Extreme Precipitation In Europe Research Articles

On the temporal clustering of European extreme precipitation events and its relationship to persistent and transient large-scale atmospheric drivers

Extreme precipitation events that occur in close succession can have important societal and economic repercussions. Here we use 42 years of reanalysis data (ERA-5) to investigate the link between Euro-Atlantic large-scale pattern of weather and climate variability and the temporal clustering of extreme rainfall events over Europe. We implicitly model the seasonal rate of extreme occurrences as part of a Poisson General Additive Model (GAM) using cyclic regression cubic splines. The smoothed seasonal rate of extreme rainfall occurrences is used to (i) infer the frequency of significant temporal clustering and (ii) implicitly serves as the baseline rate when modeling the effects of atmospheric drivers on extreme rainfall clustering. We use GAMs to model the association between the temporal clustering of extreme rainfall events and seven predominant year-round weather regimes in the Euro-Atlantic sector as well as a measure of synoptic-scale transient recurrent Rossby wave packets. Sub-seasonal clustering of precipitation events is significant at all grid-points over Europe; the proportion of extreme rainfall events that cluster in time ranges between 2% to 27%. The most relevant weather regime is the Atlantic Trough (corresponding to NAO+ with a southward shift of the jet) explaining most of the significant increase in clustering probability over Europe. The Greenland Blocking regime explains most of the clustering over the Iberian Peninsula. The Scandinavian Blocking regime is associated with a significant increase in clustering probability over the western Mediterranean, with a northwards shift in the signal to central Europe in summer.

On the Temporal Clustering of European Extreme Precipitation Events and its Relationship to Persistent and Transient Large-Scale Atmospheric Drivers

On the Temporal Clustering of European Extreme Precipitation Events and its Relationship to Persistent and Transient Large-Scale Atmospheric Drivers

European extreme precipitation: The effects of spatio-temporal resolution of the data

European wintertime precipitation is known to be skilfully estimated in reanalysis data and model simulations since it is highly correlated with large scale, low frequency modes of variability, namely the North Atlantic Oscillation (NAO). Since the NAO is mainly a wintertime mode of variability, the skill of estimating precipitation becomes more limited in other seasons, most importantly in summer, when precipitation is mainly a result of mesoscale convection. In this study, we use the Weather Research and Forecast (WRF) model, to show the added value of using a high resolution, convection-permitting model to estimate precipitation extremes. The results show that WRF succeeds to correct the failure of ERA-Interim reanalysis to capture the positive trends over the last decades of European extreme precipitation in summer and transition seasons, that are indicated by observational data (E-OBS) and previous literature. Partial improvements are evident using ERA5 reanalysis, specifically in Spring and in Autumn. In winter, changes in European extreme precipitation over the last decades are dominated by variations in the NAO index, and are well reproduced both in reanalysis data and in the high resolution WRF downscaling.

Identifying robust bias adjustment methods for European extreme precipitation in a multi-model pseudo-reality setting

Abstract. Severe precipitation events occur rarely and are often localised in space and of short duration, but they are important for societal managing of infrastructure. Therefore, there is a demand for estimating future changes in the statistics of the occurrence of these rare events. These are often projected using data from regional climate model (RCM) simulations combined with extreme value analysis to obtain selected return levels of precipitation intensity. However, due to imperfections in the formulation of the physical parameterisations in the RCMs, the simulated present-day climate usually has biases relative to observations; these biases can be in the mean and/or in the higher moments. Therefore, the RCM results are adjusted to account for these deficiencies. However, this does not guarantee that the adjusted projected results will match the future reality better, since the bias may not be stationary in a changing climate. In the present work, we evaluate different adjustment techniques in a changing climate. This is done in an inter-model cross-validation set-up in which each model simulation, in turn, performs pseudo-observations against which the remaining model simulations are adjusted and validated. The study uses hourly data from historical and RCP8.5 scenario runs from 19 model simulations from the EURO-CORDEX ensemble at a 0.11∘ resolution. Fields of return levels for selected return periods are calculated for hourly and daily timescales based on 25-year-long time slices representing the present-day (1981–2005) and end-21st-century (2075–2099). The adjustment techniques applied to the return levels are based on extreme value analysis and include climate factor and quantile-mapping approaches. Generally, we find that future return levels can be improved by adjustment, compared to obtaining them from raw scenario model data. The performance of the different methods depends on the timescale considered. On hourly timescales, the climate factor approach performs better than the quantile-mapping approaches. On daily timescales, the superior approach is to simply deduce future return levels from pseudo-observations, and the second-best choice is using the quantile-mapping approaches. These results are found in all European subregions considered. Applying the inter-model cross-validation against model ensemble medians instead of individual models does not change the overall conclusions much.

