Meteorological indicator dataset for selected European NUTS 3 regions

Published: 7 May 2020| Version 3 | DOI: 10.17632/sf9x4h5jfk.3
Denitsa Angelova, Norman Blanco Lupio


The harmonization of data granularity in spatial and temporal terms is an important pre-step to any econometric and machine learning applications. Researchers, who wish to statistically test hypotheses on the relationship between agro-meteorological and economic outcomes, often observe that agro-meteorological data is typically stored in gridded and temporally detailed form, while many relevant economic outcomes are only available on an aggregated level. This dataset intends to aid empirical investigations by providing a dataset with monthly meteorological indicators on a European NUTS 3 regional level for 13 countries for the period from 1989 to 2018. We created this dataset from daily data in a grid of 25km x 25km provided by the Joint Research Centre of the European Commission. We matched the map with the raw data to a map with the administrative boundaries of European NUTS3 regions. After appropriately weighting, we calculated the monthly, regional mean, variance and kurtosis of the following variables: daily maximum, minimum, average air temperature in degrees Centigrade, sum of precipitation in mm per day and snow depth in cm. We report the covariance between the average temperature and the precipitation as well.



Technische Universitat Munchen


Meteorology, Economics, Econometrics