Abstract
Changes in precipitation pattern have been associated with global warming and is of more importance particularly for monsoon dependent regions such as India, which receives maximum rainfall from south-west monsoon. Indian land mass is surrounded by ocean from three sides named Arabian Sea (AS), Bay of Bengal (BOB) and rest of the Indian Ocean (IO) which makes its climate more sensitive. To understand the effect of global warming, long term (1960–2017) annually averaged in-situ sea surface temperature (SST) is studied which shows an increasing trend (~ 0.11 °C/decade; P < 0.05) with higher variations (r2AS = 0.46; r2BOB = 0.43) over AS and BOB whereas comparatively lower in magnitude (~ 0.14 °C/decade; P < 0.05) with less variation (r2IO = 0.74) over IO. Rise in SST could vary evaporation rate, moisture content, cloud temperature and initial conditions required for cloud formation. To understand this heterogeneity in conjunction with seasonal variation, present study correlates cloud microphysical properties such as cloud effective radius (CER) with SST and aerosol optical depth (AOD) at high-resolution (1° × 1°) using linear interpolation method during 2001–2016. Features of north-east monsoon captures with high (~ 0.006–0.012 kg/kg) specific humidity at 850 hPa, positive correlation (~ 0.1–0.8) of SST-CER and negative correlation (~ − 0.1 to ~ − 0.8) of AOD–CER over BOB which may imply formation of bigger droplets due to presence of more moisture and less AOD. Though these patches show prominent results, it also shows scattered interpolation signifying role of other parameters on CER. Findings would be promising with more parameters, which can be used as an input data in climate models to understand regional climate variability.
Published Version
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