A climate study of temperature over North-Central Italy: comparing results from three different datasets

Surface air temperature is one of the Essential Climate Variables (ECVs). The availability of reliable gridded temperature datasets is therefore essential for climate research and impact studies. This thesis evaluates the performance of the ERA5-Land reanalysis and the E-OBS gridded observational dataset over Central-Northern Italy using the recently developed ArCIS dataset as the observational reference. The analysis of seasonal climatologies and temperature extremes is performed over the 1991--2020 reference period, whereas long-term trends are evaluated for the 1991--2025 period. Seasonal climatologies are compared using spatial analyses and standard performance metrics (MBE, MAE, and RMSE) after harmonizing the spatial resolution of the datasets. Trends are estimated through linear regression and assessed using the Mann--Kendall significance test. Temperature extremes are characterized through climatological percentile thresholds following the ETCCDI framework. The comparison highlights differences among the three datasets in representing the temperature characteristics of Central-Northern Italy. E-OBS generally shows a closer agreement with ArCIS in reproducing seasonal climatologies, while ERA5-Land exhibits larger seasonal and spatially dependent biases, particularly over complex mountainous areas and for maximum temperature. All datasets consistently identify a widespread warming signal over the study region, although differences emerge in the magnitude, spatial distribution, and statistical significance of the estimated trends. The analysis of temperature extremes shows a good agreement between ArCIS and E-OBS, whereas ERA5-Land exhibits seasonally dependent biases affecting the representation of both warm and cold extremes. Overall, this work provides an assessment of the strengths and limitations of these gridded temperature datasets, offering useful guidance for their application in climatological analyses and climate change studies.