2008 ◽  
Vol 12 (3) ◽  
pp. 825-839 ◽  
Author(s):  
L. Gaál ◽  
J. Kyselý ◽  
J. Szolgay

Abstract. The paper compares different approaches to regional frequency analysis with the main focus on the implementation of the region-of-influence (ROI) technique for the modelling of probabilities of heavy precipitation amounts in the area of the Western Carpathians. Unlike the conventional regional frequency analysis where the at-site design values are estimated within a fixed pooling group (region), the ROI approach as a specific alternative to focused pooling techniques makes use of flexible pooling groups, i.e. each target site has its own group of sufficiently similar sites. In this paper, various ROI pooling schemes are constructed as combinations of different alternatives of sites' similarity (pooling groups defined according to climatological characteristics and geographical proximity of sites, respectively) and pooled weighting factors. The performance of the ROI pooling schemes and statistical models of conventional (regional and at-site) frequency analysis is assessed by means of Monte Carlo simulation studies for precipitation annual maxima for the 1-day and 5-day durations in Slovakia. It is demonstrated that a) all the frequency models based on the ROI method yield estimates of growth curves that are superior to the standard regional and at-site estimates at most individual sites, and b) the selection of a suitable ROI pooling scheme should be adjusted to the dominant character of the formation of heavy precipitation.


2017 ◽  
Author(s):  
Edouard Goudenhoofdt ◽  
Laurent Delobbe ◽  
Patrick Willems

Abstract. In Belgium, only rain gauge time-series have been used so far to study extreme precipitation 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, independent sliding 1 h and 24 h rainfall extremes from automatic rain gauges and collocated radar estimates are compared. The extremes are fitted to the exponential distribution using regression in QQ-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 of convective cells and strong radar signal attenuation. Differences between radar and gauge values are caused by spatial and temporal sampling, gauge rainfall underestimations and radar errors due to the relation between reflectivity and rain rate. 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 is performed on radar data within 20 km of the locations of 4 rain gauges with records from 1965 to 2008. Assuming that the extremes are correlated within the region, the fit to the two closest rain gauge data is within the confidence interval of the radar fit, which is small due to the sample size. In Brussels, the extremes on the period 1965–2008 from a rain gauge are significantly lower than the extremes from an automatic gauge and the radar on the period 2005–2016. For 1 h duration, the location parameter varies slightly with topography and the scale parameter exhibits some variations from region to region. The radar-based extreme value analysis can be extended to other durations.


Sign in / Sign up

Export Citation Format

Share Document