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US-Uaf: University of Alaska, Fairbanks

Tower_team:
PI: Hiroki Iwata hiwata@shinshu-u.ac.jp - Shinshu University
PI: Masahito Ueyama miyabi-flux@muh.biglobe.ne.jp - Osaka Prefecture University
PI: Yoshinobu Harazono harazono2009gl@gmail.com - Osaka Prefecture University
Lat, Long: 64.86627, -147.85553
Elevation(m): 155
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: Dwc (Subarctic: severe, dry winter, cool summer )
Mean Annual Temp (°C): -2.9
Mean Annual Precip. (mm): 263
Flux Species Measured: CO2, H, H2O, CH4
Years Data Collected: AmeriFlux: 2002 - Present
Description: This tower is located near Smith Lake, University of Alaska, Fairbanks. The open black spruce is dominated on discontinuous permafrost.
URL: http://atmenv.envi.osakafu-u.ac.jp/data/uaf_data/
Research Topics: Long-term monitoring energy & greenhouse gas fluxes under high-latitude climate change
Acknowledgment: Supported by Arctic Challenge for Sustainability (ArCS) project by the Ministry of Education, Culture, Sports, Science and Technology, Japan.
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Image Credit:
Copyright preference: Open use
Site Publication More Site Publications

US-Uaf: University of Alaska, Fairbanks

Instructions for DOIs for This Site

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

DOIs

  • AmeriFlux
  • Citation: Masahito Ueyama, Hiroki Iwata, Yoshinobu Harazono (2002-) AmeriFlux US-Uaf University of Alaska, Fairbanks, 10.17190/AMF/1480322
  • Link: http://dx.doi.org/10.17190/AMF/1480322

Publications to use for Citations for this Site

Acknowledgements

  • Supported by Arctic Challenge for Sustainability (ArCS) project by the Ministry of Education, Culture, Sports, Science and Technology, Japan.

Resources

US-Uaf: University of Alaska, Fairbanks

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-Uaf: University of Alaska, Fairbanks

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-Uaf: University of Alaska, Fairbanks

Year Publication
2018 Masahito UEYAMA, Narumi TAHARA, Hirohiko NAGANO, Naoki MAKITA, Hiroki IWATA, Yoshinobu HARAZONO (2018) Leaf- and ecosystem-scale photosynthetic parameters for the overstory and understory of boreal forests in interior Alaska, journal of Agricultural Meteorology, 74(2), 79-86.
2012 Ruehr, N. K., Martin, J. G., Law, B. E. (2012) Effects Of Water Availability On Carbon And Water Exchange In A Young Ponderosa Pine Forest: Above- And Belowground Responses, Agricultural And Forest Meteorology, 164, 136-148.
2017 Euskirchen, E. S., Bret-Harte, M. S., Shaver, G. R., Edgar, C. W., Romanovsky, V. E. (2017) Long-Term Release Of Carbon Dioxide From Arctic Tundra Ecosystems In Alaska, Ecosystems, 20(5), 960-974.
2016 Ueyama, M., Tahara, N., Iwata, H., Euskirchen, E. S., Ikawa, H., Kobayashi, H., Nagano, H., Nakai, T., and Harazono, Y. (2016) Optimization of a biochemical model with eddy covariance measurements in black spruce forests of Alaska for estimating CO2 fertilization effects, Agric. Forest Meteorol., 222, 98-111.
2015 Iwata, H., Harazono, Y., Ueyama, M., Sakabe, A., Nagano H., Kosugi, Y., Takahashi, K., and Kim, Y. (2015) Methane exchange in a poorly-drained black spruce forest over permafrost observed using the eddy covariance technique, Agric. Forest Meteorol., 214-215, 157-168.
2015 Harazono, Y., Iwata, H., Sakabe, A., Ueyama, M., Takahashi, K., Nagano, H., Nakai, T., and Kosugi, Y. (2015) Effects of water vapor dilution on trace gas flux, and practical correction methods, J. Agric. Meteorol., 71, 65-76.
2014 Ueyama, M., Kudo, S., Iwama, C., Nagano, H., Kobayashi, H., Harazono, Y. and Yoshikawa, K. (2014) Does summer warming reduce black spruce productivity in interior Alaska?, J. Forest Res., 20, 52-59.
2014 Ueyama, M., Iwata, H., Harazono, Y. (2014) Autumn Warming Reduces The Co2sink Of A Black Spruce Forest In Interior Alaska Based On A Nine-Year Eddy Covariance Measurement, Global Change Biology, 20(4), 1161-1173.
2012 Iwata, H., Harazono, Y., and Ueyama, M. (2012) Sensitivity and offset changes of a fast-response open-path infrared gas analyzer during long-term observations in an Arctic environment, J. Agric. Meteorol., 68, 175-181.
2010 Ueyama, M., Harazono, Y., and Ichii, K. (2010) Satellite-based modeling of the carbon fluxes in mature black spruce forests in Alaska: a synthesis of the eddy covariance data and satellite remote sensing data, 2010, 14, 1-27.
2010 Iwata, H., Harazono, Y., and Ueyama, M. (2010) Influence of source/sink distributions on flux-gradient relationships in the roughtness sublayer over an open forest canopy under unstable conditions, Boundary Layer Meteorol., 136, 391-405.
2009 Ueyama, M., Harazono, Y., Kim, Y. and Tanaka, N. (2009) Response of the carbon cycle in sub-arctic black spruce forests to climate change: Reduction of a carbon sink related to the sensitivity of heterotrophic respiration., Agric. Forest Meteorol., 149, 582-602.
2009 Date, T., Ueyama. M., Harazono, Y., Ota, Y., Iwata, T. and Yamamoto, S. (2009) Satellite observations of decadal scale CO2 fluxes over black spruce forests in Alaska associated with climate variability., J. Agric. Meteorol., 65, 47-60.
2007 Kitamoto, T., Ueyama, M., Harazono, Y., Iwata, T. and Yamamoto, S. (2007) Applications of NOAA/AVHRR and observed fluxes to estimate regional carbon fluxes over black spruce forests in Alaska., J. Agric. Meteorol., 63, 171-183.
2012 Iwata, H., Harazono, Y., and Ueyama, M. (2012) The role of permafrost on water exchange of a black spruce forest in Interior Alaska, Agric. Forest Meteorol., 161(107-115), .
2007 Kim, Y., Ueyama, M., Nakagawa, F., Tsunogai, U., Harazono, Y. and Tanaka, N. (2007) Assessment of winter fluxes of CO2 and CH4 in boreal forest soils of central Alaska estimated by the profile method and the chamber method: A diagnosis of methane emission and implications for the regional carbon budget, Tellus, 59B, 223-233.
2006 Ueyama, M., Harazaono, Y., Okada, R., Nojiri, A., Ohtaki, E. and Miyata, A. (2006) Micrometeorological measurements of methane flux at a boreal forest in central Alaska, Mem. Natl Inst. Polar Res., Spec. Issue, 59, 156-167.
2006 Ueyama, M., Harazono, Y., Okada, R., Nojiri, A., Ohataki, E. and Miyata, A. (2006) Controlling factors on the inter-annual CO2 budget at a sub-arctic black spruce forest in interior Alaska, Tellus, 58B, 491-501.

US-Uaf: University of Alaska, Fairbanks

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-Uaf: University of Alaska, Fairbanks

Wind Roses

Click an image below to enlarge it, or use the navigation panel.
  • Image scale: 431m x 431m
  • 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
    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