The weather effects of aerosol types were investigated using well-posed aerosol climatology through the aerosol sensitivity test of thermodynamic and hydrometeor fields, and the weather forecast performances in July of 2017. The largest aerosol direct radiative forcing (ADRF) in July was due to dust aerosols at the surface and atmosphere, and sulfate at the top of the atmosphere (TOA), respectively. The ADRF of total aerosols had unilateral tendencies in thermodynamic and hydrometeor fields. The contribution of individual aerosols was linearly additive to those of total aerosols in the heat fluxes, heating rates, humidity, and convective precipitation. However, no such linearity existed in temperature, geopotential height, cloud liquid or ice contents, and large-scale precipitation. Dust was the most influential forcing agent in July among five aerosol types due to the largest light-absorption capacity. Such unilateral tendencies of total aerosols and a part of the linearity of individual aerosols were exerted on the weather systems. The verification of medium-range forecasts showed that aerosols alleviated the overestimation of surface shortwave (SW) downward fluxes, the negative biases of temperature and geopotential heights at TOA and surface, and the underestimation in light and moderate precipitation. In contrast, they enhanced warm biases at the mid-atmosphere and underestimation in heavy precipitations, particularly negative biases in the intertropical convergence zone (ITCZ). Weather forecast scores including current aerosol information were improved in geopotential height (GPH) of the northern hemisphere (NH); however, they got worse in the temperature and the upper atmosphere GPH of the southern hemisphere (SH), which was mostly due to black carbon (BC) aerosols in the tropical regions. The missing mechanisms such as aerosol-cloud interactions, better aerosol spectral optical properties including mixing states and aging, and the near-real-time (NRT) based aerosol loading data are worthwhile to be tried in the near future for fixing the intrinsic underestimation of precipitation in ITCZ and surface radiative fluxes in the desert and biomass burning area.

The regional climate model RegCM 4.4 at 50km resolution is used to conduct a sensitivity study over South Asia Coordinated Regional climate Downscaling Experiment domain during the period 1998-2002, in order to investigate the best cumulus convective precipitation scheme, planetary boundary layer (PBL) and land-surface scheme. The inferences obtained from 11 sensitivity experiments include the better performance of community land model version 4.5 (CLM 4.5) over biosphere-atmosphere transfer scheme, Tiedtke as cumulus convective precipitation scheme and University of Washington (UW) as PBL scheme. The simulation with these parameterization schemes well captures the monsoon precipitation pattern over India similar to 7mm/day and North Eastern Region of India (NER) similar to 12mm/day, which are comparable to observations with a significant correlation of R-2>0.93. The observed temperatures are also well simulated by the model. Therefore, RegCM 4.4 with these parameterization schemes is further used to simulate the aerosol fields (aerosol optical depth, AOD and black carbon, BC) and aerosol direct radiative forcing (DRF) for the period 2011-2014 over the same domain with special emphasis on NER. The model captures the seasonality in AOD and BC over the Indian Subcontinent and NER. BC hotspots in the Indo-Gangetic Plain and China are well captured by the model. The observed to simulated BC ratio over Dibrugarh (located in NER) is found to be improved. The model underestimation is significant in the dry season when burning over the region is predominant, which has not been considered by the emission inventories properly. Simulated DRF is found to exhibit seasonality qualitatively as well as a North-South latitudinal gradient.