Canopy temperature Tcan is a key driver of plant function that emerges as a result of interacting biotic and abiotic processes and properties. However, understanding controls on Tcan and forecasting canopy responses to weather extremes and climate change are difficult due to sparse measurements of Tcan at appropriate spatial and …
Journal: New Phytologist, Volume 230 (5): 1746-1753 (2021). DOI: https://doi.org/10.1111/nph.17321 Sites: US-Me2, US-Wrc
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
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). 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
Temperature is a primary environmental control on ecological systems and processes at a range of spatial and temporal scales. The surface temperature of organisms is often more relevant for ecological processes than air temperature, which is much more commonly measured. Surface temperature influences—and is influenced by—a range …
Journal: Ecosphere, Volume 10 (6): (2019). DOI: https://doi.org/10.1002/ecs2.2768 Sites: US-Me2, US-Wrc
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
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
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). 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
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). DOI: doi:10.1016/j.agrformet.2017.08.006 Sites: US-Me2, US-Me3, US-MRf
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). 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
Journal: Nature Climate Change, Volume 6 (11): 1023-1027 (2016). 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