US-Dk2: Duke Forest-hardwoods
- Overview
- Windroses
- Data Citation
- Data Use Log
- Image Gallery
- Remote Sensing Data
- MODIS
- PhenoCam
- GeoNEX
- Publications
- BADM
| Tower_team: | |
| PI: | A. Christopher Oishi andrew.c.oishi@usda.gov - USDA Forest Service |
| PI: | Kim Novick knovick@indiana.edu - Indiana University |
| PI: | Paul Stoy paul.stoy@montana.edu - Montana State University |
| Lat, Long: | 35.9736, -79.1004 |
| Elevation(m): | 168 |
| Network Affiliations: | AmeriFlux, Phenocam |
| Vegetation IGBP: | DBF (Deciduous Broadleaf Forests: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods.) |
| Climate Koeppen: | Cfa (Humid Subtropical: mild with no dry season, hot summer) |
| Mean Annual Temp (°C): | 14.36 |
| Mean Annual Precip. (mm): | 1168.69 |
| Flux Species Measured: | CO2 |
| Years Data Collected: | 2001 - 2008 |
| Years Data Available: | AmeriFlux BASE 2001 - 2008 Data Citation |
| Data Use Policy: | AmeriFlux CC-BY-4.0 Policy1 |
| Description: | private land adjacent to the Duke Forest in November 2002 |
| URL: | http://www.nicholas.duke.edu/other/AMERIFLUX/amerflux.html |
| Research Topics: | The research objectives of the Duke Forest Hardwoods site are as follows: 1) Examine ecological roles of vegetation and climate in controlling long-term ... The research objectives of the Duke Forest Hardwoods site are as follows: 1) Examine ecological roles of vegetation and climate in controlling long-term carbon exchange; 2) Determine the contribution of vegetation from that of climate and soils on controlling ET at three adjacent SE Piedmont ecosystems, namely the three Duke Forest Sites, US-Dk1, US-Dk2, and US-Dk3; 3) Quantify seasonal and annual forest floor CO2 efflux in a mature oak-hickory forest type, and to separate the effect of forest type from that of climate or soil on the magnitude and dynamics of forest floor CO2 efflux. (Stoy et al., 2008, Stoy et al., 2006, Palmroth et al., 2005) See MoreShow Less |
| Acknowledgment: | — |
Site Tasks
- 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.
US-Dk2
Site Photo
More Site Images
Site Publication
More Site Publications
US-Dk2: Duke Forest-hardwoods
- Overview
- Windroses
- Data Citation
- Data Use Log
- Image Gallery
- Remote Sensing Data
- MODIS
- PhenoCam
- GeoNEX
- Publications
- BADM
Use the information below for citation of this site. See the Data Policy page for more details.
DOI(s) for citing US-Dk2 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-Dk2 data are combined with data from sites that require the AmeriFlux Legacy Policy.
- AmeriFlux BASE: https://doi.org/10.17190/AMF/1246047
Citation: Chris Oishi, Kim Novick, Paul Stoy (2018), AmeriFlux BASE US-Dk2 Duke Forest-hardwoods, Ver. 4-5, AmeriFlux AMP, (Dataset). https://doi.org/10.17190/AMF/1246047
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
- AmeriFlux Logos & Acknowledgments
US-Dk2: Duke Forest-hardwoods
- Overview
- Windroses
- Data Citation
- Data Use Log
- Image Gallery
- Remote Sensing Data
- MODIS
- PhenoCam
- GeoNEX
- Publications
- BADM
This page displays the list of downloads of data for the site US-Dk2.
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.
| Date | Name | Data Product | Version | Intended Use | Intended Use Description | Download Count |
|---|
| Date | Name | Data Product | Vers. | Intended Use | Intended Use Description | Download Count |
|---|---|---|---|---|---|---|
Showing 0 to 0 of 0 results
Items Per Page:
Not Found
Uh Oh. Something is missing. Try double checking the URL and try again.
US-Dk2: Duke Forest-hardwoods
- Overview
- Windroses
- Data Citation
- Data Use Log
- Image Gallery
- Remote Sensing Data
- MODIS
- PhenoCam
- GeoNEX
- Publications
- BADM
Search Images for this Site Images found : 0
| AmeriFlux Images | Add Image |
No photos found matching your search criteria. Check back soon!
