Links between large-scale circulation patterns and streamflow in Central Europe: A review

Steirou, Eva; Gerlitz, Lars; Apel, Heiko; Merz, Bruno

doi:10.1016/j.jhydrol.2017.04.003

Cited by 79 publications

(69 citation statements)

References 83 publications

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“…The CM-SSF is more skilful at predicting anomalously low and high streamflows than the ESP in about 10-20 % of the European regions during those seasons. Other studies have found similar patterns for (parts of) Europe; these include less skill in summer than in winter overall for basins in France (Crochemore et al, 2016), less skill for the low flow season (July to October) for basins in central Europe (Meißner et al, 2017), negative correlations in summer and autumn seasonal streamflow forecasts in central Europe as the influence of the winter NAO fades away (Steirou et al, 2017), and less skill overall in summer than in winter in Europe (Bierkens and van Beek, 2009). The lower CM-SSF skill for predicting lower and higher streamflows than normal in summer could additionally be due to the convective storms in summer over Europe, which are hard to predict, and to the fact that it is the dry season in most of Europe, where rivers are groundwater fed.…”

Section: Discussionmentioning

confidence: 60%

“…groundwaterdriven streamflow or snowmelt-driven streamflow), as highlighted by Bierkens and van Beek (2009) Singla et al (2012) for parts of France, Lorenzo-Lacruz et al (2011) for the Iberian Peninsula and Meißner et al (2017) for the Rhine. Moreover, it could be that most of the gained predictability occurs in March, a transition month between the more predictable winter (as mentioned above) and spring, as discussed by Steirou et al (2017). The ESP is overall more skilful than the CM-SSF at predicting the spring streamflow in snow-dominated regions (e.g.…”

Section: Discussionmentioning

confidence: 95%

“…The CM-SSF is more skilful at predicting anomalously low and high streamflows than the ESP in certain seasons and regions, and noticeably in winter in almost 40 % of the European regions, mostly clustered in rainfall-dominated areas of western and central Europe. Several authors have discussed the higher winter predictability over (parts of) Europe, with examples in basins in France (Crochemore et al, 2016), central Europe (Steirou et al, 2017), the UK and the Iberian Peninsula (Lorenzo-Lacruz et al, 2011). Bierkens and van Beek (2009) additionally showed that there was a higher winter predictability in Scandinavia, the Iberian Peninsula and around the Black Sea.…”

Section: Discussionmentioning

confidence: 99%

“…It was shown to affect streamflow predictability, especially during winter (Dettinger and Diaz, 2000;Bierkens and van Beek, 2009;Steirou et al, 2017), in addition to the IHC and the land surface memory. It was furthermore shown to be an indicator of flood damage and occurrence in parts of Europe (Guimarães Nobre et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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Skilful seasonal forecasts of streamflow over Europe?

Arnal

Cloke

Stephens

et al. 2018

Hydrol. Earth Syst. Sci.

113

104

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Abstract. This paper considers whether there is any added value in using seasonal climate forecasts instead of historical meteorological observations for forecasting streamflow on seasonal timescales over Europe. A Europe-wide analysis of the skill of the newly operational EFAS (European Flood Awareness System) seasonal streamflow forecasts (produced by forcing the Lisflood model with the ECMWF System 4 seasonal climate forecasts), benchmarked against the ensemble streamflow prediction (ESP) forecasting approach (produced by forcing the Lisflood model with historical meteorological observations), is undertaken. The results suggest that, on average, the System 4 seasonal climate forecasts improve the streamflow predictability over historical meteorological observations for the first month of lead time only (in terms of hindcast accuracy, sharpness and overall performance). However, the predictability varies in space and time and is greater in winter and autumn. Parts of Europe additionally exhibit a longer predictability, up to 7 months of lead time, for certain months within a season. In terms of hindcast reliability, the EFAS seasonal streamflow hindcasts are on average less skilful than the ESP for all lead times. The results also highlight the potential usefulness of the EFAS seasonal streamflow forecasts for decision-making (measured in terms of the hindcast discrimination for the lower and upper terciles of the simulated streamflow). Although the ESP is the most potentially useful forecasting approach in Europe, the EFAS seasonal streamflow forecasts appear more potentially useful than the ESP in some regions and for certain seasons, especially in winter for almost 40 % of Europe. Patterns in the EFAS seasonal streamflow hindcast skill are however not mirrored in the System 4 seasonal climate hindcasts, hinting at the need for a better understanding of the link between hydrological and meteorological variables on seasonal timescales, with the aim of improving climate-model-based seasonal streamflow forecasting.

