Revisiting HISTALP precipitation dataset

Author:

Chimani Barbara1ORCID,Bochníček Oliver2,Brunetti Michele3,Ganekind Manfred1,Holec Juraj2,Izsák Beatrix4ORCID,Lakatos Mónika4,Tadić Melita Perčec5,Manara Veronica6,Maugeri Maurizio6,Šťastný Pavel2,Szentes Olivér4ORCID,Zardi Dino7

Affiliation:

1. GeoSphere Austria Vienna Austria

2. Slovak Hydrometeorological Institute (SMHU) Bratislava Slovak Republic

3. National Research Council Institute of Atmospheric Sciences and Climate (CNR‐ISAC) Bologna Italy

4. Országos Meteorológiai Szolgálat (OMSZ) Budapest Hungary

5. Croatian Meteorological and Hydrological Service (DHMZ) Zagreb Croatia

6. Department of Environmental Science and Policy Universitá degli Studi di Milano Milano Italy

7. Department of Civil, Environmental and Mechanical Engineering (DICAM) University of Trento Trento Italy

Abstract

AbstractThe article presents a recent update of a comprehensive dataset of long‐term series of precipitation data from instrumental observations in the Greater Alpine Region (GAR), that is, the region of Europe including the Alpine mountain range and their nearer surroundings (4°–19° E in longitude and 43°–49° N in latitude). A comparison to different national homogenized datasets is also presented. Results show that in the national homogenized datasets more breaks have been detected due to higher station density. They also demonstrate the necessity of constant exchange with data providers. The resulting trends in all datasets are mainly weak and only a minority of them is statistically significant. In most cases the similarity of statistical index numbers are promising, with, for example, small RMSE between the presented new HISTALP homogenization and the time series of the national homogenized datasets. Nevertheless, for some stations higher differences occur and break signals are not what would be expected due to possible causes in the station history. The differences between the national and the HISTALP new homogenization—due to, for example, different methods used, different points in time when the homogenization took place, different options of data handling (combination of station data, gap filling routines, …) and different reference stations—illustrate the inherent uncertainty unavoidably associated to homogenization and point out the need of careful communication and use of the data. On the other hand, the results highlight the advantage of consistently homogenized datasets, versus the risks associated with mixing results from different homogenizations.

Publisher

Wiley

Subject

Atmospheric Science

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