Multivariate testing of spatio-temporal consistence of daily precipitation records
| Autor: | Hermann Mächel, A. Kapala |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Atmospheric Science
Multivariate statistics Screening test Meteorology Ecological Modeling Homogenization (climate) Mode (statistics) lcsh:QC851-999 Pollution lcsh:QC1-999 Geophysics Principal component analysis Environmental science lcsh:Q lcsh:Meteorology. Climatology Data pre-processing Precipitation lcsh:Science Raw data lcsh:Physics |
| Zdroj: | Advances in Science and Research, Vol 10, Pp 85-90 (2013) |
| ISSN: | 1992-0636 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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