Zobrazeno 1 - 10
of 24
pro vyhledávání: '"K. T. PAW U"'
Publikováno v:
Biogeosciences, Vol 15, Pp 2945-2960 (2018)
The ACASA (Advanced Canopy–Atmosphere–Soil Algorithm) model, with a higher-order closure for tall vegetation, has already been successfully tested and validated for homogeneous spruce forests. The aim of this paper is to test the model using
Externí odkaz:
https://doaj.org/article/c29ffdbed27a498aa227c8770272bd0a
Publikováno v:
Geoscientific Model Development, Vol 7, Iss 6, Pp 2917-2932 (2014)
In this study, the Weather Research and Forecasting (WRF) model is coupled with the Advanced Canopy–Atmosphere–Soil Algorithm (ACASA), a high-complexity land surface model. Although WRF is a state-of-the-art regional atmospheric model with high s
Externí odkaz:
https://doaj.org/article/7c7a6cd2502648fa99b18bc28ef82803
Publikováno v:
Biogeosciences, Vol 10, Iss 7, Pp 4419-4432 (2013)
It is not well understood whether coastal upwelling is a net CO2 source to the atmosphere or a net CO2 sink to the ocean due to high temporal variability of air–sea CO2 exchange (CO2 flux) in coastal upwelling zones. Upwelling transports heterotrop
Externí odkaz:
https://doaj.org/article/4d0e02aa4f424bdd9ea621d408184c45
Publikováno v:
Biogeosciences, Vol 7, Iss 11, Pp 3685-3705 (2010)
The sensitivity and predictive uncertainty of the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA) was assessed by employing the Generalized Likelihood Uncertainty Estimation (GLUE) method. ACASA is a stand-scale, multi-layer soil-vegetation-atmosph
Externí odkaz:
https://doaj.org/article/79bab7644556448bbee72afa18ae1bb2
Autor:
L. Montagnani, J. H. McCaughey, J. Campos, G. Wohlfahrt, N. Arriga, B. E. Law, M. Detto, M. Reichstein, M. D. Mahecha, J. Stanovick, G. G. Katul, D. D. Baldocchi, A. D. Richardson, P. C. Stoy, K. T. Paw U, S. Sevanto, M. Williams
Publikováno v:
Biogeosciences, Vol 6, Iss 10, Pp 2297-2312 (2009)
The net ecosystem exchange of CO2 (NEE) varies at time scales from seconds to years and longer via the response of its components, gross ecosystem productivity (GEP) and ecosystem respiration (RE), to physical and biological drivers. Quantifying the
Externí odkaz:
https://doaj.org/article/d0d06b80b8a34eee96e6273197d62e56
Autor:
A. J. Wong, Y. Jin, J. Medellín‐Azuara, K. T. Paw U, E. R. Kent, J. M. Clay, F. Gao, J. B. Fisher, G. Rivera, C. M. Lee, K. S. Hemes, E. Eichelmann, D. D. Baldocchi, S. J. Hook
Publikováno v:
Water Resources Research
Water resources research, vol 57, iss 9
Water resources research, vol 57, iss 9
Spatial estimates of crop evapotranspiration with high accuracy from the field to watershed scale have become increasingly important for water management, particularly over irrigated agriculture in semiarid regions. Here, we provide a comprehensive a
Autor:
K. T. Paw U, S. L. Ustin, R. D. Pyles, Matthias Falk, L. Xu, M. L. Whiting, B. L. Sanden, P. H. Brown
Publikováno v:
Journal of Hydrometeorology. 15:744-758
Among the uncertain consequences of climate change on agriculture are changes in timing and quantity of precipitation together with predicted higher temperatures and changes in length of growing season. The understanding of how these uncertainties wi
Publikováno v:
Boundary-Layer Meteorology. 145:27-44
Ramp features in the turbulent scalar field are associated with turbulent coherent structures, which dominate energy and mass fluxes in the atmospheric surface layer. Although finer scale ramp-like shapes embedded within larger scale ramp-like shapes
Publikováno v:
Boundary-Layer Meteorology. 145:5-25
Structure functions are used to study the dissipation and inertial range scales of turbulent energy, to parametrize remote turbulence measurements, and to characterize ramp features in the turbulent field. Ramp features are associated with turbulent
Publikováno v:
Global Change Biology. 16:1870-1882
Greenhouse gas fluxes from vegetated drained lake basins have been largely unstudied, although these land features constitute up to 47% of the land cover in the Arctic Coastal Plain in northern Alaska. To describe current and to better predict future