Turbulence associated with mountain waves over Northern Scandinavia – a case study using the ESRAD VHF radar and the WRF mesoscale model
We use measurements by the 52 MHz wind-profiling radar ESRAD, situated near Kiruna in Arctic Sweden, and simulations using the Advanced Research and Weather Forecasting model, WRF, to study vertical winds and turbulence in the troposphere in mountain-wave conditions on 23, 24 and 25 January 2003. We...
Published in: | Atmospheric Chemistry and Physics |
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Main Authors: | , , , |
Format: | Text |
Language: | English |
Published: |
2018
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Subjects: | |
Online Access: | https://doi.org/10.5194/acp-10-3583-2010 https://www.atmos-chem-phys.net/10/3583/2010/ |
Summary: | We use measurements by the 52 MHz wind-profiling radar ESRAD, situated near Kiruna in Arctic Sweden, and simulations using the Advanced Research and Weather Forecasting model, WRF, to study vertical winds and turbulence in the troposphere in mountain-wave conditions on 23, 24 and 25 January 2003. We find that WRF can accurately match the vertical wind signatures at the radar site when the spatial resolution for the simulations is 1 km. The horizontal and vertical wavelengths of the dominating mountain-waves are ~10–20 km and the amplitudes in vertical wind 1–2 m/s. Turbulence below 5500 m height, is seen by ESRAD about 40% of the time. This is a much higher rate than WRF predictions for conditions of Richardson number ( R i ) <1 but similar to WRF predictions of R i <2. WRF predicts that air crossing the 100 km wide model domain centred on ESRAD has a ~10% chance of encountering convective instabilities ( R i <0) somewhere along the path. The cause of low R i is a combination of wind-shear at synoptic upper-level fronts and perturbations in static stability due to the mountain-waves. Comparison with radiosondes suggests that WRF underestimates wind-shear and the occurrence of thin layers with very low static stability, so that vertical mixing by turbulence associated with mountain waves may be significantly more than suggested by the model. |
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