US-Dk2: Duke Forest-hardwoods
- Overview
- Windroses
- Data Citation
- Data Use Log
- Image Gallery
- Remote Sensing Data
- MODIS
- PhenoCam
- GeoNEX
- Publications
- BADM
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. Terrestrial Ecology Subsetting & Visualization Services (TESViS) Fixed Sites Subsets. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1567
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.
PhenoCam Images and Derived Time Series Data
PhenoCams are high-resolution digital cameras that take repeated images of studied ecosystems and provide quantitative information about the canopy phenology. The PhenoCam Network coordinates the camera installation and data reporting/analyses across sites in the Americas, providing automated, near-surface remote sensing of canopy phenology across a range of ecosystems and climate zones. Use of PhenoCam images / data should follow the PhenoCam Data Use Policy .
PhenoCam sites for US-Dk2:
Use the links below to explore camera images and interactive timeseries for these sites.
Citation:
B. Seyednasrollah, A. M. Young, K. Hufkens, T. Milliman, M. A. Friedl, S. Frolking, and A. D. Richardson. Tracking vegetation phenology across diverse biomes using version 2.0 of the phenocam dataset. Scientific Data, 6(1):222, 2019. doi:10.1038/s41597-019-0229-9Camera Imagery
Milliman, T., B. Seyednasrollah, A.M. Young, K. Hufkens, M.A. Friedl, S. Frolking, A.D. Richardson, M. Abraha, D.W. Allen, M. Apple, M.A. Arain, J.M. Baker, D. Baldocchi, C.J. Bernacchi, J. Bhattacharjee, P. Blanken, D.D. Bosch, R. Boughton, E.H. Boughton, R.F. Brown, D.M. Browning, N. Brunsell, S.P. Burns, M. Cavagna, H. Chu, P.E. Clark, B.J. Conrad, E. Cremonese, D. Debinski, A.R. Desai, R. Diaz-Delgado, L. Duchesne, A.L. Dunn, D.M. Eissenstat, T. El-Madany, D.S.S. Ellum, S.M. Ernest, A. Esposito, L. Fenstermaker, L.B. Flanagan, B. Forsythe, J. Gallagher, D. Gianelle, T. Griffis, P. Groffman, L. Gu, J. Guillemot, M. Halpin, P.J. Hanson, D. Hemming, A.A. Hove, E.R. Humphreys, A. Jaimes-Hernandez, A.A. Jaradat, J. Johnson, E. Keel, V.R. Kelly, J.W. Kirchner, P.B. Kirchner, M. Knapp, M. Krassovski, O. Langvall, G. Lanthier, G.l. Maire, E. Magliulo, T.A. Martin, B. McNeil, G.A. Meyer, M. Migliavacca, B.P. Mohanty, C.E. Moore, R. Mudd, J.W. Munger, Z.E. Murrell, Z. Nesic, H.S. Neufeld, W. Oechel, A.C. Oishi, W.W. Oswald, T.D. Perkins, M.L. Reba, B. Rundquist, B.R. Runkle, E.S. Russell, E.J. Sadler, A. Saha, N.Z. Saliendra, L. Schmalbeck, M.D. Schwartz, R.L. Scott, E.M. Smith, O. Sonnentag, P. Stoy, S. Strachan, K. Suvocarev, J.E. Thom, R.Q. Thomas, A.K. Van den berg, R. Vargas, J. Verfaillie, C.S. Vogel, J.J. Walker, N. Webb, P. Wetzel, S. Weyers, A.V. Whipple, T.G. Whitham, G. Wohlfahrt, J.D. Wood, J. Yang, X. Yang, G. Yenni, Y. Zhang, Q. Zhang, and D. Zona. 2019. PhenoCam Dataset v2.0: Digital Camera Imagery from the PhenoCam Network, 2000-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1689
Green Chromatic Coordinate Time Series
