Projected changes of rainfall event characteristics for the Czech Republic

Svoboda, Vojtěch; Hanel, Martin; Máca, Petr; Kyselý, Jan

doi:10.1515/johh-2016-0036

Cited by 25 publications

(16 citation statements)

References 51 publications

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“…In particular, we study the slopes of the 0.05-0.95 quantiles in steps of 0.05 (see Figure 1). This builds upon the results of Moberg et al (2006), who partitioned precipitation distribution in 2%, 5%, 10%, 90%, 95%, and 98% percentiles and calculated the corresponding trends, and Allan and Soden (2008), Rossow et al (2013), Svoboda et al (2016Svoboda et al ( , 2017 who considered discrete 5-10% quantile bins, in a comparison between observed data and model simulations.…”

Section: Methodsmentioning

confidence: 84%

Assessment of Water Cycle Intensification Over Land using a Multisource Global Gridded Precipitation DataSet

et al. 2019

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The change in the empirical distribution of future global precipitation is one of the major implications regarding the intensification of global water cycle. Heavier events are expected to occur more often, compensated by decline of light precipitation and/or number of wet days. Here, we scrutinize a new global, high‐resolution precipitation data set, namely, the Multi‐Source Weighted‐Ensemble Precipitation v2.0, to determine changes in the precipitation distribution over land during 1979–2016. To this end, the fluctuations of wet days precipitation quantiles on an annual basis and their interplay with annual totals and number of wet days were investigated. The results show increase in total precipitation, number of wet days, and heavy events over land, as suggested by the intensification hypothesis. However, the decline in light/medium precipitation or wet days was weaker than expected, debating the “compensation” mechanism.

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Section: Methodsmentioning

confidence: 84%

Assessment of Water Cycle Intensification Over Land using a Multisource Global Gridded Precipitation DataSet

et al. 2019

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“…However, recent values of the erosivity index were not exceptional when compared to a longer (91-year) record available at a single station. Considerable projected increases in the rainfall erosivity index in an ensemble of regional climate model simulations for the Czech Republic were reported by Svoboda et al (2016b).…”

Section: Introductionmentioning

confidence: 99%

The rainfall erosivity factor in the Czech Republic and its uncertainty

Hanel

Máca

Bašta

et al. 2016

Hydrol. Earth Syst. Sci.

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Abstract. In the present paper, the rainfall erosivity factor (R factor) for the area of the Czech Republic is assessed. Based on 10 min data for 96 stations and corresponding R factor estimates, a number of spatial interpolation methods are applied and cross-validated. These methods include inverse distance weighting, standard, ordinary, and regression kriging with parameters estimated by the method of moments and restricted maximum likelihood, and a generalized least-squares (GLS) model. For the regression-based methods, various statistics of monthly precipitation as well as geographical indices are considered as covariates. In addition to the uncertainty originating from spatial interpolation, the uncertainty due to estimation of the rainfall kinetic energy (needed for calculation of the R factor) as well as the effect of record length and spatial coverage are also addressed. Finally, the contribution of each source of uncertainty is quantified. The average R factor for the area of the Czech Republic is 640 MJ ha−1 mm h−1, with values for the individual stations ranging between 320 and 1520 MJ ha−1 mm h−1. Among various spatial interpolation methods, the GLS model relating the R factor to the altitude, longitude, mean precipitation, and mean fraction of precipitation above the 95th percentile of monthly precipitation performed best. Application of the GLS model also reduced the uncertainty due to the record length, which is substantial when the R factor is estimated for individual sites. Our results revealed that reasonable estimates of the R factor can be obtained even from relatively short records (15–20 years), provided sufficient spatial coverage and covariates are available.

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“…It is noteworthy that extreme rainfall changes for the Iberian Peninsula are different from those in other regions. For instance, some studies have found evidence of increasing trends in intensity for various European regions, with the Czech Republic being an example [27].…”

Section: Discussionmentioning

confidence: 99%

Return Level Estimation of Extreme Rainfall over the Iberian Peninsula: Comparison of Methods

Acero

Parey

García

et al. 2018

Water

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Different ways to estimate future return levels (RLs) for extreme rainfall, based on extreme value theory (EVT), are described and applied to the Iberian Peninsula (IP). The study was done for an ensemble of high quality rainfall time series observed in the IP during the period 1961-2010. Two approaches, peaks-over-threshold (POT) and block maxima (BM) with the generalized extreme value (GEV) distribution, were compared in order to identify which is the more appropriate for the estimation of RLs. For the first approach, which identifies trends in the parameters of the asymptotic distributions of extremes, both all-days and rainy-days-only datasets were considered because a major fraction of values of daily rainfall over the IP is zero. For the second approach, rainy-days-only data were considered showing how the mean, variance and number of rainy days evolve. The 20-year RLs expected for 2020 were estimated using these methods for three seasons: autumn, spring and winter. The GEV is less reliable than the POT because fixed blocks lead to the selection of non-extreme values. Future RLs obtained with the POT are greater than those estimated with the GEV, mainly because some gauges show significant positive trends for the number of rainy days. Autumn, rather than winter, is currently the season with the heaviest rainfall for some regions.

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Projected changes of rainfall event characteristics for the Czech Republic

Cited by 25 publications

References 51 publications

Assessment of Water Cycle Intensification Over Land using a Multisource Global Gridded Precipitation DataSet

Assessment of Water Cycle Intensification Over Land using a Multisource Global Gridded Precipitation DataSet

The rainfall erosivity factor in the Czech Republic and its uncertainty

Return Level Estimation of Extreme Rainfall over the Iberian Peninsula: Comparison of Methods

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