Abstract

AbstractThe temporal and spatial scale of atmospheric turbulence can be highly dynamic, requiring sophisticated methods for adequate detection and monitoring with high resolution. Doppler light detection and ranging (lidar) systems have been widely used to observe and monitor wind velocity and atmospheric turbulence profiles as Doppler lidar systems can provide continuous information about wind fields. The use of lidars in the subarctic region is particularly challenging as aerosol abundance can be very low, leading to weak backscatter signals. In the present study, we analysed data collected with a Leosphere Windcube 200S lidar system stationed in Reykjavik, Iceland, to estimate the eddy dissipation rate (EDR) as an indicator of turbulence intensity. For this purpose, we retrieved radial wind velocity observations from velocity–azimuth display scans and computed the EDR based on the Kolmogorov theory. We compared different noise filter thresholds, scan strategies and calculation approaches during typical Icelandic weather conditions to assess the accuracy and the uncertainty of our EDR estimations. The developed algorithm can process raw lidar observations, retrieve EDR and determine the qualitative distribution of the EDR. The processed lidar observations suggest that lidar observations can be of high importance for potential end‐users, for example air traffic controllers and aviation safety experts. The work is an essential step towards enhanced aviation safety in Iceland where aerosol concentration is in general low and severe turbulence occurs regularly.

Highlights

  • We developed an algorithm to estimate the eddy dissipation rate (EDR) by using the velocity structure function and applied the algorithm to our lidar data obtained in Reykjavik

  • We investigate how Leosphere Windcube 200S Doppler lidars can be used to detect and quantify atmospheric turbulence in Iceland where the climate and weather conditions are characterized by strong winds and intense turbulence

  • The clean air in Iceland leads to reduced backscatter signals from lidar systems and may require a different carrier-to-noise ratio (CNR) threshold than previous studies in other locations to screen the lidar data

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Summary

Introduction

In the present study we develop an algorithm to retrieve the EDR as an indicator of turbulence intensity from horizontal wind measurement by lidar in Reykjavik, Iceland. One possible explanation is that, with the same range resolution, the lower elevation angle results in higher vertical resolution (12.9 m at 15 compared to 48.3 m at 75), and we know the spatial scale of turbulence can be relatively small (dozens of metres).

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