The Improvement of Turbulent Heat Flux Parameterization for Use in the Tropical Regions Using Low Wind Speed Excess Resistance Parameter

Abstract Reliable simulation of turbulent heat fluxes needed for modeling land‐atmosphere interactions remains a challenge over the humid tropical region. This may be connected with the inadequate parameterization of the roughness lengths for momentum (z0m) and heat (z0h) transfer usually expressed...

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Main Authors: R.T. Akinnubi, M.O. Adeniyi
Format: Article
Language:English
Published: American Geophysical Union (AGU) 2019-11-01
Series:Journal of Advances in Modeling Earth Systems
Subjects:
Online Access:https://doi.org/10.1029/2018MS001466
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author R.T. Akinnubi
M.O. Adeniyi
author_facet R.T. Akinnubi
M.O. Adeniyi
author_sort R.T. Akinnubi
collection DOAJ
description Abstract Reliable simulation of turbulent heat fluxes needed for modeling land‐atmosphere interactions remains a challenge over the humid tropical region. This may be connected with the inadequate parameterization of the roughness lengths for momentum (z0m) and heat (z0h) transfer usually expressed in terms of excess resistance factor (κB−1). This paper assesses the performance of existing κB−1 schemes developed for high wind speed conditions over the humid tropical region. Thereafter, a more appropriate κB−1 suitable for low wind speed condition is developed for use in the aerodynamic resistance parameterization. Based on observed surface heat fluxes and profile measurements of wind speed and temperature from Nigeria Micrometeorological Experimental site, new κB−1 parameterization was derived through the application of the Monin‐Obukhov similarity theory and Brutsaert theoretical model for heat transfer. The derived κB−1=6.66Re*0.02−5.47, where Re* is the Reynolds number. Turbulent flux parameterization with this new formula provides better estimates of heat fluxes with reference to results from existing κB−1 schemes. The R2 increased by about 85%, while mean bias error and root‐mean‐square error in the parameterized QH based on the derived κB−1 reduced by about 63% and 66.7%, respectively. Similarly, the R2 increased by about 38%, while mean bias error and root‐mean‐square error in the parameterized QE based on the derived κB−1 reduced by about 47.8% and 52.6%, respectively. The derived κB−1 gave better estimates of QH than QE during the daytime. The derived κB−1 scheme corrects a well‐documented, large overestimation of turbulent heat fluxes, and it is therefore recommended for use in regions where low wind speed is prevalent.
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spelling doaj.art-992a2f6ef4834447bb26645c9454ab542022-12-21T18:34:25ZengAmerican Geophysical Union (AGU)Journal of Advances in Modeling Earth Systems1942-24662019-11-0111113636364910.1029/2018MS001466The Improvement of Turbulent Heat Flux Parameterization for Use in the Tropical Regions Using Low Wind Speed Excess Resistance ParameterR.T. Akinnubi0M.O. Adeniyi1Department of Physics Adeyemi College of Education Ondo NigeriaDepartment of Physics University of Ibadan Ibadan NigeriaAbstract Reliable simulation of turbulent heat fluxes needed for modeling land‐atmosphere interactions remains a challenge over the humid tropical region. This may be connected with the inadequate parameterization of the roughness lengths for momentum (z0m) and heat (z0h) transfer usually expressed in terms of excess resistance factor (κB−1). This paper assesses the performance of existing κB−1 schemes developed for high wind speed conditions over the humid tropical region. Thereafter, a more appropriate κB−1 suitable for low wind speed condition is developed for use in the aerodynamic resistance parameterization. Based on observed surface heat fluxes and profile measurements of wind speed and temperature from Nigeria Micrometeorological Experimental site, new κB−1 parameterization was derived through the application of the Monin‐Obukhov similarity theory and Brutsaert theoretical model for heat transfer. The derived κB−1=6.66Re*0.02−5.47, where Re* is the Reynolds number. Turbulent flux parameterization with this new formula provides better estimates of heat fluxes with reference to results from existing κB−1 schemes. The R2 increased by about 85%, while mean bias error and root‐mean‐square error in the parameterized QH based on the derived κB−1 reduced by about 63% and 66.7%, respectively. Similarly, the R2 increased by about 38%, while mean bias error and root‐mean‐square error in the parameterized QE based on the derived κB−1 reduced by about 47.8% and 52.6%, respectively. The derived κB−1 gave better estimates of QH than QE during the daytime. The derived κB−1 scheme corrects a well‐documented, large overestimation of turbulent heat fluxes, and it is therefore recommended for use in regions where low wind speed is prevalent.https://doi.org/10.1029/2018MS001466tropicsexcess resistance factorturbulent heat fluxes
spellingShingle R.T. Akinnubi
M.O. Adeniyi
The Improvement of Turbulent Heat Flux Parameterization for Use in the Tropical Regions Using Low Wind Speed Excess Resistance Parameter
Journal of Advances in Modeling Earth Systems
tropics
excess resistance factor
turbulent heat fluxes
title The Improvement of Turbulent Heat Flux Parameterization for Use in the Tropical Regions Using Low Wind Speed Excess Resistance Parameter
title_full The Improvement of Turbulent Heat Flux Parameterization for Use in the Tropical Regions Using Low Wind Speed Excess Resistance Parameter
title_fullStr The Improvement of Turbulent Heat Flux Parameterization for Use in the Tropical Regions Using Low Wind Speed Excess Resistance Parameter
title_full_unstemmed The Improvement of Turbulent Heat Flux Parameterization for Use in the Tropical Regions Using Low Wind Speed Excess Resistance Parameter
title_short The Improvement of Turbulent Heat Flux Parameterization for Use in the Tropical Regions Using Low Wind Speed Excess Resistance Parameter
title_sort improvement of turbulent heat flux parameterization for use in the tropical regions using low wind speed excess resistance parameter
topic tropics
excess resistance factor
turbulent heat fluxes
url https://doi.org/10.1029/2018MS001466
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