Climate-change effects on extreme precipitation in central Europe: uncertainties of scenarios based on regional climate models

Kyselý, Jan; Beranová, Romana

doi:10.1007/s00704-008-0014-8

Cited by 98 publications

(63 citation statements)

References 49 publications

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“…Hence, in accordance with another study on extreme precipitation of Kyselý and Beranova (2009), two POT events are considered to be independent when the minimum separation time between both events is one day.…”

Section: ) Error Statisticsmentioning

confidence: 95%

“…However, the choice of a suitable threshold and separation time is relatively arbitrary. The threshold has to be high enough in order to ensure extreme events and to avoid dependency between the events, but a threshold that is too high prevents statistical significance owing to a loss of information (Kyselý and Beranova 2009;Heikkil€ a et al 2011). Similar to the study of Heikkil€ a et al, the threshold has been defined for each station separately as the 0.95th quantile of daily summer precipitation so that spatial differences in the precipitation amount (see Fig.…”

Section: ) Error Statisticsmentioning

confidence: 99%

“…This approach by which model output is directly compared against station observations can be motivated by the fact that the station-level observations provide the closest representation of extreme events (Duliere et al 2011). Furthermore, the motivation for only considering summer precipitation is threefold: (i) other regional climate studies (e.g., Caldwell et al 2009;Soares et al 2012a,b) show difficulties of RCMs to simulate summer precipitation; (ii) the new parameterization scheme within ALARO-0 mostly modifies convection, which is the process most relevant for (extreme) precipitation events in summer (Kyselý and Beranova 2009;Soares et al 2012a); and (iii) the relatively small scale on which these convective processes often occur better corresponds to the high-resolution ALARO-0 simulation (Kyselý and Beranova 2009).…”

Section: Introductionmentioning

confidence: 99%

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Multiscale Performance of the ALARO-0 Model for Simulating Extreme Summer Precipitation Climatology in Belgium

et al. 2013

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Daily summer precipitation over Belgium from the Aire Limitee Adaptation Dynamique Developpement International (ALADIN) model and a version of the model that has been updated with physical parameterizations, the so-called ALARO-0 model [ALADIN and AROME (Application de la Recherche a l'Operationnel a Meso-Echelle) combined model, first baseline version released in 1998], are compared with respect to station observations for the period 1961-90. The 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40) is dynamically downscaled using both models on a horizontal resolution of 40 km, followed by a one-way nesting on high spatial resolutions of 10 and 4 km. This setup allows us to explore the relative importance of spatial resolution versus parameterization formulation on the model skill to correctly simulate extreme daily precipitation. Model performances are assessed through standard statistical errors and density, frequency, and quantile distributions as well as extreme value analysis, using the peak-over-threshold method and generalized Pareto distribution. The 40-km simulations of ALADIN and ALARO-0 show similar results, both reproducing the observations reasonably well. For the high-resolution simulations, ALARO-0 at both 10 and 4 km is in better agreement with the observations than ALADIN. The ALADIN model consistently produces too high precipitation rates. The findings demonstrate that the new parameterizations within the ALARO-0 model are responsible for a correct simulation of extreme summer precipitation at various horizontal resolutions. Moreover, this study shows that ALARO-0 is a good candidate model for regional climate modeling.

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Section: ) Error Statisticsmentioning

confidence: 95%

Section: ) Error Statisticsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multiscale Performance of the ALARO-0 Model for Simulating Extreme Summer Precipitation Climatology in Belgium

et al. 2013

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“…The methodology may also benefit from the 'peaks-over-threshold' analysis (Ding et al, 2008), provided that the issue of regional homogeneity is bridged (the regional homogeneity tests have been designed for the 'block maxima' approach). Last but not the least, non-stationarity may easily be incorporated in the ROI method of the frequency analysis using time index as a covariate (Coles, 2001), in order to address possible effects of climate change on probabilities of precipitation extremes (which are, however, relatively uncertain in central Europe according to recent regional climate model simulations; Kyselý and Beranová, 2009).…”

Section: Discussionmentioning

confidence: 99%

“…The interest in high quantiles of precipitation distributions is also related to possible climate change effects, as climate model simulations -although not capable of reproducing some important features of observed patterns, which reduces their credibility -tend to project increased severity of precipitation extremes over central Europe in a warmer climate (Christensen and Christensen, 2004;Beniston et al, 2007;Kyselý and Beranová, 2009). …”

Section: Introductionmentioning

confidence: 99%

Comparison of regional and at‐site approaches to modelling probabilities of heavy precipitation

Kyselý¹,

Gaál²,

Picek³

2011

Intl Journal of Climatology

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Several approaches to estimating distributions of precipitation extremes are compared by means of simulation experiments, and their applications into observed data in the Czech Republic are evaluated. Regional frequency models, which take into account data in fixed or flexible 'regions' when fitting a distribution at any site, lead to estimates with much smaller errors compared to a single-site analysis, and efficiently reduce random and climatologically irrelevant variations in the estimates of the model parameters and high quantiles. The region-of-influence (ROI) methodology with a built-in regional homogeneity test is recognized as a useful approach, with the model based on proximity of sites outperforming the Hosking-Wallis regional frequency analysis. Comparison of estimates of the return period of a heavy precipitation event on 24 June 2009, which triggered a disastrous local flash flood, illustrates that the at-site analysis leads to unrealistic and extremely uncertain estimates that strongly depend on whether or not a single outlying observation is involved in the sample, while all regional methods yield return periods in the same order of several hundreds of years, notwithstanding whether the 2009 data are included in the sample. The ROI method may be found useful for modelling probabilities of other meteorological variables, extremes of which are strongly influenced by sampling variability, and may also represent an efficient tool for 'smoothing' random variations in the estimates of model parameters and high quantiles of precipitation in high-resolution regional climate model simulations.

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Extreme rainfall flushes out tadpoles of the yellow‐bellied toad Bombinavariegata from its breeding ponds

Adamski,

Łaciak

2023

Ecology

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Climate-change effects on extreme precipitation in central Europe: uncertainties of scenarios based on regional climate models

Cited by 98 publications

References 49 publications

Multiscale Performance of the ALARO-0 Model for Simulating Extreme Summer Precipitation Climatology in Belgium

Multiscale Performance of the ALARO-0 Model for Simulating Extreme Summer Precipitation Climatology in Belgium

Comparison of regional and at‐site approaches to modelling probabilities of heavy precipitation

Extreme rainfall flushes out tadpoles of the yellow‐bellied toad Bombinavariegata from its breeding ponds

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