Location: Southwest Watershed Research Center
Title: Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sitesAuthor
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CHU, H. - Lawrence Berkeley National Laboratory |
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LUO, X. - Lawrence Berkeley National Laboratory |
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OUYANG, Z. - Stanford University |
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CHAN, W.S. - Lawrence Berkeley National Laboratory |
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DENGEL, S. - Lawrence Berkeley National Laboratory |
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BIRAUD, S.C. - Lawrence Berkeley National Laboratory |
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TORN, M.S. - Lawrence Berkeley National Laboratory |
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METZGER, S. - Neon, Inc |
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KUMAR, J. - Oak Ridge National Laboratory |
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ARAIN, M.A. - McMaster University |
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ARKEBAUER, T.J. - University Of Nebraska |
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BALDOCCHI, D. - University Of California |
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BERNACCHI, D. - University Of Nebraska |
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BLACK, T.A. - University Of British Columbia |
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BLANKEN, P.D. - University Of Colorado |
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BOHRER, G. - The Ohio State University |
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BRACHO, R. - University Of Florida |
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BROWN, S. - University Of Guelph |
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BRUNSELL, N.A. - University Of Kansas |
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CHEN, J. - Michigan State University |
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CHEN, X. - Pacific Northwest National Laboratory |
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CLARK, K. - Us Forest Service (FS) |
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DESAI, A.R. - University Of Wisconsin |
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DUMAN, T. - University Of New Mexico |
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DURDEN, T. - Neon, Inc |
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FARES, S. - National Research Council - Italy |
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FORBRICH, I. - Woods Hole Marine Biological Laboratory |
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GAMON, J.A. - University Of Alberta |
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GRIFFIS, T. - University Of Minnesota |
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HELBIG, M. - Dalhousie University |
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HOLLINGER, D. - Us Forest Service (FS) |
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HUMPHREYS, E. - Carleton University - Canada |
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IKAWA, H. - National Agriculture And Food Research Organization (NARO), Agricultrual Research Center |
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IWATA, H. - Shinshu University |
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JU, Y. - The Ohio State University |
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Knowles, John |
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KNOX, S. - University Of British Columbia |
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KOBAYASHI, H. - Japan Agency For Marine-Earth Science And Technology (JAMSTEC) |
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KOLB, T. - Northern Arizona University |
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LAW, B. - Oregon State University |
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LEE, X. - Yale University |
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LITVAK, M. - University Of New Mexico |
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LIU, H. - Washington State University |
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MUNGER, J.W. - Harvard University |
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NOORMETS, A. - Texas A&M University |
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NOVICK, K. - Indiana University |
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OBERBAUER, S.F. - Florida International University |
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OECHEL, W. - San Diego State University |
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OIKAWA, P. - California State University |
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PAPUGA, S.A. - Wayne State University |
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PENDALL, E. - University Of Western Australia |
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PRAJAPATI, P. - Texas A&M University |
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Prueger, John |
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QUINTON, W.L. - Wilfrid Laurier University |
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RICHARDSON, A.D. - Northern Arizona University |
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RUSSELL, E.S. - Washington State University |
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Scott, Russell - Russ |
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STARR, G. - University Of Alabama |
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STAEBLER, R. - Environment And Climate Change Canada |
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STOY, P. - University Of Wisconsin |
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STUART-HAËNTJENS, E. - Us Geological Survey (USGS) |
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SONNENTAG, O. - Universite De Montreal |
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SULLIVAN, R.C. - Argonne National Laboratory |
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SUYKER, A. - University Of Nebraska |
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UEYAMA, M. - Osaka Prefecture University |
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VARGAS - University Of Delaware |
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WOOD, J.D. - University Of Missouri |
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ZONA, D. - San Diego State University |
Submitted to: Agricultural and Forest Meteorology
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 1/31/2021 Publication Date: 2/14/2021 Citation: Chu, H., Luo, X., Ouyang, Z., Chan, W., Dengel, S., Biraud, S., Torn, M., Metzger, S., Kumar, J., Arain, M., Arkebauer, T., Baldocchi, D., Bernacchi, D., Black, T., Blanken, P., Bohrer, G., Bracho, R., Brown, S., Brunsell, N., Chen, J., Chen, X., Clark, K., Desai, A., Duman, T., Durden, T., Fares, S., Forbrich, I., Gamon, J., Griffis, T., Helbig, M., Hollinger, D., Humphreys, E., Ikawa, H., Iwata, H., Ju, Y., Knowles, J.F., Knox, S., Kobayashi, H., Kolb, T., Law, B., Lee, X., Litvak, M., Liu, H., Munger, J., Noormets, A., Novick, K., Oberbauer, S., Oechel, W., Oikawa, P., Papuga, S., Pendall, E., Prajapati, P., Prueger, J.H., Quinton, W., Richardson, A., Russell, E., Scott, R.L., Starr, G., Staebler, R., Stoy, P., Stuart-Haëntjens, E., Sonnentag, O., Sullivan, R., Suyker, A., Ueyama, M., Vargas, Wood, J., Zona, D. 2021. Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites. Agricultural and Forest Meteorology. 301-302, Article 108350. https://doi.org/10.1016/j.agrformet.2021.108350. DOI: https://doi.org/10.1016/j.agrformet.2021.108350 Interpretive Summary: Tower-based measurements are the primary tool with which to benchmark satellite- or model-based fluxes of energy, water, and/or nutrient exchange between Earth’s surface and the atmosphere. These fluxes encompass the processes of photosynthesis, respiration, and evaporation that are critically important to water availability, ecosystem health, and greenhouse gas absorption and emission. However, the value of these benchmarking comparisons depends on the degree to which flux measurements from a single tower location represent the aggregated flux conditions over an area that is represented by a 106 – 108 m2 satellite- or model-based grid cell. As a result, the current study quantified how land cover and vegetation characteristics contribute to heterogeneity within the source area that contributes to measured tower-based fluxes (known as the flux “footprint”; typically ranges from 103 – 107 m2) at 214 sites across 13 vegetation classes. This analysis indicates that footprint heterogeneity over space and time can introduce a bias of between 4% and 20% into comparisons between tower and satellite- or model-derived data. Accordingly, we propose a set of representativeness indices to identify sites and/or time periods that may be suitable for specific applications. These indices are designed to promote “footprint awareness”, in order to guide effective model and data benchmarking. Technical 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 evaluated 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. The flux footprints varied across sites and through time depending on the measurement heights, underlying vegetation- and ground-surface characteristics, and turbulent state of the atmosphere. Monthly 80% footprint climatologies ranged four orders of magnitude from 103–107 m2. 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. And these biases were 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 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-years suitable for specific applications and to provide general guidance for data use. |