US-Myb: Mayberry Wetland
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| Tower_team: | |
| PI: | Dennis Baldocchi baldocchi@berkeley.edu - University of California, Berkeley |
| AncContact: | Joe Verfaillie jverfail@berkeley.edu - University of California, Berkeley |
| FluxContact: | Daphne Szutu daphneszutu@berkeley.edu - UC Berkeley |
| Lat, Long: | 38.0499, -121.7650 |
| Elevation(m): | -4 |
| Network Affiliations: | AmeriFlux, Phenocam |
| Vegetation IGBP: | WET (Permanent Wetlands: Lands with a permanent mixture of water and herbaceous or woody vegetation that cover extensive areas. 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): | 15.9 |
| Mean Annual Precip. (mm): | 338 |
| Flux Species Measured: | CO2, CH4, H2O |
| Years Data Collected: | 2010 - Present |
| Years Data Available: | AmeriFlux BASE 2010 - 2023 Data Citation AmeriFlux FLUXNET 2010 - 2021 Data Citation |
| Data Use Policy: | AmeriFlux CC-BY-4.0 Policy1 |
| Description: | The Mayberry Wetland site is a 300-acre restored wetland on Sherman Island, north of Mayberry Slough, that is on the property of Mayberry Farms and managed ... The Mayberry Wetland site is a 300-acre restored wetland on Sherman Island, north of Mayberry Slough, that is on the property of Mayberry Farms and managed by the California Department of Water Resources and Ducks Unlimited. During Summer 2010, the site was restored from a pepperweed and annual grassland pasture to a wetland through a project managed by Bryan Brock (bpbrock@water.ca.gov). A flux tower equipped to analyze energy, H2O, CO2, and CH4 fluxes was installed on October 14, 2010. At the time of installation, flooding of the site had only recently begun after extensive reconstruction of the wetland bathymetry conducted during the summer. Although some small patches of tules remain within the site, the site is a patchwork of deep and shallow open water with some remaining vegetation. Currently, there is an intention to flood-to-kill the current pepperweed and upland grasses and let the wetland plants propagate naturally, so no additional plant manipulation will occur. See MoreShow Less |
| URL: | http://nature.berkeley.edu/biometlab/sites.php?tab=US-Myb |
| Research Topics: | The research approach of the University of California, Berkeley Biometeorology Laboratory involves the coordinated use of experimental measurements and ... The research approach of the University of California, Berkeley Biometeorology Laboratory involves the coordinated use of experimental measurements and theoretical models to understand the physical, biological, and chemical processes that control trace gas fluxes between the biosphere and atmosphere and to quantify their temporal and spatial variations. The research objectives of the Mayberry Wetland, Sherman Island, and Twitchell Island sites are as follows: 1) Describe differences in the fluxes of CO2, CH4, H2O, and energy between different land uses; 2) Understand the mechanisms controlling these fluxes; 3) Use ecosystem modeling to understand controls on these mechanisms under different environmental scenarios. These three sites were selected to capture a wide range of inundated conditions within the Sacramento-San Joaquin River Delta. The research focuses on the eddy covariance technique to measure CH4, CO2, H2O, and energy fluxes and works to combine measurements of both net fluxes and partitioned fluxes in order to achieve a mechanistic understanding of the ecological controls on current and future carbon flux in the Delta. See MoreShow Less |
| Acknowledgment: | Biometeorology Lab, University of California, Berkeley, PI: Dennis Baldocchi |
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- 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.
US-Myb
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Knox, S. H.,, Sturtevant, C., Matthes, J.H., Koteen, L., Verfaillie,J., Baldocchi. D. 2014.
Agricultural peatland restoration: effects of land-use change on greenhouse gas (CO2 and CH4) fluxes in the Sacramento-San Joaquin Delta,
Global Change Biology, 21, 750-765.
US-Myb: Mayberry Wetland
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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-Myb 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-Myb data are combined with data from sites that require the AmeriFlux Legacy Policy.
- AmeriFlux BASE: https://doi.org/10.17190/AMF/1246139
Citation: Jaclyn Hatala Matthes, Cove Sturtevant, Patty Oikawa, Samuel D Chamberlain, Daphne Szutu, Ariane Arias-Ortiz, Joseph Verfaillie, Dennis Baldocchi (2024), AmeriFlux BASE US-Myb Mayberry Wetland, Ver. 14-5, AmeriFlux AMP, (Dataset). https://doi.org/10.17190/AMF/1246139 - AmeriFlux FLUXNET: https://doi.org/10.17190/AMF/1871139
Citation: Jaclyn Hatala Matthes, Cove Sturtevant, Patty Oikawa, Samuel D Chamberlain, Daphne Szutu, Ariane Arias-Ortiz, Joseph Verfaillie, Dennis Baldocchi (2022), AmeriFlux FLUXNET-1F US-Myb Mayberry Wetland, Ver. 3-5, AmeriFlux AMP, (Dataset). https://doi.org/10.17190/AMF/1871139
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.
