The Nature of the Ny-Ålesund Wind Field Analysed by High-Resolution Windlidar Data

sandra.grassl [ at ]


In this work we present windlidar data for the research village Ny-Ålesund located on Svalbard in the European Arctic (78.923°N, 11.928°E) from 2013 to 2021. The data have a resolution of 50 m and 10 min with an overlapping height of about 150 m. The maximum range depends on the meteorologic situation. Up to 1000 m altitude the data availability is better than 71%. We found that the highest wind speeds occur in November and December, the lowest ones in June and July, up to 500 m altitude the wind is channelled strongly in ESE to NW direction parallel to the fjord axis and the synoptic conditions above 1000 m altitude already dominate. While the fraction of windy days (v>10m/s) varies significantly from month to month, there is no overall trend of the wind visible in our data set. We define gusts and jets by the requirement of wind maxima v>2m/s above and below a wind maximum. In total, more than 24,000 of these events were identified (corresponding to 6% of the time), of which 223 lasted for at least 100 min (“Long Jets”). All of these events are fairly equally distributed over the months relatively to the available data. Further, gusts and jets follow different distributions (in terms of altitude or depths) and occur more frequently for synoptic flow from roughly a southerly direction. Jets do not show a clear correlation between occurrence and synoptic flow. Gusts and jets are not related to cloud cover. We conclude that the atmosphere from 400 m to 1000 m above Ny-Ålesund is dominated by a turbulent wind shear zone, which connects the micrometeorology in the atmospheric boundary layer (ABL) with the synoptic flow.

Item Type
Primary Division
Primary Topic
Helmholtz Cross Cutting Activity (2021-2027)
Research Networks
Publication Status
Published online
Eprint ID
DOI 10.3390/rs14153771

Cite as
Graßl, S. , Ritter, C. and Schulz, A. (2022): The Nature of the Ny-Ålesund Wind Field Analysed by High-Resolution Windlidar Data , Remote Sensing, 14 (15) . doi: 10.3390/rs14153771

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