the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 16 Jun 2025
Urban Eddy Covariance – The INFLUX Network
Abstract. The eddy covariance method is used by various disciplines to measure surface-atmosphere fluxes of both vector and scalar quantities. However, eddy covariance observations are uncommon in urban areas. One of the few long-term and ongoing urban flux experiments is the Indianapolis Flux Experiment (INFLUX), which has successfully deployed eddy covariance towers at eleven locations measuring fluxes from various land cover types in and around the urban environment. The data collected from this network of towers has been used to determine urban greenhouse gas emissions, assess transport model performance, and separate anthropogenic from biogenic sources. This paper describes the available data associated with the INFLUX eddy covariance network, provides details of data processing and quality control, and provides site attributes needed to interpret the data. For access to the various data products from the INFLUX eddy covariance work, please see the data availability section below.
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RC1: 'Comments on Urban Eddy Covariance – The INFLUX Network by Horne et al.', Anonymous Referee #1, 23 Jul 2025
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This manuscript introduces the turbulent flux measurements made by eddy covariance during the long-term Indianapolis Flux Experiment (INFLUX). These measurements aim to investigate the exchange of carbon and energy between Indianapolis’ urban surface and its surroundings with their overlying atmospheres.
The experiment is still ongoing, with two eddy covariance flux systems. Over the course of eleven years, up to four systems have operated simultaneously, three over built-up areas and the rest over agricultural fields and turfgrass-covered ecosystems. It is one of the few initiatives that has run a large number of eddy covariance flux towers over an extended length of time. In that respect, this publication is appropriate for ESSD, with the goal of making the collected data available to the public for future research.
However, despite certain omissions in the observation site's description, there is a major problem with the urban flux systems. The three systems were installed in sites that do not meet the eddy covariance working assumption (see specific comments to Figures 7, 8, and 9). The eddy covariance method requires a uniform landscape in terms of topography, urban morphology, building heights and densities, and distribution of emission sources and sinks. As explained in the chapter on eddy covariance flux measurements in the IG3IS Urban Greenhouse Gas Emission Observation and Monitoring Good Research Practice Guidelines (GAW Report No. 275), this entails having streets with similar traffic and houses with similar characteristics all around. Large factories, parking lots, parks, and any other major distinctive emission source or sink within the footprint should be avoided. According to this reviewer's experience, siting an eddy covariance flux tower based on these considerations is challenging, as cities are inherently heterogeneous; nonetheless, proper sites can be found where such heterogeneity is relatively homogeneous.
Based on previous publications and participation in various forums, this reviewer is familiar with the authors' arguments in favor of installing eddy covariance flux towers in extremely heterogeneous urban landscapes. These arguments have not convinced him, and while the results may have some consistency, he does not believe they are robust enough to contribute to determining greenhouse gas emissions in cities.
This reviewer recognizes the personal and financial resources required to run this monitoring network. However, he cannot endorse the installation of flux towers in such conditions. If the manuscript is published, he would use it as an example of what not to do when applying the eddy covariance method on urban surfaces.
General comments
All text. Figures and tables must be added after they have been mentioned in the text, not before. Please double-check that all abbreviations have been defined in the text before using them.
Missing data in the general context of Indianapolis: height above sea level, climate (Köppen classification), annual rainfall, and mean, min, and max ambient temperature and relative humidity.
Missing data for each flux tower: latitude and longitude.
Missing data for each urban flux tower: zero-displacement height, aerodynamic roughness length, normalized wall surface, canyon height-to-width ratio, sky view factor in the middle of the street, mean albedo, surface emissivity, and population density.
Specific comments
12-13. Indeed, the number of urban eddy covariance flux towers remains limited in comparison to the number of flux towers in natural ecosystems, but I would not call them uncommon. The number is increasing, albeit gradually.