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US-Myb: Mayberry Wetland
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This page displays the list of downloads of data for the site US-Myb.
Note: Results are the number of downloads to distinct data users. The Download Count column indicates the number of times the data user downloaded the data. The Version column refers to the version of the data product for the site that was downloaded by the data user.
| Date | Name | Data Product | Version | Intended Use | Intended Use Description | Download Count |
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US-Myb: Mayberry Wetland
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Search Images for this Site Images found : 7
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US-Myb 2014.US.Myb.Sitevisit.20140908_IMG_013944
Description:
2014.US.Myb.Sitevisit.20140908_IMG_013944
Keywords: —
Site ID: US-Myb
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Location:
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US-Myb mayberry scaffold
Keywords: —
Credit: Berkeley BiometLab
Site ID: US-Myb
Location: California, United States
Location: California, United States
Image Date: 2014/09/08
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Article Title: —
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Right to Use: Open use
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US-Myb ddb in the mayberry wetland
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Credit: Berkeley BiometLab
Site ID: US-Myb
Location: California, United States
Location: California, United States
Image Date: 2016/06/24
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US-Myb mayberry winter
Description:
bould corn tower
Keywords: —
Credit: Berkeley BiometLab
Site ID: US-Myb
Location: California, United States
Location: California, United States
Image Date: 2014/10/02
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US-Myb MayberryFluxTower
Description:
flux tower on Mayberry in 2011
Keywords: —
Credit: Dennis Baldocchi
Site ID: US-Myb
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Location:
Image Date: 2011/10/07
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US-Myb Mayberry wetland
Description:
flux tower and veg and fetch
Keywords: —
Credit: Dennis Baldocchi
Site ID: US-Myb
Location: California, United States
Location: California, United States
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US-Myb Cristina Poindexter, AmeriFlux Data Team, is measuring instrument locations at Mayberry Island (US_Myb). This provided her first-person experience of what is involved in mapping out instrumentation on a flux site.
Keywords: —
Credit: Marilyn Saarni
Site ID: US-Myb
Location: California, United States
Location: California, United States
Image Date: 2014/09/08
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US-Myb: Mayberry Wetland
- Overview
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- Remote Sensing Data
- MODIS
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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. Terrestrial Ecology Subsetting & Visualization Services (TESViS) Fixed Sites Subsets. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1567
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.
PhenoCam Images and Derived Time Series Data
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 .
PhenoCam sites for US-Myb:
Use the links below to explore camera images and interactive timeseries for these sites.
Citation:
B. Seyednasrollah, A. M. Young, K. Hufkens, T. Milliman, M. A. Friedl, S. Frolking, and A. D. Richardson. Tracking vegetation phenology across diverse biomes using version 2.0 of the phenocam dataset. Scientific Data, 6(1):222, 2019. doi:10.1038/s41597-019-0229-9Camera Imagery
