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US-Var: Vaira Ranch- Ione

Tower_team:
PI: Dennis Baldocchi Baldocchi@berkeley.edu - University of California, Berkeley
AncContact: Joe Verfaillie jverfail@berkeley.edu - University of California, Berkeley
Technician: Daphne Szutu daphneszutu@berkeley.edu - UC Berkeley
Lat, Long: 38.4133, -120.9508
Elevation(m): 129
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: Csa (Mediterranean: mild with dry, hot summer)
Mean Annual Temp (°C): 15.8
Mean Annual Precip. (mm): 559
Flux Species Measured: CO2, H2O
Years Data Collected: 2000 - Present
Years Data Available:

AmeriFlux BASE 2000 - 2024   Data Citation

AmeriFlux FLUXNET 2000 - 2021   Data Citation
Data Use Policy:AmeriFlux CC-BY-4.0 Policy1
Description:
Located in the lower foothills of the Sierra Nevada Mountains on privately owned land, the Vaira Ranch site is classified as a grassland dominated by C3 ...
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URL: http://nature.berkeley.edu/biometlab/sites.php?tab=US-Var
Research Topics:
The research approach of the University of California, Berkeley Biometeorology Laboratory involves the coordinated use of experimental measurements and ...
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Acknowledgment: This research was supported in part by the Office of Science (BER), U.S. Department of Energy, Grant No. DE-FG02-03ER63638
Site Tasks
  1. 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.
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Image Credit:
Copyright preference: Request for permission
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US-Var: Vaira Ranch- Ione

Use the information below for citation of this site. See the Data Policy page for more details.

DOI(s) for citing US-Var 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-Var data are combined with data from sites that require the AmeriFlux Legacy Policy.

  • AmeriFlux BASE: https://doi.org/10.17190/AMF/1245984
    Citation: Siyan Ma, Liukang Xu, Joseph Verfaillie, Dennis Baldocchi (2025), AmeriFlux BASE US-Var Vaira Ranch- Ione, Ver. 23-5, AmeriFlux AMP, (Dataset). https://doi.org/10.17190/AMF/1245984
  • AmeriFlux FLUXNET: https://doi.org/10.17190/AMF/1993904
    Citation: Siyan Ma, Liukang Xu, Joseph Verfaillie, Dennis Baldocchi (2023), AmeriFlux FLUXNET-1F US-Var Vaira Ranch- Ione, Ver. 3-5, AmeriFlux AMP, (Dataset). https://doi.org/10.17190/AMF/1993904

Find global FLUXNET datasets, like FLUXNET2015 and FLUXNET-CH4, and their citation information at fluxnet.org.

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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Acknowledgments

