Spatiotemporal patterns in the mean and extreme temperature indices of India, 1971–2005 - Panda, D.K.; Mishra, Atmaram; Kumar, A.; Mandal, K.G.; Thakur, A.K.; Srivastava, R.C. (Wiley, 2014)
This study provides the comprehensive analysis of changes in mean and extreme temperature indices of India to assist the climate change mitigation and adaptation strategies and to add information for the global comparisons, using a high-resolution daily gridded temperature data set (1 ×1 ) during 1971–2005. In addition to the indices recommended by the World Meteorological Organization/CLIVAR Expert Team on Climate Change Detection and Indices, few more indices having social and agricultural implication are investigated at the seasonal and annual scales, utilizing widely adopted statistical methodologies in climate research. The results show, in general, a robust signal of warming, broadly consistent with what has been observed and predicted in other parts of the world in the context of global warming. The frequency and intensity of warm extremes, especially representing the daily minimum temperature, have increased with simultaneous decreases in cold extremes in large parts of the country, but the spatial distribution of the trend magnitude reflects the complex natural climatic settings of India and its possible interaction with the anthropogenic forcing. Seasonal analysis reveals a faster warming in day and night temperatures in winter affecting the major wheat crop. In summer, however, both human and ecosystems appear to be more vulnerable to the increasing tendency of the heatwave occurrences, particularly during night-time, since the 1990s. The relationship with the large-scale natural climatic modes indicates that the warming indices tend to increase in the year following the El Ni˜no events as evident from the correlation with the NINO3.4 index, with a relatively higher association in the monsoon season. Moreover, the concurrent correspondence of the summer heatwaves with the north Indian Ocean sea surface temperature suggests a degree of predictability of the heat stress episode.