In this study, the impact of enhanced anthropogenic greenhouse gas emissions on the possible future changes in different aspects of daily-to-interannual variability of Indian summer monsoon (ISM) is systematically assessed using 20 coupled models participated in the Coupled Model Inter-comparison Project Phase 5. The historical (1951-1999) and future (2051-2099) simulations under the strongest Representative Concentration Pathway have been analyzed for this purpose. A few reliable models are selected based on their competence in simulating the basic features of present-climate ISM variability. The robust and consistent projections across the selected models suggest substantial changes in the ISM variability by the end of 21 st century indicating strong sensitivity of ISM to global warming. On the seasonal scale, the all-India summer monsoon mean rainfall is likely to increase moderately in future, primarily governed by enhanced thermodynamic conditions due to atmospheric warming, but slightly offset by weakened large scale monsoon circulation. It is projected that the rainfall magnitude will increase over core monsoon zone in future climate, along with lengthening of the season due to late withdrawal. On interannual timescales, it is speculated that severity and frequency of both strong monsoon (SM) and weak monsoon (WM) might increase noticeably in future climate. Substantial changes in the daily variability of ISM are also projected, which are largely associated with the increase in heavy rainfall events and decrease in both low rain-rate and number of wet days during future monsoon. On the subseasonal scale, the model projections depict considerable amplification of higher frequency (below 30day mode) components; although the dominant northward propagating 30-70 day mode of monsoon intraseasonal oscillations may not change appreciably in a warmer climate. It is speculated that the enhanced high frequency mode of monsoon ISOs due to increased GHG induced warming may notably modulate the ISM rainfall in future climate. Both extreme wet and dry episodes are likely to ACCEPTED MANUSCRIPT 3 intensify and regionally extend in future climate with enhanced propensity of short active and long break spells. The SM (WM) could also be more wet (dry) in future due to the increment in longer active (break) spells. However, future changes in the spatial pattern during active/break phase of SM and WM are geographically inconsistent among the models. The results point out the growing climate-related vulnerability over Indian subcontinent, and further suggest the requisite of profound adaptation measures and better policy making in future.
Improved understanding of underlying mechanism responsible for Indian summer monsoon (ISM) droughts is important due to their profound socio-economic impact over the region. While some droughts are associated with 'external forcing' such as the El-Niño and Southern Oscillation (ENSO), many ISM droughts are not related to any known 'external forcing'. Here, we unravel a fundamental dynamic process responsible for droughts arising not only from external forcing but also those associated with internal dynamics. We show that most ISM droughts are associated with at least one very long break (VLB; breaks with duration of more than 10 days) and that the processes responsible for VLBs may also be the mechanism responsible for ISM droughts. Our analysis also reveals that all extended monsoon breaks (whether co-occurred with El-Niño or not) are associated with an eastward propagating Madden-Julian Oscillation (MJO) in the equatorial Indian Ocean and western Pacific extending to the dateline and westward propagating Rossby waves between 10°and 25°N. The divergent Rossby wave associated with the dry phase of equatorial convection propagates westward towards Indian land, couple with the northward propagating dry phase and leads to the sustenance of breaks. Thus, the propensity of eastward propagating MJO during boreal summer is largely the cause of monsoon droughts. While short breaks are not accompanied by westerly wind events (WWE) over equatorial western Pacific favorable for initiating air-sea interaction, all VLBs are accompanied by sustained WWE. The WWEs associated with all VLB during 1975-2005 initiate air-sea interaction on intraseasonal time scale, extend the warm pool eastward allowing the convectively coupled MJO to propagate further eastward and thereby sustaining the divergent circulation over India and the monsoon break. The ocean-atmosphere coupling on interannual time scale (such as El-Niño) can also produce VLB, but not necessary.
In spite of the summer monsoon’s importance in determining the life and economy of an agriculture-dependent country like India, committed efforts toward improving its prediction and simulation have been limited. Hence, a focused mission mode program Monsoon Mission (MM) was founded in 2012 to spur progress in this direction. This article explains the efforts made by the Earth System Science Organization (ESSO), Ministry of Earth Sciences (MoES), Government of India, in implementing MM to develop a dynamical prediction framework to improve monsoon prediction. Climate Forecast System, version 2 (CFSv2), and the Met Office Unified Model (UM) were chosen as the base models. The efforts in this program have resulted in 1) unparalleled skill of 0.63 for seasonal prediction of the Indian monsoon (for the period 1981–2010) in a high-resolution (∼38 km) seasonal prediction system, relative to present-generation seasonal prediction models; 2) extended-range predictions by a CFS-based grand multimodel ensemble (MME) prediction system; and 3) a gain of 2-day lead time from very high-resolution (12.5 km) Global Forecast System (GFS)-based short-range predictions up to 10 days. These prediction skills are on par with other global leading weather and climate centers, and are better in some areas. Several developmental activities like coupled data assimilation, changes in convective parameterization, cloud microphysics schemes, and parameterization of land surface processes (including snow and sea ice) led to the improvements such as reducing the strong model biases in the Indian summer monsoon simulation and elsewhere in the tropics.
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