the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A monthly 0.01° terrestrial evapotranspiration product (1982–2018) for the Tibetan Plateau
- 1Land-Atmosphere Interaction and its Climatic Effects Group, State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
- 2College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
- 3College of Atmospheric Science, Lanzhou University, Lanzhou 730000, China
- 4National Observation and Research Station for Qomolongma Special Atmospheric Processes and Environmental Changes, Dingri 858200, China
- 5Kathmandu Center of Research and Education, Chinese Academy of Sciences, Beijing 100101, China
- 6China-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences, Islamabad 45320, Pakistan
- 1Land-Atmosphere Interaction and its Climatic Effects Group, State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
- 2College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
- 3College of Atmospheric Science, Lanzhou University, Lanzhou 730000, China
- 4National Observation and Research Station for Qomolongma Special Atmospheric Processes and Environmental Changes, Dingri 858200, China
- 5Kathmandu Center of Research and Education, Chinese Academy of Sciences, Beijing 100101, China
- 6China-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences, Islamabad 45320, Pakistan
Abstract. Evapotranspiration (ET) is an important component of the water balance system in the “Asian water tower” region, the Tibetan Plateau (TP). However, accurately monitoring and understanding the spatial and temporal variability of the ET components (soil evaporation Es, canopy transpiration Ec, and intercepted water evaporation Ew) on the TP remains gravely challenging due to the paucity of observational data for this remote area. In this study, the 37 years (1982–2018) of monthly ET component data for the TP were produced using the MOD16-STM model, which uses the recently available soil properties, meteorological conditions, and remote sensing datasets. The estimated ET results correlate very well with the measurements from nine flux towers, with a low root mean square error of 13.48 mm/month, mean bias of 2.85 mm/month, coefficient of determination of 0.83, and index of agreement of 0.92. The annual average ET for the entire TP (specified as elevations higher than 2500 m) is about 0.93 ± 0.037 Gt/year. The main contribution of the ET on the TP comes from the soil, with the Es accounting for more than 84 % of the ET. During the study period, the ET exhibited a significant increasing trend, with rates of about 1–4 mm/year (p < 0.05), over most parts of the central and eastern TP and a significant decreasing trend, with rates of −3 to −1 mm/year, over the northwestern TP. The rate of increase in the ET on the TP over the past 37 years was around 0.96 mm/year. The increase in the ET over the entire TP from 1982 to 2018 can be explained by the warming and wetting trend of the climate on the TP during this period. The MOD16-STM ET data exhibited an acceptable performance over the TP compared with previous results. The MOD16-STM ET can adequately represent the actual ET and can be used for research on water resource management, drought monitoring, and ecological change. The whole datasets are freely available at the Science Data Bank (http://doi.org/10.11922/sciencedb.00020, Y. Ma, X.Chen, L. Yuan, 2021) and the National Tibetan Plateau Data Center (TPDC) (http://doi.org/10.11888/Terre.tpdc.271913, L. Yuan, X.Chen, Y. Ma, 2021).
Ling Yuan et al.
Status: final response (author comments only)
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RC1: 'Comment on essd-2022-195', Anonymous Referee #1, 13 Nov 2022
This manuscript generated a long-time evapotranspiration (ET) datasets, including its three components, for the arid and cold areas of the Tibetan Plateau. The intent of the manuscript is worthy and significant, and the topic generally fits the scope of Earth System Science Data. However, I'm afraid the paper still requires thoroughly editing to reach the level of international publications and before publication is granted. One major concern is that the ET estimation methods were not clear enough, i.e., the MOD16-STM was an existing algorithm, what’s your contribution? If introducing soil moisture is, how about the estimates without using soil moisture? Furthermore, the validation is somewhat weird. Particularly the components did not perform any validation or the proposed products did not compare to any existing ET products.
Major concerns:
- Introduction section. Although the introduction section was well written, it’s unclear why the authors perform this study. I would encourage the authors to directly point out the challenges that the present ET products have, rather than stating a lack of long-term remote sensing ET products (which is not true). Give a clear message to the reader what are the critical problems in the studied topic, why you did the study, and what problem(s) will be solved in the current study.
