A Repository for Preprocessing Multiple Sources of Radar Data

[in Development]

This python code converts several internaitonal radar datasets into a common format with certain grid size and time step.

The following datasets are considered.

An Italian Alps radar precipitation dataset for the period 2010-2019, by Franch et al.(2020)

• Franch et al., 2020, TAASRAD19, a high-resolution weather radar reflectivity dataset for precipitation nowcasting
• https://www.nature.com/articles/s41597-020-0574-8

A radar precipitation dataset by the German Weather Service for the year 2016-2017, prepared by Georgy Ayzel (2020)

• Ayzel, Georgy, RYDL: the sample data of the RY product for deep learning applications
• https://zenodo.org/record/3629951#.X7DKR2gzYzN

A radar precipitation dataset by MeteoSwiss for the year 2018, prepared by Jussi Leinonen (2019)

• Leinonen, Jussi, 2019, "Weather radar observation dataset for machine learning", https://doi.org/10.7910/DVN/ZDWWMG, Harvard Dataverse, V1
• https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/ZDWWMG

A Level-II radar dataset by NOAA NWS.

• NWS WSR-88D Level II Data
• https://www.roc.noaa.gov/WSR88D/Level_II/Level2Info.aspx

[MIT]

[inoue0406]