Geophysical Research Letters, Volume 45, Issue 17


Anthology ID:
G18-30
Month:
Year:
2018
Address:
Venue:
GWF
SIG:
Publisher:
American Geophysical Union (AGU)
URL:
https://gwf-uwaterloo.github.io/gwf-publications/G18-30
DOI:
Bib Export formats:
BibTeX MODS XML EndNote

pdf bib
Temporal Dynamics of Aerodynamic Canopy Height Derived From Eddy Covariance Momentum Flux Data Across North American Flux Networks
Housen Chu | Dennis Baldocchi | C. Poindexter | Michael Abraha | Ankur R. Desai | Gil Bohrer | M. Altaf Arain | Timothy J. Griffis | Peter D. Blanken | Thomas L. O’Halloran | R. Quinn Thomas | Quan Zhang | Sean P. Burns | J. M. Frank | Christian Dold | Shannon Brown | T. Andrew Black | Christopher M. Gough | B. E. Law | Xuhui Lee | Jiquan Chen | David E. Reed | W. J. Massman | Kenneth L. Clark | Jerry L. Hatfield | John H. Prueger | Rosvel Bracho | John M. Baker | Timothy A. Martin

Author(s): Chu, H; Baldocchi, DD; Poindexter, C; Abraha, M; Desai, AR; Bohrer, G; Arain, MA; Griffis, T; Blanken, PD; O'Halloran, TL; Thomas, RQ; Zhang, Q; Burns, SP; Frank, JM; Christian, D; Brown, S; Black, TA; Gough, CM; Law, BE; Lee, X; Chen, J; Reed, DE; Massman, WJ; Clark, K; Hatfield, J; Prueger, J; Bracho, R; Baker, JM; Martin, TA | Abstract: 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 momentum-flux data. At 69 forest sites, annual ha robustly predicted site-to-site and year-to-year differences in canopy heights (R2n=n0.88, 111nsite-years). At 23 cropland/grassland sites, weekly ha successfully captured the dynamics of vegetation canopies over growing seasons (R2ngn0.70 in 74nsite-years). Our results demonstrate the potential of flux-derived ha determination for tracking the seasonal, interannual, and/or decadal dynamics of vegetation canopies including growth, harvest, land use change, and disturbance. The large-scale and time-varying ha derived from flux networks worldwide provides a new benchmark for regional and global Earth system models and satellite remote sensing of canopy structure.