Knowledge of the response of extreme precipitation to urbanization is essential to ensure societal preparedness for the extreme events caused by climate change. To quantify this response, this study scales extreme precipitation according to temperature using the statistical quantile regression and binning methods for 231 rain gauges during the period of 1985–2014. The positive 3%–7% scaling rates were found at most stations. The nonstationary return levels of extreme precipitation are investigated using monthly blocks of the maximum daily precipitation, considering the dependency of precipitation on the dewpoint, atmospheric air temperatures, and the North Atlantic Oscillation (NAO) index. Consideration of Coordination of Information on the Environment (CORINE) land-cover types upwind of the stations in different directions classifies stations as urban and nonurban. The return levels for the maximum daily precipitation are greater over urban stations than those over nonurban stations especially after the spring months. This discrepancy was found by 5%–7% larger values in August for all of the classified station types. Analysis of the intensity–duration–frequency curves for urban and nonurban precipitation in August reveals that the assumption of stationarity leads to the underestimation of precipitation extremes due to the sensitivity of extreme precipitation to the nonstationary condition. The study concludes that nonstationary models should be used to estimate the return levels of extreme precipitation by considering the probable covariates such as the dewpoint and atmospheric air temperatures. In addition to the external forces, such as large-scale weather modes, circulation types, and temperature changes that drive extreme precipitation, urbanization could impact extreme precipitation in the Netherlands, particularly for short-duration events.

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The detection of changes in the weather of urban areas is an important issue for understanding the impact of weather on human lives. Five years of basic weather observations (2011−2015) from automatic and amateur networks across The Netherlands were used to investigate the urban effects on meteorological parameters with a focus on temperature (e.g. urban heat island [UHI]) and precipitation. Representative stations were selected based on metadata and a set of criteria for data quality control. An hourly analysis indicates that UHIs are a nocturnal phenomenon in The Netherlands and are more prominent after sunset, when they exceed 2°C. A seasonal analysis shows that UHIs occur in all seasons during the year, with the most significant UHI occurring in the summer. Furthermore, the differences in the precipitation of urban and rural areas were shown to be greatest after sunrise during the day. The maximum hourly UHI and hourly precipitation distributions were analyzed using a generalized extreme value model. The occurrences of maximum precipitation are likely to be more frequent at urban stations than at the nearby rural stations. Additionally, the distinct seasonal cycle of precipitation that is dependent on the UHI demonstrates that the maximum UHI and precipitation occurred in the summer. Our results indicate that the UHI and precipitation enhancements in Dutch urban residential areas, as obtained from the data of weather amateurs, are in agreement with the results presented in the literature, and that 7% more precipitation occurs in cities than in rural areas.

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