbon cycle at the global scale. Here, we present a new biogeochemical process-based carbon and nitrogen cycle model for representing SIF retrievals (VISIT-SIF version 1.0) acquired by the Greenhouse gases Observing SATellite (GOSAT) with an hourly time step and a spatial resolution of approximately 0.31 × 0.31 degrees. VISIT-SIF is characterized by its ease of implementation for the representation of radiation transfer processes between surface canopy and satellite measurements. With an initial seven years of data (2009–2015), our model simulations showed a consistent global mean value of 0.51±0.39, with GOSAT SIF retrievals of 0.46±0.42 mW m-2 sr-1 nm-1; the root-mean-square error was 0.29 mW m-2 sr-1 nm-1. We also found that the mean seasonal variability in the simulated SIFs mostly consisted of the GOSAT SIF retrievals at the subcontinental scale. However, the simulated results indicated less sensitivity to water stress in the late dry season in arid and semiarid regions relative to that of the GOSAT SIF retrievals, which is consistent with the findings of previous studies using multiple biogeochemical process-based models. This comparison suggested that there is a critical need to improve our knowledge of SIF variability and biophysical processes in such regions.
- Preprint
(1798 KB) - Metadata XML
- BibTeX
- EndNote
Status: final response (author comments only)
-
RC1: 'Comment on egusphere-2024-1542', Anonymous Referee #1, 01 Aug 2024
Miyauchi et al describe the VISIT-SIF model for simulation of satellite SIF observations. The model was used to simulate GOSAT SIF measurements, and good results were obtained. The incorporation of SIF simulation in LSMs like VISIT provides opportunities to constrain and improve LSMs using data assimilation, and the proposed VISIT SIF model has the advantage of being capable of simulations with various viewing angles, which is not possible in many current models. However, I have several concerns as listed below. The manuscript has the potential for publication in GMD after revision.
Major comments:
1. The comparison between the VISIT-SIF model and the SIF simulations in other LSMs could be more accurate and more in-depth. And the advantages and unique features of VISIT-SIF can be emphasized more (Also see comment 2).
The statement that no model can simulate GOSAT SIF (L68) is not true according to my knowledge. Lee et al (2015) and Norton et al (2018) have specifically evaluated simulations with GOSAT or used GOSAT for data assimilation. Actually, I believe most current models (listed in Table 1 in Li et al, 2022) can be used to simulate GOSAT SIF. Instead, stating the advantage of VISIT-SIF on simulating SIF observed at different angles here could be helpful.
Lee, J. E., Berry, J. A., van der Tol, C., Yang, X., Guanter, L., Damm, A., ... & Frankenberg, C. (2015). Simulations of chlorophyll fluorescence incorporated into the Community L and Model version 4. Global change biology, 21(9), 3469-3477.
Norton, A. J., Rayner, P. J., Koffi, E. N., & Scholze, M. (2018). Assimilating solar-induced chlorophyll fluorescence into the terrestrial biosphere model BETHY-SCOPE v1. 0: model description and information content. Geoscientific Model Development, 11(4), 1517-1536.
Li, R., Lombardozzi, D., Shi, M., Frankenberg, C., Parazoo, N. C., Köhler, P., ... & Yang, X. (2022). Representation of leaf‐to‐canopy radiative transfer processes improves simulation of far‐red solar‐induced chlorophyll fluorescence in the community land model version 5. Journal of advances in modeling earth systems, 14(3), e2021MS002747.
2. In my view, one advantage of the VISIT-SIF compared with existing models is its capability to simulate satellite SIF at arbitrary viewing direction. I would suggest putting more emphasis on this and providing more analysis using SCOPE and GOSAT data.
The lookup table approach for roz/sz and rshade/sun should be evaluated. Factors including leaf biochemical properties, leaf angle, and atmospheric conditions would also affect these parameters. It is critical to know whether the LUTs perform well when these factors are different from what is set in Table A1. I suggest running SCOPE with these parameters being varied, and evaluating the LUT results against the truth derived from SCOPE.
The evaluation of the geometry effect in Figure 3 looks a bit weird to me. The issue with most current models is that they only simulate for the nadir direction. I suggest also comparing the simulations with a scenario assuming nadir viewing angle.
