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

Abstract

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.

Prediction of occurrence of daily summer monsoon precipitation over Karnataka

“…The station rainfall depends on various surface and upper air parameters (Mohanty and Mohapatra, 2007). However, the relationship varies with respect to the location of the rain gauge station due to the varied physiography of Karnataka.…”

“…Considering the importance of the daily rainfall prediction in various fields, a number of methods are used by forecasters. A review of the synoptic analogues developed by various authors for different regions of India for prediction of precipitation is given by Mohanty and Mohapatra (2007). The dynamical numerical models are used by many centres for predicting the rainfall and other weather elements, but these are highly dependent on the initial data, parameterization schemes and numerical techniques used for solving the governing equations.…”

“…Mohanty et al (2001) developed an objective technique to forecast POP over Delhi and provide the quantitative precipitation forecast (QPF) using a classical multivariate regression technique. Mohanty and Mohapatra (2007) have developed a statistical model for POP based on forward stepwise regression for Orissa State. Their results show that the POP model performs very well, with the percentage correct (PC) forecast as 73 and 65% respectively for the developmental and the independent data.…”

Chapter 24 A review of volcanic hazard and risk-assessment praxis at the Soufrière Hills Volcano, Montserrat from 1997 to 2011

“…Whilst attempting this in any authoritative way is beyond the scope of the present discussion, Hagedorn & Smith (2009) have proposed a basis for communicating the value of probabilistic (meteorological) forecasts using a gambling analogy they term 'weather roulette'. Applying their roulette betting formulation to the record of 110 separate forecasts from Montserrat that were testable post hoc, with individual forecast odds reflecting the likelihood of each outcome as anticipated by the SAC, a governor investing £1 on the SAC's selections from July 1995 onwards would have netted about £32 by October 2008 (Fig.…”

Comparative Study of Monsoon Rainfall Variability over India and the Odisha State

“…It is known that monsoons exhibit variability even on inter-decadal time scales in association with many other global climate variables. The complexities of the ISM have been studied by several authors emphasizing its spatial variability [1][2][3][4][5][6][7][8][9]. The spatial variability of ISM has also been studied by a few researchers [10][11][12].…”