the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Spatiotemporal dynamics and drivers of bare soil albedo in European croplands
Abstract. Bare soil albedo plays a critical role in regulating surface energy balance and land-atmosphere interactions in agricultural systems, yet its spatiotemporal variability and controlling factors remain poorly quantified at the field scale across heterogeneous cropland landscapes. To address this, we investigate the spatial patterns and temporal dynamics of bare soil albedo in European croplands. We develop a method to reconstruct field-scale, spatiotemporally continuous bare soil albedo at a 5-day temporal resolution and 0.3 km spatial resolution using Sentinel-2 reflectance observations. Bare soil periods are identified by multiple spectral indices and the corresponding soil albedo values are derived for the period 2018–2020 using a novel machine learning framework. Two random forest models were employed to separately capture the long-term spatial structure and short-term temporal anomalies of bare soil albedo, allowing gaps caused by clouds, snow, and vegetation cover to be bridged. Model evaluation against independent site observations and existing products shows that the estimated bare soil albedo reproduces observed spatial gradients and seasonal variability across European croplands. Such variations in bare soil albedo are jointly controlled by soil properties, observation geometry and short-term soil moisture dynamics rather than by any single factor. Because these variations are of the same order of magnitude as radiation management solutions, soil radiative properties must be considered in their assessment. The resulting bare soil albedo offers a process-oriented basis for improving the representation of surface radiative properties and land-atmosphere coupling in agroecosystem and land surface models.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Biogeosciences.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.- Preprint
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Status: open (until 03 May 2026)
- RC1: 'Comment on egusphere-2026-219', Anonymous Referee #1, 27 Mar 2026 reply
Data sets
Bare soil albedo datasets at high spatio-temporal resolution from Sentinel-2 observations Ke Yu, Yang Su, Philippe Ciais, Ronny Lauerwald, David Makowski, Tianqi Shi, Shengbiao Wu, Petra Sieber, Chuanlong Zhou, Daniel S. Goll https://doi.org/10.6084/m9.figshare.30488027
Model code and software
code for producing European bare soil albedo Ke Yu, Yang Su, Philippe Ciais, Ronny Lauerwald, David Makowski, Tianqi Shi, Shengbiao Wu, Petra Sieber, Chuanlong Zhou, Daniel S. Goll https://doi.org/10.6084/m9.figshare.30488027
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The manuscript “Spatiotemporal dynamics and drivers of bare soil albedo in European croplands” investigates the spatial patterns and temporal dynamics of bare soil albedo in European croplands. For this study authors reconstructed field-scale, spatiotemporally continuous bare soil albedo at a 5-day temporal resolution and 0.3 km spatial resolution using Sentinel-2 reflectance observations. Bare soil periods were identified by multiple spectral indices and the corresponding soil albedo values are derived for the period 2018-2020 using a novel machine learning framework. Two hypotheses were tested, i) spatial distribution of bare soil albedo, soil properties exert a stronger control than radiative factors, and (ii) for temporal variability of bare soil albedo, fluctuation in soil moisture is more influential than static soil properties.
To address these hypotheses, the study quantified the spatial patterns of bare soil albedo at the field scale across Europe, characterized the temporal dynamics of bare soil albedo during bare soil periods, and identified the relative contributions of soil and topographic properties. This was done by random forest models to separately capture the long-term spatial structure and short-term temporal anomalies of bare soil albedo.
Model evaluation showed that the estimated bare soil albedo reproduces observed spatial gradients and seasonal variability across European croplands. Variations in bare soil albedo were controlled by soil properties, and short-term soil moisture dynamics rather than by any single factor. Variations in bare soil albedo were comparable to those related management solutions. Authors recommend to better considered bare soil albedo in order to improve the representation of surface radiative properties and land-atmosphere coupling in agroecosystem and land surface models.
I have read this manuscript with interest. The study is well written, clearly illustrated, and easy to follow.
It convincingly highlights the importance of incorporating daily bare soil albedo information into land surface and agroecosystem models in order to improve the simulation of short-term thermal and moisture dynamics. This is particularly relevant, as static or climatological representations of bare soil albedo may limit the ability of models to capture rapid transitions associated with soil wetting-drying cycles.
Overall, I the manuscript is of very good quality and can be accepted after some minor revisions.
General comments
I feel that the manuscript would benefit from a clearer and more explicit illustration of the relationships between soil moisture, soil texture, and albedo, which are mentioned in the abstract, objectives, and discussion (see also L391, L429, L455 and following).
As a 1st step I this suggest moving Supplementary Figure 7 (linear relationship between site-level bare soil albedo and soil moisture) into the main text, as it directly supports some of the key arguments of the study.
Along the same lines, it would be useful to provide some basic contextual information for the validation sites, such as pedoclimatic conditions, crop rotations, and fallow periods. This would help the reader better understand the representativeness and variability of the dataset.
Specific comments
L238 and following:
Could you add a notion of a gradient in your evaluation dataset? The dataset includes only eight sites, and it would strengthen the manuscript to better demonstrate that these sites cover a meaningful pedoclimatic gradient. I recommend to better describ how the selected sites represent variability in:
soil types (e.g. texture, possibly linked to soil color),
climatic conditions (e.g. radiation, cloud cover),
management practices (e.g. crop rotations, fallow periods),
seasonal dynamics (as proxies for variations in radiation intensity, cloud cover, and soil moisture throughout the year; see also L271).
L238 please cite Figure 3
Figure 5 as non of the values is over 0.4 may be adjust the Figure to y axis 0-0.3
Figure 6 as non of the values is over 0.4 may be adjust the Figure to y axis 0-0.3