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High‐resolution monthly precipitation climatologies over Norway (1981–2010): Joining numerical model data sets and in situ observations
Author(s) -
Crespi Alice,
Lussana Cristian,
Brunetti Michele,
Dobler Andreas,
Maugeri Maurizio,
Tveito Ole Einar
Publication year - 2018
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/joc.5933
Subject(s) - kriging , environmental science , downscaling , precipitation , climatology , interpolation (computer graphics) , meteorology , multivariate interpolation , linear regression , data set , mathematics , geology , statistics , geography , computer science , animation , computer graphics (images) , bilinear interpolation
The 1981–2010 monthly precipitation climatologies for Norway at 1 km resolution are presented. They are computed by an interpolation procedure (HCLIM+RK) combining the output from a numerical model with the in situ observations. Specifically, the regional climate model data set HCLIM‐AROME, based on the dynamical downscaling of the global ERA‐Interim reanalysis onto 2.5 km resolution, is considered together with 2009 rain‐gauges located within the model domain. The precipitation climatologies are defined by superimposing the grid of 1981–2010 monthly normals from the numerical model and the kriging interpolation of station residuals. The combined approach aims at improving the quality of gridded climatologies and at providing reliable precipitation gradients also over those remote Norwegian regions not covered by observations, especially over the northernmost mountainous areas. The integration of rain‐gauge data greatly reduces the original HCLIM‐AROME biases. The HCLIM+RK errors obtained from the leave‐one‐out station validation turn out to be lower than those provided by two considered interpolation schemes based on observations only: a multi‐linear local regression kriging (MLRK) and a local weighted linear regression (LWLR). As average over all months, the mean absolute (percentage) error is 10.0 mm (11%) for HCLIM+RK, and 11.4 (12%) and 11.6 mm (12%) for MLRK and LWLR, respectively. In addition, by comparing the results at both station and grid cell level, the accuracy of MLRK and LWLR is more sensitive to the spatial variability of station distribution over the domain and their interpolated fields are more affected by discontinuities and outliers, especially over those areas not covered by the rain‐gauge network. The obtained HCLIM+RK climatologies clearly depict the main west‐to‐east gradient occurring from the orographic precipitation regime of the coast to the more continental climate of the inland and it allows to point out the features of the climatic subzones of Norway.