Interannual Variability of Rhine River Streamflow and Its Relationship with Large-Scale Anomaly Patterns in Spring and Autumn

Monica Ionita Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany

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Gerrit Lohmann Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany

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Norel Rimbu Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany, and Faculty of Physics, University of Bucharest, and Climed Norad, Bucharest, Romania

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Silvia Chelcea National Institute of Hydrology and Water Management, Bucharest, Romania

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Abstract

Interannual-to-decadal variability of Rhine River streamflow and their relationship with large-scale climate anomaly patterns for spring [March–May (MAM)] and autumn [September–November (SON)] are investigated through a statistical analysis of observed streamflow data and global climate anomaly fields. A wavelet analysis reveals that spring streamflow variability is nonstationary with enhanced variability in the 8–16-yr band from 1860 to 1900 and in the 2–8 and 16–30 yr after 1960. A composite analysis reveals that streamflow anomalies during spring are related to a sea surface temperature (SST) pattern that resembles the corresponding El Niño–Southern Oscillation (ENSO) SST pattern. The corresponding atmospheric circulation pattern favors enhanced moisture advection over the 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-yr band. Autumn streamflow anomalies are significantly related only with the North Atlantic SST anomalies. The atmospheric circulation pattern associated with 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 northwestern part of Europe and a shift southward of the Atlantic jet axis. The orientation of the axis of the Atlantic and African jets, 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.

Corresponding author address: Monica Ionita, Alfred Wegener Institute for Polar and Marine Research, Bussestrasse 24, 27570, Bremerhaven, Germany. E-mail: monica.ionita@awi.de

Abstract

Interannual-to-decadal variability of Rhine River streamflow and their relationship with large-scale climate anomaly patterns for spring [March–May (MAM)] and autumn [September–November (SON)] are investigated through a statistical analysis of observed streamflow data and global climate anomaly fields. A wavelet analysis reveals that spring streamflow variability is nonstationary with enhanced variability in the 8–16-yr band from 1860 to 1900 and in the 2–8 and 16–30 yr after 1960. A composite analysis reveals that streamflow anomalies during spring are related to a sea surface temperature (SST) pattern that resembles the corresponding El Niño–Southern Oscillation (ENSO) SST pattern. The corresponding atmospheric circulation pattern favors enhanced moisture advection over the 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-yr band. Autumn streamflow anomalies are significantly related only with the North Atlantic SST anomalies. The atmospheric circulation pattern associated with 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 northwestern part of Europe and a shift southward of the Atlantic jet axis. The orientation of the axis of the Atlantic and African jets, 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.

Corresponding author address: Monica Ionita, Alfred Wegener Institute for Polar and Marine Research, Bussestrasse 24, 27570, Bremerhaven, Germany. E-mail: monica.ionita@awi.de
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