the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 26 Jan 2026
A Year-Long Eddy Covariance Dataset over an Alpine Steppe: A Landscape Perspective on Carbon and Energy Fluxes
Abstract. The Tibetan Plateau (TP) is warming rapidly, with future projections suggesting continued warming that may amplify climate–carbon feedbacks. However, sparse in-situ observations and pronounced spatial heterogeneity in vegetation, soil moisture, and climate have limited our understanding of these ecosystem responses. Here, we present a continuous record of carbon and energy fluxes measured at a landscape scale (~30 ha / 0.3 km2) in an alpine steppe ecosystem on the TP from July 2018 to June 2019. Flux measurements were quality-filtered and gap-filled to produce a complete seasonal record using two complementary approaches, marginal distribution sampling (MDS) and random forest (RF). Eddy covariance measurements represent integrated fluxes over their footprint area, which are often much smaller than most model grids or remote sensing pixels, particularly in grassland ecosystems. Owing to the higher measurement height (19 m) at this site, the measurement footprint closely aligns with the spatial resolution of Moderate Resolution Imaging Spectroradiometer (MODIS) products, facilitating more consistent landscape-scale comparisons. The data include quality flags indicating observed or gap-filled values, uncertainty estimates, footprint diagnostics, and auxiliary meteorological variables. The data described in this manuscript provides a robust foundation for examining carbon–climate interactions in alpine environments, supporting ecosystem modeling and satellite product validation.
- Preprint
(895 KB) - Metadata XML
-
Supplement
(252 KB) - BibTeX
- EndNote
Status: final response (author comments only)
-
RC1: 'Comment on essd-2025-785', Thomas Foken, 07 Feb 2026
The comment was uploaded in the form of a supplement: https://essd.copernicus.org/preprints/essd-2025-785/essd-2025-785-RC1-supplement.pdfCitation: https://doi.org/
10.5194/essd-2025-785-RC1 -
RC2: 'Comment on essd-2025-785', Anonymous Referee #2, 21 Jun 2026
This ESSD manuscript and data set A Year-Long Eddy Covariance Dataset over an Alpine Steppe: A Landscape Perspective on Carbon and Energy Fluxes from Pillai et al. describe a continuous record of carbon and energy fluxes measured at a landscape scale in an alpine steppe ecosystem on the Tibetan Plaetau from July 2018 to June 2019 despite challenging logistics. The authors provide detailed descriptions of the handling (quality-filtering, gap filling) of the Flux measurements in the manuscript and in the product guide of the data publication. Also of high value is the footprint analysis. However, the manuscript requires major revisions on the data visualization, format (e.g. correct introduction of abbreviations), in parts more careful formulations, see the detailed comments below.
The authors should enrich the discussion part on the footprint analyses, and representativity and landscape scale.
Abstract Your results that you show in your manuscript are data rich in gap filling processing and Uncertainty analyses and your discussion is centered on these topics.
In contrast you do not show comparison of your measurements versus e.g. MODIS products on Gross Primary Productivity (GPP) or Net Photosynthesis (PSN) at 500m to 1km resolution. Therefore, you cannot make the statements you currently show in your abstract: ‘Owing to the higher measurement height (19 m) at this site, the measurement footprint closely aligns with the spatial resolution of Moderate Resolution Imaging Spectroradiometer (MODIS) products, facilitating more consistent landscape-scale comparisons. ‘ ….. ‘supporting satellite product validation.’
Please enrich your abstract with more results and numbers , e.g. quality results of the gap filling, which gap filling method performed best, uncertainties, - consider to add details from your footprint analyses in your abstract. Name the auxiliary meteorological variables.
Introduction You are starting strong with the statement on the world's largest alpine grassland … (Wang et al., 2021), continuing to cite Cai et al (2025) on the estimated vegetation carbon sequestration potential of about 1965.6 Tg across the Tibetan Plateau, however the largest contributions in Cai et al (2025) is from evergreen coniferous forest i) not representing large areas of the Tibetan Plateau and ii) not representing your land cover unit (alpine grasslands). In Cai et al. (2025) alpine grasslands on the Tibetan Plateau provide 229.25 Tg, please differentiate in your statement on carbon and also cite the estimated magnitude linked to the alpine grasslands of the Tibetan Plateau.
Figure 1 –this important figure would need some edits for harmonization and improvement:
- please align the upper and lower borders of images B and E, and C and D
- please enlarge the letters of latitude, longitude. Further enhancements E, D you could shift the longitude axis below the image D, (not E and do remove the longitude values below image E)
- The order of images looks not familiar, usually with A linked to the inlet map: the letters B, C would be used for the upper row of images, D, E for the lower row or B, D for the upper row and C, E for the lower row
- Figure caption issues: It is also more common to show the letter in the beginning of the sentences, please adapt
- Image A – you could enhance the visibility of the location symbol in the overview map with a larger symbol and brighter color. – latitude and longitude letters are too small – please enlarge and you could choose larger steps between
- Image B – color scale DEM is missing, SRTM reference is missing
- Image C ‘19 m EC covariance unit’ is not a good wording please describe in more detail in the figure caption what the photo shows.
