Hydrological response in the Danube lower basin to some internal and external climate forcing factors
Of the internal factors, we tested the predictors from the fields of precipitation, temperature, pressure and geopotential at 500hPa. From the external factors, we considered the indices of solar/geomagnetic activity. Our analysis was achieved separately for each season, for two time periods 1901–20...
| Main Authors: | , , , |
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| Format: | Text |
| Language: | English |
| Published: |
2018
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| Subjects: | |
| Online Access: | https://doi.org/10.5194/hess-2016-304 https://www.hydrol-earth-syst-sci-discuss.net/hess-2016-304/ |
| Summary: | Of the internal factors, we tested the predictors from the fields of precipitation, temperature, pressure and geopotential at 500hPa. From the external factors, we considered the indices of solar/geomagnetic activity. Our analysis was achieved separately for each season, for two time periods 1901–2000 and 1948–2000. We applied developments in empirical orthogonal functions (EOFs), cross correlations, power spectra, filters, composite maps. In analysis of the correlative results, we took into account, the serial correlation of time series. For the atmospheric variables simultaneously, the most significant results (confidence levels of 95 %) are related to the predictors, considering the difference between standardized temperatures and precipitation (TPP), except for winter season, when the best predictors are the first principal component (PC1) of the precipitation field and the Greenland-Balkan-Oscillation index (GBOI). The GBOI is better predictor for precipitation, in comparison with North Atlantic Oscillation index (NAOI) for the middle and lower Danube basin. The significant results, with the confidence level more than 95 %, were obtained for the PC1-precipitation and TPP during winter/spring, which can be considered good predictors for spring/summer discharge in the Danube lower basin. Simultaneous, the significant signal of geomagnetic index (aa), was obtained for the smoothed data by band pass filter. For the different lags, the atmospheric variables respond to solar/geomagnetic activity after about 2–3 years. The external signals in the terrestrial variables are revealed also by power spectra and composite maps. The power spectra for the terrestrial variables show significant peaks that can be associated with the interannual variability, Quasi-Biennial Oscillation influence and solar/geomagnetic signals. The filtering procedures led to improvement of the correlative analyses between solar or geomagnetic activity and terrestrial variables, under the condition of a rigorous test of the statistical significance. |
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