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

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 bulkmore » 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.« less

Authors:
 [1];  [2];  [1];  [3];  [4];  [3];  [2];  [1]
  1. National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States). Physical Sciences Laboratory; Univ. of Colorado, Boulder, CO (United States)
  2. National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States). Physical Sciences Laboratory
  3. University of Notre Dame, IN (United States)
  4. University of Notre Dame, IN (United States); Univ. of Bologna (Italy)
Publication Date:
Research Org.:
National Oceanic and Atmospheric Administration (NOAA), Silver Spring, MD (United States). Office of Oceanic and Atmospheric Research
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE); National Oceanic and Atmospheric Administration (NOAA)
OSTI Identifier:
1980907
Grant/Contract Number:  
EE0007605; AGS-1565535; AGS-1921554; FOA-0000984; WFIFP2-SUB-001
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Applied Meteorology and Climatology
Additional Journal Information:
Journal Volume: 61; Journal Issue: 4; Journal ID: ISSN 1558-8424
Publisher:
American Meteorological Society
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Meteorology & Atmospheric Sciences; Atmosphere-land interaction; Fluxes; Heat budgets/fluxes; Water vapor; Parameterization

Citation Formats

Grachev, Andrey A., Fairall, Christopher W., Blomquist, Byron W., Fernando, Harindra S., Leo, Laura S., Otárola-Bustos, Sebastián F., Wilczak, James M., and McCaffrey, Katherine L. A Hybrid Bulk Algorithm to Predict Turbulent Fluxes over Dry and Wet Bare Soils. United States: N. p., 2022. Web. doi:10.1175/jamc-d-20-0232.1.
Grachev, Andrey A., Fairall, Christopher W., Blomquist, Byron W., Fernando, Harindra S., Leo, Laura S., Otárola-Bustos, Sebastián F., Wilczak, James M., & McCaffrey, Katherine L. A Hybrid Bulk Algorithm to Predict Turbulent Fluxes over Dry and Wet Bare Soils. United States. https://doi.org/10.1175/jamc-d-20-0232.1
Grachev, Andrey A., Fairall, Christopher W., Blomquist, Byron W., Fernando, Harindra S., Leo, Laura S., Otárola-Bustos, Sebastián F., Wilczak, James M., and McCaffrey, Katherine L. Fri . "A Hybrid Bulk Algorithm to Predict Turbulent Fluxes over Dry and Wet Bare Soils". United States. https://doi.org/10.1175/jamc-d-20-0232.1. https://www.osti.gov/servlets/purl/1980907.
@article{osti_1980907,
title = {A Hybrid Bulk Algorithm to Predict Turbulent Fluxes over Dry and Wet Bare Soils},
author = {Grachev, Andrey A. and Fairall, Christopher W. and Blomquist, Byron W. and Fernando, Harindra S. and Leo, Laura S. and Otárola-Bustos, Sebastián F. and Wilczak, James M. and McCaffrey, Katherine L.},
abstractNote = {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.},
doi = {10.1175/jamc-d-20-0232.1},
journal = {Journal of Applied Meteorology and Climatology},
number = 4,
volume = 61,
place = {United States},
year = {Fri Apr 01 00:00:00 EDT 2022},
month = {Fri Apr 01 00:00:00 EDT 2022}
}

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