Abstract
Abstract. In Belgium, only rain gauge time series have been used so far to study extreme rainfall at a given location. In this paper, the potential of a 12-year quantitative precipitation estimation (QPE) from a single weather radar is evaluated. For the period 2005–2016, 1 and 24 h rainfall extremes from automatic rain gauges and collocated radar estimates are compared. The peak intensities are fitted to the exponential distribution using regression in Q-Q plots with a threshold rank which minimises the mean squared error. A basic radar product used as reference exhibits unrealistic high extremes and is not suitable for extreme value analysis. For 24 h rainfall extremes, which occur partly in winter, the radar-based QPE needs a bias correction. A few missing events are caused by the wind drift associated with convective cells and strong radar signal attenuation. Differences between radar and gauge rainfall values are caused by spatial and temporal sampling, gauge underestimations and radar errors. Nonetheless the fit to the QPE data is within the confidence interval of the gauge fit, which remains large due to the short study period. A regional frequency analysis for 1 h duration is performed at the locations of four gauges with 1965–2008 records using the spatially independent QPE data in a circle of 20 km. The confidence interval of the radar fit, which is small due to the sample size, contains the gauge fit for the two closest stations from the radar. In Brussels, the radar extremes are significantly higher than the gauge rainfall extremes, but similar to those observed by an automatic gauge during the same period. The extreme statistics exhibit slight variations related to topography. The radar-based extreme value analysis can be extended to other durations.
Highlights
Localised rainfall extremes can have a strong impact on human activities especially in urban areas (Ootegem et al, 2016)
For flood management applications it is needed to know the probability that rainfall exceeds a given amount. This probability is often expressed as the rainfall level which, on average, will be exceeded once over a given period of T years, which is defined as the return period
The quantitative precipitation estimation (QPE) is obtained by a careful processing of the volumetric reflectivity measurements from a single weather radar in Belgium
Summary
Localised rainfall extremes can have a strong impact on human activities especially in urban areas (Ootegem et al, 2016). Saito and Matsuyama (2015) used a 26-year radar-gauge dataset (without RFA) to study the spatial variation of hourly rainfall extremes in Japan. Different index flood approaches were tested by Eldardiry et al (2015) in Louisiana, who defined a region as a square window of 44 km size They found for Louisiana (USA) that the relatively short period (13 years) explains the high uncertainty of the analysis, that the index flood method is recommended and that a systematic underestimation is associated with the radar products (its spatial resolution is 4 × 4 km). Using a 10-year high-resolution radar rainfall dataset, Wright et al (2014b) performed a RFA using stochastic storm transposition They found that the radar-based intensity-durationfrequency (IDF) estimates generally reproduce conventional gauge-based IDF estimates but overestimate these for longer return periods and shorter durations. The regional approach is applied at each radar pixel on the whole of Belgium to study the spatial variations of the rainfall extremes
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