Prediction of summer rainfall over the source region of the Blue Nile by using teleconnections based on sea surface temperatures

  • Asmaa Alhamshry
  • Ayele Almaw Fenta
  • Hiroshi YasudaEmail author
  • Katsuyuki Shimizu
  • Takayuki Kawai
Original Paper


Summer rainfall (June–September) accounts for about 80% of the annual rainfall in the Lake Tana basin of Ethiopia, the source region of the Blue Nile River. Prediction of summer rainfall would be valuable for managing the region’s water resources and agricultural operations. This study investigated the influence of sea surface temperature (SST) as a predictor of summer rainfall in the basin by applying cross-correlation analysis between summer rainfall and climatic indices and SST in various oceanic regions from 1985 to 2015. Summer rainfall showed a strong negative correlation (− 0.619) with the Pacific Decadal Oscillation index at short time lags. Further analysis identified strong teleconnections (|r| ≥ 0.5) between SSTs in specific parts of the Pacific Ocean and summer rainfall in the Lake Tana basin, raising the possibility of predicting summer rainfall from Pacific SSTs with a lead time of 4 to 5 months. Average SSTs of an area near the Philippines and an area west of North America were positively correlated (0.629) and negatively correlated (− 0.538), respectively, with summer rainfall in the Lake Tana basin. Predictions of summer rainfall from these teleconnected SSTs by an Elman recurrent neural network model were encouraging, indicating a strong correlation (r > 0.77) between the observed and predicted summer rainfall. Our results suggest that neural network techniques may have sufficient skill to support seasonal rainfall predictions over the Lake Tana basin.



We thank the Ethiopian National Meteorological Agency for providing the rain gauge data. Our data sources consisted of CHIRPS satellite rainfall data (, the CRU database (, and HadISST data from the British Atmospheric Data Center.

Funding information

We thank the Egypt-Japan Education Partnership for the Ph.D. research grant for the first author. This study was financially supported by the International Platform for Dryland Research and Education, Tottori University.


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Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2019

Authors and Affiliations

  • Asmaa Alhamshry
    • 1
    • 2
  • Ayele Almaw Fenta
    • 1
  • Hiroshi Yasuda
    • 1
    Email author
  • Katsuyuki Shimizu
    • 3
  • Takayuki Kawai
    • 1
  1. 1.Arid Land Research CenterTottori UniversityTottoriJapan
  2. 2.National Research CentreDokkiEgypt
  3. 3.Faculty of AgricultureTottori UniversityTottoriJapan

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