Homogenizing Monthly Rainfall and Temperature Data Series in Maharashtra & Goa

Abstract

Annual rainfall and temperature data series of all climate stations in Maharashtra & Goa are statistically tested for data homogeneity. To inspect homogeneity of a station, a two-step approach is followed. First, four homogeneity tests Standard normal homogeneity test, Pettit’s test, Buishand’s range test and Von Neumann ration test at 5% level of significance are used to determine test hypothesis for homogeneity on testing parameters of annual rainfall and temperature. Second, results from all these four tests aggregated together into three different classes as ‘useful’, ‘doubtful’ and ‘suspect’. Here 30 rainfall, 29 maximum and minimum temperature climate stations were tested. The results showed 80% stations as ‘useful’, 7% as ‘suspect’ and 13% as ‘doubtful’ for rainfall, for maximum temperature series these results are 17% as ‘useful’, 7% as ‘suspect’ and 76% as ‘doubtful’, while for minimum temperature series these results are 21% as ‘useful’, 10% as ‘suspect’ and 69% as ‘doubtful’. Further, in this study an attempt is also made to correct the monthly rainfall and temperature data series for homogeneity. Stations categorised as ‘useful’ are used as reference series to remove inhomogeneities from ‘suspect’ and ‘doubtful’ stations. To correct rainfall series ratio’s method is used while for temperature series addition method is used. Correction results showed significant improvement in ‘suspect’ category stations. After correction of inhomogeneous series, the results shows all 100% of rainfall stations and more than 65% of temperature stations are now in ‘useful’ category. The corrected stations may be included in further climate research studies.