The National Centre for Environmental Prediction (NCEP) Climate Forecast System (CFS) is being used for operational monsoon prediction over the Indian region. Recent studies indicate that the moist convective process in CFS is one of the major sources of uncertainty in monsoon predictions. In this study, the existing simple cloud microphysics of CFS is replaced by the six‐class Weather Research Forecasting (WRF) single moment (WSM6) microphysical scheme. Additionally, a revised convective parameterization is employed to improve the performance of the model in simulating the boreal summer mean climate and intraseasonal variability over the Indian summer monsoon (ISM) region. The revised version of the model (CFSCR) exhibits a potential to improve shortcomings in the seasonal mean precipitation distribution relative to the standard CFS (CTRL), especially over the ISM region. Consistently, notable improvements are also evident in other observed ISM characteristics. These improvements are found to be associated with a better simulation of spatial and vertical distributions of cloud hydrometeors in CFSCR. A reasonable representation of the subgrid‐scale convective parameterization along with cloud hydrometeors helps to improve the convective and large‐scale precipitation distribution in the model. As a consequence, the simulated low‐frequency boreal summer intraseasonal oscillation (BSISO) exhibits realistic propagation and the observed northwest‐southeast rainband is well reproduced in CFSCR. Additionally, both the high and low‐frequency BSISOs are better captured in CFSCR. The improvement of low and high‐frequency BSISOs in CFSCR is shown to be related to a realistic phase relationship of clouds.

The impact of modified fractional conversion parameter (from cloud condensate to precipitation) in the revised simplified Arakawa‐Schubert (RSAS) convection scheme in Climate Forecast System version 2 on the simulation of Indian summer monsoon (ISM) is examined. While the default fractional conversion parameter is constant in RSAS, the modified parameter has the form of an exponential function of temperature above the freezing level, whereas below the freezing, level it is kept constant. The model simulation indicates RSAS with modified conversion parameter (RSAS_mod) shows a better fidelity in capturing the mean monsoon features over the ISM region. The spatial distribution of precipitation shows notable improvement over the ISM region. Most of the global general circulation models has a tendency to grossly overestimate (underestimate) the convective (large‐scale) rainfall over the ISM region, which has somewhat improved in RSAS_mod simulation. It is suggested that reduced rate of conversion of cloud condensate to convective precipitation above the freezing level leads to suppression of convective precipitation, which further increases the detrained moisture from the upper‐level, resulting enhancement in large‐scale precipitation. Further, improvement has been noted in outgoing longwave radiation, wind circulation, total cloud fraction, and dynamical and thermodynamical processes in RSAS_mod simulation. The modified conversion parameter helps in improving the feedback between moisture and convective processes through better lower tropospheric moistening. In addition to mean summer monsoon, the RSAS_mod indicates its potential in predicting an extreme rainfall event over Mumbai in high‐resolution global forecast system at T1534 horizontal resolution. However, its fidelity needs to be further tested for more number of heavy rainfall events.

We present a symbolic testing tool BEST for finding atomicity violations. We automatically infer and generate potential atomicity properties from an observed run of a multi-threaded program, and use precise modeling and constraint-based symbolic search to find atomicity violating schedules in the most generalization of the observed run. We focus mainly on the tool scalability by devising various simplification steps to reduce the formula and the search space by orders-of-magnitude. To that effect, we also introduce a new notion of atomicity that is useful and simple to check. We demonstrate the effectiveness of the combined techniques on several public C/C++/Java benchmarks in finding known/unknown atomicity bugs.