Uncertainty in calculating the spatial-and interannual variability of precipitation over India and Tibet from widely used gridded precipitation datasets is examined for the 29-year period from 1979 to 2007. Uncertainty is defined in terms of the spread among the variability calculated from multiple datasets, a useful method when multiple datasets of similar or unknown accuracy are available for analyses. The resulting uncertainty varies for regions and seasons. Geographical variations are clearly seen in the signal-to-noise ratio (SNR), with the largest uncertainty in the Jammu and Kashmir (J&K), western India-eastern Pakistan, Tibet, Hindu-Kush mountains, and Western Ghats which are characterized by either dry climate or complex terrain, or both. Seasonally, the uncertainty is larger for the December-February period (DJF) than for the June-September period (JJAS) in most of the region except J&K which is characterized by two wet seasons: winter and summer. The uncertainty in the interannual variability also varies according to regions especially in J&K where the calculated interannual variability varies by nearly a factor of two among the datasets. The uncertainty range in the calculated interannual variability is determined largely by two gauge-based data of the finest resolution, Asian Precipitation -Highly-Resolved Observational Data Integration Towards Evaluation of water resources (smallest) and India Meteorological Department (largest) in all regions.The regional and seasonal variations in the uncertainty do not appear to depend on either the spatial resolution or the length of records. This implies that analysis methodology such as the quality control of input data, spatial/temporal interpolation, and retrieval algorithms used in producing these gridded datasets plays a crucial role in determining the characteristics of precipitation climatology represented by individual datasets. Our results show that calculating precipitation characteristics must be accompanied by careful examinations of uncertainty among available datasets, especially for dry seasons and arid/mountainous regions.

Midtropospheric cyclones (MTCs) are a distinct class of synoptic disturbances, characterized by quasi-stationary cyclonic circulation in midtropospheric levels, which often produce heavy rainfall and floods over western India during the summer monsoon. This study presents a composite and diagnostic process study of long-lived (>5 days) midtropospheric cyclonic circulation events identified by the India Meteorological Department (IMD). Reanalysis data confirm earlier studies in revealing that the MTC composite has its strongest circulation in the midtroposphere. Lagged composites show that these events co-occur with broader-scale monsoon evolution, including larger synoptic-scale low pressure systems over the Bay of Bengal (BoB) and east coast, and the active phase of regional-scale poleward-propagating intraseasonal rain belts, with associated drying ahead (north) of the convectively active area. Diabatic heating composites, in particular the TRMM latent heating and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2)-derived radiative cooling in the dry inland areas of southwest Asia north of the rain belt, are used to drive a nonlinear multilayer dynamical model in a forced-damped reconstruction of the global circulation. Results show that the midlevel circulation is largely attributable to top-heavy latent heating, indicative of the prevalence of stratiform-type precipitation in mesoscale convective systems in these moist, active larger-scale settings. Both the west coast and BoB latent heating are important, while the radiative cooling over southwest Asia plays a modest role in sharpening some of the simulated features. A conceptual model encapsulates the paradigm based on this composite and diagnostic modeling, a diabatic update of early theoretical studies that emphasized hydrodynamic flow instabilities.

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Key Messages • The frequency and spatial extent of droughts over India have increased significantly during 1951-2015. An increase in drought severity is observed mainly over the central parts of India, including parts of Indo-Gangetic Plains (high confidence). These changes are consistent with the observed decline in the mean summer monsoon rainfall. • Increased frequency of localized heavy rainfall on sub-daily and daily timescales has enhanced flood risk over India (high confidence). Increased frequency and impacts of floods are also on the rise in urban areas. • Climate model projections indicate an increase in frequency, spatial extent and severity of droughts over India during the twenty-first century (medium confidence), while flood propensity is projected to increase over the major Himalayan river basins (e.g. Indus, Ganga and Brahmaputra) (high confidence).

Key Messages • Annual mean, maximum and minimum temperatures averaged over India during 1986-2015 show significant warming trend of 0.15°C, 0.15°C and 0.13°C per decade, respectively (high confidence), which is consistent with dendroclimatic studies. • Pre-monsoon temperatures displayed the highest warming trend followed by post-monsoon and monsoon seasons. • The frequency of warm extremes over India has increased during 1951-2015, with accelerated warming trends during the recent 30 year period 1986-2015 (high confidence). Significant warming is observed for the warmest day, warmest night and coldest night since 1986. • The CORDEX mean surface air temperature change over India for the mid-term (long-term) period 2040-2069 (2070-2099) relative to 1976-2005 is projected to be in the range of 1.39-2.70°C (1.33-4.44°C) across greenhouse gas warming scenarios. The ranges of these Indian mean temperature trends are broadly consistent with the CMIP5 based estimates. • The frequency and intensity of warm days and warm nights are projected to increase over India in the next decades, while that of cold days and cold nights will decrease (high confidence). These changes will be more pronounced for cold nights and warm nights. • The pre-monsoon season heatwave frequency, duration, intensity and areal coverage over India are projected to substantially increase during the twenty-first century (high confidence).