Publication Search
Burns, S. P., Humphrey, V., Gutmann, E. D., Raleigh, M. S.,, Bowling, D. R., Blanken, P. D.
Recent advances in the measurement of water content within a forest have led to new possibilities to study canopy evaporation. We used a pair of Global Navigation Satellite System (GNSS) receivers (one above the canopy and one near the forest floor) to calculate the vegetation optical depth (VOD) during the warm season in a Colorado …
Journal: Biogeosciences, Volume 22: 5741–5769 (2025). DOI: 10.5194/bg-22-5741-2025 Sites: US-NR1
Webb, R., Knowles, J., Fox, A., Fabricus, A., Corrie, T., Mooney, K., Gallais, J., Frimpong, N., Akurugu, C., Barron‐Gafford, G., Blanken, P., Burns, S., Frank, J., Litvak, M.
Journal: Hydrological Processes, Volume 38 (10): (2024). DOI: 10.1002/hyp.15297 Sites: US-GLE, US-Mpj, US-MtB, US-NR1, US-Vcm
Yang, J. C., Bowling, D. R., Smith, K. R., Kunik, L., Raczka, B., Anderegg, W. R., Bahn, M., Blanken, P. D., Richardson, A. D., Burns, S. P., Bohrer, G., Desai, A. R., Arain, M. A., Staebler, R. M., Ouimette, A. P., Munger, J. W., Litvak, M. E.
Journal: Agricultural And Forest Meteorology, Volume 353: 110054 (2024). DOI: 10.1016/j.agrformet.2024.110054 Sites: US-NR1
Javadian, M., Aubrecht, D. M., Fisher, J. B., Scott, R. L., Burns, S. P., Diehl, J. L., Munger, J. W., Richardson, A. D.
Understanding tree transpiration variability is vital for assessing ecosystem water-use efficiency and forest health amid climate change, yet most landscape-level measurements do not differentiate individual trees. Using canopy temperature data from thermal cameras, we estimated the transpiration rates of individual trees at Harvard …
Journal: Geophysical Research Letters, Volume 51 (20): (2024). DOI: https://doi.org/10.1029/2024GL111479 Sites: US-Ha1, US-NR1
Teets, A., Moore, D. J., Alexander, M. R., Blanken, P. D., Bohrer, G., Burns, S. P., Carbone, M. S., Ducey, M. J., Fraver, S., Gough, C. M., Hollinger, D. Y., Koch, G., Kolb, T., Munger, J. W., Novick, K. A., Ollinger, S. V., Ouimette, A. P., Pederson, N., Ricciuto, D. M., Seyednasrollah, B., Vogel, C. S., Richardson, A. D.
Linking biometric measurements of stand-level biomass growth to tower-based measurements of carbon uptake—gross primary productivity and net ecosystem productivity—has been the focus of numerous ecosystem-level studies aimed to better understand the factors regulating carbon allocation to slow-turnover wood biomass pools. However, …
Journal: Journal Of Geophysical Research: Biogeosciences, Volume 127 (4): (2022). DOI: 10.1029/2021JG006690 Sites: US-Bar, US-Ha1, US-Ho1, US-MMS, US-NR1, US-UMB
Braghiere,R.K., Wang,Y., Doughty,R., Sousa,D., Magney,T., Widlowski,J.-L., Longo,M., Bloom,A.A., Worden,J., Gentine,P., Frankenberg,C.
Three-dimensional (3D) vegetation canopy structure plays an important role in the way radiation interacts with the land surface. Accurately representing this process in Earth System models (ESMs) is crucial for the modeling of the global carbon, energy, and water cycles and hence future climate projections. Despite the importance …
Journal: Remote Sensing of Environment, Volume 261: (2021). DOI: https://doi.org/10.1016/j.rse.2021.112497 Sites: US-NR1, US-UMB
Burns, S. P., Frank, J. M., Massman, W. J., Patton, E. G., Blanken, P. D.
Journal: Agricultural And Forest Meteorology, Volume 306: 108402 (2021). DOI: 10.1016/j.agrformet.2021.108402 Sites: US-GLE, US-NR1
Wang, Y., Köhler, P., He, L., Doughty, R., Braghiere, R. K., Wood, J. D., Frankenberg, C.
Journal: Geoscientific Model Development, Volume 14 (11): 6741-6763 (2021). DOI: https://doi.org/10.5194/gmd-14-6741-2021 Sites: US-MOz, US-NR1
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
Tai, X., Anderegg, W. R., Blanken, P. D., Burns, S. P., Christensen, L., Brooks, P. D.
Journal: Water Resources Research, Volume 56 (11): (2020). DOI: 10.1029/2020WR027630 Sites: US-NR1