Characteristics of monsoonal precipitating cloud systems over the Indian subcontinent derived from weather radar data

The convective area within a mesoscale convective system (MCS) contains intense convective cells or storms which themselves could be made of a single cumulonimbus cloud or several of them joined together. Interconnection between MCS evolution and storms has not been reported previously. We address this gap area by using the Doppler Weather Radar (DWR) data collected at four stations in India during the summer monsoon season of 2013. The four DWR locations selected have different climates ranging from coastal to semi-arid. Storm is defined as a set of contiguous radar pixels in three-dimensional space with a reflectivity threshold of 30 dBZ and the threshold criterion is satisfied in a volume of at least 50km(3). Monsoonal MCSs contain a few to more than 20 storms depending on geographic location and MCS life stage. The average area of storms ranges from 13 to 170km(2) while storm heights mostly lie between 6 and 10km. The growth stage of an MCS is characterized by a rapid increase in the number of storms, while their number and average area decrease in the dissipation stage. Storms occupy 30-70% of the convective area within an MCS and contribute 90-97% of the convective precipitation at any given instant. Thus, a few to several cumulonimbus clouds grouped together in a contiguous manner matter most for convective precipitation, making storm scale an important scale in the hierarchy of scales in tropical deep convective cloud systems. This has implications for cumulus parametrization as well as planning satellite payloads for observing precipitation

Long-term cloud fraction biases in CMIP5 GCMs over India during monsoon season

Using 24years of cloud fraction (CF) data from the International Satellite Cloud Climatology Project (ISCCP) observations and their corresponding simulators in general circulation models (GCMs) from the Coupled Model Intercomparison Project phase 5 (CMIP5), we have analyzed cloud biases and their role on radiation over the Indian region (65-100 degrees E and 5-40 degrees N) for the monsoon season of June to September. The present study reports the spatial patterns of CFs and their biases in GCMs compared to observations. It is found that the simulated CFs are highly underestimated up to 40%. Mean of total CF from ISCCP observations is 75% with at least 10% difference with simulated CFs. For high-topped clouds, this difference is about 3-4%. Except for high-topped clouds, other cloud types are not simulated realistically by CMIP5 models used in this study. Further, we investigated the individual cloud types classified based on cloud optical depth and cloud top pressure. We found that, in general, individual cloud types are poorly simulated by models, although some (Max Planck Institute Earth System Model, Low Resolution and Hadley Centre Global Environmental Model, version 2, Earth System) models convincingly simulate high-topped thin clouds. To assess the impact of cloud biases on the simulated radiative forcings, we studied shortwave and longwave cloud radiative forcings from CERES (Clouds and the Earth's Radiant Energy System) observations and CMIP5 GCMs. It is noticed that the spatial patterns of biases in radiative forcings are similar to the patterns of biases in CFs for high-topped clouds, specifically over the oceanic regions. We find that the biases in cloud radiative forcings could potentially be caused due to the inefficacy of CMIP5 models in simulating high-topped anvil clouds (high-topped cirrus/stratocirrus clouds). The present study confirms that the uncertainty in simulating cloud fractions over the Indian region is still a prominent issue to be addressed in general circulation models

Abstracts of National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020

This book presents the abstracts of the papers presented to the Online National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020 (RDMPMC-2020) held on 26th and 27th August 2020 organized by the Department of Metallurgical and Materials Science in Association with the Department of Production and Industrial Engineering, National Institute of Technology Jamshedpur, Jharkhand, India. Conference Title: National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020Conference Acronym: RDMPMC-2020Conference Date: 26–27 August 2020Conference Location: Online (Virtual Mode)Conference Organizer: Department of Metallurgical and Materials Engineering, National Institute of Technology JamshedpurCo-organizer: Department of Production and Industrial Engineering, National Institute of Technology Jamshedpur, Jharkhand, IndiaConference Sponsor: TEQIP-