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US-GLE: GLEES

Tower_team:
PI: Bill Massman wmassman@fs.fed.us - USDA Forest Service
DataManager: John Frank jfrank@fs.fed.us - USDA Forest Service
Lat, Long: 41.36653, -106.2399
Elevation(m): 3197
Network Affiliations: AmeriFlux
Vegetation IGBP: ENF (Evergreen Needleleaf Forests: Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage.)
Climate Koeppen: Dfc (Subarctic: severe winter, no dry season, cool summer)
Mean Annual Temp (°C): 0.80
Mean Annual Precip. (mm): 1200
Flux Species Measured: CO2, H, H2O
Years Data Collected: 2004 - Present
Years Data Available:1999 - 2018
Description:
The Glacier Lakes Ecosystem Experiments Site (GLEES) site is located on land owned by the U.S. government and managed by US Forest Service as part of the ...
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URL: http://www.fs.fed.us/rmrs/experimental-forests-and-ranges/glees-glacier-lakes-ecosystem-experiments-site
Research Topics:
The main analytical objectives of the GLEES AmeriFlux site include the flux measurements of momentum, sensible heat, water vapor, latent heat, and CO2 ...
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Acknowledgment: —
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Image Credit:
Copyright preference: Request for permission
Site Publication More Site Publications

US-GLE: GLEES

Instructions for DOIs for This Site

When using DOIs for this site, use the publications and acknowledgments listed below.

DOIs

Publications to use for Citations for this Site

    —

Acknowledgements

    —

Resources

US-GLE: GLEES

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. The download count indicates the number of times the person downloaded the data.

Year Range
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US-GLE: GLEES

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-GLE: GLEES

Year Publication
2020 Mercer, J. J., Liefert, D. T., Williams, D. G. (2020) Atmospheric Vapour And Precipitation Are Not In Isotopic Equilibrium In A Continental Mountain Environment, Hydrological Processes, .
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.
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.
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.
2019 Frank, J. M., Massman, W. J., Ewers, B. E., Williams, D. G. (2019) Bayesian Analyses of 17 Winters of Water Vapor Fluxes Show Bark Beetles Reduce Sublimation, Water Resources Research, 55(2), 1598-1623.
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.
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.
2018 Baldocchi, D., Penuelas, J. (2018) The Physics And Ecology Of Mining Carbon Dioxide From The Atmosphere By Ecosystems, Global Change Biology, .
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.
2018 Helliker, B. R., Song, X., Goulden, M. L., Clark, K., Bolstad, P., Munger, J. W., Chen, J., Noormets, A., Hollinger, D., Wofsy, S., Martin, T., Baldocchi, D., Euskirchenn, E., Desai, A., Burns, S. P. (2018) Assessing The Interplay Between Canopy Energy Balance And Photosynthesis With Cellulose δ18o: Large-Scale Patterns And Independent Ground-Truthing, Oecologia, .
2005 Arain, M. A., Restrepo-Coupe, N. (2005) Net Ecosystem Production In A Temperate Pine Plantation In Southeastern Canada, Agricultural And Forest Meteorology, 128(3-4), 223-241.
2015 Speckman, H. N., Frank, J. M., Bradford, J. B., Miles, B. L., Massman, W. J., Parton, W. J., Ryan, M. G. (2015) Forest Ecosystem Respiration Estimated From Eddy Covariance And Chamber Measurements Under High Turbulence And Substantial Tree Mortality From Bark Beetles, Global Change Biology, 21(2), 708-721.
2000 McDowell, N. G., Marshall, J. D., Hooker, T. D., Musselman, R. (2000) Estimating CO2 Flux From Snowpacks At Three Sites In The Rocky Mountains, Tree Physiology, 20(11), 745-753.
2000 Zeller, K., Nikolov, N. (2000) Quantifying Simultaneous Fluxes Of Ozone, Carbon Dioxide And Water Vapor Above A Subalpine Forest Ecosystem, Environmental Pollution, 107(1), 1-20.
2014 Frank, J. M., Massman, W. J., Ewers, B. E., Huckaby, L. S., Negrón, J. F. (2014) Ecosystem CO2 /H2O Fluxes Are Explained By Hydraulically Limited Gas Exchange During Tree Mortality From Spruce Bark Beetles, Journal Of Geophysical Research: Biogeosciences, 119(6), 1195-1215.
2005 Del Grosso, S., Parton, W., Mosier, A., Holland, E., Pendall, E., Schimel, D., Ojima, D. (2005) Modeling Soil CO2 Emissions From Ecosystems, Biogeochemistry, 73(1), 71-91.
2008 Bradford, J. B., Birdsey, R. A., Joyce, L. A., Ryan, M. G. (2008) Tree Age, Disturbance History, And Carbon Stocks And Fluxes In Subalpine Rocky Mountain Forests, Global Change Biology, 14(12), 2882-2897.

US-GLE: GLEES

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-GLE: GLEES

Wind Roses

Click an image below to enlarge it, or use the navigation panel.
  • Image scale: 762m x 762m
  • 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