Publication Search
Knowles, J. F., Scott, R. L., Biederman, J. A., Blanken, P. D., Burns, S. P., Dore, S., Kolb, T. E., Litvak, M. E., Barron‐Gafford, G. A.
High-elevation montane forests are disproportionately important to carbon sequestration
in semiarid climates where low elevations are dry and characterized by low
carbon density ecosystems. However, these ecosystems are increasingly threatened
by climate change with seasonal implications for photosynthesis and forest growth.
As …
Journal: Global Change Biology, Volume 26 (12): 6945-6958 (2020). DOI: 10.1111/gcb.15335 Sites: US-Fuf, US-MtB, US-NR1, US-Vcm, US-Vcp, US-Vcs
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
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
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). 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
Magney, T. S., Bowling, D. R., Logan, B. A., Grossmann, K., Stutz, J., Blanken, P. D., Burns, S. P., Cheng, R., Garcia, M. A., Kӧhler, P., Lopez, S., Parazoo, N. C., Raczka, B., Schimel, D., Frankenberg, C.
Northern hemisphere evergreen forests assimilate a significant fraction of global atmospheric CO2 but monitoring large-scale changes in gross primary production (GPP) in these systems is challenging. Recent advances in remote sensing allow the detection of solar-induced chlorophyll fluorescence (SIF) emission from vegetation, which …
Journal: Proceedings Of The National Academy Of Sciences, Volume : 201900278 (2019). DOI: 10.1073/pnas.1900278116 Sites: US-NR1
Swenson, S. C., Burns, S. P., Lawrence, D. M.
Atmospheric models used for weather prediction and future climate projections rely on land models to calculate surface boundary conditions. Observations of near‐surface states and fluxes made at flux measurement sites provide valuable data with which to assess the quality of simulated lower boundary conditions. A previous assessment …
Journal: Journal Of Advances In Modeling Earth Systems, Volume 11 (1): 83-98 (2019). DOI: 10.1029/2018MS001476 Sites: US-NR1
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
Berryman, E. M., Vanderhoof, M. K., Bradford, J. B., Hawbaker, T. J., Henne, P. D., Burns, S. P., Frank, J. M., Birdsey, R. A., Ryan, M. G.
Landscape carbon (C) flux estimates help assess the ability of terrestrial ecosystems to buffer further increases in anthropogenic carbon dioxide (CO2) emissions. Advances in remote sensing have led to coarse‐scale estimates of gross primary productivity (GPP; e.g., MODIS 17), yet efforts to develop spatial respiration products …
Journal: Journal Of Geophysical Research: Biogeosciences, Volume 123 (10): 3231-3249 (2018). DOI: 10.1029/2018JG004613 Sites: US-NR1
Bowling, D. R., Logan, B. A., Hufkens, K., Aubrecht, D. M., Richardson, A. D., Burns, S. P., Anderegg, W. R., Blanken, P. D., Eiriksson, D. P.
Temperate and boreal conifer forests are dormant for many months during the cold season. Climate change is altering the winter environment, with increased temperature, altered precipitation, and earlier snowmelt in many locations. If significant enough, these changes may alter patterns of dormancy and activity of evergreens. Here …
Journal: Agricultural And Forest Meteorology, Volume 252: 241-255 (2018). DOI: 10.1016/j.agrformet.2018.01.025 Sites: US-NR1
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). 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