Federal Office of Meteorology and Climatology MeteoSwiss

Reduced space optimal interpolation of daily rain gauge precipitation in Switzerland

Application of the reduced space optimal interpolation

 

The coarse spacing of automatic rain gauges complicates near-real-time spatial analyses of precipitation. We test the possibility of improving such analyses by considering, in addition to the in situ measurements, the spatial covariance structure inferred from past observations with a denser network. To this end, a statistical reconstruction technique, reduced space optimal interpolation (RSOI), is applied over Switzerland, a region of complex topography. RSOI consists of two main parts. First, principal component analysis (PCA) is applied to obtain a reduced space representation of gridded high-resolution precipitation fields available for a multiyear calibration period in the past. Second, sparse real-time rain gauge observations are used to estimate the principal component scores and to reconstruct the precipitation field. In this way, climatological information at higher resolution than the near-real-time measurements is incorporated into the spatial analysis. PCA is found to efficiently reduce the dimensionality of the calibration fields, and RSOI is successful despite the difficulties associated with the statistical distribution of daily precipitation (skewness, dry days). Examples and a systematic evaluation show substantial added value over a simple interpolation technique that uses near-real-time observations only (figure 1). The benefit is particularly strong for larger-scale precipitation and prominent topographic effects. Small-scale precipitation features are reconstructed at a skill comparable to that of the simple technique. Stratifying the reconstruction method by the types of weather type classifications yields little added skill. Apart from application in near real time, RSOI may also be valuable for enhancing instrumental precipitation analyses for the historic past when direct observations were sparse.

 

Fields of daily precipitation totals for a set of example cases.

Figure1: Fields of daily precipitation totals for a set of example cases. Left column (SIMPLE): Simple interpolation technique based on near-real-time observations only; middle column (RSOI): Spatial reconstruction using near-real-time observations and their statistical relationship to high-resolution observations of the past; Right column (OBS): Analysis based on all observations. Numbers in the upper left corner of each panel represent ?explained spatial variance? as measured with the mean squared error skill score (the larger the better).

This study was supported by COST Action 733.

Reference:
Schiemann, R., Liniger, M. A. and Frei, C. (2010): Reduced space optimal interpolation of daily rain gauge precipitation in Switzerland, J. Geophys. Res., 115, D14109.

Contact:
For further information please contact Christoph Frei.

 

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