Seyednasrollah, B., A.M. Young, K. Hufkens, T. Milliman, M.A. Friedl, S. Frolking, A.D. Richardson, M. Abraha, D.W. Allen, M. Apple, M.A. Arain, J. Baker, J.M. Baker, D. Baldocchi, C.J. Bernacchi, J. Bhattacharjee, P. Blanken, D.D. Bosch, R. Boughton, E.H. Boughton, R.F. Brown, D.M. Browning, N. Brunsell, S.P. Burns, M. Cavagna, H. Chu, P.E. Clark, B.J. Conrad, E. Cremonese, D. Debinski, A.R. Desai, R. Diaz-Delgado, L. Duchesne, A.L. Dunn, D.M. Eissenstat, T. El-Madany, D.S.S. Ellum, S.M. Ernest, A. Esposito, L. Fenstermaker, L.B. Flanagan, B. Forsythe, J. Gallagher, D. Gianelle, T. Griffis, P. Groffman, L. Gu, J. Guillemot, M. Halpin, P.J. Hanson, D. Hemming, A.A. Hove, E.R. Humphreys, A. Jaimes-Hernandez, A.A. Jaradat, J. Johnson, E. Keel, V.R. Kelly, J.W. Kirchner, P.B. Kirchner, M. Knapp, M. Krassovski, O. Langvall, G. Lanthier, G.l. Maire, E. Magliulo, T.A. Martin, B. McNeil, G.A. Meyer, M. Migliavacca, B.P. Mohanty, C.E. Moore, R. Mudd, J.W. Munger, Z.E. Murrell, Z. Nesic, H.S. Neufeld, T.L. O'Halloran, W. Oechel, A.C. Oishi, W.W. Oswald, T.D. Perkins, M.L. Reba, B. Rundquist, B.R. Runkle, E.S. Russell, E.J. Sadler, A. Saha, N.Z. Saliendra, L. Schmalbeck, M.D. Schwartz, R.L. Scott, E.M. Smith, O. Sonnentag, P. Stoy, S. Strachan, K. Suvocarev, J.E. Thom, R.Q. Thomas, A.K. Van den berg, R. Vargas, J. Verfaillie, C.S. Vogel, J.J. Walker, N. Webb, P. Wetzel, S. Weyers, A.V. Whipple, T.G. Whitham, G. Wohlfahrt, J.D. Wood, S. Wolf, J. Yang, X. Yang, G. Yenni, Y. Zhang, Q. Zhang, and D. Zona. 2019. PhenoCam Dataset v2.0: Vegetation Phenology from Digital Camera Imagery, 2000-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1674
GeoNEX Data Products
GeoNEX led by NASA Earth eXchange (NEX) is a collaborative effort for generating Earth monitoring products from the new generation of geostationary satellite sensors. GeoNEX has produced a suite of geostationary data products including surface reflectance, land surface temperature, surface solar radiation, and many others.
The GeoNEX Common Grid locates GeoNEX data in the geographic (latitude/longitude) projection. Pixels (grid cells) are created at regular 0.005°, 0.01°, and 0.02° resolutions.
GeoNEX pixels below cover the area 0.06° x 0.06° around and including site US-Dk2, 35.9736, -79.1004.
Click a square in the grid at left to display its data below.
Coordinates for selected GeoNEX Pixel
Graph controls:
- Zoom: click-drag
- Pan: shift-click-drag
- Restore zoom level: double-click
- Use the slider below the time series to zoom in and out.
All download requests will be logged.
NDVI: Normalized Difference Vegetation Index
No NDVI data have been received for site US-Dk2.
NDVI (unitless)
Resolution: 0.01° x 0.01° & 10 minutes
Coordinates for pixel:
NIRv Near-Infrared Reflectance of vegetation
No NIRv data have been received for site US-Dk2.
NIRv (unitless)
Resolution: 0.01° x 0.01° & 10 minutes
Coordinates for pixel:
DSR: Surface downward shortwave radiation
No DSR data have been received for site US-Dk2.
Shortwave Radiation (W/m2)
Resolution: 0.01° x 0.01° & Hourly
Coordinates for pixel:
LST: Land Surface Temperature
No LST data have been received for site US-Dk2.
