the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Application of flux footprint equations from Kljun et al. (2015) to field eddy-covariance systems for footprint characteristics into flux network datasets
Abstract. Gas fluxes passing through an eddy-covariance (EC) system's measurement volume reflect the outgassing rate of these molecules from an upwind area known as the "flux footprint". While sources/sinks of these molecules may be uniform over a flat field, their spatial contribution to the measured fluxes is not. Thus, understanding the contribution to measured fluxes and the spatial quantification of sources/sinks from the measured fluxes requires footprint analysis. Such analysis yields flux footprint characteristics, which commonly include upwind maximum footprint location, upwind fetch containing certain percentages of measured flux (70%, 80%, 90%), and the percent of flux from a user-defined upwind fetch of interest. These characteristics are included in the datasets of flux networks such as ChinaFlux, AmeriFlux, and FluxNet. Ideally, the characteristics are calculated in real-time and on-site by EC systems in the field, but this has often not been the case due to the calculations being computationally challenging. For field applications, this study develops the equations and algorithms for these characteristics from analytical crosswind-integrated flux footprint equations. The development shows that in-field computation is made feasible by the following means: using time-efficient algorithms, taking advantage of the nondimensional nature of the footprint equations of Kljun et al. (2015), implementing practical limits on numerical integration, and developing a differential-based estimation of boundary layer height for each EC interval. Accuracy of in field calculations is maintained by the selection of footprint equations based on boundary-layer conditions and considerations of integration methods and computation techniques. This computational approach may also be applied to footprint analyses over complex terrain, nonuniform sources/sinks, or in cases where other footprint equations are used. The most popular application of footprint analysis is to optimize the EC sensor height for maximization of measured fluxes from an area of interest. This optimization using the nondimensional footprint equations is discussed, which leads to a practical methodology. This work serves as a technical reference for users or developers of EasyFlux programs, widely used in Campbell Scientific EC systems globally.
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Status: open (until 11 Mar 2026)
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CC1: 'Comment on egusphere-2025-4576', Emma Feng, 16 Jan 2026
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CC8: 'Reply on CC1', Xinhua Zhou, 18 Jan 2026
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Thank you so much for your comment.
Citation: https://doi.org/10.5194/egusphere-2025-4576-CC8
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CC8: 'Reply on CC1', Xinhua Zhou, 18 Jan 2026
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CC2: 'Comment on egusphere-2025-4576', Lei Guan, 16 Jan 2026
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The algorithms make programming easier for applications of Kljun et all 2015) to footprint characteristics while saving computation time.
Citation: https://doi.org/10.5194/egusphere-2025-4576-CC2 -
CC7: 'Reply on CC2', Xinhua Zhou, 18 Jan 2026
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Thank you so much for your comment.
Citation: https://doi.org/10.5194/egusphere-2025-4576-CC7
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CC7: 'Reply on CC2', Xinhua Zhou, 18 Jan 2026
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CC3: 'Comment on egusphere-2025-4576', Shihao Cheng, 16 Jan 2026
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This preprint does a fantastic job solving the computational hurdles of EC flux footprint analysis with Kljun et al. (2015)’s nondimensional equations. It's helpful for scientists who are interested in EC flux methods.
Citation: https://doi.org/10.5194/egusphere-2025-4576-CC3 -
CC6: 'Reply on CC3', Xinhua Zhou, 18 Jan 2026
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Thank you so much for your comment.
Citation: https://doi.org/10.5194/egusphere-2025-4576-CC6
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CC6: 'Reply on CC3', Xinhua Zhou, 18 Jan 2026
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CC4: 'Comment on egusphere-2025-4576', Dongming Cao, 18 Jan 2026
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Enables real-time computation of flux footprint characteristics in field EC systems, compatible with major flux networks—super practical!
Citation: https://doi.org/10.5194/egusphere-2025-4576-CC4 -
CC5: 'Reply on CC4', Xinhua Zhou, 18 Jan 2026
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Thank you so much for your comment.
Citation: https://doi.org/10.5194/egusphere-2025-4576-CC5
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CC5: 'Reply on CC4', Xinhua Zhou, 18 Jan 2026
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CC9: 'Comment on egusphere-2025-4576', Dexiong Teng, 19 Jan 2026
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By advancing footprint analysis from a post-processing technique to an onboard, operational routine through an embedded algorithm that calculates real-time fetch metrics on low-power dataloggers, this work demonstrates considerable innovation and immediate practical utility.
Citation: https://doi.org/10.5194/egusphere-2025-4576-CC9 -
CC10: 'Reply on CC9', Xinhua Zhou, 19 Jan 2026
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Thank you very much for your deeper understanding of our work.
Citation: https://doi.org/10.5194/egusphere-2025-4576-CC10
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CC10: 'Reply on CC9', Xinhua Zhou, 19 Jan 2026
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CC11: 'Comment on egusphere-2025-4576', Shizuo Fu, 25 Jan 2026
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This is a very detailed study on the application of the footprint model. It would be very useful to users of the Campbell Eddy Covariance Systems. One particular point that is important in my opinion is that the limitations of the Kljun et al. (2015) model should be explicitly discussed. Further clarifications at some places may also be important. The specific comments are provided below.
Line 17 and some lines later. A footprint is a transfer function relating the source area to the measured flux. The footprint itself is not an area. However, the footprint can be used to calculate the footprint. See Steinfeld et al. (2008) and Fu et al. (2025). In addition, even over a horizontally homogeneous terrain, it is likely that the footprint can extend to the downwind side of the EC system. Over complex terrain, as found by Fu et al. (2025), the extension in the downwind direction may be substantial.
References:
Steinfeld, G., Raasch, S., & Markkanen, T. (2008). Footprints in homogeneously and heterogeneously driven boundary layers derived from a Lagrangian Stochastic Particle Model embedded into large‐eddy simulation. Boundary‐Layer Meteorology, 129(2), 225–248. https://doi.org/10.1007/s10546‐008‐9317‐7
Fu, S., Chen, J. M., Zhang, J., Cheng, Z., Miao, G., Wang, R., et al. (2025). Flux footprints over a forested hill derived from a Lagrangian particle model coupled into a large‐eddy simulation model. Journal of Geophysical Research: Atmospheres, 130, e2025JD043591. https://doi.org/10.1029/2025JD043591
Lines 25-29. It is unclear why the model can be efficiently calculated in the field. From the summary section, it becomes clear that some parts are precalculated so it is not necessary to calculate them in the field. I suggest adding this explicitly into the abstract.
Lines 30-31. Since the footprint model by Kljun et al. (2015) was developed for flat ground, it may not be appropriate to state that the model developed based on Kljun et al. (2015) can be used over complex terrain.
Lines 63-75. The discussion of the symmetry seems to suggest that the source area for a negative flux is in the downwind side of the EC system. This is in contrast to my expectation.
Section 4.4. Since the boundary layer height appears at multiple places in the footprint model. It might be important to the users how sensitive the footprint model is to the boundary layer height. In addition, it might be informative to the users if some examples of the boundary layer height are calculated and provided using methods in Appendix B, and these example heights can be compared to the typical values from the literatures.
Citation: https://doi.org/10.5194/egusphere-2025-4576-CC11 -
CC12: 'Reply on CC11', Xinhua Zhou, 27 Jan 2026
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We really appreciate your comments which remind us of clarifying some issues. See attached for our detailed responses
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CC12: 'Reply on CC11', Xinhua Zhou, 27 Jan 2026
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The article is helpful. This manuscript makes flux footprint easy to be understood.