Prediction of occurrence and quantity of daily summer monsoon precipitation over Orissa (India)

Abstract

The precipitation over Orissa State, a meteorological subdivision on the east coast of India, shows large-scale spatio-temporal variation caused by the interaction of the basic monsoon flow with the monsoon disturbances over the Bay of Bengal and the orography owing to the Eastern Ghats and other hill peaks in Orissa and its neighbourhood. Hence, it is difficult to predict daily precipitation over Orissa. The objective of this study is to predict the occurrence and quantity of precipitation 24 h ahead, over specific locations of Orissa during the summer monsoon season (June-September). For this purpose, a probability of precipitation (PoP) model has been developed by applying stepwise regression with the available surface and upper air parameters from synoptic and radiosonde and radio wind stations in and around Orissa as potential predictors. The parameters selected through stepwise regression for the PoP model have been used to develop a probabilistic model for a Quantitative Precipitation Forecast (QPF) in different ranges, such as 0.1-10, 11-25, 26-50, 51-100 and >100 mm, using Multiple Discriminant Analysis (MDA). Both the PoP and QPF models have been developed based on data from 1980 to 1994 and verified with the data from 1995 to 1998. Considering six representative stations for six homogeneous regions in Orissa, the PoP model performs very well with percentages of correct forecast for occurrence/non-occurrence of precipitation being about 73 and 65% respectively for developmental and independent data. However, the skill score of the MDA model for categorical forecast is poor, especially for higher values of precipitation.