In this paper an attempt has been made to develop a discrete precipitation model for the daily series of precipitation occurrences over North East India. The point of approach is to model the duration of consecutive dry and wet days i.e. spell, instead of individual wet and dry days. Various distributions viz. uniform, geometric, logarithmic, negative binomial, Poisson and Markov chain of order one and two, Eggenberger-Polya distribution have been fitted to describe the wet and dry spell frequencies of occurrences. The models are fitted to the observed data of seven stations namely Imphal, Mohanbari, Guwahati, Cherrapunji, Silcoorie, North Bank and Tocklai (Jorhat) of North-East India with pronounced attention to summer monsoon season. The goodness of fit of the proposed model has been tested using Kolmogorov-Smirnov test. It is observed that Eggenberger-Polya distribution fairly fits wet and dry spell frequencies and can be used in the future for an estimation of the wet and dry spells in the area under study.
Bruhn, J. A., Fry, W. E. and Fick, G. W. (1980). Simulation of daily weather data using theoretical probability distributions, J. of Appl. Met., 19 :1029-1036.
Dubrovsky, M. (1997). Creating Daily Weather Series With Use of the Weather Generator. Environmetrics, 8: 409-424.
Fisher, R. A. (1924). The influence of rainfall on the yield of wheat at Rothamsted. Phil.Trans. Roy. Stat. Soc. London. B, 213:89-142.
Gabriel. K. R. and Neumann, J. (1962). A Markov Chain model for daily occurrence at Tel Aviv, Quart. J.R. met. Soc., 88: 90-95.
Geng, S.(1986). A simple method for generating daily rainfall data. Agricultural and Forest Meteorology, 36:363-376.
Giuseppe, E. D., Vento, D., Epifani, C. and Esposito, S. (2005). Analysis of dry and wet spells from 1870 to 2000 in four Italian sites, Geophysical Research Abstracts, 7: 1-6.
Katz, R. W. (1974). Computing probabilities associated with the Markov chain model for precipitation, J. Appl. Meteorol., 13:953-954.
Massey, J. and Frank, J. (1951). The Kolmogorov test for goodness of fit. JASA, 46:68-78.
Matyasovszky, I. and Dobi, I. (1989). Methods for analysis of time series of precipitation data using Markov chains (in Hungarian) , IdoÃˆjaÃ‚raÃ‚s, 93: 276-288.
Medhi, J. (1976). A Markov Chain for the occurrence of wet and dry days, Ind. J. Met. Hydro. & Geophys. 27: 431-435.
Nobilis, F. (1986). Dry spells in the Alpine country Austria, J. Hydrol., 88: 235-251.
Pal, S. K.(1998). Statistics for Geoscientists: Techniques and Applications, Concept Publishing Company, New Delhi.
Racsko, P., Szeidl, L and Semenov, L.(1991). A serial approach to local stochastic weather models. Ecological Modelling, 57: 27-41.
Richardson, C. W.(1981). Stochastic simulation of daily precipitation, temperature, and solar radiation, Water Resources Research, 17: 182-190.
Tolika, K. and Maheras, P.(2005), Spatial and temporal characteristics of wet spells in Greece, Theor. Appl. Climatol. 81: 71â€“85.
Wilks, D.(1992). Adapting stochastic weather generation algorithm for climate change studies. Climate Change, 22: 67-84.
Wantuch, W., Mika, J. and Szeidl, L.(2000). Modelling Wet and Dry Spells with Mixture Distributions, Meteorology and Atmospheric Physics, 73: 245-256.
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