The contribution of anthropogenic influence to more anomalous extreme precipitation in Europe

Anthropogenic influences can modulate the low‐frequency variability of extreme precipitation and increase the likelihood of flooding events. It is not, however, clear how much and in what manner the low-frequency variability has changed in recent decades as global warming has intensified. Here, we investigate the contribution of anthropogenic influences to the time evolution of extreme precipitation anomalies in different seasons using Coupled Model Intercomparison Project Phase 6 (CMIP6) and CMIP5 model simulations and observations over Europe. Our results show a latitudinal dependence of changes in extreme precipitation anomalies for all seasons due to anthropogenic impacts. While the contribution of anthropogenic influences to extreme precipitation anomalies at low latitudes (<50°) is less than 8% in all seasons, it goes up to 26% and 41% at mid (50°–60°) and high (>60°) latitudes. Without the offsetting effect of anthropogenic aerosols, anthropogenic emissions of greenhouse gases alone should have produced larger anomalies than observed. For all seasons, the more extreme the precipitation, the larger the anthropogenic influences.

Moisture fluxes conducive to central European extreme precipitation events

For the emergence of central European extreme precipitation events (EPEs), moisture supply mainly from the Atlantic or Mediterranean and an ascent of moist air are the most important ingredients. In the present study, we aim to define groups of EPEs with characteristic moisture flux conditions in the area of extra high upward vertical velocity, as well as to find the connection between the variants of moisture flux conditions and the spatio-seasonal distribution of extreme precipitation. Using ERA5 reanalysis data, we assigned one of three moisture flux variants to the set of 43 EPEs from 1979 to 2013 and thus specified (i) events with dominating moisture flux from the north (Nf), (ii) events with dominating moisture flux from the west (Wf), and (iii) other low-flux events (Ot). The classification of EPEs corresponds perfectly with seasonal and spatial patterns of extreme precipitation: while Nf events were concentrated only in the warm half-year and affected mainly eastern central Europe, Wf events occurred in the west and exclusively from September to March. Mainly in the case of Nf events, a direct link existing between anomalies in moisture flux and precipitation extremes can be beneficial for improving skill in forecasting EPEs.

Observed extreme precipitation trends and scaling in Central Europe

In this publication we aim to relate observed changes in Central European extreme precipitation to the respective large-scale thermodynamic state of the atmosphere. Maxima of long-term (1901–2013) daily precipitation records from a densely sampled Central European station network, spanning Austria, Switzerland, Germany and the Netherlands, are scaled with Northern Hemispheric and regional temperature anomalies. Scaling coefficients are estimated at station level and aggregated to infer a robust regional extreme precipitation – temperature relationship. Across Central Europe, an overall intensification and a positive scaling signal with Northern Hemispheric temperature is detected in annual, summer, and winter single-day to monthly maximum precipitation. Generally, the estimates are consistent also when only considering data after 1950, and the scaling of annual maxima is also significant for all individual countries but Austria. However, scaling magnitudes are found to vary considerably between seasons and subregions. Also, scaling with regional temperature is non-significant, except for winter extreme precipitation.

Spatial patterns and time distribution of central European extreme precipitation events between 1961 and 2013

Precipitation extremes always have an area‐related effect, emphasizing the need for a spatial assessment of extreme precipitation events that sometimes show similar behaviour in precipitation patterns due to recurring synoptic features. Our study investigates spatial patterns in the extreme precipitation events (EPEs) that occurred in central Europe between 1961 and 2013. As many as 53 maximum events were selected by the weather extremity index (WEI), reflecting simultaneously the spatial extent and the return periods of t day precipitation totals within an event‐adjusted study area. The extremity of the EPEs is further evaluated at two lower spatial levels, the main river basins (the Rhine, Weser/Ems, Elbe, Danube, and Oder) and 20 smaller subcatchments, which enables a more detailed study of the events’ spatial structure and similarity. A correlation analysis demonstrated that heavy precipitation occurs simultaneously not only in neighbouring subcatchments but also in rather distant regions with similar orientations of mountain ranges (e.g., in the Elbe‐a and Danube‐b subcatchments). In contrast, strong negative correlations appeared between several subcatchments in the Oder and Rhine River basins, which exclude heavy precipitation from occurring simultaneously in both basins. Similar spatial patterns are obvious among precipitation extremes; using the relative WEI values as the similarity measure, agglomerative hierarchical clustering detected two well‐separated groups of events, namely, W‐CE and E‐CE, affecting mainly the western and eastern parts of central Europe, respectively. A finer division of the EPEs distinguished five clusters of events with different spatio‐temporal characteristics. Only two clusters, ED (Elbe‐Danube) and O (Oder), were represented among the top 10 central European EPEs, which occurred exclusively from the end of May to the beginning of September. Three other clusters consisted of generally lower extreme events rather equally distributed throughout the year.

