Published September 29, 2023 | Version v1

Identification of high-wind features within extratropical cyclones using a probabilistic random forest - Part 2: Climatology - Dataset

  • 1. Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany
  • 2. Institute for Stochastics, Karlsruhe Institute of Technology, Karlsruhe, Germany

Description

This dataset provides output of RAMEFI for the wind feature climatology presented in Eisenstein et al. (2023; 10.5194/wcd-2023-10) for the winter months October to March 2000-2019 using COSMO-REA6 (https://reanalysis.meteo.uni-bonn.de/?COSMO-REA6).

rf_crea_<yyyymm>.nc include the unfiltered probabilities for 'no feature' (p0), warm jet (p1), cold-frontal convection (p2), cold jet (p3) and cold-sector winds (p5) for each month.

To filter for cyclone tracks, use cyclone_tracks.csv. The file includes interpolated ERA5 cyclone tracks for the investigated area and time period (see Section 2.4 of the paper).

mask.nc includes a land sea mask, height of surface level and a mask to exclude certain grid points as discussed in the manuscript (e.g., grid points with an altitude over 800m and the Balkans) for further filtering.

Files

cyclone_tracks.csv

Files (27.2 GB)

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md5:87b120cd0b250e4f4445b4ada143c7f6
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md5:b4c6d1faebdf5890886fd1fcd5867f25
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md5:97a9db2bac88817b914779841580c207
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Additional details

Related works

Is required by
Video/Audio: 10.5281/zenodo.7729357 (DOI)
Is supplement to
Preprint: 10.5194/wcd-2023-10 (DOI)
Requires
Software: 10.5281/zenodo.6541303 (DOI)