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Publications Found: 5
Representativeness Of Eddy-Covariance Flux Footprints For Areas Surrounding Ameriflux Sites
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.

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 …


Journal: Agricultural And Forest Meteorology, Volume 301-302: 108350 (2021), ISBN . DOI: 10.1016/j.agrformet.2021.108350 Sites: CA-ARB, CA-ARF, CA-Ca1, CA-Ca2, CA-Ca3, CA-Cbo, CA-DBB, CA-ER1, CA-Gro, CA-Let, CA-Man, CA-MR3, CA-MR5, CA-Na1, CA-NS1, CA-NS2, CA-NS3, CA-NS4, CA-NS5, CA-NS6, CA-NS7, CA-Oas, CA-Obs, CA-Ojp, CA-Qc2, CA-Qcu, CA-Qfo, CA-SCC, CA-SF1, CA-SF2, CA-SF3, CA-SJ2, CA-SJ3, CA-TP1, CA-TP3, CA-TP4, CA-TPD, CA-WP1, US-A03, US-A10, US-A32, US-A74, US-ADR, US-AR1, US-AR2, US-ARb, US-ARc, US-ARM, US-Aud, US-Bar, US-Bi1, US-Bi2, US-Bkg, US-Blk, US-Blo, US-Bn1, US-Bn2, US-Bn3, US-Bo1, US-Bo2, US-Br3, US-CaV, US-Ced, US-CF1, US-CF2, US-CF3, US-CF4, US-ChR, US-Cop, US-CPk, US-CRT, US-Ctn, US-Dia, US-Dix, US-Dk1, US-Dk2, US-Dk3, US-EDN, US-Elm, US-EML, US-Fmf, US-FPe, US-FR2, US-FR3, US-Fuf, US-Fwf, US-GLE, US-GMF, US-Goo, US-Ha1, US-Ha2, US-Hn2, US-Hn3, US-Ho1, US-Ho2, US-Ho3, US-IB1, US-IB2, US-Ivo, US-KFS, US-KLS, US-Kon, US-KS1, US-KS2, US-KUT, US-Lin, US-Los, US-LPH, US-LWW, US-Me1, US-Me2, US-Me3, US-Me4, US-Me5, US-Me6, US-MMS, US-MOz, US-Mpj, US-MRf, US-MtB, US-Myb, US-NC1, US-NC2, US-NC3, US-NC4, US-Ne1, US-Ne2, US-Ne3, US-NGB, US-NR1, US-Oho, US-ORv, US-PHM, US-Pon, US-Prr, US-RC1, US-RC2, US-RC3, US-RC4, US-RC5, US-Rls, US-Rms, US-Ro1, US-Ro2, US-Ro5, US-Ro6, US-Rpf, US-Rws, US-SdH, US-Seg, US-Ses, US-SFP, US-Shd, US-Skr, US-Slt, US-Snd, US-Sne, US-Snf, US-SO2, US-SO3, US-SO4, US-SP1, US-SP2, US-SP3, US-SRC, US-SRG, US-SRM, US-Srr, US-Sta, US-StJ, US-Syv, US-Ton, US-Tw1, US-Tw2, US-Tw3, US-Tw4, US-Tw5, US-Twt, US-Uaf, US-UMB, US-UMd, US-Var, US-Vcm, US-Vcp, US-Vcs, US-WBW, US-WCr, US-Wdn, US-Wgr, US-Whs, US-Wi0, US-Wi1, US-Wi3, US-Wi4, US-Wi5, US-Wi6, US-Wi7, US-Wi8, US-Wi9, US-Wjs, US-Wkg, US-Wlr, US-Wpp, US-WPT, US-Wrc, US-xBR, US-xCP, US-xDL, US-xHA, US-xKA, US-xKZ, US-xRM, US-xSR, US-xWD
The Influence Of Hydrological Variability On Inherent Water Use Efficiency In Forests Of Contrasting Composition, Age, And Precipitation Regimes In The Pacific Northwest
Kwon, H., Law, B. E., Thomas, C. K., Johnson, B. G.

