Preprints
https://doi.org/10.5194/essd-2024-285
https://doi.org/10.5194/essd-2024-285
24 Sep 2024
 | 24 Sep 2024
Status: this preprint is currently under review for the journal ESSD.

EEAR-Clim: A high density observational dataset of daily precipitation and air temperature for the Extended European Alpine Region

Giulio Bongiovanni, Michael Matiu, Alice Crespi, Anna Napoli, Bruno Majone, and Dino Zardi

Abstract. The Extended European Alpine Region (EEAR) exhibits a well-established and very high-density network of in-situ weather stations, hardly attainable in other mountainous regions of the world. However, the strong fragmentation into national and regional administrations and the diversity of data sources have so far hampered full exploitation of the available data for climate research. Here, we present EEAR-Clim, a new observational dataset gathering in-situ daily measurements of air temperature and precipitation from a variety of meteorological and hydrological services covering the whole EEAR. Data collected include time series from recordings up to 2020, the longest ones spanning up to 200 years. The overall observational network encompasses about 9000 in-situ weather stations, significantly enhancing data coverage at high elevations and achieving an average spatial density of one station per 6.8 8 km2 over the period 1991–2020. Data collected from many sources were tested for quality to ensure internal, temporal, and spatial consistency of time series, including outliers removal. Data homogeneity was assessed through a cross-comparison of the outcomes using three methods well established in the literature, namely Climatol, ACMANT, and RH Test. Quantile matching was applied to adjust inhomogeneous periods in time series. Overall, about 4 % of data were flagged as non-reliable and about 20 % of air temperature time series were corrected for one or more inhomogeneous periods. In the case of precipitation time series, fewer breakpoints were detected, confirming the well-known challenge of properly identifying inhomogeneities in noisy data. The dataset aims to serve as a powerful tool for better understanding climate change over the European Alps.

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Giulio Bongiovanni, Michael Matiu, Alice Crespi, Anna Napoli, Bruno Majone, and Dino Zardi

Status: open (until 02 Nov 2024)

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Giulio Bongiovanni, Michael Matiu, Alice Crespi, Anna Napoli, Bruno Majone, and Dino Zardi

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EEAR-Clim: A high density observational dataset of daily precipitation and air temperature for the Extended European Alpine Region Giulio Bongiovanni, Michael Matiu, Alice Crespi, Anna Napoli, Bruno Majone, and Dino Zardi https://doi.org/10.5281/zenodo.10951609

Giulio Bongiovanni, Michael Matiu, Alice Crespi, Anna Napoli, Bruno Majone, and Dino Zardi

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Short summary
EEAR-Clim is a new and unprecedented observational dataset gathering in-situ daily measurements of air temperature and precipitation from a network of about 9000 weather stations covering the European Alps. Data collected, including time series from recordings up to 2020 and significantly enhancing data coverage at high elevations, were tested for quality and homogeneity. The dataset aims to serve as a powerful tool for better understanding climate change over the European Alpine region.
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