Milliman, T., B. Seyednasrollah, A.M. Young, K. Hufkens, M.A. Friedl, S. Frolking, A.D. Richardson, M. Abraha, D.W. Allen, M. Apple, M.A. Arain, J.M. Baker, D. Baldocchi, C.J. Bernacchi, J. Bhattacharjee, P. Blanken, D.D. Bosch, R. Boughton, E.H. Boughton, R.F. Brown, D.M. Browning, N. Brunsell, S.P. Burns, M. Cavagna, H. Chu, P.E. Clark, B.J. Conrad, E. Cremonese, D. Debinski, A.R. Desai, R. Diaz-Delgado, L. Duchesne, A.L. Dunn, D.M. Eissenstat, T. El-Madany, D.S.S. Ellum, S.M. Ernest, A. Esposito, L. Fenstermaker, L.B. Flanagan, B. Forsythe, J. Gallagher, D. Gianelle, T. Griffis, P. Groffman, L. Gu, J. Guillemot, M. Halpin, P.J. Hanson, D. Hemming, A.A. Hove, E.R. Humphreys, A. Jaimes-Hernandez, A.A. Jaradat, J. Johnson, E. Keel, V.R. Kelly, J.W. Kirchner, P.B. Kirchner, M. Knapp, M. Krassovski, O. Langvall, G. Lanthier, G.l. Maire, E. Magliulo, T.A. Martin, B. McNeil, G.A. Meyer, M. Migliavacca, B.P. Mohanty, C.E. Moore, R. Mudd, J.W. Munger, Z.E. Murrell, Z. Nesic, H.S. Neufeld, W. Oechel, A.C. Oishi, W.W. Oswald, T.D. Perkins, M.L. Reba, B. Rundquist, B.R. Runkle, E.S. Russell, E.J. Sadler, A. Saha, N.Z. Saliendra, L. Schmalbeck, M.D. Schwartz, R.L. Scott, E.M. Smith, O. Sonnentag, P. Stoy, S. Strachan, K. Suvocarev, J.E. Thom, R.Q. Thomas, A.K. Van den berg, R. Vargas, J. Verfaillie, C.S. Vogel, J.J. Walker, N. Webb, P. Wetzel, S. Weyers, A.V. Whipple, T.G. Whitham, G. Wohlfahrt, J.D. Wood, J. Yang, X. Yang, G. Yenni, Y. Zhang, Q. Zhang, and D. Zona. 2019. PhenoCam Dataset v2.0: Digital Camera Imagery from the PhenoCam Network, 2000-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1689
Green Chromatic Coordinate Time Series
Seyednasrollah, B., A.M. Young, K. Hufkens, T. Milliman, M.A. Friedl, S. Frolking, A.D. Richardson, M. Abraha, D.W. Allen, M. Apple, M.A. Arain, J. Baker, J.M. Baker, D. Baldocchi, C.J. Bernacchi, J. Bhattacharjee, P. Blanken, D.D. Bosch, R. Boughton, E.H. Boughton, R.F. Brown, D.M. Browning, N. Brunsell, S.P. Burns, M. Cavagna, H. Chu, P.E. Clark, B.J. Conrad, E. Cremonese, D. Debinski, A.R. Desai, R. Diaz-Delgado, L. Duchesne, A.L. Dunn, D.M. Eissenstat, T. El-Madany, D.S.S. Ellum, S.M. Ernest, A. Esposito, L. Fenstermaker, L.B. Flanagan, B. Forsythe, J. Gallagher, D. Gianelle, T. Griffis, P. Groffman, L. Gu, J. Guillemot, M. Halpin, P.J. Hanson, D. Hemming, A.A. Hove, E.R. Humphreys, A. Jaimes-Hernandez, A.A. Jaradat, J. Johnson, E. Keel, V.R. Kelly, J.W. Kirchner, P.B. Kirchner, M. Knapp, M. Krassovski, O. Langvall, G. Lanthier, G.l. Maire, E. Magliulo, T.A. Martin, B. McNeil, G.A. Meyer, M. Migliavacca, B.P. Mohanty, C.E. Moore, R. Mudd, J.W. Munger, Z.E. Murrell, Z. Nesic, H.S. Neufeld, T.L. O'Halloran, W. Oechel, A.C. Oishi, W.W. Oswald, T.D. Perkins, M.L. Reba, B. Rundquist, B.R. Runkle, E.S. Russell, E.J. Sadler, A. Saha, N.Z. Saliendra, L. Schmalbeck, M.D. Schwartz, R.L. Scott, E.M. Smith, O. Sonnentag, P. Stoy, S. Strachan, K. Suvocarev, J.E. Thom, R.Q. Thomas, A.K. Van den berg, R. Vargas, J. Verfaillie, C.S. Vogel, J.J. Walker, N. Webb, P. Wetzel, S. Weyers, A.V. Whipple, T.G. Whitham, G. Wohlfahrt, J.D. Wood, S. Wolf, J. Yang, X. Yang, G. Yenni, Y. Zhang, Q. Zhang, and D. Zona. 2019. PhenoCam Dataset v2.0: Vegetation Phenology from Digital Camera Imagery, 2000-2018. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1674
GeoNEX Data Products
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 US-Myb, 38.0499, -121.765.
Click a square in the grid at left to display its data below.
Coordinates for selected GeoNEX Pixel
Lat: 38.0700 Long: -121.8000
US-Myb
Graph controls:
- Zoom: click-drag
- Pan: shift-click-drag
- Restore zoom level: double-click
- Use the slider below the time series to zoom in and out.
All download requests will be logged.
NDVI: Normalized Difference Vegetation Index
No NDVI data have been received for site US-Myb.