- Method section. The authors use a two source PM equation. However, they did not sperate rs and rc (Eqs. 1 to 3). In fact, these two resistances as well as resistance for wet canopy (interception) are estimated using different methods in MOD16, but they were estimated in the same way in this study. In addition, the input datasets have different temporal scales and how did you deal with the problem (or model simulation at what kind of temporal scale)? It is also unclear how the estimates were validated. For example, at half-hour or daily scale? How to match the EC tower data with the pixel?
- Results section. I’m somewhat confused by the results shown in figure 5, particularly the ET and its component in forest land. The ET can be high as greater than 700 mm, but the Ec looks like only around 150 mm. Could you show some published data to justify the estimates? Moreover, how accurate is the Ei comparing to the other results (e.g., Zheng’s product)? In section 3.4, could you show some comparisons between your estimates and the other products (e.g., using plots)?
- Discussion section. In 4.2, insightful discussion is missing. For example, in ET estimation, a lot of empirical coefficients were used, did they cause any uncertainty?
Specific comments
- Line 68. What did you mean by using “the remote nature of the TP”?
- Line 77-99. It mentioned that “It is also difficult to separate and validate the ET components effectively.” Maybe a comprehensive validation of the ET components is needed to prove that this challenge has been overcome in this dataset. Otherwise, the product does not solve the problem mentioned in the introduction section: “Interestingly, there are significant differences in the global and regional contributions of the Es, Ec, and Ei even if the total ET estimates are consistent across different products (Lawrence et al., 2007; Blyth and Harding, 2011; Miralles et al., 2016).”
- Figure 1. It is better to use different color for each panel. Where are these data from?
- Line 82-83. “The MOD16 algorithm is also used to separately estimate…” may be better.
- The authors claim that the new ET product exhibited acceptable performance on the TP based on nine flux towers. Overall, it is agree well with the flux tower ET (Figure 3j), but overestimation occurred at lower ET rates and underestimation at larger ET rates (obviously in Figures 3d, e, f, i). It is better to give some explanation and make insightful discussion (or improvement).
- Is it necessary to use a question for a section title?
- I’m quite confused by using the MOD16-STM. What does STM mean (or abbreviation for what)?
- In the following paragraph, the writing style of T* was varied. Please unify them.
- Although the 18 ET products are proved with accept accuracy, they show a large uncertainty in both trends and averaged ET on the TP. To compare their performances on the TP, it is suggested to compare the averaged ET from these products to the EC measurements (i.e., monthly and annual scales) and water balance method.
- Be careful when using “very”, for example Lines 37, 63, 277, 361, etc.
- Figure 4. It is unclear which data is observation and which is observation.
- Figure 5. What does Ew mean?
- Figure 10. The legends include CR-Ma, while it is not shown in the figure.
- It seems the conclusion is too long.
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RC2: 'Comment on essd-2022-195', Anonymous Referee #2, 14 Nov 2022
Review Comments of “A monthly 0.01° terrestrial evapotranspiration product (1982-2018) for the Tibetan Plateau” by Yuan et al.
The manuscript (MS) provides a long-term ET dataset over the Tibetan Plateau, a region that is known as “Asian Water Tower” because it is the source region of a few large Asian rivers. For this reason, accurate information of ET is particularly important. I very much appreciate the considerable efforts made by the authors to the ET community, as shown by not only this gridded dataset but also the eddy-covariance flux observations in Tibetan Plateau. The latter was published by these authors in also ESSD in 2020 (https://doi.org/10.5194/essd-12-2937-2020), which has been widely used by the community to improve the understanding of hydrological and climatological processes in the Tibetan Plateau. The present MS is an obviously big step forward upon the previous one, which is also definitely significant for understanding the land surface processes in the Third Pole Region.
The MS is generally well organized and I suggest “Minor Revision”.
I have two main concerns:
- The authors stated their new ET dataset is at 0.01 degree. However, the best resolution of the inputs (Table 1) is just 0.05 degree and this is only for albedo and NDVI, others are even coarser. Usually, for any models (not only ET models), the resolution of model’s output cannot exceed the best resolution of inputs, otherwise it becomes simple “resampling” of the data (e.g., nearest neighbor or bilinear interpolation). This does not make sense since it cannot bring new spatial information. Therefore, I think the best resolution of this new ET dataset from their model can only be 0.05 degree.
