Detection and attribution of climate change signals in South India maximum and minimum temperatures

Abstract

South India has seen significant changes in climate. Previous studies have shown that the southern part of India is more susceptible to effects of climate change than the rest of the country. We performed a rigorous climate model-based detection and attribution analysis to determine the root cause of the recent changes in climate over South India using fingerprint analysis. A modified Mann-Kendall test signalized non-stationariness in maximum and minimum temperatures (T-max and T-min) in most seasons during the period 1950-2012. The diminishing cloud cover trend may have induced significant changes in temperature during the considered time period. Significant downward trends in relative humidity during most seasons could be evidence of the recent significant warming. The observed seasonal T-max and T-min change patterns are strongly associated with the El Nino Southern Oscillation. Significant positive associations between South India temperatures and the Nino3.4 index were found in all seasons. The fingerprint approach indicated that the natural internal variability obtained from 14 climate model control simulations could not explain these significant changes in T-max (post-monsoon) and T-min (pre-monsoon and monsoon) in South India. Moreover, an experiment simulating natural external forcings (solar and volcanic) did not coincide with the observed signal strength. The dominant external factors leading to climate change are greenhouse gases, and their impact is eminent compared to other factors such as land use change and anthropogenic aerosols. Anthropogenic signals are identifiable in observed changes in T-max and T-min, of South India, and these changes can be explained only when anthropogenic forcing is involved.