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US-Ne3: Mead - rainfed maize-soybean rotation site

Tower_team:
PI: Andy Suyker asuyker1@unl.edu - University of Nebraska - Lincoln
DataManager: Dan Hatch dhatch2@unl.edu - University of Nebraska
Lat, Long: 41.1797, -96.4397
Elevation(m): 363
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): 10.11
Mean Annual Precip. (mm): 783.68
Flux Species Measured: CO2
Years Data Collected: 2001 - Present
Years Data Available:

AmeriFlux BASE 2001 - 2024   Data Citation
Data Use Policy:AmeriFlux CC-BY-4.0 Policy1
Description:
The study site is one of three fields (all located within 1.6 km of each other) at the University of Nebraska Agricultural Research and Development Center ...
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URL: http://csp.unl.edu/public/
Research Topics:
The overall goals are to investigate the C sequestration potential of major rainfed and irrigated agroecosystems in the north-central USA and to understand ...
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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-Ne3: Mead - rainfed maize-soybean rotation site

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

DOI(s) for citing US-Ne3 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-Ne3 data are combined with data from sites that require the AmeriFlux Legacy Policy.

  • AmeriFlux BASE: https://doi.org/10.17190/AMF/1246086
    Citation: Andy Suyker (2024), AmeriFlux BASE US-Ne3 Mead - rainfed maize-soybean rotation site, Ver. 18-5, AmeriFlux AMP, (Dataset). https://doi.org/10.17190/AMF/1246086

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

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Acknowledgments

    —

Resources

US-Ne3: Mead - rainfed maize-soybean rotation site

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US-Ne3: Mead - rainfed maize-soybean rotation site