3. I have a few concerns regarding the method:
a. The fluorescence yield at the leaf level and the photosystem level seem confused in the SIF model. Eq.2 requires leaf-level fluorescence yield, while Eq.3 provides photosystem-level fluorescence yield. Only part of photosystem-level fluorescence escapes the leaf as some are absorbed within leaf (Porcar-Castell et al, 2021). Using photosystem-level fluorescence yield as a leaf-level parameter would lead to bias in the simulation. Various approaches have been used to address this issue in other models, for example, see Lee et al, (2015) and Li et al, (2022).
Porcar-Castell, A., Malenovský, Z., Magney, T., Van Wittenberghe, S., Fernández-Marín, B., Maignan, F., ... & Logan, B. (2021). Chlorophyll a fluorescence illuminates a path connecting plant molecular biology to Earth-system science. Nature plants, 7(8), 998-1009.
Lee, J. E., Berry, J. A., van der Tol, C., Yang, X., Guanter, L., Damm, A., ... & Frankenberg, C. (2015). Simulations of chlorophyll fluorescence incorporated into the Community L and Model version 4. Global change biology, 21(9), 3469-3477.
Li, R., Lombardozzi, D., Shi, M., Frankenberg, C., Parazoo, N. C., Köhler, P., ... & Yang, X. (2022). Representation of leaf‐to‐canopy radiative transfer processes improves simulation of far‐red solar‐induced chlorophyll fluorescence in the community land model version 5. Journal of advances in modeling earth systems, 14(3), e2021MS002747.
b. L131: I suggest providing some details on how VISIT simulates APAR, it is confusing to me why that can be considered APARsun.
c. L132: How is fu derived?
Minor comments:
- L16: We also found … This sentence is not clear to me, please rephrase.
- L40: “close to the oxygen absorption band” might be a more accurate description
Citation: https://doi.org/10.5194/egusphere-2024-1542-RC1 -
RC2: 'Comment on egusphere-2024-1542', Anonymous Referee #2, 16 Aug 2024
Miyauchi et al. developed a new model, VISIT-SIF version 1.0, to predict SIF and compared it with GOSAT SIF retrievals. The VISIT-SIF model is a significant contribution to the modeling of SIF and has the potential to further our understanding of carbon dynamics. The manuscript is well written and suitable for publication in GMD. However, I have several comments listed below. A revision is necessary before publication.
Major comments:
- The abstract could be strengthened by emphasizing the uniqueness of the VISIT-SIF model and mentioning how it differs from other existing models. The authors could highlight the capability of the VISIT-SIF model to simulate SIF from different angles. Additionally, it would be beneficial to briefly summarize the application of modeling SIF to broader contexts, either in the abstract or conclusion.
- GOSAT-SIF data used in this study contain negative values. Why do the authors not consider data filtering on the GOSAT-SIF before comparison with VISIT-SIF?
- In Eq.2 and Figure 1, how is fu calculated?
Minor comments:
Line 32: “increases to prevent damae to the photosynthetic system due to the accumulation of excess energy.” Should damae be damage?
Ling 33-34: “hence, the quantum yield of photochemistry is positively and negatively correlated with fluorescence and heat dissipation" to “hence, the quantum yield of photochemistry is positively correlated with fluorescence and negatively correlated with heat dissipation”.
Line 69: “has not been developed since the launch of GOSAT in January 2009” to “has not been developed until the launch of GOSAT in January 2009”.
Line 257: “for the satellite observations and model simulations” to “between the satellite observations and model simulations”.
Ling 258: “according to this comparison” to “According to this comparison”
Line 377: “temperature and water and light limitations.” To “temperature, and water and
light limitations.”
Line 401-403: Please give relevant reference to GOME-2, OCO-2, TROPOMI, etc.
Figure 1: The description to the figure is too short. Please give necessary information about the diagram, for example the major components or the work flows.
Figure 6: The circles are overlapped. It is recommended to show them in different colors or shapes.
Figure 7: Only 9 regions are selected to show, is there any specific reason that other regions are not shown?
Citation: https://doi.org/10.5194/egusphere-2024-1542-RC2
Model code and software
Process-based Modeling of Solar-induced Chlorophyll Fluorescence with VISIT-SIF version 1.0 (model code and dataset) Tatsuya Miyauchi, Makoto Saito, Hibiki M. Noda, Akihiko Ito, Tomomichi Kato, and Tsuneo Matsunaga https://doi.org/10.5281/zenodo.11243578
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 282 | 93 | 26 | 401 | 16 | 15 |
- HTML: 282
- PDF: 93
- XML: 26
- Total: 401
- BibTeX: 16
- EndNote: 15
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1