Lagged influence of Atlantic and Pacific climate patterns on European extreme precipitation

The risk of European extreme precipitation and flooding as an economic and humanitarian disaster is modulated by large-scale atmospheric processes that operate over (multi-)decadal periods and transport huge quantities of moisture inland from the oceans. Yet the previous studies for better understanding of extreme precipitation variability and its skillful seasonal prediction are far from comprehensive. Here we show that the winter North Atlantic Oscillation (NAO) and, to a lesser extent, winter ENSO signal have a controlling influence not only concurrently on European extreme precipitation anomaly in winter, but in a delayed way on the extremes in the following seasons. In a similar pattern, there is a strong footprint of summer atmospheric circulations over the Mediterranean Sea on summer extreme precipitation and with 1-, 2- and 3-season lags on the following autumn, winter and spring extremes. The combined influences of the different atmospheric circulation patterns mark a significant step forward for an improved predictability of European extreme precipitation in the state-of-the-art seasonal prediction systems.

Inter-comparison of statistical downscaling methods for projection of extreme precipitation in Europe

Abstract. Information on extreme precipitation for future climate is needed to assess the changes in the frequency and intensity of flooding. The primary source of information in climate change impact studies is climate model projections. However, due to the coarse resolution and biases of these models, they cannot be directly used in hydrological models. Hence, statistical downscaling is necessary to address climate change impacts at the catchment scale. This study compares eight statistical downscaling methods (SDMs) often used in climate change impact studies. Four methods are based on change factors (CFs), three are bias correction (BC) methods, and one is a perfect prognosis method. The eight methods are used to downscale precipitation output from 15 regional climate models (RCMs) from the ENSEMBLES project for 11 catchments in Europe. The overall results point to an increase in extreme precipitation in most catchments in both winter and summer. For individual catchments, the downscaled time series tend to agree on the direction of the change but differ in the magnitude. Differences between the SDMs vary between the catchments and depend on the season analysed. Similarly, general conclusions cannot be drawn regarding the differences between CFs and BC methods. The performance of the BC methods during the control period also depends on the catchment, but in most cases they represent an improvement compared to RCM outputs. Analysis of the variance in the ensemble of RCMs and SDMs indicates that at least 30% and up to approximately half of the total variance is derived from the SDMs. This study illustrates the large variability in the expected changes in extreme precipitation and highlights the need for considering an ensemble of both SDMs and climate models. Recommendations are provided for the selection of the most suitable SDMs to include in the analysis.

Space‐time structure of extreme precipitation in Europe over the last century

ABSTRACTWe investigate the space‐time structure of extreme precipitation in Europe over the last century, using daily rainfall data from the European Climate Assessment &amp; Dataset (ECA&amp;D) archive. The database includes 267 stations with records longer than 100 years. In the winter season (October to March), for each station, two classes of daily rainfall amount values are selected that, respectively, exceed the 90th and 95th percentile of daily rainfall amount over all the 100 years. For each class, and at each location, an annual time series of the frequency of exceedance and of the total precipitation, defined respectively as the number of days the rainfall threshold (90th and 95th percentiles) is exceeded and total precipitation on days when the percentile is exceeded, are developed. Space‐time structure of the frequency and total precipitation time series at the different locations are then pursued using multivariate time and frequency domain methods. The identified key trends and organized spectral modes are linked to well‐known climate indices, as North Atlantic Oscillation (NAO) and El Nino Southern Oscillation (ENSO). The spectra of the leading principal component of frequency of exceedance and of total precipitation have a peak with a 5‐year period that is significant at the 5% level. These are also significantly correlated with ENSO series with this period. The spectrum of total rainfall is significant at the 10% level with a period of ∼8 years. This appears to be significantly correlated to the NAO index at this period. Thus, a decomposition of both secular trends and quasi‐periodic behaviour in extreme daily rainfall is provided.

Projected changes in European extreme precipitation indices on the basis of global and regional climate model ensembles

ABSTRACTAs both global (GCM) and regional (RCM) climate models have their own advantages, the most comprehensive picture of changes in precipitation and their uncertainty ranges can be achieved by comparing the results of both model categories. Here we have evaluated seasonal changes in indices representing excess or scarcity of precipitation in Europe on the basis of simulations performed with ten GCMs with a reasonably high spatial resolution and, for comparison, with five RCMs driven by one and the same GCM. We found no fundamental differences between the GCMs and RCMs in the projected tendency towards a more extreme precipitation climate, characterized by increases both in indices representing wet conditions and also dry conditions. Most evidently in the Northern European summer and Southern European winter, the differences in the responses of the various indices between the present sets of GCMs and RCMs could be explained by the dissimilar changes in seasonal mean precipitation. The scatter among the projected changes was in general much smaller for the RCM than for the GCM simulations. The projections of individual RCMs mainly fall within the interval determined by the GCM projections. This indicates that the GCM ensemble yielded more comprehensive estimates for the uncertainty ranges in the extreme precipitation indices.

