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US-IB1
US-IB1: Fermi National Accelerator Laboratory- Batavia (Agricultural site)
Windroses
Data Use Log
Tower_team:
PI: Roser Matamala matamala@anl.gov - Argonne National Laboratory
FluxContact: David Cook dsgcook@prodigy.net - Argonne National Laboratory
Lat, Long: 41.8593, -88.2227
Elevation(m): 226.5
Network Affiliations: AmeriFlux
Vegetation IGBP: CRO (Croplands: Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type.)
Climate Koeppen: Dfa (Humid Continental: humid with severe winter, no dry season, hot summer)
Mean Annual Temp (°C): 9.18
Mean Annual Precip. (mm): 929.23
Flux Species Measured: CO2
Years Data Collected: 2005 - Present
Years Data Available:
AmeriFlux BASE 2005 - 2018 Data Citation
Data Use Policy: AmeriFlux Legacy Policy
Two eddy correlation systems are installed at Fermi National Accelerator Laboratory: one on a restored prairie (established October 2004) and one on a ...
Two eddy correlation systems are installed at Fermi National Accelerator Laboratory: one on a restored prairie (established October 2004) and one on a corn/soybean rotation agricultural field (established in July 2005). The prairie site had been farmed for more than 100 years, but was converted to prairie in 1989. The agricultural site has likely been farmed for more than 100 years, but the first documented instance of agricultural activity dates back to a picture taken in 1952.
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URL: http://www.atmos.anl.gov/FERMI/index.html
Research Topics:
The primary objectives of the proposed study are to (1) compare net ecosystem production derived by integrating eddy covariance estimates of net ecosystem ...
The primary objectives of the proposed study are to (1) compare net ecosystem production derived by integrating eddy covariance estimates of net ecosystem exchange over time with independent biometric measurements of ecosystem carbon stocks, and (2) compare carbon dynamics and stocks for the two management practices. The study contributes to the North American Carbon Program by providing information on the magnitude and distribution of carbon stocks and the processes that control carbon dynamics in cultivated and CRP-restored land in the U.S. Midwest.
Acknowledgment: —
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Use the information below for citation of this site. See the Data Policy page for more details.
DOI(s) for citing US-IB1 data
AmeriFlux BASE: https://doi.org/10.17190/AMF/1246065
Citation: Roser Matamala (2019), AmeriFlux BASE US-IB1 Fermi National Accelerator Laboratory- Batavia (Agricultural site), Ver. 8-5, AmeriFlux AMP, (Dataset). https://doi.org/10.17190/AMF/1246065
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
AmeriFlux Logos & Acknowledgments
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MODIS NDVI
The time series shows the 16-day Normalized Difference Vegetation Index (NDVI) average from the MOD13Q1 data product.
Use the slider below the time series to zoom in and out.
Includes all pixels that have acceptable quality
To view / download these data and other MOD13Q1 products for this site, visit MODIS/Terra Vegetation Indices.
For other related products, visit MODIS/VIIRS Fixed Sites Subsets Tool.
ORNL DAAC. 2018. MODIS and VIIRS Land Products Fixed Sites Subsetting and Visualization Tool. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1567
Read more on how to cite these MODIS products. Data come from NASA's MODIS instruments installed on satellites Terra and Aqua, which scan the entire Earth's surface every one to two days.
MODIS NDVI subsetted data is not yet available for this site.
For a complete list of AmeriFlux sites, visit ORNL DAAC's MODIS/VIIRS Fixed Sites Subsets Tool.
Search Publications for this Site Publications Found: 12
AmeriFlux Publications Add Publication
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
2013 Barr, A., Richardson, A., Hollinger, D., Papale, D., Arain, M., Black, T., Bohrer, G., Dragoni, D., Fischer, M., Gu, L., Law, B., Margolis, H., McCaughey, J., Munger, J., Oechel, W., Schaeffer, K. (2013) Use Of Change-Point Detection For Friction–Velocity Threshold Evaluation In Eddy-Covariance Studies, Agricultural And Forest Meteorology, 171-172, 31-45. https://doi.org/10.1016/j.agrformet.2012.11.023
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
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
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.
Download BADM for this site*
View Site General Info for this site (Overview tab)*
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* 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.
Click an image below to enlarge it, or use the navigation panel.
Image scale: 756m x 756m
Image scale: 1512m x 1512m
Data Collected:
Wind roses use variables 'WS' and 'WD'.
Download Data Download Wind Rose as Image File (PNG)
Wind Speed (m/s)
Annual Annual Average
Mar-Jun 6AM to 6PM 6PM to 6AM
Jun-Sep 6AM to 6PM 6PM to 6AM
Sep-Dec 6AM to 6PM 6PM to 6AM
Dec-Mar 6AM to 6PM 6PM to 6AM
Graph Type Sector Bar
Wind Speed Scale Per Site Non-Linear
Wind Direction Scale (%) Per Site AmeriFlux
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
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