US-Me1: Metolius - Eyerly burn

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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 US-Me1 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-Me1 data are combined with data from sites that require the AmeriFlux Legacy Policy.

AmeriFlux BASE: https://doi.org/10.17190/AMF/1246074
Citation: Bev Law (2019), AmeriFlux BASE US-Me1 Metolius - Eyerly burn, Ver. 3-5, AmeriFlux AMP, (Dataset). https://doi.org/10.17190/AMF/1246074
AmeriFlux FLUXNET: https://doi.org/10.17190/AMF/1902834
Citation: Bev Law (2024), AmeriFlux FLUXNET-1F US-Me1 Metolius - Eyerly burn, Ver. 4-6, AmeriFlux AMP, (Dataset). https://doi.org/10.17190/AMF/1902834

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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US-Me1: Metolius - Eyerly burn

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US-Me1: Metolius - Eyerly burn

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2005.US.Me1.sitevisit.101-0168_IMG
**Description:**
2005.US.Me1.sitevisit.101-0168_IMG
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**Site ID:** US-Me1
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US-Me1: Metolius - Eyerly burn

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

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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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 .

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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 .

Click a square in the grid at left to display its data below.

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NDVI: Normalized Difference Vegetation Index

Resolution: 0.01° x 0.01° & 10 minutes

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NIRv Near-Infrared Reflectance of vegetation

Resolution: 0.01° x 0.01° & 10 minutes

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DSR: Surface downward shortwave radiation

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LST: Land Surface Temperature

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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.

GeoNEX Surface Downward Solar Radiation (DSR):

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.

GeoNEX Land Surface Temperature (LST):

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.

US-Me1: Metolius - Eyerly burn

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Search Publications for this Site Publications Found: 6

AmeriFlux Publications

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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
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
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
2004	Sun, O. J., Campbell, J., Law, B. E., Wolf, V. (2004) Dynamics Of Carbon Stocks In Soils And Detritus Across Chronosequences Of Different Forest Types In The Pacific Northwest, USA, Global Change Biology, 10(9), 1470-1481. https://doi.org/10.1111/j.1365-2486.2004.00829.x
2007	Irvine, J., Law, B. E., Hibbard, K. A. (2007) Postfire Carbon Pools And Fluxes In Semiarid Ponderosa Pine In Central Oregon, Global Change Biology, 13(8), 1748-1760. https://doi.org/10.1111/j.1365-2486.2007.01368.x
2004	Bond-Lamberty, B., Wang, C., Gower, S. T. (2004) A Global Relationship Between The Heterotrophic And Autotrophic Components Of Soil Respiration?, Global Change Biology, 10(10), 1756-1766. https://doi.org/10.1111/j.1365-2486.2004.00816.x

US-Me1: Metolius - Eyerly burn

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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)^*

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US-Me1: Metolius - Eyerly burn

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Wind Roses

Click an image below to enlarge it, or use the navigation panel.

Image scale: 723m x 723m

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 (%)

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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

Tower_team:
PI:	Bev Law bev.law@oregonstate.edu - Oregon State University
DataManager:	Chand Hanson chand.hanson@oregonstate.edu - Oregon State University
Lat, Long:	44.5794, -121.5000
Elevation(m):	896
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:	Csb (Mediterranean: mild with dry, warm summer)
Mean Annual Temp (°C):	7.88
Mean Annual Precip. (mm):	704.61
Flux Species Measured:	CO2, H2O
Years Data Collected:	2004 - 2005
Years Data Available:	AmeriFlux BASE 2004 - 2005 Data Citation AmeriFlux FLUXNET 2004 - 2005 Data Citation
Data Use Policy:	AmeriFlux CC-BY-4.0 Policy¹
Description:	An intermediate aged ponderosa pine forest that was severely burned in the 2002 Eyerly wildfire. All trees were killed (stand replacing event). Irvine ... An intermediate aged ponderosa pine forest that was severely burned in the 2002 Eyerly wildfire. All trees were killed (stand replacing event). Irvine et al (2007) GCB 13 (8), 1748–1760. See More Show Less
URL:	http://wwwdata.forestry.oregonstate.edu/terra/flux.htm
Research Topics:	The research and science objectives of the Metolius Eyerly Burn site are as follows: 1) To quantify how successional stages and management practices in ... The research and science objectives of the Metolius Eyerly Burn site are as follows: 1) To quantify how successional stages and management practices in forest ecosystems influence processes controlling net ecosystem exchange of CO2 in varying climatic conditions; 2) Investigate the effects of disturbance processes controlling carbon storage and CO2 and energy exchange with the atmosphere in varying climatic conditions; 3) Measure the effects of disturbance and climate on the CO2 and energy exchange of ponderosa pine forests in the Pacific Northwest; 4) Investigate postfire carbon dynamics and contrast results with data collected on unburned forest stands that represent the prefire conditions; 5) Measure carbon pools and key carbon fluxes in forest stands subject to moderate and high severity fire in order to estimate NEP. (Irvine et al. 2007) See More Show Less
Acknowledgment:	DOE acknowledgment for Eyerly site research: This research was supported by the Of?ce of Science (BER), U.S. Department of Energy (DOE, Grant no. DE-FG02-06ER64318)

US-Me1: Metolius - Eyerly burn

US-Me1: Metolius - Eyerly burn

DOI(s) for citing US-Me1 data

Publication(s) for citing site characterization

Acknowledgments

Resources

US-Me1: Metolius - Eyerly burn

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US-Me1: Metolius - Eyerly burn

2005.US.Me1.sitevisit.101-0168_IMG

US-Me1: Metolius - Eyerly burn

US-Me1: Metolius - Eyerly burn

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US-Me1: Metolius - Eyerly burn

Wind Roses

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