Kuvar Satya Sing

Bio: Kuvar Satya Sing is an academic researcher from Indian Institute of Technology Kharagpur. The author has contributed to research in topics: Weather Research and Forecasting Model & Cyclone. The author has an hindex of 1, co-authored 1 publications receiving 9 citations.

Sensitivity of mesoscale simulation of Aila Cyclone to the parameterization of physical processes using WRF model

Abstract: Land falling tropical cyclones (TCs) that form over the Bay of Bengal (BoB) cause enormous damage to the life and property along the east coast of India, Bangladesh and Myanmar. The focal point in reducing TC disaster is to provide more accurate prediction of the track, intensity and landfall of the storm. A number of studies (Anthes, 1982; Davis et al., 2001) suggested that the numerical prediction of tropical cyclone depends on representation of various physical processes in the model. Mandal et al. (2004) studied the sensitivity of cumulus convection, planetary boundary layer (PBL) and radiation parameterization towards mesoscale simulation of BoB cyclones using fifth generation mesoscale model (MM5). Their study indicates that the model simulation is sensitive to the choice of cumulus convection, PBL and radiation parameterization schemes.

Assessment of the Weather Research and Forecasting (WRF) model for simulation of extreme rainfall events in the upper Ganga Basin

Abstract: Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods Most of the global rainfall products are available at a coarse resolution, rendering them less desirable for extreme rainfall analysis Therefore, regional mesoscale models such as the advanced research version of the Weather Research and Forecasting (WRF) model are often used to provide rainfall estimates at fine grid spacing Modelling heavy rainfall events is an enduring challenge, as such events depend on multi-scale interactions, and the model configurations such as grid spacing, physical parameterization and initialization With this background, the WRF model is implemented in this study to investigate the impact of different processes on extreme rainfall simulation, by considering a representative event that occurred during 15–18 June 2013 over the Ganga Basin in India, which is located at the foothills of the Himalayas This event is simulated with ensembles involving four different microphysics (MP), two cumulus (CU) parameterizations, two planetary boundary layers (PBLs) and two land surface physics options, as well as different resolutions (grid spacing) within the WRF model The simulated rainfall is evaluated against the observations from 18 rain gauges and the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) 3B42RT version 7 data From the analysis, it should be noted that the choice of MP scheme influences the spatial pattern of rainfall, while the choice of PBL and CU parameterizations influences the magnitude of rainfall in the model simulations Further, the WRF run with Goddard MP, Mellor–Yamada–Janjic PBL and Betts–Miller–Janjic CU scheme is found to perform best in simulating this heavy rain event The selected configuration is evaluated for several heavy to extremely heavy rainfall events that occurred across different months of the monsoon season in the region The model performance improved through incorporation of detailed land surface processes involving prognostic soil moisture evolution in Noah scheme compared to the simple Slab model To analyse the effect of model grid spacing, two sets of downscaling ratios – (i) 1 : 3, global to regional (G2R) scale and (ii) 1 : 9, global to convection-permitting scale (G2C) – are employed Results indicate that a higher downscaling ratio (G2C) causes higher variability and consequently large errors in the simulations Therefore, G2R is adopted as a suitable choice for simulating heavy rainfall event in the present case study Further, the WRF-simulated rainfall is found to exhibit less bias when compared with the NCEP FiNaL (FNL) reanalysis data

Impact of Initial and Boundary Conditions on Mesoscale Simulation of Bay of Bengal Cyclones Using WRF-ARW Model

Abstract: Land falling tropical cyclones (TCs) that form over the BOB cause disaster along the east coast of India, Bangladesh and Myanmar. The destruction is mainly due to the strong wind, heavy rainfall and associated storm surges. It causes huge damage to property. So, it is very important to predict the TCs as accurately as possible to reduce the loss of life and damage to the property. The track and intensity predictions of the tropical cyclone remain a challenging task for atmospheric scientists and operational forecasters. Several studies suggested that incomplete representation of physical processes, insufficient model spatial resolution (Demaria and Kaplan 1999; Zhang et al. 2011) and inaccurate IBCs are possible reasons for poor forecast of the tropical cyclones (Cacciamani et al. 2000).