the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
CAMELE: Collocation-Analyzed Multi-source Ensembled Land Evapotranspiration Data
Changming Li
Ziwei Liu
Wencong Yang
Zhuoyi Tu
Juntai Han
Sien Li
Abstract. Land evapotranspiration (ET) plays a crucial role in Earth's water-carbon cycle, and accurately estimating global land ET is vital for advancing our understanding of land-atmosphere interactions. Despite the development of numerous ET products in recent decades, widely used products still possess inherent uncertainties arising from using different forcing inputs and imperfect model parameterizations. Furthermore, the lack of sufficient global in-situ observations makes direct evaluation of ET products impractical, impeding their utilization and assimilation. Therefore, establishing a reliable global benchmark dataset and exploring evaluation methodologies for ET products is paramount. This study aims to address these challenges by (1) proposing a collocation-based method that considers non-zero error cross-correlation for merging multi-source data and (2) employing this merging method to generate a long-term daily global ET product at resolutions of 0.1° (2000–2020) and 0.25° (1980–2022), incorporating inputs from ERA5L, FluxCom, PMLv2, GLDAS, and GLEAM. The resulting product is the Collocation-Analyzed Multi-source Ensembled Land Evapotranspiration Data (CAMELE). CAMELE exhibits excellent performance across various vegetation coverage types, as validated against in-situ observations. The evaluation process yielded Pearson correlation coefficients (R) of 0.63 and 0.65, root-mean-square-errors (RMSE) of 0.81 and 0.73 mm/d, unbiased root-mean-square-errors (ubRMSE) of 1.20 and 1.04 mm/d, mean absolute errors (MAE) of 0.81 and 0.73 mm/d, and Kling-Gupta efficiency (KGE) of 0.60 and 0.65 on average over resolutions of 0.1° and 0.25°, respectively.
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Changming Li et al.
Status: open (until 05 Nov 2023)
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RC1: 'Comment on essd-2023-226', Anonymous Referee #1, 05 Sep 2023
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The objective of the article titled "CAMELE: Collocation-Analyzed Multi-source Ensembled Land Evapotranspiration Data" is to create a daily merged evaporation product using a collocation-based data ensemble method. This method takes into account 117 non-zero error covariance conditions to merge multiple ET (Evapotranspiration) products, resulting in the Collocation Analyzed Multi-source Ensembled Land Evapotranspiration data. In general, the article is clear and well-written, and it falls within the scope of this journal. Below, I provide some points and comments that, in my opinion, can further enhance the manuscript:
1. It would be beneficial if the Scenario 1 product (at 0.10 degrees) could be extended until 2020. As far as I can see, PMLv2 is available until 2020 (please verify the link to the product). Additionally, it is important for the authors to outline their plans for updating the product and whether it will become operational. This is crucial, as many datasets become obsolete after publication.
2. I recommend expanding the introduction to clarify the implications of non-zero error covariance between different products. This will help readers better understand the importance of considering this aspect in merging strategies, especially when the assumption of error independence is violated.
3. Please consider using the modified Kling-Gupta efficiency proposed by Kling et al. (2012) instead of the KGE of Gupta et al. (2009).
- Kling, H., Fuchs, M., & Paulin, M. (2012). Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios. Journal of hydrology, 424, 264-277.
4. The authors employ slightly different products for different periods in the development of the Scenario 1 and Scenario 2 CAMELE products. It's important to discuss the implications of this choice. Can the authors evaluate if there are changes in performance in the different periods selected to construct the datasets? Does this affect the trends reported in Section 4.3?
5. If CAMELE performs similarly to other products, why should it be used? The goal in merging datasets is to outperform the products used in the merging procedure and thus better represent spatio-temporal evaporation patterns. The authors could focus on the fact that even though CAMELE may not outperform all products in all metrics, it performs better when considering all metrics. This suggests that it is a robust product and that the method can generate a product that leverages the complementary strengths of different datasets to some extent.
