The data is described in Karhu et al. (2025) (submitted to Geoscience Data Journal) PV power, ancillary and meteorological data for each PV system are organised in their respective, semicolon separated, csv-files with unique headers explaining the variables: - FMI_Helsinki_PV.csv - FMI_Kuopio_PV.csv - FMI_Sodankyla_20deg_PV.csv - FMI_Sodankyla_90deg_PV.csv Below is an example how to read the datafiles to a pandas dataframe with python. Please note, that the header lengths vary: - Helsinki and Kuopio: 63 - Sodankylä: 93 ### import pandas as pd dtype_dict = {'Remarks': str} df = pd.read_csv('FMI_Sodankyla_20deg_PV.csv', sep=';', parse_dates=['utctime'], index_col=['utctime'], dtype=dtype_dict, header=93) ### Hourly photographs of the Sodankylä modules are in a tarball: - Sodankyla_module_images_2018-2021.tar.gz Metadata, additional photographs of the PV sites and their surroundings as well as data sheets and technical information of the modules and inverters can be found in a separate tarball: - siteinfo_and_metadata.tar.gz

2025