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    AMER METEOROLOGICAL SOC
    In:  EPIC3Journal of Hydrometeorology, AMER METEOROLOGICAL SOC, (13), pp. 172-188, ISSN: 1525-755X
    Publication Date: 2018-03-07
    Description: Interannual to decadal variability of Rhine river streamflow and their relationship with large-scale climate anomaly patterns for spring (MAM) and autumn (SON) are investigated through statistical analysis of observed streamflow data and global climate anomaly fields. A wavelet analysis reveals that spring streamflow variability is non-stationary with enhanced variability in the 8–16 years band from 1860 to 1900 and in the 2–8 years and 16–30 years after 1960. A composite analysis reveals that streamflow anomalies during spring are related with a sea surface temperature (SST) pattern which resembles the corresponding El Nino-Southern Oscillation (ENSO) SST pattern. The corresponding atmospheric circulation pattern favors enhanced moisture advection over Rhine catchment area during positive streamflow anomalies. During autumn the streamflow variability follows a distribution similar to spring streamflow but with a strong peak in the 30–60 year band. Autumn streamflow anomalies are significantly related only with the North Atlantic SST anomalies. The atmospheric circulation pattern associated to high streamflow during autumn, which is more regional than the corresponding spring pattern, shows a deep low-pressure system over the British Isles and the north-western part of Europe and a shift southward of the Atlantic jet axis. The orientation of the axis of the Atlantic and African Jet, as well as the advection of the moist air from the ocean, plays a crucial role in the variability of Rhine streamflow both in spring and autumn.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 2
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    AMER METEOROLOGICAL SOC
    In:  EPIC3Journal of Hydrometeorology, AMER METEOROLOGICAL SOC, 16(2), pp. 598-614, ISSN: 1525-755X
    Publication Date: 2015-06-05
    Description: Over the past decades Europe has experienced heavy floods with major consequences for thousands of people and billions of Euros worth of damage. In particular, the summer 2013 flood in Central Europe showed how vulnerable modern society is to hydrological extremes and emphasizes once more the need for improved forecast methods of such extreme climatic events. Based on a multiple linear regression model, it is shown here that 55% of the June 2013 Elbe River extreme discharge could have been predicted using May precipitation, soil moisture and sea level pressure. Moreover, our model was able to predict more than 75% of the total Elbe River discharge for June 2013 (in terms of magnitude) by incorporating also the amount of precipitation recorded during the days prior the flood, but the predicted discharge for the June 2013 event was still underestimated by 25%. Given that all predictors used in the model are available at the end of each month, the forecast scheme can be used to predict extreme events and to provide early warnings for upcoming floods. The forecast methodology could be efficient for other rivers also, depending on their location and their climatic background.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
    Location Call Number Limitation Availability
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