Year 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
2019 Novick, K. A., Konings, A. G., Gentine, P. (2019) Beyond Soil Water Potential: An Expanded View On Isohydricity Including Land–Atmosphere Interactions And Phenology, Plant, Cell & Environment, 42(6), 1802-1815. https://doi.org/10.1111/pce.13517
2019 Zhang, Q., Ficklin, D. L., Manzoni, S., Wang, L., Way, D., Phillips, R. P., Novick, K. A. (2019) Response Of Ecosystem Intrinsic Water Use Efficiency And Gross Primary Productivity To Rising Vapor Pressure Deficit, Environmental Research Letters, 14(7), 074023. https://doi.org/10.1088/1748-9326/ab2603
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
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 McCombs, A. G., Hiscox, A. L., Wang, C., Desai, A. R., Suyker, A. E., Biraud, S. C. (2018) Carbon Flux Phenology From The Sky: Evaluation For Maize And Soybean, Journal Of Atmospheric And Oceanic Technology, 35(4), 877-892. https://doi.org/https://doi.org/10.1175/JTECH-D-17-0004.1
2019 Sullivan, R. C., Kotamarthi, V. R., Feng, Y. (2019) Recovering Evapotranspiration Trends From Biased CMIP5 Simulations And Sensitivity To Changing Climate Over North America, Journal Of Hydrometeorology, 20(8), 1619-1633. https://doi.org/10.1175/JHM-D-18-0259.1
2019 Sullivan, R. C., Cook, D. R., Ghate, V. P., Kotamarthi, V. R., Feng, Y. (2019) Improved Spatiotemporal Representativeness And Bias Reduction Of Satellite-Based Evapotranspiration Retrievals Via Use Of In Situ Meteorology And Constrained Canopy Surface Resistance, Journal Of Geophysical Research: Biogeosciences, 124(2), 342-352. https://doi.org/10.1029/2018JG004744
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
2003 Dobermann, A., Ping, J. L., Adamchuk, V. I., Simbahan, G. C., Ferguson, R. B. (2003) Classification Of Crop Yield Variability In Irrigated Production Fields, Agronomy Journal, 95(5), 1105-1120. https://doi.org/10.2134/agronj2003.1105
2006 Richardson, A. D., Hollinger, D. Y., Burba, G. G., Davis, K. J., Flanagan, L. B., Katul, G. G., William Munger, J., Ricciuto, D. M., Stoy, P. C., Suyker, A. E., Verma, S. B., Wofsy, S. C. (2006) A Multi-Site Analysis Of Random Error In Tower-Based Measurements Of Carbon And Energy Fluxes, Agricultural And Forest Meteorology, 136(1-2), 1-18. https://doi.org/10.1016/j.agrformet.2006.01.007
2004 Simbahan, G. C., Dobermann, A., Ping, J. L. (2004) Screening Yield Monitor Data Improves Grain Yield Maps, Agronomy Journal, 96(4), 1091-1102. https://doi.org/10.2134/agronj2004.1091
2003 Gitelson, A. A., Viña, A., Arkebauer, T. J., Rundquist, D. C., Keydan, G., Leavitt, B. (2003) Remote Estimation Of Leaf Area Index And Green Leaf Biomass In Maize Canopies, Geophysical Research Letters, 30(5), n/a-n/a. https://doi.org/10.1029/2002gl016450
2005 Mahmood, R., Hubbard, K. G. (2005) Assessing Bias In Evapotranspiration And Soil Moisture Estimates Due To The Use Of Modeled Solar Radiation And Dew Point Temperature Data, Agricultural And Forest Meteorology, 130(1-2), 71-84. https://doi.org/10.1016/j.agrformet.2005.02.004
2004 Suyker, A., Verma, S., Burba, G., Arkebauer, T., Walters, D., Hubbard, K. (2004) Growing Season Carbon Dioxide Exchange In Irrigated And Rainfed Maize, Agricultural And Forest Meteorology, 124(1-2), 1-13. https://doi.org/10.1016/j.agrformet.2004.01.011
2004 Yang, H., Dobermann, A., Lindquist, J., Walters, D., Arkebauer, T., Cassman, K. (2004) Hybrid-Maize—A Maize Simulation Model That Combines Two Crop Modeling Approaches, Field Crops Research, 87(2-3), 131-154. https://doi.org/10.1016/j.fcr.2003.10.003
2005 Ping, J. L., Dobermann, A. (2005) Processing Of Yield Map Data, Precision Agriculture, 6(2), 193-212. https://doi.org/10.1007/s11119-005-1035-2
2006 Simbahan, G. C., Dobermann, A., Goovaerts, P., Ping, J., Haddix, M. L. (2006) Fine-Resolution Mapping Of Soil Organic Carbon Based On Multivariate Secondary Data, Geoderma, 132(3-4), 471-489. https://doi.org/10.1016/j.geoderma.2005.07.001
2004 Viña, A., Gitelson, A. A., Rundquist, D. C., Keydan, G., Leavitt, B., Schepers, J. (2004) Monitoring Maize (Zea Mays L.) Phenology With Remote Sensing, Agronomy Journal, 96(4), 1139-1147. https://doi.org/10.2134/agronj2004.1139
2004 Viña, A., Genebry, G.M., Gitelson, A. A. (2004) Satellite Monitoring Of Vegetation Dynamics: Sensitivity Enhancement By The Wide Dynamic Range Vegetation Index, Geophysical Research Letters, 31(4), 1-4. https://doi.org/10.1029/2003gl019034
2005 Amos, B., Arkebauer, T. J., Doran, J. W. (2005) Soil Surface Fluxes Of Greenhouse Gases In An Irrigated Maize-Based Agroecosystem, Soil Science Society Of America Journal, 69(2), 387-395. https://doi.org/10.2136/sssaj2005.0387
2003 Ping, J. L., Dobermann, A. (2003) Creating Spatially Contiguous Yield Classes For Site-Specific Management, Agronomy Journal, 95(5), 1121-1131. https://doi.org/10.2134/agronj2003.1121
2004 Gitelson, A. A. (2004) Wide Dynamic Range Vegetation Index For Remote Quantification Of Biophysical Characteristics Of Vegetation, Journal Of Plant Physiology, 161(2), 165-173. https://doi.org/10.1078/0176-1617-01176
2003 Gitelson, A. A., Verma, S. B., Rundquist, D. C., Keydan, G., Leavitt, B., Arkebauer, T. J., Burba, G. G., Suyker, A. E. (2003) Novel Technique For Remote Estimation Of CO2 Flux In Maize, Geophysical Research Letters, 30(9), 1486-n/a. https://doi.org/10.1029/2002gl016543
2003 Cassman, K. G., Dobermann, A., Walters, D. T., Yang, H. (2003) Meeting Cereal Demand While Protecting Natural Resources And Improving Environmental Quality, Annual Review Of Environment And Resources, 28(1), 315-358. https://doi.org/10.1146/annurev.energy.28.040202.122858
2005 Suyker, A. E., Verma, S. B., Burba, G. G., Arkebauer, T. J. (2005) Gross Primary Production And Ecosystem Respiration Of Irrigated Maize And Irrigated Soybean During A Growing Season, Agricultural And Forest Meteorology, 131(3-4), 180-190. https://doi.org/10.1016/j.agrformet.2005.05.007
2005 Verma, S. B., Dobermann, A., Cassman, K. G., Walters, D. T., Knops, J. M., Arkebauer, T. J., Suyker, A. E., Burba, G. G., Amos, B., Yang, H., Ginting, D., Hubbard, K. G., Gitelson, A. A., Walter-Shea, E. A. (2005) Annual Carbon Dioxide Exchange In Irrigated And Rainfed Maize-Based Agroecosystems, Agricultural And Forest Meteorology, 131(1-2), 77-96. https://doi.org/10.1016/j.agrformet.2005.05.003
2005 Ginting, D., Eghball, B. (2005) Nitrous Oxide Emission From No-Till Irrigated Corn, Soil Science Society Of America Journal, 69(3), 915-925. https://doi.org/10.2136/sssaj2004.0292

US-Ne3: Mead - rainfed maize-soybean rotation 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-Ne3: Mead - rainfed maize-soybean rotation site

Wind Roses

Click an image below to enlarge it, or use the navigation panel.
  • Image scale: 764m x 764m
  • 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