Driver Drowsiness Detection

Abstract

India Meteorological Department has implemented state level medium range rainfall forecast system applying multi model ensemble technique, making use of model outputs of state-of-the-art global models from the five leading global NWP centers. The pre-assigned grid point weights on the basis of anomaly correlation coefficients (CC) between the observed values and forecast values are determined for each constituent model utilizing two season datasets and the multi model ensemble forecasts are generated at the same resolution on a real-time basis. The ensemble forecast fields are then used to prepare forecasts for each state, taking the average value of all grid points falling in a particular district. In this paper, we describe the development strategy of the technique and performance skill of the system during 15 years of rain fall at different states in india. The study demonstrates the potential of the system for predicting future rainfall forecasts for upcoming years and scale over Indian region. District wise performance of the ensemble rainfall forecast reveals that the technique, in general, is capable of providing reasonably good forecast skill over most states of the country, particularly over the states where the monsoon systems are more dominant.