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Title: Temporal Dynamics of Aerodynamic Canopy Height Derived From Eddy Covariance Momentum Flux Data Across North American Flux Networks

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 ( R2 = 0.88, 111 site-years). At 23 cropland/grassland sites, weekly ha successfully captured the dynamics of vegetation canopies over growing seasons ( R2 > 0.70 in 74 site-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.

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3];  [4]; ORCiD logo [5]; ORCiD logo [6]; ORCiD logo [7]; ORCiD logo [8]; ORCiD logo [9];  [10]; ORCiD logo [11];  [12]; ORCiD logo [9]; ORCiD logo [13];  [14]; ORCiD logo [15];  [16]; ORCiD logo [17];  [18]; ORCiD logo [19] more »; ORCiD logo [20]; ORCiD logo [20]; ORCiD logo [13];  [13];  [14];  [14];  [21];  [22];  [21] « less
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Earth and Environmental Sciences Area; Univ. of California, Berkeley CA (United States). Dept. of Environmental Sciences, Policy, and Management
  2. Univ. of California, Berkeley CA (United States). Dept. of Environmental Sciences, Policy, and Management
  3. California State Univ., Sacramento CA (United States). Dept. of Civil Engineering
  4. Michigan State Univ., East Lansing, MI (United States). Great Lakes Bioenergy Research Center
  5. Univ. of Wisconsin-Madison, Madison, WI (United States). Dept. of Atmospheric and Oceanic Sciences
  6. The Ohio State Univ., Columbus, OH (United States). Dept. of Civil, Environmental and Geodetic Engineering
  7. McMaster Univ., Hamilton, Ontario (Canada). School of Geography and Earth Sciences
  8. Univ. of Minnesota, Minneapolis, MN (United States). Dept. of Soil, Water, and Climate
  9. Univ. of Colorado, Boulder, CO (United States). Dept. of Geography
  10. Clemson Univ., Clemson, SC (United States). Forestry and Environmental Conservation Dept.
  11. Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States). Dept. of Forest Resources and Environmental Conservation
  12. Wuhan Univ., Wuhan (China). State Key Lab. of Water Resources and Hydropower Engineering Science; Indiana University, Bloomington, IN (United States). School of Public and Environmental Affairs
  13. USDA-Forest Service, Rocky Mountain Research Station, Fort Collins, CO (United States)
  14. US Dept. of Agriculture (USDA)., Ames, IA (United States). National Lab. for Agriculture and the Environment
  15. Univ. of Guelph, Guelph, ON (Canada). School of Environmental Sciences
  16. Univ. of British Columbia, Vancouver, BC (Canada). Faculty of Land and Food Systems
  17. Virginia Commonwealth University, Richmond VA (United States). Dept. of Biology
  18. Oregon State Univ., Corvallis, OR (United States). Dept. of Forest Ecosystems and Society
  19. Yale Univ., New Haven, CT (United States). School of Forestry and Environmental Studies
  20. Michigan State Univ., East Lansing, MI (United States). Dept. of Geography, Environment, and Spatial Sciences
  21. Univ. of Florida, Gainesville, FL (United States). School of Forest Resources and Conservation
  22. Univ. of Minnesota, Minneapolis, MN (United States). Department of Soil, Water, and Climate; USDA-Agricultural Research Service, Saint Paul, MN (United States). Soil and Water Research Unit
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1561895
Alternate Identifier(s):
OSTI ID: 1468829
Grant/Contract Number:  
AC02-05CH11231; SC0012456
Resource Type:
Accepted Manuscript
Journal Name:
Geophysical Research Letters
Additional Journal Information:
Journal Volume: 45; Journal Issue: 17; Journal ID: ISSN 0094-8276
Publisher:
American Geophysical Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; momentum flux; AmeriFlux; eddy covariance; canopy height; phenology

