Multivariate testing of spatio-temporal consistence of daily precipitation records

Mächel, H.; Kapala, A.

The project KLIDADIGI of the German Meteorological Service (DWD) systematically rescues historical daily climate data of Germany by keying and imaging. Up to now, daily nearly gap-free precipitation time series at 118 locations for the period 1901–2000 are collected and extended by digitalization of hand-written protocols. To screen the spatio-temporal consistence of these raw data, we apply principal component analysis (PCA) in S (spatial) mode for daily precipitation records as well as for indices such as the number of rainy days above a certain threshold, intensity and absolute daily maximum in monthly, seasonal or annual resolution. Results of this screening test indicate that the PCA is a useful tool for detection of questionable stations and data preprocessing for further quality control and homogenization.

Zitieren

Zitierform:

Mächel, H. / Kapala, A.: Multivariate testing of spatio-temporal consistence of daily precipitation records. 2013. Copernicus Publications.

Rechte

Rechteinhaber: H. Mächel

Nutzung und Vervielfältigung:

Export