14-15. Rewrite. Indeed, you have installed flux towers in eleven sites, but only three of them have run for an extended period of time; the other eight have run for only a short time. Reading the abstract, one could assume that all eleven flux systems have operated simultaneously.
17. ‘… and separate anthropogenic from biogenic contributions.’
44. Define footprint and source area.
55. Do you mean flux contributions from a number of emission sources and sinks? Remember that the eddy covariance method measures integrated fluxes from a myriad of emission sources and sinks within the observed footprint.
80-81. But it provides valuable information for assessing the accuracy of bottom-up emission inventories, at least for a particular area of the city. Typically, the footprint size observed by urban flux towers is similar to that of grid cells used to build emission inventories for regulatory purposes.
112. The term ‘tall tower’ is subjective. Consider replacing it with ‘urban tower.’ Flux towers over 100 m tall have been installed in London, Beijing, and Zurich, but this reviewer disagrees with them because they fail to meet the method's fundamental assumptions.
116. Figure 1. See comment above.
142. Table 1. The site identifications are not practical. Don't expect readers to memorize what kind of site each one is. Add identifiers to mark which correspond to turfgrass, croplands, and built-up areas.
142. Table 1. Include plant species for the agricultural and turfgrass sites. For the latter, indicate the grass type. It would also be nice to include the soil characteristics for each site, including soil texture and pH, bulk density, and total organic carbon content.
145. Table 2. Only two sites were equipped with net radiometers, meaning that the energy balance partitioning wasn’t assessed at the other nine sites.
145. Table 2. Why were meteorological probes not included in the three urban flux towers? They are necessary to correct the virtual temperature obtained from the sonic anemometer and could be used to indirectly calibrate the IRGA water vapor records. How were the periods affected by precipitation identified?
152. Define SFTP.
204-205. Provide a reference. Similar to other authors, this reviewer has run urban flux towers and has proved that well-designed towers installed in proper locations meet the eddy covariance assumptions.
206-208. To avoid this issue, urban flux towers must be placed in neighborhoods with relatively homogenous building morphology and emission sources and sinks homogeneously distributed across the observed footprint.
223. How do you define weak turbulence?
232. Figure 4. Make reference to Table 3 to indicate which filters were included in each filtering set. It would be nice to include the percentage of remaining data points after each filtering set.
239. Table 3. Which was the friction velocity threshold? Define 'hf w' and 'hf CO₂.'.
267. Figure 5. At the bottom you may add the total daily flux for each site.
291-292. Which was the source for the boundary layer height required as input data by the FFP model?
341. Table 4. Define LCZ. Add units for RE density. Is it possible to split RE density in trees and buildings? Similarly, could you include the mean height and variability of each one? In the case of trees, it would be nice to indicate the main species. Also indicate the turfgrass species and type.
341. Tall buildings are likely to obstruct the flow and alter the eddy spectra at sites US-Inc and US-INf based on the maximum height of the roughness elements within the measured footprint in all directions.
361. Figure 7. A communication tower located in the center of a complex roadway network is clearly not an appropriate site to mount an eddy covariance system. The photograph shows that the underlying surface is not reasonably uniform. In each sector, there are a myriad of buildings with different morphologies, as well as roadways with various characteristics and traffic.
368. Figure 8. This site provides an excellent example of where not to install an eddy covariance flux system. First, the system should not be affected by a major emission source, such as the freeway within 150 m of the tower. Second, the distribution of emission sources and sinks varies in all directions. For example, in the west sector, the eddy covariance system collects fluxes from a densely forested area, then from a neighborhood surrounding a lake, and finally from another neighborhood with a different topology.
375. Figure 9. It's unclear what kind of fluxes this tower is supposed to characterize. Looking at the east sector, for example, it appears to include contributions from a warehouse, a parking lot, and a lake.
389-390. This is not feasible. It is only possible if two or three sectors contain relatively well-distributed emission sources and sinks across their entire footprint. When a sector is divided by many large areas with varied land uses, this is not possible.