LST (K)
Resolution: 0.02° x 0.02° & Hourly
Coordinates for pixel:
Citation
This material can be used without obtaining permission from NASA. NASA should be acknowledged as the source of this material.
Subset Data Citation:
- Hashimoto, H., Wang, W., Park, T., Khajehei, S., Ichii, K., Michaelis, A.R., Guzman, A., Nemani, R.R., Torn, M., Yi, K., Brosnan, I.G. (in preparation). Subsets of geostationary satellite data over international observing network sites for studying the diurnal dynamics of energy, carbon, and water cycles.
Relevant Science Publication Citation:
GeoNEX Surface Reflectance for Vegetation Indices (NDVI & NIRv)- Wang, W., Wang, Y., Lyapustin, A., Hashimoto, H., Park, T., Michaelis, A., & Nemani, R. (2022). A novel atmospheric correction algorithm to exploit the diurnal variability in hypertemporal geostationary observations. Remote Sensing, 14(4), 964.
- Li, R., Wang, D., Wang, W., & Nemani, R. (2023). A GeoNEX-based high-spatiotemporal-resolution product of land surface downward shortwave radiation and photosynthetically active radiation. Earth System Science Data, 15(3), 1419-1436.
- Jia, A., Liang, S., & Wang, D. (2022). Generating a 2-km, all-sky, hourly land surface temperature product from Advanced Baseline Imager data. Remote Sensing of Environment, 278, 113105.
US-Dk2: Duke Forest-hardwoods
- Overview
- Windroses
- Data Citation
- Data Use Log
- Image Gallery
- Remote Sensing Data
- MODIS
- PhenoCam
- GeoNEX
- Publications
- BADM
Search Publications for this Site
Publications Found: 17
| AmeriFlux Publications | Add Publication |
| 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 |
| 2020 | Zhang, Q., Barnes, M., Benson, M., Burakowski, E., Oishi, A. C., Ouimette, A., Sanders‐DeMott, R., Stoy, P. C., Wenzel, M., Xiong, L., Yi, K., Novick, K. A. (2020) Reforestation And Surface Cooling In Temperate Zones: Mechanisms And Implications, Global Change Biology, 26(6), 3384-3401. https://doi.org/10.1111/gcb.15069 |
| 2019 | Guerrieri, R., Belmecheri, S., Ollinger, S. V., Asbjornsen, H., Jennings, K., Xiao, J., Stocker, B. D., Martin, M., Hollinger, D. Y., Bracho-Garrillo, R., Clark, K., Dore, S., Kolb, T., Munger, J. W., Novick, K., Richardson, A. D. (2019) Disentangling The Role Of Photosynthesis And Stomatal Conductance On Rising Forest Water-Use Efficiency, Proceedings Of The National Academy Of Sciences, 116(34), 16909-16914. https://doi.org/10.1073/pnas.1905912116 |
| 2018 | Zhang, Q., Phillips, R. P., Manzoni, S., Scott, R. L., Oishi, A. C., Finzi, A., Daly, E., Vargas, R., Novick, K. A. (2018) Changes In Photosynthesis And Soil Moisture Drive The Seasonal Soil Respiration-Temperature Hysteresis Relationship, Agricultural And Forest Meteorology, 259, 184-195. https://doi.org/10.1016/j.agrformet.2018.05.005 |
| 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 |
| 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 |
| 2015 | Domec, J.C., Ward, E.J., Oishi, A.C., Palmroth, S., Radecki, A., Bell, D.M., Miao, G., Gavazzi, M., Johnson, D.M., King, J.S., McNulty, S.G., Oren, R., Sun, G., Noormets, A. (2015) Conversion of natural forests to managed forest plantations impacts tree response to climatic variable and affects negatively tree resistance to prolonged droughts, Forest Ecology and Management, 355, 58-71. https://doi.org/10.1016 |
| 2009 | Novick, K., Oren, R., Stoy, P., Siqueira, M., Katul, G. (2009) Nocturnal Evapotranspiration In Eddy-Covariance Records From Three Co-Located Ecosystems In The Southeastern U.S.: Implications For Annual Fluxes, Agricultural And Forest Meteorology, 149(9), 1491-1504. https://doi.org/10.1016/j.agrformet.2009.04.005 |