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Section: Discussionmentioning

confidence: 60%

Section: Discussionmentioning

confidence: 95%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Skilful seasonal forecasts of streamflow over Europe?

Arnal

Cloke

Stephens

et al. 2018

Hydrol. Earth Syst. Sci.

113

104

View full text Add to dashboard Cite

show abstract

“…We refer the reader to other studies devoted to this phenomenon, e.g. Rutkowska et al (2017), Pociask-Karteczka (2006), Wrzesiński (2011) and a recent review article of Steirou et al (2017).…”

Section: Discussionmentioning

confidence: 99%

Trend detection in river flow indices in Poland

2018

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The issue of trend detection in long time series of river flow records is of vast theoretical interest and considerable practical relevance. Water management is based on the assumption of stationarity; hence, it is crucial to check whether taking this assumption is justified. The objective of this study is to analyse long-term trends in selected river flow indices in small-and medium-sized catchments with relatively unmodified flow regime (semi-natural catchments) in Poland. The examined indices describe annual and seasonal average conditions as well as annual extreme conditions-low and high flows. The special focus is on the spatial analysis of trends, carried out on a comprehensive, representative data set of flow gauges. The present paper is timely, as no spatially comprehensive studies (i.e. covering the entire Poland or its large parts) on trend detection in time series of river flow have been done in the recent 15 years or so. The results suggest that there is a strong random component in the river flow process, the changes are weak and the spatial pattern is complex. Yet, the results of trend detection in different indices of river flow in Poland show that there exists a spatial divide that seems to hold quite generally for various indices (annual, seasonal, as well as low and high flow). Decreases of river flow dominate in the northern part of the country and increases usually in the southern part. Stations in the central part show mostly 'no trend' results. However, the spatial gradient is apparent only for the data for the period 1981-2016 rather than for 1956-2016. It seems also that the magnitude of increases of river flow is generally lower than that of decreases.

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Do Changing Weather Types Explain Observed Climatic Trends in the Rhine Basin? An Analysis of Within‐ and Between‐Type Changes

et al. 2018

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For attributing hydrological changes to anthropogenic climate change, catchment models are driven by climate model output. A widespread approach to bridge the spatial gap between global climate and hydrological catchment models is to use a weather generator conditioned on weather patterns (WPs). This approach assumes that changes in local climate are characterized by between‐type changes of patterns. In this study we test this assumption by analyzing a previously developed WP classification for the Rhine basin, which is based on dynamic and thermodynamic variables. We quantify changes in pattern characteristics and associated climatic properties. The amount of between‐ and within‐type changes is investigated by comparing observed trends to trends resulting solely from WP occurrence. To overcome uncertainties in trend detection resulting from the selected time period, all possible periods in 1901–2010 with a minimum length of 31 years are analyzed. Increasing frequency is found for some patterns associated with high precipitation, although the trend sign highly depends on the considered period. Trends and interannual variations of WP frequencies are related to the long‐term variability of large‐scale circulation modes. Long‐term WP internal warming is evident for summer patterns and enhanced warming for spring/autumn patterns since the 1970s. Observed trends in temperature and partly in precipitation are mainly associated with frequency changes of specific WPs, but some amount of within‐type changes remains. The classification can be used for downscaling of past changes considering this limitation, but the inclusion of thermodynamic variables into the classification impedes the downscaling of future climate projections.

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Links between large-scale circulation patterns and streamflow in Central Europe: A review

Cited by 79 publications

References 83 publications

Skilful seasonal forecasts of streamflow over Europe?

Skilful seasonal forecasts of streamflow over Europe?

Trend detection in river flow indices in Poland

Do Changing Weather Types Explain Observed Climatic Trends in the Rhine Basin? An Analysis of Within‐ and Between‐Type Changes

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