Citation Formats

Chu, Housen, Baldocchi, Dennis D., Poindexter, Cristina, Abraha, Michael, Desai, Ankur R., Bohrer, Gil, Arain, M. Altaf, Griffis, Timothy, Blanken, Peter D., O'Halloran, Thomas L., Thomas, R. Quinn, Zhang, Quan, Burns, Sean P., Frank, John M., Christian, Dold, Brown, Shannon, Black, T. Andrew, Gough, Christopher M., Law, Beverly E., Lee, Xuhui, Chen, Jiquan, Reed, David E., Massman, William J., Clark, Kenneth, Hatfield, Jerry, Prueger, John, Bracho, Rosvel, Baker, John M., and Martin, Timothy A. Temporal Dynamics of Aerodynamic Canopy Height Derived From Eddy Covariance Momentum Flux Data Across North American Flux Networks. United States: N. p., 2018. Web. doi:10.1029/2018gl079306.
Chu, Housen, Baldocchi, Dennis D., Poindexter, Cristina, Abraha, Michael, Desai, Ankur R., Bohrer, Gil, Arain, M. Altaf, Griffis, Timothy, Blanken, Peter D., O'Halloran, Thomas L., Thomas, R. Quinn, Zhang, Quan, Burns, Sean P., Frank, John M., Christian, Dold, Brown, Shannon, Black, T. Andrew, Gough, Christopher M., Law, Beverly E., Lee, Xuhui, Chen, Jiquan, Reed, David E., Massman, William J., Clark, Kenneth, Hatfield, Jerry, Prueger, John, Bracho, Rosvel, Baker, John M., & Martin, Timothy A. Temporal Dynamics of Aerodynamic Canopy Height Derived From Eddy Covariance Momentum Flux Data Across North American Flux Networks. United States. doi:10.1029/2018gl079306.
Chu, Housen, Baldocchi, Dennis D., Poindexter, Cristina, Abraha, Michael, Desai, Ankur R., Bohrer, Gil, Arain, M. Altaf, Griffis, Timothy, Blanken, Peter D., O'Halloran, Thomas L., Thomas, R. Quinn, Zhang, Quan, Burns, Sean P., Frank, John M., Christian, Dold, Brown, Shannon, Black, T. Andrew, Gough, Christopher M., Law, Beverly E., Lee, Xuhui, Chen, Jiquan, Reed, David E., Massman, William J., Clark, Kenneth, Hatfield, Jerry, Prueger, John, Bracho, Rosvel, Baker, John M., and Martin, Timothy A. Fri . "Temporal Dynamics of Aerodynamic Canopy Height Derived From Eddy Covariance Momentum Flux Data Across North American Flux Networks". United States. doi:10.1029/2018gl079306. https://www.osti.gov/servlets/purl/1561895.
@article{osti_1561895,
title = {Temporal Dynamics of Aerodynamic Canopy Height Derived From Eddy Covariance Momentum Flux Data Across North American Flux Networks},
author = {Chu, Housen and Baldocchi, Dennis D. and Poindexter, Cristina and Abraha, Michael and Desai, Ankur R. and Bohrer, Gil and Arain, M. Altaf and Griffis, Timothy and Blanken, Peter D. and O'Halloran, Thomas L. and Thomas, R. Quinn and Zhang, Quan and Burns, Sean P. and Frank, John M. and Christian, Dold and Brown, Shannon and Black, T. Andrew and Gough, Christopher M. and Law, Beverly E. and Lee, Xuhui and Chen, Jiquan and Reed, David E. and Massman, William J. and Clark, Kenneth and Hatfield, Jerry and Prueger, John and Bracho, Rosvel and Baker, John M. and Martin, Timothy A.},
abstractNote = {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 (R2 = 0.88, 111 site-years). At 23 cropland/grassland sites, weekly ha successfully captured the dynamics of vegetation canopies over growing seasons (R2 > 0.70 in 74 site-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.},
doi = {10.1029/2018gl079306},
journal = {Geophysical Research Letters},
number = 17,
volume = 45,
place = {United States},
year = {2018},
month = {8}
}

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Figures / Tables:

Figure 1 Figure 1: Annual canopy heights across 69 AmeriFlux forest sites (site ID in y axis). The horizontal bars and gray segments indicate the multiyear means of aerodynamic canopy heights (ha) and the 95 percentile range (N = 1–22). The asterisks denote the mean actual canopy heights (hc) for available yearsmore » (N = 1–5). The colors denote the plant functional types. The inset compares ha and hc in all available site-years (N = 111). The vertical and horizontal gray segments represent the 95 percentile ranges of ha and reported upper-lower ranges of hc, respectively. The black solid and dashed lines denote the linear regression and its 95% confidence intervals. The gray dotted-dash line shows the 1:1 reference line. Please refer to Table S1 for site general information and Table S3 for summary statistics of linear regression.« less

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