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Resources

US-Var: Vaira Ranch- Ione

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US-Var: Vaira Ranch- Ione

Year Publication
2021 Baldocchi, D., Ma, S., Verfaillie, J. (2021) On The Inter‐ And Intra‐Annual Variability Of Ecosystem Evapotranspiration And Water Use Efficiency Of An Oak Savanna And Annual Grassland Subjected To Booms And Busts In Rainfall, Global Change Biology, 27(2), 359-375. https://doi.org/10.1111/gcb.15414
2020 Ma, S., Eichelmann, E., Wolf, S., Rey-Sanchez, C., Baldocchi, D. D. (2020) Transpiration And Evaporation In A Californian Oak-Grass Savanna: Field Measurements And Partitioning Model Results, Agricultural And Forest Meteorology, 295, 108204. https://doi.org/10.1016/j.agrformet.2020.108204
2020 Baldocchi, D. D., Ryu, Y., Dechant, B., Eichelmann, E., Hemes, K., Ma, S., Sanchez, C. R., Shortt, R., Szutu, D., Valach, A., Verfaillie, J., Badgley, G., Zeng, Y., Berry, J. A. (2020) Outgoing Near‐Infrared Radiation From Vegetation Scales With Canopy Photosynthesis Across A Spectrum Of Function, Structure, Physiological Capacity, And Weather, Journal Of Geophysical Research: Biogeosciences, 125(7), . https://doi.org/10.1029/2019jg005534
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
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. https://doi.org/10.1111/pce.13517
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. https://doi.org/10.1088/1748-9326/ab2603
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
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
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
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
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. https://doi.org/10.1175/JHM-D-18-0259.1
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. https://doi.org/10.1029/2018JG004744
2018 Baldocchi, D., Penuelas, J. (2018) The Physics And Ecology Of Mining Carbon Dioxide From The Atmosphere By Ecosystems, Global Change Biology, . https://doi.org/10.1111/gcb.14559
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
2018 Schmidt, A., Creason, W., Law, B. E. (2018) Estimating Regional Effects Of Climate Change And Altered Land Use On Biosphere Carbon Fluxes Using Distributed Time Delay Neural Networks With Bayesian Regularized Learning, Neural Networks, 108, 97-113. https://doi.org/10.1016/j.neunet.2018.08.004
2017 Liu, Y., Hill, M. J., Zhang, X., Wang, Z., Richardson, A. D., Hufkens, K., Filippa, G., Baldocchi, D. D., Ma, S., Verfaillie, J., Schaaf, C. B. (2017) Using Data From Landsat, Modis, Viirs And Phenocams To Monitor The Phenology Of California Oak/Grass Savanna And Open Grassland Across Spatial Scales, Agricultural And Forest Meteorology, 237-238, 311-325. https://doi.org/10.1016/j.agrformet.2017.02.026
2017 Filippa, G, Cremonesea, E, Migliavacca M., Galvagno, M., Sonnentag, O., Humphrey, E., Hufkens,K., Ryu, Y. Verfaillie, J., Morra di Cella, U., Richardson, A. (2017) NDVI derived from near-infrared-enabled digital cameras: Applicability across different plant functional types, Agricultural and Forest Meteorology, . https://doi.org/https://doi.org/10.1016/j.agrformet.2017.11.003
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
2006 Kim, J., Guo, Q., Baldocchi, D., Leclerc, M., Xu, L., Schmid, H. (2006) Upscaling Fluxes From Tower To Landscape: Overlaying Flux Footprints On High-Resolution (IKONOS) Images Of Vegetation Cover, Agricultural And Forest Meteorology, 136(3-4), 132-146. https://doi.org/10.1016/j.agrformet.2004.11.015
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
2012 Grant, R., Baldocchi, D., Ma, S. (2012) Ecological Controls On Net Ecosystem Productivity Of A Seasonally Dry Annual Grassland Under Current And Future Climates: Modelling With Ecosys, Agricultural And Forest Meteorology, 152, 189-200. https://doi.org/10.1016/j.agrformet.2011.09.012
2004 Xu, L., Baldocchi, D. D. (2004) Seasonal Variation In Carbon Dioxide Exchange Over A Mediterranean Annual Grassland In California, Agricultural And Forest Meteorology, 123(1-2), 79-96. https://doi.org/10.1016/j.agrformet.2003.10.004
2004 Baldocchi, D. D., Xu, L., Kiang, N. (2004) How Plant Functional-Type, Weather, Seasonal Drought, And Soil Physical Properties Alter Water And Energy Fluxes Of An Oak–Grass Savanna And An Annual Grassland, Agricultural And Forest Meteorology, 123(1-2), 13-39. https://doi.org/10.1016/j.agrformet.2003.11.006
2007 Ma, S., Baldocchi, D. D., Xu, L., Hehn, T. (2007) Inter-Annual Variability In Carbon Dioxide Exchange Of An Oak/Grass Savanna And Open Grassland In California, Agricultural And Forest Meteorology, 147(3-4), 157-171. https://doi.org/10.1016/j.agrformet.2007.07.008
2005 Gu, L., Falge, E. M., Boden, T., Baldocchi, D. D., Black, T., Saleska, S. R., Suni, T., Verma, S. B., Vesala, T., Wofsy, S. C., Xu, L. (2005) Objective Threshold Determination For Nighttime Eddy Flux Filtering, Agricultural And Forest Meteorology, 128(3-4), 179-197. https://doi.org/10.1016/j.agrformet.2004.11.006
2008 Ryu, Y, Baldoicchi, D. D., Ma, S., Hehn, T. (2008) Interannual Variability Of Evapotranspiration And Energy Exchange Over An Annual Grassland In California, Journal Of Geophysical Research, 113(D09104), n/a-n/a. https://doi.org/10.1029/2007jd009263
2004 Xu, L., Baldocchi, D. D., Tang, J. (2004) How Soil Moisture, Rain Pulses, And Growth Alter The Response Of Ecosystem Respiration To Temperature, Global Biogeochemical Cycles, 18(4), n/a-n/a. https://doi.org/10.1029/2004gb002281
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. https://doi.org/10.1073/pnas.1519620113
2016 Ma, S, Baldocchi, D.D., Wolf, S., Verfaillie, J. (2016) Slow ecosystem responses conditionally regulate annual carbon balance over 15 years in Californian oak-grass savanna, Agricultural and Forest Meteorology, 252-264. https://doi.org/10.1016/j.agrformet.2016.07.016

US-Var: Vaira Ranch- Ione

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-Var: Vaira Ranch- Ione

Wind Roses

Click an image below to enlarge it, or use the navigation panel.
  • Image scale: 795m x 795m
  • 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
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    Sep - Dec; 6am - 6pm
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    Dec - Mar; 6am - 6pm
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