CA-Let: Alberta - Mixed Grass Prairie
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| Tower_team: | |
| PI: | Lawrence B. Flanagan larry.flanagan@uleth.ca - |
| Lat, Long: | 49.7093, -112.9402 |
| Elevation(m): | 960 |
| Network Affiliations: | AmeriFlux, Fluxnet-Canada, 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: | Dfb (Warm Summer Continental: significant precipitation in all seasons ) |
| Mean Annual Temp (°C): | 5.36 |
| Mean Annual Precip. (mm): | 398.4 |
| Flux Species Measured: | CO2 |
| Years Data Collected: | 1998 - Present |
| Years Data Available: | AmeriFlux BASE 1998 - 2008 Data Citation |
| Data Use Policy: | AmeriFlux Legacy Policy |
| Description: | Latitude 49.43° N; Longitude 112.56° W, altitude 951 meters,Mixed Grass Prairie that includes the following major species: Agropyron spp. (Wheat Grasses), ... Latitude 49.43° N; Longitude 112.56° W, altitude 951 meters,Mixed Grass Prairie that includes the following major species: Agropyron spp. (Wheat Grasses), Tragopogon dubius (Goat’s Beard), Vicia americana (Wild Vetch), Koleria cristata (June Grass), Eurotia lanata (Winter Fat), Stipa comata (Spear Grass), Achillea millefolium (Yarrow); Artemisia frigida (Pasture Sage); Carex spp. (Sedges), Bouteloua gracilis (Blue Grama Grass). Maximum canopy height varies from year to year See MoreShow Less |
| URL: | — |
| Research Topics: | — |
| Acknowledgment: | — |
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CA-Let: Alberta - Mixed Grass Prairie
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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 CA-Let data
Data Use Policy: AmeriFlux Legacy Policy
- AmeriFlux BASE: https://doi.org/10.17190/AMF/1436318
Citation: Lawrence B. Flanagan (2018), AmeriFlux BASE CA-Let Alberta - Mixed Grass Prairie, Ver. 1-5, AmeriFlux AMP, (Dataset). https://doi.org/10.17190/AMF/1436318
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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CA-Let: Alberta - Mixed Grass Prairie
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This page displays the list of downloads of data for the site CA-Let.
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 |
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| Date | Name | Data Product | Vers. | Intended Use | Intended Use Description | Download Count |
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CA-Let: Alberta - Mixed Grass Prairie
- Overview
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- MODIS
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CA-Let: Alberta - Mixed Grass Prairie
- 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 CA-Let:
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 CA-Let, 49.7093, -112.9402.
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 CA-Let.
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 CA-Let.
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 CA-Let.
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 CA-Let.
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.
CA-Let: Alberta - Mixed Grass Prairie
- Overview
- Windroses
- Data Citation
- Data Use Log
- Image Gallery
- Remote Sensing Data
- MODIS
- PhenoCam
- GeoNEX
- Publications
- BADM
Search Publications for this Site
Publications Found: 16
| 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 |
| 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 |
| 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 |
| 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 |
| 2006 | Ponton, S., Flanagan, L. B., Alstad, K. P., Johnson, B. G., Morgenstern, K., Kljun, N., Black, T. A., Barr, A. G. (2006) Comparison Of Ecosystem Water-Use Efficiency Among Douglas-Fir Forest, Aspen Forest And Grassland Using Eddy Covariance And Carbon Isotope Techniques, Global Change Biology, 12(2), 294-310. https://doi.org/10.1111/j.1365-2486.2005.01103.x |
