Publication Search
Xia, Y., Sanderman, J., Watts, J. D., Machmuller, M. B., Mullen, A. L., Rivard, C., Endsley, A., Hernandez, H., Kimball, J., Ewing, S. A., Litvak, M., Duman, T., Krishnan, P., Meyers, T., Brunsell, N. A., Mohanty, B., Liu, H., Gao, Z., Chen, J., Abraha, M., Scott, R. L., Flerchinger, G. N., Clark, P. E., Stoy, P. C., Khan, A. M., Brookshire, E. N., Zhang, Q., Cook, D. R., Thienelt, T., Mitra, B., Mauritz‐Tozer, M., Tweedie, C. E., Torn, M. S., Billesbach, D.
Rangelands provide significant environmental benefits through many ecosystem services, which may include soil organic carbon (SOC) sequestration. However, quantifying SOC stocks and monitoring carbon (C) fluxes in rangelands are challenging due to the considerable spatial and temporal variability tied to rangeland C dynamics as well …
Journal: Journal Of Advances In Modeling Earth Systems, Volume 17 (3): (2025). DOI: 10.1029/2024MS004342 Sites: US-A32, US-AR1, US-AR2, US-ARb, US-ARc, US-Aud, US-Bkg, US-BMM, US-BRG, US-Cop, US-Ctn, US-CZ1, US-Dia, US-FPe, US-Fwf, US-Hn1, US-Hn2, US-IB2, US-Jo1, US-KFS, US-KLS, US-KM2, US-KM3, US-KM4, US-Kon, US-LS1, US-LS2, US-Mpj, US-RFW, US-Rls, US-Rms, US-Ro4, US-Rwe, US-Rwf, US-Rws, US-SCg, US-SdH, US-Seg, US-Ses, US-Snd, US-SRM, US-Ton, US-Tx1, US-Tx2, US-Var, US-Wdn, US-Wjs, US-Wkg, US-xAE, US-xCL, US-xCP, US-xDC, US-xJR, US-xKA, US-xKZ, US-xMB, US-xNG, US-xNQ, US-xSJ, US-xWD, US-xYE
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). 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
Baldocchi, D., Ma, S., Verfaillie, J.
Journal: Global Change Biology, Volume 27 (2): 359-375 (2021). DOI: 10.1111/gcb.15414 Sites: US-Ton, US-Var
Braghiere, R. K., Quaife, T., Black, E., Ryu, Y., Chen, Q., De Kauwe, M. G., Baldocchi, D.
Journal: Agricultural And Forest Meteorology, Volume 291: 108065 (2020). DOI: 10.1016/j.agrformet.2020.108065 Sites: CA-Oas, US-Ton
Ma, S., Eichelmann, E., Wolf, S., Rey-Sanchez, C., Baldocchi, D. D.
Journal: Agricultural And Forest Meteorology, Volume 295: 108204 (2020). DOI: 10.1016/j.agrformet.2020.108204 Sites: US-Ton, US-Var
Baldocchi, D. D., Ryu, Y., Dechant, B., Eichelmann, E., Hemes, K., Ma, S., Sanchez, C. R., Shortt, R., Szutu, D., Valach, A., Verfaillie, J., Badgley, G., Zeng, Y., Berry, J. A.
Journal: Journal Of Geophysical Research: Biogeosciences, Volume 125 (7): (2020). DOI: 10.1029/2019jg005534 Sites: US-Bi1, US-Bi2, US-Ton, US-Tw1, US-Var
Zhang, Q., Ficklin, D. L., Manzoni, S., Wang, L., Way, D., Phillips, R. P., Novick, K. A.
Journal: Environmental Research Letters, Volume 14 (7): 074023 (2019). DOI: 10.1088/1748-9326/ab2603 Sites: CA-NS1, CA-NS2, CA-NS3, CA-NS4, CA-NS6, CA-NS7, US-AR1, US-AR2, US-ARM, US-Blo, US-GLE, US-KS2, US-Me2, US-MMS, US-Ne1, US-Ne2, US-Ne3, US-NR1, US-SRG, US-SRM, US-Syv, US-Ton, US-UMB, US-Var, US-WCr, US-Whs
Novick, K. A., Konings, A. G., Gentine, P.
Journal: Plant, Cell & Environment, Volume 42 (6): 1802-1815 (2019). DOI: 10.1111/pce.13517 Sites: US-ARM, US-Blo, US-GLE, US-KS2, US-MMS, US-Ne3, US-NR1, US-SRG, US-SRM, US-Ton, US-Var, US-WCr, US-Whs, US-Wkg
Sadeghi, M., Tuller, M., Warrick, A. W., Babaeian, E., Parajuli, K., Gohardoust, M. R., Jones, S. B.
The accurate determination of land surface water fluxes at various spatiotemporal scales remains a challenge in hydrological sciences. It is intuitive that land surface net water flux (i.e., infiltration minus evapotranspiration) directly affects near-surface soil moisture. However, there exists no hydrological model suitable to …
Journal: Journal of Hydrology, Volume 570: 26-37 (2019). DOI: 10.1016/j.jhydrol.2018.12.038 Sites: US-Ton
Sullivan, R. C., Cook, D. R., Ghate, V. P., Kotamarthi, V. R., Feng, Y.
Evapotranspiration (ET) is a key component of the atmospheric and terrestrial water and energy budgets. Satellite‐based vegetation index approaches have used remotely sensed vegetation and reanalysis meteorological properties with surface energy balance models to estimate global ET (MOD16 ET). We reconstructed satellite retrievals …
Journal: Journal Of Geophysical Research: Biogeosciences, Volume 124 (2): 342-352 (2019). DOI: 10.1029/2018JG004744 Sites: US-AR1, US-AR2, US-ARM, US-Blo, US-Cop, US-GLE, US-Ha1, US-Los, US-Me2, US-Me6, US-MMS, US-Myb, US-Ne1, US-Ne2, US-Ne3, US-NR1, US-ORv, US-PFa, US-SRG, US-SRM, US-Syv, US-Ton, US-Tw1, US-Tw2, US-Tw3, US-Tw4, US-Twt, US-UMB, US-UMd, US-Var, US-WCr, US-Whs, US-Wkg
