Daily histograms of wind speed (100m), wind direction (100m) and atmospheric stability derived from ERA5

<p dir="ltr">This dataset contains daily histograms of wind speed at 100m ("WS100"), wind direction at 100 m ("WD100") and an atmospheric stability proxy ("STAB") derived from the ERA5 hourly data on single levels [1] accessed via the Copernicus Climate Change Climate Data Store [2]. The dataset covers six geographical regions (illustrated in regions.png) on a reduced 0.5 x 0.5 degrees regular grid and covers the period 1994 to 2023 (both years included). The dataset is packaged as a zip folder per region which contains a range of monthly zip folders following the convention of zarr ZipStores (more details here: https://zarr.readthedocs.io/en/stable/api/storage.html). Thus, the monthly zip folders are intended to be used in connection with the xarray python package (no unzipping of the monthly files needed).</p><p dir="ltr">Wind speed and wind direction are derived from the U- and V-components. The stability metric makes use of a 5-class classification scheme [3] based on the Obukhov length whereby the required Obukhov length was computed using [4]. The following bins (left edges) have been used to create the histograms:</p><p dir="ltr">Wind speed: [0, 40) m/s (bin width 1 m/s)<br>Wind direction: [0,360) deg (bin width 15 deg)<br>Stability: 5 discrete stability classes (1: very unstable, 2: unstable, 3: neutral, 4: stable, 5: very stable)</p><p><br></p><p dir="ltr"><b>Main Purpose:</b> The dataset serves as minimum input data for the CLIMatological REPresentative PERiods (climrepper) python package (https://gitlab.windenergy.dtu.dk/climrepper/climrepper) in preparation for public release).</p><p><br></p><p dir="ltr">References:<br>[1] Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2023): ERA5 hourly data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: <a href="https://doi.org/10.24381/cds.adbb2d47" target="_blank">10.24381/cds.adbb2d47</a> (Accessed Nov. 2024)</p><p><br></p><p dir="ltr">[2] Copernicus Climate Change Service, Climate Data Store, (2023): ERA5 hourly data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: <a href="https://doi.org/10.24381/cds.adbb2d47" target="_blank">10.24381/cds.adbb2d47</a> (Accessed Nov. 2024)'<br><br>[3] Holtslag, M. C., Bierbooms, W. A. A. M., & Bussel, G. J. W. van. (2014). Estimating atmospheric stability from observations and correcting wind shear models accordingly. In Journal of Physics: Conference Series (Vol. 555, p. 012052). IOP Publishing. <a href="https://doi.org/10.1088/1742-6596/555/1/012052" rel="noreferrer" target="_blank">https://doi.org/10.1088/1742-6596/555/1/012052</a></p><p><br></p><p dir="ltr">[4] Copernicus Knowledge Base, ERA5: How to calculate Obukhov Length, URL: <a href="https://confluence.ecmwf.int/display/CKB/ERA5:+How+to+calculate+Obukhov+Length" rel="noreferrer" target="_blank">https://confluence.ecmwf.int/display/CKB/ERA5:+How+to+calculate+Obukhov+Length</a>, last accessed: Nov 2024</p><p><br></p>