Discriminant Analysis of the Solar Input on the Danube’s Discharge in the Lower Basin

This paper presents the extent to which the combination of extra-atmospheric and hydroclimatic factors can be deciphered to record their contribution to the evolution and forecasting of the Danube discharge (Q) in the lower basin. A combination of methods such as wavelet filtering and deep learning...

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Published in:Atmosphere
Main Authors: Constantin Mares, Ileana Mares, Venera Dobrica, Crisan Demetrescu
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2023
Subjects:
NAO
GBO
Online Access:https://doi.org/10.3390/atmos14081281
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spelling ftmdpi:oai:mdpi.com:/2073-4433/14/8/1281/ 2023-09-05T13:19:56+02:00 Discriminant Analysis of the Solar Input on the Danube’s Discharge in the Lower Basin Constantin Mares Ileana Mares Venera Dobrica Crisan Demetrescu agris 2023-08-13 application/pdf https://doi.org/10.3390/atmos14081281 EN eng Multidisciplinary Digital Publishing Institute Climatology https://dx.doi.org/10.3390/atmos14081281 https://creativecommons.org/licenses/by/4.0/ Atmosphere; Volume 14; Issue 8; Pages: 1281 NAO GBO Palmer index Schwabe and Hale solar cycles Danube discharge filter wavelet transform deep learning machine Text 2023 ftmdpi https://doi.org/10.3390/atmos14081281 2023-08-20T23:52:12Z This paper presents the extent to which the combination of extra-atmospheric and hydroclimatic factors can be deciphered to record their contribution to the evolution and forecasting of the Danube discharge (Q) in the lower basin. A combination of methods such as wavelet filtering and deep learning (DL) constitutes the basic method for discriminating the external factors (solar activity through Wolf numbers) that significantly contribute to the evolution and prediction of the lower Danube discharge. An ensemble of some of the most important factors, namely, those representing the atmospheric components, i.e., the Greenland-Balkan Oscillation Index (GBOI) and the North Atlantic Oscillation Index (NAOI); the hydroclimatic indicator, the Palmer Hydrological Drought Index (PHDI); and the extra-atmospheric factor, constitutes the set of predictors by means of which the predictand, Q, in the summer season, is estimated. The external factor has to be discriminated in the Schwabe and Hale spectra to make its convolutional contribution to the Q estimation in the lower Danube basin. An interesting finding is that adding two solar predictors (associated with the Schwabe and Hale cycles) to the terrestrial ones give a better estimation of the Danube discharge in summer, compared to using only terrestrial predictors. Based on the Nash–Sutcliffe (NS) index, a measure of performance given by the extreme learning machine (ELM), it is shown that, in association with certain terrestrial predictors, the contribution of the Hale cycle is more significant than the contribution of the Schwabe cycle to the estimation of the Danube discharge in the lower basin. Text Greenland North Atlantic North Atlantic oscillation MDPI Open Access Publishing Greenland Hale ENVELOPE(-86.317,-86.317,-78.067,-78.067) Nash ENVELOPE(-62.350,-62.350,-74.233,-74.233) Sutcliffe ENVELOPE(-81.383,-81.383,50.683,50.683) Atmosphere 14 8 1281
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic NAO
GBO
Palmer index
Schwabe and Hale solar cycles
Danube discharge
filter wavelet transform
deep learning machine
spellingShingle NAO
GBO
Palmer index
Schwabe and Hale solar cycles
Danube discharge
filter wavelet transform
deep learning machine
Constantin Mares
Ileana Mares
Venera Dobrica
Crisan Demetrescu
Discriminant Analysis of the Solar Input on the Danube’s Discharge in the Lower Basin
topic_facet NAO
GBO
Palmer index
Schwabe and Hale solar cycles
Danube discharge
filter wavelet transform
deep learning machine
description This paper presents the extent to which the combination of extra-atmospheric and hydroclimatic factors can be deciphered to record their contribution to the evolution and forecasting of the Danube discharge (Q) in the lower basin. A combination of methods such as wavelet filtering and deep learning (DL) constitutes the basic method for discriminating the external factors (solar activity through Wolf numbers) that significantly contribute to the evolution and prediction of the lower Danube discharge. An ensemble of some of the most important factors, namely, those representing the atmospheric components, i.e., the Greenland-Balkan Oscillation Index (GBOI) and the North Atlantic Oscillation Index (NAOI); the hydroclimatic indicator, the Palmer Hydrological Drought Index (PHDI); and the extra-atmospheric factor, constitutes the set of predictors by means of which the predictand, Q, in the summer season, is estimated. The external factor has to be discriminated in the Schwabe and Hale spectra to make its convolutional contribution to the Q estimation in the lower Danube basin. An interesting finding is that adding two solar predictors (associated with the Schwabe and Hale cycles) to the terrestrial ones give a better estimation of the Danube discharge in summer, compared to using only terrestrial predictors. Based on the Nash–Sutcliffe (NS) index, a measure of performance given by the extreme learning machine (ELM), it is shown that, in association with certain terrestrial predictors, the contribution of the Hale cycle is more significant than the contribution of the Schwabe cycle to the estimation of the Danube discharge in the lower basin.
format Text
author Constantin Mares
Ileana Mares
Venera Dobrica
Crisan Demetrescu
author_facet Constantin Mares
Ileana Mares
Venera Dobrica
Crisan Demetrescu
author_sort Constantin Mares
title Discriminant Analysis of the Solar Input on the Danube’s Discharge in the Lower Basin
title_short Discriminant Analysis of the Solar Input on the Danube’s Discharge in the Lower Basin
title_full Discriminant Analysis of the Solar Input on the Danube’s Discharge in the Lower Basin
title_fullStr Discriminant Analysis of the Solar Input on the Danube’s Discharge in the Lower Basin
title_full_unstemmed Discriminant Analysis of the Solar Input on the Danube’s Discharge in the Lower Basin
title_sort discriminant analysis of the solar input on the danube’s discharge in the lower basin
publisher Multidisciplinary Digital Publishing Institute
publishDate 2023
url https://doi.org/10.3390/atmos14081281
op_coverage agris
long_lat ENVELOPE(-86.317,-86.317,-78.067,-78.067)
ENVELOPE(-62.350,-62.350,-74.233,-74.233)
ENVELOPE(-81.383,-81.383,50.683,50.683)
geographic Greenland
Hale
Nash
Sutcliffe
geographic_facet Greenland
Hale
Nash
Sutcliffe
genre Greenland
North Atlantic
North Atlantic oscillation
genre_facet Greenland
North Atlantic
North Atlantic oscillation
op_source Atmosphere; Volume 14; Issue 8; Pages: 1281
op_relation Climatology
https://dx.doi.org/10.3390/atmos14081281
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/atmos14081281
container_title Atmosphere
container_volume 14
container_issue 8
container_start_page 1281
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