Modeling and Prediction of the Daily Maximum Temperature

This correspondence examines the possibility of recursive prediction for the daily maximum temperature based on a state variable model. It is shown that past data can be processed for identifying a suitable noisy state model for this process. Once the model is selected the ``corrector-predictor´´ algorithm of Kalman is readily applied for predicting the daily maximum temperature for a chosen lead time. The method is illustrated by predicting the daily maximum temperature of Delhi, India.