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Publications Found: 32
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
Seasonal Variability Of Forest Sensitivity To Heat And Drought Stresses: A Synthesis Based On Carbon Fluxes From North American Forest Ecosystems
Xu, B., Arain, M. A., Black, T. A., Law, B. E., Pastorello, G. Z., Chu, H.

Climate extremes such as heat waves and droughts are projected to occur more Frequently with increasing temperature and an intensified hydrological cycle. It is Important to understand and quantify how forest carbon fluxes respond to heat and drought stress. In this study, we developed a series of daily indices of sensitivity to …


Journal: Global Change Biology, Volume 26 (2): 901-918 (2020), ISBN . DOI: 10.1111/gcb.14843 Sites: CA-Ca1, CA-Ca2, CA-Ca3, CA-Gro, CA-Man, CA-NS1, CA-NS2, CA-NS3, CA-NS4, CA-NS5, CA-Oas, CA-Obs, CA-Qfo, CA-SF2, CA-TP1, CA-TP2, CA-TP3, CA-TP4, US-Bar, US-Blo, US-GLE, US-Ha1, US-Ho1, US-Me2, US-Me3, US-Me6, US-MMS, US-NR1, US-Oho, US-PFa, US-Prr, US-Syv, US-UMB, US-UMd, US-WCr
Improved Spatiotemporal Representativeness And Bias Reduction Of Satellite-Based Evapotranspiration Retrievals Via Use Of In Situ Meteorology And Constrained Canopy Surface Resistance
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), ISBN . 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
Recovering Evapotranspiration Trends From Biased CMIP5 Simulations And Sensitivity To Changing Climate Over North America
Sullivan, R. C., Kotamarthi, V. R., Feng, Y.

Future projections of evapotranspiration (ET) are of critical importance for agricultural and freshwater management and for predicting land–atmosphere feedbacks on the climate system. However, ET from phase 5 of the Coupled Model Intercomparison Project (CMIP5) simulations exhibits substantial biases, bolstering little confidence …


Journal: Journal Of Hydrometeorology, Volume 20 (8): 1619-1633 (2019), ISBN . DOI: 10.1175/JHM-D-18-0259.1 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
Spatial Variation In Canopy Structure Across Forest Landscapes
Hardiman, B., LaRue, E., Atkins, J., Fahey, R., Wagner, F., Gough, C.


Journal: Forests, Volume 9 (8): 474 (2018), ISBN . DOI: 10.3390/f9080474 Sites: US-UMB, US-UMd
Forest Aging, Disturbance And The Carbon Cycle
Curtis, P. S., Gough, C. M.


Journal: New Phytologist, Volume 219 (4): 1188-1193 (2018), ISBN . DOI: 10.1111/nph.15227 Sites: US-UMB, US-UMd
Globally Rising Soil Heterotrophic Respiration Over Recent Decades
Bond-Lamberty, B., Bailey, V. L., Chen, M., Gough, C. M., Vargas, R.


Journal: Nature, Volume 560 (7716): 80-83 (2018), ISBN . DOI: 10.1038/s41586-018-0358-x Sites: US-UMB, US-UMd
Forest Canopy Structural Complexity And Light Absorption Relationships At The Subcontinental Scale
Atkins, J. W., Fahey, R. T., Hardiman, B. H., Gough, C. M.


Journal: Journal Of Geophysical Research: Biogeosciences, Volume 123 (4): 1387-1405 (2018), ISBN . DOI: 10.1002/2017JG004256 Sites: US-UMB, US-UMd
Linking Landsat To Terrestrial Lidar: Vegetation Metrics Of Forest Greenness Are Correlated With Canopy Structural Complexity
LaRue, E. A., Atkins, J. W., Dahlin, K., Fahey, R., Fei, S., Gough, C., Hardiman, B. S.


Journal: International Journal Of Applied Earth Observation And Geoinformation, Volume 73: 420-427 (2018), ISBN . DOI: 10.1016/j.jag.2018.07.001 Sites: US-UMB, US-UMd
Moderate Disturbance Has Similar Effects On Production Regardless Of Site Quality And Composition
Sagara, B., Fahey, R., Vogel, C., Fotis, A., Curtis, P., Gough, C.


Journal: Forests, Volume 9 (2): 70 (2018), ISBN . DOI: 10.3390/f9020070 Sites: US-UMB, US-UMd