NDVI (unitless)
Resolution: 0.01° x 0.01° & 10 minutes
Coordinates for pixel: Lat: 38.0700 Long: -121.8000
NIRv Near-Infrared Reflectance of vegetation
No NIRv data have been received for site US-Myb.
NIRv (unitless)
Resolution: 0.01° x 0.01° & 10 minutes
Coordinates for pixel: Lat: 38.0700 Long: -121.8000
DSR: Surface downward shortwave radiation
No DSR data have been received for site US-Myb.
Shortwave Radiation (W/m2)
Resolution: 0.01° x 0.01° & Hourly
Coordinates for pixel: Lat: 38.0700 Long: -121.8000
LST: Land Surface Temperature
No LST data have been received for site US-Myb.
LST (K)
Resolution: 0.02° x 0.02° & Hourly
Coordinates for pixel: Lat: 38.0600 Long: -121.8000
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.
- 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.
- 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-Myb: Mayberry Wetland
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- MODIS
- PhenoCam
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Search Publications for this Site
Publications Found: 20
| AmeriFlux Publications | Add Publication |
| 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 |
| 2021 | Rey‐Sanchez, C., Wharton, S., Vilà‐Guerau de Arellano, J., Paw U, K. T., Hemes, K. S., Fuentes, J. D., Osuna, J., Szutu, D., Ribeiro, J. V., Verfaillie, J., Baldocchi, D. (2021) Evaluation Of Atmospheric Boundary Layer Height From Wind Profiling Radar And Slab Models And Its Responses To Seasonality Of Land Cover, Subsidence, And Advection, Journal Of Geophysical Research: Atmospheres, 126(7), . https://doi.org/10.1029/2020JD033775 |
| 2021 | Valach, A. C., Kasak, K., Hemes, K. S., Anthony, T. L., Dronova, I., Taddeo, S., Silver, W. L., Szutu, D., Verfaillie, J., Baldocchi, D. D. (2021) Productive Wetlands Restored For Carbon Sequestration Quickly Become Net Co2 Sinks With Site-Level Factors Driving Uptake Variability, Plos One, 16(3), e0248398. https://doi.org/10.1371/journal.pone.0248398 |
| 2021 | Valach, Alex C. Kasak, Kuno Hemes, Kyle S. Szutu, Daphne Verfaillie, Joe Baldocchi, Dennis D. (2021) Carbon Flux Trajectories and Site Conditions from Restored Impounded Marshes in the Sacramento-San Joaquin Delta, Wetland Carbon and Environmental Management, . https://doi.org/10.1002/9781119639305.ch13 |
| 2021 | Arias‐Ortiz, A., Oikawa, P. Y., Carlin, J., Masqué, P., Shahan, J., Kanneg, S., Paytan, A., Baldocchi, D. D. (2021) Tidal And Nontidal Marsh Restoration: A Trade‐Off Between Carbon Sequestration, Methane Emissions, And Soil Accretion, Journal Of Geophysical Research: Biogeosciences, 126(12), . https://doi.org/10.1029/2021JG006573 |
| 2019 | Hemes, K. S., Chamberlain, S. D., Eichelmann, E., Anthony, T., Valach, A., Kasak, K., Szutu, D., Verfaillie, J., Silver, W. L., Baldocchi, D. D. (2019) Assessing The Carbon And Climate Benefit Of Restoring Degraded Agricultural Peat Soils To Managed Wetlands, Agricultural And Forest Meteorology, 268, 202-214. https://doi.org/10.1016/j.agrformet.2019.01.017 |
| 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 |
| 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 | Chamberlain, S. D., Hemes, K. S., Eichelmann, E., Szutu, D. J., Verfaillie, J. G., Baldocchi, D. D. (2019) Effect Of Drought-Induced Salinization On Wetland Methane Emissions, Gross Ecosystem Productivity, And Their Interactions, Ecosystems, . https://doi.org/10.1007/s10021-019-00430-5 |
| 2018 | Eichelmann, E., Hemes, K. S., Knox, S. H., Oikawa, P. Y., Chamberlain, S. D., Sturtevant, C., Verfaillie, J., Baldocchi, D. D. (2018) The Effect Of Land Cover Type And Structure On Evapotranspiration From Agricultural And Wetland Sites In The Sacramento–San Joaquin River Delta, California, Agricultural And Forest Meteorology, 256-257, 179-195. https://doi.org/10.1016/j.agrformet.2018.03.007 |
