Tower_team:
PI:	Sonia Wharton wharton4@llnl.gov - Lawrence Livermore National Laboratory
Lat, Long:	45.8205, -121.9519
Elevation(m):	371
Network Affiliations:	AmeriFlux, Phenocam
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:	Csb (Mediterranean: mild with dry, warm summer)
Mean Annual Temp (°C):	8.8
Mean Annual Precip. (mm):	2452
Flux Species Measured:	CO2
Years Data Collected:	1998 - 2016
Years Data Available:	AmeriFlux BASE 1998 - 2015 Data Citation
Data Use Policy:	AmeriFlux CC-BY-4.0 Policy¹
Description:	Wind River Field Station flux tower site is located in the T.T. Munger Research Area of the Wind River Ranger District in the Gifford Pinchot National ... Wind River Field Station flux tower site is located in the T.T. Munger Research Area of the Wind River Ranger District in the Gifford Pinchot National Forest. Protected since 1926, the T.T. Munger Research Natural Area (RNA) is administered by the USDA Forest Service Pacific Northwest Research Station and Gifford Pinchot National Forest. The Douglas-fir/western hemlock dominant stand is approximately 500 years old and represents end points of several ecological gradients including age, biomass, structural complexity, and density of the dominant overstory species. A complete stand replacement fire, approximately 450-500 years ago, resulted in the initial establishment. No significant disturbances have occurred since the fire aside from those confined to small groups of single trees, such as overturn from high wind activity and mechanical damage from winter precipitation. See More Show Less
URL:	http://depts.washington.edu/wrccrf/
Research Topics:	Research and monitoring objectives are to 1) Describe the estimation of CO2 exchange from the oldest forest ecosystem (500 years old) in the AmeriFlux ... Research and monitoring objectives are to 1) Describe the estimation of CO2 exchange from the oldest forest ecosystem (500 years old) in the AmeriFlux network, based on eddy covariance, using accepted AmeriFlux correction techniques for low friction velocities and turbulence levels, and related advection calculation methods; 2) Examine the CO2 exchange response to diurnal, seasonal, annual, and interannual variations, and relate the exchange to meteorologic variables such as photosynthetically active radiation (PAR) and soil and air temperatures; 3) Relate measurements to ecosystem physiological processes and identify when the forest is a source or sink in relation to these processes; 4) support collaborative efforts with other ecological studies. See More Show Less
Acknowledgment:	—

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Site Publication More Site Publications

Wharton, S., Falk, M., Bible, K., Schroeder, M., Paw U, K.T. 2012. Old-Growth CO2 Flux Measurements Reveal High Sensitivity To Climate Anomalies Across Seasonal, Annual And Decadal Time Scales, Agricultural and Forest Meteorology, 161, 1-14.

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DOI(s) for citing US-Wrc data

Data Use Policy: AmeriFlux CC-BY-4.0 License

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The AmeriFlux Legacy Policy must be followed if US-Wrc data are combined with data from sites that require the AmeriFlux Legacy Policy.

AmeriFlux BASE: https://doi.org/10.17190/AMF/1246114
Citation: Sonia Wharton (2016), AmeriFlux BASE US-Wrc Wind River Crane Site, Ver. 8-1, AmeriFlux AMP, (Dataset). https://doi.org/10.17190/AMF/1246114

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2014.US.Wrc.Sitevisit.DSC_0385
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2014.US.Wrc.Sitevisit.DSC_0385
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2014.US.Wrc.Sitevisit.IMG_5481
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Wind River old-growth canopy
**Description:**
Trees within the old-growth stand range in age from 0 to ~500 years old and reach maximum heights of 60 m. The dominant trees are Western Hemlock and Douglas-fir. Note the vertical complexity within the canopy.
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Wind River AmeriFlux Tower – overstory measurements
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At approximately 67 m above ground level a 3-D sonic anemometer and closed-path IRGA are mounted on the Wind River AmeriFlux tower. These instruments collect the EC data at the site.
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Wind River AmeriFlux
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**Image Date:** 2008/03/01
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MODIS NDVI

The time series shows the 16-day Normalized Difference Vegetation Index (NDVI) average from the MOD13Q1 data product.
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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.

