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US-IB2: Fermi National Accelerator Laboratory- Batavia (Prairie site)

Tower_team:
PI: Roser Matamala matamala@anl.gov - Argonne National Laboratory
FluxContact: David Cook dsgcook@prodigy.net - Argonne National Laboratory
Lat, Long: 41.8406, -88.2410
Elevation(m): 226.5
Network Affiliations: AmeriFlux
Vegetation IGBP: GRA (Grasslands: Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent wetlands lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water.)
Climate Koeppen: Dfa (Humid Continental: humid with severe winter, no dry season, hot summer)
Mean Annual Temp (°C): 9.04
Mean Annual Precip. (mm): 930.25
Flux Species Measured: CO2
Years Data Collected: 2004 - Present
Years Data Available:

AmeriFlux BASE 2004 - 2018   Data Citation
Data Use Policy:AmeriFlux CC-BY-4.0 Policy1
Description:
Two eddy correlation systems are installed at Fermi National Accelerator Laboratory: one on a restored prairie (established October 2004) and one on a ...
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URL: http://www.atmos.anl.gov/FERMI/index.html
Research Topics: —
Acknowledgment: —
Site Tasks
  1. This site’s data can also be used under the more restrictive AmeriFlux Legacy Policy.
    The AmeriFlux Legacy Policy must be followed if this site’s data are combined with data from sites that require the AmeriFlux Legacy Policy.
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Image Credit:
Copyright preference: Request for permission
Site Publication More Site Publications

US-IB2: Fermi National Accelerator Laboratory- Batavia (Prairie site)

Use the information below for citation of this site. See the Data Policy page for more details.

DOI(s) for citing US-IB2 data

Data Use Policy: AmeriFlux CC-BY-4.0 License

This site’s data can also be used under the more restrictive AmeriFlux Legacy Policy.
The AmeriFlux Legacy Policy must be followed if US-IB2 data are combined with data from sites that require the AmeriFlux Legacy Policy.

  • AmeriFlux BASE: https://doi.org/10.17190/AMF/1246066
    Citation: Roser Matamala (2019), AmeriFlux BASE US-IB2 Fermi National Accelerator Laboratory- Batavia (Prairie site), Ver. 8-5, AmeriFlux AMP, (Dataset). https://doi.org/10.17190/AMF/1246066

To cite BADM when downloaded on their own, use the publications below for citing site characterization. When using BADM that are downloaded with AmeriFlux BASE and AmeriFlux FLUXNET products, use the DOI citation for the associated data product.

Publication(s) for citing site characterization

    —

Acknowledgments

    —

Resources

US-IB2: Fermi National Accelerator Laboratory- Batavia (Prairie site)

This page displays the list of downloads of data for the site {{siteId}}.

Note: Results are the number of downloads to distinct data users. The Download Count column indicates the number of times the data user downloaded the data. The Version column refers to the version of the data product for the site that was downloaded by the data user.

Year Range

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US-IB2: Fermi National Accelerator Laboratory- Batavia (Prairie site)