- Image D also this figure caption text ‘the 95% footprint climatology overlaid on classified NDVI’ is not so clear and can be improved, please name Sentinel-2 as NDVI source, better name your NDVI visualization ‘color-coded’ and not ‘classified’ - is climatology the correct wording in this context?
- Image E Sentinel 2 – MSS (20 May 2019) false colour composite (FCC) imagery’. Please correct: i) The imaging sensor on board Sentinel 2 is the Multispectral Instrument (MSI), there exists no MSS sensor, however it would be enough to name Sentinel 2 without adding the sensor, ii) FCC: Despite on Sentinel hub the band imagery combination with the NIR band on the red channel is called ‘ False Color Composite’ the FFC term is specifically the term used for airborne or droneborne RGB composites using the NIR channel. Please follow the NASA recommendations to cite this type of RGB band combination as Color Infrared RGB composite (8-4-3), please see also https://www.earthdata.nasa.gov/learn/tutorials/customize-hls-rgb-imagery-composites-worldview
L84 you could already introduce the abbreviations for the radiation products in this paragraph, e.g. Rg
For a better overview, could you provide a table with the variables, variable codes, and instruments
L92 3 m EC dataset could you either introduce an abbreviation or formulate it with more text: EC measured at 3 m height, similar for ‘within the 19 m footprint’
L130 u* , was this term introduced before?
For a better overview, could you provide a table for the variables named in the paragraph 2.6 of the foot print modelling
L220 ‘.. land use land cover (LULC) map (Figure S2). The LULC map was created by visual interpretation of cloud-free Sentinel-2 Level-1C (L1C)’ - I understand that your map was created by digitization of the land cover units on the computer screen. Did you use the Color Infrared RGB composite (8-4-3) (e.g. Figure 1 E), and / or the True Color RGB composite (4-3-2) visualization of the 10 m band res. Sentinel-2 image bands? (Sentinel-2 also has 20 m res. bands). Please add these few more technical details in this paragraph and the information that the map was created by digitization.
In addition, I advise not to use the more operationally used term LULC for your digitized map. You could e.g. use the term land cover map or land unit map.
Figure S2: please enhance Figure descriptions, legend and figure caption of the land cover map Figure S2.
- On the map, please add the lake names ‘Namco Lake’ and Small Lake – then you can change the legend code for the color blue from lake to water
- Legend text needs to be enhanced please write out the words and find better descriptions for your placeholder names of the classes, not ‘main steppe’ but alpine steppe– can you assign a vegetation composition for the class you name now vegetation south west – you could use e.g. the class aggregations in Cai et al (2025) from field sampling – e.g. eventually drier less productive land cover class units represent alpine desert grassland patches?
- Figure caption: please formulate a sentence with more details, e.g. that the land units are digitized on Sentinel-2 imagery, add the date of the acquisition
3.3. L257 …’the main steppe (MSteppe)’ and other class names seem to represent placeholder names only, not proper class names. Please also see the comments related to the place holder name of the classes in the land cover map (Figure S2) and table 2. The place holder name ‘lake shore’ seems to cover the only class with dense productive vegetation according to the high NDVI values in Figure 1. Can you find a better class name expressing this high productive vegetation. What type of vegetation is represented by the place holder name ‘Vegetation SW’? You can use your land cover description in the last paragraph of the introduction to describe the landscape (2-3 sentences more) e.g. the class main steppe could be named ‘alpine steppe’ etc., please revise Figure S2 and Figure 3, Table 3 and the class names in the text accordingly.
Discussion: consider to structure your discussion by subchapters centered on the different topics, e.g. foot print analyses could become a separate discussion subchapter.
Your Codes are added to the zipped supplement, this does not seem appropriate for a FAIR DATA ESSD publication, please consider to publish your code and add the information in the availability section
General:
- please do not use abbreviations in the titles and subtitles –
- please decide if you use a non-breaking space between values and units or if you use no space between, and apply consistently
- please correctly introduce all abbreviations when they first appear in the text, e.g. carbon dioxide for CO2, Net Ecosystem Exchange for NEE, etc.
Citation: https://doi.org/10.5194/essd-2025-785-RC2
Data sets
Year-long eddy covariance measurements of carbon and energy fluxes in an alpine steppe on the Tibetan Plateau Nithin D. Pillai, Christian Wille, Felix Nieberding, Manuel Helbig, and Torsten Sachs https://dataservices.gfz.de/panmetaworks/review/597791b173aeaca12b572c6a1791d52b15bc81045fee538ebf1a21a27fd2ad18/
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 303 | 153 | 29 | 485 | 36 | 46 | 59 |
- HTML: 303
- PDF: 153
- XML: 29
- Total: 485
- Supplement: 36
- BibTeX: 46
- EndNote: 59
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1