Evaluation of Large Eddy Effects on Land Surface Modeling Based on the FLUXNET Dataset

Surface fluxes are vital to understanding land–atmosphere interactions, with similarity theory forming the basis for their parameterization. However, this theory has limitations, particularly due to large eddy effects, which have not been widely considered in Earth system models. A novel scheme was proposed to address this, considering large eddy effects under unstable atmospheric conditions. This study systematically evaluates the proposed scheme using the CoLM2014 model, FLUXNET2015 data, and ERA5 data. Based on the analysis of flux parameterization mechanisms, it proposes specific improvements aimed at enhancing the scheme’s performance. Our findings indicate that the proposed and classical schemes yield similar results, partly because they employ the same dimensionless wind speed gradient under near-neutral conditions. Furthermore, the results revealed that friction velocity responded more strongly to large eddies than did heat flux, as friction velocity influenced atmospheric stability and thereby mitigates the large eddy effects on heat flux. Additionally, our analysis reveals that bare soil exhibits the most pronounced changes in surface fluxes and energy partitioning, while grassland-type and forest-type sites display more complex responses. These findings indicate that different land cover types respond distinctly to the influence of large eddies. Overall, this research deepens our understanding of large eddy impacts and improves Earth system modeling by enhancing land–atmosphere interaction parameterization.

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Publication Details

Journal
Atmosphere
Published
2025-03-13
DOI
https://doi.org/10.3390/atmos16030328
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
0.00

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article

Evaluation of Large Eddy Effects on Land Surface Modeling Based on the FLUXNET Dataset

Qian Shi, Shaofeng Liu, Hui‐Shan Huang, Lingke Li
Atmosphere
Meteorological Phenomena and Simulations
article

Evaluation of Large Eddy Effects on Land Surface Modeling Based on the FLUXNET Dataset

Qian Shi, Shaofeng Liu, Hui‐Shan Huang, Lingke Li
article en

Abstract

Surface fluxes are vital to understanding land–atmosphere interactions, with similarity theory forming the basis for their parameterization. However, this theory has limitations, particularly due to large eddy effects, which have not been widely considered in Earth system models. A novel scheme was proposed to address this, considering large eddy effects under unstable atmospheric conditions. This study systematically evaluates the proposed scheme using the CoLM2014 model, FLUXNET2015 data, and ERA5 data. Based on the analysis of flux parameterization mechanisms, it proposes specific improvements aimed at enhancing the scheme’s performance. Our findings indicate that the proposed and classical schemes yield similar results, partly because they employ the same dimensionless wind speed gradient under near-neutral conditions. Furthermore, the results revealed that friction velocity responded more strongly to large eddies than did heat flux, as friction velocity influenced atmospheric stability and thereby mitigates the large eddy effects on heat flux. Additionally, our analysis reveals that bare soil exhibits the most pronounced changes in surface fluxes and energy partitioning, while grassland-type and forest-type sites display more complex responses. These findings indicate that different land cover types respond distinctly to the influence of large eddies. Overall, this research deepens our understanding of large eddy impacts and improves Earth system modeling by enhancing land–atmosphere interaction parameterization.

AtmosphereVol. 16(3)
Sun Yat-sen University (CN), Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (CN), Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 96%
Meteorological Phenomena and Simulations
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Evaluation of Large Eddy Effects on Land Surface Modeling Based on the FLUXNET Dataset — Qian Shi, Shaofeng Liu, et al. · Atmosphere (2025) | TGRS Research Map | TGRS