Climate change has altered the characteristics and frequency of extreme precipitation and temperature. Characteristic analysis of extreme climate indices (ECI) is essential for the planning and management of water resources and disaster preparedness. This study performed the fractal characterization of ECIs over four Indian megacities of Mumbai, Guwahati, Cochi and Delhi of different climatic zones using multifractal detrended fluctuation analysis (MFDFA). Firstly, eight temperature indices and five precipitation indices of the cities are estimated from precipitation along with minimum and maximum temperature of 1951–2021 period collected at daily scale. The ECIs included the four percentile-based indices (Cool nights, Warm nights, Warm days, Cool days), seven absolute indices (R10 mm, R20 mm, PRCPTOT, TXx, TNn, Rx1day and Rx5day) and duration-based indices like number of summer days (SU) and tropical nights (TR). The scaling behaviour of different indices is found to be ranging between biweekly to seasonal scale of 3 months in different time series. The results showed that most of the percentile-based temperature indices deciphered long term persistence (Hurst exponent ranging between 0.55 to 0.92) and strong multifractality, irrespective of the city location, whereas rest of the temperature indices showed weak multifractality in all the cities. Precipitation indices are short-term persistent in character, which displayed multifractality only for the data of Delhi. Multifractal spectrum of majority of the climatic indices indicated a right asymmetry indicating high probability of high fluctuations, except for the city of Guwahati. TN90p series of all cities exhibited string multifractality, which is due to the predominance in wideness of probability density function.