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Search Publications for this Site Publications Found: 21

AmeriFlux Publications

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Year	Publication
2019	Still, C., Powell, R., Aubrecht, D., Kim, Y., Helliker, B., Roberts, D., Richardson, A. D., Goulden, M. (2019) Thermal Imaging In Plant And Ecosystem Ecology: Applications And Challenges, Ecosphere, 10(6), . https://doi.org/https://doi.org/10.1002/ecs2.2768
2021	Still, C. J., Rastogi, B., Page, G. F., Griffith, D. M., Sibley, A., Schulze, M., Hawkins, L., Pau, S., Detto, M., Helliker, B. R. (2021) Imaging Canopy Temperature: Shedding (Thermal) Light On Ecosystem Processes, New Phytologist, 230(5), 1746-1753. https://doi.org/https://doi.org/10.1111/nph.17321
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	Toomey, M., Friedl, M. A., Frolking, S., Hufkens, K., Klosterman, S., Sonnentag, O., Baldocchi, D. D., Bernacchi, C. J., Biraud, S. C., Bohrer, G., Brzostek, E., Burns, S. P., Coursolle, C., Hollinger, D. Y., Margolis, H. A., McCaughey, H., Monson, R. K., Munger, J. W., Pallardy, S., Phillips, R. P., Torn, M. S., Wharton, S., Zeri, M., Richardson, A. D. (2015) Greenness Indices From Digital Cameras Predict The Timing And Seasonal Dynamics Of Canopy-Scale Photosynthesis, Ecological Applications, 25(1), 99-115. https://doi.org/http://doi.org/10.1890/14-0005.1
2017	Raczka, B., Biraud, S. C., Ehleringer, J. R., Lai, C., Miller, J. B., Pataki, D. E., Saleska, S. R., Torn, M. S., Vaughn, B. H., Wehr, R., Bowling, D. R. (2017) Does Vapor Pressure Deficit Drive The Seasonality Of δ13C Of The Net Land-Atmosphere Co2 Exchange Across The United States?, Journal Of Geophysical Research: Biogeosciences, 122(8), 1969-1987. https://doi.org/https://doi.org/10.1002/2017JG003795
2018	Rastogi, B., Berkelhammer, M., Wharton, S., Whelan, M. E., Meinzer, F. C., Noone, D., Still, C. J. (2018) Ecosystem Fluxes Of Carbonyl Sulfide In An Old-Growth Forest: Temporal Dynamics And Responses To Diffuse Radiation And Heat Waves, Biogeosciences, 15(23), 7127-7139. https://doi.org/10.5194/bg-15-7127-2018
2018	Rastogi, B., Berkelhammer, M., Wharton, S., Whelan, M. E., Itter, M. S., Leen, J. B., Gupta, M. X., Noone, D., Still, C. J. (2018) Large Uptake Of Atmospheric Ocs Observed At A Moist Old Growth Forest: Controls And Implications For Carbon Cycle Applications, Journal Of Geophysical Research: Biogeosciences, 123(11), 3424-3438. https://doi.org/10.1029/2018JG004430
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
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
2017	Wharton, S., Ma, S., Baldocchi, D.D., Falk, M., Newman, J.F., Osuna, J.L, Bible, K. (2017) Influence of regional nighttime atmospheric regimes on canopy turbulence and gradients at a closed and open forest in mountain-valley terrain, Agricultural and Forest Meteorology, 237–238, 18-29. https://doi.org/10.1016/j.agrformet.2017.01.020
2015	Taylor, A.J., Lai, C.-T., Hopkins, F.M., Wharton, S., Bible, K., Xu, X., Phillips, C., Bush, S., Ehleringer, J.R. (2015) Radiocarbon-based partitioning of soil respiration in an old-growth coniferous forest, Ecosystems, 18, 459-470.
2005	Falk, M., Paw U, K.T., Wharton, S., Schroeder, M. (2005) Is soil respiration a major contributor to the carbon budget within a Pacific Northwest old-growth forest?, Agricultural and Forest Meteorology, 135, 269-283.
