Large-eddy simulations of real-world episodes in complex terrain based on era-reanalysis and validated by ground-based remote sensing data
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
A computationally efficient and inexpensive approach for using the capabilities of large-eddy simulations (LES) to model small-scale local weather phenomena is presented. The setup uses the LES capabilities of the Weather Research and Forecasting Model (WRF-LES) on a single domain that is directly driven by reanalysis data as boundary conditions. The simulated area is an example for complex terrain, and the employed parameterizations are chosen in a way to represent realistic conditions during two 48-h periods while still keeping the required computing time around 105 CPU hours. We show by evaluating turbulence characteristics that the model results conform to results from typical LES. A comparison with ground-based remote sensing data from a triple Doppler-lidar setup, employed during the "ScaleX'' campaigns, shows the grade of adherence of the results to the measured local weather conditions. The representation of mesoscale phenomena, including nocturnal low-level jets, strongly depends on the temporal and spatial resolution of the meteorological boundary conditions used to drive the model. Small-scale meteorological features that are induced by the terrain, such as katabatic flows, are present in the simulated output as well as in the measured data. This result shows that the four-dimensional output of WRF-LES simulations for a real area and real episode can be technically realized, allowing a more comprehensive and detailed view of the micrometeorological conditions than can be achieved with measurements alone.
Details
Original language | English |
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Pages (from-to) | 4325-4343 |
Number of pages | 19 |
Journal | Monthly Weather Review |
Volume | 147 |
Issue number | 12 |
Publication status | Published - 2019 |
Peer-reviewed | Yes |
External IDs
ORCID | /0000-0002-8789-163X/work/163766110 |
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