Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5) are unable to resolve the spatial and temporal characteristics of the South Asian Monsoon satisfactorily. A CGCM with the capability to reliably project the global as well as the regional climatic features would be a valuable tool for scientists and policymakers. Analysis of 28 CMIP5 models highlights varying degree of biases in precipitation and 2 m surface air temperature (T2m) over south Asia, and the Community Earth System Model (CESM) developed at the National Center for Atmospheric Research is found to be one of the best performing models. However, like all other CMIP5 models, CESM also has some inherent model biases. Using CESM, it is found that the precipitation and T2M biases reduce with increase in the model horizontal resolution from 2° to 0.5°. Further, a few deep convective parameters in the Zhang-McFarlane convection scheme are tuned for 2° and 1° model resolutions using both manual and semi-automatic model tuning methods. Comparing results from the two tuning methods we find that the performance of the manually tuned model is better than that of the semi-automated one.

Using all ensemble members of NCAR CCSM4 for historical natural, RCP4.5 and RCP8.5 scenarios from CMIP5, we analyse changes in mean and extreme precipitation over the south Asian region for every 0.5 o C increase in global warming. An increase in mean annual precipitation is projected over majority of the south Asian region with increased levels of warming. Over Indian land, the spatiallyaveraged annual mean precipitation shows an increase in the range of~2-14 % based on the RCP scenario and level of warming. However, a decrease in mean annual precipitation is projected over northwest parts of the Indian sub-continent and the equatorial Indian Ocean with increased levels of warming. In general, we find multifold increase in the frequency of occurrence of daily precipitation extremes over the Indian subcontinent and surrounding oceans. Over Indian land, frequency of occurrence of daily precipitation extremes show up to three-fold increase under both RCP scenarios for global warming levels in the range of 1.5 o C-2.5 o C. With further increase in warming we find that the frequency of occurrence of daily precipitation extremes could show a massive four-to six-fold increase over majority of Indian land. Notably, unlike the projected increase in the frequency of occurrence of daily precipitation extremes, the projected change in annual mean precipitation is found to be insignificant in a 1.5 o C warmer world, over majority of the south Asian region, under both RCP scenarios. Given the projected large increase in frequency of daily precipitation extremes with increased levels of warming, our study provides scientific support to the recommendations of the Paris Agreement of 2015.

The response of the Indian Summer Monsoon (ISM) to global warming, solar geoengineering and its termination is examined using the multi-model mean of seven global climate model simulations from G2 experiment of the Geoengineering Model Intercomparison Project. Under the global warming scenario, land–ocean temperature contrasts and low-level monsoon circulation progressively strengthen accompanied by enhanced precipitation over the Indian subcontinent. Notably, in the solar geoengineered scenario, marginal surface cooling is projected over the majority of the ISM region, and there is strengthening of both upper and lower level circulation. However, preferential precipitation near Western Ghats leads to dry bias over majority of Indian land. Upon the termination of the geoengineering, the climatic conditions—temperature, precipitation, winds and moisture would abruptly change to what it would have been under the global warming scenario. Thus, this may be important to note that such changes may need attention for the future mitigation and adaptation purposes if solar geoengineering is required to implement in future.

Nor’wester studies have a long history of climatological, synoptic and radar observations. These studies have been briefly mentioned and the field programs for the study of Nor’westers implemented in India Meteorological Department (IMD) from 1931-1941 have been touched upon. Indian atmospheric science community organized a multi-year STORM program during 2007-2010 to understand the formation of these severe local storms and also understand their dynamics through modeling. An attempt is made to use INSAT Infrared and Visible imageries to document the convective cells which developed over Eastern and North-East (NE) Indian states and adjoining countries of Bangladesh, Bhutan and Nepal for the year 2009. Also convective cells which organized themselves into Mesoscale Convective Complexes (MCCs) for the four years period 2007-2010 have been studied. It is found that by and large Eastern India (Jharkhand, Orissa, Sub Himalayan West Bengal and Bangladesh) is responsible for the initiation of convection. Development occurs as the cells propagate over the neighbouring areas of Bangladesh and NE India. Important observations with regard to initiation, maturity and dissipation etc. of the MCCs are provided. It is suggested that half hourly to hourly monitoring of convection can be accomplished by using INSAT imagery, along with multiple overlapping radar coverages, which could help in nowcasting of convective cells. Synoptic and thermodynamic forcing can help as broad guidance. The only effective way for effective warning is nowcasting using satellite and multiple radar coverage.

The tendency of convective rainfall to initiate over a wetter or drier land surface is a critical feedback process in the climate system, influencing the hydrological cycle on a variety of spatial scales, especially in parts of the world where water is limited. A simple algebraic solution is derived from fundamental physical equations, to predict the sign of this convective rainfall feedback with the surface. The tendency for convection to occur is evaluated by the rate at which the convective boundary‐layer top approaches the level of free convection. Well‐known integral models predict the rate of ascent of the boundary‐layer top, which tends to be faster over a dry surface. The associated changes in equivalent potential temperature in the boundary layer determine the rate at which the level of free convection descends, typically faster over a wet surface, as a function of the ambient profile, the thermodynamic forcing and the surface Bowen ratio. The resulting system is controlled by three parameters. Two nondimensional parameters determine whether there is wet or dry “advantage”; the Bowen ratio at the boundary‐layer top and a “convective instability parameter,” defined as the ratio of the vertical gradient of saturated equivalent potential temperature at the level of free convection to the profile stability just above the boundary layer. A dimensional function, dependent on the surface fluxes, the boundary‐layer depth, and the profile stability, provides the magnitude of the response. In comparison with previous work, the solution is both rigorously derived from physical principles and encapsulated in a simple algebraic form. A first evaluation of the theoretical framework has been made using data from a convection‐permitting numerical model simulation over India, and this indicates that the equations successfully determine the conditions under which convection is triggered over dry surfaces.

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The WRF model forecast during monsoon season 2010 has been verified with daily observed gridded rainfall analysis with 0.5° spatial resolution. Firstly, the conventional neighborhood technique has been deployed to calculate common scores like mean error and root mean square error. Along with, widely used two categorical skill scores have been computed for seven different rainfall thresholds. The scores only found the general nature of the model performance and depicted the degradation of forecast accuracy exceeding moderate rainfall category of 7.5 mm. The object oriented Contiguous Rain Area method also has been considered for the verification of rainfall forecasts to gather more information about model performance. The method similarly has endorsed that the performance of the model degrades along with the increase in rainfall amount. But at the same time, the decomposition of mean square error has pointed out that the maximum error occurred due the shifting of rain object or event in the forecast compared to observation. The volume error contributes less as compared to pattern error in 24 hour forecasts irrespective of rainfall thresholds. But in 48 hour forecasts, their values are comparable and change along with rainfall threshold. During whole monsoon season, all contiguous rain areas in model forecasts have been searched over observed rainfall analyses applying best-fit criteria. For contiguous rain areas below 50 mm more than 70 percent match was found.

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