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Title: Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites
Authors: Chu, Housen
Luo, Xiangzhong 
Ouyang, Zutao
Chan, W. Stephen
Dengel, Sigrid
Biraud, Sebastien C.
Torn, Margaret S.
Metzger, Stefan
Kumar, Jitendra
Arain, M. Altaf
Arkebauer, Tim J.
Baldocchi, Dennis
Bernacchi, Carl
Billesbach, Dave
Black, T. Andrew
Blanken, Peter D.
Bohrer, Gil
Bracho, Rosvel
Brown, Shannon
Brunsell, Nathaniel A.
Chen, Jiquan
Chen, Xingyuan
Clark, Kenneth
Desai, Ankur R.
Duman, Tomer
Durden, David
Fares, Silvano
Forbrich, Inke
Gamon, John A.
Gough, Christopher M.
Griffis, Timothy
Helbig, Manuel
Hollinger, David
Humphreys, Elyn
Ikawa, Hiroki
Iwata, Hiroki
Ju, Yang
Knowles, John F.
Knox, Sara H.
Kobayashi, Hideki
Kolb, Thomas
Law, Beverly
Lee, Xuhui
Litvak, Marcy
Liu, Heping
Munger, J. William
Noormets, Asko
Novick, Kim
Oberbauer, Steven F.
Oechel, Walter
Oikawa, Patty
Papuga, Shirley A.
Pendall, Elise
Prajapati, Prajaya
Prueger, John
Quinton, William L.
Richardson, Andrew D.
Russell, Eric S.
Scott, Russell L.
Starr, Gregory
Staebler, Ralf
Stoy, Paul C.
Stuart-Haëntjens, E.
Sonnentag, Oliver
Sullivan, Ryan C.
Suyker, Andy
Ueyama, Masahito
Vargas, Rodrigo
Wood, Jeffrey D.
Zona, Donatella
Keywords: Flux footprint
Land cover
Landsat EVI
Model-data benchmarking
Sensor location bias
Spatial representativeness
Issue Date: 1-May-2021
Publisher: Elsevier B.V.
Citation: Chu, Housen, Luo, Xiangzhong, Ouyang, Zutao, Chan, W. Stephen, Dengel, Sigrid, Biraud, Sebastien C., Torn, Margaret S., Metzger, Stefan, Kumar, Jitendra, Arain, M. Altaf, Arkebauer, Tim J., Baldocchi, Dennis, Bernacchi, Carl, Billesbach, Dave, Black, T. Andrew, Blanken, Peter D., Bohrer, Gil, Bracho, Rosvel, Brown, Shannon, Brunsell, Nathaniel A., Chen, Jiquan, Chen, Xingyuan, Clark, Kenneth, Desai, Ankur R., Duman, Tomer, Durden, David, Fares, Silvano, Forbrich, Inke, Gamon, John A., Gough, Christopher M., Griffis, Timothy, Helbig, Manuel, Hollinger, David, Humphreys, Elyn, Ikawa, Hiroki, Iwata, Hiroki, Ju, Yang, Knowles, John F., Knox, Sara H., Kobayashi, Hideki, Kolb, Thomas, Law, Beverly, Lee, Xuhui, Litvak, Marcy, Liu, Heping, Munger, J. William, Noormets, Asko, Novick, Kim, Oberbauer, Steven F., Oechel, Walter, Oikawa, Patty, Papuga, Shirley A., Pendall, Elise, Prajapati, Prajaya, Prueger, John, Quinton, William L., Richardson, Andrew D., Russell, Eric S., Scott, Russell L., Starr, Gregory, Staebler, Ralf, Stoy, Paul C., Stuart-Haëntjens, E., Sonnentag, Oliver, Sullivan, Ryan C., Suyker, Andy, Ueyama, Masahito, Vargas, Rodrigo, Wood, Jeffrey D., Zona, Donatella (2021-05-01). Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites. Agricultural and Forest Meteorology 301-302 : 108350. ScholarBank@NUS Repository.
Rights: Attribution 4.0 International
Abstract: Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 103 to 107 m2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applications and to provide general guidance for data use. © 2021
Source Title: Agricultural and Forest Meteorology
ISSN: 0168-1923
DOI: 10.1016/j.agrformet.2021.108350
Rights: Attribution 4.0 International
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