| 2018 | Hemes, K. S., Eichelmann, E., Chamberlain, S., Knox, S. H., Oikawa, P. Y., Sturtevant, C., Verfaillie, J., Szutu, D., Baldocchi, D. D. (2018) A Unique Combination Of Aerodynamic And Surface Properties Contribute To Surface Cooling In Restored Wetlands Of The Sacramento-San Joaquin Delta, California, Journal Of Geophysical Research: Biogeosciences, . https://doi.org/10.1029/2018JG004494 |
| 2018 | Hemes, K. S., Chamberlain, S. D., Eichelmann, E., Knox, S. H., Baldocchi, D. D. (2018) A Biogeochemical Compromise: The High Methane Cost Of Sequestering Carbon In Restored Wetlands, Geophysical Research Letters, . https://doi.org/10.1029/2018GL077747 |
| 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 |
| 2017 | Oikawa, P. Y.; Jenerette, G. D.; Knox, S. H.; Sturtevant, C.; Verfaillie, J.; Dronova, I.; Poindexter, C. M. ; Eichelmann, E.; Baldocchi, D. D. (2017) Evaluation of a hierarchy of models reveals importance of substrate limitation for predicting carbon dioxide and methane exchange in restored wetlands, Journal of Geophysical Research: Biogeosciences, 122(1), 145-167. https://doi.org/10.1002/2016JG003438 |
| 2017 | Knox, Sara Helen Dronova, Iryna Sturtevant, Cove Oikawa, Patricia Y. Matthes, Jaclyn Hatala Verfaillie, Joseph Baldocchi, Dennis (2017) Using digital camera and Landsat imagery with eddy covariance data to model gross primary production in restored wetlands, Agricultural and Forest Meteorology, 237–238, 233-245. https://doi.org/http://dx.doi.org/10.1016/j.agrformet.2017.02.020 |
| 2017 | Chamberlain, S. D., Verfaillie, J., Eichelmann, E., Hemes, K. S., Baldocchi, D. D. (2017) Evaluation Of Density Corrections To Methane Fluxes Measured By Open-Path Eddy Covariance Over Contrasting Landscapes, Boundary-Layer Meteorology, . https://doi.org/10.1007/s10546-017-0275-9 |
| 2016 | McNicol, G., C. S. Sturtevant, S. H. Knox, I. Dronova, D. D. Baldocchi, and W. L. Silver. (2016) 2016. Effects of seasonality, transport-pathway, and spatial structure on greenhouse gas fluxes in a restored wetland., Global Change Biology, nnn-nnn. https://doi.org/10.1111/gcb.13580 |
| 2015 | Sturtevant, C., B. L. Ruddell, S. H. Knox, J. Verfaillie, J. H. Matthes, P. Y. Oikawa, and D. Baldocchi. (2015) 2015. Identifying scale-emergent, non-linear, asynchronous processes of wetland methane exchange., Journal of Geophysical Research: Biogeosciences, 121, 188-204. https://doi.org/10.1002/2015jg003054 |
| 2014 | Knox, S. H.,, Sturtevant, C., Matthes, J.H., Koteen, L., Verfaillie,J., Baldocchi. D. (2014) Agricultural peatland restoration: effects of land-use change on greenhouse gas (CO2 and CH4) fluxes in the Sacramento-San Joaquin Delta, Global Change Biology, 21, 750-765. https://doi.org/10.1111/gcb.12745 |
| 2014 | Matthes, J. H., Sturtevant, C., Verfaillie, J., Knox, S., Baldocchi, D. (2014) Parsing The Variability In Ch4 flux At A Spatially Heterogeneous Wetland: Integrating Multiple Eddy Covariance Towers With High-Resolution Flux Footprint Analysis, Journal Of Geophysical Research: Biogeosciences, 119(7), 1322-1339. https://doi.org/10.1002/2014JG002642 |
US-Myb: Mayberry Wetland
- Overview
- Windroses
- Data Citation
- Data Use Log
- Image Gallery
- Remote Sensing Data
- MODIS
- PhenoCam
- GeoNEX
- Publications
- BADM
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)*
- Use Online Editor to update Site General Info or DOI Authorship
- Update information about submitted data (Variable Information tool)
- More BADM resources
* 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-Myb: Mayberry Wetland
- Overview
- Windroses
- Data Citation
- Data Use Log
- Image Gallery
- Remote Sensing Data
- MODIS
- PhenoCam
- GeoNEX
- Publications
- BADM
Wind Roses
Click an image below to enlarge it, or use the navigation panel.
Wind Speed (m/s)
Navigation
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