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The Performance of a Time-Varying Filter Time Under Stable Conditions over Mountainous Terrain
Eddy-covariance data from five stations in the Inn Valley, Austria, are analyzed for stable conditions to determine the gap scale that separates turbulent from large-scale, non-turbulent motions. The gap scale is identified from (co)spectra calculated from different variables using both Fourier anal...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10492749/ https://www.ncbi.nlm.nih.gov/pubmed/37701414 http://dx.doi.org/10.1007/s10546-023-00824-y |
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author | Lehner, Manuela Rotach, Mathias W. |
author_facet | Lehner, Manuela Rotach, Mathias W. |
author_sort | Lehner, Manuela |
collection | PubMed |
description | Eddy-covariance data from five stations in the Inn Valley, Austria, are analyzed for stable conditions to determine the gap scale that separates turbulent from large-scale, non-turbulent motions. The gap scale is identified from (co)spectra calculated from different variables using both Fourier analysis and multi-resolution flux decomposition. A correlation is found between the gap scale and the mean wind speed and stability parameter z/L that is used to determine a time-varying filter time, whose performance in separating turbulent and non-turbulent motions is compared to the performance of constant filter times between 0.5 and 30 min. The impact of applying different filter times on the turbulence statistics depends on the parameter and location, with a comparatively smaller impact on the variance of the vertical wind component than on the horizontal components and the turbulent fluxes. Results indicate that a time-varying filter time based on a multi-variable fit taking both mean wind speed and stability into account and a constant filter time of 2–3 min perform best in that they remove most of the non-turbulent motions while at the same time capturing most of the turbulence. For the studied sites and conditions, a time-varying filter time does not outperform a well chosen constant filter time because of relatively small variations in the filter time predicted by the correlation with mean flow parameters. |
format | Online Article Text |
id | pubmed-10492749 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-104927492023-09-11 The Performance of a Time-Varying Filter Time Under Stable Conditions over Mountainous Terrain Lehner, Manuela Rotach, Mathias W. Boundary Layer Meteorol Research Article Eddy-covariance data from five stations in the Inn Valley, Austria, are analyzed for stable conditions to determine the gap scale that separates turbulent from large-scale, non-turbulent motions. The gap scale is identified from (co)spectra calculated from different variables using both Fourier analysis and multi-resolution flux decomposition. A correlation is found between the gap scale and the mean wind speed and stability parameter z/L that is used to determine a time-varying filter time, whose performance in separating turbulent and non-turbulent motions is compared to the performance of constant filter times between 0.5 and 30 min. The impact of applying different filter times on the turbulence statistics depends on the parameter and location, with a comparatively smaller impact on the variance of the vertical wind component than on the horizontal components and the turbulent fluxes. Results indicate that a time-varying filter time based on a multi-variable fit taking both mean wind speed and stability into account and a constant filter time of 2–3 min perform best in that they remove most of the non-turbulent motions while at the same time capturing most of the turbulence. For the studied sites and conditions, a time-varying filter time does not outperform a well chosen constant filter time because of relatively small variations in the filter time predicted by the correlation with mean flow parameters. Springer Netherlands 2023-07-29 2023 /pmc/articles/PMC10492749/ /pubmed/37701414 http://dx.doi.org/10.1007/s10546-023-00824-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Article Lehner, Manuela Rotach, Mathias W. The Performance of a Time-Varying Filter Time Under Stable Conditions over Mountainous Terrain |
title | The Performance of a Time-Varying Filter Time Under Stable Conditions over Mountainous Terrain |
title_full | The Performance of a Time-Varying Filter Time Under Stable Conditions over Mountainous Terrain |
title_fullStr | The Performance of a Time-Varying Filter Time Under Stable Conditions over Mountainous Terrain |
title_full_unstemmed | The Performance of a Time-Varying Filter Time Under Stable Conditions over Mountainous Terrain |
title_short | The Performance of a Time-Varying Filter Time Under Stable Conditions over Mountainous Terrain |
title_sort | performance of a time-varying filter time under stable conditions over mountainous terrain |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10492749/ https://www.ncbi.nlm.nih.gov/pubmed/37701414 http://dx.doi.org/10.1007/s10546-023-00824-y |
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