Attributing seasonal variation of daily extreme precipitation events across The Netherlands
A recent study showed a rise in total and extreme precipitation in the Netherlands over the past century. The present study attempts to characterize and attribute the seasonal variation of daily extreme precipitation events in the Netherlands. Statistical models for extreme values were used to fit daily rainfall maxima for all months during the period 1961–2014, using data from the 231 rain gauges distributed across the country. A generalized extreme value (GEV) approach was used to determine the probability distribution of extreme values and their dependency on time and the monthly North Atla... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2016 |
Reihe/Periodikum: | Weather and Climate Extremes, Vol 14, Iss C, Pp 56-66 (2016) |
Verlag/Hrsg.: |
Elsevier
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Schlagwörter: | Extreme precipitation / Non-stationary model / GEV parameters / Annual cycle / Seasonal variation / Return levels / Meteorology. Climatology / QC851-999 |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-26804474 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://doi.org/10.1016/j.wace.2016.11.003 |
A recent study showed a rise in total and extreme precipitation in the Netherlands over the past century. The present study attempts to characterize and attribute the seasonal variation of daily extreme precipitation events in the Netherlands. Statistical models for extreme values were used to fit daily rainfall maxima for all months during the period 1961–2014, using data from the 231 rain gauges distributed across the country. A generalized extreme value (GEV) approach was used to determine the probability distribution of extreme values and their dependency on time and the monthly North Atlantic Oscillation (NAO) index. The non-stationary models used to represent the annual cycle of the GEV parameters assumed an invariant shape parameter and harmonic functions as location and scale parameters. The best non-stationary model was selected using Akaike’s information criterion (AIC) and the log-likelihood ratio test (LRT). The results indicated that the estimates derived from the non-stationary model differed from those obtained with the aid of the stationary model, and had lower uncertainties. These non-stationary estimates were within the confidence intervals (CI) of the stationary estimates at most rain gauge stations. The non-stationary model estimated parameters with less uncertainty and with smaller CI, thus permitting more accurate representation of extreme precipitation in the Netherlands. The spatial pattern of annual mean location and scale GEV parameters was compatible with coastal, land cover (such as the wooded and heathland areas of the Veluwe region of the province of Gelderland) and orography (in the southeast of the country). The location parameter peaked over the west coast, especially on the central west coast during the summer half-year, while the centre and east of the country had the highest values during the winter half-year. The scale parameter peaked in the centre of the country during the summer, in the east in the early summer and along the west coast in the spring. The 10-year and ...