Implementation of an Effective Roughness Length Formulation for Subgrid-Scale Orographic Drag in the WRF Model.
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| Title: | Implementation of an Effective Roughness Length Formulation for Subgrid-Scale Orographic Drag in the WRF Model. |
|---|---|
| Authors: | Lee, Sang-Hyun1,2 (AUTHOR) sanghyun@kongju.ac.kr, Lee, Doo-Il1 (AUTHOR), Oh, Jun-Seo1 (AUTHOR) |
| Source: | Journal of Applied Meteorology & Climatology. Sep2026, Vol. 65 Issue 9, p1421-1433. 13p. |
| Subjects: | Drag (Aerodynamics), Large eddy simulation models, Atmospheric boundary layer, Weather forecasting, Wind forecasting, Topographic maps |
| Abstract: | Accurate near-surface wind forecasts over complex terrain are crucial for various applications, including air quality dispersion, wind energy assessment, and hydrometeorology. However, mesoscale models such as the Weather Research and Forecasting (WRF) Model frequently exhibit a persistent systematic high wind bias in mountainous regions. This study introduces a physically based formulation for the effective roughness length ( z 0 eff ) to better incorporate subgrid-scale (SGS) orographic drag. Derived from large-eddy simulations (LESs), the new formulation utilizes the first three statistical moments (mean, standard deviation, and skewness) of high-resolution topographic data. The performance of the formulation was evaluated through a year-long, 3-km-resolution WRF simulation over the Korean Peninsula for 2016. Validation against 95 surface stations and seven radiosonde sounding stations demonstrates that the new formulation substantially improves the model's predictive skill. The proposed scheme reduced the annual-mean RMSE for 10-m wind speed from 2.0 m s−1 in the control run to 1.4 m s−1, representing a 30% reduction in the overall error magnitude. Unlike preexisting empirical drag schemes, this improvement was consistently maintained across both daytime and nighttime periods, and its influence extended vertically within the atmospheric boundary layer (ABL). These results confirm that the LES-based formulation provides a physically robust correction for momentum sinks, offering enhanced fidelity for meteorological and air quality forecasting in complex terrain. Significance Statement: Weather forecast models often exhibit a persistent systematic high wind bias over complex terrain, which limits their reliability for critical societal applications. This study introduces a new, physically based method to improve the representation of surface drag from unresolved topography in the Weather Research and Forecasting (WRF) Model by utilizing an effective roughness length ( z 0 eff ) derived from high-resolution topographic statistics. Our evaluation demonstrates that this new parameterization effectively reduces the model's overestimation of surface wind speeds, decreasing the annual-mean root-mean-square error (RMSE) from 2.0 to 1.4 m s−1, representing a 30% improvement in overall forecast precision. This substantial increase in forecast accuracy directly benefits applied fields such as air quality dispersion modeling, wind energy assessment, and hydrometeorology, all of which depend on reliable near-surface and atmospheric boundary layer (ABL) wind data. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Applied Meteorology & Climatology is the property of American Meteorological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 197279700 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Implementation of an Effective Roughness Length Formulation for Subgrid-Scale Orographic Drag in the WRF Model. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Lee%2C+Sang-Hyun%22">Lee, Sang-Hyun</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> sanghyun@kongju.ac.kr</i><br /><searchLink fieldCode="AR" term="%22Lee%2C+Doo-Il%22">Lee, Doo-Il</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Oh%2C+Jun-Seo%22">Oh, Jun-Seo</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Applied+Meteorology+%26+Climatology%22">Journal of Applied Meteorology & Climatology</searchLink>. Sep2026, Vol. 65 Issue 9, p1421-1433. 13p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Drag+%28Aerodynamics%29%22">Drag (Aerodynamics)</searchLink><br /><searchLink fieldCode="DE" term="%22Large+eddy+simulation+models%22">Large eddy simulation models</searchLink><br /><searchLink fieldCode="DE" term="%22Atmospheric+boundary+layer%22">Atmospheric boundary layer</searchLink><br /><searchLink fieldCode="DE" term="%22Weather+forecasting%22">Weather forecasting</searchLink><br /><searchLink fieldCode="DE" term="%22Wind+forecasting%22">Wind forecasting</searchLink><br /><searchLink fieldCode="DE" term="%22Topographic+maps%22">Topographic maps</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Accurate near-surface wind forecasts over complex terrain are crucial for various applications, including air quality dispersion, wind energy assessment, and hydrometeorology. However, mesoscale models such as the Weather Research and Forecasting (WRF) Model frequently exhibit a persistent systematic high wind bias in mountainous regions. This study introduces a physically based formulation for the effective roughness length ( z 0 eff ) to better incorporate subgrid-scale (SGS) orographic drag. Derived from large-eddy simulations (LESs), the new formulation utilizes the first three statistical moments (mean, standard deviation, and skewness) of high-resolution topographic data. The performance of the formulation was evaluated through a year-long, 3-km-resolution WRF simulation over the Korean Peninsula for 2016. Validation against 95 surface stations and seven radiosonde sounding stations demonstrates that the new formulation substantially improves the model's predictive skill. The proposed scheme reduced the annual-mean RMSE for 10-m wind speed from 2.0 m s−1 in the control run to 1.4 m s−1, representing a 30% reduction in the overall error magnitude. Unlike preexisting empirical drag schemes, this improvement was consistently maintained across both daytime and nighttime periods, and its influence extended vertically within the atmospheric boundary layer (ABL). These results confirm that the LES-based formulation provides a physically robust correction for momentum sinks, offering enhanced fidelity for meteorological and air quality forecasting in complex terrain. Significance Statement: Weather forecast models often exhibit a persistent systematic high wind bias over complex terrain, which limits their reliability for critical societal applications. This study introduces a new, physically based method to improve the representation of surface drag from unresolved topography in the Weather Research and Forecasting (WRF) Model by utilizing an effective roughness length ( z 0 eff ) derived from high-resolution topographic statistics. Our evaluation demonstrates that this new parameterization effectively reduces the model's overestimation of surface wind speeds, decreasing the annual-mean root-mean-square error (RMSE) from 2.0 to 1.4 m s−1, representing a 30% improvement in overall forecast precision. This substantial increase in forecast accuracy directly benefits applied fields such as air quality dispersion modeling, wind energy assessment, and hydrometeorology, all of which depend on reliable near-surface and atmospheric boundary layer (ABL) wind data. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Applied Meteorology & Climatology is the property of American Meteorological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=197279700 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1175/JAMC-D-25-0191.1 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 13 StartPage: 1421 Subjects: – SubjectFull: Drag (Aerodynamics) Type: general – SubjectFull: Large eddy simulation models Type: general – SubjectFull: Atmospheric boundary layer Type: general – SubjectFull: Weather forecasting Type: general – SubjectFull: Wind forecasting Type: general – SubjectFull: Topographic maps Type: general Titles: – TitleFull: Implementation of an Effective Roughness Length Formulation for Subgrid-Scale Orographic Drag in the WRF Model. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Lee, Sang-Hyun – PersonEntity: Name: NameFull: Lee, Doo-Il – PersonEntity: Name: NameFull: Oh, Jun-Seo IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 15588424 Numbering: – Type: volume Value: 65 – Type: issue Value: 9 Titles: – TitleFull: Journal of Applied Meteorology & Climatology Type: main |
| ResultId | 1 |