6. The multi-year comparison is interesting as it highlights variations in the datasets. The authors might consider excluding the trends comparison, as it may lack significance without a comparison with in-situ-based trends. This change would also help to reduce the manuscript.
7. What are the implications of adding FluxCom for 2001-2015 in Scenario 1? It might be more suitable to use FluxCom as a benchmark and produce the Scenario 1 product solely with ERA5-Land and PMLv2, using only the IVD method. If the authors choose not to follow this suggestion, they should explain, evaluate, and discuss the implications of using two different methods with an additional product for different periods in the Scenario 1 product.
8. Similarly, it would be beneficial to address the transition from GLDASv20 to GLDASv21 in 1999 for Scenario 2. Can the authors discuss the implications of changing the product versions?
9. The discussion regarding the impact of underlying assumptions in collocation analysis could be more closely related to the development of CAMELE. As it currently stands, it seems to be a comparison of evaporation datasets. Readers would benefit from a more direct connection between the performance of CAMELE and the assumptions of the methods used in its development.
10. It's worth exploring why the merging scheme did not significantly improve the performance of CAMELE. Could this be attributed to non-linear relationships between evaporation magnitudes and their respective errors? The authors should consider expanding on this in the discussion section.
Some additional minor comments:
Line 28: I would recommend caution in using qualitative terminology like "excellent performance." Additionally, I find this statement a bit misleading because the merged products performed closely to the products used in their merging. Please revise carefully the manuscript to avoid these overstatements.
Lines 58-59: The authors mention the following: "...previous research has predominantly focused on regional-scale ET estimation, necessitating a more straightforward and reliable global simulation method." It would be helpful for the authors to clarify what they mean by a "straightforward and reliable simulation method."
Line 224: A space before the reference is missing. It should be added for proper formatting.
Line 254: Was the IGBP classification obtained from a dataset? If so, how were the functional types calculated? Do they change during the period of analysis? Please provide details regarding the source and methodology for classifying the functional types.
Figure 4: The quality of Figure 4 could be improved. Consider enhancing the clarity and readability of the figure. You might want to simplify the information presented or consider moving some details to a supplementary figure.
Line 557: The authors mention that based on the results of Figure 4, CAMELE performs well at 0.10 and 0.25 degrees, and all products have similar performance. The phrase "performs well" may sound like it performs better compared to other products, which could be misleading. Consider rephrasing this to clarify that CAMELE performs similarly to other products.
Line 585: While it's understandable that the authors want to promote their product, it might seem a bit odd to say that CAMELE performs exceptionally well and closely resembles two of the products used in the merging scheme. The desired outcome in merging datasets is to outperform the products used in the merging procedure. Consider rephrasing this to maintain objectivity.
Figure 6: The quality of Figure 6 could be improved for better clarity and readability. Consider reducing the information presented in the figure or moving some details to a supplementary figure. Another option is to highlight the top three performing products for each IGBP class with color coding.
Line 863: Remove the word "excellent" from this line to maintain a more neutral tone
Citation: https://doi.org/10.5194/essd-2023-226-RC1 -
AC1: 'Reply on RC1', Changming li, 28 Sep 2023
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Please refer to the supplement.
While responding to this reviewer's comments, we have not yet received feedback from another reviewer. Therefore, the system does not recommend uploading a revised manuscript in this reply. Instead, we have included the previous manuscript's revised or new content and relevant content in our response. This is done to facilitate the reviewer and other readers so they do not need to refer to two versions of the manuscript while reviewing our response. This has resulted in a relatively lengthy response, and we hope that the reviewer and readers will understand this approach. We also suggest using the provided headings to navigate specific issues for easier reference.
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AC1: 'Reply on RC1', Changming li, 28 Sep 2023
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Changming Li et al.
Data sets
CAMELE: Collocation-Analyzed Multi-source Ensembled Land Evapotranspiration Data Changming Li; Ziwei Liu; Wencong Yang; Zhuoyi Tu; Juntai Han; Li Sien; Yang Hanbo https://doi.org/10.5281/zenodo.5704736
Changming Li et al.
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