Trends in Precipitation Extremes over India - (IMD), Pune

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From the list prescribed by WMO, we have not considered indices of R10mmand R20mm, because rainfall events of 10 or 20 mm are quite common in the Indiansub-continent during the southwest monsoon season. Hence, we have consideredR7.5cm (75 mm) and R12.5cm (125mm) to study the trends in heavy precipitationfrequencies of rainfall greater than or equal to 7.5cm and 12.5cm.The definitions of indices allow seasonal and monthly partitions. As mentionedearlier, here, we have considered only the southwest monsoon season (June –September), the main rainy season in India. Most of the indices are defined in termsof counts of days crossing the thresholds either absolute (fixed) thresholds orpercentile (variable) thresholds. Annual or seasonal day-count indices based onpercentile thresholds are expressions of anomalies relative to the local climate.Consequently, the value of the thresholds is site specific. Such indices allow forspatial comparisons, because they sample same part of precipitation (probabilitydensity) distributions at each station. On the other hand, annual/seasonal day-countindices based on absolute thresholds are less suitable for spatial comparisons. Thereason being, over an area as large as India, thresholds of sample may vary differentfor different parts of the precipitation distributions. This means that in another climateregime the variability in such indices readily stems from another season. Forexample, R7.5cm may be an extreme event in North-west India, while such eventsare quite common along the west coast and NE India.Extreme rainfall indices considered for the analysis are calculated for eachyear for each station. Trends of these indices are calculated using linear regressionmodel to calculate the magnitude of the trends. Since most of the indices are countsof days, a non-parametric model will be the best suited to test the significance ratherthan using Students’ t test. Hence, we have used the Kendall -Tau test (Press et al.,1986) to examine the significance of the trend. The trends referred to as significantexceed the 95% or 99% confidence limits in the Kendall–Tau test. As mentionedearlier, missing data was not filled up while calculating the indices and trends.6
3. Results and DiscussionsWe have calculated the trends of 16 indices for monsoon season and onannual scale and estimated the statistical significance using the Kendal-Tau test. Forthe present study, results and discussions are presented for the monsoon season inrespect of the indices listed in Table-1. However, the trends with the annual data arealso found similar. Table – 2 shows the percentage of stations showing significanttrends in each index. The details of the trends in extreme indices are given below.Significant trend values are plotted in Figs 2-6 and magnitude of the trends perdecade are listed in Table-3.R7.5cm – Number of days with rainfall 7.5cm or moreFor the monsoon season, 63% of stations did not show any trend. 17% of thestations have shown positive significant trends. The significant positive trends areobserved (Fig. 2a) mainly along the west coast and some parts of central India andover Bihar. Higher values of trends are observed over stations of northern parts ofwest-coast. However, Mahabaleshwar has shown a significant negative trend innumber of days with 7.5cm or more.R12.5cm – Number of days with rainfall 12.5cm or moreWest coast stations and two stations of foothills of Himalayas have significantpositive trends (Fig. 2b) during the monsoon season. Similar to R7.5cm,Mahabaleshwar has shown a significant negative trend in number of days with12.5cm or more.RX1day – Highest one day total and RX5day – highest 5 day totalOut of the 100 stations, 73% of the stations during the monsoon season haveshown positive trend. However, the trends at only 15% of stations are statisticallysignificant. These stations (Fig. 2c) are mainly along the west coast of India, parts ofcentral India, northern parts of peninsular India and few stations in West Bengal and7
Page 1 and 2: OCTOBER2006NCC3NCC RESEARCH REPORTT
Page 3 and 4: AbstractOne of the most significant
Page 5 and 6: et al. 2001; Kunkel 2003). Signific
Page 7: In section 2, details of data used
Page 11 and 12: Regional Average TrendsIn the time
Page 13 and 14: translate into a huge increase in s
Page 15 and 16: Houghton Jr, Ding Y, Griggs Dj, Nog
Page 17 and 18: Table - 1Extreme Rainfall Indices c
Page 19 and 20: Table - 4Rainfall Indices (1901-200
Page 21 and 22: abcd- Significant Positive Trends -
Page 23 and 24: ab- Significant Positive Trends - S
Page 25 and 26: Rainfall in mm200150100500Rainfall
Page 27: N C C RESEARCH REPORTS New statisti

Trends in Precipitation Extremes over India - (IMD), Pune

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