Meteorological variables for Agriculture: a Dataset for the Italian Area (MADIA)

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 1981-2022, 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, 5^th, 10^th, 50^th, 90^th, 95^th 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. Another vector file is included with the ERA5 cell polygons covering the Italian country for visualizing and mapping csv data. 

A daily version of the MADIA dataset (only in csv format) is also available on Zenodo at https://doi.org/10.5281/zenodo.7621453.

Both MADIA datasets will be periodically updated.

Attached content

A ZIP archive composed by the following folders

1. nc_data: annual time series from 1981 to 2022 and climate normals (1981-2010 and 1991-2020) in NetCDF format
2. csv_data: annual time series from 1981 to 2022 and climate normals (1981-2010 and 1991-2020) in csv format
3. metadata: discovery and description metadata 
4. shp_data: two complementary vector layers with the NUTS2-3 cover fractions and the ERA5 cell polygons for Italy

Acknowledgments

This work was supported by the Italian Ministry of Agricultural, Food and Forestry Policies (AgriDigit-Agromodelli, DM n. 36502 of 20/12/2018)