Improved Indian Summer Monsoon rainfall simulation: the significance of reassessing the autoconversion parameterization in coupled climate model

• Published in: Climate dynamics 2024-06, Vol.62 (6), p.5543-5565
• Main Authors: Bhowmik, Moumita, Hazra, Anupam, Srivastava, Ankur, Mudiar, Dipjyoti, Chaudhari, Hemantkumar S., Rao, Suryachandra A., Wang, Lian-Ping
• Format: Article
• Language: English
• Subjects: Climate; Climate models; Climate system; Climatology; Cloud droplet growth; Cloud droplets; Clouds; Convective clouds; Dispersion; Drop size; Drop size distribution; Earth and Environmental Science; Earth Sciences; Geophysics/Geodesy; Global climate; Global climate models; Liquid water content; Long wave radiation; Moisture content; Monsoon rainfall; Monsoons; Oceanography; Original Article; Outgoing long-wave radiation; Parameter sensitivity; Parameterization; Precipitation; Probability distribution; Rain; Rain water; Rainfall; Rainfall intensity; Rainfall simulators; Scale models; Simulation; Size distribution; Small-scale models; Specific humidity; Summer; Summer monsoon; Water content
• ISSN: 0930-7575; 1432-0894
• DOI: 10.1007/s00382-024-07243-w

An unresolved problem of the current Global Climate Models (GCM) is the unrealistic distribution of rainfall over the Indian Summer Monsoon (ISM) region, which is also related to the persistent dry bias over the Indian landmass. Therefore, quantitative prediction of the intensity of rainfall events has remained a challenge for state-of-the-art GCMs. Based on observations, it is hypothesized that the insufficient growth of cloud droplets and the processes responsible for the cloud-to-rainwater conversion are the key components in distinguishing between shallow and convective clouds. The Eulerian–Lagrangian particle-by-particle-based small-scale model provides a path for reassessing the ‘autoconversion’ parameterization schemes and suggests the relative dispersion-based ‘autoconversion’ parameterization scheme for the climate model. The realistic information on cloud drop size distribution is incorporated into the microphysical parameterization scheme of the climate model. Two sensitivity simulations are conducted using the climate forecast system (CFSv2) model. The coupled climate model incorporates a relative dispersion-based Liu–Daum-type autoconversion parameterization scheme in place of the traditional Sundqvist-type autoconversion, which, based on small-scale model analysis, makes the model more accurate in simulating the probability distribution (PDF) of rainfall with accompanying specific humidity, liquid water content, and outgoing long-wave radiation (OLR). The improved simulation of rainfall PDF appears to have been aided by a significantly improved simulation of OLR, which led to a more accurate simulation of the ISM rainfall.