| 2008 | Oishi, A. C., Oren, R., Stoy, P. C. (2008) Estimating Components Of Forest Evapotranspiration: A Footprint Approach For Scaling Sap Flux Measurements, Agricultural And Forest Meteorology, 148(11), 1719-1732. https://doi.org/10.1016/j.agrformet.2008.06.013 |
| 2007 | Juang, J., Porporato, A., Stoy, P. C., Siqueira, M. S., Oishi, A. C., Detto, M., Kim, H., Katul, G. G. (2007) Hydrologic And Atmospheric Controls On Initiation Of Convective Precipitation Events, Water Resources Research, 43(3), n/a-n/a. https://doi.org/10.1029/2006WR004954 |
| 2006 | Oren, R., Hsieh, C., Stoy, P., Albertson, J., Mccarthy, H. R., Harrell, P., Katul, G. G. (2006) Estimating The Uncertainty In Annual Net Ecosystem Carbon Exchange: Spatial Variation In Turbulent Fluxes And Sampling Errors In Eddy-Covariance Measurements, Global Change Biology, 12(5), 883-896. https://doi.org/10.1111/j.1365-2486.2006.01131.x |
| 2006 | Siqueira, M. B., Katul, G. G., Sampson, D. A., Stoy, P. C., Juang, J., Mccarthy, H. R., Oren, R. (2006) Multiscale Model Intercomparisons Of CO2 And H2O Exchange Rates In A Maturing Southeastern US Pine Forest, Global Change Biology, 12(7), 1189-1207. https://doi.org/10.1111/j.1365-2486.2006.01158.x |
| 2005 | Butnor, J. R., Johnsen, K. H., Maier, C. A. (2005) Soil Properties Differently Influence Estimates Of Soil CO2 Efflux From Three Chamber-Based Measurement Systems, Biogeochemistry, 73(1), 283-301. https://doi.org/10.1007/s10533-004-4022-1 |
| 2004 | Bond-Lamberty, B., Wang, C., Gower, S. T. (2004) A Global Relationship Between The Heterotrophic And Autotrophic Components Of Soil Respiration?, Global Change Biology, 10(10), 1756-1766. https://doi.org/10.1111/j.1365-2486.2004.00816.x |
| 2004 | Ellsworth, D. S., Reich, P. B., Naumburg, E. S., Koch, G. W., Kubiske, M. E., Smith, S. D. (2004) Photosynthesis, Carboxylation And Leaf Nitrogen Responses Of 16 Species To Elevated pCO2 Across Four Free-Air CO2 Enrichment Experiments In Forest, Grassland And Desert, Global Change Biology, 10(12), 2121-2138. https://doi.org/10.1111/j.1365-2486.2004.00867.x |
| 2003 | Pataki, D., Oren, R. (2003) Species Differences In Stomatal Control Of Water Loss At The Canopy Scale In A Mature Bottomland Deciduous Forest, Advances In Water Resources, 26(12), 1267-1278. https://doi.org/10.1016/j.advwatres.2003.08.001 |
| 2003 | Katul, G., Leuning, R., Oren, R. (2003) Relationship Between Plant Hydraulic And Biochemical Properties Derived From A Steady-State Coupled Water And Carbon Transport Model, Plant, Cell And Environment, 26(3), 339-350. https://doi.org/10.1046/j.1365-3040.2003.00965.x |
US-Dk2: Duke Forest-hardwoods
- Overview
- Windroses
- Data Citation
- Data Use Log
- Image Gallery
- Remote Sensing Data
- MODIS
- PhenoCam
- GeoNEX
- Publications
- BADM
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)*
- Use Online Editor to update Site General Info or DOI Authorship
- Update information about submitted data (Variable Information tool)
- More BADM resources
* 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-Dk2: Duke Forest-hardwoods
- Overview
- Windroses
- Data Citation
- Data Use Log
- Image Gallery
- Remote Sensing Data
- MODIS
- PhenoCam
- GeoNEX
- Publications
- BADM
Wind Roses
Click an image below to enlarge it, or use the navigation panel.
Wind Speed (m/s)
Navigation
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