Oceanography and Atmospheric Sciences and Meteorology Commons^™

Application Of Recurrent Neural Networks For Drought Projections In California, J. A. Le, Hesham El-Askary, Mohamed Allali, Daniele C. Struppa

Mathematics, Physics, and Computer Science Faculty Articles and Research

We use recurrent neural networks (RNNs) to investigate the complex interactions between the long-term trend in dryness and a projected, short but intense, period of wetness due to the 2015-2016 El Niño. Although it was forecasted that this El Niño season would bring significant rainfall to the region, our long-term projections of the Palmer Z Index (PZI) showed a continuing drought trend, contrasting with the 1998-1999 El Niño event. RNN training considered PZI data during 1896-2006 that was validated against the 2006-2015 period to evaluate the potential of extreme precipitation forecast. We achieved a statistically significant correlation of 0.610 between …