Evaluation of modeled changes in extreme precipitation in Europe and the Rhine basin

In this study, we investigate the change in multi-day precipitation extremes in late winter in Europe using observations and climate models. The objectives of the analysis are to determine whether climate models can accurately reproduce observed trends and, if not, to find the causes of the difference in trends. Similarly to an earlier finding for mean precipitation trends, and despite a lower signal to noise ratio, climate models fail to reproduce the increase in extremes in much of northern Europe: the model simulations do not cover the observed trend in large parts of this area. A dipole in the sea-level pressure trend over continental Europe causes positive trends in extremes in northern Europe and negative trends in the Iberian Peninsula. Climate models have a much weaker pressure trend dipole and as a result a much weaker (extreme) precipitation response. The inability of climate models to correctly simulate observed changes in atmospheric circulation is also primarily responsible for the underestimation of trends in the Rhine basin. When it has been adjusted for the circulation trend mismatch, the observed trend is well within the spread of the climate model simulations. Therefore, it is important that we improve our understanding of circulation changes, in particular related to the cause of the apparent mismatch between observed and modeled circulation trends over the past century.

Extreme precipitation in Europe: statistical threshold selection based on climatological criteria

In the present study, both parametric (peak over threshold: mean residual life, dispersion index, threshold choice) and non-parametric (percentiles indices 95% and 99%) statistical techniques are employed, aiming at the identification of rainfall thresholds above which a precipitation event can be characterized as extreme. The analysis is based on 45 years (1960–2004) rain gauge daily records from 65 meteorological stations over the European region. According to two climatologically based criteria that were introduced in the study, it was found that a combined peak over threshold methodology has been shown to yield higher threshold values above which extreme precipitation events occur, in comparison to the 95th percentile indices. Overall, concerning northern Europe, it was found that in the majority of the stations, the threshold values vary from 20 to 30 mm, while the results concerning the Mediterranean region are less coherent and the selection of extreme precipitation thresholds differs from region to region. Stations over eastern Mediterranean appear to have thresholds higher than 30 mm, while stations located over the main cyclone trajectories and the cyclogenesis zone of Mediterranean are those with the higher extreme precipitation thresholds (higher than 45 mm).

Climatological aspects of extreme precipitation in Europe, related to mid-latitude cyclonic systems

Climatic aspects of extreme European precipitation are studied. Daily pluviometric data from 280 stations across Europe, covering the period from 1958 to 2000, are used. First, the criteria for extreme precipitation cases and episodes are communicated using threshold and spatial definitions. The cases and episodes meeting these criteria are grouped according to their area of appearance. Most of them are located in three major areas: Greece, the Alps, and the Iberian Peninsula. The existence of trends in the annual and seasonal time series of these extreme events is examined. Decreasing trends are found in most of the cases, for Greece, the Iberian Peninsula, and Europe, as a whole. The Alps present a different behavior, with no trend at all in the southern part, and a possible increasing trend in the northern part. Finally, the positive impact of altitude in the frequency of occurrence of extreme precipitation episodes in Europe is discussed.

Improving Estimates of Heavy and Extreme Precipitation Using Daily Records from European Rain Gauges

Abstract The long-term variability in heavy precipitation characteristics over Europe for the period 1950–2000 is analyzed using high-quality daily records of rain gauge measurements from the European Climate Assessment (ECA) dataset. To improve the accuracy of heavy precipitation estimates, the authors suggest estimating the fractional contribution of very wet days to total precipitation from the probability distribution of daily precipitation than from the raw data, as it is adopted for the widely used R95tot precipitation index. This is feasible under the assumption that daily precipitation follows an analytical distribution like the gamma probability density function (PDF). The extended index R95tt based on the gamma PDF is compared to the classical R95tot index. The authors find that R95tt is more stable, especially when precipitation extremes are estimated from the limited number of wet days of seasonal and monthly time series. When annual daily time series are analyzed, linear trends in R95tt and R95tot are qualitatively consistent; both hint at a growing occurrence of extreme precipitation of up to 3% decade−1 in central western Europe and in south European Russia, with a somewhat more evident trend pattern for the R95tt index. Linear trends estimated for individual seasons, however, exhibit pronounced differences when derived from both indices. In particular, in winter, R95tt clearly reveals an increasing occurrence of extreme precipitation in western European Russia (up to 4% decade−1), while during summer, a downward tendency in the fractional contribution of very wet days is found in central western Europe. The new index also allows for a better association of European extreme precipitation with the North Atlantic Oscillation (NAO) index by showing a more consistent spatial correlation pattern and higher correlation levels compared to R95tot.