Forecasting maximum and minimum temperature over airports with special relevance to aviation in flight planning

Abstract

Forecasting of maximum temperature and minimum temperature for aviation and non-aviation purpose has been attempted through auto regression and by employing the method of adaptive filtering and Kalman filtering during the hot weather season (March to May) over Madras. The filtering techniques have been outlined and the results are compared with the method of climatology and persistence. The Kalman filter using the model output of adaptive filtering. forecasts well the day-to-day variability of maximum and minimum temperature during hot weather season over Madras with an efficiency close to 90%. As the model performs reasonably well over Madras. a coastal station. the same has been tried over Trichy (300 km southwest of Madras), an inland airport station in Tamilnadu to ascertain its efficacy. The efficiency is better than 90% in predicting maximum and minimum temperature within an accuracy of 2°C).