UK RSE Conference 2022 Walkthrough - MLOps for RSEs - Sample Data

• Main Author: Stephen Hadadad
• Format: Other/Unknown Material
• Language: English
• Published: Zenodo 2022
• Subjects: Machine Learning; Weather; MLOps; Pipeline; North Atlantic
• Online Access: https://doi.org/10.5281/zenodo.7022648

This record is intended as sample data for a Walkthrough at the UK RSE 2022 Conference titled "MLOps for RSEs". The code that uses this sample dataset can be found on GitHub . There are 2 parts based on the sample problems in the walkthrough Classifying wind rotor events Clustering weather regimes Rotors Dataset This dataset is intended as a machine learning dataset, to train a model to predict the occurrenceof turbulent wind gusts called "rotors". These are wind gusts happening on the leeward side of mountains. When they occur near an airfield, this can be hazardous from aviation operations. This data is intended to be used with the code on the Met Office Data Science Community of Practice GitHub repository. Files: 2021_met_office_aviation_rotors.csv - Raw dataset 2021_met_office_aviation_rotors_preprocessed.csv - Preprocessed dataset ready for machine learning rotors_catalog.yml - Intake Catalog file for the rotors dataset. More Information: MO Data Science Community of Practice GitHub -https://github.com/MetOffice/data_science_cop/tree/master/challenges/2021_falklands_rotors Met Office Youtube - What are rotors? https://www.youtube.com/watch?v=jgSZG9SqN_s What are Lee Waves? https://www.metoffice.gov.uk/weather/learn-about/weather/types-of-weather/wind/lee-waves\ Weather Regime Clustering This dataset is a UK and North Atlantic cutout of the Mean Sea-level Pressure (MSLP) field in ERA5 reanalysis dataset produced by ECMWF. This dataset is used for demonstrating an unsupervised learning pipeline. Files: era5_mslp_UK_2017_2020.nc - Gridded dataset of ERA5 reanalysis data.