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History of modifications to this User Guide
Version | Date | Description of modification | Chapters / Sections |
1.0 | 2019-05-01 | First version | Whole document |
List of versions covered by this document
Version | Release date | Period covered | Comments/modifications |
LAPrec1871.v1.0 | 2019-05-01 | From 1871-01-01 to 2017-12-31 | First release. Provisional period: 2012-2017. |
LAPrec1871.v1.1 | 2021-02-10 | From 1871-01-01 to 2019-12-31 | Update. Provisional period: 2014-2019. |
Acronyms
Version |
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APGD | Alpine precipitation grid dataset |
ARSO | Agencija Republike Slovenije Okolje |
EPSG | European Petroleum Survey Group Geodesy |
ETRS89 / ETRS-LAEA | European Terrestrial Reference System 1989-Lambert Azimuthal Equal Area |
DHMZ | Državni hidrometeorološki zavod |
DWD | Deutscher WetterDienst |
FHMZ | Federalni hidrometeorološki zavod |
HISTALP | Historical Instrumental Climatological Surface Time Series Of The Greater Alpine Region |
LAPrec | Long-term Alpine Precipitation Reconstruction |
MAE | Mean Absolute Error |
MSESS | Mean-Squared Error Skill Score |
OMSZ | Országos Meteorológiai Szolgálat |
PCA | Principal Component Analysis |
PRISM | Parameter-elevation Regressions on Independent Slopes Model |
RSOI | Reduced Space Optimal Interpolation |
UERRA | Uncertainties in Ensembles of Regional ReAnalyses |
ZAMG | Zentralanstalt für Meteorologie und Geodynamik |
Introduction
Spatial climate analyses that extend back over many decades are an important basis for monitoring climate variations and long-term change (e.g. van der Schrier et al., 2013). They also serve as input for modelling environmental systems (e.g. ecosystems and glaciers, Kittel et al., 2004), and for calibrating climate reconstructions with proxy data (tree rings, Frank & Esper, 2005).
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Parameter | monthly precipitation sum (mm) |
Domain | Alpine region (approx. 43–49°N, 4–17°E, land area only) |
Time period | two versions: starting 1871 and 1901, respectively |
Time resolution | monthly |
Coordinate system | ETRS89 / ETRS-LAEA (EPSG 3035) |
Grid spacing | 5 km |
Input Data | HISTALP (Auer et al. 2007), APGD (Isotta et al. 2014) |
Method | RSOI (Kaplan et al. 1997; Schiemann et al. 2010) |
Data
The construction of LAPrec builds on two data components, namely a dataset of high-quality long-term station series that contributes information on long-term variations, and a dataset of high-resolution grid data that enhances information on spatial variability. The two data components are described in the following.
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Table 2: Error measures (in mm per month) from a leave-one-out cross-validation using all reconstruction stations of the respective reconstruction windowAnchor table2 table2
Dataset | LAPrec1871 | LAPrec1901 |
evaluation period | 1871–2017 | 1901–2017 |
bias | 0.8 | 2.1 |
mean absolute error | 18.6 | 17.3 |
The mean absolute error (MAE) is about 18 mm per month. Nominally, the error is only marginally larger in the longer dataset, but this may be due to differences between the station samples from which the statistics has been calculated. Indeed, the mean absolute error varies considerably between test station, as is shown in Figure 7. MAE is typically twice as large in areas of complex topography (Switzerland, Austria), and in areas of coarse station density (Italy and Croatia), compared to densely sampled flatlands (Swiss Plateau, Eastern France).
In terms of seasonal variation, the mean absolute error is largest in summer, when the monthly sums are larger and when convection induces, generally, smaller-scale precipitation anomalies.
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