Inter-annual variability of aerosols and its relationship with regional climate over Indian subcontinent

The spatio-temporal variability of aerosols over Indian subcontinent is mainly due to transported dust from adjacent deserts (Thar and Middle East deserts), local emission due to anthropogenic activities and prevailing meteorological conditions. On large scale, the quantification of transported and locally emitted aerosol from these regions is complicated. Here, we used empirical orthogonal function (EOF) analysis to identify these regions and their variability by using 33 years of Total Ozone Monitoring Spectrometer (TOMS) satellite data. The maximum variability in aerosol is explained by first two EOF modes (70.31 and 20.57) over Indian subcontinent. The major aerosol, i.e. transported dust from adjacent deserts confined to NW India and Pakistan, is observed in first leading mode, whereas biomass burning, industrial and dense populated region of southeast and eastern region of the Indo-Gangetic Plain (IGP) are revealed in the second dominant mode. The EOF analysis is carried out specifically for the pre-monsoon and monsoon seasons over Indian subcontinent as maximum aerosol loading is observed during this period. The region of NW India, IGP, Pakistan and northern Arabian Sea explains maximum variability in both seasons. The first three leading modes and their relationship with different atmospheric and surface variables are carried out for pre-monsoon and monsoon seasons. This study explains the potential role of aerosols on reduction in cloudiness, increased shortwave at the ground, land-surface tropospheric warming and its feedback to other related processes. This study strongly suggests that there is a need for further appropriate observational as well as modelling study on the role of semi-direct aerosol effect over Indian subcontinent

Assessment of the aerosol distribution over Indian subcontinent in CMIP5 models

This paper examines the aerosol distribution over Indian subcontinent as represented in 21 models from Coupled Model Inter-comparison Project Phase 5 (CMIP5) simulations, wherein model simulated aerosol optical depth (AOD) is compared with Moderate Resolution Imaging Spectro-radiometer (MODIS) satellite observations. The objective of the study is to provide an assessment of the capability of various global models, participating in CMIP5 project, in capturing the realistic spatial and temporal distribution of aerosol species over the Indian subcontinent. Results from our analysis show that majority of the CMIP5 models (excepting HADGEM2-ES, HADGEM2-CC) seriously underestimates the spatio-temporal variability of aerosol species over the Indian subcontinent, in particular over Indo-Gangetic Plains (IGP). Since IGP region is dominated by anthropogenic activities, high population density, and wind driven transport of dust and other aerosol species, MODIS observations reveal high AOD values over this region. Though the representation of black carbon (BC) loading in many models is fairly good, the dust loading is observed to be significantly low in majority of the models. The presence of pronounced dust activity over northern India and dust being one of the major constituent of aerosol species, the biases in dust loading has a great impact on the AOD of that region. We found that considerable biases in simulating the 850hPa wind field (which plays important role in transport of dust from adjacent deserts) would be the possible reason for poor representation of dust AOD and in turn total AOD over Indian region in CMIP5 models. In addition, aerosol radiative forcing (ARF) underestimated/overestimated in most of the models. However, spatial distribution of ARF in multi-model ensemble mean is comparable reasonably well with observations with bias in magnitudes. This analysis emphasizes the fundamental need to improve the representation of aerosol species in current state of the art climate models. As reported in Intergovernmental Panel on Climate Change (IPCC) fourth assessment report (AR4), the level of scientific understanding (LOSU) of climatic impact of aerosols is medium-low. For better understanding of short and long term implications of changing concentrations of aerosol species on climate, it is imperative to have a realistic representation of aerosol distribution over regions with high aerosol loading