A Timely El Niño-Southern Oscillation Forecast Method Based on Daily Niño Index to Ensure Food Security

Abstract

The El Nino-Southern Oscillation (ENSO) is the Earth's dominant inter-annual climate fluctuation, often accompanied by extreme weathers. The occurrence of drought, flood, heavy rainfall, hurricanes, extreme cold, and so on, may cause significant crops yield reduction or even no crop. Therefore, a timely ENSO forecast is critical to global agricultural production and food safety. The current mainstream ENSO indexes are based on monthly or quarterly data without a strong timeliness. This paper proposes a new ENSO index, named as Daily Nino Index (DNI), to study the ENSO events in daily temporal scale. To the best of our knowledge, there is no previous study defining ENSO events in daily temporal scale. High correlations between NOAA daily Optimum Interpolation Sea Surface Temperature (OISST) data set and some popular monthly Sea Surface Temperature (SST) data sets show the feasibility of using daily data to study ENSO events. Nino 3.4 SST region is selected as the computational domain for DNI in order to maximize the ENSO signal among SST-based indexes to identify the El Nino and La Nina events. Comparisons are made between DNI and some other ENSO forecast indexes. Experiment results illustrate that DNI is highly correlated with other indexes and advances the forecast time two to three months earlier.