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
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), ISBN . DOI: 10.1073/pnas.1900278116 Sites: US-NR1
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), ISBN . DOI: 10.1029/2018MS001476 Sites: US-NR1
Journal: Plant, Cell & Environment, Volume 42 (6): 1802-1815 (2019), ISBN . 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
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), ISBN . DOI: 10.1029/2018JG004613 Sites: US-NR1
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), ISBN . DOI: 10.1016/j.agrformet.2018.01.025 Sites: US-NR1
Journal: Journal Of Advances In Modeling Earth Systems, Volume : (2018), ISBN . DOI: 10.1002/2017MS001248 Sites: US-NR1
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), ISBN . 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: Oecologia, Volume 184 (1): 25-41 (2017), ISBN . DOI: 10.1007/s00442-017-3853-0 Sites: US-NR1
The seasonal pattern of the carbon isotope content (δ13C) of atmospheric CO2 depends on local and nonlocal land‐atmosphere exchange and atmospheric transport. Previous studies suggested that the δ13C of the net land‐atmosphere CO2 flux (δsource) varies seasonally as stomatal conductance of plants responds to vapor pressure …
Journal: Journal Of Geophysical Research: Biogeosciences, Volume 122 (8): 1969-1987 (2017), ISBN . DOI: https://doi.org/10.1002/2017JG003795 Sites: US-ARM, US-Ha1, US-Ho1, US-NR1, US-Wrc