Long-term precipitation forecasts can provide valuable information to help mitigate some of the outcome of floods and enhance water manage. This study aims to extract significant information from oceanic-atmospheric oscillations that could enhance seasonal precipitation forecasting. A hybrid AI-type data-driven artificial neural network model called MWD-NARX based on a non-linear autoregressive network with exogenous inputs coupled to multiresolution wavelet decomposition (MWD) is then developed in this work. First, MWD is used to decompose climatic indices and precipitation data. Then the NARX ensemble model allowed to identify the statistical links between the decomposed indices and the decomposed precipitation according to temporal scales and to predict each precipitation decomposition. Ensemble precipitation forecasts are carried out over horizons ranging from 1 to 6 months. For operational forecasting, the forecasts obtained from the decompositions are summed to represent the true precipitation forecast value. The seasonal forecasts of average precipitation by sub-basins (SBV) of the Medjerda are carried out. Large scale teleconnections ENSO, PDO, NAO, AO and as well as Mediterranean Oscillation were used as inputs to the model. The forecasting model coupled to data pre-processing method made it possible to produce very satisfactory forecasts of non-stationary data by extracting modes of variability. The results indicate that exogenous inputs like climatic indices clearly improves the accuracy of forecasts on 82% of SBVs and increases the forecast lead-time up to 6 months. This research is the first of its kind using a hybrid prediction approach by means of indices related to ocean-atmospheric oscillations in North Africa.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Climate Teleconnections Contribution to Seasonal Precipitation Forecasts Using Hybrid Intelligent Model


    Additional title:

    Sustain. Civil Infrastruct.


    Contributors:

    Conference:

    International Road Federation World Meeting & Exhibition ; 2021 ; Dubai, United Arab Emirates November 07, 2021 - November 10, 2021



    Publication date :

    2022-04-21


    Size :

    14 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    A spatiotemporal stochastic climate model for benchmarking causal discovery methods for teleconnections

    Tibau Alberdi, Xavier Andoni / Reimers, Christian / Gerhardus, Andreas et al. | German Aerospace Center (DLR) | 2022

    Free access



    Evaluating NWS Precipitation Type Forecasts

    Erickson, M. C. / American Meteorological Society | British Library Conference Proceedings | 1995


    A stepwise-cluster forecasting approach for monthly streamflows based on climate teleconnections

    Fan, Y. R. / Huang, W. / Huang, G. H. et al. | British Library Online Contents | 2015