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US-Kon: Konza Prairie LTER (KNZ)

Tower_team:
PI: Nathaniel Brunsell brunsell@ku.edu - Kansas University
DataManager: Bryan Conrad bryan.j.conrad@ku.edu - Kansas University
Technician: Jeff Taylor jht@ksu.edu - Kansas State University
Lat, Long: 39.0824, -96.5603
Elevation(m): 417
Network Affiliations: AmeriFlux, Phenocam
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: Cfa (Humid Subtropical: mild with no dry season, hot summer)
Mean Annual Temp (°C): 12.77
Mean Annual Precip. (mm): 867
Flux Species Measured: CO2, H2O
Years Data Collected: 2006 - Present
Years Data Available:2004 - 2019   DOIs to use for Citation of Data
Description: Burned on an annual basis. Bison reintroduced in 1987. Experimental cattle herds in 1992
URL: http://www.konza.ksu.edu
Research Topics: —
Acknowledgment: —
Site Photo More Site Images
Image Credit:
Copyright preference: Request for permission
Site Publication More Site Publications

US-Kon: Konza Prairie LTER (KNZ)

DOIs for this site and other citation information

Citations: For data, use the DOI citation. For site characterization, use the site publication. For funding, use acknowledgments.

DOIs to use for Citation of Data

  • AmeriFlux
  • Citation: Nathaniel Brunsell (2020), AmeriFlux US-Kon Konza Prairie LTER (KNZ), Ver. 5-5, AmeriFlux AMP, (Dataset). https://doi.org/10.17190/AMF/1246068
  • Link: https://doi.org/10.17190/AMF/1246068

Publication(s) to use for citations of site characterization

    —

Acknowledgements

    —

Resources

US-Kon: Konza Prairie LTER (KNZ)

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

NOTE: Version refers to the version of the AmeriFlux BASE-BADM product for the site was downloaded by the user and the download count indicates the number of times the person downloaded that version.

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US-Kon: Konza Prairie LTER (KNZ)

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.

Citation:

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.

US-Kon: Konza Prairie LTER (KNZ)

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.
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.
2001 Antunes, M. A. H., Walter-Shea, E. A., Mesarch, M. A. (2001) Test Of An Extended Mathematical Approach To Calculate Maize Leaf Area Index And Leaf Angle Distribution, Agricultural And Forest Meteorology, 108(1), 45-53.
2003 Danner, B. T., Knapp, A. K. (2003) Abiotic Constraints On The Establishment Of Quercus Seedlings In Grassland, Global Change Biology, 9(2), 266-275.
1999 Turner, D. P., Cohen, W. B., Kennedy, R. E., Fassnacht, K. S., Briggs, J. M. (1999) Relationships Between Leaf Area Index And Landsat TM Spectral Vegetation Indices Across Three Temperate Zone Sites, Remote Sensing Of Environment, 70(1), 52-68.
1999 Smith, M. D., Hartnett, D. C., Wilson, G. W. (1999) Interacting Influence Of Mycorrhizal Symbiosis And Competition On Plant Diversity In Tallgrass Prairie, Oecologia, 121(4), 574-582.
1999 Reich, P. B., Turner, D. P., Bolstad, P. (1999) An Approach To Spatially Distributed Modeling Of Net Primary Production (NPP) At The Landscape Scale And Its Application In Validation Of EOS NPP Products, Remote Sensing Of Environment, 70(1), 69-81.
2003 Turner, D. P., Urbanski, S., Bremer, D., Wofsy, S. C., Meyers, T., Gower, S. T., Gregory, M. (2003) A Cross-Biome Comparison Of Daily Light Use Efficiency For Gross Primary Production, Global Change Biology, 9(3), 383-395.
2002 Scurlock, J. M., Johnson, K., Olson, R. J. (2002) Estimating Net Primary Productivity From Grassland Biomass Dynamics Measurements, Global Change Biology, 8(8), 736-753.
1999 Bremer, D. J., Ham, J. M. (1999) Effect Of Spring Burning On The Surface Energy Balance In A Tallgrass Prairie, Agricultural And Forest Meteorology, 97(1), 43-54.
2016 Wolf, S., Keenan, T.F., Fisher, J.B., Baldocchi, D.D., Desai, A.R., Richardson, A.D., Scott, R.L., Law, B.E., Litvak, M.E., Brunsell, N.A., Peters, W., van der Laan-Luijkx, I.T. (2016) Warm spring reduced carbon cycle impact of the 2012 US summer drought, Proceedings of the National Academy of Sciences, 113(21), 5880-5885.

US-Kon: Konza Prairie LTER (KNZ)

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-Kon: Konza Prairie LTER (KNZ)

Wind Roses

Click an image below to enlarge it, or use the navigation panel.
  • Image scale: 788m x 788m
  • 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