This study characterizes biases in water vapor, dynamics, shortwave (SW) and longwave (LW) radiative properties in contemporary global climate models (GCMs) against observations over tropical Pacific Ocean. The observations are based on Atmospheric Infrared Sounder for water vapor, CloudSat 2B‐FLXHR‐LIDAR for LW and SW radiative heating profiles, and radiative flux from Clouds and the Earth's Radiant Energy System products. The model radiative heating profiles are adopted from the coupled and uncoupled National Center for Atmospheric Research (NCAR) Community Earth System Model version 1 (CESM1) and joint Year of Tropical Convection (YOTC)/Madden Julian Oscillation (MJO) Task Force‐Global Energy and Water Cycle Experiment Atmospheric System Studies (GASS) Multi‐Model Physical Processes Experiment (YOTC‐GASS). The results from the model evaluation for YOTC‐GASS and NCAR CESM1 demonstrate a number of systematic radiative biases. These biases include excessive outgoing LW radiation and excessive SW surface radiative fluxes, in conjunction with a radiatively unstable atmosphere with excessive LW cooling in the upper troposphere over convectively active areas, such as the Intertropical Convergence Zone/South Pacific Convergence Zone (ITCZ/SPCZ) and warm pool. Using sensitivity experiments with the NCAR‐uncoupled/NCAR‐coupled CESM1, we infer that these biases partly result from the interactions between falling snow and radiation that are missing in most contemporary GCMs (e.g., YOTC‐GASS, Coupled Model Intercomparison Project 3 (CMIP)3, and Atmospheric Model Intercomparison Project 5 (AMIP5)/CMIP5). A number of biases in the YOTC‐GASS model simulations are consistent with model biases in CMIP3, AMIP5/CMIP5, and NCAR‐uncoupled/NCAR‐coupled model simulation without snow‐radiation interactions. These include excessive upper level convection and low level downward motion with outflow from ITCZ/SPCZ. This generates weaker low‐level trade winds and excessive precipitation in the Central Pacific Trade wind regions. The excessive LW radiative cooling in NCAR‐coupled/NCAR‐uncoupled GCM simulations is reduced by 10–20% with snow‐radiative effects considered.

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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.

A global forecast system model at a horizontal resolution of T1534 (∼12.5 km) has been evaluated for the monsoon seasons of 2016 and 2017 over the Indian region. It is for the first time that such a high-resolution global model is being run operationally for monsoon weather forecast. A detailed validation of the model therefore is essential. The validation of mean monsoon rainfall for the season and individual months indicates a tendency for wet bias over the land region in all the forecast lead time. The probability distribution of forecast rainfall shows an overestimation (underestimation) of rainfall for the lighter (heavy) categories. However, the probability distribution functions of moderate rainfall categories are found to be reasonable. The model shows fidelity in capturing the extremely heavy rainfall categories with shorter lead times. The model reasonably predicts the large-scale parameters associated with the Indian summer monsoon, particularly, the vertical profile of the moisture. The diurnal rainfall variability forecasts in all lead times show certain biases over different land and oceanic regions and, particularly, over the northwest Indian region. Although the model has a reasonable fidelity in capturing the spatiotemporal variability of the monsoon rain, further development is needed to enhance the skill of forecast of a higher rain rate with a longer lead time.

The impact of revised simplified Arakawa‐Schubert (RSAS) convective parameterization scheme in Climate Forecast System (CFS) version 2 (CFSv2) on the simulation of active and break phases of Indian summer monsoon (ISM) has been investigated. The results revealed that RSAS showed better fidelity in simulating monsoon features from diurnal to daily scales during active and break periods as compared to SAS simulation. Prominent improvement can be noted in simulating diurnal phase of precipitation in RSAS over central India (CI) and equatorial Indian Ocean (EIO) region during active periods. The spatial distribution of precipitation largely improved in RSAS simulation during active and break episodes. CFSv2 with SAS simulation has noticeable dry bias over CI and wet bias over EIO region which appeared to be largely reduced in RSAS simulation during both phases of the intraseasonal oscillation (ISO). During active periods, RSAS simulates more realistic probability distribution function (PDF) in good agreement with the observation. The relative improvement has been identified in outgoing longwave radiation, monsoon circulations, and vertical velocities in RSAS over SAS simulation. The improvement of rainfall distribution appears to be contributed by proper simulation of convective rainfall in RSAS. CFSv2 with RSAS simulation is able to simulate observed diurnal cycle of rainfall over CI. It correctly reproduces the time of maximum rainfall over CI. It is found that the improved feedback between moisture and convective processes in RSAS may be attributed to its improved simulation. Besides improvement, RSAS could not reproduce proper tropospheric temperature, cloud hydrometeors over ISM domain which shows the scope for future development.