Year Publication
2025 Xia, Y., Sanderman, J., Watts, J. D., Machmuller, M. B., Mullen, A. L., Rivard, C., Endsley, A., Hernandez, H., Kimball, J., Ewing, S. A., Litvak, M., Duman, T., Krishnan, P., Meyers, T., Brunsell, N. A., Mohanty, B., Liu, H., Gao, Z., Chen, J., Abraha, M., Scott, R. L., Flerchinger, G. N., Clark, P. E., Stoy, P. C., Khan, A. M., Brookshire, E. N., Zhang, Q., Cook, D. R., Thienelt, T., Mitra, B., Mauritz‐Tozer, M., Tweedie, C. E., Torn, M. S., Billesbach, D. (2025) Coupling Remote Sensing With A Process Model For The Simulation Of Rangeland Carbon Dynamics, Journal Of Advances In Modeling Earth Systems, 17(3), . https://doi.org/10.1029/2024MS004342
2021 Chu, H., Luo, X., Ouyang, Z., Chan, W. S., Dengel, S., Biraud, S. C., Torn, M. S., Metzger, S., Kumar, J., Arain, M. A., Arkebauer, T. J., Baldocchi, D., Bernacchi, C., Billesbach, D., Black, T. A., Blanken, P. D., Bohrer, G., Bracho, R., Brown, S., Brunsell, N. A., Chen, J., Chen, X., Clark, K., Desai, A. R., Duman, T., Durden, D., Fares, S., Forbrich, I., Gamon, J. A., Gough, C. M., Griffis, T., Helbig, M., Hollinger, D., Humphreys, E., Ikawa, H., Iwata, H., Ju, Y., Knowles, J. F., Knox, S. H., Kobayashi, H., Kolb, T., Law, B., Lee, X., Litvak, M., Liu, H., Munger, J. W., Noormets, A., Novick, K., Oberbauer, S. F., Oechel, W., Oikawa, P., Papuga, S. A., Pendall, E., Prajapati, P., Prueger, J., Quinton, W. L., Richardson, A. D., Russell, E. S., Scott, R. L., Starr, G., Staebler, R., Stoy, P. C., Stuart-Haëntjens, E., Sonnentag, O., Sullivan, R. C., Suyker, A., Ueyama, M., Vargas, R., Wood, J. D., Zona, D. (2021) Representativeness Of Eddy-Covariance Flux Footprints For Areas Surrounding Ameriflux Sites, Agricultural And Forest Meteorology, 301-302, 108350. https://doi.org/10.1016/j.agrformet.2021.108350
2016 Novick, K. A., Ficklin, D. L., Stoy, P. C., Williams, C. A., Bohrer, G., Oishi, A., Papuga, S. A., Blanken, P. D., Noormets, A., Sulman, B. N., Scott, R. L., Wang, L., Phillips, R. P. (2016) The Increasing Importance Of Atmospheric Demand For Ecosystem Water And Carbon Fluxes, Nature Climate Change, 6(11), 1023-1027. https://doi.org/10.1038/nclimate3114
2014 Matheny, A. M., Bohrer, G., Stoy, P. C., Baker, I. T., Black, A. T., Desai, A. R., Dietze, M. C., Gough, C. M., Ivanov, V. Y., Jassal, R. S., Novick, K. A., Schäfer, K. V., Verbeeck, H. (2014) Characterizing The Diurnal Patterns of Errors in The Prediction of Evapotranspiration by Several Land-Surface Models: An Nacp Analysis, Journal Of Geophysical Research: Biogeosciences, 119(7), 1458-1473. https://doi.org/10.1002/2014JG002623
2018 Chu, H., Baldocchi, D. D., Poindexter, C., Abraha, M., Desai, A. R., Bohrer, G., Arain, M. A., Griffis, T., Blanken, P. D., O'Halloran, T. L., Thomas, R. Q., Zhang, Q., Burns, S. P., Frank, J. M., Christian, D., Brown, S., Black, T. A., Gough, C. M., Law, B. E., Lee, X., Chen, J., Reed, D. E., Massman, W. J., Clark, K., Hatfield, J., Prueger, J., Bracho, R., Baker, J. M., Martin, T. A. (2018) Temporal Dynamics Of Aerodynamic Canopy Height Derived From Eddy Covariance Momentum Flux Data Across North American Flux Networks, Geophysical Research Letters, 45, 9275–9287. https://doi.org/10.1029/2018GL079306
2015 Dennis Baldocchi, Cove Sturtevant (2015) Does day and night sampling reduce spurious correlation between canopy photosynthesis and ecosystem respiration?, Agricultural and Forest Meteorology, 207, 117-126. https://doi.org/10.1016/j.agrformet.2015.03.010
2004 Post, W. M., Izaurralde, R. C., Jastrow, J. D., McCarl, B. A., Amonette, J. E., Bailey, V. L., Jardine, P. M., West, T. O., Zhou, J. (2004) Enhancement Of Carbon Sequestration In US Soils, Bioscience, 54(10), 895-908. https://doi.org/10.1641/0006-3568(2004)054[0895:eocsiu]2.0.co;2
2008 Matamala, R., Jastrow, J. D., Miller, R. M., Garten, C. T. (2008) Temporal Changes In C And N Stocks Of Restored Prairie: Implications For C Sequestration Strategies, Ecological Applications, 18(6), 1470-1488. https://doi.org/10.1890/07-1609.1
2005 Allison, V. J., Miller, R. M., Jastrow, J. D., Matamala, R., Zak, D. R. (2005) Changes In Soil Microbial Community Structure In A Tallgrass Prairie Chronosequence, Soil Science Society Of America Journal, 69(5), 1412-1421. https://doi.org/10.2136/sssaj2004.0252
1987 Jastrow, J. D. (1987) Changes In Soil Aggregation Associated With Tallgrass Prairie Restoration, American Journal Of Botany, 74(11), 1656-1664. https://doi.org/10.2307/2444134
1998 Jastrow, J., Miller, R., Lussenhop, J. (1998) Contributions Of Interacting Biological Mechanisms To Soil Aggregate Stabilization In Restored Prairie, Soil Biology And Biochemistry, 30(7), 905-916. https://doi.org/10.1016/s0038-0717(97)00207-1
1996 Jastrow, J. (1996) Soil Aggregate Formation And The Accrual Of Particulate And Mineral-Associated Organic Matter, Soil Biology And Biochemistry, 28(4-5), 665-676. https://doi.org/10.1016/0038-0717(95)00159-x
2002 Sluis, W. J. (2002) Patterns Of Species Richness And Composition In Re-Created Grassland, Restoration Ecology, 10(4), 677-684. https://doi.org/10.1046/j.1526-100x.2002.01048.x
2002 Miller, R. M., Miller, S. P., Jastrow, J. D., Rivetta, C. B. (2002) Mycorrhizal Mediated Feedbacks Influence Net Carbon Gain And Nutrient Uptake In Andropogon Gerardii, New Phytologist, 155(1), 149-162. https://doi.org/10.1046/j.1469-8137.2002.00429.x