400-402. There is no flux footprint model for urban settings; thus, they must be used to get a sense of the source area observed by the eddy covariance flux tower.
Citation: https://doi.org/10.5194/essd-2025-232-RC1 -
RC2: 'Comment on essd-2025-232', Anonymous Referee #2, 25 Jul 2025
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Comment on essd-2025-232 by Horne et al.
General Comments:
The manuscript presents eddy covariance (EC) measurements collected as part of the long-term and ongoing Indianapolis Flux Experiment (INFLUX), which aims to investigate the exchange of CO₂, H₂O, energy, and momentum fluxes in and around the city of Indianapolis. The INFLUX EC network encompasses more than a decade and a half of observational site-years across a range of surface landscapes, making it, to my knowledge, one of the few initiatives to operate a large number of EC towers over such an extended time period in an urban context.
While interpreting EC data in urban environments poses significant challenges—primarily due to surface heterogeneity, which often violates the foundational assumptions of the EC technique—and despite ongoing debate about the applicability of post-processing procedures (e.g., spectral corrections, steady-state tests, and integral turbulence characteristics) originally developed for ecosystem sites, the dataset introduced in this manuscript offers unique and valuable insights into land-atmosphere interactions and greenhouse gas emissions in urban and peri-urban areas.
Given the scientific merit, the long-term nature of the dataset, and its potential for future research, I find this manuscript well-suited for publication in Earth System Science Data (ESSD), and I believe the dataset represents a meaningful contribution to the community.
Specific Comments:
- It would be helpful if the authors could provide a brief overview of the general climate characteristics of the Indianapolis region, including seasonal variations in air temperature, radiation, and precipitation. This contextual information would aid in interpreting the flux measurements and understanding the environmental background of the study.
- Table 1.Consider including additional key metadata parameters in Table 1, such as canopy height, roughness length, and displacement height. These variables are relevant for interpreting the EC fluxes and would enhance the utility of the dataset. Furthermore, it would be useful to incorporate the landscape categories described in Lines 124–126 directly into the table for easier reference.
- Table 2.The table indicates that ambient temperature and humidity are not measured at three urban sites. Could the authors clarify why these variables are missing? Additionally, if these data are unavailable, how are the sonic temperature normalization (SND) and Webb-Pearman-Leuning (WPL) corrections handled at these sites?
- Table 3.Please specify the threshold value(s) used for friction velocity. Is a uniform or site-specific threshold?
- 5.Lines 179–180.The statement regarding data processing for the US-INf site could be clarified. Do the authors mean that despiking, WPL correction, and spectral corrections were not applied at this site? If so, what is the rationale for excluding these standard procedures?
- Lines 252–254.The authors mention that flux data were removed due to a masking effect, but only for momentum flux. Could the authors elaborate on why this masking correction was applied exclusively to momentum flux, and not to other fluxes?
Citation: https://doi.org/10.5194/essd-2025-232-RC2
Data sets
Eddy Covariance High-Frequency Data for Turfgrass and Pasture in Indianapolis, Indiana and Montgomery County, Maryland (US-INa, US-INb, US-BWa, US-BWb, US-BWc) S. J. Richardson et al. https://doi.org/10.26208/CJTC-KS26
Eddy Covariance High-Frequency Data for Agricultural Sites near Indianapolis, Indiana (US-INd, US-INe, US-INi, US-INj, US-INn, US-INp) S. J. Richardson et al. https://doi.org/10.26208/fsy8-h855
Eddy Covariance High-Frequency Data for Urban and Suburban Sites in Indianapolis, Indiana (US-INc, US-INg) S. J. Richardson et al. https://doi.org/10.26208/2NT2-RS82
Eddy covariance flux tower data for Indianapolis, IN (INFLUX project) D. P. Sarmiento, K. J. Davis https://doi.org/10.17190/AMF/2001304
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