The Pacific Northwest (PNW) region of the United States has some of the most productive forests in the world. As precipitation regimes may shift with changing climate in this area, droughts are predicted to increase in both frequency and degree of severity, which will have a significant impact on already drought-prone ecosystems. …


Journal: Agricultural And Forest Meteorology, Volume 249: 488-500 (2018), ISBN . DOI: doi:10.1016/j.agrformet.2017.08.006 Sites: US-Me2, US-Me3, US-MRf
Temporal Dynamics Of Aerodynamic Canopy Height Derived From Eddy Covariance Momentum Flux Data Across North American Flux Networks
Chu, H., Baldocchi, D. D., Poindexter, C., Abraha, M., Desai, A. R., Bohrer, G., Arain, M. A., Griffis, T., Blanken, P. D., O'Halloran, T. L., Thomas, R. Q., Zhang, Q., Burns, S. P., Frank, J. M., Christian, D., Brown, S., Black, T. A., Gough, C. M., Law, B. E., Lee, X., Chen, J., Reed, D. E., Massman, W. J., Clark, K., Hatfield, J., Prueger, J., Bracho, R., Baker, J. M., Martin, T. A.

Aerodynamic canopy height (ha) is the effective height of vegetation canopy for its influence on atmospheric fluxes and is a key parameter of surface‐atmosphere coupling. However, methods to estimate ha from data are limited. This synthesis evaluates the applicability and robustness of the calculation of ha from eddy covariance …


Journal: Geophysical Research Letters, Volume 45: 9275–9287 (2018), ISBN . DOI: 10.1029/2018GL079306 Sites: BR-Sa1, BR-Sa3, CA-Ca1, CA-Ca2, CA-Ca3, CA-Cbo, CA-ER1, CA-Gro, CA-Man, CA-NS1, CA-NS2, CA-NS3, CA-NS4, CA-NS5, CA-Oas, CA-Obs, CA-Ojp, CA-Qfo, CA-TP1, CA-TP3, CA-TP4, CA-TPD, US-Blo, US-Bn1, US-Bn2, US-Br1, US-Br3, US-Ced, US-CPk, US-CRT, US-Dix, US-Dk2, US-Dk3, US-Fmf, US-Fuf, US-GBT, US-GLE, US-GMF, US-Ha1, US-Ha2, US-Ho2, US-Ho3, US-IB1, US-IB2, US-KL1, US-KL2, US-KL3, US-KM1, US-KM2, US-KM3, US-KM4, US-Me2, US-Me3, US-Me4, US-Me5, US-Me6, US-MMS, US-MRf, US-NC1, US-NC2, US-Ne1, US-Ne2, US-Ne3, US-NR1, US-Oho, US-Prr, US-Ro1, US-Ro3, US-SB1, US-Shd, US-Skr, US-Slt, US-SP1, US-SP2, US-SP3, US-SRM, US-Srr, US-Syv, US-Ton, US-Tw3, US-Twt, US-UMB, US-UMd, US-Var, US-Vcm, US-WBW, US-Wi0, US-Wi1, US-Wi3, US-Wi4, US-Wi5, US-Wi8, US-Wi9, US-Wrc
Bayesian Optimization Of The Community Land Model Simulated Biosphere–Atmosphere Exchange Using Co2observations From A Dense Tower Network And Aircraft Campaigns Over Oregon
Schmidt, A., Law, B. E., Göckede, M., Hanson, C., Yang, Z., Conley, S.


Journal: Earth Interactions, Volume 20 (22): 1-35 (2016), ISBN . DOI: 10.1175/EI-D-16-0011.1 Sites: US-MRf
The Increasing Importance Of Atmospheric Demand For Ecosystem Water And Carbon Fluxes
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.


Journal: Nature Climate Change, Volume 6 (11): 1023-1027 (2016), ISBN . DOI: 10.1038/nclimate3114 Sites: US-ARM, US-Bar, US-Blk, US-Blo, US-Bo1, US-Br3, US-Dk1, US-Dk2, US-Dk3, US-Fmf, US-FR2, US-Fuf, US-GLE, US-IB1, US-IB2, US-KFS, US-Kon, US-KS2, US-Me1, US-Me2, US-MMS, US-MOz, US-MRf, US-Ne1, US-Ne3, US-NR1, US-Oho, US-SRG, US-SRM, US-Syv, US-Ton, US-UMB, US-Var, US-WBW, US-WCr, US-Whs, US-Wkg