- There have been a great number of studies that reported Tibetan Plateau is greening. This is not surprised because warming and wetting in recent decades may promote vegetation growth in such a cold and dry region. However, the NDVI significantly decreased after 2000 in Fig 9a, while warming (Fig 9b) and wetting (Fig 9e) are still seen for this period. This seems different with the NDVI reported in Wang et al. (2022). Because NDVI is a key input of the model that determines both canopy transpiration and soil evaporation (fc in the Equations 1 and 2), I would suggest the authors to test if other NDVI datasets (perhaps even other leaf area index data?) also show similar interannual variations and how ET varied if they are also used in the modeling, otherwise the trends in transpiration and soil evaporation in the MS should be interpreted with caution.
I have further line-by-line comments below:
Ln61: Here the Immerzeel et al. 2010 Science paper should be cited since this paper is perhaps the first one that proposed Asian Water Tower concept?
Ln75: Please delete the “pan evaporation” studies here since they are not really relevant to the present topic—ET.
Ln76-77: Please do not combine EC and reanalysis into one sentence. I would suggest moving reanalysis to the previous sentence since it belongs to “dataset”. However, EC is a kind of ground observation and is much more valuable/reliable than above “datasets”, which should be specially highlighted.
Ln144: Please show how fc is derived from NDVI.
Ln195: Prec is not shown in Tabel 1?
Ln199-201: Please show the source reference and website of the NDVI dataset.
Ln205: The emissivity data is not shown in Table 1? Please also show the resolution for it.
Table 2: I suggest adding the reference for each EC flux observation station in the Table 2. Also, the land cover type is not clear for BJ, does it belong to grassland?
Ln297-298: This point is important, but different precipitation products may produce different ratios of ET to precipitation. Did you test other datasets? I am not fully convinced by the reanalysis Prec product (especially in TP). Please also consider other Prec data, e.g., CMFD, TPHiPr (Jiang et al., 2022), and the latest gauge-satellite merged product GPCP Version 3.2 released in this year, etc. This suggestion also applies to Figure 9f because the lakes in TP continued to rapidly expand after 2000, but Prec from the current Figure 9f even decreased. Please see Fig 4e and Fig 6 in Zhang et al. (2020).
Ln330: What is the difference between “wetting” and “increased precipitation”? The “wetting” occurs many times throughout the MS…. I assume you mean the increased soil moisture? Please state clearly.
Figure 9: Please show the specific periods for different slopes shown in the Figure 9?
Ln430: “evaporated” from the entire TP.
Ln432: Please add the p value also for the significant decreasing trend.
Appendix A: I do not know whether ESSD allows Online Supplementary Materials. If so, I suggest moving all tables and figures in Appendix to Online Supplementary Materials. There is no need to show them (some are even out of TP) in this MS.
References:
Immerzeel, W. W., et al. 2010. Climate change will affect the Asian water towers. Science. https://www.science.org/doi/abs/10.1126/science.1183188
Jiang, Y., et al. 2022. TPHiPr: A long-term high-accuracy precipitation dataset for the Third Pole region based on high-resolution atmospheric modeling and dense observations, Earth Syst. Sci. Data Discuss https://doi.org/10.5194/essd-2022-299
Wang, Y., et al., 2022. Grassland changes and adaptive management on the Qinghai–Tibetan Plateau. Nature Reviews of Earth & Environment. https://www.nature.com/articles/s43017-022-00330-8
Wei, Z., et al., 2017. Revisiting the contribution of transpiration to global terrestrial evapotranspiration. Geophysical Research Letters. https://doi.org/10.1002/2016GL072235
Zhang, G., et al., 2020. Response of Tibetan Plateau lakes to climate change: Trends, patterns, and mechanisms. Earth-Science Reviews. https://doi.org/10.1016/j.earscirev.2020.103269
Ling Yuan et al.
Data sets
Long term variations of monthly terrestrial evapotranspiration over the Tibetan Plateau (1982-2018) Yaoming Ma, Xuelong Chen, Ling Yuan http://doi.org/10.11922/sciencedb.00020
Significantly increased evapotranspiration reveals accelerated water cycle on the Tibetan Plateau during 1982–2018 Ling Yuan, Xuelong Chen, Ma Yaoming http://doi.org/10.11888/Terre.tpdc.271913
Ling Yuan et al.
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