US-IB2: Fermi National Accelerator Laboratory- Batavia (Prairie site)

BADM for This Site

Access the Biological, Ancillary, Disturbance and Metadata (BADM) information and data for this site.

BADM contain information for many uses, such as characterizing a site’s vegetation and soil, describing disturbance history, and defining instrumentation for flux processing. They complement the flux/met data.

* Online updates are shown on the Overview tab real time. However, downloaded BADM files will not reflect those updates until they have been reviewed for QA/QC.

US-IB2: Fermi National Accelerator Laboratory- Batavia (Prairie site)

Wind Roses

Click an image below to enlarge it, or use the navigation panel.
  • Image scale: 756m x 756m
  • Data Collected:
    • Wind roses use variables ‘WS’ and ‘WD’.
    Download Data Download Wind Rose as Image File (PNG)

    Wind Speed (m/s)

  • Graph Type
  • Wind Speed Scale
  • Wind Direction Scale (%)
  • Show Satellite Image
  • Show Wind Rose
    • Annual Average
    About Ameriflux Wind Roses
    Wind Rose Explanation
    A wind rose gives a succinct view of how wind speed and direction are typically distributed at a particular location. Presented in a circular format, a wind rose shows the frequency and intensity of winds blowing from particular directions. The length of each “spoke” around the circle indicates the amount of time (frequency) that the wind blows from a particular direction. Colors along the spokes indicate categories of wind speed (intensity). Each concentric circle represents a different frequency, emanating from zero at the center to increasing frequencies at the outer circles
    Utility
    This information can be useful to gain insight into regions surrounding a flux tower that contribute to the measured fluxes, and how those regions change in dependence of the time of day and season. The wind roses presented here are for four periods of the year, and in 16 cardinal directions. Graphics are available for all sites in the AmeriFlux network based on reported wind measurements at each site.
    Data from each site can be downloaded by clicking the ‘download’ button.
    Hover the cursor over a wind rose to obtain directions, speeds and intensities.
    Note that wind roses are not equivalent to flux footprints. Specifically, the term flux footprint describes an upwind area “seen” by the instruments measuring vertical turbulent fluxes, such that heat, water, gas and momentum transport generated in this area is registered by the instruments. Wind roses, on the other hand, identify only the direction and speed of wind.
    Where do these data come from?
    The wind roses are based on observed hourly data from the sites registered with the AmeriFlux Network.
    Parameters for AmeriFlux Wind Roses
    To use wind roses for a single AmeriFlux site, the following parameters may be most useful:
    • Wind Speed Scale: Per Site
    • Wind Direction Scale (%): Per Site
    To compare wind roses from more than one single AmeriFlux site, the following parameters may be most useful:
    • Wind Speed Scale: Non-Linear
    • Wind Direction Scale (%): AmeriFlux
    Mar - Jun; 6am - 6pm
    Mar - Jun; 6pm - 6am
    Jun - Sep; 6am - 6pm
    Jun - Sep; 6pm - 6am
    Sep - Dec; 6am - 6pm
    Sep - Dec; 6pm - 6am
    Dec - Mar; 6am - 6pm
    Dec - Mar; 6pm - 6am