Simulation of Severe Thunderstorm Event on 29 th April 2019 in Pokhara Using Advance Research Weather Research and Forecasting Model (WRF-ARW)
Date
2021
Authors
Prajapati, Krishna Ram
Journal Title
Journal ISSN
Volume Title
Publisher
Department of Hydrology and Meteorology
Abstract
During the pre-monsoon (March, April and May) in Nepal, severe thunderstorms and
hailstorms cause significant property and agricultural damage, in addition to loss of life
from lightening. In the present study, Severe thunderstorm event occurred at Pokhara, 800
asl, in Central Nepal on 29
th
April, 2019, during early afternoon is performed. The event
was lasted half hour and produced the golf ball-sized hailstones that destroyed vehicles
windshields, damaged the crops worth millions of rupees and more. The Advanced
Research-Weather Research and Forecasting (WRF-ARW) model was used to simulate
the features associated with a severe thunderstorm and examined its sensitivity to six
different micro-physical (MP) schemes (Thompson, Morrison, Goddard, Lin, WSM6 and
Ferrier). The three nested domains with the innermost domain of 1km horizontal
resolution and integrated for 36hr with the spin-up time of 24 hr. Numerical study of
thunderstorms have been discussed with its antecedent thermodynamic stability indices
that include K Index, Total totals index (TTI), Convective Available Potential Energy
(CAPE), Convective Inhibition Energy (CINE), and Precipitable Water (PW) used for the
short range prediction of thunderstorms. For validating simulated features of the
thunderstorm, Automatic Weather Station data of Lumle station and observed data of
Pokhara synoptic station were used with statistic error analysis using Root Mean Square
Error (RMSE), Mean Absolute Error (MAE) and Correlation Coefficient (CC). All the
microphysics scheme well predicts the instability indices required for the thunderstorm
occurrence. Overall Morrison and Thompson scheme performed well with same
correlation coefficient of 0.80, whereas WSM6 has least results with mean correlation
coefficient of 0.46 compared to the observed.
Keywords: WRF-ARW, Microphysics, Thunderstorm, Instability Indices.
Description
Keywords
WRF-ARW, Microphysics, Thunderstorm, Instability Indices