The dataset is the supplementary material for the following journal paper: Parisse B.*, Alilla R., Pepe A.G., De Natale F., MADIA - Meteorological variables for Agriculture: a Dataset for the Italian Area, Data in Brief, 46 (2023), 108843, 10.1016/j.dib.2022.108843, (https://www.sciencedirect.com/science/article/pii/S2352340922010460) Abstract The MADIA gridded dataset provides the series of the main agro-meteorological variables derived from ERA5 hourly surface data, across the Italian domain for the period 1981-2021, and their respective 1981-2010 and 1991-2020 climate normals, as well as the following statistics on the 30-year dekadal values of each variable: absolute minimum and maximum, 5th, 10th, 50th, 90th, 95th percentiles. Temporal and spatial resolutions are 10-daily and 0.25 degrees respectively. The dataset contains time series of minimum, average and maximum air temperature, minimum and maximum air relative humidity, wind speed, solar radiation, precipitation and reference evapotranspiration according to the FAO Penman-Monteith method. The dataset is provided in both NetCDF and csv format. In addition, discovery and description metadata are provided. In order to facilitate the data reuse for computing statistics at Italian NUTS 2 and 3 levels, a complementary vector file is provided which reports the cell weight in terms of fraction covered of each administrative unit considered. The MADIA dataset will be periodically updated. Attached content A ZIP archive composed by the following folders nc_data: annual time series from 1981 to 2021 and climate normals (1981-2010 and 1991-2020) in NetCDF format csv_data: annual time series from 1981 to 2021 and climate normals (1981-2010 and 1991-2020) in csv format metadata: discovery and description metadata shp_data: complementary vector data with the NUTS2-3 cover fractions Acknowledgments This work was supported by the Italian Ministry of Agricultural, Food and Forestry Policies (AgriDigit-Agromodelli, DM n. 36502 of 20/12/2018)

{"references": ["B. Parisse, A. Pontrandolfi, C. Epifani, R. Alilla, F. De Natale (2020) An agrometeorological analysis of weather extremes supporting decisions for the agricultural policies in Italy. Italian Journal of Agrometeorology (3): 15-30. https://doi.org/10.13128/ijam-790"]}

In this version (v.1.1) the main statistic on the 30-year dekadal values of each variable (absolute minimum and maximum, 5th, 10th, 50th, 90th, 95th percentiles) have been integrated into the climate normals.