| 2006 | Coursolle, C., Margolis, H. A., Barr, A. G., Black, T. A., Amiro, B. D., McCaughey, J. H., Flanagan, L. B., Lafleur, P. M., Roulet, N. T., Bourque, C. P., Arain, M. A., Wofsy, S. C., Dunn, A., Morgenstern, K., Orchansky, A. L., Bernier, P. Y., Chen, J. M., Kidston, J., Saigusa, N., Hedstrom, N. (2006) Late-Summer Carbon Fluxes From Canadian Forests And Peatlands Along An East-West Continental Transect, Canadian Journal Of Forest Research, 36(3), 783-800. https://doi.org/10.1139/x05-270 |
| 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 |
| 2005 | Zhang, Y., Grant, R., Flanagan, L., Wang, S., Verseghy, D. (2005) Modelling CO2 And Energy Exchanges In A Northern Semiarid Grassland Using The Carbon- And Nitrogen-Coupled Canadian Land Surface Scheme (C-CLASS), Ecological Modelling, 181(4), 591-614. https://doi.org/10.1016/j.ecolmodel.2004.07.007 |
| 2005 | Gilmanov, T. G., Tieszen, L. L., Wylie, B. K., Flanagan, L. B., Frank, A. B., Haferkamp, M. R., Meyers, T. P., Morgan, J. A. (2005) Integration Of CO2 Flux And Remotely-Sensed Data For Primary Production And Ecosystem Respiration Analyses In The Northern Great Plains: Potential For Quantitative Spatial Extrapolation, Global Ecology And Biogeography, 14(3), 271-292. https://doi.org/10.1111/j.1466-822x.2005.00151.x |
| 2005 | Sims, D. A., Rahman, A. F., Cordova, V. D., Baldocchi, D. D., Flanagan, L. B., Goldstein, A. H., Hollinger, D. Y., Misson, L., Monson, R. K., Schmid, H. P., Wofsy, S. C., Xu, L. (2005) Midday Values Of Gross CO2 Flux And Light Use Efficiency During Satellite Overpasses Can Be Used To Directly Estimate Eight-Day Mean Flux, Agricultural And Forest Meteorology, 131(1-2), 1-12. https://doi.org/10.1016/j.agrformet.2005.04.006 |
| 2005 | Flanagan, L. B., Johnson, B. G. (2005) Interacting Effects Of Temperature, Soil Moisture And Plant Biomass Production On Ecosystem Respiration In A Northern Temperate Grassland, Agricultural And Forest Meteorology, 130(3-4), 237-253. https://doi.org/10.1016/j.agrformet.2005.04.002 |
| 2004 | Li, T., Grant, R. F., Flanagan, L. B. (2004) Climate Impact On Net Ecosystem Productivity Of A Semi-Arid Natural Grassland: Modeling And Measurement, Agricultural And Forest Meteorology, 126(1-2), 99-116. https://doi.org/10.1016/j.agrformet.2004.06.005 |
| 2003 | Conte, M. H., Weber, J. C., Carlson, P. J., Flanagan, L. B. (2003) Molecular And Carbon Isotopic Composition Of Leaf Wax In Vegetation And Aerosols In A Northern Prairie Ecosystem, Oecologia, 135(1), 67-77. https://doi.org/10.1007/s00442-002-1157-4 |
| 2002 | Flanagan, L. B., Wever, L. A., Carlson, P. J. (2002) Seasonal And Interannual Variation In Carbon Dioxide Exchange And Carbon Balance In A Northern Temperate Grassland, Global Change Biology, 8(7), 599-615. https://doi.org/10.1046/j.1365-2486.2002.00491.x |
| 1999 | Flanagan, L. B., Kubien, D. S., Ehleringer, J. R. (1999) Spatial And Temporal Variation In The Carbon And Oxygen Stable Isotope Ratio Of Respired CO2 In A Boreal Forest Ecosystem, Tellus Series B-Chemical and Physical Meteorology., 51(2), n/a-n/a. https://doi.org/10.3402/tellusb.v51i2.16306 |
| 1996 | Flanagan, L. B., Brooks, J. R., Varney, G. T., Berry, S. C., Ehleringer, J. R. (1996) Carbon Isotope Discrimination During Photosynthesis And The Isotope Ratio Of Respired CO2 in Boreal Forest Ecosystems, Global Biogeochemical Cycles, 10(4), 629-640. https://doi.org/10.1029/96gb02345 |
CA-Let: Alberta - Mixed Grass Prairie
- 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.
CA-Let: Alberta - Mixed Grass Prairie
- 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