Impacts of climate change on Indian Summer Monsoon Rainfall (ISMR) and the growing population pose a major threat to water and food security in India. Adapting to such changes needs reliable projections of ISMR by general circulation models. Here we find that, majority of new generation climate models from Coupled Model Intercomparison Project phase5 (CMIP5) fail to simulate the post-1950 decreasing trend of ISMR. The weakening of monsoon is associated with the warming of Southern Indian Ocean and strengthening of cyclonic formation in the tropical western Pacific Ocean. We also find that these large-scale changes are not captured by CMIP5 models, with few exceptions, which is the reason of this failure. Proper representation of these highlighted geophysical processes in next generation models may improve the reliability of ISMR projections. Our results also alert the water resource planners to evaluate the CMIP5 models before using them for adaptation strategies.

We show that 21st century increase in radiative forcing does not significantly impact the frequency of South Asian summer monsoon depressions (MDs) or their trajectories in the Coupled Model Intercomparison Project Phase 5 general circulation models (GCMs). A significant relationship exists between the climatological occurrences of MDs and the strength of the background upper (lower) tropospheric meridional (zonal) winds and tropospheric moisture in the core genesis region of MDs. Likewise, there is a strong relationship between the strength of the meridional tropospheric temperature gradient in the GCMs and the trajectories of MDs over land. While monsoon dynamics progressively weakens in the future, atmospheric moisture exhibits a strong increase, limiting the impact of changes in dynamics on the frequency of MDs. Moreover, the weakening of meridional tropospheric temperature gradient in the future is substantially weaker than its inherent underestimation in the GCMs. Our results also indicate that future increases in the extreme wet events are dominated by nondepression day occurrences, which may render the monsoon extremes less predictable in the future.

A robust understanding of the sub-seasonal cold season (November–March) precipitation variability over the High Mountains of Asia (HMA) is lacking. Here, we identify dynamic and thermodynamic pathways through which natural modes of climate variability establish their teleconnections over the HMA. First, we identify evaporative sources that contribute to the cold season precipitation over the HMA and surrounding areas. The predominant moisture contribution comes from the mid-latitude regions, including the Mediterranean/Caspian Seas and Mediterranean land. Second, we establish that several tropical and extratropical forcings display a sub-seasonally fluctuating influence on precipitation distribution over the region during the cold season. Many of them varyingly interact, so their impacts cannot be explained independently or at seasonal timescales. Lastly, a single set of evaporative sources is not identifiable as the key determinant in propagating a remote teleconnection because the sources of moisture anomalies depend on the pattern of sub-seasonally varying dynamical forcing in the atmosphere.

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Literature found that the increasing concentration of Anthropogenic Aerosol (AA) is the key reason behind the weakening trend of Indian Summer Monsoon Rainfall (ISMR), based on the Coupled Model Intercomparison Project Phase5 (CMIP5) simulations with AA-only forcing. Here, we reexamine and find that AA-only simulations show country-wide drying, in contrast to the observed east-west asymmetry in the recent ISMR trend. For further evaluation, we decompose the changes in moisture convergence during summer monsoon into dynamic and thermodynamic components. We find that multi-run ensemble averages for individual CMIP5 models do not capture the observed dominance of the changes in dynamic component over the thermodynamic one. An optimal fingerprinting technique for detection and attribution also fail to attribute the changes in ISMR to AA, either because of large internal variability and/or intermodel spread. This implies the need for more careful assessment of AA-only simulations for the ISMR before attributing the changes to AA.