Identification of Drought Occurrences Using Ensemble Predictions up to 20-Days in Advance

Abstract

In the present study, skill of an extended range forecast system has been evaluated for identifying droughts over central India 20-days in advance. Rainfall forecasts from 44 ensemble members of the forecast system developed Indian Institute of Tropical Meteorology (IITM), Pune have been used to prepare probabilistic rainfall forecasts. It is seen that the uncertainties in the forecasts (in terms of ensemble spread) increases from day-5 to day 20. As the focus of the study is for drought predictions, forecasts in the bins 0-5 mm/5 day and 5-25 mm/5 day (no rain or less rain) were studied in detail. It is found that the modeling system has a tendency to over-forecast rainfall probabilities. With bias correction, the forecasts become more reliable. Various drought indices were computed using the mean of the forecast distribution up to 20-days in advance. Standardized precipitation index (SPI) computed using Gamma and Pearson type-III distributions are similar in the study region. It was found that these are in reasonable agreement with those from observations. Probabilistic forecasts of standardized precipitation index (SPI) were made and the relative operating characteristics (ROC) scores indicate that the forecasted SPI values are suitable for application.