2009	Wharton, S., Schroeder, M., Bible, K., Falk, M., Paw U, K.T. (2009) Stand-level gas-exchange responses to seasonal drought in very young versus old Douglas-fir forests of the Pacific Northwest, Tree Physiology, 29, 959-974. https://doi.org/10.1093/treephys/tpp039
2009	Wharton, S., Chasmer, L., Falk, M., Paw U, K.T. (2009) Strong links between teleconnections and ecosystem exchange found at a Pacific Northwest old-growth forest from flux tower and MODIS EVI data, Global Change Biology, 15, 2187-2205. https://doi.org/10.1111/j.1365-2486.2009.01952.x
2009	Wharton, S., Schroeder, M., Paw U, K.T., Falk, M., Bible, K. (2009) Turbulence considerations for comparing ecosystem exchange over old-growth and clear-cut stands for limited fetch and complex canopy flow conditions, Agricultural and Forest Meteorology, 149, 1477-1490.
2012	Wharton, S., Falk, M., Bible, K., Schroeder, M., Paw U, K.T. (2012) Old-Growth CO2 Flux Measurements Reveal High Sensitivity To Climate Anomalies Across Seasonal, Annual And Decadal Time Scales, Agricultural and Forest Meteorology, 161, 1-14. https://doi.org/10.1016/j.agrformet.2012.03.007
2016	Matthias Falk (2016) Climate Indices Strongly Influence Old-Growth Forest Carbon Exchange, Environmental Research Letters, 11, 1-12.
2004	Harmon, M.E., Bible, K., Ryan, M.G., Shaw, D.C., Chen, H., Klopatek, J., Li, X. (2004) Production, Respiration, And Overall Carbon Balance In An Old-Growth Pseudotsuga-Tsuga Forest Ecosystem, Ecosystems, 7, 498-512. https://doi.org/10.1007/s10021-004-0140-9
2004	Paw U, K., Falk, M., Suchanek, T., Ustin, S., Chen, J., Park, Y., Winner, W., Thomas, S., Hsiao, T., Shaw, R., King, T., Pyles, R., Schroeder, M., Matista, A. (2004) Carbon Dioxide Exchange Between An Old-Growth Forest And The Atmosphere, Ecosystems, 7(5), 513-524. https://doi.org/10.1007/s10021-004-0141-8
2008	Falk, M., Wharton, S., Schroeder, M., Ustin, S., U, K. T. (2008) Flux Partitioning In An Old-Growth Forest: Seasonal And Interannual Dynamics, Tree Physiology, 28(4), 509-520. https://doi.org/10.1093/treephys/28.4.509
2004	Shaw, D., Franklin, J., Bible, K., Klopatek, J., Freeman, E., Greene, S., Parker, G. (2004) Ecological Setting Of The Wind River Old-Growth Forest, Ecosystems, 7(5), 427-439. https://doi.org/10.1007/s10021-004-0135-6

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.

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Wind Roses

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Image scale: 707m x 707m

Data Collected:

Wind roses use variables ‘WS’ and ‘WD’.
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Wind Speed (m/s)

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Wind Speed Scale

Wind Direction Scale (%)

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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

US-Wrc: Wind River Crane Site

US-Wrc: Wind River Crane Site

DOI(s) for citing US-Wrc data

Publication(s) for citing site characterization

Acknowledgements

Resources

US-Wrc: Wind River Crane Site

Not Found

US-Wrc: Wind River Crane Site

2014.US.Wrc.Sitevisit.DSC_0385

2014.US.Wrc.Sitevisit.IMG_5481

2014.US.Wrc.Sitevisit.IMG_5489

Wind River old-growth canopy

Wind River AmeriFlux Tower – overstory measurements

Wind River AmeriFlux

US-Wrc: Wind River Crane Site

MODIS NDVI

US-Wrc: Wind River Crane Site

US-Wrc: Wind River Crane Site

BADM for This Site

US-Wrc: Wind River Crane Site

Wind Roses

Wind Speed (m/s)

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