Comparing the use of ERA5 reanalysis dataset and ground-based agrometeorological data under different climates and topography in Italy

TLDR

The study region comprises seven irrigation districts in Italy spanning diverse climate and topographic conditions. The authors aim to assess the reliability and climate‑dependent accuracy of ERA5 and ERA5‑Land reanalysis datasets for key agrometeorological variables used in crop water‑requirement calculations across these districts. They compared variable‑by‑variable estimates (solar radiation, air temperature, relative humidity, wind speed, reference evapotranspiration) from the reanalysis products with observations from 66 automatic weather stations collected between 2008 and 2020. The reanalysis data showed good agreement with observations overall, with the best performance for air temperature, followed by relative humidity, solar radiation, and wind speed, and yielded slightly higher ET0 accuracy with ERA5‑Land, demonstrating its potential as an alternative data source.

Abstract

The study region is represented by seven irrigation districts distributed under different climate and topography conditions in Italy. This study explores the reliability and consistency of the global ERA5 single levels and ERA5-Land reanalysis datasets in predicting the main agrometeorological estimates commonly used for crop water requirements calculation. In particular, the reanalysis data was compared, variable-by-variable (e.g., solar radiation, Rs; air temperature, Tair; relative humidity, RH; wind speed, u10; reference evapotranspiration, ET0), with in situ agrometeorological observations obtained from 66 automatic weather stations (2008–2020). In addition, the presence of a climate-dependency on their accuracy was assessed at the different irrigation districts. A general good agreement was obtained between observed and reanalysis agrometeorological variables at both daily and seasonal scales. The best performance was obtained for Tair, followed by RH, Rs, and u10 for both reanalysis datasets, especially under temperate climate conditions. These performances were translated into slightly higher accuracy of ET0 estimates by ERA5-Land product, confirming the potential of using reanalysis datasets as an alternative data source for retrieving the ET0 and overcoming the unavailability of observed agrometeorological data.