Modeling of extreme events and its dynamic behavior have always been an intriguing topic. Increase in the magnitude and frequency of extreme events has widely been reported in recent decades, which is attributed to abrupt changes in climate. Numerous studies on extreme Indian monsoon characteristics, using a coarse‐resolution data set, have pointed out significant changes in heavy precipitation pattern over India. However, these studies differ in their conclusions, emphasizing the need for a fine‐resolution analysis. The present study aims to analyze the spatiotemporal variations and trends in the extreme (wet and dry) Indian monsoon precipitation, using 0.25° × 0.25° high‐resolution gridded data for a period of 113 years (1901–2013). Significant increase in the maximum intensity of rainfall and spatial heterogeneity is observed over the past half century. In addition, significant negative trends in wet spell durations and positive trends in dry spell durations are observed over wet regions; whereas contrasting trends are observed over dry regions. A shift in the frequency distribution of extreme events during the monsoon period is also noticed. The 50 year return level of maximum intensity clearly shows positive trends over the past century. Though characteristics of extremes are observed to be highly localized, apparent signs of wet regions turning drier and dry regions turning wetter are obtained. A comprehensive insight into different characteristics (intensity, spell, onset, and frequency) of Indian monsoon extremes is provided, which will help in effective water resources management and flood/drought hazard preparedness.

Various reanalyses have been utilized in numerous climate related researches around the globe, however, there exists considerable biasedness in these products, especially in precipitation and temperature data. The ability of these reanalysis products to simulate the precipitation and temperature patterns is observed to be satisfactory at global scale, while it differs significantly at regional scale, especially over regions of high spatio-temporal heterogeneity such as India. Therefore, it is essential to evaluate the applicability and robustness of reanalyses in climate related research. The annual and seasonal variability in spatiotemporal patterns and trends of precipitation and temperature data, with respect to the IMD gridded data over 34 yrs, are evaluated for six global reanalyses namely, NCEP/NCAR Reanalysis (NCEP R1), NCEP-DOE AMIP-2 Reanalysis (NCEP R2), Climate Forecast System Reanalysis (CFSR), ECMWF Interim Reanalysis (ERA-Interim), Modern Era Retrospective Analysis for Research and Application Land only model (MERRA-Land) and JMA 55-year Reanalysis (JRA-55). The ability of the reanalyses was tested based on several factors such as statistical and categorical indices, spells and trends, for annual and seasonal daily values. Several regional and seasonal differences were observed, particularly over high rainfall regions such as Western Ghats and northeastern India. MERRA-Land is found to give the best results for precipitation over India, which is attributed to the updated forcing data using gauge-based precipitation observations. Similarly, ERA-Interim and JRA-55 exhibit better performance for temperature than other datasets. All reanalyses failed to correctly reproduce the trends in IMD data, for both precipitation and temperature. These observations will provide a better perception on the reliability and applicability of reanalyses for climate and hydrological studies over India.

Understanding the evolution of Diurnal Temperature Range (DTR), which has contradicting global and regional trends, is crucial because it influences environmental and human health. Here, we analyse the regional evolution of DTR trend over different climatic zones in India using a non-stationary approach known as the Multidimensional Ensemble Empirical Mode Decomposition (MEEMD) method, to explore the generalized influence of regional climate on DTR, if any. We report a 0.36 °C increase in overall mean of DTR till 1980, however, the rate has declined since then. Further, arid deserts and warm-temperate grasslands exhibit negative DTR trends, while the west coast and sub-tropical forest in the north-east show positive trends. This transition predominantly begins with a 0.5 °C increase from the west coast and spreads with an increase of 0.25 °C per decade. These changes are more pronounced during winter and post-monsoon, especially in the arid desert and warm-temperate grasslands, the DTR decreased up to 2 °C, where the rate of increase in minimum temperature is higher than the maximum temperature. We conclude that both maximum and minimum temperature increase in response to the global climate change, however, their rates of increase are highly local and depend on the underlying climatic zone.

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