Cover Journal of Applied Meteorology and Climatology
Journal of Applied Meteorology and Climatology

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Editorial Type:
Article
Article Type:
Research Article

A Hybrid Bulk Algorithm to Predict Turbulent Fluxes over Dry and Wet Bare Soils

Andrey A. GrachevaNOAA/Physical Sciences Laboratory, Boulder, Colorado
bCooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado

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Christopher W. FairallaNOAA/Physical Sciences Laboratory, Boulder, Colorado

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Byron W. BlomquistaNOAA/Physical Sciences Laboratory, Boulder, Colorado
bCooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado

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Harindra J. S. FernandocDepartment of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana
dDepartment of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, Indiana

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Laura S. LeocDepartment of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana
eDepartment of Physics and Astronomy, Alma Mater Studiorum-University of Bologna, Bologna, Italy

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Sebastián F. Otárola-BustoscDepartment of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana

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James M. WilczakaNOAA/Physical Sciences Laboratory, Boulder, Colorado

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Katherine L. McCaffreyaNOAA/Physical Sciences Laboratory, Boulder, Colorado
bCooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado

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Online Publication:
05 Apr 2022
Print Publication:
01 Apr 2022
DOI:
https://doi.org/10.1175/JAMC-D-20-0232.1
Page(s):
393–414
Restricted access

Abstract

Measurements made in the Columbia River basin (Oregon) in an area of irregular terrain during the second Wind Forecast Improvement Project (WFIP2) field campaign are used to develop an optimized hybrid bulk algorithm to predict the surface turbulent fluxes from readily measured or modeled quantities over dry and wet bare or lightly vegetated soil surfaces. The hybrid (synthetic) algorithm combines (i) an aerodynamic method for turbulent flow, which is based on the transfer coefficients (drag coefficient and Stanton number), roughness lengths, and Monin–Obukhov similarity; and (ii) a modified Priestley–Taylor (P-T) algorithm with physically based ecophysiological constraints, which is essentially based on the surface energy budget (SEB) equation. Soil heat flux in the latter case was estimated from measurements of soil temperature and soil moisture. In the framework of the hybrid algorithm, bulk estimates of the momentum flux and the sensible heat flux are derived from a traditional aerodynamic approach, whereas the latent heat flux (or moisture flux) is evaluated from a modified P-T model. Direct measurements of the surface fluxes (turbulent and radiative) and other ancillary atmospheric/soil parameters made during WFIP2 for different soil conditions (dry and wet) are used to optimize and tune the hybrid bulk algorithm. The bulk flux estimates are validated against the measured eddy-covariance fluxes. We also discuss the SEB closure over dry and wet surfaces at various time scales based on the modeled and measured fluxes. Although this bulk flux algorithm is optimized for the data collected during the WFIP2, a hybrid approach can be used for similar flux-tower sites and field campaigns.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Grachev’s current affiliation: Boundary Layer Research Team/Atmospheric Dynamics and Analytics Branch, DEVCOM Army Research Laboratory, WSMR, New Mexico.

McCaffrey’s current affiliation: S & P Global Commodity Insights, Boulder, Colorado.

Corresponding author: Andrey A. Grachev, andrey.grachev@colorado.edu

Abstract

Measurements made in the Columbia River basin (Oregon) in an area of irregular terrain during the second Wind Forecast Improvement Project (WFIP2) field campaign are used to develop an optimized hybrid bulk algorithm to predict the surface turbulent fluxes from readily measured or modeled quantities over dry and wet bare or lightly vegetated soil surfaces. The hybrid (synthetic) algorithm combines (i) an aerodynamic method for turbulent flow, which is based on the transfer coefficients (drag coefficient and Stanton number), roughness lengths, and Monin–Obukhov similarity; and (ii) a modified Priestley–Taylor (P-T) algorithm with physically based ecophysiological constraints, which is essentially based on the surface energy budget (SEB) equation. Soil heat flux in the latter case was estimated from measurements of soil temperature and soil moisture. In the framework of the hybrid algorithm, bulk estimates of the momentum flux and the sensible heat flux are derived from a traditional aerodynamic approach, whereas the latent heat flux (or moisture flux) is evaluated from a modified P-T model. Direct measurements of the surface fluxes (turbulent and radiative) and other ancillary atmospheric/soil parameters made during WFIP2 for different soil conditions (dry and wet) are used to optimize and tune the hybrid bulk algorithm. The bulk flux estimates are validated against the measured eddy-covariance fluxes. We also discuss the SEB closure over dry and wet surfaces at various time scales based on the modeled and measured fluxes. Although this bulk flux algorithm is optimized for the data collected during the WFIP2, a hybrid approach can be used for similar flux-tower sites and field campaigns.

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Grachev’s current affiliation: Boundary Layer Research Team/Atmospheric Dynamics and Analytics Branch, DEVCOM Army Research Laboratory, WSMR, New Mexico.

McCaffrey’s current affiliation: S & P Global Commodity Insights, Boulder, Colorado.

Corresponding author: Andrey A. Grachev, andrey.grachev@colorado.edu
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