Aerosol indirect effects on precipitation were investigated in this study using a Global/Regional Integrated Model system (GRIMs) linked with a chemistry package devised for reducing the heavy computational burden occurring in common atmosphere–chemistry coupling models. The chemistry package was based on the Goddard Chemistry Aerosol Radiation and Transport scheme of Weather Research and Forecasting with Chemistry (WRF-Chem), and five tracers that are relatively important for cloud condensation nuclei (CCN) formation were treated as prognostic variables. For coupling with the cloud physics processes in the GRIMs, the CCN number concentrations derived from the simplified chemistry package were utilized in the cumulus parameterization scheme (CPS) and the microphysics scheme (MPS). The simulated CCN number concentrations were higher than those used in original cloud physics schemes and, overall, the amount of incoming shortwave radiation reaching the ground was indirectly reduced by an increase in clouds owing to a high CCN. The amount of heavier precipitation increased over the tropics owing to the inclusion of enhanced riming effects under deep precipitating convection. The trend regarding the changes in non-convective precipitation was mixed depending on the atmospheric conditions. The increase in small-size cloud water owing to a suppressed autoconversion led to a reduction in precipitation. More precipitation can occur when ice particles fall under high CCN conditions owing to the accretion of cloud water by snow and graupel, along with their melting.

To investigate the impact of advanced microphysics schemes using single and double moment (WSM6/WDM6) schemes, numerical simulations are conducted using Weather Research and Forecasting (WRF) model for a severe mesoscale convective system (MCS) formed over the Korean Peninsula. Spatial rainfall distribution and pattern correlation linked with the convective system are improved in the WDM6 simulation. During the developing stage of the system, the distribution of total hydrometeors is larger in WDM6 compared to WSM6. Along with the mixing ratio of hydrometeors (cloud, rain, graupel, snow, and ice), the number concentration of cloud and rainwater are also predictable in WDM6. To understand the differences in the vertical representation of cloud hydrometeors between the schemes, rain number concentration (Nr) from WSM6 is also computed using particle density to compare with the Nr readily available in WDM6. Varied vertical distribution and large differences in rain number concentration and rain particle mass is evident between the schemes. Inclusion of the number concentration of rain and cloud, CCN, along with the mixing ratio of different hydrometers has improved the storm morphology in WDM6. Furthermore, the latent heating (LH) profiles of six major phase transformation processes (condensation, evaporation, freezing, melting, deposition, and sublimation) are also computed from microphysical production terms to deeply study the storm vertical structure. The main differences in condensation and evaporation terms are evident between the simulations due to the varied treatment of warm rain processes and the inclusion of CCN activation in WDM6. To investigate cloud–aerosol interactions, numerical simulation is conducted by increasing the CCN (aerosol) concentration in WDM6, which simulated comparatively improved pattern correlation for rainfall simulation along with intense hydrometer distribution. It can be inferred that the change in aerosol increased the LH of evaporation and freezing and affected the warming and cooling processes, cloud vertical distribution, and subsequent rainfall. Relatively, the WDM6 simulated latent heating profile distribution is more consistent with the ERA5 computed moisture source and sink terms due to the improved formulation of warm rain processes.

To investigate the structure of latent heating rate during different stages of mesoscale convective system (MCS) over the Korean Peninsula, a four nested domain Weather Research and Forecasting (WRF) model simulation with two‐way nesting method has performed. Advanced physics options from the Korean Integrated model physics are considered for simulation. Latent heating rate associated with condensation, evaporation, deposition, sublimation, freezing and melting process is computed based on different microphysical process using WRF double moment (WDM6) microphysics scheme. During the development/mature stage of the convective system, the warming associated with latent heat release by condensation is dominant below 400 hPa, and deposition above 500 hPa. The maximum contribution of warming processes from condensation, cloud nucleation, graupel accretion, and ice, snow deposition is evident. Cooling processes from rain, cloud evaporation followed by graupel, and snow melting are also noticed. Major updrafts associated with ascent of air parcel and large hydrometeor distribution is apparent along with downdrafts in the lower levels. In the dissipating stage, the cooling due to latent heat absorption by evaporation below 600 hPa and melting around 600 hPa are dominant. Contribution from cooling processes is dominant with major downdraft motion in the lower levels corresponding to the hydrometeor fall velocity. Dominant positive (negative) total latent heating provided (restrained) the energy for convection during developing and dissipating stages of system. Varied distribution of total cloud hydrometeors in different stages is apparent. Consistency between cloud hydrometeors, net heating rates, major upward (downward) motion and corresponding rainfall in developing (dissipating) stages of MCS is noticed. Model simulated latent heating (WDM6) profiles are consistent with computed moisture source and sink terms (ERA5).

In this study, more accurate information on the levels of aerosol optical depth (AOD) was calculated from the assimilation of the modeled AOD based on the optimal interpolation method. Additionally, more realistic levels of surface particulate matters over the Arctic were estimated using the assimilated AOD based on the linear relationship between the particulate matters and AODs. In comparison to the MODIS observation, the assimilated AOD was much improved compared with the modeled AOD (e.g., increase in correlation coefficients from −0.15–0.26 to 0.17–0.76 over the Arctic). The newly inferred monthly averages of PM₁₀ and PM_2.5 for April–September 2008 were 2.18–3.70 μg m⁻³ and 0.85–1.68 μg m⁻³ over the Arctic, respectively. These corresponded to an increase of 140–180%, compared with the modeled PMs. In comparison to in-situ observation, the inferred PMs showed better performances than those from the simulations, particularly at Hyytiala station. Therefore, combining the model simulation and data assimilation provided more accurate concentrations of AOD, PM₁₀, and PM_2.5 than those only calculated from the model simulations.