A Year-Long Large-Eddy Simulation of the Weather over Cabauw: An Overview
| Autor: | F. C. Bosveld, A. P. Siebesma, H.J.J. Jonker, Jerôme Schalkwijk |
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| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
Atmospheric Science
Meteorology Computer science Turbulence large eddy simulations Spectral density Ranging Variance (accounting) clouds Wind speed model evaluation/performance Set (abstract data type) regional models Range (statistics) in situ atmospheric observations Large eddy simulation Remote sensing |
| Zdroj: | Monthly Weather Review, 143, 2015 |
| ISSN: | 0027-0644 |
| Popis: | Results are presented of two large-eddy simulation (LES) runs of the entire year 2012 centered at the Cabauw observational supersite in the Netherlands. The LES is coupled to a regional weather model that provides the large-scale information. The simulations provide three-dimensional continuous time series of LES-generated turbulence and clouds, which can be compared in detail to the extensive observational dataset of Cabauw. The LES dataset is available from the authors on request. This type of LES setup has a number of advantages. First, it can provide a more statistical approach to the study of turbulent atmospheric flow than the more common case studies, since a diverse but representative set of conditions is covered, including numerous transitions. This has advantages in the design and evaluation of parameterizations. Second, the setup can provide valuable information on the quality of the LES model when applied to such a wide range of conditions. Last, it also provides the possibility to emulate observation techniques. This might help detect limitations and potential problems of a variety of measurement techniques. The LES runs are validated through a comparison with observations from the observational supersite and with results from the “parent” large-scale model. The long time series that are generated, in combination with information on the spatial structure, provide a novel opportunity to study time scales ranging from seconds to seasons. This facilitates a study of the power spectrum of horizontal and vertical wind speed variance to identify the dominant variance-containing time scales. |
| Databáze: | OpenAIRE |
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